Making innovation happen in organizations: individual creativity mechanisms, organizational creativity mechanisms or both?

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Making Innovation Happen in Organizations: Individual Creativity Mechanisms, Organizational Creativity Mechanisms or Both? Sundar Bharadwaj and Anil Menon

Marketing managers increasingly face a product innovation dilemma. Managers will have to sell more with fewer new products in an environment where new products are providing lower revenue yields. Therefore, understanding what drives successful innovation is of paramount importance. This paper examines the organizational innovation hypothesis that innovation is a function of individual efforts and organizational systems to facilitate creativity. Our model formulates creativity as a property of thought process that can be acquired and improved through instruction and practice. In this context, individual creativity mechanisms refer to activities undertaken by individual employees within an organization to enhance their capability for developing something, which is meaningful and novel within their work environment. Organizational creativity mechanisms refer to the extent to which the organization has instituted formal approaches and tools, and provided resources to encourage meaningfully novel behaviors within the organization. Using data collected from 634 organizations, we find support for this hypothesis. The results suggest that the presence of both individual and organizational creativity mechanisms led to the highest level of innovation performance. The results also suggest that high levels of organizational creativity mechanisms (even in the presence of low levels of individual creativity) led to significantly superior innovation performance than low levels of organizational and individual creativity mechanisms. The paper also presents managerial and academic implications. This study suggests that it is not enough for organizations to hire creative people and expect the innovation performance of the firm to be superior. Similarly, it is not enough for firms to emphasize management practices to enhance creativity and ignore individual mechanisms. Although it is true that doing either will improve innovation performance, doing both should lead to higher innovation levels. Our understanding of what and how creativity influences innovation performance can be greatly enhanced by additional research that integrates the intrinsic and extrinsic drivers of creativity. Research that examines the role of team creativity efforts in enhancing innovation performance is also vital to an overall improved understanding of creativity, learning, and innovation within organizations. © 2000 Elsevier Science Inc. Address correspondence to Sundar Bharadwaj, Emory University, Robert C. Goizueta Business School, Atlanta, GA 30322-2710, USA. J PROD INNOV MANAG 2000;17:424 – 434 © 2000 Elsevier Science Inc. All rights reserved. 655 Avenue of the Americas, New York, NY 10010

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MAKING INNOVATIONS HAPPEN IN ORGANIZATIONS

Introduction

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arketing managers increasingly face a product innovation dilemma. According to a McKinsey study, although firms expect new products to deliver 34% of future top-line growth, they also plan on introducing 21% fewer new products than they did in 1998 [2]. This growth challenge is exacerbated by the fact that first-year sales of new products have declined by 14% over the past three years. This suggests that the revenue-generating capacity of any new product innovations have to be significantly higher in the future. Managers will have to sell more with fewer new products in an environment where new products are providing lower revenue yields. Therefore, understanding what drives successful innovation is of paramount importance. Available research suggests that there exist many factors, which lead to innovation in organizations. For example, the organizational orientation is critical for creating a climate that encourages innovation (cf. [27]). Similarly, the interactions between functional departments (e.g., R&D and Marketing) have been shown to impact innovation and new product success

BIOGRAPHICAL SKETCHES Sundar Bharadwaj is an Associate Professor of Marketing at the Roberto C. Goizueta Business School at Emory University, Atlanta, USA. His research and teaching focus is in the areas of marketing management and strategy, services marketing, relationship marketing, and global marketing. His research is in the areas of developing sustainable competitive advantage, understanding the drivers of superior performance, innovation, creativity and learning in marketing strategy making, developing customer profitability models, and customer retention strategy. Sundar has held brand management and sales management positions in multinational corporations where he developed branding and channel strategies for new and existing products. He has conducted workshops on developing brand equity strategy, service quality strategy, and customer relationship strategy with senior management of U.S. and European firms. Anil Menon is an Associate Professor of Marketing at Emory University’s Roberto C. Goizueta Business School, Atlanta, USA. His research and teaching interests are in the areas of marketing creativity, market learning and market vision, and quality and effectiveness of market strategy planning and implementation. His current research focuses on improving the value of market intelligence, and team and organizational factors affecting strategy creativity and innovation. Anil has worked extensively with several Fortune 500 companies on issues of market orientation, market learning, and internal marketing and has made presentations to, and conducted executive workshops with, senior executives and governmental officials in the U.S., Europe, Middle-East, and Asia on these topics.

