Creativity Research Journal 2007, Vol. 19, No. 1, 69–90

Copyright © 2007 by Lawrence Erlbaum Associates, Inc.

ARTICLE Climate for Creativity: A Quantitative Review Samuel T. Hunter, Katrina E. Bedell, and Michael D. Mumford The University of Oklahoma

ABSTRACT: Creativity is commonly held to emerge from an interaction of the person and the situation. In studies of creativity, situational influences are commonly assessed by using climate measures. In the present effort, a meta-analysis was conducted to examine 42 prior studies in which the relationships between climate dimensions, such as support and autonomy, and various indices of creative performance were assessed. These climate dimensions were found to be effective predictors of creative performance across criteria, samples, and settings. It was found, moreover, that these dimensions were especially effective predictors of creative performance in turbulent, high-pressure, competitive environments. The implications of these findings for understanding environmental influences on creativity and innovation are discussed. Creativity, the generation of new ideas, and innovation, the translation of these ideas into useful new products, are commonly held to arise as a function of an interaction between the person and the situation (Amabile, 1997; Scott & Bruce, 1994). In recent years, the field has made substantial progress in understanding the attributes of creative people with studies demonstrating the importance of expertise (Ericsson & Charness, 1994; Rich & Weisberg, 2004), information processing strategies (Lubart, 2001; Mumford, Supinski, Baughman, Costanza, & Threlfall, 1997; Ward, Patterson, & Sifonis, 2004), abilities (Sternberg & O’Hara, 1999; Vincent, Decker, & Mumford, 2002) and personality characteristics (Barron & Harrington, 1981; Feist, 1999). Other scholars have sought to understand how creativity and innovation are influenced

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by environmental variables with studies examining collaborations (Abra, 1994; Bullinger, Auernhammer, & Gomeringer, 2004), group interactions (Rickards, Chen, & Moger, 2001; West, 2002), leadership (Amabile, Schatzel, Moneta, & Kramer, 2004; Howell & Boies, 2004), and organizational structure (Cardinal & Hatfield, 2001; Damanpour, 1996). Although a variety of environmental variables have been identified that might influence creativity and innovation, many scholars stress the importance of climate (e.g., Amabile & Gryskiewicz, 1989; Anderson, De Dreu, & Nijstad, 2003; West, 2002). Climate studies examine peoples’ perceptions of, or experiences in, their immediate work environment with respect to dimensions such as support and autonomy (Mathisen & Einarsen, 2004). And, broadly speaking, the results obtained in these studies underscore the importance of climate in that (a) creative people, people evidencing the individual attributes related to creative achievement, appear especially reactive to climate variables (Oldham & Cummings, 1996); (b) climate perceptions, at both the individual and group level, have been found to be effective predictors of creativity and innovation (Tesluk, Farr, & Klein, 1997); and (c) climate assessments have provided a basis for organizational interventions that have proven useful in enhancing creativity and innovation (Basadur, 1997; Schneider, Gunnarson, & Niles-Jolly, 1994; Van De Ven, 1986). We would like to thank Ginamarie Scott, Lyle Leritz, and Jazmine Espejo for their contributions to this effort. Address correspondence to Michael D. Mumford, Department of Psychology, The University of Oklahoma, Norman, OK 73014. E-mail: [email protected].

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Despite the apparent importance of climate in shaping creative achievement, a number of questions remain unanswered (Mathisen & Einarson, 2004). For example, it is difficult to say with any certainty which of the many dimensions of climate found in the literature is the most important influence on creativity and innovation (Mumford & Hunter, 2005). It is unclear what the limitations are on the generality of these predictive relationships. And, we do not know much about the occupational, group, organizational, and environmental variables that might moderate these relationships (Anderson et al., 2004). With these points in mind, our intent in the present study was to conduct a meta-analysis of prior studies that examined the relationship between climate perceptions and creative achievement to establish overall effect size, dimensional effects, internal and external validity, and significant moderators of the strength of these relationships.

Climate Climate has been defined in different ways by different investigators (Rousseau, 1988). Climate, however, is commonly held to be reflected in peoples’ perceptions of, or beliefs about, environmental attributes shaping expectations about outcomes, contingencies, requirements, and interactions in the work environment (James, James, & Ashe, 1990; Parker et al., 2003; Schneider & Reichers, 1983). Thus climate, unlike culture, is a localized phenomenon reflecting experienced, environmental press at either the individual or group level (Cooke & Rousseau, 1988). Thus typical climate questions (Lapierre & Giroux, 2003) ask whether “employees feel free to express their ideas to bosses” or whether “people are not afraid to take risks around here.” As indicated by these questions, climate is held to be a domain referenced phenomenon (e.g., climate for creativity, climate for service) in which multiple variables, or dimensions, act to shape performance in the domain under consideration. A number of different theoretical frames have been used to specify the climate variables that might influence creative achievement. For example, a theory of intrinsic motivation was used by Amabile (Amabile & Conti, 1999; Amabile, Conti, Coon, Lazenby, & Herron, 1996; Amabile & Grykiewicz, 1989) in devel-

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oping the following eight dimension model: (1) work group support, (2) challenging work, (3) organizational encouragement, (4) supervisory encouragement, (5) organizational impediments, (6) freedom, (7) workload pressure, and (8) sufficient resources. In contrast, West and his colleagues (Anderson & West, 1988; Bain, Mann, & Pirola-Merlo, 2001; Burningham & West, 1985; West et al., 2003) used a theory of team interactions to develop the following four dimensional model: (1) participative safety, (2) support for innovation, (3) challenging objectives, and (4) task orientation. The dispositional model proposed by Ekvall and his colleagues (Ekvall, 1986; Ekvall & Ryhammer, 1999; Isakson & Lauer, 2002; Isaksen, Lauer, Ekvall, & Britz, 2001) is based on a theory of underlying psychological processes that led to the development of a nine dimension model: (1) challenge and involvement, (2) freedom, (3) trust and openness, (4) idea time, (5) playfulness and humor, (6) conflict, (7) idea support, (8) debate, and (9) risk-taking. Other models of relevant climate dimensions have been proposed with approaches based on organizational reinforcers (Abbey & Dickson, 1983), environmental appraisal (Tesluk et al., 1997), engagement (Mossholder & Dewhurst, 1980), requirements for new product development (Thamhain, 2003), and organizational learning theory (Lapierre & Giroux, 2003). In an initial attempt to integrate these varying perspectives, Lapierre and Giroux (2003) administered climate questions formulated by using the organizational learning and dispositional models to 127 information technology professionals. They found that climate questions formulated by using these two frameworks converged around a smaller set of underlying dimensions. In an extension of this work, Hunter, Bedell, and Mumford (2005) reviewed the available taxonomies of climate variables. They found that more than 90% of the variables appearing in prior taxonomies could be accounted for by a 14 dimension model that included (1) positive peer group, (2) positive supervisory relationships, (3) resources, (4) challenge, (5) mission clarity, (6) autonomy, (7) positive interpersonal exchange, (8) intellectual stimulation, (9) top management support, (10) reward orientation, (11) flexibility and risk taking, (12) product emphasis, (13) participation, and (14) organizational integration. Although some evidence is available that points to convergence of these varied approaches, application

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Climate

of different models in specifying relevant dimensions has given rise to differences in the nature of the instruments used to assess climate perceptions. Available inventories differ not only in the number of dimensions being assessed but also in the number and type of questions being applied and the response format in use. In a recent review of the psychometric properties of three of these inventories, Mathisen and Einarsen (2004) found that the dimensional scales derived from these inventories evidenced adequate internal consistency—although within-group agreement data were not available. In addition, Mathisen and Einarson (2004) found that factor analytic studies have provided some support for the hypothesized dimensional structure underlying these instruments. More centrally, the evidence compiled by Mathisen and Einarsen (2004) indicated that climate measures can predict creativity and innovation in real-world settings. The validation strategy applied in most studies involved examining the relationship between climate dimensions and self- and/or supervisory ratings of creativity (e.g., Amabile & Conti, 1996; Bunce & West, 1995; Caldwell & O’Reilly, 2003; Mohamed, 2002). However, evidence for the predictive validity of climate appraisals has been obtained by using a variety of other criteria, including expert judgments of products produced (Agrell & Gustafson, 1994), publications (Ekvall & Ryhammer, 1999; McCarrey & Edwards, 1994), engagement in entrepreneurial activities (Brendle, 2001), innovation adoption (Kitchell, 1995), and return on investment (Baer & Freese, 2003). This validation evidence, furthermore, has been accrued in samples ranging from research and development personnel (Abbey & Dickson, 1983) to health care delivery teams (Borrill, West, Shapiro, & Rees, 2000). This variability in criteria and sample characteristics, of course, broaches the question as to the extent to which validation findings bearing on these climate appraisals generalize across criteria, samples, and settings.

Moderators There is, moreover, reason to suspect that the relationship between climate variables and creativity may vary as a function of a number of moderators—moderators related to the nature of the work being done (Oldham & Cummings, 1996), the group (Curral,

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Foster, Dawson, & West, 2001), the organization (Russell & Russell, 2000), and the environment in which the organization is operating (Anderson et al., 2003). In one study along these lines, Bain et al. (2001) used a number of different criteria, including ratings of individual and team innovation, patent awards, and project outcomes, to contrast people working on research projects with people working on development projects on the basis of the hypothesis that opportunities for exploration on the job would moderate the relationship between climate variables and indices of creative achievement. In keeping with this hypothesis, they found that climate was more strongly related to indices of creativity and innovation on research projects as opposed to development projects. Ford and Sullivan (2004) have suggested that the need for creativity, and thus the influence of climate on innovation, may vary as a function of project demands—with creativity, and a creative climate, proving especially valuable in early cycle as opposed to late cycle product development efforts. The nature and status of the project, however, are not the only work-based variables that might moderate climate influences. Mumford, Whetzel, and Reiter-Palmon (1997) have argued that the amount of discretion people are granted on their jobs may also moderate the relationship between climate and creativity due to the potential for autonomous exploration. In addition to these objective job characteristics, more subjective features of the job, for example job satisfaction, vis-à-vis mood effects (Madjar, Oldham, & Pratt, 2002; Zhou & George, 2001), may also act as moderators. In addition to job characteristics, it appears that characteristics of the group may also moderate the relationship between climate and indices of creativity and innovation. One illustration of this point may be found in a study by Curral et al. (2001). They found that team size, by affecting group processes, can influence climate, and presumably, the relationship between climate and creative achievement, with large teams leading to poor climate and a weak climate–creativity relationship due to process loss. Other variables affecting group process, including trust and cohesion (Howell & Boies, 2005), interdependence (Thamhain, 2003), and the need for cross-functional teams (Keller, 2001), might also act as moderators of the relationship between climate measures and creativity.

