The present study integrates a number of independent streams of research on the antecedents of creativity and innovation to develop and test a model of individual innovative behavior. The model posits that leadership -- leader-member exchange, charisma, and leader role expectations -- and individual problem-solving style effect innovative behavior directly and indirectly through their influence on perceptions of the climate for innovation. The direct effect of prior innovative history was also tested. Structural equation modeling was used to test the fit of the proposed model to the data. The results showed that the model provided a good fit and explained almost 50 percent of the variance in innovative behavior. Implications for practice and suggestions for further research are discussed.

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This research was funded in part by grants from the University of Cincinnati Research Council. The ideas and opinions expressed in this article are not those of the funding source.

The central role of innovation in the long-term survival of organizations (Ancona & Caldwell, 1987; Ouchi, 1981; Peters & Waterman, 1982) provokes continuing interest among social scientists and practitioners alike. Since the foundation of innovation is ideas, and it is people who "...develop, carry, react to, and modify ideas" (Van de Ven, 1986, p. 592), the study of what motivates or enables individual innovative behavior is critical. Previously, innovative behavior was considered "extra-role", or behavior beyond the job description of many organizational members (Katz, 1964). Today, modern organizations are trying to promote innovative behavior among all employees (cf. Fortune, 1991) as they attempt to deal with increasingly turbulent and complex environments. As a result, unstructured problem-solving requiring novel ideas is becoming common throughout many organizations (Manz & Sims, 1984; Walton, 1985).

Given these conditions, the study of individual innovative behavior is perhaps more pressing today than at any time in the past. However, West and Farr (1989) have noted that "there has been scant attention paid to innovation at the individual and group levels" (p.17). The present research was designed to help fill this gap by using a social interactionist approach to explore how leadership and individual characteristics affect individual innovative behavior directly and indirectly through perceptions of the climate for innovation.

Van de Ven (1986) noted that one of the central problems in the management of innovation is the management of attention. Managing attention is difficult because individuals gradually adapt to the environment such that their awareness of need deteriorates and their action thresholds reach a level where only crisis can stimulate action. The challenge for managers is getting people to pay attention to the creation of new ideas instead of to the protection of existing practices. A number of theorists have suggested that climate may act as a pressure for channeling and directing both attention and activities toward innovation (e.g., Amabile, 1988; Isaksen, 1987; Kanter, 1988). However, empirical research on the effects of climate on individual innovative behavior is meager.

The purpose of the present study was to integrate a number of independent streams of research on the antecedents of creativity and innovation and to develop and test a model of individual innovative behavior. The study setting was a research and development (R&D) department of a large industrial organization. Because the central tasks of R&D traditionally have involved unstructured problem-solving, the study of R&D professionals may have substantial relevance for promoting innovation among all organizational participants.

In the model tested here (see Figure 1), individual innovative behavior is viewed as the outcome of three interacting systems -- the individual, leadership, and the climate for innovation. Here, climate represents the signals individuals receive relative to organizational expectations regarding innovation (Kanter, 1988), and leadership has often been posited as an important influence on both climate formation (e.g., Litwin & Stringer, 1968; McGregor, 1960) and innovation (Kanter, 1983; Peters & Waterman, 1982).

There are numerous theoretical approaches to leadership in the literature (Yukl, 1989), and the effect of different operationalizations of the construct on criteria of interest has seldom been examined. Thus, multiple measures of leadership were used in the current study. Two contemporary leadership perspectives -- leader-member exchange (LMX) theory (Dansereau, Graen, & Haga, 1975; Graen & Scandura, 1987) and the charismatic leader behavior approach (Bass, 1985; Conger & Kanungo, 1987) -- were used here as both have been tied previously to innovation in the literature. The effect of the leader's role expectations for subordinates on innovative behavior was also investigated, because the Pygmalion Effect (Livingston, 1969) is well accepted but seldom tested.

Climate was conceptualized here as an intervening variable between organizational context factors and individual behavior (Field & Abelson, 1982; Schneider & Reichers, 1983). Climate is not descriptive in nature but interpretive as it represents an individual's interpretation of the situation based on its meaning to him or her (James & Sells, 1981). Psychological studies of meaning (e.g., Osgood, Suci, & Tannenbaum, 1957) clearly demonstrate that individual differences shape individual interpretations of situations. Whether individual differences which are predictive of innovative behavior are also influential in determining perceptions of the climate for innovation is an open question. The model tested here posits that individual problem-solving style affects innovative behavior directly and indirectly through perceptions of the climate for innovation.

In the following sections, the theoretical rationale for each of the linkages in the proposed model is presented.

Climate and Innovative Behavior

Schneider (1975) suggested there are many types of climates and that the use of generic climate dimensions is not useful for understanding the specific phenomena under study. Rather, climate is a multidimensional perceptual domain and construct definition must be relevant to the specific criteria of interest. This study was concerned with the climate for innovation, and more specifically, with two dimensions of innovative climate often cited in the creativity and innovation literature: (1) support for innovation (e.g., Kanter, 1988; Siegel & Kaemmerer, 1978), and (2) resource supply (e.g., Amabile, 1988; Pelz & Andrews, 1966).

