Scholarship in the management arena has highlighted the important role of employee creativity in organizations (Katz, 19...
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Scholarship in the management arena has highlighted the important role of employee creativity in organizations (Katz, 1964, Oldham and Cummings, 1996; Staw, 1984; Woodman et al., 1993). Although this literature is relatively young (Amabile, 1996), a general consensus has developed defining creativity with an outcome focus as the production of novel and useful ideas or products (e.g. Amabile, 1983, 1996; Oldham and Cummings, 1996; Woodman et al., 1993). The current paper will argue that in order to understand creativity in the workplace an increased focus on the consequences and cognitive processes underlying creative behavior is necessary. To build this case, research concerning the definition of creativity, the consequences of creative behavior in organizations, and risk perceptions in organizations will each be considered. A conceptual model will be proposed, several propositions will be offered to guide future research, and the implications of the model will be considered.
Employee creativity and the role of risk Todd Dewett
The author Todd Dewett is Assistant Professor of Management, Department of Management, Raj Soin College of Business, Wright State University, Dayton, Ohio, USA.
Keywords
Employee creativity: efforts and outcomes
Employees, Innovation, Risk analysis
Abstract Creative efforts and creative outcomes are identified as distinct in employee creative performance. It is argued that an employee’s willingness to take risks is an important antecedent of creative efforts. Behavioral consequences experienced by employees following creative efforts are discussed in relation to future creative efforts considered and the subsequent willingness to take risks. A model and propositions are developed to guide future research and are considered in light of the current creativity literature.
Electronic access The Emerald Research Register for this journal is available at www.emeraldinsight.com/researchregister The current issue and full text archive of this journal is available at www.emeraldinsight.com/1460-1060.htm
European Journal of Innovation Management Volume 7 · Number 4 · 2004 · pp. 257-266 q Emerald Group Publishing Limited · ISSN 1460-1060 DOI 10.1108/14601060410565010
Creativity has been defined in numerous ways. Several researchers have offered “process”oriented definitions of creativity, focusing on the stages of individual creative production (e.g. Amabile, 1996; Parnes, 1967; Sternberg and Lubart, 1991), although most scholars have noted that the typical approach in the literature assumes an “outcome”-oriented definition (Amabile, 1983; Mumford and Gustafson, 1988). Thus, creativity is most often defined as the production of novel and useful ideas (e.g. Amabile, 1988; Oldham and Cummings, 1996; Woodman et al., 1993). At its core, this outcome-oriented definition stipulates two criteria: novelty and utility. Novelty simply implies newness or originality. Utility implies that an idea or other contribution must be directly relevant to the goals of the organization and it must be something from which the firm can reasonably expect to extract some value (Cummings and Oldham, 1997). While the literature has matured from early studies of creative persons (e.g. Mackinnon, 1962) to the more recent focus on the social psychology of creativity (e.g. Amabile, 1983), one thing has largely remained constant: our focus on the same dependent variable, creative outcomes. Thus, Drazin et al. (1999) suggest that the explicit or implicit question posed by these works is “How do you increase creative outputs in organizations?” An interesting oversight in this dialogue has been the failure to realize that creative outcomes are not easily obtained – creativity often requires
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considerable time (Amabile and Gryskiewicz, 1987; Burnside et al., 1988; Gruber and Davis, 1988; Sethia, 1989). Stated differently, creativity in the organizational sense – ideas or actions deemed by relevant others to be sufficiently novel and useful – is not a frequently occurring phenomenon relative to the maintenance of the status quo. Thus, as this literature has developed, a pattern has emerged which presents a challenge to our ultimate understanding of employee creativity: the typical definition of creativity clearly implies two different phenomena. “The production of . . .” refers to a process of creative behavior which an employee undertakes in an effort to arrive at a creative outcome. This process may result in novel ideas or actions, but may not often result in outcomes deemed useful. In turn, “. . . novel and useful ideas” represents the characteristics that an outcome must possess in order to be considered creative. In short, employees often do things that may be viewed as creative. Thus, scholars’ reliance on the typical definition of creativity has resulted in an inadequate examination of the fundamental role of creative efforts, rendering the most typical result of the creative process neglected. Following the work of Amabile (1983, 1996), Oldham and Cummings (1996), Woodman et al. (1993), Zhou (1998), and others, creative outcomes can be defined as novel and useful ideas, processes, or products offered by an employee, as judged by relevant others (e.g. one’s supervisor). In turn, creative efforts can be defined as novel or original ideas, processes, or products offered by an employee, as judged by relevant others. It is through a process of engagement with creative efforts that, occasionally, creative outcomes result. It should be noted that the definition of creative efforts does not include any mention of utility or practicality. The need to recognize the importance of creative efforts is predicated on the primacy of novelty as a requirement for creativity (Brown, 1989). It has been suggested that novelty represents the necessary first step towards the production of a creative product (Jackson and Messick, 1967). These two general facets of employee creativity, efforts and outcomes, are shown in Figure 1. Two characteristics of creative efforts make them particularly important in the context of employee creativity. First, they are thought to be considerably more common relative to creative outcomes. The typical result of an employee’s engagement in the creative process produces efforts that are in need of further development or may in fact be wholly unworkable. The second important characteristic of creative efforts will be addressed in the next section.
It must be noted that, at least conceptually, a few scholars have made a similar distinction between creative efforts and creative outcomes (e.g. Amabile, 1983, 1996; Schoenfeldt and Jansen, 1997). For example, Schoenfeldt and Jansen (1997) include ideas that are generated, yet never implemented, in their definition of creativity. They assert that when researchers consider only those ideas that are implemented, thus those that are both novel and useful, they are sampling on the dependent variable and are overly restrictive of what constitutes creative ideas. Similarly, Osborn’s (1957) early work on brainstorming sessions was based on four rules: do not criticize; quantity is wanted; combine and improve suggestions; and say all that comes to mind no matter how wild. Importantly, what these examples make clear is that for outcomes to be generated that interested parties will eventually label creative requires the generation of many novel ideas, some of which will be creative and some of which will not. This sentiment has reoccurred frequently (e.g. Albrecht and Hall, 1991; Newell et al., 1962; Politz, 1975). These ideas reflect the reality that individuals participate in the creative process in an interactive fashion by developing ideas and presenting them to relevant others; and then by learning from reactions, reworking ideas, and representing them. For example, Drazin et al. (1999) define creativity as the process of engagement in creative acts, regardless of the nature of the outcomes. By doing so they focus on how individuals attempt to orient themselves to, and take creative action in, situations or events that are complex, ambiguous, and ill defined; that is, they engage in sensemaking (e.g. Weick, 1995). Stated differently, creative engagement is a process in which an individual behaviorally, cognitively, and emotionally attempts to produce creative outcomes (Kahn, 1990).
Creative efforts and the willingness to take risks The second important characteristic of creative efforts alluded to above concerns the issue of perceived risk. Simply stated, to engage in creative efforts is not a risk free proposition. Risk can be defined as the extent to which there is uncertainty about whether potentially significant and/or disappointing outcomes of decisions will be realized (Sitkin and Pablo, 1992). In the present discussion, this view is extended into a context beyond decision making to include the evaluation of any task-related actions one might take at work. Consequently, new ideas can pose a risk to an employee because they represent disturbances in routines, relationships, power balances, and job
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Figure 1 A general model of employee creativity
security. New ideas represent a change from the status quo (Pfeffer and Sutton, 2000) and invite evaluation, which can be dangerous given that it is often difficult for people to separate ideas from their source (Albrecht and Hall, 1991). Research outside of the organizational arena clearly notes the central role of risk in creativity. For example, Simonton’s research examining the eminence of creators from scientific as well as artistic disciplines points out that each product produced by an illustrious creator does not contribute credit to their name (Simonton, 1997). Indeed, a work that provides a creator with great acclaim may very well be followed by something quite embarrassing (Simonton, 2000). He notes that Beethoven created many compositions that his admirers did not like and that, in the realm of science, even Edison invented many useless contraptions. In science in general, it has been suggested that the search for new discoveries carries with it the inherent possibility of failure, a prospect which may threaten the innovators’ economic and or social status (Silver, 1983). Similarly, one might expect that employees in organizations could experience such a risk when they consider the manner in which to pursue their work – a notion endorsed by Deming (1986). Recent findings support this contention. As one example, Pfeffer and Sutton (2000) explored the “knowing-doing gap” in organizations and suggested that a lack of employee action, even when requisite knowledge was readily at hand, could be the result of obstacles such as fear of potential negative outcomes. In fact, their research suggests that fear is a pervasive reality in the modern workplace and that a distinct minority of employees feel that creative ideas can fail without negative repercussions for the person or work group responsible. Indeed, only half of the workers in their study felt that it was acceptable to challenge the status quo or to take informed risks in their work (Pfeffer and Sutton, 2000). This clearly presents a challenge to Katz’s (1964)
suggestion that one key employee behavior required for organizational success is for employees to be willing to engage in innovative and spontaneous activity beyond role prescriptions. Importantly, several scholars have noted, yet not fully developed, the link between perceived risk and creativity in organizations (e.g. Fidler and Johnson, 1984; Jalan and Kleiner, 1995; Shalley, 1995; Tesluk et al., 1997; Zhou and George, 2001). For example, Sethia (1989) notes that creative activity is a largely uncertain endeavor in which the action-outcome link is often unclear and drawn out over time. In essence, although scholars agree that creativity implies personal risk, very few have formally treated the issue of risk as central to the creative process at work. It is important to note that when employees produce creative efforts they assume risk, while, technically, creative outcomes do not imply risk. Creative efforts, as noted above, imply risk because they are ideas or behaviors that are not within the normal range of work and thus depart from the status quo. Conversely, creative outcomes, which by definition are deemed novel and useful by relevant others, do not entail risk. However, in reality, an employee engaged in a creative effort does not have a priori knowledge of the outcome of his or her work. They are likely cognizant of the possibility that, ultimately, their work may or may not be judged to be creative. Thus, if we are to understand how an employee might consistently engage in a process that will only occasionally, maybe even rarely, result in creative outcomes, we must develop a theoretical understanding of the mechanism that drives their behavior. Implied in Simonton’s (1997, 2000) work on eminent creators was the creators’ willingness to plunge forward into new works while having no knowledge of how the resulting product would be evaluated. They were willing to accept that risk. While examining employees in organizations is clearly different than studying eminent creators, a parallel nonetheless exists. Consequently,
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willingness to take risks (WTR) is an important antecedent of creative efforts, as shown in Figure 1. WTR is defined as a willingness to take calculated risks within the scope of one’s job in an effort to produce positive job-related outcomes such that one is open to potential failure as a result. This definition attempts to capture an employee’s willingness to “go out on a limb” with an idea that they perceive as worthwhile in an effort to accomplish their work and reach their goals. Importantly, WTR is not so broadly defined as to include a WTR directed towards nonproductive behaviors such as lying, habitual tardiness, or embezzlement – only the employee’s willingness to take risks that are intended to be positive with regard to their core job tasks. WTR is somewhat related to the construct of psychological safety. Kahn (1990) defines psychological safety as the employee’s sense of being able to show and employ one’s self without fear of negative consequences to self-image, status, or career. Edmondson (1999) defines the construct similarly in a group context. Both treatments position the construct as a belief that risk is low or nonexistent as the result of a particular context. In contrast, the WTR construct is specifically defined in the context of creative behaviors to recognize that risk is present and salient and that employees vary in their willingness to engage that risk. Importantly, WTR is not meant to suggest the need for a blind WTR or for an excessive level of positive affect, rather, a willingness to take reasonable risks in the face of potential negative outcomes. WTR as a distinct construct is a largely new consideration in the creativity literature, although several organizational and creativity researchers have suggested or implied the need for such a construct. For example, in their often cited work, Abbey and Dickson (1983) note that successful R&D units are characterized by a willingness to take risks. In a decision-making context, Dutton (1993) and Krueger and Dickson (1994) have illustrated how the sense of threat evoked in organizations by discussing problems limits employee’s willingness to engage in problemsolving activities. This suggests that in some situations employees will perceive the career and interpersonal threat of certain discussions or actions as sufficiently low, leading them to ask for help, admit errors, and discuss problems (Edmondson, 1999). In other situations employees feel that they cannot ask for help or freely admit errors. Further, it should be noted that, in general, people tend to avoid risks while preferring actions that afford the same or higher expected value – what the decision-making literature refers to as risk aversion (Larrik, 1993). This is important to the discussion of how to foster
creativity given that some people are more motivated to avoid failure than to achieve success (McClelland, 1961). In short, for people to engage in any change-related behavior they must be willing to take risks and see a path forward that will not be catastrophic (Schein, 1993). The WTR construct has relevance to creativity at work given that managers and organizations can develop environments that should impact the willingness to engage certain risks. For example, several researchers have described what might constitute a climate for creativity or a context supportive of creativity (see Amabile, 1983; Amabile et al., 1996; Scott and Bruce, 1994; Woodman et al., 1993 for more), but most seem to agree that you know when a climate for creativity exists because employees are willing to take risks (Tesluk et al., 1997). However, Ford (1996) suggests that even under conditions which are favorable to employee creativity, creative behavior will be forsaken by employees in organizations when habitual actions remain more attractive. This leads Pfeffer and Sutton (2000) to suggest that managers must drive fear out of the organization, treat failure to act as the only true failure, and never punish people for trying new things. In fact, recent research examining electronic brainstorming suggests the importance of WTR. For a variety of reasons, group brainstorming has not provided the benefits its creators envisioned (Stein, 1975). One reason is the perceived risk that group members face when offering potential solutions that might be viewed negatively, damaging their standing in the group. Electronic brainstorming has begun to address this issue by offering anonymity to participants. Early studies clearly show that groups using computer assisted idea generation techniques outperform equivalent nominal groups in idea generation tasks (Valacich et al., 1994). Clearly, one potential explanation for these results is that the anonymity afforded by the software reduces the risk of participation. Thus, based on the above reasoning, comments from scholars concerning the risk involved in creativity (e.g. Fidler and Johnson, 1984; Jalan and Kleiner, 1995; Shalley, 1995; Tesluk et al., 1997), and the evidence suggesting that such perceived risks affect creativity- related behaviors (e.g. Pfeffer and Sutton, 2000; Valacich et al., 1994), I propose: P1. WTR is positively related to creative efforts.
Exploring the cycle of creative engagement As depicted in Figure 1, the cycle of employee creative behavior involves a series of relationships.
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It will be argued that employee creative efforts are preceded by a WTR, creative efforts produce behavioral consequences, and these consequences influence both the subsequent WTR as well as the type of creative effort considered. Above, the effort/outcome link and the effort/consequences link were discussed. The consequences resulting from creative efforts were briefly mentioned, but are deserving of further elaboration given the contention that to be creative at work is not a risk free proposition. An employee might experience several types of personal consequences, either affirming or nonaffirming, following creative efforts. For example, affirming consequences might include supportive comments, formal evaluation acknowledging the value of the creative effort, or praise. However, given that creative efforts lack utility and occur more frequently than creative outcomes, the potential non-affirming consequences may be more important. These might include being negatively evaluated, being ridiculed or reprimanded, or even being taken seriously only to see one’s idea fail. Thus, as one considers the potential consequences that an employee might face, it becomes necessary to consider the relationship between these consequences and the employee’s subsequent WTR. This is vital because an employee cannot have a priori knowledge of the outcomes of their behavior, suggesting that one of the clearest indicators the employee may consider is how they have been treated following past incidents of creative effort. Did anyone listen to them? Were they taken seriously? Was their effort applauded as valuable? Were they encouraged to maintain these types of efforts? Stated simply, aside from the ambiguity associated with any potential creative effort being considered, an employee’s WTR will be influenced by the consequences they have experienced following past creative efforts. For example, research indicates that reward and recognition for creative acts supports continued creative behavior (e.g. Amabile, 1988; Livingstone et al., 1997; Mumford and Gustafson, 1988). Following Figure 1, this type of management response should subsequently bolster the employee’s willingness to take risks. Thus, if an employee perceives, on balance, that their creative efforts have been valued and affirmed they should be more willing to risk future creative efforts. Conversely, if they perceive that their creative efforts have not been valued and affirmed, they will be less willing to risk future creative efforts. Thus I propose: P2. The behavioral consequences that an employee has experienced as a result of creative efforts will be related to WTR such that affirming consequences will be
associated with stronger WTR and nonaffirming consequences will be associated with lower WTR. Beyond the relationship between behavioral consequences and WTR, these consequences should also influence the type of subsequent creative effort the employee considers. At this point, the discussion of the cycle of creative engagement becomes more complex because of the need to recognize the multidimensional nature of creativity. It has already been noted that creative outcomes are comprised of both novelty and a utility in the most general sense. However, this description does not address different forms of creativity. Unsworth’s (2001) typology of creativity provides a much needed elaboration of the creativity construct by describing four qualitatively different types of creative outcomes that have often been subsumed and unexamined in the discussion of what constitutes creative performance. The four types she describes are based on the juxtaposition of two primary reasons that one might engage in creative action: the behavioral trigger (is the person internally or externally driven) and the type of problem to be addressed (open versus closed). Below, each of these creative outcomes will be briefly considered in terms of the potential perceived risks each presents for the employee, how the type of creative effort considered may be influenced by prior behavioral consequences, and how the types of creativity might relate to the employee’s WTR. Figure 2 presents a slightly modified version of Unsworth’s (2001) typology. Responsive creativity refers to situations in which employees are responding to an environmental demand to solve a particular problem that has a known or accepted path that can be used to solve the problem. An example might be a directive from a superior to a employee to consider ways that the speed of a particular process can be increased using variations of solutions that have worked in the past. Expected creativity is also externally driven but occurs in response to a self-discovered open-ended problem. The example in this case would require the employee to discover or create a solution for the process improvement task. Contributory creativity is said to be self-determined and based on a clearly formulated problem. The key difference in the case of contributory creativity is the lack of external direction. Thus, in this example the employee initiates the action for a process improvement and applies some variation of a known solution in an effort to accomplish their goal. Finally, proactive creativity occurs when the individual is internally motivated and is actively searching for open-ended problems to solve. Here again, the employee is initiating the effort to
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Figure 2 Modified version of Unsworth’s (2001) typology of creativity
improve the process, but in this case they do not have a known solution and must create a way to solve the problem. The one key difference between Figure 2 and the figure provided by Unsworth (2001) is that each quadrant now notes some level of perceived personal risk. Thus, while it is clear that employees faced with any given type of creativity, as argued above, will perceive some amount of personal risk, the task becomes understanding whether or not different types of creative outcomes, which require different types of creative efforts, will influence WTR in meaningfully different ways. When the four types of creative outcomes in Figure 2 are evaluated from this perspective, it can be argued that there are, in fact, systematic differences across the quadrants. Specifically, it is likely that open problems, as opposed to closed problems, and internal drivers, as opposed to external drivers, will generate greater levels of perceived personal risk as employees consider the effort that will be required. In the first case, open problems do not provide employees with known paths to solutions. Thus, by definition, they require one to consider untested ideas, untested means of solving the problem, and unknown probabilities associated with each effort to find a solution. Conversely, closed problems typically provide some known paths useful for generating solutions (e.g. Getzels and Csikszentmihalyi, 1967). In short, it is likely that when facing open-ended problems, employees are likely to
perceive a higher likelihood of negative personal outcomes - that is, higher perceived personal risk. Similarly, in the case of externally driven engagement with creativity there is a sanctioned reason to act – permission has been granted to behave creatively. Presumably, the employee is thus aware that some relevant other (e.g. a supervisor responsible for charging them with the task) expects and understands that the employee will provide a creative effort which may or may not immediately bear fruit. As opposed to an external trigger, when an employee acts based on an internal driver they are likely to be aware that they have not been specifically sanctioned to behave in such a manner and as such they have less ability to predict the reaction that a relevant other might have. The importance of intrinsic motivation (e.g. Amabile, 1996) aside, this suggests that perceived personal risk may be higher in the case of an internal trigger. While the risk an employee will perceive in a given situation will vary by individual, the above logic was used to suggest that, in general, perceived risk will be modest in the open/external and closed/internal situations quadrants, low in the closed/external quadrant, and high in the open/ internal quadrant. Beyond suggesting that open problems versus closed problems and internal drivers versus external drivers might lead to different amounts of perceived personal risk, it is important to note that this typology can be seen to offer a paradox. Responsive creativity is the most studied form of
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creativity – and typically applies to explicitly creative roles such as R&D positions (Unsworth, 2001). While obviously important, these types of roles in organizations are in the minority and many authors have called for a broader examination of creativity that applies to all employees. Thus a truly creative and innovative organization would desire a high amount of proactive creativity – they very type of creativity in Figure 2 (based on the discussion of open/closed problems and internal/ external drivers) which is likely to lead an employee to perceive the highest amount of personal risk. Stated differently, the type of creativity that managers desire for positive changes and improvements inside organizations may be the least likely to occur. Accordingly, it is when this form of creativity is considered by an employee that the implications for WTR are most salient. Following Figure 1, and given the different forms of creativity, it becomes necessary to consider how affirming and non-affirming behavioral consequences might influence the subsequent type of creativity considered by an employee. This discussion is of course bound by the issue of employee control – that is, if the effort is externally triggered via a job mandate handed down by a supervisor, the employee has no choice as to whether or not to engage the task as charged. Thus, the challenge is to describe the relationship between behavioral consequences and the consideration of internally driven creative efforts, labeled contributory and proactive creativity in Figure 2. This highlights the issue of volition. If internally driven creativity can said to be voluntary, under what conditions will the employee actively consider this form of creative effort? Given substantial research linking encouraging and supportive management to employee creativity (e.g. Abbey and Dickson, 1983; Amabile, 1988; Delbecq and Mills, 1985; Farr and Ford, 1990; Kanter, 1983; Tesluk et al., 1997; West and Farr, 1989) it would appear that affirming behavioral consequences are likely to produce this result. As an extreme negative example, if an employee’s well-intentioned creative effort results in a reprimand from his or her supervisor, one would not expect that employee to be as likely to consider voluntary creative efforts in the future. Thus I propose: P3. Affirming behavioral consequences are positively related to the consideration of internally-driven (voluntary) creative efforts.
considered in turn. Responsive creativity (closed problem, externally driven) poses the lowest theoretical risk to an employee. The employee has been told to engage a particular task and the path to solution is well defined. Given that their actions are sanctioned and the degree of creativity required of them is relatively low, this situation should be associated with a higher WTR in the service of this task. Expected and contributory creativity, resulting from open-ended problems with external drivers and closed problems with internal drivers respectively, carry a modest risk. In turn, it is expected that these situations would be generally associated with a moderate level of WTR. Finally, proactive creativity, resulting from open-ended problems and internal drivers, is the most ambiguous form of creativity to consider in terms of the potential consequences and should generally be associated with a lower level of WTR. Summarizing the above comments, I propose: P4. The type of creative effort considered by an employee will be related to WTR such that creative efforts associated with higher amounts of perceived risk will be associated with lower levels of WTR.
Continuing with Figure 1, the type of creativity considered should influence WTR. Building on the general levels of perceived risk likely associated with each form of creativity noted in Figure 2, responsive creativity, expected and contributory creativity, and proactive creativity will each be
Finally, antecedents are included in Figure 1 in order to provide a link to the current literature on creativity and an opportunity to begin exploring the link between common antecedents and WTR. At one level of abstraction, the literature on the antecedents of creativity, particularly in the organizational arena, comprises various contextual factors at work as well as various individual differences. While the discussion here will be far from exhaustive, it is instructive to consider a few cases which highlight the role of WTR as depicted in the conceptual model. For example, autonomy is the degree to which a task provides substantial freedom, independence, and discretion to employees in determining the specific procedures to be used in carrying out their work (Hackman and Oldham, 1980). Several researchers have stated that in order for employees to be creative, they require freedom so they can experiment with ideas and enlarge the range of possibilities and potential solutions to a problem (e.g. Abbey and Dickson, 1983; Amabile, 1988, 1996; Deci and Ryan, 1987; Mumford and Gustafson, 1988; Scott and Bruce, 1994; Shalley, 1991; Shalley et al., 2000). Autonomy has often been considered as a direct influence on creativity, although there is reason to believe that the effect is actually indirect, via an increased WTR. For example, Kahn’s (1990) research indicates that when employees view themselves as having autonomy, their WTR will increase. This naturally follows from Amabile and Gryskiewicz’s (1987) suggestion that increased autonomy allows
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individuals freedom from rigid work rules and the ability to pursue novel considerations. Similarly, consider the case of self-efficacy as an individual difference often linked to creativity. Self-efficacy influences choice behavior, i.e. the situations and activities that individuals choose for themselves, as well as the extent to which individuals will exert the effort required to overcome obstacles and persist through aversive circumstances (Bandura, 1986). A significant amount of research has developed the relationship between self-efficacy and creativity (Barron and Harrington, 1981; Farr and Ford, 1990; Getzels and Csikszentmihalyi, 1976; Gist, 1989; Redmond et al., 1993; Tierney and Farmer, 2002). Interestingly, it may be partially through an increased WTR that self-efficacy influences creativity. For example, drawing on the work of Bandura and Wood (1989), Krueger and Dickson (1994) note that managers with high self-efficacy tend to see setbacks as learning experiences and thus they persevere. Conversely, for managers with low self-efficacy, setbacks are cause to become preoccupied with the risk of failure. This aligns well with research indicating that threat perceptions in organizations lead to a lower WTR (Dutton, 1993).
creativity will benefit from attempting to develop and measure the relationships among the variables presented in the Figure 1 and described in the propositions noted earlier. While the theoretical support for these constructs appears to be adequate, they have yet to be empirically developed or verified. For example, building on Unsworth’s (2001) typology, research will benefit by attempting to specify the type of creativity that is being studied. Earlier it was suggested that different types of creativity should carry with them different amounts of personal perceived risk. However, this is clearly a contention in need of empirical support. For example, by devising a measure of creativity which encompasses each of the four quadrants of Unsworth’s (2001) typology, field research could begin to uncover the relative frequency of occurrence of the different types of creativity in the workplace and the perception of risk that employees attach to each form of creativity. It is also important to note that creativity is a process – creative outcomes do not randomly appear, but are the result of a protracted process of creative engagement (Drazin et al., 1999). The typical approach to measurement in the literature to date has been cross-sectional. However, several authors have noted the longitudinal nature of creativity (Amabile and Gryskiewicz, 1987; Burnside et al., 1988; Gruber and Davis, 1988; Sethia, 1989) which suggests that it will be worthwhile to measure creativity over time. As the conceptual model presented here suggests, a longitudinal approach may in fact be explicitly required to test the temporal nature of the relationships involved in the process. Employee creativity is indeed vital for the ongoing health of organizations. While scholars have noted that creative employee behaviors imply risk, the issue has not yet assumed a central role in the discussion nor has it been empirically assessed. If we desire to understand why employees will engage in creative efforts we must address the risks they are sure to perceive. To that end, it is hoped that the ideas presented here can contribute to our evolving understanding of creativity in organizations.
