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The Moderating Effect of Market Turbulence on Organizational Intelligence

Mumin Dayan

College of Business Administration University of Sharjah

PO BOX 27272, Sharjah, UAE Abstract: Organizational intelligence has become a popular topic recently in business and academia and attracts many researchers and practitioners from different fields. Because of many studies in such different disciplines and perspectives, the interpretation of organizational intelligence shows a discrepancy, resulting in disorder in the organizational intelligence literature. The organizational intelligence literature reveals three basic features of an intelligent organization. An intelligent organization is considered a learning organization, a market-driven organization, and an innovative organization. Each disciple has its own terminology to define organizational intelligence. In this study, the concept, the scope, and the constructs of organizational intelligence are clearly identified to reduce confusion about organizational intelligence by reviewing intelligence in product innovation, organizational learning, and marketing strategy literatures. In addition, this study explores the antecedent factors that impact new product development team intelligent as well as its consequences. By studying 207 new product teams, it was found that: 1. The most direct antecedents of team intelligent are procedural knowledge, declarative knowledge and information technology, and 2. Team intelligent has a significantly positive effect on product creativity.

I. INTRODUCTION In strategic management literature, performance variations among companies are explained with the resource-based view of the firm [1,2]. Firms possessing unique and inimitable resources are believed to survive or have better performance in the competitive marketplace [3]. An organization’s knowledge base is one such resource, and has been at the heart of much of the recent discussion of the concepts of knowledge management [4], knowledge creation [5], and organizational intelligence [6, 7, 8, 9, 10]. These concepts explain the relationship between organizational knowledge and competitive advantage [11]. Organizations that have effective knowledge management systems providing knowledge based competitive advantages over the competitors are considered to be intelligent organizations [12]. The organizational intelligence literature reveals three basic features of an intelligent organization. An intelligent organization is considered a learning organization, a market-driven organization, and an innovative organization [7]. Hence, the concept of organizational intelligence uses theories of organizational learning [e.g., 9] and market orientation [13] as well as individual intelligence [7] as platforms for providing insight into how organizations can acquire information, disseminate information, utilize information, respond this information to facilitate and create competitive advantages.

Researchers exploring the determinants and consequences of organizational intelligence have been especially interested in organizational structure [e.g., 14], organizational culture [15], or organizational strategy [16] as the determinants; and organizational performance [17, 18], product advantage [19], or product characteristics [20] as the consequences. We argue that issue that is even more important is the moderating effect of market turbulence in the relationship between organizational intelligence and product creativity. Furthermore, there exists a large body of research on organizational-level intelligence [22, 21, 23]. Researchers [7, 24] indicate that understanding factors affecting intelligence at the product development project and team level will provide a valuable complement.

II. THEORETICAL BACKGROUND ON ORGANIZATIONAL INTELLIGENCE

Intelligence is found in the product innovation literature concerned with market knowledge and marketing proficiency [25, 26], competitive and market intelligence activities [27, 28, 29), environmental scanning [30, 31], market information processing [15, and 21], and market knowledge competence [19]. In the literature, the concept of team or group intelligence is distinguished from the more familiar concept of individual intelligence. Group intelligence is perceived as the functional intelligence of a group of people working as unit. However, researchers have attempted to measure group intelligence based on only group performance, group member characteristics, or group interaction. Recently, Akgun [24] have measured organizational intelligence at team level-NPD teams. He found out that NPD team intelligence is the key variable for team learning as well as new product success. He defines NPD team intelligence as the ability of teams to gather information from outside of the organization, and within the organization, and the ability of teams to respond this information. Because of insufficient amount of researches on team intelligence, in this study NPD team intelligence will be operationalized and empirically tested based on the constructs of organizational intelligence. Researchers also indicate that

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understanding team intelligence provide us a foundation for understanding organizational intelligence, because of the following reasons: First, because groups or teams are small representations of organizations, and show the similar behavioral patterns as organizations do. Hence, organizational constructs can be operationalized at the team level [58]. Literature on popular physics notes the importance of fractal geometry and images in system thinking [59]. The basic philosophy is that all characteristic patterns of the system are found repeatedly at the descending scales [59]. This is similar to holographic systems, which create processes where the whole can be encoded in all of the parts, so that each represents the whole [10]. Second, new product development as the process from idea-generation phase to the launch phase is viewed as the central aim of organizational intelligence. Recent studies on organizational learning and market orientation focus on innovation (implementation of new ideas, products, or processes) as the primary mechanism for responding to markets [36, 24], since throughout innovation process, organizations and/or teams are engaged in intelligence generation, dissemination, utilization and responsiveness [7].