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In contrast to group size, organizational size appears to have a rather different pattern of effects on the relationship between climate and creative achievement. Nystrom, Ramamurthy, and Wilson (2002) examined innovation adoption in health care organizations. They found not only that size and resources were positively related to innovation but also that size and resources interacted with climate by allowing organizations to act on the ideas flowing from a creative climate. In addition to size and resources, other organizational variables that might operate to moderate the relationship between climate and creative achievement include horizontal as opposed to vertical structuring (Russell & Russsell, 2002), capital intensity (Mumford & Hunter, in press), professionalization (Damanpour, 1991), and organizational learning with regard to innovation (Cohen & Levinthal, 1990). Environmental influences that might moderate the relationship between climate and creative achievement have received less attention than group and organizational level variables. In a notable exception to this general trend, Russell and Russell (2002) found that environmental turbulence was positively related to both creative climate and adoption of a corporate strategy stressing innovation. On the basis of the findings of Borrill et al. (2002) concerning the influence of market demands on the relationship between climate and innovation, Janssen, Van De Vliert, and West (2004) argued that turbulence, production pressure, and competitive pressure not only establish a need for innovation but will lead climate to become a more important influence on creative achievement.

Objectives Clearly, a number of variables operating at the job, group, organizational, and environmental levels might moderate the relationship between climate and creativity. Our ultimate goal in the present study was to identify the job, group, organizational, and environmental variables that may be noteworthy moderators of the relationship between climate and creativity in organizational settings. To provide a substantive foundation for this moderators analysis, however, it was first necessary to demonstrate that across studies, climate dimensions in fact provide sizable relationships with measures of creativity and that these relationships are not an artifact of study design characteristics (internal va-

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lidity considerations) or the population and settings being studies (external validity considerations).

Method Literature Search To examine the effects of these moderators, and to establish the internal and external validity of climate measures in accounting for creative achievement, we conducted a meta-analysis. Identification of the studies to be included in this meta-analysis began with an examination of general review articles on climate and innovation in organizational settings (e.g., Anderson et al., 2003; Mumford & Hunter, 2005; Tesluk et al., 1997). Additionally, prior issues of journals that frequently publish articles on climate and creativity were reviewed, including the Creativity Research Journal, Journal of Creative Behavior, Organizational Behavior and Human Decision Processes, Journal of Applied Psychology, Academy of Management Review, Academy of Management Journal, Journal of Organizational Behavior, R & D Management, and Creativity and Innovation Management. After reviewing likely publication sources, we searched relevant databases to identify additional studies. This data base search, with the key words creativity or innovation with climate or culture, included Psychological Abstracts, JSTOR, Business Source Elite, Google Scholar, and Dissertation Abstracts. Following this database search, we reviewed programs of relevant conferences of the American Psychological Association, the Society for Industrial and Organizational Psychology, and the Academy of Management to identify any conference papers that might be included in this meta-analysis. Although application of these procedures resulted in a reasonably comprehensive review of studies that had appeared in print or in conferences, it could not ensure that studies that had not been publicly presented were included in the meta-analysis. To address this “file drawer” problem (Rosenthal, 1979; Rosenthal 1992)—failure to consider studies producing weak effects which would lead to overestimation of effect size—an attempt was made to obtain unpublished studies that might be relevant to the present effort. Accordingly, the initial literature review was used to identify scholars who had published two or more articles on

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Climate

topics relevant to creativity and climate over the last 10 years or who were known to have been involved in, or to be in the process of, initiating research programs in this area. E-mails were sent to each of these scholars describing the intent of the study and asking if they could forward any unpublished manuscripts. Application of these procedures resulted in the identification of 88 articles, conference papers, or manuscripts that might be considered for inclusion in the meta-analysis. Each article, conference paper, or manuscript was reviewed by a psychologist familiar with the literature on climate and creative achievement and were eliminated if (a) they only presented qualitative data, (b) they only examined organizational influences on climate as opposed to examining the relationship between climate and creativity, (c) the performance criteria applied were not described, (d) the performance criteria applied did not expressly examine creativity or innovation, (e) the sample and setting in which the study (or studies) was conducted were not described, (f) the specific climate dimensions examined were not described, and (g) the relationships between specific climate dimensions and measures of creative achievement were not presented. On the basis of the application of these criteria, 42 articles, conference papers, dissertations, or manuscripts, all using independent samples, were included in the meta-analysis, which presented data drawn from 14,490 participants. Effect Size Estimates To provide a basis for estimating effect size in terms of specific climate dimensions, a psychologist familiar with the literature on climate and creativity was asked to review the definitions of, and markers used to measure, each of the climate dimensions examined in a given study. On the basis of this information, he/she was then asked to assign each climate dimension under consideration in a study of one, or more, of the 14 dimensions appearing in the general taxonomy of climate dimensions developed by Hunter et al. (in press). These 14 dimensions and their operational definitions are presented in Table 1. A reliability check, examining the percentage agreement among three judges, indicated greater than 90% agreement in the assignment of climate dimensions found in the literature to the 14 climate dimensions included in this general taxonomy. If a climate di-

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mension appearing in a study could not be assigned to at least one of the 14 dimensions included in the taxonomy, it was dropped from the study. Only 5% of the dimensions identified in prior studies could not be assigned to one or more of the 14 dimensions included in the general taxonomy of climate dimensions. After reviewing and cross-classifying the climate dimensions, a psychologist was asked to review the description of the criteria used to measure creative achievement. After reviewing the description of the criterion measure being applied, this judge was to indicate the level of criterion measurement (1 = individual, 2 = group, 3 = organizational, or 4 = mixed) and the type of criteria applied (1 = ratings of creative performance or innovative achievement, 2 = new products or services, 3 = patents or awards, 4 = publications, and 5 = other). Because a large proportion of the studies appearing in the literature are based on ratings, this judge was also asked to indicate rating type, and, if ratings were applied, to classify the ratings as to source (1 = self, 2 = peer, 3 = supervisor, 4 = subordinate, 5 = researcher, or 6 = mixed). Effect size estimates were obtained for each climate dimension against each criteria measure under consideration in a given study. All of the studies selected for inclusion in this meta-analysis used one of two basic strategies to establish the relationship between appraisals of a climate dimension and performance; either (a) the climate dimension was correlated with a criterion or (b) differences in mean climate scores on the dimensions were presented contrasting more or less creative groups as defined by a creative performance measure. In the case of studies that used a group differences design, effect size was assessed by using Glass, McGaw, and Cohen’s delta statistic ∆ as estimated with the pooled within-group variation (Huberty, 2002). In the case of studies that used a correlational design, ∆ estimates were obtained for each dimension with respect to each criterion by using the procedure described by McGaw and Glass (1980) for converting correlations to deltas. After calculating these effect sizes, the average delta across dimensions was obtained for each criterion examined in each study to control for the differences in the number of climate dimensions being examined. Then the average delta across studies examining multiple criteria was obtained to avoid overweighting data obtained from one sample in the overall analysis.

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Table 1. Summary of General Taxonomy Dimensions Label 1. Positive Peer Group

2. Positive Supervisor Relations 3. Resources

4. Challenge

5. Mission Clarity

6. Autonomy 7. Positive Interpersonal Exchange 8. Intellectual Stimulation 9. Top Management Support

Example of Climate Dimension

Operational Definition Perception of a supportive and intellectually stimulating peer group. Relationships are characterized by trust, openness, humor, and good communication. Perception that an employee’s supervisor is supportive of new and innovative ideas. Supervisor also operates in a non-controlling manner. Perception that the organization has, and is willing to use, resources to facilitate, encourage and eventually implement creative ideas. Perception that jobs and/or tasks are challenging, complex, and interesting—yet at the same time not overly taxing or unduly overwhelming. Perception and awareness of goals and expectations regarding creative performance. Perception that employees have autonomy and freedom in performing their jobs. Employees perceive a sense of “togetherness” and cohesion in the organization. Employees experience little emotional or affectively laden conflict in the organization. Perception that debate and discussion of ideas (not persons) is encouraged and supported in the organization. Perception that creativity is supported and encouraged at the upper levels of the organization.

10. Reward Orientation

Perception that creative performance is tied to rewards in the organization.

11. Flexibility and Risk-Taking

Perception that the organization is willing to take risks and deal with uncertainty and ambiguity associated with creative endeavors.

12. Product Emphasis

Perception that the organization is committed to quality as well as originality of ideas. Perception that participation is encouraged and supported. Communication between peers, supervisors and subordinates is clear, open, and effective. Perception that the organization is well integrated with external factors (e.g., outsourcing) as well as internal factors (e.g., use of cross-functional teams).

13. Participation

14. Organizational Integration

Variable Coding To examine overall effect size, taking into account relevant internal and external validity considerations and potential moderators of these effects operating at the individual, group, organizational, and environmental levels, we conducted a content analysis. In this content analysis, three judges, all doctoral candidates in industrial and organizational psychology were asked to

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Cooperation (Abbey & Dickson, 1983) Supportive supervision (Oldham & Cummings, 1996) Resources (Amabile, Conti, Coon, Lazenby, & Herron, 1996) Job complexity (Oldham, & Cummings 1996) Clear organizational objectives (Thamhain, 2003) Freedom (Ekvall, 1996) Conflict harmonization (Ayers, Dahlstrom, & Skinnner, 1997) Debate (Ekvall, 1996) Support for Innovation (Anderson & West, 1988) Reward orientation (Tesluk, Farr, & Klein, 1997) Flexibility (Ayers, Dahlstrom, & Skinner, 1997) Quality orientation (Sethi & Nicholson, 2001) Participative safety (Anderson & West, 1988) Cross-functional cooperation and support (Thamhain, 2003)

review the description of each study providing a basis for effect size estimates. These judges were blind to the hypotheses underlying the present effort but were familiar with the creativity and climate literature. Prior to starting work coding the relevant variables, these judges were exposed to a 40-hr training program. In this training program, they were familiarized with the nature of the variables to be coded and the coding scheme to be applied to each variable. In making these

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evaluations, judges were instructed to code a variable only if the description of the study explicitly considered material relevant to the appraisal—otherwise a missing data code was to be applied. After this initial training, judges were asked to code five studies. Once they had made their study ratings, they met as a panel to discuss their ratings and to resolve any discrepancies. Subsequently, these judges were presented with 10 studies, selected to represent a range of material likely to be encountered, and were asked to evaluate these studies by using the coding scheme. A reliability check examining percent agreement across the three judges indicated 92% agreement in the coding of the relevant variables.

population, and setting. The population variables examined gender: (a) 80% or more of the sample men, (b) 80% of the sample women, or (c) mixed; age: (a) 80% of more of the sample over 40, (b) 80% of the sample under 40, or (c) mixed; educational background: (a) professional, (b) nonprofessional, or (c) mixed; country type: (a) industrial or (b) nonindustrial; and country culture: (a) individualistic or (b) collectivist (Hofstede, 1996). The setting variables considered whether the study was conducted in a for-profit or in nonprofit organization and the major kind of work conducted in the organization using sample members—(a) research and development, (b) manufacturing, (c) service, or (d) mixed (Florida, 2003).

