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Organizational learning and technological innovation: the distinct dimensions of novelty and meaningfulness that impact firm performance

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Abstract

This manuscript delineates technological innovation into the separate dimensions of novelty and meaningfulness to examine how a firm’s organizational learning modes of adaptive learning and experimental learning, together with unabsorbed slack resources, influence the effects of novelty and meaningfulness on firm financial performance. The multi-method empirical approach leverages secondary data from firm patent information and COMPUSTAT, and primary data from senior executives at 167 firms in various high-tech industries. The results indicate that adaptive learning heightens meaningfulness but diminishes novelty, whereas experimental learning harms meaningfulness. Additionally, firms’ unabsorbed slack resources moderate the relationships of experimental and adaptive learning with novelty. In particular, experimental learning enhances novelty only when a firm has sufficient unabsorbed slack to adjust resource levels in accordance with experimentation. Further, the results suggest that meaningfulness increases firm financial performance as represented by Tobin’s q, both independently and jointly when considered with novelty. These insights underscore the necessity of treating novelty and meaningfulness as separate dimensions of technological innovation that impact firm performance.

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References

  • Ahuja, G., & Morris Lampert, C. (2001). Entrepreneurship in the large corporation: A longitudinal study of how established firms create breakthrough inventions. Strategic Management Journal, 22(6–7), 521–543.

    Google Scholar 

  • Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Newbury Park: Sage.

  • Amit, R., & Schoemaker, P. J. H. (1993). Strategic assets and organizational rent. Strategic Management Journal, 14(1), 33–46.

    Google Scholar 

  • Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–425.

    Google Scholar 

  • Argote, L. (2012). Organizational learning: Creating, retaining and transferring knowledge. Springer Science & Business Media.

  • Argyris, C., & Schon, D. A. (1978). Organizational learning: A theory of action perspective. Reading: Addison-Wesley.

    Google Scholar 

  • Armstrong, S. J., & Overton, T. S. (1977). Estimating non-response bias in mail surveys. Journal of Marketing Research, 14(3), 396–402.

    Google Scholar 

  • Arnold, T. J., Fang, E. E., & Palmatier, R. W. (2011). The effects of customer acquisition and retention orientations on a firm’s radical and incremental innovation performance. Journal of the Academy of Marketing Science, 39(2), 234–251.

    Google Scholar 

  • Bagozzi, R. P., Yi, Y., & Phillips, L. W. (1991). Assessing construct validity in organizational research. Administrative Science Quarterly, 36(3), 421–458.

    Google Scholar 

  • Baker, W. E., & Sinkula, J. M. (1999). The synergistic effect of market orientation and learning orientation on organizational performance. Journal of the Academy of Marketing Science, 27(4), 411–427.

    Google Scholar 

  • Bell, S. J., Whitwell, G. J., & Lukas, B. A. (2002). Schools of thought in organizational learning. Journal of the Academy of Marketing Science, 30(1), 70–86.

    Google Scholar 

  • Bonaccorsi, A., & Thoma, G. (2007). Institutional complementarity and inventive performance in nano science and technology. Research Policy, 36(6), 813–831.

    Google Scholar 

  • Bourgeois, L. J. (1981). On the measurement of organizational slack. Academy of Management Review, 6(1), 29–39.

    Google Scholar 

  • Brady, T., & Davies, A. (2004). Building project capabilities: From exploratory to exploitative learning. Organization Studies, 25(9), 1601–1621.

    Google Scholar 

  • Cankurtaran, P., Langerak, F., & Griffin, A. (2013). Consequences of new product development speed: A meta-analysis. Journal of Product Innovation Management, 30(3), 465–486.

    Google Scholar 

  • Cardinal, L. B. (2001). Technological innovation in the pharmaceutical industry: The use of organizational control in managing research and development. Organization Science, 12(1), 19–36.

    Google Scholar 

  • Chakravarthy, B. S. (1982). Adaptation: A promising metaphor for strategic management. Academy of Management Review, 7(1), 35–44.

    Google Scholar 

  • Chandrasekaran, D., & Tellis, G. J. (2011). Getting a grip on the saddle: Chasms or cycles? Journal of Marketing, 75(4), 21–34.

    Google Scholar 

  • Chandy, R., & Tellis, G. J. (1998). Organizing for radical product innovation: The overlooked role of willingness to cannibalize. Journal of Marketing Research, 35(4), 474–487.

    Google Scholar 

  • Chandy, R., Narasimhan, O., Hopstaken, B., & Prabhu, J. (2006). From invention to innovation: conversion ability in product development. Journal of Marketing Research, 35(3), 494–508.

    Google Scholar 

  • Cheng, J., & Kesner, I. (1997). Organizational slack and response to environmental shifts: The impact of resource allocation patterns. Journal of Management, 23(1), 1–18.

    Google Scholar 

  • Chung, K. H., & Pruitt, S. W. (1994). A simple approximation of Tobin’s Q. Financial Management, 23(3), 70–77.

    Google Scholar 

  • Churchill, G. A. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16(1), 64–73.

    Google Scholar 

  • Cohen, W., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128–152.

    Google Scholar 

  • Crossan, M. M., & Berdrow, I. (2003). Organizational learning and strategic renewal. Strategic Management Journal, 24(11), 1087–1105.