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(cf. [9,56]). Meta-analytic and literature reviews of the new product development literature conducted in marketing [44] and in management [21,15] point to the unexplored role of creativity in making innovation happen within organizations. Indeed, although some have suggested that creativity, a firm’s intangible capability, is the first step in innovation [3,22], empirical support is lacking for this hypothesized relationship. This article examines the organizational innovation hypothesis that innovation is a function of individual efforts and institutionalized systems to facilitate creativity (cf. [18,30]). We label these individual and institutional efforts to develop, sustain and enhance creativity in organizations as creativity mechanisms.

Theory and Hypotheses In the marketing literature, creativity is widely viewed as actions, processes, and programs that are meaningfully novel relative to existing practices (cf. [8,13,42]). In this context, individual creativity mechanisms refer to activities undertaken by individual employees within an organization to enhance their capability for developing something, which is meaningful and novel within their work environment. Organizational creativity mechanisms refer to the extent to which the organization has instituted formal approaches and tools, and provided resources to encourage meaningfully novel behaviors within the organization. Although not empirically tested, the innovation hypothesis proposes that innovation within organizations is a function of individual efforts and institutionalized mechanisms to facilitate creativity (cf. [18,30]). The literature on innovation and creativity that focuses on the role of individuals in creating innovations has examined factors such as intelligence, motivation to innovate, and creativity skills (cf. [4,56]). The process-orientation approach views intelligence as an innate attribute, and suggests that the latter two factors can be influenced by external factors. Therefore, our model, which is based on the process-orientation approach, formulates creativity as a property of thought process that can be acquired and improved through instruction and practice (cf. [51]). Amabile (1988) argues that innovation in an organization is significantly influenced by the extent of creativity-relevant skills possessed by its employees. These creativity-relevant skills can be developed, sustained, and enhanced through formal and informal mechanisms such as training and education [3]. Aside from these skills, individuals need to put at risk the

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desire to appear consistent, comfortable, confident and competent (the 4Cs) to improvise and be innovative [19]. Workshops and training programs are effective mechanisms to develop “a perspective or orientation that enables one to risk the 4Cs.” (p. 598, [19]). Hence, the preceding discussion suggests that when employees improve their creative abilities, it enhances the innovation performance of a firm [10,11]. Therefore: Hypothesis 1: The greater the level of individual creativity mechanisms, the higher the innovation performance of the organization.

Organizational expectations play a clear role in activating or inhibiting innovation. Kanter (1988) points out that “[o]ne way organizations signal an expectation for innovation is by allocating funds specifically.” In fact, Delbecq and Mills (1985) found that in comparing innovation successes with failures, failures were handicapped by a lack of resources whereas successful projects had special innovation funds. In addition to appropriate resources, the literature on the organizational context of creativity has identified several elements of the work environment, such as management practices and processes, use of teams, and organization orientation, as drivers of innovation [5,6,26]. This research suggests that organizations can put into place creativity processes, techniques, and tools to facilitate and enhance innovation. Hypothesis 2: The greater the level of organizational creativity mechanisms, the higher the innovation performance of the organization.

The decision-making and cognitive psychology literatures suggest that individuals are constrained by the presence of a number of biases such as self-serving bias (see [46] for a meta-analysis), attribution bias (see [29,52] for reviews), inadequate and shallow search bias [25,28,31,35], availability and selective search bias (cf., [41]) and selective weighting bias (cf., [40,32]), all of which cause them to make-less than effective decisions. The cognitive repairs literature suggests that organizations can institute practices and procedures that can overcome these cognitive limitations [33]. For example, Bridgestone Tire has instituted a practice called “The Kokai Watch” where employees with different perspectives (watchers) are temporarily drawn in to generate alternative hypotheses and solutions to a problem faced by a team or an individual [58]. This practice enables the organization to overcome the narrow search bias. Similarly, Toyota has instituted a practice called “Five Whys” wherein

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employees have to ask “Why?” five times before they stop generating hypotheses. Such a procedure enables the employee to find the root cause and overcome a shallow search bias [33,38]. Based on a review of the research on creativity, Amabile (1988) concludes that individual creativity efforts are strengthened by the presence of organizational systems, procedures, and processes that enable creativity. Consistent with these expectations, an experimental study found that more creative personalities produced more creative output than less creative personalities only when they were surrounded by an organizational context that facilitated creativity [20]. Thus, although individual and organizational creativity mechanisms can individually impact innovation performance, we hypothesize that the effectiveness at making innovation happen will be greater when both individual and organizational creativity mechanisms occur simultaneously. Stated formally, Hypothesis 3: The greater the level of both individual and organizational creativity mechanisms, the higher the level of innovation performance.