Internal Validity

Moderators

The internal validity of these studies was assessed by using indices of study quality commonly applied in meta-analytic efforts (Scott, Leritz, & Mumford, 2004). More specifically, these evaluations of internal validity, or study quality, considered (a) sample size, either above or below average; (b) whether the study appeared in a peer reviewed journal; (c) the educational level, doctorate or nondoctorate, of the principal investigator; (d) whether reliability estimates were presented for scores on the climate dimensions; and (e) whether the criterion data were collected anonymously. In addition to these general indices of study quality, two additional variables were examined uniquely relevant to studies of climate and creative achievement. As Mathisen and Einarsen (2004) have pointed out, many climate studies are based on well-researched, standardized instruments, whereas other studies are based on locally developed, exploratory instruments. Accordingly, studies were coded as to whether standardized or local exploratory measures were applied. Moreover, as Mumford and Hunter (2005) have pointed out, these measures differ with respect to underlying assumptions about key climate variables. As a result, each study was assessed as to the approach used in developing climate measures, that is (a) psychological/dispositional, (b) motivational, (c) team, (d) organizational, or (e) mixed.

Job. The job moderators examined attributes of the work being done that might moderate the relationship between climate and creative achievement. The first set of moderators pertained to the work being done. Here judges were asked to evaluate (a) whether the generation of new ideas was required for employment; (b) the kind of innovations, product innovations (e.g., new designs), process innovations (e.g., new services), or both, that were sought on the job; (c) the stage of the innovation process involved—early (generation), middle (refinement), late (fielding; Ford & Sullivan, 2004; Mumford 2000). Additionally, on the basis of the observations of Mumford et al. (1997), judges were asked to rate, on a 3-point scale, the amount of discretion people were given in performing their work. The second set of job level moderators examined motivation and emotional reactions. Judges, on the basis of the material presented in the study description, were asked to indicate whether rewards were provided for creativity and innovation and whether the rewards provided were primarily intrinsic or extrinsic in nature. They were also asked to rate, on a 3-point scale, the overall level of job satisfaction.

External Validity External validity was to be assessed taking into account three key considerations: generality of findings,

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Group. The first group-level moderator was whether the task at hand required people to work in teams. Additionally, on the basis of the observations of Curral et al. (2001), judges were asked to record team size with team size being coded as very large (15+), large (10–14), medium (6–9), and small (2–5). Judges were also asked to use the descriptive material pro-

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vided and to rate, on a 3-point scale, the degree of interdependence in team work and the cohesion of team members. Organization. The observations of Damanapour (1991), Nystrom et al. (2002), and Subramanian and Nilakanta (1996) were used to specify the organizational moderators. After reading through the description of the organization being studied, judges were asked to rate, on a 3-point scale, the (a) wealth of the organization as reflected in size and resources, (b) the degree of professionalization, (c) and capital intensity. Additionally, judges were asked to indicate whether their organization used a vertical structure, a horizontal structure, or a mixed vertical and horizontal structure. It is of note that these ratings were made only for studies examining climate–creativity relationships in a single organization. Studies that examined multiple organizations were treated as missing data. Environment. In the case of environment, judges were to make ratings only if a single type of organization was being studied. With regard to these environmental variables, judges were asked to indicate whether competition in this industrial sector was based on fielding innovative new products. They were also asked to rate, again on a 3-point scale, the amount of

turbulence in the environment, the amount of competitive pressure, and the performance pressure placed on organizations operating in this market sector by competitors.

Results Effects Table 2 presents the average, cross-criteria delta obtained for each of the 14 climate dimensions included in Hunter et al.’s (in press) general taxonomy of climate dimensions. Additionally, the cross-dimension average overall delta is presented. This table also presents the number of studies providing data for each effect size estimate, the standard error for these delta estimates of effect size, and the 90% upper and lower bound confidence intervals. Additionally, Orwin’s (1983) fail-safe N statistic is presented to provide information pertaining to the number of null studies that would be required to reduce this effect size estimate below .20. As may be seen, all of the dimensions commonly examined in the climate studies produced sizable effects with respect to measures of creativity and innovation. The overall, cross-dimension delta was .75

Table 2. Overall Effects of Climate Within and Across Climate Dimensions

Overall Positive Peer Group Positive Supervisor Relations Resources Challenge Mission Clarity Autonomy Positive Interpersonal Exchange Intellectual Stimulation Top Management Support Reward Orientation Flexibility and Risk-Taking Product Emphasis Participation Organizational Integration

NE

∆

SE

SD

CI

FSN

42 27 24 14 12 18 15 10 11 30 9 24 13 22 20

.75 .69 .73 .51 .85 .62 .48 .91 .88 .75 .55 .78 .59 .61 .62

.10 .12 .12 .19 .14 .09 .09 .39 .18 .10 .19 .12 .12 .11 .13

0.63 0.63 0.64 0.70 0.47 0.36 0.35 1.24 0.66 0.57 0.56 0.59 0.43 0.52 0.57

0.62–0.94 0.48–0.89 0.57–0.93 0.18–0.84 0.61–1.09 0.47–0.77 0.32–0.64 0.19–1.63 0.56–1.21 0.57–0.92 0.56–0.89 0.59–0.99 0.43–0.80 0.52–0.80 0.57–0.84

122 66 77 22 39 38 21 36 37 83 16 70 25 45 42

Note. NE = number of effect size estimates; ∆ = average effect size estimates using Cohen’s delta; SE = standard error of effect size estimate; SD = standard deviation in effect sizes across studies; CI = 90% lower and upper bound confidence interval; FSN = fail-safe N or number of studies needed to decrease effect size below .20.

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whereas the associated standard error was .10. The fail-safe N statistic indicated that more than 120 null studies would be required to change this conclusion. To ensure that these effects could not be attributed to a few outliers, these analyses were replicated after eliminating outliers—specifically studies yielding deltas above +2 or below -2 for each dimension. The resulting average, cross-dimension, effect size obtained after eliminating outliers (∆= .61, SE = .06) was comparable to that obtained in our initial analysis. Thus, it appears that our general conclusion concerning the positive effects of climate on creativity and innovation cannot be attributed to a few studies producing atypical results. The results presented in Table 2, however, also indicate that some variability was observed in the magnitude of the effects associated with different climate dimensions. The effect sizes obtained for the 14 general dimensions ranged from .51 to .91. The dimensions producing the largest deltas were positive interpersonal exchange (∆ = .91, SE = .39), intellectual stimulation (∆ = .88, SE = .18), and challenge (∆ = .85, SE = .14). Apparently, an intellectually stimulating environment in which people have challenging work, and colleagues with who they can exchange ideas, is critical to creativity and innovation. The dimensions producing relatively small effect sizes are also of some interest. Although autonomy is often considered critical for creativity and innovation, the

autonomy dimension produced the smallest delta (∆ = .48, SE = .09). Although this finding may at first glance seem surprising, it is consistent with Trevelyan’s (2001) observation concerning the need for some direction and interpersonal exchange in most real-world creative efforts. Relatively small effect size estimates were also obtained for the resources (∆ = .51, SE = .19) and reward orientation (∆ = .55, SE = .14). Apparently though it is desirable, and perhaps necessary, to provide requisite resources and recognize creative work, resources and recognition are not as important as providing challenging work in an intellectually stimulating environment. The question that arises at this juncture, of course, is whether these effects were contingent on the kind of criteria used to assess creativity and innovation. Table 3 presents the results obtained in the examination of the generality of our findings across criterion types, in which the various objective indices (e.g., patents, publications) were aggregated to provide a more stable comparison of effects vis-à-vis ratings. As may be seen, studies that used ratings as a basis for assessing creative achievement (∆ = .78, SE = .09) produced effect size estimates comparable to those obtained in studies that used more objective measures of creative achievement (∆ = .77, SE = .24). Thus, it appears that conclusions about climate effects on creativity generalize across subjective and objective measures of performance.

Table 3. Overall, Cross Dimensional Effects of Climate by Criterion Type

Criterion Type Ratings Nonratings Rating Type Self Peer Supervisor Subordinate Researcher Mixed Criterion Level Individual Group Organizational

NE

∆

SE

SD

CI

FSN

29 13

0.78 0.77

.09 .24

.51 .86

0.62–0.94 0.35–1.20

84 37

13 2 9 – 3 6

0.97 0.37 0.55 – 1.08 0.56

.16 .08 .10 – .25 .14

.59 .12 .29 – .43 .35

0.68–1.26 –0.16–0.90 0.37–0.73 – 0.37–1.80 0.27–0.86

50 2 16 – 13 11

15 15 9

0.44 1.04 1.02

.08 .15 .30

.31 .58 .89

0.30–0.58 0.78–1.31 0.46–1.58

18 63 37

Note. NE = number of effect size estimates; ∆ = average effect size estimates using Cohen’s delta; SE = standard error of effect size estimate; SD = standard deviation in effect sizes across studies; CI = 90% lower and upper bound confidence interval; FSN = fail-safe N or number of studies needed to decrease effect size below .20.