Empirical support for climate's effects on creativity and innovation has been offered in studies at both the organizational and subunit level (Abbey & Dickson, 1983; Ekvall & Tangeberg-Andersson, 1986; Paolillo & Brown, 1978; Siegel & Kaemmerer, 1978). However, empirical study of climate's effects on individual innovative behavior has been limited.

At the individual level, climate represents a cognitive interpretation of the organizational situation and has been labeled psychological climate (PC) thus differentiating it from the aggregated, consensual perceptions at the organizational level (James, James, & Ashe, 1990). PC theory posits that individuals respond primarily to cognitive representations of environments "rather than to the environments per se" (James & Sells, 1981). Climate represents signals individuals receive relative to organizational expectations of behavior and potential outcomes of behavior. Individuals respond to these expectations through self-regulation of behavior in order to realize positive self-evaluative consequences (e.g., self-satisfaction and self-pride) (Bandura, 1988). Individuals also use this cognitively processed situational information to formulate expectancies and instrumentalities (James, Hartman, Stebbins, & Jones, 1977). Thus, organizational expectations, as perceived and interpreted by the individual, influence behavior through self-regulatory mechanisms and act as a pressure for directing and channeling individual activity (Pritchard & Karasick, 1973). Individuals who perceive that the organization expects, sponsors, and supports innovation respond with innovative behavior for both intrinsic reasons -- self-satisfaction -- and because outcome expectancies are increased.

Thus, the PC for innovation was posited to have a direct, positive relationship with individual innovative behavior. More specifically, it was hypothesized that individuals who perceived greater support for innovation and greater resource supply would exhibit more innovative behavior.

Leadership and Innovative Behavior

Numerous writers have implicated leadership as critical in the innovation process, but for the most part, such accounts have focused on the need for participative or collaborative leader styles (Kanter, 1983; Peters & Waterman, 1982) or have provided lists of specific activities that leaders should engage in to allow creativity to emerge (e.g., Amabile, 1988). Theoretical development in this arena is still sparse as traditional leadership approaches are more relevant to the explanation and prediction of productivity outcomes than to innovation outcomes (Waldman & Bass, 1991). The three approaches to leadership used in this study are reviewed below.

Leader-member exchange (LMX) theory. LMX theory specifically suggests that the quality of the relationship between supervisor and subordinate is related to innovativeness (Graen & Scandura, 1987). In essence, LMX theory posits that supervisor and subordinate engage in a role development process during which understandings are arrived at regarding the amount of decision latitude, influence, and autonomy the subordinate will be allowed (Graen & Cashman, 1975). Over time, some leader-subordinate relationships develop from interactions that are formal and impersonal (low LMX) to "mature" interactions characterized by trust, mutual liking, and respect (high LMX). In high LMX relationships subordinates are allowed greater autonomy and decision latitude, both of which have been shown to be essential to innovative behavior (Cotgrove & Box, 1970; Pelz & Andrews, 1966) Two recent studies (Basu, 1991; Scott & Bruce, 1992) support a positive direct relationship between LMX and innovative behavior. In the present study, we hypothesized that a positive and direct relationship between LMX and innovative behavior would again emerge.

In this study, LMX was also hypothesized to influence innovative behavior indirectly through its influence on the formation of climate perceptions. Contemporary theorists focus on cognitive sense-making to describe the formation of PC and give primary emphasis to the social influence processes which affect the sense-making process (Ashforth, 1985; Glick, 1985, 1988; Schneider, 1983). Central to this approach is the notion that proximal others -- those in close psychological proximity to the focal individual (e.g., co-workers and the leader) -- are likely to have a strong influence on individuals' perceptions of PC (Lewin, 1938). Indeed, the leader has been suggested to be a "key filter" in the interpretations subordinates make regarding organizational features (Kozlowski & Doherty, 1989).

In a recent integration of LMX theory and the extant climate literature, Kozlowski and Doherty (1989) argued that because the supervisor is the most salient representative of management actions, policies, and procedures, subordinates tend to generalize their perceptions of the supervisor to the organization at large. Thus, subordinates negotiating a high quality relationship with their supervisor will perceive the organization as providing greater autonomy, greater decision-making latitude, and greater supportiveness overall than will subordinates with low quality relationships with the supervisor. Empirical support for a positive relationship between LMX and climate perceptions has been reported in several studies (Kozlowski & Doherty, 1989; Dunegan, Tierney, & Duchon, in press).

The present study tested the relationship between LMX and perceptions of the climate for innovation. Kanter (1983) suggested that dimensions of organizations which encourage innovation include broad, nonroutine, and challenging job assignments; an organizational orientation toward achievement; and recognition for individual excellence. LMX theory suggests that the subordinate's perception of these qualities are a direct result of the quality of the relationship developed between supervisor and subordinate. Therefore, we hypothesized that there would be a direct and positive relationship between the quality of the relationship between supervisors and subordinates (i.e., LMX) and subordinates' perceptions of both support for innovation and resource supply.