Given that our primary interest was on the role of individual and organizational creativity mechanisms on innovation performance, we controlled for other factors that could potentially influence innovation. Drawing on the innovation literature (cf., [1,15,34, 44]), we controlled for R&D intensity, availability of organizational slack, importance of innovation to the organization, size of the organization and individual’s experience in the organization.

Method Data Data for this study were gathered through a mail survey of key respondents in 750 business units of S&P 500 corporations. The sample represents a 11% response rate (unadjusted for nondeliverable rate)1. The corporations represented a wide range of industries including banking, telecommunications, manufacturing, media, consumer packaged goods, and healthcare. Approximately 14% of respondents were 1 This response rate is lower than the average response rate of 20% in organizational surveys [49,57]]. If we had followed traditional practice in marketing literature to adjust upwards the response rate to account for non deliverable surveys (cf., Hunt and Vasquez–Parraga, 1993 who demonstrate an effective response rate of 54% after adjusting for non-deliverable of 72%), our effective response rate would have been much closer to the average.

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Table 1. Descriptive Statistics and Correlation Variables 1. Innovation performance 2. Individual creativity learning efforts 3. Organizational creativity learning efforts 4. R&D intensity 5. Organizational slack 6. Importance of innovation 7. Size 8. Experience

Mean (SD) 3.15 (0.66) 12.90 (9.57) 2.33 (0.96) 2.85 (1.15) 0.35 (0.75) 4.18 (0.79) 2.40 (1.46) 14.00 (9.72)

1

2

3

4

5

6

7

8

0.75 0.14a 0.38a

0.21b

0.76

0.29a

0.06

0.21a

0.04

0.02

0.31a

0.18b

0.19a

0.16

⫺0.02

0.06

0.15b

⫺0.06

⫺0.002

⫺0.03

⫺0.01

0.13b

⫺0.07

⫺0.01

⫺0.03

⫺0.01 ⫺0.06 0.01 ⫺0.06

0.20a

Significant at p ⱕ 0.0001. Significant at p ⱕ 0.05. Items on the diagonal are cronbach alphas. a

b

CEOs or COOs; 66% were vice presidents, general managers or directors of their SBUs; the rest were marketing managers or group product managers Test of key informant competence. To verify the appropriateness of the key informant, we assessed their knowledge, by utilizing experience and involvement as proxies for knowledge [48,53]. On average, respondents had thirteen years of experience with the firm, levels comparable to other samples of top management informants [43]. We eliminated 33 respondents who had one year or less of experience in the firm. We also eliminated an additional 46 respondents whose job responsibilities did not include innovation and creativity. Test of data poolability. Once the appropriateness of our key informants had been identified, responses needed to be tested for cross-sectional pooling of three categories of groups [16,24]. In terms of organization level, the respondents in this sample fall into three groups: CEOs/COOs; vice presidents/general managers/directors of their SBUs; and marketing managers/group product managers. In terms of organization type, 62.8% were publicly traded firms and the rest were private. In terms of industry sectors, 47.1% of the sample belonged to the manufacturing sector and the rest to the services sector. To test for the suitability of pooling respondents from the groups described above, we examined if they responded differently on the constructs of interest to

the study. The omnibus F-test indicated no statistical difference between the three manager groups, public and private organizations, and industry. On the strength of these tests, we conclude that pooling the manager groups, organization type, and industry sectors in the sample was appropriate and justified. After eliminating seventy-nine responses due to inappropriate respondents and an additional 37 responses because of excessive missing data, the final sample consisted of 634 responses. The average sales revenue of the firms in the sample was $2.4 billion, which is comparable to the bottom 30% of the firms in the S&P 500 firms (COMPUSTAT Database). The firms in the sample had on average between 5,000 to 10,000 employees. Measures Because we were not able to find extant measures for the constructs used in this study, we developed items and measures using the literature on creativity as a guide (see Appendix for scale items). The dependent variable, innovation performance, was measured using a five point six item scale that subjectively rated how frequently the different departments of the organization exhibit innovation and an overall summary item that captured the organization’s actual performance on making innovation happen. An examination of the descriptive properties for the innovation performance