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The relatively large number of studies that used ratings as a basis for assessing creative achievement permitted an examination of the effects of rater type. The data presented in Table 3 indicate that studies based on supervisory (∆ = .55, SE = .10), peer (∆ = .37, SE = .08), and multiple source (∆ = .56, SE = .14) ratings typically provide smaller effect size estimates than do studies based on self-ratings (∆ = .97, SE = .16). Although this difference in effect sizes might be attributed to the inflationary bias commonly observed in self ratings, the sizable effects obtained for experimenter ratings (∆ = 1.08, SE = .25) suggest that the relatively small effects obtained for supervisory and peer evaluations may be due to range restriction in that supervision and peer evaluations are often obtained in samples in which most people evidence above average creativity. Not only were differences observed as a function of rater type, the level at which creative achievement was evaluated also resulted in differences in the obtained effect size estimates. Although climate exerted sizable effects when measures of creative achievement were obtained at the individual level (∆ = .44, SE = .08), larger climate effects were obtained in studies that assessed creative achievement at the group (∆ = 1.02, SE = .30) level. Apparently, climate is an especially important influence on creative achievement when performance is contingent on interactions among individuals and their collective perceptions of the work and work environment. Nonetheless, even at an individual level, climate was still found to exert nontrivial effects on creative achievement. Internal Validity Although it seems clear that climate can exert noteworthy effects on creative achievement, effects that apparently evidence some generality across different measures of creativity and innovation, the question remains as to whether these effects might be an artifact of study design. Some initial answers to those questions may be found in the results obtained in the internal validity analyses. Table 4 presents a summary of the results obtained in these analyses. In keeping with the observations of Scott et al. (2004), it was found that publication source was related to differences in observed effect size with larger effect sizes being reported in peer reviewed (∆ = .86,

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SE = .11) than in nonpeer reviewed (∆ = .59, SE = .15) publications. This difference, of course, may reflect the tendency of authors to submit manuscripts to peer reviewed journals and the tendency of editors to accept manuscripts that produce relatively strong effects. Along similar lines, studies that provided reliability estimates (∆ = .83, SE = .13) tended to produce larger effects than did studies that failed to report reliability estimates (∆ = .69, SE = .14). Apparently, larger effects are obtained when investigations are more careful with regard to the conduct of analyses. Although these effects are of some interest, a broader point should be borne in mind. Sizable climate effects were obtained in nonpeer reviewed studies and studies that failed to provide reliability coefficients. This point is reiterated by the failure of large differences in effect size to emerge in contrasting studies on the basis of author education, doctorate (∆ = .77, SE = .11) versus nondoctorate (∆ = .82, SE = .16), and data-collection method, anonymous (∆ = .77, SE = .21) versus nonanonymous (∆ = .66, SE = .09). Examination of effect sizes broken down by sample size revealed a somewhat larger difference, however, with studies based on larger samples producing a smaller effect size (∆ = .67, SE = .13) than did studies based on smaller samples (∆ = .89, SE = .15). Although these differences in effect size by sample size are notable, it appears, taken as a whole, that poor study design does not provide a complete explanation for the apparent effects of climate on creative achievement. In this regard, however, it is important to bear in mind the results obtained in contrasting studies based on standardized climate inventories such as Amabile’s KEYS (Amabile et al., 1996) West’s TCI (Anderson & West, 1996) and Ekvall’s CCQ (Ekvall, 1996) with locally developed inventories. Studies based on well-developed standardized instruments (∆ = 1.00, SE = .22) of the sort described above typically produced far larger effects than did studies that were based on locally developed instruments (∆ = .63, SE = .09). Not only does this finding recommend the use of well-developed, well-researched instruments in studies of climate, it suggests that the widespread use of locally developed inventories may have induced a conservative bias in studies seeking to assess the relationship between climate and achievement. It was also found that differences across studies in the theoretical approach used to develop the climate inven-

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Climate

Table 4. Internal Validity Influences on the Effects of Climate

Sample Size Above Average Below Average Source Peer Reviewed Nonpeer Reviewed Author Education Doctorate Nondoctorate Data Collection Anonymous Nonanonymous Analyses Reliability Estimates Provided Reliability Estimates Not Provided Nature of Climate Measure Standardized Inventory Locally Developed Inventory Approach Used in Measure Development Psychological/Dispositional Motivational Team Organizational Mixed

NE

∆

SE

SD

CI

21 21

.67 .89

.13 .15

.58 .67

0.45–0.89 0.64–1.14

49 72

37 5

.86 .59

.11 .21

.65 .48

0.62–0.98 0.14–1.05

111 10

35 7

.77 .82

.11 .16

.66 .43

0.55–0.96 0.51–1.15

100 2

10 15

.77 .66

.21 .09

.65 .36

0.40–1.15 0.49–0.82

24 35

27 15

.83 .69

.13 .14

.59 .53

0.61–1.06 0.44–0.98

85 37

14 27

1.00 .63

.22 .09

.81 .47

0.62–1.39 0.48–0.79

56 58

4 11 11 8 8

1.07 1.01 .85 .34 .65

.46 .20 .22 .06 .12

.93 .66 .77 .18 .35

–0.02–2.17 0.65–1.38 0.45–1.25 0.27–0.46 0.42–0.88

17 45 36 6 18

FSN

Note. NE = number of effect size estimates; ∆ = average effect size estimates using Cohen’s delta; SE = standard error of effect size estimate; SD = standard deviation in effect sizes across studies; CI = 90% lower and upper bound confidence interval; FSN = fail-safe N or number of studies needed to decrease effect size below .20.

tory resulted in differences in effect size. Studies that used a psychological/dispositional model (∆ = 1.07, SE = .46), a motivational model (∆ = 1.01, SE = .20), or a team performance model (∆ = .86, SE = .22) in developing climate questions typically produced stronger effects than did studies that used an organizational (∆ = .34, SE = .06) or mixed (∆ = .65, S.E = .12) model. Apparently, creative achievement is more strongly related to individual perceptions of personally significant local events than did general organizational influences such as reward structures or organizational learning. External Validity It seems clear that climate is related to creative achievement, especially when climate assessments are based on well-developed measures examining perceptions of the local environment. What is unclear at this point is the generality of these effects across populations and settings. Table 5, however, presents the re-

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sults obtained in contrasting obtained effect size estimates with respect to variables bearing on population and setting. Broadly speaking, the results obtained in the analysis indicate that the effects of climate on creative achievement evidence some generality across population and setting. Because the majority of the studies used samples of mixed age and gender, it is difficult to draw strong conclusions about the generality of climate effects across men and women or younger and older workers. With this caveat in mind, however, it should be noted that unusually large effects were obtained in the three studies examining older (over 40) workers (∆ = 1.20, SE = .48) rather than a typical mixed sample study (∆ = .76, SE = .10). One explanation for these effects is that older workers, by virtue of experience and the availability of broader frames of reference, are especially sensitive to climate. However, it is possible that these effects are an artifact of the relatively small number of studies that focus on older workers. A somewhat stron-

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Table 5. External Validity Influences of the Effects of Climate

Gender of Sample 80% Male 80% Female Mixed Age of Sample 80% Over 40 80% Under 40 Mixed Educational Level Professional Nonprofessional Mixed Country Type Industrialized Nonindustrialized Organization Type For Profit Not for Profit Setting Research and Development Manufacturing Service Mixed

NE

∆

SE

SD

7 1 34

0.75 0.41 0.80

.24 – .11

.64 – .64

0.28–1.22 – 0.61–0.98

19 – 102

3 1 38

1.20 0.26 0.76

.48 – .10

.82 – .61

–0.18–2.60 – 0.59–0.93

15 – 106

26 4 12

0.82 0.41 0.80

.14 .06 .15

.71 .12 .52

0.58–1.06 0.27–0.56 0.54–1.07

81 4 36

38 3

0.77 1.03

.10 .29

.64 .50

0.59–0.94 0.18–1.87

108 12

34 7

0.77 0.75

.11 .19

.66 .51

0.58–0.96 0.37–1.12

97 19

16 12 3 11

0.58 0.74 0.40 1.21

.10 .14 .11 .27

.40 .49 .18 .89

0.40–0.75 0.49–0.99 0.09–0.70 0.74–1.70

30 32 3 56

CI

FSN

Note. NE = number of effect size estimates; ∆ = average effect size estimates using Cohen’s delta; SE = standard error of effect size estimate; SD = standard deviation in effect sizes across studies; CI = 90% lower and upper bound confidence interval; FSN = fail-safe N or number of studies needed to decrease effect size below .20.

ger pattern of effects was obtained for educational level with studies conducted in professional (∆ = .82, SE = .14) and mixed professional and nonprofessional (∆ = .80, SE = .15) samples producing stronger effects than studies conducted in non-professional (∆ = .41, SE samples. This pattern of findings is, of course, consistent with greater value placed on creativity and climate in professional settings. With regard to country and culture, it is apparent that most climate studies have been conducted in Western, industrialized countries evidencing an individualistic cultural orientation. Although studies conducted in individualistic (∆ = .74, SE = .12) and collectivist (∆ = .76, SE = .11) cultures produced similar effects, it was found that stronger relationships were obtained between climate and creative achievement in nonindustrialized (∆ = 1.03, SE = .24) as opposed to industrialized (∆ = .77, SE = .10) countries. However, some caution is necessary in interpreting these effects given the small number of studies conducted in nonindustrialized countries. In this regard, however, it

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should be borne in mind that regardless of country or culture, climate was again found to be related to creative achievement. Not only do the effects of climate appear to generalize across populations but also they were found to generalize across settings. Similar effect sizes were obtained for climate studies conducted in for-profit (∆ = .77, SE = .11) and nonprofit (∆ = .75, SE = .14) organizations. Moreover, sizable, and nontrivial, effects were obtained for studies conducted in research and development (∆ = .58, SE = .10), manufacturing, (∆ = .74, SE = .14), service (∆ = .40, SE = .11), as well as mixed (∆ = 1.21, SE = .40) settings. The relatively small effect size observed in service settings is not simply a function of the number of available studies, it is possible that these effects may be due to restrictions on the range of feasible innovations (Florida, 2003). The relatively strong effects obtained for studies conducted in mixed settings, in service sector jobs, may reflect the importance of local climate in large diversified organizations.