Leader role expectations. Leaders may be constrained from granting high levels of autonomy and discretion to subordinates. The organization may enforce rigid role definitions that do not allow such action, or the leader may have inflexible expectations for specific roles within his or her domain (Graen & Scandura, 1987). Indeed, the expectations that supervisors have for their subordinates have been suggested to directly shape the behavior of subordinates (Livingston, 1969). Supervisors are important "role senders", and they exert pressure on subordinates to conform to their beliefs about the appropriate way to behave (Kahn, Wolfe, Quinn, & Snoek, 1964). Thus, the degree to which subordinates are innovative may be due partly to the degree to which their leaders expect them to be innovative. We, therefore, hypothesized that the degree to which a supervisor holds expectations for a subordinate to be innovative would be positively and directly related to the level of innovative behavior demonstrated by the subordinate.

Charisma. Leader charisma has recently received substantial attention in the leadership literature (e.g., Bass, 1985; Conger & Kanungo, 1987). House, Woycke, and Fodor (1988) suggested that the behaviors of charismatic leaders include articulating a mission or vision, demonstrating a high degree of self-confidence, communicating high performance expectations of followers and confidence in followers' abilities to meet such expectations, and showing individualized consideration for followers. Conger and Kanungo (1987) described the charismatic leader as one who has an idealized vision that contrasts with the status quo, tries to change the status quo using unconventional means, openly shares his or her vision with others, and transforms people to share the radical changes advocated. The charismatic leader, from these descriptions, clearly acts as a change agent within his or her organization.

Howell and Higgins (1990) demonstrated that charismatic leader behaviors collectively distinguish idea champions from non-champions. A champion is a person who makes "a decisive contribution to the innovation by actively and enthusiastically promoting its progress through the critical organizational stages" (Achilladelis, Jervis, & Robertson, 1971). Supervisors who are idea champions encourage idea creation, and sponsor subordinates' ideas throughout the innovation process. We expect that these behaviors will positively influence subordinates expectancies and instrumentalities, and thus, we infer that subordinates will be motivated to innovate under a charismatic leader. Therefore, we hypothesized a positive and direct relationship between charisma and innovative behavior.

Since subordinates generalize leader behavior as being representative of the organization (Kozlowski & Doherty, 1989), perceptions of the supervisor as charismatic -- as being a change agent and as an active sponsor for their ideas -- are likely to result in perceptions of the organization as being supportive of change and innovation. Thus, it was hypothesized that there would be a positive direct relationship between the degree to which subordinates perceived their leader as charismatic and subordinates' perceptions of support for innovation and resource supply.

Problem-Solving Style and Innovative Behavior

Since innovation involves an active search for and generation of ideas, there are a number of potential cognitive characteristics which are likely to affect innovative behavior just as they affect creativity (Barron & Harrington, 1981). Recently, there has been increased attention given to specific dimensions of cognitive style as antecedents of innovative behavior (e.g., Kirton, 1976; Jabri, 1991).

Kirton proposed that individuals characteristically produce qualitatively different solutions to seemingly similar problems, and that individuals can be located on a continuum ranging from an ability to do things "better" to an ability to do things "differently". He labeled the ends of the continuum adaptive and innovative, respectively. Drawing on Koestler's work (1964) on associative/bisociative thinking, Jabri (1991) proposed that two independent modes of problem solving exist. Associative thinking is based on habit or the following of set routines, and this mode represents a conforming or conventional problem-solving style. Bisociative thinking, in contrast, is characterized by the overlapping of separate domains of thought simultaneously, and this mode represents a non-conventional or creative problem-solving style. The creative problem solver has a propensity to process information from different paradigms simultaneously, and, therefore, is more likely to generate novel problem solutions (Isaksen, 1987). Thus, it was hypothesized that creative problem-solving style would be positively and directly related to innovative behavior, and conventional problem-solving style would be negatively and directly related to innovative behavior.

We also suggest that problem-solving style is related indirectly to innovative behavior through its effect on climate perceptions. Although most climate research has treated differences in work group members' climate perceptions as error variance (James, Hater, Gent, & Bruni, 1978), others have continued to argue the importance of individual personalities, values, and cognitive characteristics (e.g., James et al., 1990). This study tested the effect of problem-solving style on perceptions of the climate for innovation.

James et al. (1990) argued that climate entails not only a perceptual process but also an evaluative one. Individual interpretations of environmental phenomena are made with reference to personal values. Personal values are "that which a person wants or seeks to obtain..." because it is "that which one regards as conducive to ones' welfare" (Locke, 1976, p.1304). Valuation, therefore, is made against an internal standard of what is beneficial to one's welfare, and PC perceptions are the result of this valuation (James & Sells, 1981; Jones & James, 1979). Internal standards of what is beneficial to one's welfare (what one values in the workplace) are the result of prior experiences relative to self-concept, one's own competencies and needs, and the environment.

For example, individuals who see themselves as creative are likely to value environments that are highly supportive of creativity because prior experience suggests that such environments will assist them in meeting their needs to engage in creative activity. An environment that supports creativity is relatively more salient for creative individuals, therefore, than it is for individuals who do not see themselves as creative. The question becomes what effect does this increasing salience have on individual interpretations of environmental stimuli?

Two recent studies addressed the relationship between individuals' cognitions and their perceptions of PC. Eiter (1991) demonstrated that individual characteristics were related to perceptions of organizational climate. Individuals who scored high on a risk-taking measure were likely to see their organizations as less encouraging of initiative, less responsive to new opportunities, and to have less challenging goals than low risk takers. In a second study, Isaksen and Kaufmann (1990) found that those with an innovative problem-solving style perceived less challenge in their organizational environment than those with an adaptive problem-solving style. Thus, it seems that creative problem solvers evaluate dimensions of innovative climate against higher standards than do less creative problem-solvers.