III. HYPOTHESES DEVELOPMENT Organizational Memory: In the organizational literature, the stock of organizational beliefs, prior knowledge, experience, values, norms, routines, and procedures is named organizational memory [61, 62, 63, 64]. Moorman and Miner’s literature review [61] on organizational memory reveal that organizational memory is manifested in terms of forms, roles, and characteristics. It is proposed that the foundation of organizational memory is clustered in two distinct forms. The first cluster consists of organizational beliefs, knowledge, frames of reference, models, values, and norms. The second one is about formal and informal routines, procedures, and scripts; and the last one is about an organization’s physical artifacts such as product design, materials, and logos. One of the characteristics of memory is the amount or level of information an organization stores in one of the forms listed above. Another characteristic is the content of organizational memory that consists of procedural and declarative knowledge. Declarative knowledge is the way through which knowledge is first achieved [65]. Unlike procedural knowledge, declarative knowledge is easy to explain, verbalize, and demonstrate, because it is about factual statements on rules and objects [66]. Although researchers have point out the positive effects of stored information or memory on product and technological developments, under certain conditions negative effects of organizational memory on new product development are revealed as well [61]. Dougherty [69] suggests that if organizations aim to develop creative or radical products, firms ‘competencies including organizational memory may prevent

firms from implementing their aims. Similarly, Miner, highlights the same detracting effects of organizational memory on product creativity for firms operating under turbulent environment. Moorman and Miner [61] analyzed and tested this relationship between organizational memory and new product development. Their research results revealed that under the conditions of high market and technological turbulences, high organizational memory dispersion leads to low level of product creativity. These findings have two important implications for organizational intelligence. First, under market turbulence organizational memory dispersion may detract from product creativity, because under such conditions, the needs of customers rapidly change and firms’ stored old information may not be enough sources for firms to be creative or to develop radical products. Second, firms need to refresh their memory and get new information from environment to make quick response to it. The literature on organizational intelligence indicates this positive effect of organizational memory on organizational intelligence under turbulent conditions. For example, Choo [9] points out this relationship. He indicates that organizational memory helps firms to develop rules and standards that are used in any situations to develop their intelligence system. Hence, under the conditions of environmental turbulent, as revealed by Moorman & Miner [61] organizational memory may not help firms to be creative but may help them to be creative through generating, disseminating, utilizing and responding new information in new product development process. Therefore: H1: Market turbulence strengthens the associations between declarative knowledge and team intelligence in new product development. H2: Market turbulence strengthens the associations between procedural knowledge and team intelligence in new product development. Functional Diversity: Cross-functional diversity refers to the number of functional areas represented on the team whose members are fully involved in the project. The development and introduction of new programs and products usually require the combined expertise of a variety of organizational personnel, since as the firm grows; its functional area becomes specialized. Based on the literature the necessity of team diversity for organizational intelligence and new product success comes from the ability of cross-functional teams to generate and disseminate market information, and responsiveness to this information [17, 7]. Moreover, the literature on human intelligence has also shown that intelligence is fostered in social climates in which diversity of viewpoints is permitted. Hence, small groups often outperform individuals on a variety of problem-solving and cognitive tasks that require intelligence generation and