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Climate

Job Moderators Taken as a whole, it appears that climate is related to creative achievement with these effects evidencing some generality across population and setting. Nonetheless, it is possible that the effects of climate on creative achievement might be moderated by a number of variables operating at the job, group, organizational, and environmental levels (Anderson et al., 2003). Table 6 presents the results obtained in examining job-level moderators of the relationship between climate and creative achievement. Not all studies provided information that permitted coding of the job-level moderators—a finding that held across all of the various types of moderators under consideration. For example, relatively few studies indicated the stage of innovation under consideration. It is interesting to note, however, that even late stage efforts produced nontrivial effects (∆ = .64, SE = .13). Studies were more likely to report the type of innovation than the innovation stage. However, sizable effects were ob-

tained for product (∆ = .63, SE = .12), process (∆ = .84, SE = .17), and mixed product-process efforts (∆ = .96, SE = .30). The especially large effect size obtained from mixed product-process studies may reflect the fact that climate becomes more important in complex, multifaceted creative efforts. In keeping with this observation, it was found that two key job characteristics influenced the relationship between climate and creative achievement. More specifically, larger effect sizes were obtained when the generation of new ideas and products was a fundamental requirement for the job (∆ = .71, SE = .10) than when the generation of new ideas and products was not a fundamental requirement of the job (∆ = .42, SE = .09). Additionally, when the job was structured to allow people substantial discretion into how to go about accomplishing the work (∆ = 1.51, SE = .58) stronger climate effects were obtained than when the job was structured such that only moderate (∆ = .75, SE =.15) or low (∆ = .44, SE = .003) levels of discretion were al-

Table 6. Job Level Moderator Variables Influences on Effect Size

Creativity Required Generation Required Generation Not Required Kind of Innovation Product Process Mixed Stage of Innovation Early Mid Late Amount of Discretion on Job Low Medium High Rewards for Creative Performance Yes No Type of Rewards Provided Intrinsic Extrinsic Job Satisfaction Low Medium High

NE

∆

SE

SD

CI

FSN

27 4

0.71 0.42

.10 .09

.51 .19

0.54–0.87 0.20–0.65

69 4

16 13 9

0.63 0.84 0.96

.12 .17 .30

.50 .63 .91

0.41–0.85 0.57–1.14 0.40–1.53

34 42 34

1 – 3

0.52 – 0.64

– – .13

– – .22

– – 0.27–1.02

– – 7

2 11 4

0.44 0.75 1.51

.03 .15 .58

.05 .58 1.16

0.24–0.64 0.53–1.04 0.14–2.87

2 47 26

7 2

0.40 0.54

.13 .38

.33 .54

0.15–0.64 –1.87–2.96

7 3

3 2

0.51 0.27

.22 .13

.39 .19

–0.15–1.16 –0.57–1.12

5 1

2 5 2

1.47 0.96 0.60

.67 .38 .32

.95 .85 .45

–2.76–5.66 0.16–1.77 –1.43–2.63

13 14 4

Note. NE = number of effect size estimates; ∆ = average effect size estimates using Cohen’s delta; SE = standard error of effect size estimate; SD = standard deviation in effect sizes across studies; CI = 90% lower and upper bound confidence interval; FSN = fail-safe N or number of studies needed to decrease effect size below .20.

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lowed. Thus, when creativity and innovation are required on a job, and people are granted the discretion needed to do creative work, climate measures are more strongly related to creative achievement. Although only a rather small number of studies indicated the availability and type of rewards provided for creative efforts, these moderators produced a consistent pattern of effects. More specifically, stronger effects were obtained when a) rewards were not provided (∆ = .54, SE = .38) than when rewards were provided (∆ = .40, SE = .13) and when intrinsic rewards were provided (∆ = .51, SE = .22) than when extrinsic rewards were provided (∆ = .27, SE = .13). These findings are, of course, broadly consistent with the observations of Collins and Amabile (1999) concerning the inhibitory effects of extrinsic rewards on motivation in creative efforts. However, it is also possible that by calling attention to contingencies rather than to interactions, extrinsic rewards undermine the relationship between climate and creative achievement. At first glance, the results obtained in contrasting studies providing information about job satisfaction levels may seem surprising. More specifically, low (∆ = 1.47, SE = .67) and medium (∆ = .96, SE = .38) levels of satisfaction were associated with stronger effect size than were high levels (∆ = .60, SE = .32) of satisfac-

tion. Bearing in mind the findings of Zhou and George (2001) concerning the motivational effects of dissatisfaction on creativity, however, it seems likely that this pattern of findings reflects an increase in motivation such that the investment in creativity arising from dissatisfaction results in the emergence of a stronger relationship between climate and creative achievement. Group Moderators Table 7 presents the results obtained in examining the group level moderators. As may be seen, a requirement for people to work with others did not appear to moderate the relationship between climate and creative achievement. Thus studies in which people were (∆ = .70, SE = .13) or were not (∆ = .73, SE = .13) required to work with others produced similar effects. Moreover, studies indicating the degree of interdependence involved in the work, low (∆ = .71, SE = .23), medium (∆ = .64, SE = .04), and high (∆ = .60, SE = .20), all produced similar effects. Although requirements for team work did not moderate the relationship between climate and creative achievement, certain characteristics of the group and its pattern of interaction did produce some potentially interesting moderator effects. In keeping with the ob-

Table 7. Group Level Moderator Variable Influences on Effect Size

Teamwork Required Work in Teams Do Not Work in Teams Team Size Small (2–5) Medium (6–9) Large (10–14) Very Large (15+) Degree of Interdependence Low Medium High Degree of Cohesion Low Medium High

NE

∆

SE

SD

CI

FSN

20 6

.70 .73

.13 .13

.56 .31

0.48–0.92 0.48–0.98

50 16

3 4 4 1

.53 .86 .72 .14

.14 .13 .29 –

.25 .24 .58 –

0.12–0.94 0.51–1.89 0.04–1.41 –

5 12 10 –

4 12 6

.71 .64 .60

.46 .33 .49

.46 .33 .49

0.17–1.25 0.47–0.81 0.20–1.00

10 26 12

1 5 1

.93 .55 .16

– .14 –

– .14 –

– 0.4–0.69 –

– 9 –

Note. NE = number of effect size estimates; ∆ = average effect size estimates using Cohen’s delta; SE = standard error of effect size estimate; SD = standard deviation in effect sizes across studies; CI = 90% lower and upper bound confidence interval; FSN = fail-safe N or number of studies needed to decrease effect size below .20.

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servations of Curral et al. (2001), it was found that climate effects were weaker in the single study examining very large groups of 15 or more (∆ = .14) than in the small (∆ = .53, SE = .14), medium (∆ = .86, SE = .13), and large (∆ = .72, SE = .29) groups. The findings obtained for cohesion are also consistent with the earlier observations of Allen and Cohen (1964) indicating that high levels of cohesion can induce a “not invented here” syndrome. Because this syndrome leads people to discount creativity, it was not surprising that climate produced stronger relationships with creative achievement in groups of low (∆ = .93) and moderate (∆ = .55, SE = .06) cohesion than in highly cohesive (∆ = .16) groups. Although these findings must be interpreted cautiously given the number of studies involved, they do point to the value of studies examining group process as a moderator of climate effects.

Organizational Moderators A somewhat stronger pattern of relationships emerged in examining the influence of organizational variables on the relationship between climate and creative achievement. Table 8 summarizes the results obtained in these analyses. As might be expected on the basis of the findings obtained in earlier studies (Russell & Russell, 2002), climate produced stronger relation-

ships with indices of creative achievement in organizations evidencing a horizontal (∆ = 1.17, SE = .66) as opposed to a vertical (∆ = 29, SE = .14) structure. Apparently, centralized control undermines the effects of local climate and perhaps restricts creativity and innovation. In keeping with this observation, stronger effects of climate on creative achievement were observed in low (∆ = 1.15, SE = .43) capital intensity organizations as opposed to organizations of moderate (∆ = .66, SE = .20) and high (∆ = .73, SE = .13) capital intensity—a finding which suggests that prior investments may limit the feasibility of pursing new ideas and thus restrict, albeit not eliminate, the effects of a creative climate. The effects observed for organizational wealth, however, remind us that size and resources should not be arbitrarily associated with capital intensity. In fact, high levels of organizational wealth (∆ = .84, SE = .10) were associated with stronger climate effects than were medium levels (∆ = .61, SE = .10) and low levels (∆ = .75, SE = .21) of wealth. Apparently, the availability of resources allows people to pursue the ideas arising from a creative climate. Given the need for ideas, and the tendency of creative achievement to arise from, and to be recognized in, organizations relying on knowledge-based work, it was not surprising that climate was more strongly related to creative achievement in orga-

Table 8. Organizational Level Moderator Variable Influences on Effect Size

Organizational Wealth Low Medium High Degree of Professionalism Low Medium High Capital Intensity Low Medium High Structure Vertical Horizontal Mixed

NE

∆

SE

SD

CI

FSN

4 15 15

0.75 0.61 084

.21 .61 .84

.43 .39 .76

0.24–1.26 0.43–0.78 0.50–1.19

11 31 48

4 6 25

0.50 0.75 0.81

.04 .15 .15

.07 .37 .73

0.41–0.59 0.45–1.06 0.50–1.06

6 17 76

5 11 20

1.15 0.66 0.73

.43 .20 .13

.87 .65 .59

0.22–2.08 0.31–1.02 0.50–0.96

24 25 53

2 3 3

0.29 1.17 0.76

.14 .66 .16

.20 1.15 .27

–0.63–1.20 –0.76–3.10 0.30–1.21

1 15 8

Note. NE = number of effect size estimates; ∆ = average effect size estimates using Cohen’s delta; SE = standard error of effect size estimate; SD = standard deviation in effect sizes across studies; CI = 90% lower and upper bound confidence interval; FSN = fail-safe N or number of studies needed to decrease effect size below .20.

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nizations evidencing high (∆ = .81, SE = .15) or medium (∆ = .75, SE = .15) levels of professionalization than those with low (∆ = .50, SE = .04) levels of professionalization.

mate, under conditions of change and performance pressure.