Implications and conclusions While supporting the current direction in the creativity literature, this paper also supports Woodman et al.’s (1993) suggestion that creativity is a complex construct and the notion that we still have much to discover about creativity in organizations (Amabile, 1996). An argument has been provided suggesting the need to separate the treatment of creative efforts from creative outcomes. The more frequent occurrence of, and the risk associated with creative efforts suggests that they are qualitatively different than the creative outcomes that are sometimes realized. Consequently, the issue of perceived risk must be central to the discussion of employee creative efforts. While this topic has received some attention in the study of work roles explicitly requiring creativity, it has received scant attention in the examination of employee creativity among employees in general. Specifically, it was suggested that one’s WTR should be a central predictor of employee creative efforts and that the behavioral consequences an employee experiences as a result of a creative effort will have implications for the subsequent type of creative efforts they consider as well as the level of WTR they will subsequently possess. Moving forward, several areas of investigation are imperative. First, future empirical studies of
References Abbey, A. and Dickson, J.W. (1983), “R&D work climate and innovation in semiconductors”, Academy of Management Journal, Vol. 26 No. 2, pp. 362-8. Albrecht, T.L. and Hall, B.J. (1991), “Facilitating talk about new ideas: the role of personal relationships in organizational innovation”, Communication Monographs, Vol. 58, pp. 273-88. Amabile, T.M. (1983), The Social Psychology of Creativity, Springer-Verlag, New York, NY.
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Amabile, T.M. (1988), “A model of creativity and innovation in organizations”, in Staw, B. and Cummings, L.L. (Eds), Research in Organizational Behavior, Vol. 10, JAI Press, Greenwich, CT, pp. 123-37. Amabile, T.M. (1996), Creativity in Context, Westview Press, Boulder, CO. Amabile, T.M. and Gryskiewicz, S.S. (1987), Creativity in the R&D Laboratory, Technical Report No. 30, Center for Creative Leadership, Greensboro, NC. Amabile, T.M., Conti, R., Coon, H., Lazenby, J. and Herron, M. (1996), “Assessing the work environment for creativity”, Academy of Management Journal, Vol. 39 No. 5, pp. 1154-84. Bandura, A. (1986), Social Foundations of Thought and Action: A Social-cognitive View, Prentice-Hall, Englewood Cliffs, NJ. Bandura, A. and Wood, R. (1989), “The effect of perceived controllability and performance standards on self-regulation of complex decision making”, Journal of Personality and Social Psychology, Vol. 56 No. 5, pp. 805-14. Barron, F. and Harrington, D.M. (1981), “Creativity, intelligence, personality”, Annual Review of Psychology, Vol. 32, pp. 439-76. Brown, R.T. (1989), “Creativity: what are we to measure?”, in Glover, J.A., Ronning, R.R. and Reynolds, C.R. (Eds), Handbook of Creativity, Plenum Press, New York, NY. Burnside, R.M., Amabile, T.M. and Gryskiewicz, S.S. (1988), “Assessing organizational climates for creativity and innovation – methodological review of large company audits”, in Ijiri, Y. and Kuhn, R.L. (Eds), New Directions in Creative and Innovative Management: Bridging Theory and Practice, Ballinger, Cambridge, MA, pp. 169-85. Cummings, A. and Oldham, G.R. (1997), “Enhancing creativity: managing work contexts for the high potential employee”, California Management Review, Vol. 40 No. 1, pp. 22-38. Deci, E.L. and Ryan, R.M. (1987), “The support of autonomy and the control of behavior”, Journal of Personality and Social Psychology, Vol. 53 No. 6, pp. 1024-37. Delbecq, A.L. and Mills, P.K. (1985), “Managerial practices that enhance innovation”, Organizational Dynamics, Vol. 14 No. 1, pp. 24-34. Deming, W.E. (1986), Out of the Crisis, MIT Press, Cambridge, MA. Drazin, R., Glynn, M.A. and Kazanjian, R.K. (1999), “Multilevel theorizing about creativity in organizations: a sensemaking perspective”, Academy of Management Review, Vol. 24 No. 2, pp. 286-307. Dutton, J.E. (1993), “The making of organizational opportunities: interpretive pathway to organizational change”, in Staw, B. and Cummings, L. (Eds), Research in Organizational Behavior, Vol. 15, JAI, Greenwich, CT, pp. 195-226. Edmondson, A. (1999), “Psychological safety and learning behavior in work teams”, Administrative Science Quarterly, Vol. 44 No. 2, pp. 350-83. Farr, J.L. and Ford, C.M. (1990), “Individual innovation”, in West, M.A. and Farr, J.L. (Eds), Innovation and Creativity at Work, John Wiley & Sons, New York, NY, pp. 63-80. Fidler, L.A. and Johnson, J.D. (1984), “Communication and innovation implementation”, Academy of Management Review, Vol. 9 No. 4, pp. 704-11. Ford, C.M. (1996), “A theory of individual creative action in multiple social domains”, Academy of Management Review, Vol. 21 No. 4, pp. 1112-42.
Getzels, J.W. and Csikszentmihalyi, M. (1967), “Scientific creativity”, Science Journal, Vol. 3 No. 9, pp. 80-4. Getzels, J.W. and Csikszentmihalyi, M. (1976), The Creative Vision: A Longitudinal Study of Problem Solving in Art, Wiley, New York, NY. Gist, M.E. (1989), “The influence of training method on self-efficacy and idea generation among managers”, Personnel Psychology, Vol. 42 No. 4, pp. 787-805. Gruber, H.E. and Davis, S.N. (1988), “Inching our way up Mount Olympus: the evolving-systems approach to creative thinking”, in Sternberg, R.J. (Ed.), The Nature of Creativity: Contemporary Psychological Perspectives, Cambridge University Press, Cambridge, pp. 243-70. Hackman, J.R. and Oldham, G.R. (1980), Work Redesign, Addison-Wesley, Reading, MA. Jackson, P.W. and Messick, S. (1967), “The person, the product, and the response: conceptual problems in the assessment of creativity”, in Kagan, J. (Ed.), Creativity and Learning, Houghton Mifflin, Boston, MA, pp. 1-19. Jalan, A. and Kleiner, B.H. (1995), “New developments in developing creativity”, Journal of Managerial Psychology, Vol. 10 No. 8, pp. 20-3. Kahn, W.A. (1990), “Psychological conditions of personal engagement and disengagement at work”, Academy of Management Journal, Vol. 33 No. 4, pp. 692-724. Kanter, R. (1983), The Change Masters, Simon & Schuster, New York, NY. Katz, D. (1964), “The motivational basis of organizational behavior”, Behavioral Science, Vol. 9, pp. 131-3. Krueger, N. and Dickson, P.R. (1994), “How believing in ourselves increases risk taking: perceived self-efficacy and opportunity recognition”, Decision Sciences, Vol. 25 No. 3, pp. 385-400. Larrik, R.P. (1993), “Motivational factors in decision theories: the role of self-protection”, Psychological Bulletin, Vol. 113 No. 3, pp. 440-50. Livingstone, L.P., Nelson, D.L. and Barr, S.H. (1997), “Person-environment fit and creativity: an examination of supply-value and demand-ability versions of fit”, Journal of Management, Vol. 23 No. 2, pp. 119-46. McClelland, D. (1961), The Achieving Society, Nostrand, Princeton, NJ. Mackinnon, D. (1962), “The personality correlates of creativity: a study of American architects”, Proceedings of the 14th Congress on Applied Psychology, Vol. 2, pp. 11-39. Mumford, M.D. and Gustafson, S.B. (1988), “Creativity syndrome: integration, application, and innovation”, Psychological Bulletin, Vol. 103 No. 1, pp. 27-43. Newell, A., Shaw, J. and Simon, H. (1962), “The processes of creative thinking”, in Gruber, H., Terrell, G. and Wertheimer, M. (Eds), Contemporary Approaches to Creative Thinking, Atherton Press, New York, NY. Oldham, G.R. and Cummings, A. (1996), “Employee creativity: personal and contextual factors at work”, Academy of Management Journal, Vol. 39 No. 3, pp. 607-34. Osborn, A.F. (1957), Applied Imagination, Scribner, New York, NY. Parnes, S. (1967), Creative Behavior Guidebook, Scribner, New York, NY. Pfeffer, J. and Sutton, R.I. (2000), The Knowing-Doing Gap, Harvard Business School Press, Cambridge, MA. Politz, A. (1975), “Creativeness and imagination”, Journal of Advertising, Vol. 4 No. 3, pp. 11-14. Redmond, M.R., Mumford, M.D. and Teach, R. (1993), “Putting creativity to work: effects of leader behavior on subordinate creativity”, Organizational Behavior and Human Decision Processes, Vol. 55 No. 1, pp. 120-51.
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Employee creativity and the role of risk
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Schein, E.H. (1993), “How can organizations learn faster? The challenge of entering the green room”, Sloan Management Review, Winter, pp. 85-92. Schoenfeldt, L.F. and Jansen, K.J. (1997), “Methodological requirements for studying creativity in organizations”, Journal of Creative Behavior, Vol. 31 No. 1, pp. 73-90. Scott, S.G. and Bruce, R.A. (1994), “Determinants of innovative behavior: a path model of individual innovation in the workplace”, Academy of Management Journal, Vol. 37 No. 3, pp. 580-607. Sethia, N.K. (1989), “The shaping of creativity in organizations”, Academy of Management Best Papers Proceedings, 49th Annual Meeting, August 13-16, Washington, DC, pp. 224-8. Shalley, C.E. (1991), “Effects of productivity goals, creativity goals, and personal discretion on individual creativity”, Journal of Applied Psychology, Vol. 76 No. 2, pp. 179-85. Shalley, C.E. (1995), “Effects of coaction, expected evaluation, and goal setting on creativity and productivity”, Academy of Management Journal, Vol. 38 No. 2, pp. 483-503. Shalley, C.R., Gilson, L.L. and Blum, T.C. (2000), “Matching creativity requirements and the work environment: effects on satisfaction and intentions to leave”, Academy of Management Journal, Vol. 43 No. 2, pp. 215-33. Silver, H.R. (1983), “Scientific achievement and the concept of risk”, The British Journal of Sociology, Vol. 34 No. 1, pp. 39-43. Simonton, D.K. (1997), “Creative productivity: a predictive and explanatory model of career trajectories and landmarks”, Psychological Review, Vol. 104 No. 1, pp. 66-89. Simonton, D.K. (2000), “Methodological and theoretical orientation and the long-term disciplinary impact of 54 eminent psychologists”, Review of General Psychology, Vol. 4 No. 1, pp. 13-24. Sitkin, S.B. and Pablo, A.L. (1992), “Reconceptualizing the determinants of risk behavior”, Academy of Management Review, Vol. 17 No. 1, pp. 9-38. Staw, B.M. (1984), “Organizational behavior”, in Rosenweig, M.R. and Porter, L.W. (Eds), Annual Review of Psychology, Vol. 35, Annual Reviews, Palo Alto, CA, pp. 627-66. Stein, M.I. (1975), Stimulating Creativity, Vol. 2, Academic Press, New York, NY.
Sternberg, R.J. and Lubart, T.I. (1991), “An investment theory of creativity and its development”, Human Development, Vol. 34, pp. 1-31. Tesluk, P.E., Farr, J.L. and Klein, S.R. (1997), “Influences of organizational culture and climate on individual creativity”, The Journal of Creative Behavior, Vol. 31 No. 1, pp. 27-41. Tierney, P. and Farmer, S.M. (2002), “Creative self-efficacy: its potential antecedents and relationship to creative performance”, Academy of Management Journal, Vol. 45 No. 6, pp. 1137-48. Unsworth, K. (2001), “Unpacking creativity”, Academy of Management Review, Vol. 26 No. 2, pp. 289-97. Valacich, J.S., Dennis, A.R. and Connolly, T. (1994), “Idea generation in computer-based groups: a new ending to an old story”, Organizational Behavior and Human Decision Processes, Vol. 57 No. 3, pp. 448-67. Weick, K.E. (1995), Sensemaking in Organizations, Sage, Thousand Oaks, CA. West, M.A. and Farr, J.L. (1989), “Innovation at work: psychological perspectives”, Social Behavior, Vol. 4, pp. 15-30. Woodman, R.W., Sawyer, J.E. and Griffin, R.W. (1993), “Toward a theory of organizational creativity”, Academy of Management Review, Vol. 18 No. 2, pp. 293-321. Zhou, J. (1998), “Feedback valence, feedback style, task autonomy, and achievement orientation: interactive effects on creative performance”, Journal of Applied Psychology, Vol. 83 No. 2, pp. 261-76. Zhou, J. and George, J.M. (2001), “When job dissatisfaction leads to creativity: encouraging the expression of voice”, Academy of Management Journal, Vol. 44 No. 4, pp. 682-96.
Further reading West, M.A. (1989), “Innovation among health care professionals”, Social Behavior, Vol. 4, pp. 173-84.
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1. Introduction
Intuition and pharmaceutical research: the case of AstraZeneca
Innovation is at the bottom line, and based on the firm’s ability to manage creativity. Although creativity is a most contested and polymorphous construct, here it is used to represent new ideas and thoughts that precede an innovation. Madjar et al. (2002, p. 757) write: We consider employee creativity to be the production of ideas, products, or procedures that are (1) novel or original and (2) potentially useful to the organization.
Mats Sundgren and Alexander Styhre
One central issue in research on creativity in organizations is the ability to clearly define ideas and thought that are considered creative or are proven to be creative. The dominant approach is to treat creativity in a functionalist and instrumental manner, that is, to conceive of creativity as something that occurs or happens during certain conditions that can be arranged or managed. This rationalist view has been the dominant perspective in contemporary management theory. Gephart (1996, pp. 95-6) writes:
The authors Mats Sundgren is Executive PhD Student and Alexander Styhre is Associate Professor, both at the Fenix Research Program, Chalmers University of Technology, Gothenburg, Sweden.
Keywords Pharmaceuticals industry, Drugs, Design and development, Intuition, Organizational innovation
Abstract The role of intuition receives little attention in the literature on organizational creativity. This paper describes a study of the role of intuition and its implications for organizational creativity within pharmaceutical research. The study applies French philosopher Bergson’s philosophy of intuition. The study is based on a series of interviews with employees in pre-clinical research (discovery) in a major pharmaceutical company; in this context, creativity is defined as an organization’s ability to bring forth a new candidate drug in the gastrointestinal and cardiovascular therapy areas. This paper concludes that intuition is a resource that facilitates new drug development. Pharmaceutical researchers perceive the roles of intuition and creativity as intertwined in ground-breaking innovations. However intuition is a controversial phenomenon in the organization because it opposes reductionistic and analytical forms of thinking, which are highly prized in new drug development. Bergson’s philosophy may form a fruitful foundation from which intuition and its relevance for organizational creativity can be exploited.
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Rationality has been the driving force of modern management. Rationality has begun to dissipate in postmodernism, to become a cacophony of local rationalities, but we need to decentre rationality, not abandon rationality. We need to place rationality alongside other human faculties – passion, love, hope, and intuition – in our effort to understand and shape the future of management and history.
Although rationality remains as one of the main ingredients in management practice and theory, it is important to be open to alternative perspectives. Management is not simply the application of several rational principles, such as those suggested by Frederick W. Taylor; it also draws on “passion, love, hope, and intuition”. For example, creative work is based on highly technical and specialized knowledge within a particular field, but it is simultaneously dependent on commitment, communication, and experimental thinking. Jeffcut (2000, p. 125) writes: [T]he creative process is sustained by inspiration and informed by talent, vitality and commitment (i.e., a need to create rather than to consume): this makes creative work volatile, dynamic and risktaking, shaped by important tacit skills (or expertise) that are frequently submerged (even mystified) within domains of endeavor. Hence, the crucial relationship between creativity and innovation (i.e., the process of development of original ideas toward their realization/ consumption) remains unruly and poorly understood.
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European Journal of Innovation Management Volume 7 · Number 4 · 2004 · pp. 267-279 q Emerald Group Publishing Limited · ISSN 1460-1060 DOI 10.1108/14601060410565029
Creative work is never solely an outcome from the instrumental application of a set of management principles but must always be open to what
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Intuition and pharmaceutical research: the case of AstraZeneca
European Journal of Innovation Management
Mats Sundgren and Alexander Styhre
Volume 7 · Number 4 · 2004 · 267-279
Gephart calls “other human faculties” such as passion or intuition. This paper presents a study of the role of intuition in new drug development in the pharmaceutical industry. New drug development is a highly specialized activity that involves expertise in biosciences, such as biology, synthesis chemistry, medicine, and pharmacology. So new drug development depends on formal knowledge and expertise in relevant scientific domains. New drug development is based on formal management procedures and on factors that remain somewhat tacit: creative solutions to practical problems, unexpected applications of taken-for-granted knowledge, novel forms of thinking, and so forth (Dorabje et al., 1998). These various minor innovations and procedures draw on what we refer to here as intuition – or to use a popular metaphor: “what is in between the dots constitutes the line”. While what Gephart calls rational knowledge is widely known (and not contested facts, the dots), intuition is not well known. Intuition has a shared regime of representations; essentially, it is still epistemologically contested or slippery. In other words, intuition is between the well-known facts and procedures in scientific discovery. Intuition facilitates the ability to apply scientific knowledge and to see consequences of various experiments before formal proof is acquired. So intuition is very important for creativity in new drug development. Studies of scientific work (e.g. Knorr Cetina, 1999; Pickering, 1995; Lynch, 1985; Latour and Woolgar, 1979) show that scientific work is never as linear, homogeneous, and one-dimensional as one may think. Instead, controversies, alternative explanations, empirical inconsistencies, and local interpretations always characterize production of “scientific” facts. In short, a certain degree of heterogeneity exists within scientific knowledge. Pickering (1995, p. 70) writes:
other human faculties. More specifically, we make use of the notion of intuition developed by the French philosopher Henri Bergson. For Bergson, intuition is a key human faculty, capable of “thinking movement” rather than “solids”. While concepts and well-known facts are always appearing as fixed points and positions, the faculty of intuition is the ability to think about change and movement between such points. So for Bergson, intuition is part of all sophisticated, creative thinking.
[S]cientific knowledge should be understood as sustained by, and as part of, interactive stabilizations situated in a multiple and heterogeneous space of machines, instruments, conceptual structures, disciplined practices, social actors and their relations, and so forth.
So scientific and laboratory work is never the black box it is treated like in common sense thinking. Instead, intuition – the ability to anticipate results and to see broader pictures on the basis of empirical observations – is a highly useful skill. Drawing on a series of interviews in a pre-clinical organization in a major pharmaceutical company, this paper suggests that intuition is very important for new drug development. The new drug development process requires standard operating procedures and routine work plus creative and inventive thinking. Formal rational systems are thus always entangled with intuitive thinking and
2. Creativity in organizations Many organizations strive for these capabilities: creativity and innovation, i.e. the generation of new ideas and the ability to translate the ideas into action (Mumford et al., 2002). However, from organizational and practical perspectives, gaps exist between theory and practice when attempting to understand creative-action organizations (Ford and Gioia, 2000). From a theoretical perspective, myths and romance with creativity somewhat influenced much of the previous research on creativity. The myths may oversimplify explanations for events and attribute great achievements merely to individuals. More recent research questioned the validity of the personalized approach to creativity, and instead stressed the importance of the productive interplay between individuals and the ecosystems of individuals, i.e. organizational design and reward systems (Ford, 1995a, Gioia, 1995). According to Ford (1995b), creativity is not an inherent quality of a person, process, product, or place. It is a domain-specific social construction that is legitimized by judges who serve as gatekeepers to a particular domain. Furthermore, most of the creativity research pays no attention to organizational or professional concerns (Ford, 1995b). So an important step in understanding creativity in an organizational context is to take a more holistic approach, i.e. to take a systems approach and apply the concept of organizational creativity (Ford, 2000; Woodman et al., 1993). This leads to focus on the potential source of creativity and on increasing understanding of creativity in organizations. Another aspect of traditional creativity research is that the different distinct foci of creativity, such as the creative person, place, process, and product (e.g. Amabile, 1996; Boden, 1996; Ekvall and Ryhammar, 1999; Eysenck, 1996), do not facilitate useful understanding of how creativity works in an organizational context. So organizational creativity can be seen as a concept that accounts for the organizational context, interactions, and history
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Intuition and pharmaceutical research: the case of AstraZeneca
European Journal of Innovation Management
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Volume 7 · Number 4 · 2004 · 267-279
between the individual and the collaborative nature of creativity and links different subsets of intermediaries of creativity (Andriopoulos, 2001; Drazin et al., 1999). Intuition is an important but rather neglected subset of organizational creativity. Previous research on creativity has acknowledged the role intuition may play in the individual creative process (Policastro, 1999). However, some researchers consider the scientific study of intuition impossible. The major reasons are that intuition is either considered an esoteric phenomenon, such as ESP, or just erratic nonsense (Policastro, 1995). Empirical studies that link intuition to creativity in an organizational context are scarce (Agor, 1989). Previous research on intuition in an organizational context mainly focuses on leadership and decision making (Bechara et al., 1997; Wilson and Schooler, 1991) or as an intersection of psychology and cognitive science. So intuition is an important factor when trying to understand the management of organizational creativity. Literature on innovation management research barely acknowledges the role of intuition in organizations. There is an ongoing debate on the dominant lack of realism about the cognitive nature of technological change; and here, the prevailing assumption is that problems are fixed and known in the beginning of innovation processes (Nightingale, 2003, 1998). From this perspective, Roberts (1998), Saviotti (1998), and Nelson (2003) acknowledged and stressed the important role of tacit knowledge in technical change and how scientific knowledge is used in innovation. Nightingale (1998) demonstrates the vital role of tacit knowledge in science-driven organizations and emphasizes that for new drug development, the elusive nature of innovation depends on learned, tacit conceptions that cannot be reduced to information processing and thus demonstrates that tacit knowledge is important for creativity and is not easily captured or codified (Leonard and Sensiper, 1998). In this sense, tacit knowledge can be seen as one of several overlapping subsets or characteristics of intuition. However, it is reasonable to believe that tacit knowledge and intuition resonate rather than cohere or correspond with each other.
abandoned until the end of the century. At the start of the new millennium, interest in Bergson’s philosophy was revived (see, e.g. Linstead, 2002 and Wood, 2002). To discuss Bergson’s view of intuition, one must recapitulate other areas of Bergson’s thinking. So the notion of intuition is placed within a broader ontological and epistemological framework that gives sense and meaning to the notion of intuition. For Bergson, the basic ontological principle is that world consists of processes. Processes and movements constitute the world that we can experience – not entities:
3. The concept of intuition
In reality, things are events of a special kind, temporary crystallization of images; it would be proper to say that, for Bergson, movement is the real and original stuff the world is made of, whereas the picture of the universe as consisting of distinct material objects is an artifact of intelligence. These ideas – the logical and metaphysical priority of events over objects – was to be subsequently taken up and developed in detail by A.N. Whitehead (1968), probably not without inspiration from Bergson (Kolakowski, 1985, p. 45).
This ontological principle is also an epistemological principle. But being in the world is not based on a series of succeeding points but is instead based on what Bergson calls dure´e (duration). Moore (1996, p. 55) explains: It is not that we start from discrete items of experience spread out in time but somehow threaded together like beads on a string of consciousness. Rather we start from the experience of temporal flow. Temporal structure is not a matter of putting together given discrete items. On the contrary, so-called discrete elements are only apparent when we have a need to pluck them from our continuing experience.
Linstead (2002, p. 101) further clarifies: Bergson argues that human experience of real life is not a succession of clearly demarcated conscious states, progressing along some imaginary line (from sorrow to happiness, for example) but rather a continuous flow in which these states interpenetrate and are often unclear, being capable of sustaining multiple perspectives.
Human beings do not experience time as a mechanical stepwise movement from the past to the present and into the future. Instead, they experience time as a continuous series of events based on simultaneity – past, present, and future are never entirely separated; instead, they are always related in experience. Massumi (2002, p. 200) writes:
This section examines Bergson’s notion of intuition. Bergson is one of the most important philosophers of the twentieth century. During his lifetime, he was very influential in politics, art, and philosophy. After his death, the fashionable Bergsonism fell from grace and was essentially
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The basic insight of Henri Bergson’s philosophy . . . is that past and future are not just strung-out punctual presents. They are continuous dimensions contemporaneous to every present – which is by nature a smudged becoming, not a point state . . . Past and future are in direct, topological proximity with each other, operatively joined in a continuity of mutual folding.
Intuition and pharmaceutical research: the case of AstraZeneca
European Journal of Innovation Management
Mats Sundgren and Alexander Styhre
Volume 7 · Number 4 · 2004 · 267-279
In summary, Bergson’s notion of dure´e refuses to treat human experience as a mechanical, spatialized experience that consists of clearly demarcated solids brought together. The dure´e of a human being is always recalling the past into the future to anticipate the future. While the notion of dure´e is primarily a construct that explores the psychology of humans, the idea of continuity and what Bergson calls spatialized thinking is very important for his theory of knowledge. Just as what Bergson calls mechanical clock time tends to break down the continuous experience of dure´e into isolated points and positions, concepts and representations perform the same operation for knowledge. Language, the primary medium for thinking and knowledge, is based on concepts that are generally thought of as denoting certain events, essences, or practices. For Bergson, concepts can only capture a subset of human knowledge because they represent “cinematographic thinking”, that is, snapshots of events and occurrences in a continuous intrinsically moving reality. Concepts are thus formed as attempts to glue a world in motion into certain positions and fixed points. Bergson (1992, p. 137) writes: To know a reality in the ordinary meaning of the word “to know” is to take ready-made concepts, apportion them, and combine them until one obtains a practical equivalent of the real.
He continues: Every language, whether elaborated or crude, leaves many more things to be understood than it is able to express. Essentially discontinuous, since it proceeds by juxtaposing words, speech can only indicate by a few guideposts placed here and there the chief stages in the moment of thought (Bergson, 1999, p. 125).
Concepts are thus ready-mades that are applied to cases; they represent “classified thinking” (Bachelard, 1964, p. 75) and are therefore incapable of seeing movement. In brief, concepts are “solids”: According to his [Bergson’s] account, concepts are formed on the model of spatial solids, and it is consequently impossible to think about time without importing into it some of the features of homogeneous space (Mullarkey, 1999, p. 19).
Thinking always uses concepts, and concepts can never entirely capture the movement and becoming of being; although they are still useful tools in understanding such as world. For Bergson, intuition enables for understanding of movement. While concepts consist of solids are based on cinematographic thinking, which make us unable to see what is outside of ourselves, intuition is the faculty of thinking between the solids. Grosz (2001, p. 175) writes: Intuition is our nonpragmatic, noneffective, nonexpedient relation to the world, the capacity we
have to live in the world of excess of our needs, and in excess of the self-presentation or immanence of materiality, to collapse ourselves, as things, back into the world.
Ansell Pearson (2002, p. 124) argues: According to Bergson, the abstract intellect, which has evolved as an organ of utility and calculability, proceeds by beginning with the immobile and simply reconstructs movements with juxtaposed immobilities. By contrast, intuition, as he conceives it, starts from movement and sees in immobility only a snapshot taken by our mind.
So intuition is what breaks free from language and sees what is outside of the concept, outside of the language that we use to denote the world. Here, language is not only everyday concept, but is also equally the regime of representation that dominates the world of natural sciences and the biosciences. While language is a prosthesis for thinking (just a tool), thinking that draws on intuition abandons such a prosthesis in favor of a more free form of thinking. Whitehead (1968, p. 49) says “language halts behind intuition.” n summary, Bergson develops an ontology and epistemology of movement and becoming; processes rather than solids and entities constitute the world. So the human experience does not consist of single instances stacked on one another but is based on the simultaneity of past, present, and future. In addition, Bergson’s theory of knowledge separates use of ready-made concepts that are used as tools for thinking and communication and calls that which is positioned between concepts (solids) intuition. While concepts help us see the world as a series of demarcated instances and events, intuition makes us think in terms of movement and becoming. Intuition is thinking that lies between the known and the represented. Intuition is thinking beyond language. In terms of creativity, and more specifically, creativity in terms of new drug development in the pharmaceutical industry, intuition is thinking that uses what is already known – solids of verified knowledge or facts provided by the research efforts and laboratory work – to anticipate what is not known and established, negotiated, and agreed on as facts. Intuition is thus thinking that goes beyond or passes what is already known to enable new solutions and findings. As the empirical material suggests, this form of thinking outside of the solids is highly valued in pharmaceutical research.