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measure indicates that social desirability bias is not present, since the mean is near the midpoint (x ⫽ 3.15) and the responses ranged from 1 to 5. The independent variable, individual creativity mechanisms, was measured using a three-item formative scale that assessed the extent of time spent on creativity during the job and efforts expended to enhance the knowledge base on creativity. The other independent variable, organizational creativity mechanisms, was assessed by a six-item scale, which captured the extent to which the organization used creativity approaches, tools and provided resources to encourage creativity. Among the controls, R&D intensity was measured by a single-item measure, which captured the firm’s R&D to sales ratio compared to major competitors. Slack was measured by the firm’s return on sales, organization size was measured using number of employees, and each individual’s experience was measured using the number of years in the firm2. Innovation importance was measured using a single-item scale that rated innovation’s importance to the organization’s overall success on a five-point scale anchored on “innovation is of no practical value” and “innovation is of paramount importance.” Analysis and Results Post hoc testing for common method bias. When dependent and independent variables data are collected from the same informant, common method bias may be a potential problem. Following Menon, Bharadwaj, Adidam, and Edison (1999) we utilize the Harman’s one-factor test to examine the extent of the common method bias that may exist in this study. The logic of this approach is that if the common method bias accounts for the relationship between two or more variables, a factor analysis should yield a single method factor when all the constructs are analyzed together. The result of the principal components factor analysis reveals that there are five factors with eigenvalues greater than 1.0 that accounts for 50% of the total variance. Because several factors were identified, the first factor did not account for the majority of the variance (only 19%), and since there is no general factor in the unrotated factor structure, common method variance does not seem to be a problem [50]. 2 Sales and profit data for a subset of publicly traded companies was independently verified through a syndicated financial reporting service. Self-reported data were highly correlated with objective performance data suggesting high validity of data used in this study.

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Measurement analysis. After data collection, the measures were first subjected to maximum likelihood exploratory factor analysis (utilizing oblique rotation) and confirmatory factor analysis. The results of the exploratory factor analysis indicate that the original assignment of twelve items to the two reflective scales was appropriate. Like the exploratory factor analysis results, the overall fit of the confirmatory factor analysis with all twelve items was excellent. [Model: ␹2 ⫽ 165.95 with 53 df(p ⫽ .0001), GFI ⫽ 0.94, TLI ⫽ 0.92, CFI ⫽ 0.94, RMSEA ⫽ 0.07]. Furthermore, all the item loadings on the respective constructs were statistically significant (smallest t value ⫽ 6.30 and average t value ⫽ 13.11). The coefficient alpha for the organizational creativity mechanism scale was 0.76 and for the innovation performance scale was 0.75. Because individual creativity mechanism was measured using a formative scale, traditional reliability coefficients are not appropriate [14,36]3. Formative constructs are measured by itemizing the domain of the construct and the construct is then defined as a sum of its parts. The exploratory factor analysis for the two reflective constructs indicated that the constructs were unidimensional (i.e., a single eigen-value greater than one). Discriminant validity was assessed through three tests. First, by examining if the confidence intervals (⫾ two standard errors) around the disattenuated correlation estimates between any two factors included one. In none of the cases did the confidence intervals contain 1.0, thereby indicating discriminant validity. Second, the average variance explained by any pair of constructs was greater than the square of the correlation between them, again indicating discriminant validity. Third, by examining if the confidence intervals (⫾ two standard errors) around the correlation estimates between any two factors included one. Twofactor confirmatory factor analysis of pairs of constructs was conducted twice: once constraining the correlation between the latent variables to unity and once freeing the parameter. A ␹2 difference test was then used to test whether the ␹2 value of the unconstrained model was significantly lower, in which case discriminant validity would be upheld. The critical value (⌬␹2 (1)⬎3.85) indicates that discriminant validity was upheld in all pairwise tests. Hypothesis testing. Hypotheses were tested with multivariate analysis of covariance (MANCOVA). 3

The use of formative scales has gained precedence in marketing (cf., [17,45]).