Drawing on these findings, we hypothesized that creative problem-solving style would be negatively related to perceptions of support for innovation and resource supply. Conversely, we hypothesized that conventional problem-solving style would be positively related to perceptions of the support for innovation and resource supply.

Finally, it has long been accepted in the psychological literature that the best predictor of future behavior is past behavior. Thus, an individual's prior history of innovative activity was hypothesized to have a direct effect on individual innovative behavior.

Sample and Procedure

The sample used in this study included all engineers, scientists, and technicians employed in a large central R&D facility of a major U.S. industrial corporation. Initially, the directors and vice-president of the R&D center were interviewed to develop an understanding of how innovation was viewed in the organization and to determine what specific behaviors were seen as critical to innovation. Semi-structured interviews were then conducted with a stratified sample (N=22) of the R&D engineers, scientists, and technicians to gain an understanding of how innovation was viewed by the employees and to determine what organizational factors might play a part in the innovative process. This information was used to offer some assurance that the climate measure being used in the study was relevant in this setting and to identify factors that were important in measuring innovative behavior.

Questionnaires were administered via company mail to study participants, and they completed them during normal working hours. Participation was voluntary and confidentiality of responses was assured. Upon completion, participants mailed their responses to the researchers. The response rate to questionnaire administration was 85 percent. The sample consisted of 125 engineers and scientists, and 64 technicians. The average age was 41.6 years and average tenure in the R&D organization was 14.8 years. The sample was 93 percent male. Further, 63.8 percent of the sample had at least a baccalaureate degree and 39.2 percent of the sample had post-graduate degrees.

In addition, a separate questionnaire was administered to all 26 managers. These managers rated each of their subordinates on the criterion variables, and they completed an item that assessed their own expectations regarding the role of each subordinate (see measures below).

Measures

Innovative behavior was measured by a six-item scale developed specifically for this study. The scale was completed by each manager for each of their subordinates. Managers rated each subordinate on the degree to which the subordinate: (1) searches out new technologies, processes, techniques, and/or product ideas; (2) generates creative ideas; (3) promotes and champions ideas to others; (4) investigates and secures funds needed to implement new ideas; (5) develops adequate plans and schedules for the implementation of new ideas; and (6) is innovative, in general. Responses were made on a five-point Likert scale ranging from not at all to to an exceptional degree. Cronbach's alpha for this scale was .89.

Problem-solving style was operationalized using the two subscales of Jabri's (1991) associative/bisociative index. Since Jabri originally postulated that the two subscales were independent, they were treated as separate variables in this study. Conventional problem-solving style was operationalized using the 10-item associative scale, and creative problem-solving style was operationalized using the 9-item bisociative scale. Individuals were asked to indicate the extent to which they were likely to enjoy a list of specific activities such as "linking ideas which stem from more than one area of investigation" (creative) and "being methodical and consistent in the way I tackle problems" (conventional). The response format was a seven-point Likert scale ranging from likely to enjoy to unlikely to enjoy. All responses were reverse coded so a high score on the associative scale indicated a preference for conventional problem solving, and a high score on the bisociative scale indicated a preference for creative problem solving. Cronbach's alphas for the two scales were .83 and .88, respectively.

LMX was measured using the 14-item scale developed by Graen, Novak and Sommerkamp (1982). A standard five-point Likert response format was used for all items ranging from strongly disagree to strongly agree. The scale measures the quality of the relationship between manager and subordinate and a sample item is "My manager is investing a great deal in my career." Cronbach's alpha for this sample was .90.

The role expectations of the leader were measured by a single item which read "Not all work roles require individuals to be innovative. In fact, it could be argued that effective work groups have a blend of innovative individuals and individuals whose role it is to support the innovation of others. In this context, the role is a set of expectations of the position independent of the person holding the position. Indicate the degree to which you would describe the role for each of your subordinates as being either an innovator or being a supporter of innovation." The supervisors rated each subordinate using a five-point Likert scale ranging from role requires an innovator to role requires a supporter. The item was reversed scored so that a high score indicated an innovative role and a low score a supportive role.

Charisma was measured by nine items as adapted by Basu (1991) from Bass' (1985) work on transformational leadership. The response format for the scale was a five-point Likert scale ranging from strongly disagree to strongly agree. Sample items from the scale include "My manager inspires loyalty to the organization" and "My manager has a sense of mission which he or she transmits to me". Cronbach's alpha in this sample was .93.

The innovative climate measure contained 22 items and was a modification of the innovative climate measure developed by Siegel and Kaemmerer (1978). The original measure contained three subscales -- support for creativity, tolerance of differences, and personal commitment. The personal commitment subscale was not used in this study. The published factor structure of the support for creativity and the tolerance of differences subscales was examined, and items relating specifically to supervisors were not used in order to minimize conceptual overlap with the LMX and charisma measures, thus reducing method variance due to common source and response format. The content of the remaining items was examined to assess how well they represented dimensions suggested to be important to innovative performance during the interviews at the facility. Fourteen items were selected for use. Finally, an additional eight items were written to tap two dimensions of innovative climate that have been mentioned frequently in the literature and in interviews at the research site -- rewards and resources -- but were not included in the Siegel and Kaemmerer measure. The response scale for the final 22-item measure was a five-point Likert scale ranging from strongly disagree to strongly agree.