4. The pharmaceutical industry This paper presents a study of intuition in preclinical drug development and describes how intuition can increase knowledge about
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Intuition and pharmaceutical research: the case of AstraZeneca
European Journal of Innovation Management
Mats Sundgren and Alexander Styhre
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organizational creativity in a modern pharmaceutical industry. The focal company is one of the largest pharmaceutical companies in the world and a manufacturer of medications in many therapy areas. The company’s three largest therapy areas are cancer, cardiovascular, and gastrointestinal. The company’s research and development (R&D) centers in Europe and the USA employ more than 10,000 people, and its 2003 R&D budget was US$2.7 billion. Today, the company has more than 50,000 employees worldwide. Briefly, pharmaceutical industry research (which also applies the focal company) is divided into two major processes: discovery (pre-clinical) and development (clinical). Discovery is the most critical process in new drug development. Discovery’s primary objective is to generate ideas for disease relief (modification of disease-related problems and complaints) or in the best case, for a disease’s cure – by using a new chemical entity (NCE). Discovery begins by defining a disease area and a target to manipulate. This target should have potential for altering the disease or its symptoms in a preferred way. The target (e.g. a receptor or an enzyme) is tested against many chemical substances using in vitro systems or biological models (Lesko et al., 2000). The aim is to establish a chemical structure for a biological activity relationship, which in the successful project leads to a candidate drug (CD). The CD is then further tested for putative toxicity and if found safe, an application for approval of testing in humans is submitted (investigation of a new drug, IND) to drug regulatory authorities and ethical committees. Discovery is a complex process that involves a multitude of scientific disciplines and includes many factors that could influence a successful outcome. It normally takes three to five years to produce a CD (Pisano, 1997). After approval, the development organization takes over the CD to start initial studies in humans. Development’s objective is to transform and validate pre-clinical models for human concept tests. During development, the CD is further tested in clinical trials to clarify if the drug has the desired therapeutic effects (i.e. proof of concept). These trials are followed by larger clinical trials to meet medical, ethical, and regulatory standards and commercial demands (i.e. proof of principle). The development process often takes four to six years. The pharmaceutical industry is renowned for being knowledge-intensive, and new product development activities are long-term investments in terms of time and capital (Yeoh and Roth, 1999; Roberts, 1999; Heppard and Blasick, 2000). The pharmaceutical industry’s competitive advantage
is intertwined with the company’s ability to generate knowledge and expertise over a wide array of knowledge domains that can produce NCEs, patents, and finally new medicines that are capable of becoming marketable products (see, e.g. Roberts, 1999). The high-tech, science-based pharmaceutical industry differs from other industries with similar R&D intensity and use of new scientific concepts and technologies because pharma: . must operate in a highly regulated environment; . has long development cycles – up to 15 years; and . assumes a high degree of risk during research (Pisano, 1997). The pharmaceutical industry invests a significant amount of its sales into R&D (in the focal company more than 20 percent). Over the last decade, the cost for large clinical trials has increased dramatically (Zivin, 2000). The pharmaceutical industry has had a long tradition of scientific breakthroughs and innovations (Horrobin, 2002). However, the industry currently wrestles with many issues; some of the most serious are rapidly increasing costs of R&D coupled with only small increases in output during drug discovery (Schmid and Smith, 2002a). During the last decade, the industry has increased its focus on incremental innovation, on decreasing time to market, and on reducing bottlenecks to optimize the length of the product’s patent (Tranter, 2000). Many pharmaceutical companies have turned to rigorous project and portfolio management to make the research process more effective (Schmid and Smith, 2002b). Furthermore, extensive efforts have been made to implement technologies in pre-clinical research (discovery), such as computer-aided drug design, combinatorial chemistry linked to high throughput screening (HTS) to increase innovative output. To conclude, based on the current situation in the industry, there is pronounced concern about how to balance organizational creativity and economies of scale – to produce radical innovations (Horrobin, 2001). The present study was conducted at one of the Swedish R&D centers, which is also the largest in the company – plus a skill center for several technologies, such as like HTS and computedaided drug design.
5. Method This qualitative study (Strauss and Corbin, 1990, 1994; Silverman, 1993) is based on interviews
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(Kvale, 1996) with ten senior researchers and senior managers in AstraZeneca R&D. The discovery organization at R&D center was the focal point. Qualitative methodology facilitates investigation of complex issues through narratives. Rather than selecting a few variables on a pharmaceutical research project, we integrated several interrelated questions and issues that are important for the drug discovery process. The aim of the interviews was to encourage respondents to describe their drug research experiences in relation to intuition and organizational creativity. Here, organizational creativity is defined as the organization’s ability to bring forth a new candidate drug in the gastrointestinal and cardiovascular therapy areas. A narrative approach does not seek what Bruner (1986) calls a “logico-scientific mode of knowledge” whereby an explanation is achieved through the recognition of an event or utterance as belonging to certain category or as following a general law. In short, a narrative approach strives to present contextualized narratives to make sense of complex, ambiguous, fluid realties – and not nomological knowledge (Habermas, 1968). The respondents in this study cover the most important disciplines involved in drug discovery: medicinal chemistry, pharmacology, biochemistry, and computational chemistry. The respondents also represent important roles and managerial levels in the R&D organization, for example, disease area leader, senior scientific advisors, and project leaders. AstraZeneca R&D, Mo¨lndal was chosen for the study because it is one of the most successful pharmaceutical sites in the company. Several blockbuster drugs, the basis for the financial performance of the company as a whole, have been developed at the site, which makes the company a relevant object of study in terms of drug discovery and organizational creativity activities. The interviews were made at AstraZeneca R&D in 2003.
in the study were divided into three categories. The first defined and positioned phenomena in the context of pharmaceutical research. The second investigated how intuition plays a role in drug discovery research and its relation to organizational creativity. And the third dealt with different organizational factors, such as technoscience and leadership and their relationships to intuition. For example, how different sophisticated technologies and technoscience influence interaction with phenomena.
6. Intuition in new drug development: the case of AstraZeneca The study investigated different aspects of intuition and its relation to organizational creativity in pharmaceutical research. Pharmaceutical research in the discovery organization is based on sophisticated technoscientific laboratory work. The search for NCEs and their further development to finished products occur in distributed knowledge systems in which several different areas of expertise are integrated. NCEs are the outcomes of joint efforts by medicinal chemists, biologists, and pharmacologists. Questions and issues addressed
6.1 What is intuition in the context of pharmaceutical research? Because intuition has multiple connotations, it is important to specify its meaning in the context of pharmaceutical research. Policastro (1995) suggests two complimentary definitions of intuition: one based on a metaphorical perception of phenomena and the other on a tacit form of knowledge. One of the respondents expressed this latter form and emphasized that intuition in pharmaceutical research is a combination of broad knowledge and competence: Intuition comes from broad competence together with extensive experience in a special area. For me, intuition is the ability to predict things with pretty good precision on the basis of the competence platform somewhere in the background . . . yes, it’s like a limit between intuition and not yet proven knowledge is floating as a chemist. I mean, you can show a chemist a structure and say: “Do you think that this will be potent?” And then he has a much better opportunity to answer yes or no to the question than another chemist who has not worked in our project. He can’t point it out because that nitrogen is there or there. He can look at the structure and say: “No, I don’t think so.” It is probably doubtful. It is obvious he can point out certain things, like: “I think the chain is a little too long.” Or something like that (Pharmacology, person 1).
Another respondent defined intuition as a feeling and expressed a significant amount of vagueness and thus correlated intuition with risk taking: I think that intuition is a kind of feeling. It is like what vision is for planning. Intuition is a type of capacity that comes with experience. I actually think that intuition is very important in the whole research process – particularly in early discovery phases. Because intuition is correlated with risktaking, it’s difficult to base decisions on intuition for clinical programs, which is of course ethically correct. But in early phases in discovery, it’s simpler and easier to take intuitive decisions about different things, like in toxicity studies or choices of methods (Biochemistry, person 2).
One researcher stressed that intuition represents a dichotomy that is rational and sensible and irrational and impossible to communicate:
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Intuition is something that summarizes experience for better or worse, because sometimes it’s rational and other times it’s irrational. I believe that many experienced researchers have some kind of touch of recognition to identify new situations and put them in relation to something they have experienced before. I think that often, you see that intuition is something that you cannot put into a list. I believe in this method or in this molecule because . . . And you can list carefully researched facts about it and maybe refer to different parts, and there you have it very clearly why you recommend one. But many times it is a little weaker. Maybe you have made some calculations that are not very clear, but you have made others and maybe have seen earlier cases that remind you of it, but you cannot really put your finger on what it is. Like when it’s more vague but you anyway feel very strongly that this is the one you believe in (Computational chemistry, person 6).
An organic chemist described intuition as the ability to make combinations and explain how chemical structures can be visualized into a type of harmony: For me, intuition is almost emotional; it’s like that things look good. For example, if I have a synthesis that I am working with, I can get a feeling that “this should work” . . . it’s something that is very useful in what I do, because it has to do with combining earlier pieces of evidence – call it intuition. But it is imagination and an ability to make combinations. It’s like you feel intuitively that it’s right (Organic chemistry, person 4).
One respondent emphasized the strong relationship to knowledge and pointed out the ambiguitiy of intuition in the research process and how to handle it: Intuition is based partly on the experience of having being a part of and seen many examples and then being able to connect the experience with . . . But also being able to digest many different signals into a conclusion – that’s some kind of partial explanation of what intuition is, I think. The difficulty is that if you look at calculation methods, intuition is like neural networks; there is no explanation. You can train yourself in calculation models, calculating responses that you see are pretty good, but you do not have the vaguest idea of how the algorithms have come to that result. But that there are other robust calculation methods that are more rational, where you can understand the coefficient that appears. And man’s brain has an ability to weigh in all types of information and backgrounds and experiences into something that is a decision or an intuition or whatever you can call it. And it is good when it is rational. It is less good when it is irrational. I think we are colored by many irrational things (Computational chemistry, person 6).
and broad knowledge play an important role that may lead to important solutions for scientific problems. 6.2 Does intuition matter in drug discovery research? On the rather broad issue of whether intuition plays a role in drug discovery research, all respondents claimed in different ways that intuitition has a major, but complicated, influence. One respondent explained: Of course, it’s very important. But I firmly believe that intuition is a summarized picture you get from all the experience and the knowledge you have. So I don’t think that intuition is hocus pocus or something that you should be sceptical about. It’s a gut feeling. Very important. And I think that it’s based on things that are inside you and that you should absolutely trust it (Computational chemistry, person 7).
All respondents expressed in various ways that there is a relation between intuition and creativity. Many respondents claimed that intuition and creativity greatly overlap. In some cases, two respondents thought that intuition and creativity are basically the same concept. But they emphasized that intuition cannot be controlled and creativity can, for example, through imagination and domain knowledge: You cannot do something if you don’t know the tools: the carpenter must know his tools.
One researcher provides a concrete example of how intuition links to creativity: Intuition and creativity go together. It’s not so easy to separate them. You also must have intuition; it’s not always that it must be that way. For example, entrepreneurship need not always lead to getting there the quickest way. There can be other people who help make a decision. It’s exactly the same thing that you do in the lab. You might have a target molecule but a lot of different ways of getting to it. Not only using intuition but a combination of intuition and experience, in any case; one person maybe chooses a way that leads to being able to make the substance more quickly than the others, for example. That you really can produce it (Organic chemistry, person 4).
Another respondent gave this example, which points out that intuition can also be an obstacle to creativity:
In conclusion, all respondents expressed to varying degrees that intuition in the context of pharmaceutical research is an intinsic ability to produce various associations for which experience
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Yes, the connection is probably complicated. I’d say that creativity can be damaged by too much intuition and especially this unconscious intuition. Then I’m worried about getting stuck in a rut. That in some way, it may be wrong to say that it quantitatively obstructs creativity, but it stops it, I think there is a risk that it stops creativity qualitatively in a narrower niche. If you dare to challenge and question your own intuitive solution to problems, then you maybe broaden your perspective and come to – I would not say more or
Intuition and pharmaceutical research: the case of AstraZeneca
European Journal of Innovation Management
Mats Sundgren and Alexander Styhre
Volume 7 · Number 4 · 2004 · 267-279
less creative, I mean not fewer or more creative solutions – but you may reach other qualities, and they in turn are difficult to evaluate, which is better or which is worse? (Computational chemistry, person 6).
worry, like: “Damn, I can’t put this thing aside.” You can’t fall asleep at night, and you don’t really understand why you have that worried feeling. It must be some kind of intuition that you have. But at the same time it’s actually – you can actually describe it like you have broad competence. I think that the people who are good researchers are the ones who have the ability to store information in their heads and bring it out and remember that: “this doesn’t really go together with the article I read seven years ago”, and they get it out and look at it. Okay, it must be because of this. That ability to be able to store that information and retrieve it (Pharmacology, person 1).
Although the notion of intuition is percieved as something important, almost all respondents said that intuition is rarely or never discussed in the organization, for example: It [creativity] is discussed at times. I am one of those people who makes just these, if you could do rational methods for working instead, uses experimental design, thinks through why you do an experiment and so on. Many people say: “Yes, when we’re designing drugs, we must let the chemists use their intuition, you know?” And that makes them say: “Yes, but I’ve darn well been working with synthetic chemistry for 20 years, and I get a feeling that if we put an amide group here, then there will be higher activity”. And then the discussion comes directly into: “Yes, to what extent should we let the chemists use their intuition?” And of course, it does happen that structures that you find out are good have been intuitively designed. And then you can ask yourself if it’s what we call serendipity and how much serendipity is colored by intuition that someone has through experience. But research can be maximizing the chance to have serendipity, although where intuition is maybe a positive factor. Sometimes anyway. I think it’s very important to be aware of intuition. Going on intuition without knowing it yourself. It’s like analogous to being unaware. Lack of knowledge is pretty safe, but not knowing about your own lack of knowledge, unawareness, that is not good. And I think it’s the same with intuition, except in the other direction, because intuition can be a good thing, especially if you understand it and deal with it in a healthy way (Computational chemistry, person 6).
A specific example of how intuition plays a role in drug discovery research is given in this example. The researcher, in organic chemistry and computational drug design, was involved in a screening project that was looking for a new cardivascular drug compound. The task was to invent a pathway for how to synthesize a new chemical structure. Computational chemistry is based on computational technology being able to visualize and simulate the way in which drug molecules and targets (e.g. large proteins or an enzyme) may interact: . . . it can be small things, you might get something back – you work in a project, you get back data and get the feeling that something is wrong. It’s just not right. You look at the pattern and see for example what structures are active, what are not active, you look at the pattern and you feel that “no, this is not right.” And what do you do then? Of course you try, for example, you screen them again, you test them one more time and find out that it is wrong, everything does not really work the way it should or that it really is what it looks to be, and then there’s still something that is not right and then you must go further and then maybe it has something to do with the mechanism. You must keep on working and modifying. You have to maybe get to the bottom of the thing that is not right. The picture is not completely clear. And you proceed in that way and discover something else. Yes, you get the feeling that this is not quite right. And you work on it, make sure that you go on trying to get to the bottom of it. I have had that experience in projects (Computational chemistry, person 7).
Here, a researcher contrasted the role that intuition might play (although it is a vague, less controllable concept) with the present organization and its strong emphasis on cost effectiveness, detailed project plans, and a controlled drug discovery process: The drug development process is not so damned rational as a lot of people would like it to be, instead intuition can prove to be extremely significant. And intuition comes, I think, you can make it easier for them by having a long-term view in the disease area. I think it’s much easier to follow your intuition if you have worked within a specific disease area for a long time than when you have more general intuition about different things. It’s like a feeling when you just read a scientific paper you feel that this – sometimes you can have some kind of worried feeling – you feel that this is important for our work, but you don’t know what. And then you can’t let it go. And sometimes then the whole thing gels and you realize: “Yes of course!” And then if you have even more luck, it can lead to success. And without what you could define as intuition that gave some person that feeling of
In conclusion, all respondents express the notion that intuition in different perspectives and disciplines plays an important role in drug discovery research. In addition, most of the respondents argued that intuition is strongly linked to creativity. 6.3 Intuition and organizational aspects To make the research more effective and increase innovative output, the influence of various technologies (e.g. high throughput screening and computational drug design) is now an important part of pharmaceutical research. These new scientific screening methods represent an attempt to use various forms of what Bachelard (1984)
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calls phe´nome´notechniques, “technologies of visualization” that enable faster identification of NCEs. The technologies involve a completely new way to manage scientific data and information. These technologies might make routine work more efficient but may be an obstacle to scientific creativity (see Thomke and Kuemmerle, 2002, p. 631; Cardinal, 2001). However, as a representative for top management pointed out, the increasing role of intuition might have to bridge that gap: . . . if you can use technologies in routine work and make things more quickly and perhaps more precise, get more reliable results like a lot of these robot systems can do than if you are doing it manually then it is a great advantage, which should also actually give people more time to think creatively. Many successes in automatization make it possible for us to have access to completely new amounts of data that we can treat in a completely different way than before, because we have so much more data. We can see patterns and other things that maybe would otherwise be completely impossible to identify. You should look at these technologies as tools and then there is always a human factor when you are looking at data. This evaluation, you have to put it into its context. Is it actually reasonable? Should we choose this chemical structure that had a signal in this high throughput screening? Or is it perhaps completely impossible to do, modifying it so that it can be optimised. We don’t have a really good selection system yet. Instead, we have certain filters so that you can take away characteristics and other things but it’s still up to a creative evaluation by an experienced chemist, and it’s also based on – not just knowledge but also on intuition. I think that intuition and research are incredibly important when it comes to seeing that this is darn important. It may also be creativity. It’s a question of definition, you know, but having an intuitive feeling about this being the right way and this is an important result (Discovery senior management, person 3).
Most respondents disclosed problematic factors when dealing with intuition in the organization. One factor was the way in which intuition is increasingly affected when planning and managing drug discovery research. This is illustrated by one respondent: The organization today is in such a streamlined format in some way, it feels like. The way it works with us anyway, you maybe work for a period of months with a target and then that is the end of that and you start on something new and it can in and of itself be very stimulating, but after that time you have learned what you have started to work with and then you must stop and start on something new. I don’t know – in that way I have a little bit of a hard time thinking that we’re working in the right way somehow. There must be continuity in some way in the organization and it is a little too divided into parts in some way. Yes, I think that it actually feels like that sometimes. I hope that there is room
for continuity too, but they have not done that anyway. I mean, the press gets harder and harder on the organization too. There must be more and more targets, there are projects and so on and so forth. I mean, there is hardly time for being able to sit down and think. You must put together reports for different levels all the time. You are driven by having to have something positive to say at these meetings, and you focus on coming up with something for them, but that maybe is not really what you should be doing after all, but maybe you should work a little, little more long term, and you miss that with this type of project (Organic chemistry, person 5).
Another aspect of intuition is that it is seen as something mysterious, and subsequently unprofessional or nonscientific; a chemist explains: There are prejudices. I mean that intuition is built on – like I said, what I believe – earlier experience. And you can easily be led to believe something that is a preconceived idea and that directs you too much, and you don’t look at the facts that exist (Computational chemistry, person 7).
The importance of leadership and intuition may not be obvious. However, a respresentative from senior management pointed out the need for management attention in relation to intuitive dimensions in drug discovery: Yes, because as a leader, the point is not only to push your own ideas, you know, but to listen to the ideas of the person who is the most recent employee. I think it would also send the right signals if even higher management can accept, so to speak, the newest guy’s view of the business. As it looks through others’ eyes, too. They come from the outside (Discovery senior management, person 3).
In conclusion, although intuition in drug discovery research is claimed to be highly important, the respondents argue that it is something that is seldom or never talked about in the organization. Furthermore, the common notion from the respondents reflects different concerns about how intuition is exploited in the current rationalized drug discovery process.
7. Discussion Pharmaceutical researchers claim that the human faculty of intuition represents thinking that goes beyond the strictly rational and representational; intuition is claimed to be emotional, a gut feeling, drawing on experience, and vacillating between being rational and irrational. Intuition is a mode of thinking that accounts for what is not really proved in scientific terms, but still is valuable knowledge in the process of drug discovery and development. In addition, the faculty of intuition matters in new
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drug development. Intuition is a type of thinking that is captured by metaphors such as “thinking outside the box” or “seeing the broad picture”, that is, metaphors that depict intuition as the ability to see relationships, causalities, and other associations for which there are not yet proofs of such relationships. New drug development is a highly specialized activity that consists of many different scientific disciplines, and authorities regulate the process. Consequently, effective management of operations must support new drug development. If intuition is regarded as the capacity to make decisions under time pressure – without complete information (i.e. being subject to what Herbert Simon calls “bounded rationality”), then intuition is a highly useful resource in new drug development. But intuition is, as some of the interviewees pointed out, by no means an extrarational or super-rational capacity that can be invoked in cases for which complete information is unavailable; intuition is always at stake because it draws on experiences and emotional faculties. So invoking intuition is a political issue because by definition, it goes beyond formal decision-making systems that are provided. In short, intuition is an individual and organizational resource that is complicated to manage and not like new technologies, such as HTS, which do not rely on the experiences and emotions of pharmaceutical researchers but rather on automation of the identification of new chemical substances. The pharmaceutical researchers emphasized that intuition is an important resource in new drug development activities. Yet the concept of intuition is not fully examined in the organization creativity literature. If one follows Bergson in conceiving of intuition as thinking that is “pre-representational” and operates outside of the favored regime of representation (e.g. mathematics or a scientific vocabulary), then intuition has a rather clear meaning and role vis-a`-vis more conventional and analytical forms of rationality. For Bergson, rational thinking is analytical in terms of being able to reduce a complex matter to a signifying system, but intuition is synthetic in terms of being able to see what is outside of the signifying system. When using the metaphor of “single dots constituting a line”, then rational thinking is the individual dots which we know are there, while intuition enables synthesis from the line and substantiates the claim that the spaces between the dots are not just voids but are regularities that constitute the line. Consequently, it may be argued that the literature on organizational creativity has not been very concerned with the pre-representational forms of thinking represented by intuition. It is common to address extraordinary contributions and individuals in this literature, but there is no
coherent theoretical framework developed for use when studying such events and occurrences. So a Bergsonian view of intuition could be fruitfully developed within this literature. Rather than conceiving of some forms of thinking as being merely “original” (one trait of what we tend to deem as creative), Bergson’s thinking offers an ontological and epistemological model that can examine what this kind of originality consists of, for example, if originality in solutions will make interesting and new syntheses of what is already known. At the bottom line, Bergson may be a useful ally when criticizing the technicalinstrumental rationality that serves as the bedrock for all management activities. Standardized management solutions for engagement with an external world (e.g. calculation, reduction of continuous realities to discrete events and entities, and enactment of stable and predictable relationships between different actors) are mostly analytical in nature; the management mentality establishes a world that is manageable (Gephart, 1996). This works fine as long as such reductionism is applicable. In many cases, management practice cannot rely on its analytical apparatus and needs to develop practices, techniques, and systems that can deal with fluidity, movement, and change, in brief, when speaking of Bergson, what cannot be fully captured by the rational thinking of the intellect. Grint (1997, p. 9) writes: Like many other forms of thought, [management theory] does tend to rationalize away the paradoxes, chance, luck, errors, subjectivities, accidents, and sheer indeterminacy of life through a prism of apparent control and rationality.
In the case of new drug development, perhaps what occurs between analytical systems of HTS and other technologies are never regarded as anything more than such chance, luck, and errors. So intuition may be representative of a form of thinking that goes beyond these reductionism modes of thinking. Arvid Carlson, a 2001 Nobel laureate in medicine with extensive new drug development experience, testifies to this need for taking the consequences of what one may already know:
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Especially on the discovery side, it is like walking in a labyrinth, you face many decision points and the thing is not to jump in the wrong direction too many times. The first thing you need is luck, and then it is the other, what people call intuition . . . And then there is the question: what is intuition? Intuition is probably just that, of having a very incomplete, a very fragmentary basis and of being able despite only having fragments to see a pattern that leads your decision in a certain direction (Carlson, 2003).
Intuition and pharmaceutical research: the case of AstraZeneca
European Journal of Innovation Management
Mats Sundgren and Alexander Styhre
Volume 7 · Number 4 · 2004 · 267-279
Being able to theorize the fragmented, incomplete world inhabited by pharmaceutical researchers remains a challenge for the organization creativity literature.
reproduce knowledge in the pharmaceutical industry offers limited latitude for creating new knowledge; and this could be why the industry lacks radical innovation (Horrobin, 2002). We argue that the role of intuition is an important subset of understanding organizational creativity and a rather unexploited platform for creating new knowledge, which demands receptiveness to a more critical view of traditional knowledge management theory. Creativity in the context of the pharmaceutical industry is an ambiguous concept (Sundgren and Styhre, 2003b). The predominant notion of creativity stresses something that is purposeful; something that other scientists have not done before. Creativity must always be based on accurate knowledge of the specific domain. Thus organizational creativity in new drug development demands an organizational capacity for becoming masters of a specific scientific domain, while enabling an overview of an area of science. A clear message for senior management is to be open to discussion within the organization regarding ways in which intuition plays an important role within drug discovery research. This would enable better understanding of organizational creativity in which intuition is not seen as a fuzzy concept, but as an asset that could be in balance with the rationalistic thinking. We argue that intuition is needed, because creativity is an ambiguous concept. As Deleuze and Guattari (1995, p. 18) write:
7.1. Implications for management Implementation of a more rationalistic approach to become more effective has been the dominating trend in many large R&D organizations. Many pharmaceutical companies have turned to rigorous project and portfolio management to make research more efficient (Schmid and Smith, 2002b). One could argue against the trend to implement policy that is too rigorous. This study suggests that intuition is an intrinsic part of the creative process in drug discovery and thus an important organizational resource (Sundgren and Styhre, 2003a). The study’s narratives suggest that intuition and creativity are poorly institutionalized in research-based organizations. So here, rationalist approaches that draw on technoscientific practices (e.g. HTS) would benefit from being supported by continuous, widely shared narratives on how research, innovation, and creativity materialize in daily activities in pharmaceutical and other researchbased organizations. The narrative view of organizational practices (see, e.g. Czarniawska, 1998; Gabriel, 2000) suggests that the process of organizing is embedded in story-telling and joint sense making of events and occurrences. Narrative studies of organizations, such as Orr’s (1996) study of copy-machine technicians, Boje’s (1991) study of an office supply firm, Bryman’s (2000) examination of technology-based firms, and Humphreys and Brown’s (2002) analysis of organizational identities from a narrative perspective suggest that the institutionalization of vocabularies, standard plots, speech genres, and so forth, support and reinforce organizational practices. So this study suggests that an ongoing narrative on intuition and creativity would facilitate more effective research practices. Being able to tell stories and share experiences from highly specialized, sophisticated research-based work remains as one of the key mechanisms that underlies excellent organizational performance in the pharmaceutical industry. Thus, telling stories about intuition and creativity is an integral, yet somewhat neglected component of the pharmaceutical researcher’s skills set. From the rationalist view within contemporary management theory and from a pharmaceutical industry perspective, the rationalistic view of making research more effective somewhat parallels the dominant knowledge management tradition (Styhre, 2002). This tradition tends to manage and distribute knowledge in organizations as fixed and ready-made. This trend to codify, integrate and
In any concept there are usually bits or components that come from other concepts, which corresponded to other problems and presuposed other planes. This is inevitable because each concept carries out new cutting-out, takes on new contours, and must be reactivated or recut. On the other hand concepts also has a becoming that involves its relationships with concepts situated on the same plane.