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responsiveness. Hoffman and Maier’s research [56] has showed that heterogeneous group was more successful than homogeneous group, formulating higher quality decisions on diverse problems. When many alternative solutions are required to solve a problem, increasing the heterogeneity of the group can increase its potential problem solving ability. Hackman noted that homogeneous group members might get along well together, but lack the necessary diversity to handle the tasks. The literature also indicates that market turbulence increases the necessity of team diversity in new product development. Market turbulence is defined as the rate of change in the composition of customers and their preferences. It causes an information deficiency that is defined as information difference between the amounts of information required to perform a particular task and amount of information already possessed. The literature indicates that firms operating in high market turbulent environment and/or focusing on radical innovations are more likely to face information defects. Therefore, such firms need to obtain more information about external shocks or unexpected internal surprises than firms operating in low environmental turbulence do. Collins and Guetzkow [85] also concluded that a heterogeneous group would operate more effectively if the task is difficult representing uncertainty and radical innovations in new product development context, and if those traits on which members are heterogeneous are relevant to the task. Therefore: H3: Market turbulence strengthens the associations between a moderate level of functional diversity and team intelligence in new product development. New Product Creativity: In strategic management literature, intelligent organizations are considered to count on information to discover opportunities rising in the environment and respond with creative solutions. In other words, being creative or producing creative solutions is one of the essential features of intelligent organizations. Like organizational intelligence, individual intelligence has also been related to individual or group creativity. However, the literature reveals that high levels of individual or group intelligence do not always assure creativity [54]. Intelligence leads to creativity only if the dominant intelligence is related to the task domain in which creativity occurs [7]. Thus, the relationship between intelligence and creativity has been investigated with the concepts of job performance, and or career success rather than psychometric measures of general intelligence, such as IQ test. New product creativity is explained with the concepts of novelty and generative capacity [15]. Novelty refers to newness of the product to the market or the firm [15]. Generative capacity is about the potentials of the product to change marketing thinking and practice.

Innovation, especially radical ones, involves organizational intelligence, since innovation requires intelligence processes that are information generation, dissemination, utilization, and responsiveness to the environments. Basically, in the literature the relationship between organizational intelligence and innovation is explained with the concept of the process or stages of organizational innovation. Many researchers are consisting on the two main stages of organizational innovation, the initiation stage and the implementation stage. At the first stage, new product ideas are generated based on implementing activities pertaining to problem perception and information gathering. The second stage consists of activities pertaining to modifications, initial utilization, and continued use of innovation. Glynn [7] proposes that organizational intelligence leads to the organizational innovation. Both individual and organizational intelligence has been associated to the creativity [55]. Such as Gardner, concludes that creativity is based on breadth and combination of human intelligence. Similarly, Barron & Harrington, indicate that “Studies of creativity of adult artists, scientists, mathematicians, and writers find them scoring very high on test of general intelligence”. The literature indicate that group or team intelligence increases the teams’ ability to generate novel products, because intelligent teams are those teams that encourage decision makers to disagree and challenge one another’s opinion through intelligence generation, dissemination and utilization processes [7]. Therefore: H4: New product development team intelligence will lead to new product creativity.

IV. METHODOLOGY A list of 2,310 U.S. manufacturing companies, which identified one product manager per company, was obtained from the Project Management Institute (PMI). A mailingincluding cover letter, stamped return envelope, and questionnaire was sent to each product manager in the mailing list. We received 207 usable questionnaires from product managers representing wide range of industries including electrical/electronic, computer, pharmaceuticals, chemicals, and machinery/metal manufacturing. The effective response rate was 16.5% (207/1250). Product managers were selected as respondents because managers perceive things better than other team members do during new product development process due to their involvement and responsibility for product performance. In order to test the hypotheses, a survey was developed for the measure items. All the measures were adapted from the previous literature on market orientation, product development, organizational learning, and marketing .