After the data were gathered, a factor analysis using principle components extraction and varimax rotation was conducted. The results are in the appendix. Factor 1 (16 items) was named support for innovation and Factor 2 (6 items) was named resource supply. These factors were treated as separate dimensions of climate for innovation in the analysis of the model. Cronbach's alpha for the support for innovation subscale was .92; for the resource supply subscale it was .77.

The measure of prior innovative behavior used in this study was the total number of invention disclosures filed during the individual's organizational tenure divided by his or her organizational tenure in years. The counts of invention disclosures were obtained from the organization's archives. This measure was particularly useful in this study as it provided a validity check on the supervisory rating of innovative behavior. Although the supervisors' ratings assessed a broader set of behaviors than those represented by the formal invention disclosure system, it was expected that invention disclosures represented one of the criteria supervisors use in their assessment. Therefore, we expected to see a moderate relationship between this archival measure and the criterion.

Correlations

Table 1 presents the summary statistics, zero-order correlations, and covariances among the constructs. As can be seen, the variables most highly related to innovative behavior were leader role expectations (r = .36, p < .001), conventional problem-solving style (r = -.35, p < .001), and prior innovative behavior (r = .37, p < .001). Managers who believed a role required an innovator also rated role incumbents as innovators. The high correlation could be due in part to mono-method bias. However, individuals who reported a conventional problem-solving style were less likely to be assessed as innovative by their managers. Furthermore, prior innovative behavior was significantly correlated with managers' assessments of subordinates' innovative behavior. These last two findings obviate the mono-method bias problem and provide some validation to the supervisory rating of innovative behavior that was used here.

Interestingly, the two leadership measures included in the present study appeared to be differentially related to innovative behavior. While LMX was significantly related to innovative behavior (r = .19, p < .01), charisma showed no significant relationship (r = .03, n.s.). This is interesting given that LMX and charisma are highly related to each other (r = .78, p < .001).

Analytic Strategy for Assessing the Overall Model

The analytic strategy used LISREL VI (Jöreskog & Sörbom, 1986) to assess the goodness-of-fit of the overall hypothesized model -- something that a regression model would be unable to do. Further, LISREL VI has the power to separate questions of measurement from questions about the relationships among the latent constructs under study. However, an important requirement of maximum likelihood is that observed variables not deviate far from normality. Conditions that violate this assumption lead to increased errors in estimated standard errors and to erroneous c2 statistics (Bentler & Chou, 1987). One way to improve this situation is through the use of composite measures. Thus, in the present study, each latent construct is indicated by only one manifest variable (either a single variable or a composite measure).

Unlike many studies that use only single indicators of latent variables (cf. Fornell, 1983), perfect measurement of each variable (or scale) was not assumed. Instead, the diagonal entries in the l matrix (i.e., loadings from indicator to latent construct) were calculated as the square root of the coefficient alpha internal consistency estimate for each manifest scale and the error terms (i.e., estimate of random measurement error) were fixed to equal one minus coefficient alpha. This approach draws more traditional methods of assessing reliability into the structural equation modeling arena and follows the procedures recommended by Kenny (1979), James, Mulaik, and Brett (1982), and Williams and Hazer (1986). Netemeyer, Johnston, and Burton (1990) recently demonstrated that this approach (i.e., the combination of indicator variables into composite scales) led to path estimates that were virtually identical to those estimates generated by using multiple single variable indicators.

Evaluating the Hypothesized Model

Initial examination of the hypothesized model indicated that the data fit the model quite well (c2 = 2.69, df = 10, p = .991). Because of drawbacks to the c2 goodness-of-fit measure (e.g., sensitivity to sample size and departures from normality), researchers (e.g., Anderson & Gerbing, 1984; Bentler & Bonett, 1980; Fornell, 1983; James, Mulaik, & Brett, 1982) have suggested alternative criteria for assessing goodness-of-fit. Marsh, Balla, and McDonald (1988) argue that while neither c2 nor c2/df vary with sample size for a true model, both are strongly affected by sample size when the model is false. They recommended using the Tucker and Lewis (1973) nonnormed incremental fit index (TLI) and demonstrated that the TLI is the only widely used c2 fit index that is relatively independent of sample size. Although the TLI may be relatively independent of sample size, there is no absolute standard for the TLI that indicates what constitutes an acceptable fit. Bentler and Bonett (1980) suggested that improvement to a model can be made when TLI values are less than .90 (although this standard has yet to be empirically supported). The TLI for the hypothesized model was 1.07.

Additional goodness-of-fit measures also supported the finding of good fit (GFI = .997, AGFI = .996, RMSR = .015). Examination of normalized residuals revealed no relationships that were not accounted for in the model. Indeed, the average normalized residual was quite small (ANR = .080).

Table 2 presents the structural parameter estimates for the hypothesized model. For the equation predicting innovative behavior, all parameters were significant but one. This was the path from creative problem-solving style to innovative behavior. As hypothesized, there were significant parameters between innovative behavior and each of the other predictors -- charisma, role expectations, conventional problem-solving style, support for innovation, and resource supply.