Acknowledgement of intuition’s role in new drug development would: . enrich contextual thinking that broadens scope through radical thinking and enrich the concept of organizational creativity; . increase an organization’s ability to move between different scientific domains within new drug development; and . enable management to increase the probability of capturing ideas in an early phase, which could result in scientific breakthroughs.
8. Conclusion This paper presents a study of the role of intuition in pharmaceutical research. Conceiving of
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intuition as being the ability to synthesize on the basis of available information, intuition is contrasted with reductionistic and analytical forms of thinking. Even though the interviewees argued that intuition is a highly useful human faculty, it is still somewhat controversial to use intuition as the basis for decisions. Because intuition was more closely associated with emotionality and embodiment (e.g. gut feelings) than with cognitive capacities, intuition served as some kind of supplement to more conventional forms of thinking. Still, intuition is acknowledged among pharmaceutical researchers, especially in cases in which the researchers must account for a multiplicity of facts during decision making. Consequently, the organizational creativity literature that is highly positive to the idea of the extraordinary and ground-breaking innovations, must recognize the faculty of intuition. This paper suggests that the thinking of Bergson may be one fruitful resource to exploit in this endeavor. From an innovation management research policy perspective, this study also calls for more critical perspectives in knowledge management theory regarding how to understand and create new prerequisites for the creation of new knowledge.
in managing research and development”, Organization Science, Vol. 12 No. 1, pp. 19-36. Carlson, A. (2003), personal interview, January. Czarniawska, B. (1998), A Narrative Approach to Organization Studies, Sage, Thousand Oaks, CA, London and New Delhi. Deleuze, G. and Guattari, F. (1995), What Is Philosophy?, Verso, London. Dorabje, S., Lumley, C.E. and Cartwright, S. (1998), “Culture, innovation and successful development of new medicines – an exploratory study of the pharmaceutical industry”, Leadership & Organization Development Journal, Vol. 19 No. 4, pp. 199-210. Drazin, R., Glynn, M.A. and Kazanjian, R.K. (1999), “Multilevel theorizing about creativity in organizations: a sensemaking perspective”, Academy of Management Review, Vol. 24 No. 2, pp. 286-307. Ekvall, G. and Ryhammar, L. (1999), “The creative climate: its determinants and effects at a Swedish university”, Creativity Research Journal, Vol. 12 No. 4, pp. 303-10. Eysenck, H.J. (1996), “The measurement of creativity”, in Boden, M.A. (Ed.), Dimensions of Creativity, Bradford Books, London. Ford, C.M. (1995a), “Creativity is a mystery”, in Ford, C.M. and Gioia, D.A. (Eds), Creative Action in Organizations: Ivory Tower Visions and Real World Voices, Sage, Thousand Oaks, CA, pp. 12-53. Ford, C.M. (1995b), “A multi-domain model of creative action taking”, in Ford, C.M. and Gioia, D.A. (Eds), Creative Action in Organizations: Ivory Tower Visions and Real World Voices, Sage, Thousand Oaks, CA, pp. 330-53. Ford, C. (2000), “Creative developments in creative theory”, Academy of Management Review, Vol. 25 No. 2, pp. 284-7. Ford, C.M. and Gioia, D.A. (2000), “Factors influencing creativity in the domain of managerial decision making”, Journal of Management, Vol. 26 No. 4, pp. 705-32. Gabriel, Y. (2000), Storytelling in Organizations: Facts, Fictions, and Fantasies, Oxford University Press, Oxford. Gephart, R.P. Jr (1996), “Postmodernism and the future history of management”, Journal of Management History, Vol. 2 No. 3, pp. 90-6. Gioia, D.A. (1995), “Contrasts and convergences in creativity”, in Ford, C.M. and Gioia, D.A. (Eds), Creative Action in Organizations: Ivory Tower Visions and Real World Voices, Sage, Thousand Oaks, CA, pp. 317-29. Grint, K. (1997), Fuzzy Management: Contemporary Ideas and Practices at Work, Oxford University Press, Oxford. Grosz, E. (2001), Architecture from the Outside: Essays on Virtual and Real Spaces, The MIT Press, Cambridge, MA. Habermas, J. (1968), Knowledge and Human Interest, Heinemann, London. Heppard, K.A. and Blasick, J. (2000), “The pharmaceutical industry 1970-1995”, in Huff, A.S. and Huff, J.O. (Eds), When Firms Change Direction, Oxford University Press, Oxford. Horrobin, D.F. (2001), “Innovation in the pharmaceutical industry”, Journal of the Royal Society of Medicine, Vol. 93, pp. 341-5. Horrobin, D.F. (2002), “Effective clinical innovation: an ethical imperative”, Lancet, Vol. 359, pp. 1857-8. Humphreys, M. and Brown, A.D. (2002), “Narratives of organizational identity and identification. A case study of hegemony and resistance”, Organization Studies, Vol. 23 No. 3, pp. 421-47. Jeffcut, P. (2000), “Management and the creative industries”, Studies in Cultures, Organizations and Societies, Vol. 6, pp. 123-7.
References Agor, W. (1989), Intuition in Organizations: Leading and Managing Productively, Sage, Newbury Park, CA. Amabile, T.A. (1996), Creativity in Context: Update to the Social Psychology of Creativity, Westview, Boulder, CO. Andriopoulos, C. (2001), “Determinants of organizational creativity: a literature review”, Management Decision, Vol. 39 No. 10, pp. 834-40. Ansell Pearson, K. (2002), Philosophy and the Adventures of the Virtual: Bergson and the Time of Life, Routledge, London and New York, NY. Bachelard, G. (1964), The Poetics of Space, trans. by Jolas, M., Beacon Press, Boston, MA. Bachelard, G. (1984), The New Scientific Spirit, Beacon Press, Boston, MA. Bechara, A., Damasio, H., Tranel, D. and Damasio, A.R. (1997), “Deciding advantageously before knowing the advantageous strategy”, Science, Vol. 275, pp. 1293-5. Bergson, H. (1992), The Creative Mind: An Introduction to Metaphysics, Citadel Press, New York, NY. Bergson, H. (1999), An Introduction to Metaphysics, Hackett, Indianapolis, IN. Boden, M. (1996), Dimensions of Creativity, Bradford Books, London. Boje, D.M. (1991), “The storytelling organization: a study of story performance in an office supply firm”, Administrative Science Quarterly, Vol. 36 No. 1, pp. 106-26. Bruner, J. (1986), Actual Minds, Possible Worlds, Harvard University Press, Cambridge, MA. Bryman, A. (2000), “Telling technological tales”, Organization, Vol. 7 No. 3, pp. 455-75. Cardinal, L.B. (2001), “Technological innovation in the pharmaceutical industry: the use of organizational control
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Knorr Cetina, K. (1999), Epistemic Cultures: How Sciences Make Knowledge, Harvard University Press, Cambridge, MA. Kolakowski, L. (1985), Bergson, Oxford University Press, Oxford and New York, NY. Kvale, S. (1996), InterViewing, Sage, London. Latour, B. and Woolgar, S. (1979), Laboratory Life: The Construction of Scientific Facts, Princeton University Press, Princeton, NJ. Leonard, D. and Sensiper, S. (1998), “The role of tacit knowledge in group innovation”, California Management Review, Vol. 40 No. 3, pp. 112-30. Lesko, J.L., Rowland, M., Peck, C.C. and Blaschke, T.F. (2000), “Optimizing the science of drug development: opportunities for better candidate selection and accelerated evaluation in humans”, Pharmaceutical Research, Vol. 17 No. 11, pp. 1335-41. Linstead, S. (2002), “Organization as reply: Henri Bergson and causal organization theory”, Organization, Vol. 9 No. 1, pp. 95-111. Lynch, M. (1985), Art and Artifact in Laboratory Science. A Study of Shop Work and Shop Talk in a Research Laboratory, Routledge & Kegan Paul, London. Madjar, N., Oldham, G.R. and Pratt, M.G. (2002), “There’s no place like home? The contributions of work and non-work creativity support to employees’ creative performance”, Academy of Management Journal, Vol. 45 No. 4, pp. 757-67. Massumi, B. (2002), Parables of the Virtual: Movement, Affect, Sensation, Duke University Press, Durham, NC and London. Moore, F.C.T. (1996), Bergson: Thinking Backwards, Cambridge University Press, Cambridge. Mullarkey, J. (1999), Bergson and Philosophy, Edinburgh University Press, Edinburgh. Mumford, M.D., Scott, G.M., Gaddis, B. and Strange, J.M. (2002), “Leading creative people: orchestrating expertise and relationships”, Leadership Quarterly, Vol. 13 No. 6, pp. 705-50. Nelson, R.R. (2003), “On the uneven evolution of human know-how”, Research Policy, Vol. 32, pp. 909-22. Nightingale, P. (1998), “A cognitive model of innovation”, Research Policy, Vol. 27 No. 7, pp. 689-709. Nightingale, P. (2003), “If Nelson and Winter are only half right about tacit knowledge, which half? A Searlean critique of codification”, Industrial and Corporate Change, Vol. 12 No. 2, pp. 149-83. Orr, J.E. (1996), Talking about Machines: An Ethnography of a Modern Job, Cornell University Press, Ithaca, NY and London. Pickering, A. (1995), The Mangle of Practice: Time, Agency, and Science, The University of Chicago Press, Chicago, IL and London. Pisano, G.P. (1997), The Development Factory: Unlocking the Potential of Process Innovation, Harvard Business School Press, Boston, MA. Policastro, E. (1995), “Creative intuition: an integrative review”, Creative Research Journal, Vol. 8 No. 2, pp. 99-113. Policastro, E. (1999), “Intuition”, in Runco, M.A. and Pritzker, S.R. (Eds), Encyclopaedia of Creativity, Academic Press, London, pp. 89-91. Roberts, P.W. (1999), “Product innovation, product-market competition and persistent profitability in the US pharmaceutical industry”, Strategic Management Journal, Vol. 20 No. 7, pp. 655-70. Roberts, R. (1998), “Managing innovation: the pursuit of competitive advantage and the design of innovation
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Further reading Henderson, R. and Cockburn, I. (1994), “Measuring competence? Exploring firm effects in pharmceutical research”, Strategic Management Journal, Vol. 15, pp. 63-84.
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A technology acceptance model of innovation adoption: the case of teleworking Manuela Pe´rez Pe´rez Angel Martı´nez Sa´nchez Pilar de Luis Carnicer and Marı´a Jose´ Vela Jime´nez The authors Manuela Pe´rez Pe´rez, Angel Martı´nez Sa´nchez and Pilar de Luis Carnicer are all Associate Professors, Departamento de Economı´a y Direccio´n de Empresas, Centrico Polite´cnico Superior, University of Zaragoza, Zaragoza, Spain. Marı´a Jose´ Vela Jime´nez is Associate Professor, Departamento de Economı´a y Direccio´n de Empresas, Escuela Universitaria de Estudios Empresariales, University of Zaragoza, Zaragoza, Spain.
Keywords Teleworking, Communication technologies, Innovation
Abstract This paper develops a model of teleworking adoption based on the principles of the technology acceptance model. The framework integrates three categories of factors influencing on teleworking adoption: technological, human resources, and organisational factors. The model fills a gap in the teleworking literature by developing research propositions that take into account different theoretical perspectives to study teleworking adoption.
Electronic access The Emerald Research Register for this journal is available at www.emeraldinsight.com/researchregister The current issue and full text archive of this journal is available at www.emeraldinsight.com/1460-1060.htm
European Journal of Innovation Management Volume 7 · Number 4 · 2004 · pp. 280-291 q Emerald Group Publishing Limited · ISSN 1460-1060 DOI 10.1108/14601060410565038
1. Introduction Teleworking is the organisation of work by using information and communication technologies that enable employees and managers to access their labour activities from remote locations such as: . employees and managers’ homes (homebased teleworking); . airports, hotels and other remote locations (mobile teleworking); and . branch offices whose purpose is to alleviate employees’ commuting (telecenters or teleworking centers). Commentators have suggested many possible costs and benefits associated with teleworking. Organisations may view teleworking as a way to reduce overheads, cut absenteeism, attract scarce personnel, and increase productivity, customer service and organisational flexibility. National governments in the European Union (EU) advocate teleworking both as a means to reduce traffic congestion and offer employment opportunities. Regarding the employees, teleworking gives them more labour time flexibility and less commuting. The development of teleworking started in the 1970s, but the number of teleworkers was initially very low due to: a combination of technological limits and high costs in the information and communication technologies at that time; companies’ reluctance; and unions opposition. Teleworking was again rediscovered in the early 1990s as an alternative way to organise work in order to reduce commuting, balance work and family, and increase productivity. Although the number of teleworkers has increased significantly since the 1990s, there is still reluctance to adopt teleworking and the diffusion has remained below expectations[1]. The low diffusion has been explained by the important changes that teleworking requires in companies organisation and structure (Chapman et al., 1995; Shin et al., 2000). There are reasons to doubt that teleworking adoption results solely from technological determinism. However, in spite of the expectations of teleworking among academics and practitioners, most studies until the late 1990s have covered teleworking issues rather broadly. The reviews of the teleworking literature indicate that most studies are general surveys and case studies unmotivated by theory which cannot uncover the causal process in teleworking adoption (Chapman et al., 1995; Gillespie et al., 1995; Konradt et al., The authors thank the two reviewers for their comments and the financial support of the grant CICYT SEC2002-01883.
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2000; Shin et al., 2000; Baruch, 2001; McCloskey and Igbaria, 1998; Bailey and Kurland, 2002). Although more recent articles investigate clearly formed research questions, the literature to date has investigated demand forces more thoroughly than supply ones (Bailey and Kurland, 2002). Thus, most of the recent grounded in theory research focus on teleworkers instead of the organisations themselves in order to explain teleworking adoption. There are very few grounded in theory studies that have empirically tested the technological and organisational issues that can explain the adoption of teleworking (e.g., Gray, 1995; Ruppel and Harrington, 1995; Tomaskovic-Devey and Risman, 1993). The analysis of the empirical studies reveals the limitation of the results to elaborate a conceptual framework that explains the factors that influence the adoption of teleworking. The purpose of this article is to contribute to the development of organisational knowledge by proposing a model of causal relationships that can explain the adoption of teleworking. The article is structured as follows. The following section proposes the conceptual framework of the model. We then develop several research propositions grounded in theory and justified by empirical results. Finally, the paper concludes with the research implications.
of the innovation becomes less experimented and more widespread. Adoption itself is a stage marked by such events as the initiation of the idea, a champion supporting the innovation’s use, and some events signalling the decision to adopt it. Innovation theory has aided researchers’ understanding of whether an organisation will adopt one of a wide range of innovations that are new to the organisation (Damanpour, 1991). Ruppel and Harrington (1995) suggest that these innovation studies provide an appropriate body of research as a basis for studying the assimilation of new information system processes. Thus, innovation theory may aid our understanding of troublesome information technologies that are not being assimilated as expected. The spread of teleworking is not meeting current expectations, and therefore it is important for future planners to understand the factors influencing the adoption and use of teleworking. Innovation theory provides a body of literature that may aid in the understanding of such factors. The adoption of teleworking could be studied from the perspective of information technology innovations. Studies on adoption of information technology innovations have been well documented in the literature. Many of these studies are based on Rogers’s (1983) innovation diffusion theory. This theory states that diffusion of an innovation depends on five general attributes including relative advantage, compatibility, complexity, observability, and trialability. Tornatzky and Klein (1982) conducted a metaanalysis of findings from studies on innovation characteristics and innovation adoption and concluded that compatibility, complexity, and relative advantage are variables consistently deemed important in the adoption issue. Nevertheless, researchers on complex organisational technology and inter-organisational information systems have criticised the deficiencies of the innovation diffusion theory in explaining the adoption behaviour (e.g. Brancheau and Wetherbe, 1990). Classical diffusion variables by themselves are unlikely to be strong predictors of adoption for complex organisational technology, suggesting that additional factors, either as independent or control variables, should be added. Prescott and Conger (1995) and Chau and Hui (2001) concluded that innovation diffusion factors are not sufficient to help understand the adoption behaviour of complex organisational technologies or inter-organisational information systems. The theory of reasoned action (Fishbein and Azjen, 1975) represents another approach to user technology acceptance that can overcome the limitations of innovation diffusion theory. According to this theory, beliefs influence attitude,
2. Conceptual framework Some scholars view teleworking as a process innovation (Ruppel and Harrington, 1995) that needs the adoption of information and communication technologies. Teleworking means changes in order to organise work from different (and remote) locations with the use of hardware (home/mobile computer, mobile phone, fax) and software information technologies (e-mail, the World Wide Web, groupware, etc.). Teleworking fits the definition of innovation found in innovation literature: i.e. “an idea, practice, or object that is perceived as new by an individual or other unit of adoption” (Rogers, 1983). Teleworking is not an all-or-nothing activity. Only a small percentage of employees may be involved in teleworking. In addition, it can be practised in degrees ranging from less than one work day per week to all five work days per week. Similarly, innovation theory suggests that assimilation of an innovation occurs in core behaviours or bursts of activity, such as the initiation of the idea, initial use or intensive change, and continued use or routinisation of the innovation (Damanpour, 1991; Tyre and Orlikowski, 1993). As assimilation progresses, use
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which in turn shapes intention that subsequently guides or dictates behaviour. An important conceptual difference between innovation diffusion theory and theory of reasoned action is that the former concentrates on the characteristics intrinsic to a technology (or innovation) while the latter anchors its analysis at how important characteristics of a technology are communicated and perceived by target users. One of the most influential extensions of the theory of reasoned action in the information systems literature is the technology acceptance model (Figure 1). The technology acceptance model suggests that when users are presented with a new technology, a number of factors come into their decision about how and when they will use it (Davis, 1989). As depicted in Figure 1, behavioural intention is determined jointly by attitude and perceived usefulness, the latter of which also influences attitude directly. Perceived usefulness was defined by Davis (1989) as: “the degree to which a person believes that using a particular system would enhance his or her job performance”. Perceived ease-of-use he defined as: “the degree to which a person believes that using a particular system would be free from effort” (Davis, 1989). Earlier research on the adoption of innovations also suggested a prominent role for perceived ease of use (Tornatzky and Klein, 1982). Several scholars have replicated Davis’s (1989) original study to provide empirical evidence on the relationships that exist between usefulness, ease of use and system use (Adams et al., 1992; Davis et al., 1989; Segars and Grover, 1993; Szajna, 1994), whereas other scholars have tested extensions of the model to different technologies (e.g. Chau and Hu, 2002). A different approach can be to use the technology acceptance model to study teleworking adoption. The final decision about teleworking adoption is taken by the company’s top management (Daniels et al., 2001; Karnowski and White, 2002). From both firm’s and individual’s perspectives, teleworking will be taken into account if managers and employees perceive teleworking as usefulness and ease of use as a way to organise work in the
company. Both perceptions will influence on the managers and employees’ attitude towards teleworking that in turn may impact on the manager’s intention to offer teleworking and the employee’s willingness to whether or not to telework and how often. Figure 2 depicts the research model of teleworking adoption based on the principles of the technology acceptance model. The next section develops the propositions that guide the managers and employees’ behavioural intention to adopt teleworking.
3. A technology acceptance model of teleworking adoption Managers will be reluctance to adopt teleworking when they cannot see need for the change and/or perceive too many difficulties by using teleworking in their organisations. For example, when there is a lack of required technological resources, when teleworking costs overcome benefits, or when managers perceive that teleworking will negatively influence on the organisational culture (Chapman et al., 1995; Daniels et al., 2001; Illegems et al., 2001). Once organisations have established whether they can, and want to, implement teleworking, they have to identify potential teleworkers. Even if some employees are potential teleworkers, they may not be interested in such a work arrangement if they fear that it may difficult their professional careers. Specific skills may be required of teleworkers. Besides basic information and communication technologies knowledge, they must have self-sufficiency, reliability and communication. Self-sufficiency involves being able to work and solve problems independently, having the ability to concentrate in a non-work setting, good planning capabilities, and good time management skills. The next paragraphs explain the factors at organisational level[2] that influence on the adoption of teleworking. These factors have been classified in three groups: knowledge and technological factors, human resources factors,
Figure 1 The technology acceptance model
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Figure 2 Model of teleworking adoption
and organisational factors. Each one of them has a different influence on the managers and employees’ behavioural intention to use teleworking. Figure 2 also shows the sign (positive or negative) of the proposed relationships to explain teleworking adoption. 3.1. Knowledge and technological factors Teleworking knowledge The literature suggests that if firms are unaware of the teleworking concept, this acts as a constraint, and essentially precludes teleworking from being chosen as a possible work arrangement in the future (Illegems et al., 2001; Pe´rez et al., 2004). Teleworking’s perceived usefulness and ease of use may increase the greater the managers’ knowledge about teleworking experiences and other related issues: P1. Teleworking companies are more aware of the teleworking concept at the time of adopting than non teleworking companies.
Information and communication technologies Teleworking needs technologies, mainly the information and communication technologies: personal and mainframe computers, e-mail, Internet, local area networks (LANs), etc. The adoption of teleworking will be perceived easier if these technologies are already being used in the company, because the employees will have more skills and experience in using and maintaining them. Peters et al. (2004) found that frequent daily computer use positively affect the employees preference for teleworking. Huws et al. (1990), in a survey of 4,000 European employees, also found that their interest in teleworking was positively related to the respondents’ familiarity with new technologies. Workman et al. (2003) found that richer technology media is likely to facilitate (or less impede) commitment to teleworking. On the other hand, managers may use these technologies to monitor more easily their employees’ performance. As a consequence, companies that
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use information and communication technologies more extensively may perceive easier the use of teleworking systems: P2. Teleworking adopters use more information and communication technologies than nonadopters.
affected the opportunity to telework, and that the flatter the organisation, the more likely an employee preferred and practised teleworking. Tomaskovic-Devey and Risman (1993) also found that fears of losing control diminished the probability to offer teleworking to certain employees: P5a. Teleworking adopters perceive more teleworking benefits for the employees and the company than non-adopters. P5b. Middle managers in teleworking adopters play a less important role in human resources decision making than middle managers in non adopter companies.
Electronic communication Similarly, companies with high levels of electronic communication may perceive easier the adoption of teleworking. The literature indicates that teleworking increases the teleworker’s use of synchronous electronic media (e-mail, fax) with both colleagues and supervisors (Illegems et al., 2001). Nevertheless, some scholars (e.g. Duxbury and Neufeld, 1999) indicate that, unless there is a previous use of electronic communication in the organisation, the adoption of teleworking may impact negatively on teleworkers’ communication because colleagues and supervisors may not be used to communicate frequently as often as teleworkers would need to (for example, checking e-mail daily): P3. Teleworking adopters use more electronic communication than non-adopters. Innovation Innovative companies may experience lower difficulties to adopt organisational innovations such as teleworking, because they can benefit from knowledge and learning resources acquired through the innovation process (Rogers, 1983; Dyer and Nobeoka, 2000). Organisational change may even generate the adoption of teleworking (Daniels et al., 2001). Companies value the adoption of organisational innovations to compete through the use of information and communication technologies: P4a. Teleworking companies invest more resources in research and development and innovation than non adopters. P4b. Teleworking companies have a more innovative culture than non-adopters.
3.2. Human resources factors Institutional resistance Those employees and managers who feel threatened by teleworking will decrease its perceived ease of use and usefulness. First, the company’s employees if they perceive more costs than benefits after becoming teleworkers; for example, whenever there are fears of social isolation or bad career prospects (Gray et al., 1993; Be´langer, 1999). And second, middle managers may also feel threatened if teleworking makes their job redundant. Peters et al. (2004) found that having a supervisor at the workplace negatively
Knowledge workers Another human resources-related factor that may increase the perceived ease of use and usefulness of the teleworking is the availability of jobs suitable to teleworking. The employee’s opportunity to telework is influenced mostly by job characteristics (Mokhtarian and Salomon, 1997; Peters et al., 2004). The statistics of teleworking indicate that it is rarely found among manufacturing jobs, but is more frequent in service industries and jobs that contain information-based tasks than can be dispersed geographically and performed asynchronously (Huws et al., 1990; Empirica, 2000; McGrath and Houlihan, 1998). On the other hand, teleworking is also more feasible in non-routine jobs that require human concentration (Baruch, 2000; Be´langer, 1999), and among knowledge employees (e.g. product designers, software engineers, top managers, investment bankers, etc.). Thus, we propose that the types of jobs in the company will be related to the perceived ease of use of teleworking: P6. Teleworking adopters have larger percentages of knowledge employees in the workforce than non-adopters. Salespeople The availability of salespeople in the workforce may also increase the perceived ease of use towards teleworking. The sales function is one of the most frequently performed remotely in industrial and service companies (Empirica, 2000). Salespeople use information and communication technologies and work remotely from several locations; they are involved in their job design and programming, and their performance can be more easily monitored by results than other employees. Salespeople may facilitate the adoption of teleworking, because teleworking is more prevalent among jobs managed by results and where performance can be measured easily (Ommeren, 2000). Thus, salespeople may be role models to the virtual organisation of other activities in the company
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(Watad and Disanzo, 2000). Some scholars have found a positive relationship between the percentage of salespeople in the workforce and teleworking adoption (e.g. Pe´rez et al., 2003): P7. Teleworking adopters have larger percentages of salespeople in the workforce than non-adopters.
Perry-Smith and Blum, 2000; Eaton, 2003). The company’s experience with flextime (flexible working hours) and other human resources flexible practices may facilitate the adoption of new work organisations like teleworking (flexplace). Some scholars (e.g. Illegems et al., 2001) found a positive relationship between teleworking and human resources flexible practices: P10. Teleworking adopters use more human resources flexible practices than non adopters.
Skilled personnel turnover Labour markets characterised by high turnover or short labour supply, may benefit from teleworking (home-based teleworking or telecentres). For example, Hamblin (1995) reports the case of a large public sector employer considering homebased teleworking for secretarial staff because of difficulty in recruiting such staff. Besides, teleworking may be offered as a flexible practice for those employees with difficulties to access a fulltime presence job or to move to another town because of family reasons. Companies need to retain their human resources, who are a source of sustained competitive advantage (Huselid, 1995; Koch and McGrath, 1996). The literature also indicates that teleworking contributes to retain the most valuable employees in knowledge-intensive jobs that are besides better suitable to teleworking and are more scarce in the labour market (Khalifa and Elezadi, 1997; Teo et al., 1998). Thus, skilled personnel turnover may increase the perceived usefulness of teleworking: P8. Teleworking adopters have larger skilled personnel turnover than non adopters. Training in the company To recruit and retain the most valued employees, companies offer several incentives like “on-thejob” training. Training is often necessary to overcome cultural resistance to adopt innovations. In the case of teleworking, training is necessary to overcome both managers and employees’ reluctance when there is lack of technological expertise and other teleworking requirements (Raghuram, 1996). Some studies (e.g. Peters et al., 2004) indicate that the employees more skilled in the use of information and communication technologies are those who more often telework and/or have larger probabilities to be offered teleworking in the company: P9. Teleworking adopters do greater training efforts in teleworking-related issues than non-adopters. Human resources flexible practices Empirical studies indicate that human resources flexible practices (e.g. flextime, part-time work, compressed work week, etc.) contribute to workfamily balance and positively impact on firm performance (Konrad and Mangel, 2000;
Variable compensation Another human resources practice that can facilitate the positive perception of teleworking is variable compensation. Variable compensation is relevant here because it aligns better than fixed compensation systems the goals of the company and the employees, even though their actual behaviours are not well monitored by managers. Since employers are not able to observe teleworkers directly, teleworking might be more prevalent among jobs where performance can be measured easily (Olson, 1989; Ommeren, 2000) or where performance is aligned with the company’s goals via compensation. Thus, the use of variable compensation systems in the company may help to adopt teleworking because there is already a performance-based management and monitoring system in place: P11. Teleworking adopters use more variable compensation systems than non-adopters.