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After receiving the questionnaires, a set of statistical analyses was performed to assess the dimensionality and reliability of the measure items. First, an exploratory factor analysis was performed to assess the dimensions of the constructs. The analysis used a principle component with a varimax rotation of all items with eigenvalues greater than 1. Second, first the data was split into two samples as high turbulence and low turbulence to test the hypothesized model on both turbulence condition, and then the reliability of items was checked in sub sample. Intraitem consistency reliability, which is a test of the consistency of respondents’ answer to all items in a measure ranged from .7034 in low turbulence and .7066 in high turbulence for responsiveness to .9023 in low turbulence and .9062 in high turbulence for market turbulence indicating that there is a high agreement among the product managers in each turbulent condition answering to the items. Based on these results, we conclude that all measure items are reliable, and new product development team intelligence is best conceived as a multi-dimensional structure with four correlated but distinct constructs: information acquisition, information dissemination, information utilization, and responsiveness. After checking the reliability and validity of items, two distinct model-testing approaches to examine the proposed hypotheses were performed. First, a structural equation model (SEM) using EQS 5.7 was performed to examine the proposed hypotheses. This approach involved creating high and low levels of market turbulence by performing a median split. Then, the SEM was performed on each level of market turbulence. Second, a split group analysis was performed to examine the impact of market turbulence on the proposed model. This approach also involved creating high and low levels of market turbulence by performing a median split. Then, the relationship between the antecedents and the consequences discussed in the proposed model was examined in the high and low market turbulence conditions, and the regression results from these two conditions were compared using t-test to determine if the regression coefficients were different across the two moderator conditions.

V. RESULTS AND DISCUSSIONS

The results indicate that the model has good fit indices for both high and low market conditions (Low Market Turbulence – CFI = .92, NFI = .90, NNFI = .91, High Market Turbulence – CFI = .96, NFI = .92, NNFI = .93). Results also indicate that procedural knowledge (b = 3.43, t = .28, p = .10, in low turbulence; b = 6.33, t = .49, p = .05, in high turbulence), declarative knowledge (b = 3.10, t = .24, p = .10, in low turbulence; b = 5.40, t = .43, p = .05, in high turbulence), and information technology (b = 6.33, t = .50, p = .001, in low turbulence; b = 7.12, t = .51, p = .001, in high turbulence) are significant and positive predictors of NPD team intelligence in both high and low market turbulent conditions. Moderate level of functional diversity does not have a

significant impact on NPD team intelligence in either low turbulent condition (b = .55, t = .09, p > .10) or high turbulent condition (b = .85, t = .08, p >.10). Finally, NPD team intelligence (b = 5.34, t = .76, p = .001, in low turbulence; b = 6.19, t = .69, p = .001, in high turbulence) has significant effects on new product creativity. The split group analyses indicate that high levels of market turbulence have a positive influence on procedural (t = 3.27, p < .001) and declarative knowledge’s impact (t = 4.18, p < .001) on NPD team intelligence. We find that both declarative and procedural knowledge have a more profound influence on NPD team intelligence for the firms are operating in high turbulent markets. However, market turbulence has equally mixed effects on NPD team intelligence-new product creativity (t = 65, p > .10). We also find that there is no significant effect of moderate level of functional diversity on NPD team intelligence in either low (t = 57, p > .10) or high (t = 78, p > .10) turbulent market conditions. However, the results indicate significant effect of functional diversity (t = 3.12, p < .001) rather than moderate effect of it.

Table 1: Results

Expected Sign

Path Supported

H1 + Significant Yes H2 + Significant Yes H3 + Not Significant No H4 + Significant Yes

From an academic perspective, the findings have several important implications (see Table 1). In previous studies (i.e., Akgun, A. Ekber, 2000), NPD team intelligence was operationalized as the ability of teams on information acquisition and utilization during the NPD process. However, our findings reveal that NPD team intelligence is best conceived with not only information acquisition and utilization but also with information dissemination and responsiveness. In previous studies, both individual and organizational intelligence are associated with the creativity [55] because creativity is explained by the breadth and combination of human or organizational intelligence. Creative adults score very high on test of general intelligence. In this study, we empirically support this relationship between team intelligence and creativity in a new setting, innovation process. However, we found that to develop creative products besides forming intelligent teams, companies provide teams with adequate resources and facilities and support team during the process.