MAKING INNOVATIONS HAPPEN IN ORGANIZATIONS

The “independent variable” is defined as the polychotomous variable identifying four groups. Using median level splits on both individual and organizational creativity mechanisms, we formed four groups: low on both individual and organizational creativity mechanisms (LL); low on organizational level creativity mechanisms, but high on individual level creativity mechanisms (HL); low on individual level creativity mechanisms, but high on organizational level creativity mechanisms (LH); and high on both individual and organizational creativity mechanisms (HH). The dependent variable was the continuous variable measuring innovation performance. MANCOVA was chosen because the model included the four control variables. The results of the MANCOVA analysis are provided in three panels in Table 2. The omnibus test statistics, namely, the Pillai’s Trace, Hotelling–Lawley’s trace and Wilks’ lambda reported in Table 2 provide evidence of significant (p ⬍ .0001) differences between the four groups on innovation performance. The univariate pair-wise Tukey’s tests indicated that the HH group had a significantly higher mean than the other three groups on innovation performance thereby providing support for H3. In other words, the results suggest that the presTable 2. Multivariate Analysis of Covariance Results Mean Values of Organizational Creativity Low (L) High (H) Mean values of individual creativity

Low (L) 2.93 (200) High (H) 3.01 (167) Numbers in parentheses are cell sample size

3.23 (131) 3.48 (168)

Mean differences from other groups* Organizational Creativity Low (L) High (H) Low (L) LH, HH All other groups High (H) LH, HH All other groups *Results identical for Tukey’s test, Student–Newman–Keuls test, and Bonferroni (Dunn) t test. Individual creativity

Omnibus test results: Omnibus Tests

Value

F

Wilks’ lambda Hotelling–Lawley Trace Pillai’s Trace Roy’s Greatest Root

0.83 0.20 0.17 0.16

7.01 7.21 6.79 17.67

Significance of F 0.0001 0.0001 0.0001 0.0001

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ence of both individual and organizational creativity mechanisms led to the highest level of innovation performance. Support was also found for H2 since the LH group had a significantly higher mean than the LL group. This result suggests that high levels of organizational creativity mechanisms (even in the presence of low levels of individual creativity) led to significantly superior innovation performance than low levels of organizational and individual creativity mechanisms. H1 was not supported since Groups LL and HL were not significantly different from each other on innovation performance.

Limitations At the outset, six limitations of this study need to be evaluated. First, the scales used in this study need to be validated and improved on a number of counts. Specifically, multiple measures as well as more objective measures of the constructs under study are necessary to enhance confidence in the results. Second, because the data gathering design was cross-sectional, it is difficult to determine whether the creativity mechanisms lead to innovation performance or whether superior innovation abilities of the firms lead respondents to report on the extent of creativity mechanisms used. Although the reverse direction of causality would contradict the theoretical expectation, a longitudinal study is needed to establish causality and this clearly seems to be an important avenue for further research. Third, collecting the exogenous and outcome variables from the same source at a single point of time may have exacerbated “same source” or “common method variance” and “retrospective biases.” Although we provide reasonable evidence to rule out common method bias, the evidence is at best post hoc and the study results should be interpreted with due caution. Therefore, future research should attempt to obtain data on the dependent and independent variables from multiple sources, using multiple methods. Fourth, it might be argued that judgments of innovation performance should be performed by independent sources such as customers rather than firm employees. Although prior research has established that the judgments of managers and customers on creativity are highly correlated [7,54], future research could benefit from collecting innovation performance perceptions from independent sources. Thus, a longitudinal study (using multiple sources) of the creativity mechanisms utilized and innovation performance

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(measured by independent and objective sources) would have several advantages over cross-sectional studies such as ours. Not only would it establish causality, it would also reduce the potential for consistency biases, halo effects, priming effects as well as common method biases. Fifth, the study uses only descriptive statistics (tests of mean differences) and therefore the results can be viewed at best as ‘stylized facts’ and not as conclusive. This study can serve as the starting point for further theoretical development and empirical validation. Finally, the relatively low response rate limits the generalizability and certainty of the findings. Further empirical research is necessary to validate these initial findings.