Discussion Environmental Moderators Table 9 presents the results obtained for the environmental moderators. As expected, a stronger relationship was observed between climate and creative achievement when success in the market required the development and fielding of innovative new products (∆ = .73, SE = .14) than when it did not (∆ = .53, SE = .14). More centrally, high turbulence (∆ = 1.66, SE = .76), as opposed to conditions of medium (∆ = .70, SE = .24) and low (∆ = .86, SE = .14) turbulence, high competitive pressure (∆ = 1.24, SE = .42), as opposed to conditions of medium (∆ = .63, SE = .21) and low (∆ = .75, SE = .21) competitive pressure, and high production pressure (∆ = .92, SE = .34), as opposed to conditions of medium (∆ = .66, SE = .14) and low (∆ = .58, SE = .14) production pressure, resulted in a stronger relationship between climate and creative achievement. Thus there appears to be some support for Janssen et al.’s (2004) observations concerning the tendency of organizations to place more value on creative ideas, and thus to act on the outcomes of a creative cli-

In considering the conclusions flowing from the present study, the reader should bear in mind certain limitations. To begin, in the present study we have examined effect size in terms of the average correlations produced by the climate dimensions examined. This point is of some importance because the joint effects of the climate dimensions under consideration were not examined, and these multivariate relationships can be expected to be larger than the univariate relationships of interest in the present effort. Although it would have been desirable to examine these multivariate relationships, the tendency of prior studies to focus on univariate relationships in reporting results effectively prohibited an analysis along these lines. It should also be noted that the present study was based on traditional meta-analytic procedures (Rosenthal and DiMatteo, 2001). Thus no attempt was made herein to correct observed relationships for unreliability or to account for range restriction. Although these corrections might have resulted in a better estimate of the true relationship between climate dimen-

Table 9. Environmental Level Moderator Variable Influences on Effect Sizes

Competition Based on Innovation No Yes Turbulence Low Medium High Competitive Pressure Low Medium High Production Pressure Low Medium High

NE

∆

SE

SD

CI

FSN

5 19

0.53 0.73

.19 .14

.43 .62

0.12–0.94 0.45–0.94

8 48

5 6 2

0.86 0.70 1.66

.14 .29 .76

.31 .72 1.07

0.57–1.16 0.11–1.30 –3.13–6.43

17 15 15

4 4 5

0.75 0.63 1.29

.21 .21 .42

.43 .64 .93

0.24–1.26 0.23–1.03 0.40–2.17

11 14 27

3 18 5

0.58 0.66 0.92

.14 .14 .39

.33 .59 .88

0.02–1.14 0.43–0.90 0.08–1.75

6 41 18

Note. NE = number of effect size estimates; ∆ = average effect size estimates using Cohen’s delta; SE = standard error of effect size estimate; SD = standard deviation in effect sizes across studies; CI = 90% lower and upper bound confidence interval; FSN = fail-safe N or number of studies needed to decrease effect size below .20.

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sions and creative achievement after factoring out error (Mendoza, Bard, Mumford, & Ang, 2004; Schmidt & Hunter, 1996), they would not have provided an estimate of climate effects as they are evident in measures of varying quality—a point of some concern in the present study. More centrally, the within-group agreement measures needed to make these corrections are not commonly reported. In this study, we made an attempt to draw relatively strong conclusions about the likely effects of climate. As a result, relatively stringent criteria were applied in selecting studies that included dimensional level reporting and application of criteria directly relevant to creative achievement. Although application of relatively stringent selection standards is recommended if strong conclusions are to be drawn in a meta-analysis, application of these criteria did result in the loss of some studies—typically studies that (a) reported only overall findings without dimensional level relationships or (b) applied criteria not explicitly tied to creativity and innovation. Thus the findings obtained in the present effort were based on only 42 studies. Although 42 studies is not an atypically small sample in meta-analytic investigations, it is also true that some changes in our overall findings might occur as more studies become available. Unlike studies conducted in other areas, for example training and evaluation (Scott et al., 2004), climate studies vary widely in the nature and amount of material reported, which bears on the context in which the study was conducted. As a result, moderators were coded only if information bearing on a variable was explicitly reported in the study description. Although application of this kind of coding procedure reduces inferential errors, in some instances it limited the number of studies available that might have been used to draw conclusions about the effects of a potential moderator variable. As a result, in cases in which relatively few pertinent studies were available, or could be coded on the basis of the study description, some caution is called for in drawing strong conclusions about the likely effects of these moderators. Finally, it should be recognized that not all potential moderators of the relationship between climate and creative achievement could be examined in the present study. For example there is reason to suspect that leadership might moderate climate’s effects on creative achievement (West et al., 2003). However, the study descriptions commonly provided in climate studies do

Creativity Research Journal

not permit an adequate assessment of leader behavior. Thus not all, and perhaps a number, of the moderator variables that might influence the relationship between climate and creative achievement were, or could be, examined. Moreover, interactions among these moderators both within and across levels were not examined. Even bearing these caveats in mind, we believe that the results obtained in the present study have some noteworthy implications for understanding the relationship between climate and creative achievement. Perhaps the most straightforward, and most important, conclusion that can be drawn from the present effort pertains to the relationship between climate and creative achievement. Climate assessments were found to evidence a sizable, nontrivial relationship with creative achievement across studies. These effects were found to hold for both subjective appraisals and for more objective appraisals focusing on the production of innovative products. Moreover, though the various job, group, organizational, and environmental moderators accounted for variance in the magnitude of obtained effect sizes, in no case was it found that the operation of a given moderator reduced the effect size below the level of practical significance. Given these findings, and the obtained effect size estimates, which were substantial in the overall analysis, it seems reasonable to conclude that climate is, in fact, strongly related to creative achievement across a number of contexts and criteria. This conclusion concerning the strong, apparently rather general, relationships between climate and creative achievement should be evaluated in light of another finding that emerged in the present effort. In contrasting measures with respect to the quality of development, a comparison implied by our contrast of standardized and locally developed measures, it was found that studies based on well-developed standardized measures produced stronger effects, substantially stronger effects, than did studies based on locally developed measures. This finding is important not only because it underscores the importance of applying well-developed measures in climate studies (Mathisen & Einarsen, 2004), it indicates that our estimates of the relationship between climate and creative achievement may be somewhat conservative. The strong general relationship between climate and creative achievement, however, brings to fore a substantive question. Exactly what dimensions, or aspects, of climate are especially important? Given the plethora of dimensions found in the climate literature

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(Hunter et al., 2005), and the differences in the underlying models used to specify these dimensions (Hunter et al., 2005), it has, in the past, proven difficult to answer this question with any real certainty. The results obtained in the present study, however, do appear to provide at least an initial answer to this question. More specifically, in contrasting the effect sizes obtained for different dimensions, we found that challenge, intellectual stimulation, and positive collegial exchange produced particularly strong relationships. Apparently, a work environment that presents people with meaningful engaging work that stimulates thinking and an exchange of thoughts around significant issues is critical if one wishes to encourage creativity and innovation (West, 2002). In fact, this observation seems consistent with two other findings obtained in the present study. First, because a creative climate requires interpersonal intellectual exchange around challenging tasks, or missions, it is not surprising that climate, shared perceptions bearing on the nature of these exchanges, would exert stronger effects on group- and organizational-level measures than would individual-level measures of creative achievement. Second, because a creative climate entails engaging people in an intellectual exchange with respect to challenging tasks, it is not surprising that climate measures based on psychological/dispositional (e.g., Ekvall, 1996), motivational (e.g., Amabile & Conti, 1999), and team (e.g., Anderson & West, 1996) concepts typically produced sizeable relationships. These observations about interpersonal intellectual engagement in challenging missions have some noteworthy implications for understanding the kind of climate models most likely to prove useful in accounting for environmental influences on creativity. More specifically, these findings suggest that motivationally based systems such as Amabile’s (e.g., Amabile et al., 1996; Amabile & Gryskiewicz, 1989), dispositionally based systems such as Ekvall’s (e.g., Ekvall, 1996; Ekvall & Ryhammer, 1999), and team-based systems such as West’s (e.g., Anderson & West, 1988; West et al., 2003) are more likely to provide viable climate assessments than are organizationally based systems such as those proposed by Abbey & Dickson (1983) and Mossholder & Dewhurst (1980). These observations with respect to the importance of interpersonal engagement in intellectually challenging missions, however, should not be taken to imply

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that dimensions such as support, resources, and autonomy are not of concern in attempts to understand the kind of environment that makes creative achievement possible. In the present study these dimensions, in fact, produced nontrivial, actually sizable, relationships with regard to indices of creative achievement. Rather, these observations suggest that we should not lose sight of the fundamental importance of interpersonal intellectual engagement in challenging tasks, or missions, even as we extend this core to take into account environmental attributes, such as support, resources, and autonomy, that lead people to believe that creative work is possible and, in fact, valued. Of course, one reason climate dimensions such as resources and autonomy stand out in our minds is that they represent attributes of the environment that managers can easily, or at least reasonably easily, do something about. Managers can make a decision about how much time and resources they will allocate to a given effort. They can take actions to encourage participation and to avoid overly close supervision. Although actions of this sort may well prove valuable in encouraging creativity (Amabile, Hadley, & Kramer, 2002; Redmond, Mumford, & Teach, 1993), the importance of interpersonal intellectual engagement suggests that in applying climate assessments to guide organizational change efforts, we may need to consider a broader range of interventions—for example, building concepts of creative self-efficacy (Tierney & Farmer, 2002), assembling teams of requisite intellectual diversity (Dunbar, 1995), and defining missions that both challenge people and bring together different interests (Mumford, Scott, Gaddis, & Strange, 2002). In considering interventions along these lines, however, it is important to bear in mind the effects obtained in the various moderator variable analyses. Given the effects of the moderators, interventions of the sort described above are most likely to prove effective in professional populations or in settings in which people are (a) given some discretion about how they go about doing their work and (b) dissatisfied with “business as usual.” Moreover, although caution is called for in drawing inferences with respect to the group-level moderators, the obtained effects suggest that these interventions are most likely to prove effective when undue size and a lack of openness have not induced dysfunctionality in the day to day pattern of team interactions.