VI. REFERENCES 1. Wernerfelt, B. (1984), “A Resource-Based View of the Firm,” Strategic Management Journal, 5: 171-190.

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2. Barney, J. B. (1991), “Firm Resources and Sustained Competitive Advantage”, Journal of Management, 17: 99-120. 3. Conner, K. R., & Prahalad, C.K (1996), “A Resource-Based Theory of the Firm: Knowledge versus Opportunism,” Organization Science, 5: 477-501. 4. Hedlund, G. (1994), “A Model of Knowledge Management and the N-form Corporation”, Strategic Management Journal, 15: 73-90. 5. Nonaka, I., and Takeuchi, H. (1995), The Knowledge-Creating Company. Oxford University Press, NY. 6. March, J. G & Olsen, J. P (1986), Garbage can models of decision making in organization. Ambiguity and Command: 11-35, MA: Pitman. 7. Glynn, M. A. (1996), “Innovative Genius: A framework for relating individual and organizational Intelligence to innovation,” Academy of Management Review, 21: 1081-1111. 8. McMaster M. D. (1996), The Intelligence Advantage: Organizing for Complexity. Newton, MA: Butterworth-Heinemann 9. Choo, Wei Chun (2000), Information Management for the Intelligent Organization: The art of Scanning the Environment. Information Today Inc. Medford NJ. 10. Morgan, G. (1998), Images of Organization. The executive edition. CA: Sage Publications 11. Thomas, J. B., Sussman, S. W., and Henderson, J. C. (2001), “Understanding Strategic Learning: Linking Organizational Learning, Knowledge Management, and Sensemaking,”Organization Science, Vol.12, No.3, pp. 331-345. 12. Liebowitz, Jay (2000), Building Organizational Intelligence. CRC Press, NY. 13. Kohli, Ajay K. and Bernard J. Jaworski (1990), “Market Orientation: The Construct, Research Propositions, and Managerial Implications,” Journal of Marketing, 54 (April) 1-18. 14. Deshpande & Zaltman (1982), “Factors Affecting the Use of Market Research Information: A Path Analysis,” Journal of Marketing Research, February: 14-31. 15. Moorman, C. (1995), “Organizational Market Information Processes: Culture antecedents and New Product Outcomes,” Journal of Marketing Research, 32: 318-335. 16. Matsuno, K. & Mentzer J. T. (2000), “The Effects of Strategy Type on the Market Orientation-Performance Relationship,” Journal of Marketing, 64: 1-16. 17. Narver, C. John and Stanley F. Slater (1990), “The Effect of a Market Orientation on Business Profitability,” Journal of Marketing, October 20-35. 18. Voss, G. B & Voss, Z. G. (2000), “Strategic Orientation and Firm Performance in an Artistic Environment,” Journal of Marketing , Vol.64: 67-83. 19. Li, Tiger & Roger J. Calantone (1998), “The Impact of Market Knowledge Competence on New Product Advantage: Conceptualization an Empirical Examination,” Journal of Marketing, October, 13-29. 20. Gatignon, Hubert and Jean-Marc Xuereb (1997), “Strategic Orientation of the Firm and New Product Performance,” Journal of Marketing Research, (February) 77-90. 21. Ottum, D. Brian and William L. Moore (1997), “The Role of Market Information in New Product Success/Failure,” Journal of Product Innovation Management, Volume 14 (4) 258-273. 22. Maltz, E & Kohli, A. K (1996), “Market Intelligence Dissemination Across Functional Boundaries,” Journal of Marketing Research, 23 (February): 47-61. 23. Grewal, R. & Tansuhaj, P. (2001), “Building Organizational Capabilities for Managing Economic Crisis: The Role of Market Orientation and Strategic Flexibility,” Journal of Marketing, Vol.65: 67-80. 24. Akgun, A. Ekber (2001), “Learning Typology for new product development teams: A socio-cognitive perspective,” Unpublished Dissertation, the Faculty of the Stevens Institute of Technology. 25. Cooper, R. G. (1979), “The Dimensions of Industrial New Product Success and Failure,” Journal Of Marketing Summer 93-103. 26. Cooper, R. G. and E. J. Kleinschmidt (1987), “New Products: What Separates Winners from Losers?” Journal of Product Innovation Management, 4: 169-184.