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items geared to spark new thinking. We understand that an innovation center can’t transform people who don’t have the internal drive and desire to create. But we also know it doesn’t work to urge people to think outside the box without giving them the tools to climb out.”

We find that organizational creativity mechanisms and individual creativity mechanisms can lead to innovation in companies. Support for both H2 &H3 suggests that organizational creativity mechanisms seem to have a stronger association with innovation performance. This result is consistent with Amabile, Conti, Coon, Lazenby, and Herron’s (1996) finding that management-instituted mechanism for creativity (such as developing mechanisms for new ideas) differentiates between high and low performance organizations. These researchers contend that efforts taken by the organization in terms of developing formal processes, programs, structures, and budgets for facilitating creativity affect employees psychologically by signaling the importance of creativity and innovation. Our results are also in line with the work of Cummings and Oldham (1997) who find that organizations which provided a supportive environment and context for creativity tend to reap greater benefits from individual employees who are innately creative. Our result also provides empirical support for Woodman, Sawyer, and Griffin’s (1993) hypothesis that organizational efforts at creativity should impact innovation positively. Furthermore, we provide support to managerial views, such as those of Laurie Dunnavant, a founding fellow of the Innovation University at 3M who said,

The positive association between individual creativity mechanisms and innovation performance from our exploratory investigation provides support for the process-orientation theory of creativity [51]. In line with this theoretical perspective’s contention, we suggest that creativity can be acquired and improved through instruction and practice. Our finding is also supportive of Wheatley, Anthony and Maddox’s (1991) conjecture that creativity training for individuals will enable them to improve their problem-solving skills, leading to more innovative solutions to existing problems4. Juxtaposing this finding with the growth of creativity training for business individuals [60] point to possible convergence of academic and business perspectives that creativity is not necessarily just an innate phenomenon, but can also be inculcated, encouraged, and trained. Given these preceding findings and lack of empirical research in this domain, we conducted a further analysis to provide a richer description of the four groups5. Several differences emerge when the four groups are contrasted along demographic and behavioral dimensions. Smaller firms (under 5,000 employees) tend to emphasize individual creativity, whereas larger firms tend to emphasize organizational creativity. Also, firms in the financial sector tend to emphasize individual creativity, whereas firms that considered themselves as marketing and sales organizations tend to emphasize organizational creativity. No differences were detected between individual respondents in terms of job position and experience on the job and in the company. From the point of view of the company differences, one striking difference between the firms in the four groups was that firms that emphasized organizational creativity not only used a greater number of creativity techniques/efforts, but they also used them more often. Firms that emphasized that individual creativity tended not only to use fewer techniques/efforts, but they did not use the ones they had very much. Consider the extent of use of several key creativity tech-

“You can’t forcefeed creativity. But you can create an environment that encourages it. At 3M, we’re building an Innovation and Learning Center to do just that. . . . The center offers books, videos, and technical training

4 They examined this in the context of strategic planning and coming up with imaginative efforts and newer ideas during planning. 5 We thank an anonymous reviewer for suggesting this analysis.

Discussion and Implications Discussion

MAKING INNOVATIONS HAPPEN IN ORGANIZATIONS

niques. Although 43% of the LL group (low on both individual and organizational creativity mechanisms) and 44% of the HL group (high on individual and low on organizational creativity mechanisms) firms adopted a creative problem-solving process, they often didn’t use it in practice. In contrast, 60% of the Group LH (low on individual and high on organizational creativity mechanisms) firms and 76% of the Group HH (high on both individual and organizational creativity mechanisms) firms used the creative problemsolving approach often. Similarly, although only approximately 20% of the Group LL and the Group HL firms used outside creativity consultants, about 55% of the Group LH and 66% of the Group HH firms use such consultants often. Even passive creativity techniques such as suggestion boxes were used less by the Group LL (26%) and the Group HL (27%) firms compared to the Group LH (48%) and the Group HH (42%) firms. Interestingly, although 25% of the firms that fall within the high (individual) group firms used a system that rewards individual creativity efforts, this represented a far smaller figure than the Group LH (61%) and the Group HH (59%) firms. Finally, whereas only 16% of the Group HL firms employed team-based rewards for creativity, 60% of the Group LH and 67% of the Group HH firms used team-based rewards. Further research is clearly needed to validate these preliminary findings. Implications This study suggests that it is not enough for organizations to hire creative people and expect the innovation performance of the firm to be superior. Similarly, it is not enough for firms to emphasize management practices to enhance creativity and ignore individual mechanisms. Although it is true that doing either will improve innovation performance, doing both should lead to higher innovation levels. Our results suggest the need to recruit individuals who make regular efforts to improve the creative abilities of employees through training and on the job. The results also call for managers to formalize creativity approaches and techniques in organizations to improve innovation output. These results are consistent with the resource-based view of the firm that intangible capabilities such as creativity are the prime drivers of superior firm performance [42]. An obvious implication for marketing metrics is that firms should look at creativity expenditures as an investment, rather than treat it as expenditure. In other words, it is quite likely that the pay-