For the equations predicting the two climate measures, the only significant structural parameters were from LMX and creative problem-solving style. While creative problem-solving style was a significant predictor of both climate dimensions, conventional problem-solving style was not related to either climate dimension. Additionally, while conventional problem-solving style was related to innovative behavior, creative problem-solving style was not. Finally, there was a significant relationship between the unaccounted variances of the two climate measures (y2,3 = .421, std. error = .074, p < .001). This suggests that some unmeasured variable (or set of variables) similarly influences perceptions of both climate dimensions.

In examining the direction of the significant parameters, a number of relationships were found which were contrary to hypotheses. In the original model, both climate dimensions, support for innovation and resource supply, were hypothesized to be positively related to innovative behavior. The structural parameter from support for innovation to innovative behavior offered support for this hypothesis. However, the structural parameter from resource supply to innovative behavior was negative. This is likely the result of suppression. Support for a suppression explanation is provided by the lack of a significant correlation between resource supply and innovative behavior (r = -.07, n.s.). Thus, the relationship between resource supply and innovative behavior was interpreted as non-significant in this study despite the significant path estimate (Cohen & Cohen, 1983).

A similar suppression arose with the structural parameters between the leadership variables and innovative behavior. The paths between both LMX and role expectations and innovative behavior were significant and positive as hypothesized. However, the structural parameter from charisma to innovative behavior was significant and negative. The correlation between charisma and innovative behavior was non-significant (r = .03, n.s.), suggesting that a suppression effect was operating. Again, the interpretation is that no relationship exists between charisma and innovative behavior in this study.

The structural parameter from prior innovative behavior to innovative behavior was significant and positive as hypothesized. That is, past behavior, as demonstrated by filing of invention disclosures, appeared to be a sound predictor of current innovative behavior.

In examining the direction of the structural paths predicting PC perceptions of support for innovation and resource supply, the direction of each significant path was as hypothesized. This included the positive paths from LMX to each of the climate dimensions, and the negative paths from creative problem-solving style to each of the climate dimensions. As mentioned above, the paths from charisma, role expectations, and conventional problem-solving style to each climate dimension were not significant.

The model (i.e., PC, leadership, and individual attributes) accounted for 49.6 percent of the variance of innovative behavior. Furthermore, the leadership measures and individual attributes accounted for 37.5 percent of the variance in perceptions of support for innovation and 21.9 percent of the variance in perceptions of resource supply.

The purpose of this study was to develop and test a model of individual innovative behavior. Drawing on the extant literature, we proposed a model in which leadership and individual attributes affected innovative behavior directly and indirectly through climate perceptions. The model tested in this study provided a good fit to the data, and explained nearly half of the variance in innovative behavior. This is a substantial finding given that the development of theory in the area of individual innovative behavior is in the early stages.

The study provides evidence that the emergence of innovative behavior is highly related to the quality of the supervisor/subordinate relationship. This finding is supportive of LMX theory (i.e., Graen & Scandura, 1987) -- high quality dyadic relationships characterized by mutual trust seem to facilitate innovative behavior by providing to the subordinate levels of autonomy and discretion necessary for innovation to emerge (e.g., Cotgrove & Box, 1970; Pelz & Andrews, 1966). In addition, it appears that individuals generalize the supervisor/subordinate relationship to the organization at large. In this sample, subordinates who reported having relationships with their supervisor characterized by higher levels of support, trust, and autonomy also reported the organization to be more supportive of innovation and judged resource supply to be higher. The positive relationship found here between LMX and climate perceptions replicates prior work by Kozlowski and Doherty (1989) and others, and it does so in the context of innovative climate -- fulfilling Schneider's (1975) charge that climate studies be anchored within a specific domain of inquiry.

We also found that individual innovative behavior was influenced by the role expectations of the supervisor, providing support for the Pygmalion Effect (Livingston, 1969). This suggests that supervisory expectations, in fact, do shape the behavior of subordinates and that this effect is independent of the quality of the relationship between supervisor and subordinate. However, both role expectations and innovative behavior were assessed by the supervisor in this study. It is possible that the supervisor judged the role to be that of an innovator or a supporter based on the behavior of the person in the role.

Further, it appears that individuals do not need to be highly creative problem-solvers, as much of the creativity literature suggests, to exhibit high levels of innovative behavior, but they must not be highly conventional problem-solvers. As hypothesized, conventional problem-solving style had a direct, negative effect on innovative behavior. In contrast, the effect of creative problem-solving style on innovative behavior was not direct, but rather was mediated by PC perceptions of support for innovation. The creative problem-solver in this study evaluated support for innovation more negatively than did the less creative problem-solver. This suggests that highly creative problem-solvers have a propensity for negative evaluation of innovative climate. Since innovative behavior is related to these perceptions (at least in the case of support for innovation) the creative problem-solvers' level of innovative behavior is somewhat reduced by their tendency toward negative evaluation. Perhaps, in the case of creative problem-solvers, high LMX becomes even more critical as it may compensate for their propensity toward negative evaluation of the support for innovation.