3.3. Organisational factors Temporary contracts The percentage of temporary employees may also influence on the decision to adopt teleworking. Some scholars found a negative relationship between the percentage of temporary employees and teleworking adoption (e.g. Illegems et al., 2001). Most employees with temporary contracts perform low-skilled jobs, which are less frequently teleworked than high-qualified jobs such as knowledge and managerial jobs. Another factor that may hinder the use of teleworking among temporary employees is the need of managerial trust. Managers who trust their employees facilitate the implementation of teleworking and the remote performance of teleworkers (Harrington and Ruppel, 1999). However, temporary employees may have more difficulties in being trusted by their managers because they may view them are being less committed to the organisation than employees with a fixed contract and longer organisational tenure (Leede and Riemsdijk, 2001; Stratman et al., 2004). Thus, we propose that companies with large numbers of
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temporary employees will perceive less ease of use for teleworking in their organisation: P12. Teleworking adopters have lower percentage of temporary employees in the workforce than non-teleworking companies.
execute tasks. These employees may then be more able to work remotely because they will have more knowledge about their job and know how to organise themselves away from institutional rules: P15. Teleworking companies have larger percentages of employees who are involved in their task design and programming than non-adopters.
Activities decentralisation Companies that are more geographically decentralised need more electronic communication than companies with fewer locations, which may favour the adoption of flexible working systems (Daniels et al., 2001). We may expect a positive association between multiple locations and the need to adopt teleworking. Peters et al. (2004) found that the more locations a company has the greater the probability of offering teleworking to the employees, and the greater the preference of employees to become teleworkers: P13. Teleworking companies are more geographically decentralised than nonadopters. Outsourcing Outsourcing non-core and low-knowledge activities may facilitate the adoption of organisational innovations such as teleworking that focus on knowledge activities. Outsourcing production processes may generate in-house organisational changes that can contribute to reduce barriers to new changes like teleworking (Daniels et al., 2001; Illegems et al., 2001). Malone and Laubacher (1998) illustrate how teleworking and virtual organisations may be combined to transform a corporation into a flexible network of freelances electronically linked. On the other hand, the rising importance of flexible work and the development of information and communication technologies facilitate that organisations can change to flexible structures that retain core activities and outsource peripheral activities. Travic (1998) found a positive relationship between flexible organisational structures and the use of information and communication technologies. Thus, we expect that outsourcing will increase the perceived ease of use of teleworking: P14. Teleworking companies outsource more activities than non-adopters. Task programming The employees’ adaptation process to teleworking is related to their capabilities to overcome difficulties in the new work environment. Teleworkers cannot rely on colleagues as often as before to solve problems when they arise at home or other remote locations. Raghuram et al. (2003) found that more self-efficacy teleworkers perform better. The involvement of employees in their tasks design and programming may increase their understanding of information to co-ordinate and
Monitoring Managerial monitoring systems are very diverse, ranging from direct supervision to management by results. The literature indicates that direct supervision and control is not adequate to manage teleworkers, whereas management by results is more suitable for remote working (Illegems et al., 2001). Additionally, companies may be more willing to offer teleworking if the employees are trustworthy. Harrington and Ruppel (1999) found that teleworking adoption is facilitated by management by objectives through trustfulness and the development of a teamwork culture: P16. Teleworking companies have a management monitoring system more oriented to results than non adopters. Organisational culture Supportive organisational cultures are important for working practices that emphasise flexibility for employees. Where personal flexibility and trust are valued, teleworking adoption may be more feasible (Standen, 1997; Daniels et al., 2001). Managerial fears about losing control over remote employees decrease when there is greater trustfulness between managers and employees (Harrington and Ruppel, 1999). Similarly, managers who perceive personal flexibility as important values are more sensitive to offer family-friendly policies to employees such as teleworking (Wood, 1999). Then, we propose that organisational cultures that emphasise trust and personal flexibility will be more adopters of teleworking: P17. The organisational culture in teleworking adopters emphasise more the values of personal flexibility and trust than in teleworking non adopters. Teamworking Teleworking implementation may limit teamworking (Gray et al., 1993). If people do not work at the same place, they are not working together. Teamworking needs that everyone shares ideas and can draw on the resources of the entire team to solve problems. Wherever teams have to meet frequently to share ideas and develop the project, it will diminish the chances to telework: P18a. Teleworking companies have lower percentages of employees in teamworks than non-teleworking companies.
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P18b. Teleworking companies have lower information flows result of teamwork than non-teleworking companies. Sharing work locations The literature indicates that teleworkers obtain more job satisfaction by combining different work locations and sharing their weekly working time between the company, house, visiting customers sites, etc. (Chapman et al., 1995; Konradt et al., 2000; Kurland and Cooper, 2002). Sharing work locations can avoid the feeling of social isolation and other potential problems associated to remote working. Baruch and Nicholson (1997) found that teleworking performance increases when teleworking at home (or other remote location) is shared with working time at the company. Duxbury and Neufeld (1999) also found that parttime teleworking has little impact on the levels of communication in the organisation. Be´langer (1999) shows that employees who telework parttime are not left out the company’s network. Additionally, moderately virtual teleworkers are more identified with their work team organisation, and occupation than are those who telework large portions of their week (Scott and Timmerman, 1999). Thus, we expect that sharing work locations will facilitate the adoption of teleworking: P19. Teleworking companies offer their employees to share teleworking time and working at the office. Keeping contracts Teleworking is a change that may constitute a deviation from the institutional rules and a loss of legitimacy due to a possible rejection by some members of the organisation. Besides, if the employers offer contracts based on outcomes because they are not able to monitor the employees’ behaviour, they transfer risks that future teleworkers will not be willing to assume. On the other hand, it is important for companies to retain those employees who are a source of competitive advantage. An employee may perceive he/she still belongs to the organisation if the company keeps his/her same type of labour contract in case he/she decides to telework. As a consequence, a unified contract approach may facilitate both the employee’s decision to telework and the adoption of teleworking: P20. Teleworking companies keep the same type of contract to employees who want to telework.
3.4. Control variables Firm size Firm size has been examined with regard to teleworking adoption with mixed results (Bailey
and Kurland, 2002). Huws et al. (1990) find teleworking more appealing to managers in large firms than those in small firms, while other studies indicate the reverse (Tomaskovic-Devey and Risman, 1993): P21. There are not significant firm size differences between teleworking companies and non-teleworking companies. Gender Because primary responsibility for homemaking and childcare tasks falls on women (Shelton and John, 1996), female employees face particularly strong work-family conflicts. Firms employing relatively large percentages of female employees are more dependent on them and more likely to adopt flexible work practices as a result (Ingram and Simons, 1995). Some studies (e.g. Osterman, 1995; Konrad and Mangel, 2000) indicate that companies with larger percentages of female employees develop more extensive work-life programmes that impact positively on the firm’s productivity[3]. Teleworking is often seen as a key element of this package due to the rising trend that professional and clerical jobs have become more dependent on information technology and less dependent on time and location. Further, evidence indicates that female virtual workers are more productive than male virtual workers (Hill et al., 1998) and that women have greater adjustment to virtual work than men (Raghuram et al., 2001). However, other studies show that women employees are uninterested in such options because they perceived work, not home, as the less stressful and more emotionally rich environment (Hochschild, 1997). Women are found to be motivated by other considerations such as work flexibility, convenience and increased personal freedom (Hakim, 1995; O’Connor, 2001). The teleworking statistics do not suggest that teleworking is more suitable to female employees than male employees. Thus, despite making up 46 per cent of the total EU workforce, women make up only 19 per cent of “regular” teleworkers and 38 per cent of “supplementary” teleworkers (Empirica, 2000). Supplementary teleworkers are defined in that survey as those who work from home less than one day per week, while regular teleworkers comprise three overlapping categories: home-based teleworkers, mobile teleworkers, and telework by self-employed people in SoHos. This over-representation of men among teleworkers is echoed in the results of the UK Labour Force Survey, which, in 2001, found that men made up 67 per cent of teleworkers, although they constitute only 53 per cent of the total workforce. The breakdown of the UK teleworking workforce by gender and occupation, suggests that occupational segregation may provide the
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explanation for this: the occupations in which teleworking is most likely to be found are managerial, technical and professional, and they are also likely to be male-dominated. Similar results can be found in other countries (Huws, 1996): P22. There are not significant gender differences between teleworking companies and nonteleworking companies.
have focused on individual teleworkers. Continued research centred on teleworkers may have limited value, in large part because many expected individual level outcomes may hinge on the frequency with which one is absent from the office. Our model is a comprehensive analysis of the factors influencing the perceived usefulness and the perceived ease of use of teleworking in the organisation. Unlike models and theories aimed at individual teleworkers, models and theories focused on the organisation are not limited by the frequency with which any single employee teleworks. In the absence of theory, prior research serves as the wellspring of the hypotheses tested in the empirical studies (Bailey and Kurland, 2002). By constructing new studies of teleworkers from results of previous ones in the manner, authors insulate teleworking research from broader organisational studies and fail to develop theorybased explanations for observed phenomena. On the contrary, by making links to existing organisational theories, researchers can bring teleworking research into the greater fold of organisational studies, and provide the foundation for developing theory-based explanations for teleworking its antecedents and its outcomes. By using the technology acceptance model, we hope to have shown how this framework can help integrate previous research by building upon technological, human resources, and organisational factors. The model can be used to examine simultaneously the technological and organisational factors that influence teleworking adoption. The analysis could be further developed in order to take into account recriprocal relationships between technological and organisational factors over time. Longitudinal studies should be used to disentangle accurately causal processes. Thus, by carrying out grounded theory-building studies, researchers may be more likely to identify correctly relevant outcomes for the majority of teleworking companies and individuals who telework. There is notably little research on what forces effectively influence successful teleworking implementation at an organisation. In some organisations, teleworking programmes progressively evolved into an established organisational structure. In other organisations, attempts to establish the flexible work system failed or were abruptly terminated, often due to lack of employee response. However, our understanding of critical success factors in teleworking in organisations is highly limited. Relevant research requires identification of determinants or components of teleworking success. Our model can help identify which organisations are prime candidates to implement
Organisational tenure In an optional setting where employees make this choice for themselves, organisational tenure (the number of years in the organisation) should not influence these individuals’ choices for teleworking. However, from an organisational point of view, the number of years of work for an organisation may affect which individuals are selected for teleworking. Some teleworking organisations have established a minimum tenure (so that the organisational culture is well learned) before individuals are permitted to telework (Barnes, 1994). Managers may find difficult to manage remote workers, and may fear that the employees will lose their organisational commitment: P23. Employees’ organisational tenure in teleworking companies is longer than in non-teleworking companies. Traffic conditions Firms that may experience problems related to road congestion, such as early departures and late arrivals of staff, may be more willing to adopt teleworking in order to avoid those problems. Thus, firms located in areas with bad traffic conditions and road congestion are prime candidates for teleworking: P24a. Teleworking adopters are located in areas with worse road congestion and traffic conditions than non-teleworking companies. P24b. Teleworking companies have larger percentages of employees with longer commutes than non-teleworking adopters.
Concluding remarks This paper has developed a model of teleworking adoption based on the principles of the technology acceptance model. The model’s research propositions are grounded in theory and supported by empirical results from other studies. There is a gap in the literature of teleworking on studies grounded in theory that explain the supply side of teleworking. Most empirical studies to date
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teleworking. Managers may evaluate the feasibility of teleworking adoption according to the variables included in the model (Figure 2). The feasibility of teleworking should be directly related to the number of dimensions that are fulfilled in the organisation. Teleworking adopters will have different characteristics in these dimensions in comparison to non-adopters. One of these dimensions is innovation. If an organisation is endeavouring to introduce teleworking, an innovative culture that stimulates and fosters change would facilitate its adoption. From an institutional perspective, organisations more sensible to innovation opportunities, may have a higher aspiration level with regard to the exploitation of new technologies and may suffer less from the culture of “non-invented here”.
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Notes 1 The percentage of teleworkers in the labour force in the Europan Union was 6 per cent in the year 2000 (Empirica, 2000), whereas in the USA one in five employees participated in some type of teleworking. 2 Factors at national and/or industry level are not included in the analysis in order to simplify the model. According to Daniels et al. (2001) and Tregaskis (2000), teleworking practices are likely to be found in countries with higher percentage gross domestic product spend on information communication technologies, higher percentage of home computers, greater Internet usage per capital, lower relative costs of information technology and telecommunications usage, higher property prices, and lower population density. 3 Other studies found that, while there may be(general relationship between the gender composition of the workforce and family-friendly management, the relationship is mediated by whether or not management perceives family problems as relevant, that is whether they are conscious of these as potential factors to which they have to respond (Wood, 1999).
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Introduction
The pattern of development and diffusion of breakthrough communication technologies J. Roland Ortt and Jan P.L. Schoormans The authors J. Roland Ortt is Associate Professor in Technology Management, Faculty of Technology, Policy and Management and Jan P.L. Schoormans is Professor in Consumer Research, Faculty of Design, Engineering and Production, both at the Technical University Delft, Delft, The Netherlands.
Keywords Diffusion, Communication, Technology led strategy, Innovation
Abstract Diffusion of many successful communication technologies, like telephony and television technology, follows an almost perfect S-shaped curve. This curve implies that, after their introduction, subsequent sales of products on the basis of these technologies can be predicted accurately. However, the diffusion of other breakthroughs in communication technologies, like interactive television, videotelephony or broadband mobile communication technology, shows a more erratic pattern. Introduction of these technologies is often postponed or, once introduced, they are quickly withdrawn from the market after the first disappointing results. Rather than distinguishing alternative patterns, this article shows that the S-shaped curve and the more erratic patterns represent subsequent phases in one pattern of development and diffusion of breakthrough communication technologies. Three phases are distinguished in this pattern. Managerial implications of the differences between these phases are discussed. the paper shows that a company trying to introduce a new communication technology has to adopt different strategies in each phase.
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European Journal of Innovation Management Volume 7 · Number 4 · 2004 · pp. 292-302 q Emerald Group Publishing Limited · ISSN 1460-1060 DOI 10.1108/14601060410565047
The pattern of development and diffusion of several breakthrough communication technologies are analyzed in this article. From the perspective of a company trying to introduce such a technology, it is of vital importance to understand this pattern. In practice, the postponed introduction of universal mobile telecommunications system (UMTS) mobile communication services in diverse countries shows that large telecommunications providers have difficulties in understanding this pattern and adapting their strategies to it. In general, many pioneers trying to introduce a breakthrough technology have had similar difficulties and therefore have left the market (Olleros, 1986). Breakthrough technologies are characterized by a discontinuous advance in technology and by the emergence of new markets (Garcia and Calantone, 2002)[1]. The discontinuous advance in technology means that attainable price/ performance ratios are altered dramatically, or that new kinds of performance are possible (Tushman and Anderson, 1986). The emergence of new markets means that, rather than just substituting technologies in existing markets, new combinations of actors on the supply and the demand side of the market are formed during the process of development and diffusion. Telegraphy, telephony, television, and mobile communication technology are considered breakthrough communication technologies. At the time of their invention, they supported entirely new ways of communication. Diffusion of these technologies required new infrastructures, new procedures, new alliances between organizations, new customer segments and so on. Along with their diffusion, new markets emerged. The development and diffusion of these technologies have had important consequences for society. In the last 150 years, new communication technologies have changed the way in which we communicate or exchange information. “Technological change has placed communication on the front lines of a social revolution” (Paisley, 1985, p. 35). We have moved from a postindustrial into an information society (Naisbitt, 1984; Rogers, 1986; Toffler, 1980). Communication technology has diffused into business environments (Allen and Scott Morton, 1994) and into private households (Miles, 1988), and both have changed radically. In the previous century we witnessed the diffusion of telephony and mass media such as radio and television. More recently, we have seen the advent of mobile telephony, personal computing and Internet technology. These technologies are the precursors of a new generation of communication technologies still to come. The successful diffusion
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Development and diffusion of breakthrough communication technologies
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Volume 7 · Number 4 · 2004 · 292-302
of the “old” communication technologies has certainly had its influence on the expectations regarding the diffusion of the “new” technologies, such as broadband mobile communication. Diffusion refers to the gradual adoption of an innovation in a market segment or in a society. Most empirical diffusion studies focus on the hardware equipment of new technologies. This means that such studies describe the rate at which a particular product form incorporating the new technology is adopted. The diffusion is often depicted as an S-shaped curve indicating the cumulative percentage of a population that adopts a product in the course of time. The shape illustrates the initial low number of adopters, then the rise of the adoption rate until, finally, the number of adopters approaches a maximum. The rate of adoption is related to the steepness of the diffusion curve, while the potential market is related to the maximum height of the diffusion curve (see Figure 1)[2]. The S-shaped curve seems to be a robust model. When we look at the actual diffusion of the telephone, radio, and television, for example, we can see similar S-shaped curves (Miles, 1988; Rogers, 1986; Williams et al., 1988). The similarity of the actual diffusion patterns for telephone, radio, and television seems to indicate that predicting diffusion of new communication technologies is straightforward and that the the S-curve provides a perfect model. In practice, however, expectations turn out to be overly optimistic and of a dubious value for many new technologies (Schnaars, 1989; Wheeler and Shelley, 1987). In particular, several of the new communication technologies that have been introduced since 1970, for example Videotex[3] (Bruce, 1988), videoconferencing (Clarke, 1990),
and interactive television (Schnaars, 1989), have been confronted with a disappointing number of adopters. The diffusion of some of these communication technologies cannot be captured in a simple S-shaped curve (Easingwood and Lunn, 1992). The development and diffusion of some wellknown technological breakthroughs in communication are described in the section entitled “Phases in the pattern of development and diffusion of breakthrough communication technologies”. Subsequently, the notion of the S-curve is extended by distinguishing three phases in the process of development and diffusion of breakthrough technologies. Conclusions and managerial implications for this diffusion pattern will be presented at the end of the paper.
Before the S-curve We will show that the S-curve has to be extended to capture the pattern of development and diffusion of breakthrough communication technologies like the telegraph, telephone, fax, radio, and television technology. Four aspects of these communication technologies are described: (1) the time a breakthrough technology is invented; (2) the process of technical refinement and development of the technology; (3) the first application of the technology in the market; and (4) the applications in the market that mark the wide-scale adoption of the technology. These aspects correspond with the four columns in Table I. Before looking at the table the four aspects will be defined:
Figure 1 Examples of S-shaped diffusion curves
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1837: Morse in US and Steinhill in Germany demonstrate telegraph 1837: Cook and Wheatstone get a patent in the UK 1843: first patent granted to Bain 1847: first image transfer
1863: transmission of sound by Reis 1876: telephone demonstration by Bell
1896: first radio by Mercian (Italy) and Popoff (Russia) 1898: first demonstration of radio
1925: mechanical TV demonstration by Jenkins (US) and Bain (UK) 1926: mechanical TV demonstration by Baird 1929: electronic TV demonstration
Telegraph
Telephone
Radio
Television (TV)
294 1928: first trans-Atlantic transmission 1929: demonstration of a color TV Invention of teletex 1929-1935 experimental broadcasting in UK
Development of crystal detector and later electron tube 1957: first transistor radio from Philips
1878: improvement of the microphone Introduction of better cables and amplifiers increases the range
1844: first telegraph line in the USA Applications: Railroad traffic control Transmission of news 1863: first commercial fax system between Lyon and Paris Applications 1906: fax between newspaper offices Sending weather charts to ships 1877: burglar alarm service in the USA Toy for adults Internal communication in companies; local communication in cities From 1900 on: communication with ships, airplanes; radio amateurs built their own radio 1897: radios are built commercially 1935: regular broadcasting service in Germany 1936: first broadcast in The Netherlands
Diffusion First applications
Number of words/ minute increases 1855: the first letter print telegraph 1874: multiple use of one channel 1919: introduction of telex 1902: experimental fax transmissiona of photographs using optical scanning Speed and quality of transmission improves steadily between 1902 and now
Technical refinement
After Second World War the diffusion of TV takes off (USA). TV became a mass medium
1932: 1 million radios are sold. Radio became a mass medium
More connections after First World War. After Second World War, diffusion takes off
Public use of telegraphy. Stations in postoffices and organizations. Diffusion takes off during the 1850s. International standards after 1865 After 1960 fax becomes popular in Japanese (and after 1970) in European business
Widely used application
Note: a Fax contact in a most rudimentary form was possible after the invention of the telegraph. An image on a sheet of paper is divided into many white and black dots. A telegraph can transfer pulses. Assume a long pulse is a black dot and a short pulse is a white dot. A telegraph can then transfer the image dot by dot, and line by line, by sending the pulses that correspond with the image
Fax
Date of invention
Technology
Table I Invention, technical refinement and application of breakthrough communication technologies
Development and diffusion of breakthrough communication technologies European Journal of Innovation Management
J. Roland Ortt and Jan P.L. Schoormans Volume 7 · Number 4 · 2004 · 292-302
Development and diffusion of breakthrough communication technologies
European Journal of Innovation Management
J. Roland Ortt and Jan P.L. Schoormans
Volume 7 · Number 4 · 2004 · 292-302
(1) The time a breakthrough technology is invented. We will define the invention as the first demonstration of a technological breakthrough. The idea that an invention can be unmistakenly attributed to one inventor at a specific moment in time has been questioned by some authors (Sahal, 1981; Agarwal and Bayus, 2002). An illustration of their point of view is the fact that many inventions are made independently and almost simultaneously by different persons. In these cases, we will give the names of multiple inventors. Furthermore, when an evolutionary perspective on development of technology is adopted, it is hard to distinguish an invention among a line of gradual improvements in the technology (Bassala, 2001). An invention can be defined in various ways, ranging from the moment an idea is presented, a patent is filed, the principle of a technological breakthrough is demonstrated, or the first pilot application of a breakthrough technology is started. When possible, the time a patent was granted, or the time a technology was first demonstrated in public is shown in Table I. (2) The process of technical refinement and development of the technology. Some hallmarks in the development of the technology after the invention are listed in Table I. (3) The first applications of the technology in the market. The (timing of) the first known commercial applications of the breakthrough technologies is described in Table I. A pilot in the market without a commercial goal is not considered to be a first application of the technology. (4) The applications in the market that mark the wide-scale adoption of the technology. Although the mainstream applications for each of the breakthrough technologies are well-known, it is hard to define precisely (the time of) “widescale adoption”. We will, therefore, indicate in which decade the diffusion of products, on the basis of the breakthrough communication technologies, increased significantly.
depending on the question as to whether the demonstration of a mechanical television system in 1925 or the demonstration of an electronic television system in 1929 is considered to be the date for the invention of television. A second conclusion from our analysis is that it generally takes a decade or more after the first introduction of a communication technology into the market before diffusion takes off. Establishing when a technology is first introduced may be difficult. Establishing when its diffusion takes off is even more difficult. However, even rough estimates of the intervals between first introduction and a significant increase in diffusion rates reveal that they are considerable. The telegraph was first introduced in 1844, its diffusion took off in the 1850s when increasing numbers of telegraph stations were opened and telegraphy became a public service. This shows a time interval between introduction and diffusion take off of more than six years. Somewhat longer time intervals can be found for the telephone, radio and television (at least a decade each). Diffusion of the fax took off about a century after the first market introduction. Fax transmission was introduced into the market in 1863, but significant increases in diffusion rates would last until the 1960s. A third conclusion is that, directly after their introduction, most of the communication technologies are used in small-scale specific applications. These applications are totally different from the more wide-scale and well-known applications. The first telephones, for example, were used as a burglar alarm, as a toy, and as an appliance for internal communication in companies. Telephony was also used by the local telegraph office in order to transfer telegrams to clients, rather than the telegram being delivered to the home or office. The last application seems to have paved the way for wide-scale telephony since lines to the telegraph office could be connected in pairs to establish a local area telephone conversation. In due course, the telegraph office became a telecommunication office. Similar smallscale applications can be found for the other communication technologies.
A first conclusion from our analysis is that the average time from invention to the first market introduction is between seven and ten years for these breakthrough communication technologies. The time from invention to the first market introduction is seven and 16 years for the telegraph and fax technology, respectively. For the telephone, this time interval is either one or 14 years, depending on the question as to whether 1863 or 1876 is considered the date for the invention of the telephone. For radio technology this time interval is about four years and for television technology it is either six or ten years,
Implications of these conclusions for the pattern of development and diffusion of breakthrough communication technologies The fact that it takes some years after the invention of a technology before the first product is introduced in the market (conclusion 1) and the fact that it takes at least an additional decade before the diffusion of a successful communication technology takes off (conclusion 2), does not imply that the S-shaped diffusion curve is an inappropriate model. It suffices to say that the
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curve generally starts about a decade after the invention of a technology and that the curve is stretched at the beginning of the diffusion process. However, the fact that the first small-scale applications of a communication technology often differ from the later wide-scale application (conclusion 3), has important implications. It implies that the early stage of the diffusion process is hardly captured in a single S-shaped curve. Each of the small-scale applications can be described in a separate diffusion curve. These small-scale applications have an important role in stimulating wide-scale diffusion of the technology. Illustration that the S-shaped diffusion curve is a somewhat limited model Perhaps the best way to illustrate that the S-shaped diffusion curve does not always capture the diffusion pattern of a technology, is to look at facsimile technology. The first patents for the fax were granted in 1843, the first successful fax transmission was completed in 1902 by Jenkins (Coopersmith, 1993). It took a long time before the fax technology was introduced in the market. At first, the fax was used to transfer weather charts to ships. Shortly afterwards, in 1911, a fax was used to send pictures for newspapers between Berlin, London and Paris: Less successful were the attempts in the late 1930s by newspapers and their radio stations to broadcast newspapers. Enthusiasts promoted facsimile radio receivers that could bring newsprint into homes [. . .] (Coopersmith, 1993, p. 46).
After the first market introduction the diffusion is characterized by periodic introduction, decline and reintroduction into the marketplace. In fact, the actual S-shaped diffusion pattern really began decades later around 1960 in Japan. Around that time the telex, an appliance by which a limited number of alpha-numeric symbols could be transmitted through the ether, became more popular. Japanese, due to its large number of symbols, was unsuited to telex relay, the fax, however, was able to transfer all kind of signs and therefore became very popular at that time in Japan. Some years later, around 1970, the fax began to diffuse into business organizations in Europe. In summary, this paragraph shows that the S-shaped diffusion curve is preceded by important developments: . The S-curve does not show the relevant developments just after the invention of a breakthrough communication technology. The first products or services incorporating the technology are invariably introduced into the market some years after the invention. . The S-curve does not show the erratic patterns that can be witnessed after the first
market introduction of a product or service incorporating the breakthrough communication technology.