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In addition to indicating the kind of local conditions in which climate interventions are likely to prove effective in enhancing creative achievement, the results obtained in the present study indicate that broader organizational and environmental variables will moderate the relationship between climate and creative achievement. If prior investments or a lack of resources make it difficult to respond to creative ideas, the effects of climate on creative achievement will be attenuated (Nystrom et al., 2002; Sharma, 1999). Moreover, structures that block the flow of ideas and effective evaluation of these ideas will also attenuate the impact of climate on creative achievement (O’Connor, 1998)—a point attested to by our findings with respect to the use of vertical as opposed to horizontal structures and professionalization. Thus, although climate may be a local phenomenon, the outcomes of climate, and climate interventions, will be contingent on the nature of the organization in which ideas must be developed, appraised, and implemented (Anderson et al., 2003; Janssen et al., 2004). Not only do the effects of climate appear to depend on certain characteristics of the organization but also the organization’s external operating environment appears to be a relatively powerful moderator of the effects of climate on creative achievement. More specifically, climate proved to be more strongly related to creative achievement when innovation was necessary for organizational success, and perhaps survival, in a turbulent environment characterized by high competitive pressure and substantial production pressure. As Janssen et al. (2004) have pointed out, external demand places a premium on innovation leading climate to have a more powerful influence on creative achievement. The problem here, however, lies in the fact that under these conditions it may prove particularly difficult to develop and to maintain the kind of climate likely to promote creativity and innovation. This paradox, and paradox is common in studies of organizational innovation (Sternberg, 2005), points to the need for studies examining cross-level and multilevel influences on creative climate and creative achievement (Anderson et al., 2003), especially studies examining the development and maintenance of a creative climate under conditions of high demand. In studies along these lines, however, it would be useful to take climate research a step further. Traditionally, climate studies (e.g., Abbey & Dickson, 1983; Amabile et al., 1996; Ekvall & Ryhammer, 1999;

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Lapierre & Giroux, 2003) have applied correlational or group contrast methods in which climate is assumed to cause creativity. Systematic causal modeling studies and “field” experiments that would provide a more unequivocal demonstration of the causal effects of climate on creativity and innovation have been rare. It is hoped that the present study—through identification of moderators operating at the job, at the group, organizational, and environmental levels—will provide a foundation for the kind of experimental and causal modeling studies that would allow development of more sophisticated theories specifying exactly how a climate for creativity emerges and operates to shape creativity and innovation in organizational settings.

References References marked with an asterisk indicate studies included in the meta-analysis. *Abbey, A., & Dickson, J. (1983). R&D work climate and innovation in semiconductors. Academy of Management Journal, 25, 362–368. Abra, J. (1994). Collaboration in creative work: An initiative for investigation. Creativity Research Journal, 8, 205–218. Agrell, A., & Gustafson, R. (1994). The team climate inventory (TCI) and group innovation: A psychometric test on a Swedish sample of work groups. Journal of Occupational and Organizational Psychology, 67, 143–151. *Agrell, A., & Gustafson, R. (1994). The team climate inventory (TCI) and group innovation: A psychometric test on a Swedish sample of work groups. Journal of Occupational and Organizational Psychology, 67, 143–151. Allen, T. J., & Cohen, S. I. (1969). Information flow in research and development laboratories. Administrative Science Quarterly, 14, 12–19. Amabile, T. M. (1997). Motivating creativity in organizations: On doing what you love and loving what you do. California Management Review, 40, 39–58. *Amabile, T. M., & Conti, R. (1999). Changes in the work environment for creativity during downsizing. Academy of Management Journal, 42, 630 –641. Amabile, T. M., & Gryskiewicz, N. D. (1989). The creative environment scales: Work environment inventory. Creativity Research Journal, 2, 231–253. *Amabile, T. M., Conti, R., Coon, H., Lazenby, J., & Herron, M. (1996). Assessing the work environment for creativity. Academy of Management Journal, 39, 1154–1184. Amabile, T. M., Hadley, C. N., & Kramer, S. J. (2002). Creativity under the gun. Harvard Business Review, 80, 52–61. Amabile, T. M., Shatzel, E. A., Moneta, G. B., & Kramer, S. J. (2004). Leader behaviors and the work environment for creativity: Perceived leader support. Leadership Quarterly, 15, 5–33.

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*Anderson, N. R., & West, M. A. (1998). Measuring climate for work group innovation: Development and validation of the team climate inventory. Journal of Organizational Behavior, 19, 235–258. Anderson, N., De Dreu, C. K., Nijstad, B. A. (2004). The routinization of innovation research: a constructively critical review of the state-of-the-science. Journal of Organizational Behavior, 25, 147–173. *Baer, M., & Frese, M. (2003). Innovation is not enough: Climates for initiative and psychological safety, process innovations, and firm performance. Journal of Organizational Behavior, 24, 45–68. *Bain, P. G., Mann, L., & Pirola-Merlo, A. (2001). The innovation imperative: The relationship between team climate, innovation, and performance in research and development teams. Small Group Research, 32, 55–73. Barron, F., & Harrington, D. M. (1981). Creativity, intelligence, and personality. Annual Review of Psychology, 32, 439–476. Basadur, M. (1997). Organizational development interventions for enhancing creativity in the workplace. Journal of Creative Behavior, 31, 59–72. *Bommer, M., & Jalajas, D. (2002). The innovation work environment of high-tech SMEs in the USA and Canada. R & D Management, 32, 379–386. Borrill, C. S., Carletta, J., Carter, A. J., Dawson, J., Garrod, S., Rees, A., et al. (2000). The effectiveness of health care teams in the National Health Service. Birmingham, England: Aston Centre for Health Service Organization Research Borrill, C., West, M. A., Shapiro, D., & Rees, A. (2000). Team working and effectiveness in health care. British Journal of Health Care, 6, 364–371. *Brendle, M. G. (2001). Personality and company culture: Important contributions to innovation and a source of competitive advantage for small businesses. Unpublished doctoral dissertation. Bullinger, H. J., Auernhammer, K., & Gomeringer, A. (2004). Managing innovation networks in the knowledge-driven economy. International Journal of Production Research, 42, 3337–3344. *Bunce, D., & West, M. A. (1995). Self perceptions and perceptions of group climate as predictors of individual innovation at work. Applied Psychology: An International Review, 44, 199–215. *Burningham, C., & West, M. A. (1995). Individual, climate, and group interaction processes as predictors of work team innovation. Small Group Research, 26, 106–117. *Caldwell, D. F., & O’Reilly III, C. A. (2003). The determinants of team-based innovation in organizations: The role of social influence. Small Group Research, 34, 497–517. Cardinal, L. B., & Hatfield, D. E. (2000). Internal knowledge generation: The research laboratory and innovative productivity in the pharmaceutical industry. Journal of Engineering Technology Management, 17, 247–271. *Choi, J. N. (2004). Person-environment fit and creative behavior: Differential impacts of supplies-values and demands-abilities versions of fit. Human Relations, 57, 531–552. Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35, 128–152.

88

Collins, M. A., & Amabile, T. M. (1999). Motivation and creativity. In R. J. Sternberg (Ed.), Handbook of creativity (pp. 297–312). Cambridge, England: Cambridge University Press. Cooke, R. A., & Rousseau, D. M. (1988). Behavioral norms and expectations: A quantitative approach to the assessment of organizational culture. Group & Organization Studies, 13, 245–273. Curral, L. A., Forrester, R. H., Dawson, J. F., & West, M. A. (2001). It’s what you do and the way that you do it: Team task, team size, and innovation-related group processes. European Journal of Work and Organizational Psychology, 10, 187–204. Damanpour, F. (1996). Organizational complexity and innovation: Developing and testing multiple contingency models. Management Science, 42, 693–722. Damanpour, F. (1991). Organizational innovation: A meta-analysis of effects of determinants and moderators. Academy of Management Journal, 34, 555–590. Dunbar, K. (1995). How do scientists really reason: Scientific reasoning in real-world laboratories. In R. J. Sternberg & J. E. Davidson (Eds.), The nature of insight (pp. 365–396). Cambridge, MA: MIT Press. *Ekvall, G. (1996). Organizational climate for creativity and innovation. European Journal of Work & Organizational Psychology, 5, 105–124. *Ekvall, G., & Ryhammar, L. (1999). The creative climate: Its determinants and effects at a Swedish University. Creativity Research Journal, 12, 303–310. Ericsson, K. A., & Charness, W. (1994). Expert performance: Its structure and acquisition. American Psychologist, 49, 725–747. *Ettlie, J. E. (1983). Organizational policy and innovation among suppliers to the food processing sector. Academy of Management Journal, 26, 27–44. Feist, G. J. (1999). The influence of personality on artistic and scientific creativity. In R. J. Sternberg (Ed.), Handbook of creativity (pp. 273–296). Cambridge, England: Cambridge University Press. Florida, R. (2003). The rise of the creative class. New York: Basic Books. Ford, C., & Sullivan, D. M. (2004). A time for everything: How the timing of novel contributions influences project team outcomes. Journal of Organizational Behavior, 25, 279–292. *Hashem, A. A. S. (1999). The effects of work climate on process innovation in the Saudi Arabian petrochemical industry. Unpublished doctoral dissertation. Hofstede, G. (1996). Gender stereotypes and partner preferences of Asian women in masculine and feminine cultures. Journal of Cross-Cultural Psychology, 27, 533–546. *Holahan, P. J., Aronson, Z. H., Jurkat, M. P., & Schoorman, F. D. (2004). Implementing computer technology: a multiorganizational test of Klein and Sorra’s model. Journal of Engineering and Technology Management, 21, 31–50. Howell, J. M., & Boies, K. (2004). Champions of technological innovation: The influence of contextual knowledge, role orientation, idea generation, and idea promotion on champion emergence. Leadership Quarterly, 15, 130–149. Howell, J. M., & Boies, K. (2005). Resolving some paradoxes of innovation: A cross-level interpretation. In F. J. Yammarino & F. Dansereau (Eds.), Research in multi-level issues: Volume IV (pp. 75–92). Oxford, England: Elsevier.