It is important to note that we have treated the conventional and creative problem-solving styles independently as suggested by prior theory (Jabri, 1991). In actuality, individuals are likely to employ some mix of conventional and creative problem-solving. Further, it is likely that individuals use conventional and creative problem-solving at different times and on different tasks. Perhaps the true innovator is an individual who is able to use a style which is appropriate to the stage of the innovation cycle in which he or she is involved. Despite this conjecture, the results here suggest that individuals that describe themselves as very high in conventional problem-solving style are low on innovative behavior. Further study is needed on the effects of the various combinations of these two styles on both climate perceptions and innovative behavior.

The finding that an individual's innovative history predicted his or her current innovative behavior may seem trivial given that it confirms accepted wisdom in the literature, but the positive significant relationship provides an important validity check on the criterion variable. The moderate size of the relationship between this objective archival measure and the subjective rating of innovative behavior is also not surprising. The specific behaviors rated by the supervisors, although essential to the innovation process in this environment, do not necessarily result in innovations that lead to invention disclosures.

Several findings in the current study were contrary to hypothesis and deserve comment. First, the lack of a significant correlation between charisma and innovative behavior was surprising, and the negative beta between the two may, in fact, not be the result of suppression (as discussed in the results section). Although charisma has been reported to be positively related to the championing of innovation ideas (Howell & Higgins, 1990), the results of this study offer no evidence that charisma influences subordinates to generate or champion ideas themselves. Perhaps the charismatic leader is able to mobilize support for the leader's own vision (or innovation) but unable to sponsor (or uninterested in sponsoring) the ideas of subordinates. As a result, the charismatic leader may have a negative impact on the innovative behavior of his or her subordinates. In fact, in a recent model of leadership and innovation, Waldman and Bass (1991) posited that charisma is only of benefit in the diffusion stage of innovation when persistent effort, rather than innovativeness, is required of subordinates. Since the current study did not include persistent effort as a dimension of innovative behavior, we could not investigate their proposition.

The pattern of findings reported here on the effects of both LMX and charisma replicate the findings of Basu (1991) using an independent sample. Basu (1991) reported a strong direct relationship between LMX and innovative behavior, a non-significant correlation between charisma and innovative behavior, and a negative beta between charisma and innovative behavior. It is particularly interesting to note that the Basu sample consisted of blue-collar workers in a printing operation as compared to the current sample of R&D professionals. Thus, there is some evidence for the generalizability of the reported findings on leadership beyond the R&D organization.

The results of the test of the relationship between resource supply and innovative behavior were surprising. While PC perceptions of the support for innovation were positively related to innovative behavior, the coefficient between resource supply and innovative behavior was negative. Given that the zero-order correlation between these two was non-significant, it appears that a suppression effect was operating and that there was no relationship between resource supply and innovative behavior in this study. This finding is surprising in that resources have previously been theorized to be critical to innovation (e.g., Lawrence & Dyer, 1983).

Two explanations are offered for the lack of effect of the resource supply dimension. First, the resource supply variable used in this study is phenomenological in nature, in contrast to objective measures of resource supply typically used in the innovation literature. The findings here suggest that it is the objective reality which influences behavior, rather than the perception of reality. This has important implications for managing the innovation process for it suggests that managers would be better advised to focus on assuring adequate resource supply rather than expending considerable energy trying to manage the perceptions of their subordinates.

A second alternative explanation focuses on the form of the relationships between the climate dimensions and innovative behavior and on the nature of the variables themselves. The study of resource supply as a determinant of innovation has typically been done at the organizational rather than the individual level. Some of these studies report a positive linear relationship between resources and innovative performance (e.g., Mohr, 1969; Rogers, 1983), while others report the relationship is negative (Meyer, 1982; Patti, 1974). It seems likely that, in the case of resources, a threshold effect could operate. In other words, while perceived increases in resource supply below the threshold level may result in increases in performance, increases above the threshold level may have no effect. In the case of resource supply, enough may simply be enough. To illustrate the point, consider an R&D laboratory with inadequate equipment or severe under-staffing. It is reasonable to expect that as equipment or additional manpower were added, performance would increase. However, at some point, it is also reasonable to assume that resources would reach a level where they were adequate for the job at hand, and further increases would not yield additional increments in performance. Since the sample in this study was an R&D laboratory with the espoused mission of innovation, resources may have been available at a level above such a threshold. Thus, no relationship was found between resources and innovative behavior in this study. Cross-organizational research is needed at the individual level to broaden the range of the resource supply variable and to test for threshold effects.

In contrast to the resource supply variable, support for innovation was positively related to innovative behavior. If a threshold effect exists for the support variable, this organization may have operated below the threshold level and, thus, a positive linear relationship was found. Alternatively, it may be that the nature of the support variable is very different from the resource variable. Support for innovation, as defined here, measures abstract concepts -- flexibility, encouragement, tolerance for change -- which may, in fact, be linearly related to behavior across the entire range. In other words, more support may always be better than less.

Finally, it is quite possible that the dimensions of climate exist on a hierarchy of need. Consider again the imaginary research lab discussed above where resources were severely lacking. It is a reasonable assumption that no amount of support for innovation would be able to overcome resource deficiencies and positively influence innovative performance. Once adequate resources were available, however, support for innovation would be likely to become a critical factor in the determination of innovative performance.