Phases in the pattern of development and diffusion of breakthrough communication technologies The S-shaped diffusion model is meant to describe the diffusion of product forms rather than technologies (Dosi, 1982; Clark, 1985). Based on an analysis of four cases, we developed an extended model to describe the development and diffusion of a breakthrough communication technology. Three phases in this process will be distinguished, the last of which is represented by the well-known S-shaped curve (see Figure 2). The beginning and the end, the average length, and the market actors and factors that generally play a major role, will be described for each phase. The innovation phase The first phase, which we will call the innovation phase, comprises the period from invention of a technology up to the first market introduction of a product incorporating the technology. After the invention, a technology is available in some rudimentary form. In the innovation phase this technology is transformed into a marketable “product”[4]. The length of this phase can vary considerably. We found periods between one (for the telephone) and 16 years (for the fax) between invention and market introduction for five breakthrough communication technologies. Mansfield (1968) claimed that the average time from invention to the start of the commercial development process is about ten to 15 years. From the start of this process up to the market introduction, again, a couple of years elapse. Utterback and Brown (1972) estimate that, on average, this takes an additional five to eight years. So, according to these authors the period from invention to the first market introduction comprises 15-23 years. Agarwal and Bayus (2002) found an average period of 28 years between invention and commercialization for 30 breakthrough innovations from diverse industries. The large differences in these estimates can be attributed to multiple factors. First, differences can be attributed to the type of industry (Mansfield, 1968). Commercialization takes a relatively long period in the pharmaceutical industry compared to the fast-moving goods industry, for example. Second, we found considerably different periods for technologies in one industry. The radio, for example, was
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Figure 2 Three phases in the diffusion process
introduced less than four years after its invention whereas the fax was introduced about 16 years after its invention. Third, the length of the time interval depends on the specific definition of invention. We found time intervals from invention to commercialization for the telephone that varied from one to 14 years depending on the question as to whether the demonstration of Reis (in 1863) or the demonstration of Bell (in 1876) is considered to be the date of invention of telephony. During the innovation phase, organizations like research institutes and universities, in many cases co-funded by the government, play the central role. To attract potential consumers, the reliability and performance of the technology often has to increase whereas the price of the technology has to decrease. Potential applications have to be found and new products and services have to be developed on the basis of the technology before it can be introduced into the market. Although in this phase no products or services based on the breakthrough technology will be introduced into the market, other types of market mechanisms can be witnessed. In this phase, a good position in the market of supply and demand for reseach funds and researchers is essential for success. The market adaptation phase The second phase, referred to as the market adaptation phase, begins after the first market introduction of a product on the basis of the breakthrough technology and ends when the diffusion of this product takes off. After the first introduction, instead of a smooth S-curve, in practice an erratic process of diffusion may occur. In this situation the market is unstable and, as Clark (1985) puts it, in a “fluid state”. The diffusion is characterized by periodic introduction, decline and re-introduction of multiple products in multiple small-scale applications. Such a pattern is
not uncommon for communication technologies (Carey and Moss, 1985). We estimated that this phase comprises more than a decade for the five breakthrough communication technologies. An extended period is also found for other technologies (Mansfield, 1968; Utterback and Brown, 1972): A review of past forecasts for video recorders and microwave ovens illustrates the length of time required for even the most successful innovations to diffuse through a mass market [. . .]. Both took more than twenty years to catch fire in a large market (Schnaars, 1989, p. 120). Most innovations, in fact, diffuse at a surprisingly slow rate (Rogers, 1983, p. 7).
Agarwal and Bayus (2002) indicate that this phase, on average, lasted 18.7 years for breakthrough technologies invented before the Second World War. Companies try to establish a standard with their product during the market adaptation phase, and competition may become intense. The wide-scale diffusion of a breakthrough communication technology, however, requires coordination in the market among competitors, potential consumers, producers of complementary products or services and suppliers. In practice, this cooperation is hampered by the chicken-and-egg problem. Suppliers of complementary products and services demand a critical mass of users before they consider entering the market, yet these suppliers are desperately needed to establish this critical mass of users in the first place. Finally, since the technology quickly develops during this phase, and since dominant market applications have not yet been discovered, technology standards and dominant product designs mostly still have to be established, which means that this phase tends to have a fierce and rather Darwinistic character. In the struggle to produce the fittest products and
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services, many companies become extinct (Olleros, 1986). The market stabilization phase The third phase, referred to as the market stabilization phase, begins when the diffusion of a product on the basis of the breakthrough communication technology takes off and ends when the technology is substituted. Clark (1985) refers to this phase as a more or less rigid state. The rigidity refers to the fact that dominant product designs and applications emerge from the second phase. In this third phase, diffusion of a product form may be depicted in a single diffusion curve, which mostly resembles an S-curve when cumulative adoption is depicted in the course of time. Different curves have been found (e.g. Rink and Swan, 1979; Tellis and Crawford, 1981), but in these cases no phases were distinguished in the diffusion pattern, which means that some of the divergent patterns may be attributed to the fact that the diffusion was still in the market adaptation phase. The diffusion of the five breakthrough technologies, i.e. television, radio and telephone technology, is still continuing. While for the telegraph and the fax, the period from the take-off to substitution took about 100 and 30 years respectively. The length of this period, also referred to as the technology life cycle, can vary from a couple of years up to centuries (Jain, 1985). More or less standard strategies can be pursued in the market stabilization phase. During this phase, companies strive for typical goals like a large market share, large profits and so on. During the market stabilization phase the technology and resulting products and services will be improved constantly, although the dominant design will essentially remain the same. Several features were added to the television during the market stabilization phase, for example, that in due course became part of the standard product (Tho¨lke, 1998). Color televisions replaced black-and-white sets, teletext was added, televisions became portable, and, to attain economies of scale yet remain flexible, modular product designs or product platforms can be formed. Companies can also strive to intensify the use of a product in existing markets and thereby increase market potential. The time that the market potential for television was formed by the number of consumer households is long past, currently, television sets are commonly installed in each room of a home, in cars, in caravans and boats, in hospitals and so on. So, the level of the market potential has shifted considerably during the market stabilization phase. Companies also segment the market and offer differentiated products for each segment.
Some of the general differences between the three subsequent phases in the process of development and diffusion of breakthrough communication technologies are summarized in Table II. The first row indicates the beginning and the end of each phase. The second row lists some findings regarding the length of each phase. In the third and fourth row, the typical kind of market actors and factors as well as typical market mechanisms in each phase, are described.
Conclusions and managerial implications After investigating the pattern of development and diffusion of five breakthrough communication technologies, we conclude that the well-known S-shaped diffusion curve in fact represents just one phase of this pattern. Three phases are distinguished in this pattern. First, the innovation phase covers the period from the invention of a breakthrough communication technology up to the first market introduction of a product on the basis of the technology. In this phase, which lasts about a decade, the technology is turned into a marketable product. Second, the market adaptation phase comprises the period from the first market introduction up to the point where the diffusion takes off. This phase, also lasting about a decade, often shows an erratic pattern of diffusion with the introduction, withdrawal and re-introduction of various products on the basis of the breakthrough technology. Third, the market stabilization phase begins when a dominant product design, i.e. a basic product form that turns out to be the standard for several years, emerges and the diffusion of this product takes off. The third phase ends when the product based on the breakthrough technology is substituted and sales drop. In the introduction we stated that the patterns of development and diffusion of several new communication technologies like Videotex, videoconferencing, and interactive television are difficult to capture in a simple S-shaped curve. These patterns diverge considerably from the S-shaped patterns of diffusion of some of the older communication technologies like the telegraph, telephone, fax, radio, and television technology. At first sight these results imply that different patterns have to be distinguished for different types of communication technologies. This article shows, however, that the S-shaped pattern of diffusion of the old technologies is preceded by similar erratic patterns of diffusion. The divergent diffusion patterns of the newer communication technologies are therefore attributed to the fact that these
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Table II Differences between the three subsequent phases in the process of development and diffusion of breakthrough communication technologies Phase Characteristics
Innovation phase
Market adaptation phase
Market stabilization phase (the S-shaped pattern)
Begin and end of the phase
From invention of a technology up to the first market introduction of a product incorporating the technology
Length of the phase
Length can vary considerably (one to 30 years), but on average comprises seven to ten years Individual inventors and entrepreneurs, R&D institutes, universities, and governments (in the role of provider of research funds)
Begins after the first market introduction of a product on the basis of the breakthrough technology and ends when the diffusion of this product takes off Length can vary considerably, but mostly comprises a decade or more
Begins when the diffusion of a product on the basis of the breakthrough communication technology takes off and ends when the technology is substituted Length coincides with the life cycle of a product category
Potential competitors working on the same type of product-technology. Innovative consumers and lead users. Market actors with products and services that are complementary to the technology. Government in the role of lead user or regulator Substitution of alternative product technologies Chicken-and-egg problem Critical mass effects Finding the best product-market combinations on the basis of the technology Establish or reinforce standards Supply and demand for complementary products and services
Early adopters up to the late majority of consumers, competitors of the same product or service, suppliers and organizations providing complementary products, and services
Market actors and factors in the phase
Market mechanisms
Supply and demand for research funds and excellent researchers
technologies are in the market adaptation instead of the market stabilization phase. The idea that the development and diffusion of breakthrough communication technologies follows a pattern with three distinct phases rather than a single S-shaped curve has important management implications. The findings indicate that commercializing a breakthrough communication technology is a matter of long endurance. The time from the invention of such a technology up to the point where diffusion of the technology takes off, on average covers about two decades. An implication of this finding is that small companies, which essentially focus on one technology, may be confronted with cash-flow problems during this period. Large companies and governmentally subsidized organizations may be in a better position to survive this period. The findings also indicate that two distinct phases can be distinguished before the diffusion of a product based on a breakthrough technology takes off. The fact that these phases differ from the S-shaped diffusion curve has important managerial implications. Different market actors and factors, and different market mechanisms in each phase require different strategies on behalf of the companies trying to commercialize a breakthrough communication technology.
Product life cycle mechanisms Gradual substitution by new product technologies
Suppose that an invention results from a basic research project in a large company. Such a research and development (R&D) project, which is often mono-disciplinary, is confronted with two intra-company market mechanisms: supply and demand for top researchers and supply and demand for research budgets. The invention in many cases heralds a period of new funds. Instead of continuing the research activities, a switch is required to start up innovation activities. The latter type of activity usually requires multidisciplinary cooperation among various actors outside the R&D department of a company. For smaller companies, a similar switch of activities is required. In the pharmaceutical industry, for example, many small biotechnology research companies look for an alliance with a large company to commercialize an invention or novel drug. After the invention, project members from more disciplines are required to develop the new drug and to organize the required safety trials before the drug is accepted for commercial use. So, after the invention, when the innovation phase begins, a switch is required in the strategy. Similar switches in strategy are required during the transition from the innovation to the market adaptation phase and finally to the market stabilization phase. These findings indicate that it is important to establish the position of the
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technology in the pattern of development and diffusion and that strategies should be tailored to this position. The differences between the market adaptation and market stabilization phase also have important managerial implications. One of these implications is the different scale and approach to production and marketing that is required in the market adaptation and market stabilization phase. When a product is introduced in the market stabilization phase, once a critical mass of users is attained, companies typically try to attain a large market share by striving for large-scale production and marketing. In this scenario, these companies try to establish economies of scale in production and marketing and to attain a dominant position. However, when a product is introduced during the market adaptation phase, the introduction probably marks the beginning of an erratic pattern of introduction, withdrawal and subsequent re-introduction of the technology. In this scenario, a strategy of large-scale production and marketing may have dramatic results for a company. Cooper and Smith (1997) describe an example of a company that built a large, fully-automated plant to produce germanium transistors at the time when silicon transistors became the standard. There is a large risk of betting on the wrong standard when a company starts large-scale production during the market adaptation phase. Rather than striving for scale, in this scenario a company should strive for a quick learning process to establish mainstream applications and dominant product designs in the market and to keep pace with technological developments. A learning strategy requires small-scale and flexible ways of production and marketing, enabling prompt reactions (i.e. new products) to market and technological developments (Sanchez and Sudharshan, 1992; Lynn et al., 1996). Another implication of the differences between the market adaptation and market stabilization phase is that different types of alliances should be sought in each phase. In the market adaptation phase the main concern is to establish a market for a new product category on the basis of a breakthrough technology. In many cases establishing a new market means that an existing market with well-known products, alliances among market actors, and habits among consumers, has to be changed or even replaced by this new market. Therefore, to establish this new market, efforts are united among potential competitors and companies of complementary products and services. An example of this type of cooperation is described by Bijker (1992). The electricity utilities and General Electric, an incandescent light bulb producer, formed an alliance during the 1930s in
the USA. In a united effort, both companies tried to develop the market for electric lightning. However, when the market for electric lightning grew, and different types of lightning were developed (e.g. the fluorescent lamp) the cooperation was stopped since the interests of the light bulb producers, i.e. to develop and sell energy efficient lamps, no longer coincided with the interests of the electric utilities that wanted to supply more electricity. So, during the innovation and market adaptation phase many precompetitive alliances are established in an effort to establish a new market. Yet, when the market is there, the goal is to strive for market share at the expense of direct competitors and previous alliances are often abandoned and replaced by other types of alliances. The erratic pattern of the market adaptation phase has an important managerial implication: it makes it difficult to predict the market potential of products based on breakthrough technologies. Standard market analysis techniques, categorized as consumer analysis, expert analysis and data analysis (Armstrong, 2001; Taschner, 1999) are generally considered to be unreliable for assessing the market potential of major product innovations based on breakthrough technologies (Christensen, 1997; Lynn et al., 1986; Ortt, 1998; Ortt and Schoormans, 1993; Tauber, 1974; Veryzer, 1998). Consumer research requires that potential consumers are willing and able to evaluate (concepts of) the product on the basis of a breakthrough technology. In many cases they are not able to do so since they do not understand the product and its consequences for their daily life. Expert analysis and data analysis have in common that they are based on information from the past that can somehow be extrapolated. In the market adaptation phase especially this is rarely the case. To put it differently: that the market adaptation phase will occur may be predictable to some extent, but how it will occur and what will be the result, is less predictable. Finally two questions remain: (1) Do breakthrough communication technologies always diffuse in the same pattern? (2) When do the findings from this article apply? This article has shown that many breakthrough communication technologies develop and diffuse in a similar pattern. In some cases, the phases of the diffusion process can have quite different lengths, or phases can even be omitted. Once a breakthrough communication technology can be applied in an existing infrastructure and can benefit from prevailing procedures, organizations and so on, it can be hypothesized that the period from invention up to wide-scale diffusion of this
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technology will be relatively short compared to a breakthrough technology that requires new infrastructures, procedures and organizations. While with a technological breakthrough that can build on a previous dominant product design, like the transistor that replaced vacuum tubes in radios, it can be hypothesized that the market adaptation phase will probably be relatively short or non-existent. So, the three-stage pattern is a general pattern in which numerous variations can be expected. The findings in this article particularly apply when the: . technological change represents a technological breakthrough; . technology can be incorporated in multiple product forms, which can be considered major innovations from the perspective of potential consumers; . technology can be applied in multiple market applications; and . diffusion has to cope with considerable externalities, such as a network, in the case of telecommunication appliances. In conclusion, we think that the three-stage process of development and diffusion of breakthrough technologies explains many controversies with regard to diffusion. This process has important managerial implications for companies that want to introduce breakthrough communication technologies in the market.
Notes 1 Garcia and Calantone (2002) define different types of innovations rather than technologies. 2 Some products are adopted by a household, e.g. the first telephones, while other products are adopted by an individual, e.g. the mobile phone. So the “adopter” may refer to different units. The potential market refers to the maximum number of adopters that can reasonably be expected. In some cases the potential market for a product in a country is considerably smaller than the number of individuals or households in that country. That is the case if many of these individuals or households will for some reason never adopt the product. 3 Videotex is an interactive information and shopping service which can be used by connecting a small terminal with the ordinary telephone infrastructure. Videotex was invented around 1973. 4 The difference between invention and innovation is described by several authors (e.g. Dosi, 1982; Mansfield, 1968; Utterback and Brown, 1972; Weiss and Birnbaum, 1989). The basic difference is that an invention is just an idea in some form, a sketch, a model or a kind of prototype, while an innovation is something that is actually marketable. In specific cases the distinction may prove somewhat fuzzy, we therefore decided to combine the activities of invention and innovation in one phase: the innovation phase.
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Olleros, F. (1986), “Emerging industries and the burnout of pioneers”, Journal of Product Innovation Management, Vol. 3 No. 1, pp. 5-18. Ortt, J.R. (1998), “Videotelephony in the consumer market”, PhD dissertation, Technical University Delft, Delft. Ortt, J.R. and Schoormans, J.P.L. (1993), “Consumer research in the development process of a major innovation”, Journal of the Market Research Society, Vol. 35 No. 4, pp. 375-88. Paisley, W. (1985), “Communication in the communication sciences”, in Dervin, B. and Voght, M.J. (Eds), Progress in the Communication Sciences, Vol. 5, Ablex, Norwood, NJ. Rink, D.R. and Swan, J.E. (1979), “Product life cycle research: a literature review”, Journal of Business Research, Vol. 78 September, pp. 219-42. Rogers, E.M. (1983), Diffusion of Innovations, The Free Press, New York, NY. Rogers, E.M. (1986), Communication Technology: The New Media in Society, The Free Press, New York, NY. Sahal, D. (1981), Patterns of Technological Innovation, Addison-Wesley, Reading, MA. Sanchez, R. and Sudharshan, D. (1992), “Real-time market research: learning-by-doing in the development of new products”, Proceedings of the International Product Development Management Conference on New Approaches to Development and Engineering, Brussels, pp. 515-30. Schnaars, S.P. (1989), Megamistakes: Forecasting and the Myth of Rapid Technological Change, The Free Press, New York, NY. Taschner, A. (1999), “Forecasting new telecommunication services at a ‘pre-development’ product stage”, in Loomis, D.G. and Taylor, L.D. (Eds), The Future of the
Telecommunication Industry: Forecasting and Demand Analysis, Kluwer Academic Publishers, Dordrecht, pp. 137-65. Tauber, E.M. (1974), “How market research discourages major innovation”, Business Horizons, Vol. 17, pp. 22-6. Tellis, G.J. and Crawford, C.M. (1981), “An evolutionary approach to product growth theory”, Journal of Marketing, pp. 125-34. Tho¨lke, J.M. (1998), “Product feature management”, PhD dissertation, Technical University Delft, Delft. Toffler, A. (1980), The Third Wave, Bantam Books, New York, NY. Tushman, M.L. and Anderson, P. (1986), “Technological discontinuities and organizational environments”, Administrative Science Quarterly, Vol. 31 No. 3, pp. 439-65. Utterback, J.M. and Brown, J.W. (1972), “Monitoring for technological opportunities”, Business Horizons, Vol. 15, October, pp. 5-15. Veryzer, R.W. (1998), “Key factors affecting customer evaluation of discontinuous new products”, Journal of Product Innovation Management, Vol. 15 No. 2, pp. 136-50. Weiss, A.R. and Birnbaum, P.H. (1989), “Technological infrastructure and the implementation of technological strategies”, Management Science, Vol. 35, 8 August, pp. 1014-26. Wheeler, D.R. and Shelley, C.J. (1987), “Toward more realistic forecasts for high-technology products”, The Journal of Business & Industrial Marketing, Vol. 3, Summer, pp. 55-63. Williams, F., Rice, R.E. and Rogers, E.M. (1988), Research Methods and the New Media, The Free Press, New York, NY.
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Introduction
The development and validation of the organisational innovativeness construct using confirmatory factor analysis Catherine L. Wang and Pervaiz K. Ahmed The authors Catherine L. Wang is Senior Lecturer in International Strategic Management, Oxford Brookes University Business School, Oxford, UK. Pervaiz K. Ahmed is Head, Centre for Enterprise Excellence, University of Wolverhampton Business School, Telford, UK.
Keywords Organizational innovation, Factor analysis
Abstract The role of organisational innovativeness, or innovative capability, in attaining competitive advantage has been widely discussed. Most research examines innovation activities and their associations with organisational characteristics, or investigates certain perspectives of innovative capability, such as product innovation. Much less attention, however, has been paid to develop and validate measurement constructs of organisational innovativeness. Through an extensive literature review, five dimensions of an organisation’s overall innovativeness are identified. These five dimensions form the component factors of the organisational innovativeness construct. Following a three-step approach, a final 20-item measurement construct is validated. Theoretical and methodological issues in relation to application of the organisational innovativeness construct are discussed in light of these findings.
Electronic access The Emerald Research Register for this journal is available at www.emeraldinsight.com/researchregister The current issue and full text archive of this journal is available at www.emeraldinsight.com/1460-1060.htm
European Journal of Innovation Management Volume 7 · Number 4 · 2004 · pp. 303-313 q Emerald Group Publishing Limited · ISSN 1460-1060 DOI 10.1108/14601060410565056
The literature of innovation is long-standing. An organisation’s ability to innovate is recognised as one of the determinant factors for it to survive and succeed (Doyle, 1998; Quinn, 2000). However, there is little empirical evidence in terms of development and validation of organisational innovativeness scales. Authors, such as Miller and Friesen (1983), Capon et al. (1992), Avlonitis et al. (1994), Guimaraes and Langley (1994), Subramanian and Nilakanta (1996), Hurley and Hult (1998), Lyon et al. (2000) and North and Smallbone (2000), address the concern of measuring organisational innovativeness effectively. However, the primary focus of these studies is not scale development. As such, the measures used are often ad hoc and do not conform to systematic procedures for scale development. Second, scales used in the area of innovative capability often adopt a certain perspective, such as product innovativeness (see Song and Parry, 1997; Sethi et al., 2001; Danneels and Kleinschmidt, 2001) instead of overall innovative capability. Product innovativeness emphasises the outcome-oriented innovative capability, but undermines the importance of underlying factors, such as behavioural changes, process innovation and strategic orientation towards innovation. Additionally, a prime interest in the existing literature is to investigate innovation activities and their associations, where adoption of one or more innovations is examined as the dependent variable and linked to attributes of the organisation, the individual respondent, and the innovation itself (Gallivan, 2001). This stream of research views innovation narrowly, often unidimensionally, neglecting multiple facets pertinent to the domain. This has led to confusion in innovation research, either making it difficult to compare findings across studies or leading to biased conclusions (Zaltman et al., 1973; Tushman and Anderson, 1986; Utterback, 1994; Subramanian and Nilakanta, 1996; Cooper, 1998). The above is one of the reasons why the extant innovation literature often does not arrive at consensus over many issues. Reconciling the contradiction and confusion requires a validated measurement scale of an organisation’s overall innovative capability, i.e. the propensity or likelihood that an organisation produces innovative outcomes. The objective of this paper is to develop an organisational innovativeness construct and assess its validity and reliability. Component factors and key variables for the construct are identified through extensive literature review. Confirmatory factor analysis is performed using AMOS 4.0 to check on the
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Development and validation of the organisational innovativeness construct
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Catherine L. Wang and Pervaiz K. Ahmed
Volume 7 · Number 4 · 2004 · 303-313
construct and identify the model fitness. This is conducted by following a three-step process of data pruning, second-order confirmatory factor analysis, and nested models.
Theoretical development of the organisational innovativeness construct Innovation may be present in various forms, such as product or process innovation, radical or incremental innovation, administrative or technological innovation, etc. (Zaltman et al., 1973; Utterback, 1994; Cooper, 1998). The importance of different dimensions is emphasised by authors. For example, Schumpeter (1934) suggests a range of possible innovative alternatives, namely developing new products or services, developing new methods of production, identifying new markets, discovering new sources of supply, and developing new organisational forms. Miller and Friesen (1983) focus on four dimensions: new product or service innovation, methods of production or rendering of services, risk taking by key executives, and seeking unusual and novel solutions. While Capon et al. (1992) adopt three dimensions of organisational innovativeness: market innovativeness, strategic tendency to pioneer, and technological sophistication. From various research, we identify five main areas that determine an organisation’s overall innovativeness. They are product innovativeness, market innovativeness, process innovativeness, behavioural innovativeness, and strategic innovativeness. Research emphasising these different dimensions is briefly summarised in Table I. In line with these perspectives, we define organisational innovativeness as “an organisation’s overall innovative capability of introducing new products to the market, or opening up new markets, through combining strategic orientation with innovative behaviour and process”. Product innovativeness Product innovativeness (Zirger, 1997) has been a major interest (Masaaki and Scott, 1995; Schmidt
and Calantone, 1998), in that it is a critical antecedent to product success (Zirger, 1997; Sethi et al., 2001), which in turn is highly associated to sustainable business success (Henard and Szymanski, 2001). Innovative products present great opportunities for businesses in terms of growth and expansion into new areas. Significant innovations allow companies to establish dominant position in the competitive marketplace, and afford new entrants an opportunity to gain a foothold in the market (Danneels and Kleinschmidt, 2001). Product innovativeness is most often referred to as perceived newness, novelty, originality, or uniqueness of products (Henard and Szymanski, 2001). This perceived newness encompasses two perspectives: from the consumers’ perspective and the firm’s perspective (Atuahene-Gima, 1995; Cooper and de Brentani, 1991; Danneels and Kleinschmidt, 2001). Andrews and Smith (1996) consider appropriateness, the extent to which a new product is viewed as useful or beneficial to some consumers, as an important feature of product innovativeness. There is also a propensity in the literature to incorporate various other perspectives of innovativeness in product innovativeness. For example, Danneels and Kleinschmidt (2001) incorporate two perspectives of product innovativeness: (1) From the customers’ perspective, characteristics such as innovation attributes, adoption risks, and levels of change in established behavioural patterns are regarded as forms of product newness. (2) From the firm’s perspective, environmental familiarity and project-firm fit, and technological and marketing aspects are viewed as dimensions of product innovativeness. In this paper, we define product innovativeness as the novelty and meaningfulness of new products introduced to the market at a timely fashion. This distinguishes product innovativeness from other innovative factors as discussed below. Thus, product innovativeness can be regarded as a salient dimension.
Table I Dimensions of organisational innovativeness Author Schumpeter (1934) Miller and Friesen (1983) Capon et al. (1992) Avlonitis et al. (1994) Subramanian and Nilakanta (1996) Hurley and Hult (1998) Rainey (1999) Lyon et al. (2000) North and Smallbone (2000)
Product
Market
Process
Behaviour
Strategic
£ £
£
£ £
£ £
£ £ £
£ £
£
£ £
£ £
£ £
£
304
£ £
£
Development and validation of the organisational innovativeness construct
European Journal of Innovation Management
Catherine L. Wang and Pervaiz K. Ahmed
Volume 7 · Number 4 · 2004 · 303-313
Market innovativeness Market innovativeness is highly connected to product innovativeness, and often studied as product-market innovativeness (Schumpeter, 1934; Cooper, 1973; Miller, 1983). In fact, Ali et al. (1995) consider innovativeness as a marketbased construct and define innovativeness as the uniqueness or novelty of the product to the market. At a broader level, market innovativeness refers to innovation related to market research, advertising and promotion (Andrews and Smith, 1996), as well as identification of new market opportunities and entry into new markets (Ali et al., 1995). As a component factor separate from product innovativeness, we refer to market innovativeness as the newness of approaches that companies adopt to enter and exploit the targeted market. For some companies, this means that they can enter a market or identify a new market niche and launch products with cutting-edge technological content. An alternative approach would be based on existing products, but with adoption of new marketing programmes to promote the products and services. Under both circumstances, the company is very likely to take up against new competitors either in a new market, or an existing market segment. While product innovativeness maintains a central focus of product newness, market innovativeness emphasises the novelty of marketoriented approaches. Although they are treated as salient factors, product and market innovativeness are inevitably inter-twined.
and management processes. Process innovativeness is imperative in overall innovative capability, in that an organisation’s ability to exploit their resources and capabilities, and most importantly, the ability to recombine and reconfigure its resources and capabilities to meet the requirement of creative production is critical to organisational success.