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Climate

Huberty, C. J. (2002). A history of effect size estimates. Educational and Psychological Measurement, 62, 227–240. Hunter, S. T., Bedell, K. E., & Mumford, M. D. (2005). Dimensions of creative climate: A general taxonomy. Korean Journal of Thinking and Problem Solving, 15, 97–116. *Hurley, R. F., & Hult, T. M. (1998). Innovation, market orientation, and organizational learning: An integration and empirical examination. Journal of Marketing, 62, 42–54. *Isaksen, S. G., & Lauer, K. J. (2002). The climate for creativity and change in teams. Creativity and Innovation Management, 11, 74–86. Isaksen, S. G., Lauer, K. J., Ekvall, G., & Britz, A. (2001). Perceptions of the best and worst climate for creativity: Preliminary validation evidence for the situational outlook questionnaire. Creativity Research Journal, 13, 171–184. James, L. R., James, L. A., & Ashe, D. K. (1990). The meaning of organizations: The role of cognition and values. In B. Schneider (Ed.), Organizational climate and culture (pp. 40–84). San Francisco, CA: Jossey-Bass. Janssen, O., Van De Vliert, E.V., & West, M. (2004). The bright and dark sides of individual and group innovation: A special issue introduction. Journal of Organizational Behavior, 25, 129–145. Keller, R. T. (2001). Cross-functional project groups in research and new product development: Diversity, communications, job stress, and outcomes. Academy of Management Journal, 44, 547–553. *Kim, J. (2000). A study of relationships among work motivation. Problem-solving style, leadership style, and team climate on creative behavior in the South Korean workplace. Unpublished doctoral dissertation. *Kitchell, S. (1995). Corporate culture, environmental adaptation, and innovation adoption: A qualitative/quantitative approach. Journal of the Academy of Marketing Science, 23, 195–205. *Lapierre, J., & Giroux, V. (2003). Creativity and work environment in a high-tech context. Creativity and Work Environment, 12, 11–23. Lubart, T. I. (2001). Models of the creative process: Past, present, and future. Creativity Research Journal, 13, 295–308. *Madjar, N., Oldham, G. R., & Pratt, M. G. (2002). There’s no place like home? The contributions of work and nonwork creativity support to employees’ creative performance. Academy of Management Journal, 45, 757–767. Mathisen, G. E., & Einarsen, S. (2004). A review of instruments assessing creative and innovative environments within organizations. Creativity Research Journal, 16, 119–140. *McCarrey, M.W., & Edwards, S. A. (1973). Organizational climate conditions for effective research scientist role performance. Organizational Behavior and Human Performance, 9, 439–459. McGaw, B., & Glass, G. (1980). Choice of the metric for effect size in meta-analysis. Educational Research Journal, 17, 325–337. Mendoza, J. L., Bard, D. E., Mumford, M. D., & Ang, S. (2004). Criterion-related validity in multiple-hurdle designs: Estimation and bias. Organizational Research Methods, 7, 418–441. *Miron, E., Erez, M., & Naveh, E. (2004). Do personal characteristics and cultural values that promote innovation, quality, and efficiency compete or complement each other? Journal of Organizational Behavior, 25, 175–199.

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*Mohamed, M. A. K. (2002). Assessing determinants of departmental innovation: An exploratory multi-level approach. Personnel Review, 31, 620–641. Mossholder, K. W., & Dewhurst, H. D. (1980). The appropriateness of management by objectives for development and research personnel. Journal of Management, 6, 145–156. Mumford, M. D. (2000). Managing creative people: Strategies and tactics for innovation. Human Resource Management Review, 10, 1–29. Mumford, M. D., & Hunter, S. T. (2005). Innovation in organizations: A multi-level perspective on creativity. In F. J. Yammarino & F. Dansereau (Eds.), Research in multi-level issues: Volume IV (pp. 11–74). Oxford, England: Elsevier. Mumford, M. D., Scott, G. M., Gaddis, B., & Strange, J. M. (2002). Leading creative people: Orchestrating expertise and relationships. The Leadership Quarterly, 13, 705–750. Mumford, M. D., Supinski, E. P., Baughman, W. A., Costanza, D. P., & Threlfall, K. V. (1997). Process-based measures of creative problem-solving skills: I. Overall prediction. Creativity Research Journal, 10, 77–85. Mumford, M. D., Whetzel, D. L., & Reiter-Palmon, R. (1997). Thinking creatively at work: Organizational influences on creative problem solving. Journal of Creative Behavior, 31, 7–17. *Nystrom, P. C., Ramamurthy, K., & Wilson, A. L. (2002). Organizational context, climate and innovativeness: Adoption of imaging technology. Journal of Engineering Technology and Management, 19, 221–247. O’Connor, G. C. (1998). Market learning and radical innovation: A cross case comparison of eight radical innovation projects. Journal of Product Innovation Management, 15, 151–131. Oldham, G. R., & Cummings, A. (1996). Employee creativity: Personal and contextual factors at work. Academy of Management Journal, 39, 607–634. Orwin, R. G. (1983). A fail-safe N for effect size. Journal of Educational Statistics, 8, 157–159 Parker, C. P., Baltes, B.B., Young, S. A., Huff, J. W., Altmann, R. A., Lacost, H. A., & Roberts, J. E. (2003). Relationships between psychological climate perceptions and work outcomes: A meta-analytic review. Journal of Organizational Behavior, 24, 389–416. *Phelan, S. G. (2001). Developing creative competence at work: The reciprocal effects of creative \thinking, self-efficacy and organizational culture on creative performance. Unpublished doctoral dissertation. *Pirola-Merlo, A., & Mann, L. (2004). The relationship between individual creativity and team creativity: Aggregating across people and time. Journal of Organizational Behavior, 25, 235–257. *Porter, C. (1984). Organizational climate and creative output in two excellent research and development divisions. Unpublished doctoral dissertation. *Ramus, C. A., & Steger, U. (2000). The roles of supervisory support behaviors and environmental policy in employee “Ecoinitiatives” at leading-edge European companies. Academy of Management Journal, 43, 605–626. Redmond, M. R., Mumford, M. D., & Teach, R. J. (1993). Putting creativity to work: Leader influences on subordinate creativity. Organizational Behavior and Human Decision Processes, 55, 120–151.

89

S. T. Hunter, K. E. Bedell, and M. D. Mumford

Rich, J. D., & Weisberg, R. W. (2004). Creating all in the family: A case study in creative thinking. Creativity Research Journal, 16, 247–259. Rickards, T., Chen, M., & Moger, S. (2001). Development of a self-report instrument for exploring team factor, leadership and performance relationships. British Journal of Management, 12, 243–251. *Robben, M. A. (1998). A study of the determinants of individual innovative behavior in a high-technology product development organization. Unpublished doctoral dissertation. Rosenthal, R. (1979). The file drawer problem and tolerance for null result. Psychological Bulletin, 86, 638–641. Rosenthal, R. (1992). Effect size estimation, significance testing, and the file-drawer problem. Journal of Parapsychology, 56, 57–58. Rosenthal, R., & DiMatteo, M. R. (2000). Meta analysis: Recent developments in quantitative methods for literature reviews. Annual Review of Psychology, 52, 59–82. Rousseau, D. M. (1988). The construction of climate in organizational research. International Review of Industrial and Organizational Psychology, 10, 139–146. Russell, R. D., & Russell, C. J. (2002). An examination of the effects of organizational norms, organizational structure, and environmental uncertainty on entrepreneurial strategy. Journal of Management, 18, 639–656. Schmidt, F. L., & Hunter, J. E. (1996). Measurement error in psychological research: Lessons from 26 research scenarios. Psychological Methods, 1, 199–223. Schneider, B., & Reichers, A. E. (1983). On the etiology of climates. Personnel Psychology, 36, 19–39. Schneider, B., Gunnarson, S. K., & Niles-Jolly, K. (1994). Creating the climate and culture of success. Organizational Dynamics, 17–29. Scott, G., Leritz, L. E., & Mumford, M. D. (2004). The effectiveness of creativity training: A quantitative review. Creativity Research Journal, 16, 361–388. Scott, S. G., & Bruce, R. A. (1994). Determinants of innovative behavior: A path model of individual innovation in the workplace. Academy of Management Journal, 37, 580–607. *Sethi, R., & Nicholson, C. Y. (2001). Structural and contextual correlates of charged behavior in product development teams. The Journal of Product Innovation Management, 18, 154–168. Sharma, A. (1999). Central dilemmas of managing innovation in large firms. California Management Review, 41, 65–85. Sternberg, R. J. (2005). “We want creativity! No we don’t!” In F. J. Yammarino & F. Dansereau (Eds.), Research in multi-level issues: Volume IV (pp. 93–104). Oxford, England: Elsevier. Sternberg, R. J., & O’Hara, L. A. (1999). Creativity and intelligence. In R. J. Sternberg (Ed.), Handbook of creativity (pp. 297–312). Cambridge, England: Cambridge University Press. Subramanian, A., & Nilakanta, S. (1996). Organizational innovativeness: Exploring the relationship between organiza-

90

tional determinants of innovation, types of innovations, and measure of organizational performance. International Journal of Management Science, 24, 631–647. *Suliman, A. M. T. (2001). Are we ready to innovate? Work climate-readiness to innovate relationship: The case of Jordan. Creativity and Innovation Management, 10, 49–59. *Tannenbaum, S. I., & Dupuree-Bruno, L. M. (1994). The relationship between organizational and environmental factors and the use of innovative human resource practices. Group & Organizational Management, 19, 171–202. Tesluk, P. E., Farr, J. L., & Klein, S. R. (1997). Influences of organizational culture and climate on individual creativity. Journal of Creative Behavior, 31, 27–41. *Thamhain, H. J. (2003). Managing innovative R&D teams. R&D Management, 33, 297–311. Tierney, P., & Farmer, S. M. (2002). Creative self-efficacy: Its potential antecedents and relationship to creative performance. Academy of Management Journal, 45, 1137–1148. Trevelyan, R. (2001). The paradox of autonomy: The case of academic research scientists. Human Relations, 54, 495–525. *Troy, L. C., Szymanski, D. M., & Varadarajan, P. R. (2001). Generating new product ideas: An initial investigation of the role of market information and organizational characteristics. Journal of the Academy of Marketing Science, 29, 84–101. Van de Ven, A. H. (1986). Central problems in the management of innovation. Management Science, 32, 590–607. Vincent, P. H., Decker, B. P., & Mumford, M. D. (2002). Divergent thinking, intelligence, and expertise: a test of alternative models. Creativity Research Journal, 14, 163–178. Ward, T. B., Patterson, M. J., & Sifonis, C. M. (2004). The role of specificity and abstraction in creative idea generation. Creativity Research Journal, 16, 1–9. West, M. A. (2002). Sparkling fountains or stagnant ponds: An integrative model of creativity and innovation implementation in work groups. Applied Psychology: An International Review, 51, 355–387. *West, M. A., & Anderson, N. R. (1996). Innovation in top management teams. Journal of Applied Psychology, 81, 680–693. West, M. A., Borrill, C. S., Dawson, J. F., Brodbeck, F. C., Shapiro, D. A., & Howard, B. (2003). Leadership clarity and team innovation in health care. Leadership Quarterly, 14, 393–410. *West, M. A., Borrill, C. S., Dawson, J. F., Brodbeck, F. C., Shapiro, D. A., & Howard, B. (2003). Leadership clarity and team innovation in health care. Leadership Quarterly, 14, 393–410. *Zain, M., Richardson, S., & Adam, M. N. K. (2002). The implementation of innovation by a multinational operating in two different environments: A comparative study. Creativity and Innovation Management, 11, 98–106. *Zhou, J., & George, J. M. (2001). When job dissatisfaction leads to creativity: Encouraging the expression of voice. Academy of Management Journal, 44, 682–696.

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