The findings in this study are subject to a number of caveats. First, the cross-sectional nature of the research design limits the ability to determine causation. This is particularly problematic with LMX and role expectations. A high quality relationship between supervisor and subordinate may result from, rather than cause innovative behavior. In fact, the relationship between LMX and performance outcomes has been conceptualized previously as reciprocal (Graen & Scandura, 1987). A longitudinal design would be required to test for such a reciprocal relationship between LMX and innovative behavior.

The second caveat concerns the generalizability of these findings to other types of work organizations and to other functional areas of organizations. Although, as previously mentioned a number of the hypothesized relationships replicate the work of others, the test of the overall model should be replicated in other settings.

Mono-method bias has been minimized as much as possible in this study, but remains an issue, particularly as regards the determination of climate. Although care was taken to assure that items in the measures of the predictors of climate tapped separate conceptual domains, all of the measures used similar response formats and were completed by the same source. However, same-source responses were avoided in assessing the determinants of innovative behavior. While the criterion was a supervisory assessment of innovative behavior, measures of the independent variables were assessed by subordinates or from the archives with the exception of role expectations.

The current study provides an attempt at modeling a complex phenomena -- individual innovative behavior. Although, there has been no scarcity in the literature of suggested antecedents to individual creativity and innovation, this study has attempted to integrate some of these disaggregated findings into a cohesive model and to test it in the natural work context of an R&D facility. As such it provides some understanding of the complex interrelationships among and causal paths between a number of antecedents often cited in the literature. While the findings reported here provide some guidance to practicing managers, they also pose a whole new set of questions for researchers. What is the joint affect of conventional and creative problem-solving style? Is there a threshold level at which additional resources no longer improve innovative behavior? Is this threshold effect true of all types of resources -- time as well as equipment and facilities? Will additional support for innovation continue to improve innovative behavior, and to what level? The answers to these questions await further study.

Studying individual innovative behavior in the natural work context is a complex and difficult task because the criterion is often difficult to validate, and we are often limited to the use of perceptual measures. But as organizations continue to face increasingly turbulent environments and innovation becomes part of every employee's job description, the need for this kind of research is ever increasing. This study has made one step in this direction and has provided evidence of the significant influence of leadership, individual attributes, and climate on innovative behavior.

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Variable Mean S.D. 1 2 3 4 5 6 7 8 9

1. Innovative Behavior 3.24 .85 .72 .11 -.05 .11 .34 .02 -.33 .17 .13

2. PC: Support 3.42 .73 .18 .53 .33 .26 .11 .29 .09 .01 .03

3. PC: Resource Supply 2.74 .80 -.07 .57 .64 .18 -.02 .18 .13 -.09 -.02

4. LMX 3.74 .66 .19 .54 .33 .44 .07 .42 .13 .13 .02

5. Role Expectations 2.94 1.13 .36 .13 -.02 .10 1.28 .07 -.16 .17 .17

6. Charisma 3.52 .82 .03 .49 .27 .78 .07 .67 .15 .14 .01

7. Conventional P-S Style 4.28 1.10 -.35 .11 .15 .18 -.13 .17 1.20 -.22 .06

8. Creative P-S Style 5.12 .99 .20 .02 -.11 .20 .16 .17 -.20 .99 .06

9. Prior innovative behavior 2.74 5.25 .37 .11 -.06 .05 .35 .03 -.12 .14 .18

N = 189.

Note: Correlations are in bold and at the lower half of the matrix; Variance/covariance matrix occupies the diagonal
and upper half of the matrix.

r > .12, p < .05

r > .16, p < .01

r > .21, p < .001

Dependent Standardized Path Standard Path
Variable Path Estimates Error Significance

* p < .05

** p < .01

*** p < .001

Items 1 2

1. Creativity is encouraged here. .66 .23

2. Our ability to function creatively is respected by the leadership. .65 .34

3. Around here, people are allowed to try to solve the

same problems in different ways. .52 .39

4. The main function of members in this organization is to

follow orders which come down through channels. -.73 -.01

5. Around here, a person can get in a lot of trouble by being different. -.69 -.18

6. This organization can be described as flexible and

continually adapting to change. .58 .32

7. A person can't do things that are too different around here

without provoking anger. -.68 -.28

8. The best way to get along in this organization is to think

the way the rest of the group does. -.66 -.25

9. People around here are expected to deal with problems in

the same way. -.69 -.22

10. This organization is open and responsive to change. .65 .36

11. The people in charge around here usually get credit for others' ideas. -.53 -.03

12. In this organization, we tend to stick to tried and true ways. -.55 -.36

13. This place seems to be more concerned with the status quo

than with change. -.70 -.34

14. Assistance in developing new ideas is readily available. .25 .62

15. There are adequate resources devoted to innovation in this

organization. .18 .70

16. There is adequate time available to pursue creative ideas here. .12 .80

17. Lack of funding to investigate creative ideas is a problem

in this organization. -.08 -.53

18. Personnel shortages inhibit innovation in this organization. -.10 -.55

19. This organization gives me free time to pursue creative ideas

during the workday. .28 .64

20. The reward system here encourages innovation. .55 .31

21. This organization publicly recognizes those who are innovative. .59 .07

22. The reward system here benefits mainly those who don't rock the boat. -.68 -.21

Eigenvalue 6.97 3.46

Percent of variance 31.67 15.74