Process innovativeness Process innovativeness is not often explicitly discussed in the literature. In most studies, process innovativeness is considered as a sub-element of technological innovativeness. For example, Kitchell (1997) considers technological innovativeness is best examined in light of the nature and process of innovation adoption. Avlonitis et al. (1994) consider technological innovation challenges in relation to machinery and production methods as measures for technological innovativeness. In our view, technological innovativeness is embedded in either product innovativeness that embodies the unique, novel technological content in new products, or process innovativeness that exploits new equipments of technological advancement. Hence, technological innovativeness is not considered as a salient factor in this research. Therefore, we use process innovativeness, which captures the introduction of new production methods, new management approaches, and new technology that can be used to improve production
Behavioural innovativeness Behavioural innovativeness can be present at different levels: individuals, teams and management. Measuring behavioural innovativeness of an organisation cannot be accomplished simply by examining occasional innovation events, or innovative characteristics of certain small groups in the organisation. The behavioural dimension should reflect the “sustained behavioural change” of the organisation towards innovations, i.e. behavioural commitment (Avlonitis et al., 1994). Individual innovativeness can be considered as “a normally distributed underlying personality construct, which may be interpreted as a willingness to change” (Hurt et al., 1977). Team innovativeness is the team’s adaptability to change (Lovelace et al., 2001). It is not simply a sum of innovative individuals, but a synergy based on the group dynamics. While managerial innovativeness demonstrates management’s willingness to change, and commitment to encourage new ways of doing things, as well as the willingness to foster new ideas (Rainey, 1999). Behavioural innovativeness demonstrated through individuals, teams and management enables the formation of an innovative culture, the overall internal receptivity to new ideas and innovation. Behavioural innovativeness is a fundamental factor that underlines innovative outcomes. Innovative culture serves as a catalyst of innovations, while lack of it acts as blocker of innovations. Strategic innovativeness Strategic innovation is about “a fundamental reconceptualisation of what the business is all about that, in turn, leads to a dramatically different way of playing the game in an existing business” (Markides, 1998). Strategic innovation takes place when a company identifies gaps in industry positioning, goes after them, and the gaps grow to become the new mass market. In a broad sense, Besanko et al. (1996) define strategic innovation as the development of new competitive strategies that create value for the firm. The primary focus of strategic innovativeness in this paper is to measure an organisation’s ability to manage ambitious organisational objectives, and identify a mismatch
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Catherine L. Wang and Pervaiz K. Ahmed
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of these ambitions and existing resources in order to stretch or leverage limited resources creatively. In many organisations, strategic innovation faces many obstacles. A typical scenario is one in which companies are very successful in their existing markets, and do not feel any urge to change. Under other circumstances, companies have already recognised the need to change, but do not have the capabilities of managing the change, or executives hesitate to take risks due to uncertainty of change (Markides, 1998). Empirical research on strategic innovativeness is very limited. The majority of authors do not consider strategic innovativeness as a component factor of organisational innovativeness, while some others include a single item of strategic innovativeness. For example, Miller and Friesen (1983) view key executives’ risk taking in seizing and exploring chancy growth opportunities as an important criterion of organisational innovativeness. Capon et al. (1992) consider a company’s strategic tendency to pioneer as a dimension of organisational innovativeness. Avlonitis et al. (1994) include manifested strategic innovation intentions in measuring organisational innovativeness. The above five aspects are inter-linked. In particular, product innovativeness and market innovativeness are inter-twined. They are externally-focused and market-based, whereas behaviour and process innovativeness are both internally-focused, and underline the need for product and market innovativeness. While strategic innovativeness highlights an organisation’s ability to identify external opportunities in a timely fashion and match external opportunities with internal capabilities in order to deliver innovative products and explore new markets or market sectors. Product and market innovativeness embodies the process, behavioural, and strategic innovativeness. These five aspects together depict an organisation’s overall innovativeness. We, therefore, propose the following research hypotheses: H1. Though the organisational innovativeness construct is conceptualised as consisting of five distinct components (i.e. behavioural innovativeness, product innovativeness, process innovativeness, market innovativeness, and strategic innovativeness), the covariance among the 29 items can be accounted for by a single factor (i.e. a general organisational innovativeness factor). H2. Covariance among the 29 items can be accounted for by a restricted five-factor model, wherein each factor represents a particular conceptual component of organisational innovativeness and each item
H3.
is reflective only of a single component (i.e. loads only on one factor). The five factors are correlated. Responses to each item are reflective of two factors: a general organisational innovativeness factor and a specific component factor corresponding to one of the five conceptual components. Thus, the covariance among the items can be accounted for by a six-factor model.
Research methodology A total of 29 items were generated from literature (see Table II). A questionnaire was used to collect empirical data. The questionnaire uses a sevenpoint Likert scale, ranging from 1 ¼ strongly disagree, 2 ¼ disagree, 3 ¼ slightly disagree, 4 ¼ neither disagree or agree, 5 ¼ slightly agree, 6 ¼ agree, 7 ¼ strongly agree. A neutral response, “neither disagree or agree”, was adopted to reduce uninformed response, since it assures respondents that they need not feel compelled to answer every questionnaire item (Wilcox, 1994). A sample of 1,500 companies (with no less than 50 employees and a primary trading address within England, Wales, and Scotland) were randomly selected from the FAME Database, and were sent a questionnaire with a cover letter to the company director or senior executive, and a pre-paid return envelope. The initial letter was followed by two reminders. A total of 231 completed questionnaires were received, representing a 15.4 per cent response rate. The rate for the usable responses was 14.2 per cent. To check the non-response bias, the analysis of variance (ANOVA) test was performed to confirm the existence or absence of bias, as suggested by Armstrong and Overton (1977). Respondents were divided into three groups: the first mailing, the first follow-up and the second follow-up. It was assumed that the last group who responded to the second follow-up were most similar to nonrespondents (Armstrong and Overton, 1977). Using the ANOVA test, three groups were compared on all variables. The results revealed that there was no significant difference (at the 5 per cent significance level) between the three groups. Because the group sizes are unequal, the post-hoc Turkey’s b-test using the harmonic means of the group sizes also evidenced that all the variables were homogenous (at the 5 per cent significance level) between three groups. Confirmatory factor analysis is reckoned as a best-known statistical procedure for testing a hypothesised factor structure (Schumacker and
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Table II The organisational innovativeness construct Code
Key variables
Mean
Standard deviation
IN01 IN02 IN03
In new product and service introductions, our company is often first-to-market Our new products and services are often perceived as very novel by customers Our recent new products and services are only minor changes from our previous products and services (R) New products and services in our company often take us up against new competitors In comparison with our competitors, our company has introduced more innovative products and services during the past five years In comparison with our competitors, our company is faster in bringing new products or services into the market In comparison with our competitors, our company has a lower success rate in new products and services launch(R) In comparison with our competitors, our products’ most recent marketing programme is revolutionary in the market Our company’s most recent new product introduction required a new form of advertising and promotion, different from that used for our existing products In new product and service introductions, our company is often at the cutting edge of technology The technology of our main machinery in use is very up-to-date Our future investments in new machinery and equipment are significant compared with our annual turnover In comparison with our competitors, we are late in adoption of technological innovations (R) Our firm’s R&D or product development resources are not adequate to handle the development need of new products and services (R) The nature of the manufacturing process in our company is new compared with that of our main competitors We are constantly improving our business processes Our company changes production methods at a great speed in comparison with our competitors Our future investments in new methods of production are significant compared with our annual turnover During the past five years, our company has developed many new management approaches We get a lot of support from managers if we want to try new ways of doing things Management is very cautious in adopting innovative ideas (R) Key executives of the firm are willing to take risks to seize and explore “chancy” growth opportunities Management actively responds to the adoption of “new ways of doing things” by main competitors Senior executives constantly seek unusual, novel solutions to problems via the use of “idea men” In our company, we tolerate individuals who do things in a different way We are willing to try new ways of doing things and seek unusual, novel solutions We encourage people to think and behave in original and novel ways When we see new ways of doing things, we are last at adopting them (R) When we cannot solve a problem using conventional methods, we improvise on new methods
4.272 4.305 4.042
1.596 1.416 1.509
3.887 4.296
1.583 1.490
–
–
4.554
1.297
3.606
1.323
–
–
3.864
1.739
– –
– –
–
–
3.977
1.615
–
–
5.164 3.906
1.231 1.202
–
–
4.732
1.400
4.531 – 3.883
1.423 – 1.517
–
–
3.648
1.451
4.413 4.455 4.432 4.193 4.742
1.430 1.456 1.511 1.553 1.242
IN04 IN05 IN06 IN07 IN08 IN09 IN10 IN11 IN12 IN13 IN14 IN15 IN16 IN17 IN18 IN19 IN20 IN21 IN22 IN23 IN24 IN25 IN26 IN27 IN28 IN29
Notes: (R) denotes reverse coded item. Items with – under the mean and standard deviation columns are deleted in the respecified model
Lomax, 1996; Byrne, 2001). It is, therefore employed in this research. A total of 213 cases were processed using AMOS 4.0. The Maximum Likelihood (ML) estimation method was employed. A few assumptions need fulfilling in order to use the ML method:
. .
. .
307
reasonable sample size (at least 200 cases); the scale of the observed variables are continuous; the hypothesised model is valid; and the distribution of the observed variables is multivariate normal.
Development and validation of the organisational innovativeness construct
European Journal of Innovation Management
Catherine L. Wang and Pervaiz K. Ahmed
Volume 7 · Number 4 · 2004 · 303-313
The data of this research met the first two criteria. The hypothesised model was developed from theories and some empirical findings, and thus was assumed valid. Finally the normality of the observed variables were tested, following the rules of thumb suggested by West et al. (1995): for a sample size of 200 or less, moderately non-normal data (univariate skewness , 2, univariate kurtosis , 7) are acceptable, i.e. the robust standard errors provides generally accurate estimates. Recent research also shows that ML estimation method can be used for data with minor deviations from normality (Raykov and Widaman, 1995). In our data, the univariate skewness of each variable is , 0.945 in absolute value. The univariate kurtosis of each variable is , 1.171 in absolute value. Thus, the fourth assumption of ML method was also met.
.
.
Data analysis The analysis was conducted following three steps. In the first stage, all 29 items generated were included in the first-order measurement model for organisational innovativeness. The initial model fitness was assessed and subjected to respecification. In the second stage, a second order confirmatory factor analysis was performed based on the respecified model. Finally, nested models were reported to compare the accepted measurement model with other competing models. To produce an over-identified model, the first regression path in each measurement component was fixed at 1. The criteria used to evaluate the items were each item’s error variance estimate; evidence of items needing to cross-load on more than one component factor as indicated by large modification indices; the extent to which items give rise to significant residual covariance; parsimony purpose; regression coefficient of each item; reliability of the item and the reliability of the whole construct. Additionally, the logic and consistency of data with the theoretical framework was considered when evaluating each item. Data pruning and first-order confirmatory analysis The initial model fit indices were x2 ¼ 862:079, x2 =df ¼ 2:349, df ¼ 367, GFI ¼ 0:776, AGFI ¼ 0:734, RMSEA ¼ 0:80, PCLOSE ¼ 0:000, PGFI ¼ 0:654, NFI ¼ 0:731, CFI ¼ 0:823, RMR ¼ 0:158. These indicated that the original model needed to be respecified to fit better with the sample data. The following modifications were made to improve the model: . The initial estimates based on all 29 items showed that item 9 and 15 had poor square
.
.
multiple correlations (0.12 for item 9, and 0.08 for item 15), as well as low regression weights (0.29 for regression of the product factor to item 15, and 0.35 for regression of the market factor to item 9). Both items were thus deleted. By examining the error variances, item 21, 13, 12, 18, and 11 were eliminated. The error variance of item 21 was 1.49, 1.48 for item 13, 2.05 for item 12, 1.18 for item 18, and 1.44 for item 11. Eliminating these items did not affect other items significantly, while the overall goodness-of-fit indices improved. Some items with large error variances were retained, because deleting them would have caused other items to lose effect on the component factors and the overall model fit. Modification indices showed that item 5 and 6 had large error covariance (38.647). Further assessment of the squared multiple correlations and regression weights of both items showed that item 6 had less effect in the construct than item 5. The regression weight for item 6 was 0.74, and 0.78 for item 5; the squared multiple correlation was 0.55 for item 6, and 0.60 for item 5. Item 23 of the behavioural innovativeness factor cross-loaded onto other factors, namely the product factor (MI ¼ 5:467), the market factor (MI ¼ 12:470), and the process factor (MI ¼ 5:198). To avoid cross loading, item 23 was deleted. Item 4 and item 14 had low squared multiple correlations (i.e. 0.18 for both items), and relatively low regression weights (i.e. 0.42 for both). However, removing item 4 would have caused other items to lose their overall effects on the component factor. The same happened to item 14. Removing either or both items would only improve the model fit indices to a very small extent. Additionally, eliminating item 4 would have weakened the reliability value of the market innovativeness component from 0.6848 to 0.6639. Removing item 14 would have also reduced the reliability of the strategic innovativeness factor from 0.6311 to 0.6237. For the above reasons, both item 4 and item 14 were retained in the construct.
Following the above steps, nine items were eliminated in total. The modified first-order confirmatory factor analysis model fit indices are: x2 ¼ 252:453, x2 =df ¼ 1:578, df ¼ 160, GFI ¼ 0:897, AGFI ¼ 0:864, RMSEA ¼ 0:052, PCLOSE ¼ 0:372, PGFI ¼ 0:683, NFI ¼ 0:874, CFI ¼ 0:949, RMR ¼ 0:108. The respecified model fits the sample data better. From Table III, it is easy to see that the regression weights of all variables loading onto their respective factors are
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Catherine L. Wang and Pervaiz K. Ahmed
Volume 7 · Number 4 · 2004 · 303-313
Table III Loadings of the first-order confirmatory factor analysis Variables IN20 IN25 IN26 IN27 Behavioural b IN05 IN01 IN02 IN07 Product c IN16 IN19 IN29 IN17 Process c IN08 IN03 IN10 IN04 Market c IN14 IN22 IN24 IN28 Strategicc
R2 0.41 0.58 0.78 0.83 0.57 0.83 0.74 0.33
Behavioural
Product
Standard first-order loadinga Process Market
Strategic
c
0.64 0.76 0.88 0.91 –
(9.479) (10.563) (10.770)
0.53 0.75c 0.91 0.86 0.57 –
0.76
0.62
0.83
0.66 0.71c 0.54 0.63 0.57 –
0.88
0.70
0.69 0.65c 0.56 0.74 0.42 –
0.74
(13.597) (12.875) (8.270)
0.50 0.29 0.40 0.32 0.42 0.32 0.54 0.18 0.18 0.32 0.34 0.40
(6.812) (7.851) (7.134)
(7.025) (8.705) (5.409)
0.70 0.42c 0.57 0.58 0.63 –
(4.993) (5.045) (5.220)
Notes: a Standard first-order loading is the standard regression weight of the individual variables’ loading on to one of the component factors. Figures in parentheses are critical ratios from the unstandardised solutions; b Standard first-order loading for component factors (i.e. behavioural innovativeness, product innovativeness, process innovativeness, market innovativeness, and strategic innovativeness) is the covariance between any two of these component factors; c The critical ratio is not available, because the regression weight of the first variable of each component factor is fixed at 1; x 2 = 252.453, x 2/df = 1.578, df = 160, GFI = 0.897, RMSEA = 0.052, PCLOSE = 0.372, PGFI = 0.683, NFI = 0.874, CFI = 0.949, RMR = 0.108, AGFI = 0.864
between 0.42 and 0.91, with all critical ratios above 1.96 (which means that all the regressions are statistically significant at the 95 per cent confidence level). Second-order confirmatory factor analysis The purpose of the second-order confirmatory factor analysis is to facilitate testing H1 and H3, as well as for future adoption in structural equation modelling. As shown in Figure 1 and Table IV, all the first-order five factors load very well onto the second-order organisational innovativeness construct. The regression weights are very close and range from 0.77 to 0.89, with all critical ratios above 1.96. The model fit indices show similar results as the first-order confirmatory factor analysis: x2 ¼ 306:036, x2 =df ¼ 1:855, df ¼ 165, GFI ¼ 0:873, RMSEA ¼ 0:63, PCLOSE ¼ 0:025, PGFI ¼ 0:686, NFI ¼ 0:847, CFI ¼ 0:922, RMR ¼ 0:136, AGFI¼0.839. The slight difference in the first-order and secondorder estimations occurs due to the emergence of slightly different degrees of freedom between
executing the first-order and second-order measurement models. The above statistics show that all the 20 items converge into a single organisational innovativeness construct. The 20 items are partitioned into five component factors: behavioural innovativeness, product innovativeness, process innovativeness, market innovativeness, and strategic innovativeness. Each of the 20 items is loaded onto only one of these five factors, without any cross loading.
Nested models The above model was tested against other competing models. Attempts were made to incorporate one general factor plus a number of component factors. From Table V, we can see that Model 5 (one general factor plus five component factors), which is validated in the previous sections, demonstrates a best fit compared to other models. All the model fit indices of Model 5 show improvement from those of other models.
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Catherine L. Wang and Pervaiz K. Ahmed
Volume 7 · Number 4 · 2004 · 303-313
Figure 1 INNOVOR – second-order confirmatory factor analysis
Table IV Loadings of the second-order confirmatory factor analysis
Factors Behavioural innovativeness Product innovativeness Process innovativeness Market innovativeness Strategic innovativeness
R2 0.59 0.68 0.71 0.80 0.79
Standard second-order loadinga Organisational innovativeness 0.77b 0.82 0.84 0.89 0.89
(7.083) (6.761) (6.603) (4.906)
Notes: a Standard second-order loading is the standard regression weight of each of the first-order factors’ loading on to the overall organisational innovativeness construct. Figures in parentheses are critical ratios from the unstandardised solutions; b The critical ratio is not available, because the regression weight of the first component factor (i.e. organisational innovativeness ! behavioural innovativeness) is fixed at 1; x2 = 306.036, x2/df = 1.855, df ¼ 165, GFI ¼ 0:873, RMSEA ¼ 0:63, PCLOSE ¼ 0:025, PGFI ¼ 0:686, NFI ¼ 0:847, CFI ¼ 0:922, RMR ¼ 0:136, AGFI ¼ 0:839
Validity and reliability Efforts were made to maximise the validity and reliability of the organisational innovativeness construct. Techniques used include: . Multi-items were used to construct the measurement. . When available and appropriate, existing measurement items that had been empirically tested were utilised. . New items were built on theories. each item was checked against the relevant content domain for the construct to maximise face and content validity. . Confirmatory factor analysis was employed to verify that each item loads onto one single component factor of the construct without any cross loading onto other component factors. All the five components converge into one general factor – organisational innovativeness. . Our chosen measurement model for organisational innovativeness (Model 5 in
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Catherine L. Wang and Pervaiz K. Ahmed
Volume 7 · Number 4 · 2004 · 303-313
Table V Results of nested model Model
Description
1 2
One general factor One general factor + two component factors One general factor + three component factors One general factor + four component factors One general factor + five component factors One general factor + six component factors
3 4 5 6
x2
df
x2/df
GFI
RMR
RMSEA
PCLOSE
CFI
NFI
1,206.46
324
3.724
0.644
0.190
0.113
0.000
0.672
0.603
916.068
324
2.827
0.743
0.228
0.093
0.000
0.780
0.698
577.918
249
2.321
0.817
0.151
0.079
0.000
0.862
0.783
730.483
320
2.283
0.798
0.152
0.078
0.000
0.847
0.760
306.036
165
1.855
0.873
0.136
0.630
0.025
0.922
0.847
683.246
293
2.332
0.806
0.161
0.079
0.000
0.850
0.767
Note: The above reported are second-order model fit indices
Discussion and conclusion
Table V) was also compared against other models, and proved best fit among all; thus, the convergent validity of the construct is supported. To test the internal consistency reliability, Cronbach’s coefficient alpha test was performed. The item-total correlations are greater than 0.3. The alpha value of each of the five component factors as shown in Table VI are equal to or greater than 0.60, the acceptance level as suggested by Price and Mueller (1986). The overall alpha value of 20 items is 0.9091. The reliability of the organisational innovativeness is supported.
The organisational innovativeness construct developed in this paper takes a step forward towards effectively measuring an organisation’s innovative capability. The significance is primarily three-fold. First, departing from the majority of existing research that focuses on one or two aspects of innovation, the proposed organisational innovativeness construct captures the principal elements of innovative capability, and thus depicts an organisation’s overall ability to product innovative outcomes. Second, the proposed construct incorporates an organisation’s strategic
Table VI Results of the reliability test Components
Items
Item-total correlation (I)
Alpha if item deleted (I)
Alpha of components
Item-total correlation (II)
Alpha if item deleted (II)
Behaviour innovativeness
IN20 IN25 IN26 IN27 IN05 IN01 IN02 IN07 IN16 IN19 IN29 IN17 IN08 IN03 IN10 IN04 IN14 IN22 IN24 IN28
0.5965 0.7177 0.7748 0.8346 0.7081 0.7963 0.7660 0.5503 0.6032 0.4291 0.4733 0.4183 0.5176 0.4351 0.5385 0.3991 0.3280 0.4535 0.4519 0.4177
0.8878 0.8426 0.8197 0.7936 0.8158 0.7765 0.7921 0.8750 0.5491 0.6652 0.6316 0.6642 0.5969 0.6398 0.5706 0.6639 0.6237 0.5308 0.5342 0.5566
0.8736
0.5693 0.5508 0.7317 0.7194 0.6139 0.7183 0.6842 0.5217 0.5784 0.4460 0.5090 0.5054 0.5450 0.4901 0.5968 0.3612 0.3752 0.4901 0.4820 0.5636
0.9043 0.9048 0.9002 0.9004 0.9032 0.9002 0.9015 0.9055 0.9044 0.9073 0.9058 0.9059 0.9050 0.9063 0.9037 0.9099 0.9096 0.9064 0.9065 0.9045
Product innovativeness
Process innovativeness
Market innovativeness
Strategic innovativeness
0.8575
0.6935
0.6848
0.6311
Notes: The scale used is a seven-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree). The “item-total correlation (I)” is the correlation of a particular item and the component factor on to which it loads. The “alpha if item deleted (I)” is the alpha value of the component on to which a particular item loads when this item is deleted. The “item-total correlation (II)” is the correlation of a particular item and the overall construct. The “alpha if item deleted (II)” is the alpha value of the overall construct when a particular item is deleted
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orientation as a prime factor of innovation capability. This essentially means that the construct assesses the potential innovative capability and demonstrates a future orientation. This sets it apart from most of the existing constructs that measure an organisation’s innovation activities from a current and static viewpoint. Another feature of our construct is a demarcation of a general organisational innovativeness factor and five component factors. This gives a thorough assessment of an organisation’s innovative capability. In spite of these contributions, several theoretical and methodological issues regarding application of the measurement construct warrant explication.
component factor was tested and confirmed in the analysis section.
Theoretical issues More explicitly, the advantage of using a comprehensive organisational innovativeness construct over a construct of a certain dimension of innovation can be demonstrated from three aspects. First, organisational innovativeness is represented through certain traits such as newness and novelty etc., and can be easily quantified in terms of to what degree or extent that organisations are innovative, rather than simply dividing them as either innovative or not (Rothwell and Zegveld, 1982). Second, organisational innovativeness, as a trait, can be constructed to cover various key aspects of innovation. It is more likely to build up a multidimensional measurement, which is more reliable for measuring overall innovativeness rather than examining the innovative nature of an organisation through one or two aspects of innovation. Finally, organisational innovativeness measures capabilities of an organisation and indicates the propensity of the organisation to introduce new products to the market, or open up new markets. Measuring overall innovativeness is not only about measuring new product developed or new market opportunities, but also prescribes the underlying elements of innovation outcomes, i.e. behavioural innovativeness, process innovativeness, and strategic innovative orientation. A counter argument would be if an overall measurement for organisational innovativeness is beneficial. Under certain circumstances, a specific dimension of an organisation’s innovative capability perhaps gives a more insightful understanding or statistically more significant findings. For example, the product innovativeness indicates a strong prediction of successful new product development (Zirger, 1997; Sethi et al., 2001). Indeed, our five component factors offer the opportunities to utilise each of them independently. The validity and reliability of each
Methodological issues Strictly speaking, our initial hypotheses were rejected. The hypotheses were revised to discern 20 items instead of 29 items. The five component factors remain the same. The modified three hypotheses were all accepted based on the overall assessment of model fit indices. The respecified measurement model from both first-order and second-order confirmatory analysis demonstrates a good fit with the sample data, as illustrated in Tables III and IV, and Figure 1. The development and validation of scales requires retests and replications in a systematic manner (Churchill, 1979; Gerbing and Anderson, 1988). Our organisational innovativeness construct is the first test and need to be subject to further research. More items may be added to the construct and retested for validation. Additionally, although the convergent validity of the construct is confirmed in this study, the discriminant validity is not part of this research. For future studies when applying this construct, it is worthwhile to test its discriminant validity. Another recommendation would be to test the causal relationships between organisational innovativeness and other organisational parameters. By doing this, predicative validity can be further tested. In conclusion, the objective of this study was to develop a measurement for organisational innovativeness. Although additional work is needed, particularly in the methodological domain, the results reported are promising. The findings provide a basic framework and, combined with the above recommendations, provide a direction for future research.
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Basic propositions for the study of the technological innovation process in the firm Mariano Nieto
The author Mariano Nieto is Professor, Facultad de Ciencias Econo´micas y Empresariales, University of Leon, Leon, Spain.
Keywords Product technology, Innovation, Research, Development
Abstract This paper deals with the characteristics of two basic elements for the study of innovation in the firm: the concept of technological innovation, which is defined as a flow magnitude; and the concept of technology, which is defined as a stock magnitude. The technological innovation process is characterized by: being of a continuous nature; being path dependent; being irreversible and being affected by uncertainty. Technology, as the main product of this innovation, has the properties of knowledge and is characterized by: having a large tacit component; being difficult to transfer; being assimilated by accumulation; and being partially appropriable. These characteristics are articulated in a series of propositions that could contribute to the establishment of a consistent ground for the study of the technological innovation management.
Electronic access The Emerald Research Register for this journal is available at www.emeraldinsight.com/researchregister The current issue and full text archive of this journal is available at www.emeraldinsight.com/1460-1060.htm
European Journal of Innovation Management Volume 7 · Number 4 · 2004 · pp. 314-324 q Emerald Group Publishing Limited · ISSN 1460-1060 DOI 10.1108/14601060410565065
1. Introduction Over the past few years, technological innovation management has become one of the most attractive and promising areas of study in the field of management. This fact is confirmed by the following developments: . an increasing number of scholars have oriented their research towards this area; . each year there are new scientific journals specializing in the study of innovation phenomena (currently, there are more than 50); and . the consolidation of various academic associations, such as IAMOT and PICMET. However, the academia does not yet have a solid theoretical base for the study of innovation management. This deficiency is particularly apparent in the coexistence of radically different methods of approach and the absence of a commonly accepted and precise terminology. This paper puts forward a series of propositions that could contribute to the definition of a consistent basis for the study of the technological innovation process in the firm. To this end, the following section makes some terminological clarifications regarding two key concepts for the study of innovation phenomena: (1) technological innovation, which is defined as a flow magnitude; and (2) technology, which is defined as a stock magnitude. Then, in sections 3 and 4 the main characteristics of these two concepts are identified and discussed. To conclude, section 5 articulates all the propositions.