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offs of such investments in creativity may not be visible in contemporaneous accounting measures of performance. In fact the positive effects of such investments that are captured by intermediate performance measures such as innovation are reflected better in long run performance, measured through marketbased measures such as stock price or intangible performance measures such as Tobin’s q (see Bharadwaj, Bharadwaj, and Konsynski, 1999 for an illustration). In this context, it is important to recognize that there may exist other drivers of innovation performance that the model does not take into account. For example, the organizational climate and individual creative abilities and personality traits have been shown to impact innovation. Nevertheless, it is also important to underscore that the variables studied in our study are more actionable and within managerial control in contrast to other variables typically discussed in the traditional creativity literature. One of the limitations of this study and opportunity for future research is the way we measure individual creativity mechanisms and innovation performance. Future research should focus and elaborate on this construct by developing psychometrically valid scales. It is also important to note that our model does not directly measure the creativity levels achieved by employees. Instead we treat it as an unobservable that mediates the relationship between individual and organizational creativity mechanisms and innovation performance. Further research should not only measure this mediation explicitly, but also evaluate the differential effects of these mechanisms on creativity. Our understanding of what and how creativity influences innovation performance can be greatly enhanced by additional research that integrates the intrinsic and extrinsic drivers of creativity. For example, what are the effects of individuals’ proclivity for creativity and innovation? Similarly, what are the integrative effects of an organization’s proclivity for creativity and innovation (i.e., its creativity and innovation climate)? Finally, organizations are increasingly dependent on teams for developing new products and other innovations. Research that examines the role of team creativity efforts in enhancing innovation performance is vital to an overall improved understanding of creativity, learning, and innovation within organizations. The authors are listed alphabetically. We thank Dr. William Boggs for access to the data used in the study.

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Appendix Measures Individual Creativity Learning Efforts 1. Approximately what percentage of your time is spent in the areas of creativity? 2. How many books or articles have you read in the past year on creativity? % 3. How many seminars or conferences have you attended in the past year on creativity?

% Seminars

Organizational Creativity Learning Efforts Think about the following approaches to innovation and describe your organization’s actual usage: (five-point scale anchored on “Don’t Have it” to “Have it and use it often”) 1. A widely shared process for creative problem-solving 2. A formal creativity or idea generation program 3. A formal innovation approach or program, linking new ideas to specific business goals or issues 4. An “innovation center,” or a designated location within the organization set aside for idea generation 5. Designated facilitators for idea generation 6. A budget expressly set aside for creativity/innovation activities Innovation Performance Please rate the frequently the following areas exhibit innovative behavior? (five-point scale anchored on “Not frequently at all” to “Very frequently”) • • • • •

Marketing Research & Development Sales Distribution New product development

Overall, how do you rate your organization’s actual performance in making innovation happen? (five point scale anchored in “basic” to “superior”) R&D Intensity How would you describe the level of investment in overall research and development in your organization, expressed as a percentage of gross revenues, compared to your competitors’ spending? (three-point scale anchored on “not nearly as much” to “substantially more”)

434

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S. BHARADWAJ AND A. MENON

Organizational Slack Calculated as Return on Sales ⫽ Profit/Loss in $/Annual Sales in $ Size Which of the following categories best describes the number of employees in your organization? Under 1,000 1,000 but under 5,000 5,000 but under 10,000 10,000 but under 20,000 20,000 but under 50,000 over 50,000 Importance of Innovation to Organization Please rate how important innovation is to your organization’s overall success? (Five-point scale anchored on “Innovation is of no practical importance” to “Innovation is of paramount importance”) Experience How long have you worked for this organization?

years