27. Calantone, J. Roger and C. Anthony di Benedetto (1988), “An Integrative Model of the New Product Development Process: An Empirical Validation” Journal of Product Innovation Management 5: 201-215. 28. Song, X. Michael and Mark E. Parry (1997), “The Determinants of Japanese New Product Successes,” Journal of Marketing Research, February 64-76. 29. Harmsen, Hanne, Klaus G. Grunert, and Karsten Bove (2000), “Company Competencies as a Network: the Role of Product Development,” Journal of Product Innovation Management, 17: 194-207. 30. Hambrick, C. Donald (1981), “Environment, Strategy, and Power Within Top Management Teams,” Administrative Science Quarterly, 26: 253-276. 31. Howell, M. Jane and Christine M. Shea (2000), “Individual differences, environmental scanning, Innovation framing and champion behavior: key predictors of project performance,” Journal of Product Innovation Management, 18: 15-27. 32. Li, Tiger & Roger J. Calantone (1998), “The Impact of Market Knowledge Competence on New Product Advantage: Conceptualization an Empirical Examination,” Journal of Marketing, October, 13-29. 33. Olson, Walker, and Ruekert (1995), “Organizing for effective new product development: The moder”, Journal of Marketing, January, Vol. 59, Iss. 1; pg. 48, 15 pgs. 34. Day, G (1991), “Learning About Markets,” Marketing Science Institute Report, No.91-117. Cambridge. Marketing Science Institute. 35. Day, G. (1994), “The capabilities of market-driven organizations,” Journal of Marketing 58: .37-52. 36. Hurley and Hult (1998), “Innovation, market orientation, and organizational learning: An integration and empirical examination” Journal of Marketing, Vol. 62, Iss. 3; pg. 42, 13 pgs. 37. Lukas, A. Bryan and O.C Ferrell (2000), “The Effect of Market Orientation on Product Innovation,” Journal of the Academy of Marketing Science, Volume 28, No.2, pages 239-247. 38. Tidd, J. (1997), “Complexity, Networks and Learning: Integrative Themes for Research on Innovation Management,” International Journal of Innovation Management, 1: 1-21. 39. Hughes, G. D. & Chafin, D. C. (1996), “Turning New Product Development into a Continuous Learning Process,” Journal of Product Innovation Management, 13: 89-104. 40. Adams, E. M., Day G. & Dougherty D. (1998), “Enhancing New Product Development Performance: An Organizational Learning Perspective,” Journal of Product Innovation Management, Vol. 15, Number 5: 403-422. 41. Argyris, C., & Schön, D. A. (1978), Organizational Learning: A theory of action perspective. Reading. MA: Addison-Wesley Publishing Comp. 42. Fiol, C. M. & Lyles, M.A. (1985), “Organizational Learning,” Academy of Management Review, 10: 803-813. 43. Schein, E. H. (1990), “Organizational Culture,” American Psychologist, Vol.45, pp.109-119. 44. Schein, E. H. (1993), “How Can Organizations Learn Faster? The Challenge of Entering the Green Room,” Sloan Management Review, Winter, pp. 55-62. 45. Popper, M. and Lipshitz, R (1998), “Organizational learning mechanism: a structural and cultural approach to organizational learning,” The Journal of Applied Behavior Science, Vol. 34.No.2 pp.161-179. 46. Ulrich, W and Lake D. (1991), “Organizational Capability: Creating Competitive Advantage,”Academy of Management Executive, Vol. 5, No.1, pp. 177-191. 47. Smith, M. E (1997), “Disciplines of Organizational learning: contributions and critiques,” Human Relations, Vol.50 no.9 pp.1085-1112. 48. Hamel, G and Prahalad, C. K (1993), “Strategies as stretch and leverage,” Harvard Business Review, March-April pp.75-84. 49. Huber, G. P. (1991), “Organizational Learning: the Contributing Processes and the Literatures,” Organization Science, 2: 88-115. 50. Ribbens, B. A. (1997), “Organizational Learning Styles: categorizing strategic predisposition from learning,” The international Journal of Organizational Analysis, Vol.5, No. 1, pp.59-73. 51. Daft, R. L. & Weick, K. E. (1984), “Toward a Model of Organizations as Interpretation Systems” Academy of Management Review, 9:284-295. 52. Beyer, Janice M. and Harrison M. Trice (1982), “The utilization Process: A conceptual Framework and Synthesis of Empirical Findings” Administrative Science Quarterly, 27 (December) 591-622.

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