2. Technology and the technological innovation process The concepts used in the study of innovation phenomena are not usually precisely defined. There is a proliferation of terms and definition that often do not coincide with one another. The absence of a commonly used vocabulary in innovation management studies is such that the terms “innovation” and “technology” are often used interchangeably to signify the same idea. For instance, certain manuals on the study of the technological innovation process in companies refer to the subject matter in the title as “innovation management” (Afuah, 1998; Cozijnsen and Vrakking, 1993; Howells, 2003; Tidd et al., 2001; Tushman and Anderson, 1997). Others, however, prefer to use “technology management” (Betz, 1993; Dussauge et al., 1992;
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Gaynor, 1996; Harrison and Samson, 2001; Horwitch, 1986; Teece, 2003). Still others use both terms as in “management of technology and innovation” (Burgelman et al., 2003; Levy, 1997; Narayanan, 2001; Rastogi, 1996) or “management of technological innovation” (Betz, 1998; Ettlie, 2000; Dogson, 2000; Roberts, 1987; Twiss, 1986). Such terminological inconsistencies could be considered trivial were it not for the fact that there is an important underlying problem behind them: the confusion of two different concepts. The technological innovation process, which is a flow magnitude, is one thing; technology, which is a stock magnitude (see Figure 1) is something else altogether. When the two terms are used interchangeably, no distinction is made between the process of generating and disseminating new technologies (technological innovation process) and the volume of technology available at a given time (technology). In order to clarify these ideas, a few terminological points are made below with regard to these two concepts.
The same terms have been used in management literature, when dealing with the technological innovation process. Recently, however, a change in orientation has taken palace and other concepts are beginning to be used such as: “organizational learning” (Argyris and Scho¨n, 1996), “knowledge creation” (Nonaka and Takeuchi, 1995), “routine creation” (Nelson and Winter, 1982), “asset accumulation” (Dierickx and Cool, 1989), “core competency development” (Henne and Sanchez, 1996) and “dynamic capability development” (Teece et al., 1997). All of these terms describe the flow of the generation of new knowledge within organizations, and therefore refer to phenomena that are analogous to the technological innovation process. In fact, the concepts of learning and knowledge creation are often used to describe the innovation process: “Companies innovate through a constant learning process through which they generate new technological knowledge” (Nonaka and Takeuchi, 1995, p. 3). Furthermore, it has been recognized that the innovation process in companies basically consists of the development of new routines, since “the conversion of an organization’s activity into a routine constitutes the main form of storage of that organization’s specific operational knowledge” (Nelson and Winter, 1982, p. 99). The innovation process has also been associated with the creation of core competencies (Henne and Sanchez, 1996) and with the development of dynamic capabilities (Teece et al., 1997). In light of the above considerations, the innovation process in the firm could be defined as follows: P1. Technological innovation in companies is a learning process through which a flow of new knowledge competencies and capabilities is generated.
2.1. The technological innovation process In this paper, the term “technological innovation” is used to refer to the process through which technological advances are produced. The innovation process includes a set of activities that contribute to increase the capacity to produce new goods and services (product innovations) or to implement new forms of production (process innovations). Therefore, the concept of technological innovation is associated with the idea of a flow – generation, application, dissemination – of technologies. Sociologists, historians and economists usually use other terms interchangeably when talking about the innovation process, such as: technological change, technical progress, technological development or simply innovation. Traditionally, industrial economists break down the process of technological innovation into a sequence consisting of three phases: invention, innovation and diffusion. Furthermore, in a great deal of research, due to the availability of statistical data on research and development (R&D) spending, technological innovation is identified with research (pure and applied) and technological development. Figure 1 The process of technological innovation
2.2. Technology The term “technology” is used to refer to the stock of knowledge -whether codified or tacit-about the set of all industrial techniques available at a given time. It should be kept in mind that technology plays a twofold role in the technological innovation process: it is both the output of the innovation process as well as its principal input (Figure 1). The literature uses different terms to refer to the output of the innovation process, such as innovation[1], discovery, invention, technological knowledge, etc. All of them also signify stock magnitudes. In the field of management, the term “technology” has been used in various senses. An explicit definition of the term is often avoided: “technology is a key competitive factor that needs no definition”. In some cases, restrictive
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definitions have been established – “technology is applied science” – which conceive technology as a body of scientific and technical knowledge that is needed to innovate (Betz, 1993, p. 8; Friar and Horwitch, 1986, p. 144). According to this view, technology lies between scientific knowledge and the productive activities derived from it. Thus understood, the function of technology is limited exclusively to the improvement and/or creation of new processes, products and services. Traditionally, the word “technology” has been used extensively to describe the production process (Woodward, 1965) and even other activities carried out by business. In line with this tradition, today, there is a tendency to establish broad definitions of technology, equating it with the specific way in which a task is carried out in a given organization (Gaynor, 1996, p. 1.7). This conception goes beyond the restrictive idea of technology that associates it exclusively with the results of R&D work. Indeed, technology “in some cases, is a specific process; for example, a chemical process, which produces a specific product. In this case it is difficult to separate the product from the technology. In more general terms, technology can mean a manufacturing process such as continuous iron casting. Here, the technology may be separated from the product. The cash management account is another example of a process that is clearly separable from the product. New data processing technologies have made the implementation of this account possible. We may think of technology in broader terms, looking at it as the way a company has of doing business or carrying out a task” (Foster, 1986, p. 36). This broad view of technology is consistent with the consideration of the innovation process as a learning process, a process for the creation of new knowledge or for the development of new routines. In this way, the concept of technology would be akin to the concepts of knowledge or routine, which are stock magnitudes. Technology can also be seen from the perspective of core competencies and dynamic capabilities. In fact, technology is nothing more than a competency insofar as “a competency can be defined as a unique combination of knowledge and skills that allow the generation of a series of profile innovations” (Chiesa and Barbeschi, 1994, p. 293). The concept of technology can also be associated with dynamic capability since “dynamic capabilities reflect the ability of an organization to obtain new and innovative forms of competitive advantage” (Teece et al., 1997, p. 516). Table I shows the relationships that exist among technological innovation, technology and other stock and flow concepts used in the study of innovation phenomena.
In light of the above considerations, technology at the company level can be defined as follows: P2. Technology is the output and the principal input of the innovation process and reflects the volume of knowledge, competencies and capabilities that the company possesses at a given moment in time.
3. Characteristics of the technological innovation process Some recent works (Shilling, 1998; Teece, 1996) have expressed concern with identifying the characteristics of the technological innovation process. The characteristics they mention are remarkably influenced by research carried out by evolutionary economists (Arthur et al., 1987; David, 1985; Dosi, 1982, 1988; Nelson and Winter, 1982; Rosenberg, 1976) and are consistent with assumptions regarding the nature of the firm by authors using a resource-based view (Barney, 1991; Peteraf, 1993; Wernerfelt, 1984). They agree that the most relevant characteristics of the technological innovation process are being: . of a continuous nature; . path dependent; . irreversible; and . affected by uncertainty. Let us now examine each of these characteristics. 3.1. Continuity The essence of the technological innovation process is the accumulation of knowledge over time. The increase in the volume of knowledge is produced through the different creative mechanisms associated with the different modes of learning such as: . learning derived from R&D activities or “learning before doing” (Pisano, 1997); . “learning by doing”, which arises spontaneously in the production process (Arrow, 1962a); . “learning by using” which arises from observing the different ways in which clients use the company’s products (Rosenberg, 1982); and . “learning by failing” derived from analyzing erroneous decisions made by top managers (Maidique and Zirger, 1985). Such modes of learning, especially the last three, have a clearly incremental character insofar as they generate a continuous flow of new technological knowledge. Traditionally, greater importance has been given to R&D than to other modes of learning.
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Table I Terms used in the study of innovation phenomena Flow magnitudes
Stock magnitudes
Technological innovation process (transformation)
Technology (input/output)
Terms that describe the flow of the generation of new technological knowledge at macro and micro level
Terms that represent the volume of technological knowledge available at a given time at macro and micro level
Macro level: society, economic system, industry Innovation (process) Invention (process) Technological change/technological progress Technical change/technical progress Invention-innovation-diffusion R&D Basic research Applied research Technological development
Innovation (product) Invention (product) Invent Discovery Science Technique
Micro level: firm Learning Knowledge creation Creating routines Asset accumulation Core competencies development Dynamic capabilities development
Knowledge Routine Strategic asset Core competence Dynamic capability Routine
This “has served, in many basic aspects, more to obscure rather than to clarify the technological innovation process” (Rosenberg, 1976, p. 90). Indeed, overestimating the role played by R&D, distorts the way in which the flow of technological knowledge increases and materializes in new products and processes. It has been found that the economic impact of continuous improvement and small incremental innovations is greater than that of certain innovations considered to be radical. In fact, companies dedicate around 80 percent of their innovation efforts to improving existing products and just 20 percent to the development of new ones (Rosenberg, 1996). Some technology historians (Rosenberg, 1982; Basalla, 1988) have pointed to the possibility that most innovations considered to be radical – the railway system, electric lighting, etc. – are just more powerful manifestations of the accumulation of small changes which confer a certain continuous character to the innovation process. Some even come to question the very existence of radical innovations (Basalla, 1988). In general terms, the idea of technological innovation as a continuous process is consistent with other concepts used in the field of management. Continuous improvement (Imai, 1987), technological trees or clusters (GEST, 1986), the knowledge creation spiral (Nonaka and Takeuchi, 1995), strategic management based on the development of core competencies (Prahalad
and Hamel, 1990), etc. are all based on models where the implicit assumption of continuity is present. Based on such considerations, the following proposition can be established regarding the nature of the technological innovation process: P1a. The technological innovation process is essentially continuous in nature.
3.2. Path dependency The assumption that the innovation process is path dependent occupies a central place in the evolutionary approach and reflects the fact that the evolution of a technology depends fundamentally on the path it followed in the past (path dependency). This idea can be outlined in three phases (Arthur, 1989): (1) at any given moment, the choice between two different alternative technologies that serve the same function is influenced by previously made choices; (2) minor historical events that took place at the beginning of the process and the content of the initial choices play an essential role in its future evolution; and (3) previous choices determine not just the next choice, but the possibility that each alternative will be chosen. The technological decisions made now present will condition the subsequent learning process,
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determining the future path of the innovation process (David, 1975, p. 4). In the context of the competition between two technologies that appear at the same time, the content of the initial decisions has a great deal of importance. Thus, different insignificant events, such as the unexpected success of the development of the first prototype, the order in which the technologies reach the market, the whims of early adopters, political circumstances, etc. can cause a given technology to achieve a large enough base to become dominant (Arthur, 1989). The sequence in which such events occur, no matter how insignificant they may be, will affect the dissemination of each alternative technology and will condition its future development. This assumption is implicit in different concepts habitually used in innovation studies. It is usual to reflect the cumulative nature of the innovation process by representing the evolution of technologies through a “technological trajectory” (Dosi, 1982) or “innovation avenue” (Sahal, 1985). These technological trajectories/avenues run within the context of certain “technological paradigms” (Dosi, 1982) or “technological regimes” (Nelson and Winter, 1982). Such technological paradigms/regimes in turn establish “technological guideposts” (Sahal, 1985) or define “dominant designs” (Abernathy and Utterback, 1978) that determine the future development of technologies. In other words, technological paradigms, technological regimes, technological guideposts and dominant designs are similar concepts that reflect the historical factors that determine the future evolution of the innovation process along technological trajectories or avenues, hence the following proposition: P1b. The technological innovation process is path-dependent.
(2) Learning by using (Rosenberg, 1982). When users come into contact with a new technology other forms of use arise that were not initially foreseen and design improvements based on the experience of clients. The potentiality of this mode of learning is especially manifested in high-technology sectors. (3) Network externalities. As a technology is disseminated, externalities usually arise, called network effects, which improve its performance. This phenomenon can take two forms (David, 1987): . direct effects: the mere increase in the number of users of a technology (e.g. e-mail) increases its usefulness for everyone; and . indirect effects: due to improvements in the supply of supplementary services (e.g. DVD). (4) Economies of scale. The diffusion and mass use of a technology allows the mass production of the material elements that form part of such new technology (machines, facilities, components) and thus diminish their unit cost of production. (5) Complementary technologies. The diffusion of a technology induces the development of new techniques of a supplementary nature that ensure the proper functioning and/or improve the performance of the technology in question (Teece, 1987). (6) The flow of information available about the new technology. As a technology is disseminated, a large amount of information is generated, which contributes to the improvement of the knowledge of the technology. The spread of information about a given technological alternative influences the behavior of potential users and can eventually contribute to improve its performance (Hall, 1994, p. 272).
3.3. Irreversibility The development of a technology, in the context of a given technological trajectory, generates new knowledge through a series of feedback mechanisms that contribute to improving its yield. These mechanisms reinforce this dominant technology to the detriment of other alternative technologies with which it competes. There are various types of positive feedback that make the technological innovation process irreversible (Arthur et al., 1987): (1) Learning by doing (Arrow, 1962a). This arises spontaneously from the performance of repetitive tasks in production activities. Learning by doing has different manifestations, some of which have been thoroughly studied, such as the learning effect and the experience effect (Abernathy and Wayne, 1974).
In short, the combined action of these six feedback mechanisms contributes to making the innovation process irreversible. The more a technology is disseminated, the greater the possibility that it will continue to spread in the future. There are increasing advantages for adoption due to learning, network effects, economies of scale and supplementary technologies. Abandoning a technological trajectory means forsaking these advantages. In fact, the evolution of technologies along certain trajectories prevents the old rejected alternative technologies from competing even is their relative pricing structures are significantly different (Teece, 1996). Therefore, the following proposition can be suggested: P1c. The technological innovation process is partially irreversible.
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3.4. Uncertainty The most significant characteristic of the innovation process is the high level of uncertainty that surrounds the performance of all innovative activities. The origins of this uncertainty are very diverse and their effects appear throughout the innovation process. Three modes of uncertainty are identified in the literature: (1) The technical uncertainty that is inextricably linked to R&D activities. This reflects the lack of a priori knowledge regarding what the solution to the technical problem will be or whether it will even be found within the foreseen time frames and costs: What is the best technical solution? Is it feasible? Will it work? The importance traditionally given to this aspect has overshadowed the effect of other, more subtle sources of uncertainty that crop up after the completion of the “technical” phase of the innovation process, when the technology comes into contact with the market. At first blush, it could be thought that the uncertainty decreases radically once the new technology has been brought to market. However, this is not the case. After the company has successfully concluded its R&D project and begins to commercialise a new technology, new uncertainties start to appear, originating from lack of knowledge regarding (Rosenberg, 1996): the possible uses of the technology and the evolution of its technical performance in the future. (2) Uncertainty about possible uses of the technology. When a new technology appears its possible future uses and utility are not apparent. There are hundreds of historical examples that show the inability, at least in retrospect, of the innovators to foresee the uses that their new technologies will have. For example, in 1949 IBM’s legendary president Thomas Watson thought that the potential use of the computer was limited to number crunching in a few scientific research or data processing contexts, rejecting the idea that it could have a potentially wide market. (3) Uncertainty about the future evolution of the technology’s performance. Another source of uncertainty is related to the inability to anticipate future improvements of the technology and its economic consequences (Rosenberg, 1996). Many new technologies, when they appear, have characteristics that do not allow their properties to be immediately appreciated. In general, when they are born they are still imperfect and are in a very primitive form. Their potential uses arise as a result of a long process of incremental
improvements that widen the scope of their practical application. A case in point is the extraordinary evolution of the performance of computers since their appearance in the 1940s. These three modes of uncertainty justify the following proposition: P1d. The technological innovation process is affected by different types of uncertainty. It should be pointed out that efforts to minimize the effects of uncertainty by establishing technological predictions are not very useful because, due to the characteristic of irreversibility, there is no guarantee that the most efficient alternative technology will prevail. Numerous studies (David, 1985; Arthur et al., 1987) have found that the final outcome of the dissemination process, in which various technological alternatives compete, cannot be predicted at the start of the process. It is impossible to determine which technological alternative will prevail. In this context, technological prediction becomes a game of chance.
4. Characteristics of technology Traditionally, due to the neo-classical influence, technological innovation has been considered as a process that generates information from information. Thus technology has been analyzed as an information-intensive good, which possessed the attributes of public goods. Arrow (1962b), in a seminal work, which had a notable influence on subsequent research, pointed out that these particular characteristics of technology caused three types of problems: (1) It is difficult to establish property rights on a technology since the cost of reproducing it – insofar as it consists of information – is practically nil. (2) Technology is subject to indivisibilities and there is no rivalry in its consumption, due to the fact that the act of consuming information is not destructive. (3) The marketing technology poses problems of adverse selection since the fact that technology has the characteristics of information favors opportunistic behavior by agents. These three observations have contributed to reinforce the idea that the market failures caused by the production and marketing of technology are due exclusively to the fact that it is “information”. However, recent studies have substantially modified how the innovation process is viewed, by considering that technology is not free-use good
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like information, but rather that it has a strong learning and accumulated knowledge component. The technological innovation process not only produces “information” but also generates “knowledge” which reverts exclusively to the innovator (Geroski, 1995, p. 93). Thus, various aspects gain special relevance insofar as knowledge can be: (1) codified; (2) transmitted; (3) assimilated; and (4) appropriated.
types of knowledge are integrated in organizational routines that manage the innovation process (Nelson and Winter, 1982; Spender, 1996). It has already been pointed out that companies create new knowledge through different modes of learning (by studying, by using, by doing, and by failing). As the input for this process a wide variety of knowledge is use, with different degrees of codification: explicit (perfectly codified in written rules and bureaucratic procedures) and tacit (which have not been formalized but form part of the company’s culture or know-how). All companies, even high-tech ones, that fundamentally feed off knowledge that is very close to science, and therefore, easily codified, process some kind of tacit knowledge (Dosi, 1988). In general terms, the innovation process seeks to resolve different technological problems that are usually neither well structured, nor perfectly defined. For example if one wants to improve the design of a machine tool in order to reduce its failure rate, one has to discover the physical causes of failure, which can be very diverse. The initially available explicit knowledge does not in itself provide a solution to the problem automatically. Something more is needed. What are needed are other specific capabilities of a tacit nature, such as accumulated experience, intuition or creativity. Therefore, the following proposition can be formulated: P2a. All technology is made up of two types of knowledge, codified (information) and tacit.
These four characteristics are discussed below. 4.1. Tacit dimension The possibility of being codified is undoubtedly the most significant characteristic of knowledge. The codification of knowledge refers to the possibility of a given piece of knowledge to be reduced to information through drawings, formulas, numbers or words. Based on the degree of codification, two categories of knowledge have been defined: explicit[2] and tacit[3]. Explicit knowledge is fully articulated, codified in a precise manner and perfectly decipherable. The main ingredient of explicit knowledge is information and therefore its transmission and accumulation does not entail any great difficulty. The examples of this type of knowledge are extremely varied; however, they can be grouped in to the following four categories (Badaracco, 1991, pp. 17-19): (1) knowledge contained in documents, blueprints or databases; (2) knowledge contained in machinery and production equipment; (3) knowledge contained in certain raw materials, such as chemical and pharmaceutical products, special metal alloys, new materials, etc.; and (4) part of the knowledge contained in the minds of individuals and that can be transmitted easily. The tacit dimension of knowledge is that which cannot be reduced to information and therefore, cannot be codified. Most technological knowledge has a large tacit component and thus cannot be completely transmitted not even by the person who possesses it. All of us know more than we are capable of explaining (Polanyi, 1967, p. 4). The body of tacit knowledge includes all that which one knows how to do, but cannot describe how. This knowledge comes from personal actions and from experience, which is why it is difficult to share with others. The line that divides tacit and explicit knowledge is difficult to establish because both
4.2. Transmission Technological resource markets have imperfections that make it difficult to identify, acquire and assimilate technologies (Teece, 1984). Usually, companies have a hard time identifying the technologies that will provide the most competitive impact and acquiring them in the factor market. This effect, called “causal ambiguity” (Reed and DeFillippi, 1990), hinders the transfer and dissemination of technological knowledge, insofar as it increases the risk that the outcome of the imitation may not be the expected one. These difficulties constitute real barriers that hinder the transmission of technologies, and depend on multiple factors. First, the possibility that a given piece of technological knowledge can be freely transferred (or imitated) and the speed of its dissemination will depend on certain characteristics of the knowledge itself (Rogers, 2003; Winter, 1987; Zander and Kogut, 1995; Grant, 1996) such as the following: . degree of codification; . degree to which it can be taught; . degree of complexity;
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degree of dependence on other knowledge; and degree to which it can be observed.
On the other hand, even if the company is able to identify the relevant technology, it would still have to deal with the problem consisting of the fact that technological knowledge does not have perfect mobility. The transfer of technological knowledge, even if it is perfectly codified, is associated with high transaction costs. Geographic immobility, opportunistic behaviors induced by imperfect information and the idiosyncratic nature of most technological resources are factors that contribute to hinder their transfer (Grant, 2002, p. 179). Because of this, the truth is that technological resources of a strategic nature cannot be bought or lose part of their productivity on being transferred to other companies: P2b. The transmission of technologies is imperfect due to multiple factors such as certain characteristics of knowledge, the existence of causal ambiguity or transaction costs.
4.3. Assimilation As pointed out earlier, technological advances, within each technological trajectory, occur in a continuous manner along a path within the boundaries of each technological paradigm. Innovations come about based on the development and improvement of existing technologies, and advances in technological knowledge occur in a sequential manner, where one phase needs to be mastered before moving on to the next one (Teece, 1996). As a result, companies innovate – they create new products and processes or improve existing ones – obtaining the maximum advantage from their technological potential. First, they try to obtain the knowledge needed to do this based on previously accumulated knowledge (Teece, 1996). This is why the technological innovation process at the company level will have a clearly cumulative nature. Furthermore, it is reasonable to assume that what a company can achieve technologically in the future will depend on what it had been capable of doing in the past (Dosi, 1988). The cumulative nature of technological knowledge can also be seen in the case of companies that decide – and are able to – acquire technology on the technological factor market. In general, companies that lack prior knowledge of a supplementary nature will not have the absorption capacity needed to assimilate quickly new technologies coming from the outside (Cohen and Levinthal, 1990). The development of the supplementary resources needed to assimilate a technology and the learning process itself is
time-consuming. New technologies cannot be instantly adopted, but rather are gradually assimilated. Based on this, the following proposition can be formulated: P2c. The assimilation of a new technology is not instant and depends on the level of technological knowledge previously accumulated by the company, that is to say, its absorption capacity.
4.4. Appropriation The economic literature points out that the benefits generated by innovative activities are not perfectly susceptible to appropriation. Companies encounter difficulties in establishing intellectual property rights over part of its technological knowledge (Geroski, 1995, p. 92). Every technology has two components: a private one, which only the innovating company benefits from, and a public one, which is difficult to appropriate, and which other agents take advantage of (Dosi, 1988). The conditions of appropriability of a technology determine the percentage of each of these components. Certain conditions of appropriability are exogenous, insofar as they depend on factors that the company cannot control such as the characteristics of the knowledge, the institutional framework, the legal system or the structure of the industry. However, other conditions are clearly endogenous, since they depend on the strategies of the company. Companies have different mechanisms for appropriating the results of their innovative activities (Levin et al., 1987; Teece, 1987; Geroski, 1995) such as: . legal protection measures; . secrecy; . exploitation of a technological leadership position; . taking advantage of lag times; and . using complementary assets. These mechanisms are briefly discussed below. Legal protection measures (patents, trademarks, copyright) make it possible to prevent copying by imitators, and also ensure revenues from royalties. However, the effectiveness of these legal measures has been seriously questioned. Levin et al. (1987) pointed out different causes that explain why in most industries patents are not used as protection mechanism against imitators. In many industries, imitators – without running afoul of the law – can copy around the patented technology since it is usually difficult to prove that the imitator has copied anything (e.g. complex electronic systems). Some innovations are very difficult to patent since it is very expensive to prove their novelty (e.g. complex and mature
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technologies). In certain technological trajectories, advances come at such a fast pace that it does not make any sense to patent them (e.g. microelectronics). In other cases innovations are not legally protected because the complexity of the technology makes it nearly as costly, in terms of time and money, as developing the technology (e.g. electronics, aerospace, industrial machinery). This is why it was pointed out that other protection mechanism could be more effective. There are situations in which the information included in the patent limits its effectiveness and the protection mechanism used is usually industrial secrecy (e.g. Coca Cola, petrochemical processes). In general, actions aimed at exploiting a position of technological leadership through heavy investment in marketing and customer service have demonstrated their effectiveness in certain industries such the semiconductor industry. On the other hand, the time lag or temporal advantage of the innovator could be an effective protection mechanism against imitators. If the innovator continues to accumulate knowledge and to innovate continuously, it will manage to keep a technological lead over potential imitators. Another factor that could affect appropriability is related to the fact that, in order to exploit a technology, it is necessary to have certain supplementary resources of a co-specialized nature (Teece, 1987). These resources affect the conditions of appropriation insofar as the imitator also needs to gain access to such resources. In these cases the innovator can appropriate the benefits by establishing agreements and controlling the suppliers: P2d. The profits generated by a technology are not perfectly appropriable, but rather depend of the effectiveness of the protection mechanisms used by the firms.
(2) The innovation process is path dependent. At any given moment, decisions regarding the adoption of a certain technology are conditioned by a whole sequence of decisions made in the past. Minor events that occurred at the beginning of the process have a great deal of importance and condition its future evolution. (3) The innovation process is partially irreversible and this strong resistance to the abandonment of a technological trajectory. This is due to a series of positive feedback mechanisms such as: . learning by doing; . learning by using; . network effects; . complementary technologies; . economies of scale; and . the dissemination of information about the new technology. (4) The technological innovation process is affected by different types of uncertainty such as: . technical uncertainty; . uncertainty about the possible uses of the technology; and . uncertainty regarding the evolution of its performance.
5. Conclusions This paper has analyzed two key elements for the study of corporate technological innovation management: the concept of technological innovation and the concept of technology. The concept of technological innovation is used to describe the learning process through which the company generates a flow of new technological knowledge, competencies and capabilities based on inputs that are also knowledge-intensive. This is a dynamic process that has the following characteristics: (1) The innovation process is of an essentially continuous nature, insofar as most innovations originate from small incremental improvements.
The concept of technology reflects the stock of knowledge, competencies and capacities that a company has at a given moment in time. Technology is the output and the main input of the innovation process and has the following characteristics: . All technology is made up of two kinds of knowledge: codified (information) and tacit. . The transmission of technology is imperfect due to certain characteristics of knowledge, causal ambiguity, and the existence of transaction costs. . The assimilation of a new technology is not instantaneous and will depend on the level of technological knowledge previously accumulated by the company, that is to say, its absorption capacity. . The benefits generated by a technology are not perfectly appropriable but rather depend on the effectiveness of the protection mechanisms used by the company. These propositions regarding the characteristics of the technological innovation process and technology are consistent with the assumptions established by evolutionary economics and the resource-based approach. They present a dynamic vision that better reflects the historical and temporal nature of the technological innovation process. Based on this foundation, models can be
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built to analyze the technological innovation process in firms and improve the theoretical basis of technological strategy design.
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Notes 1 Note that it is common to use the term innovation to signify both the result (product) of the technological innovation process, and the entire technological process as a whole or just one of the phases in the inventioninnovation-diffusion sequence. 2 Different terms have been used in the literature to refer to explicit knowledge: “articulable” (Winter, 1987, p. 170; Nelson and Winter, 1982, p. 77), “codificability” (Zander and Kogut, 1995, p. 79), “migratory” (Badaracco, 1991, p. 16), “information” (Kogut and Zander, 1992, p. 386), “specific” (Dosi, 1988, p. 1131) and, of course, “explicit” (Grant, 1996, p. 111; Nonaka and Takeuchi, 1995, p. 9; Polanyi, 1962; Spender, 1996, p. 52). 3 The terms “know-how” (Kogut and Zander, 1992, p. 386) and “embedded knowledge” (Badaracco, 1991, p. 53) have been used to refer to tacit information.
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Mariano Nieto
Volume 7 · Number 4 · 2004 · 314-324
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