    Google Scholar 

  • Daniel, F., Lohrke, F. T., Fornaciari, C. J., & Turner, R. A. (2004). Slack resources and firm performance: A meta-analysis. Journal of Business Research, 57(6), 565–574.

    Google Scholar 

  • Day, G. S. (2014). An outside-in approach to resource-based theories. Journal of the Academy of Marketing Science, 42(1), 27–28.

    Google Scholar 

  • De Luca, L. M. D., & Atuahene-Gima, K. (2007). Market knowledge dimensions and cross-functional collaboration: Examining the different routes to product innovation performance. Journal of Marketing, 71(1), 95–112.

    Google Scholar 

  • Denrell, J., & March, J. (2001). Adaptation as information restriction: The hot stove effect. Organization Science, 12(5), 523–538.

    Google Scholar 

  • Fang, E., Palmatier, R. W., Scheer, L. K., & Li, N. (2008a). Trust at different organizational levels. Journal of Marketing, 72(2), 80–98.

    Google Scholar 

  • Fang, E., Palmatier, R. W., & Steenkamp, J. B. E. (2008b). Effect of service transition strategies on firm value. Journal of Marketing, 72(5), 1–14.

    Google Scholar 

  • Fleming, L., & Sorenson, O. (2001). Technology as a complex adaptive system: Evidence from patent data. Research Policy, 30(7), 1019–1039.

    Google Scholar 

  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 28(1), 39–50.

    Google Scholar 

  • Garcia, R., & Calantone, R. (2002). A critical look at technological innovation typology and innovativeness terminology: A literature review. Journal of Product Innovation Management, 19(2), 110–132.

    Google Scholar 

  • Gatignon, H., & Xuereb, J.-M. (1997). Strategic orientation of the firm and new product performance. Journal of Marketing Research, 34(1), 77–90.

    Google Scholar 

  • Gerbing, D., & Anderson, J. (1988). An updated paradigm for scale development incorporating unidimensionality and its assessment. Journal of Marketing Research, 25(2), 186–192.

    Google Scholar 

  • Gupta, A. K., Smith, K. G., & Shalley, C. E. (2006). The interplay between exploration and exploitation. Academy of Management Journal, 49(4), 693–706.

    Google Scholar 

  • Hall, B. H., Jaffe, A. B., & Trajtenberg, M. (2001). The NBER patent citation data file: Lessons, insights and methodological tools. (No. 8498). National Bureau of Economic Research.

  • Han, J. K., Kim, N., & Srivastava, R. K. (1998). Market orientation and organizational performance: Is innovation a missing link? Journal of Marketing, 62(4), 30–45.

    Google Scholar 

  • Hauser, J. R., Tellis, G., & Griffin, A. (2006). Research on innovation: A review and agenda for marketing science. Marketing Science, 25(6), 687–717.

    Google Scholar 

  • Hill, C. W., & Rothaermel, F. T. (2003). The performance of incumbent firms in the face of radical technological innovation. Academy of Management Review, 28(2), 257–274.

    Google Scholar 

  • Huang, J. W., & Li, Y. H. (2012). Slack resources in team learning and project performance. Journal of Business Research, 65(3), 381–388.

    Google Scholar 

  • Huber, G. P. (1991). Organizational learning: The contributing processes and the literature. Organization Science, 2(1), 88–115.

    Google Scholar 

  • Hurley, R. F., & Hult, G. T. M. (1998). Innovation, market orientation, and organizational learning: An integration and empirical examination. Journal of Marketing, 62, 42–54.

    Google Scholar 

  • Im, S., & Workman, J. P. (2004). Market orientation, creativity, and new product performance in high-technology firms. Journal of Marketing, 68(2), 114–132.

    Google Scholar 

  • Jaffe, A. B., & Trajtenberg, M. (2002). Patents, citations and innovations: A window on the knowledge economy. Boston: MIT Press.

    Google Scholar 

  • Jaworski, B. J., & Kohli, A. K. (1993). Market orientation: Antecedents and consequences. Journal of Marketing, 57(3), 53–70.

    Google Scholar 

  • Josephson, B. W., Johnson, J. L., & Mariadoss, B. J. (2016). Strategic marketing ambidexterity: Antecedents and financial consequences. Journal of the Academy of Marketing Science, 44(4), 539–554.

    Google Scholar 

  • Katsikeas, C. S., Leonidou, C. N., & Zeriti, A. (2016). Eco-friendly product development strategy: Antecedents, outcomes, and contingent effects. Journal of the Academy of Marketing Science, 44(6), 660–684.

    Google Scholar 

  • Kitchell, S. (1995). Corporate culture, environmental adaptation, and innovation adoption: a qualitative/quantitative approach. Journal of the Academy of Marketing Science, 23(3), 195–205.

    Google Scholar 

  • Lee, R., & Grewal, R. (2004). Strategic responses to new technologies and their impact on firm performance. Journal of Marketing, 68(4), 157–171.

    Google Scholar 

  • Leonard-Barton, D. (1992). Core capabilities and core rigidities: A paradox in managing new product development. Strategic Management Journal, 13(2), 111–125.

    Google Scholar 

  • Levinthal, D., & March, J. (1993). The myopia of learning. Strategic Management Journal, 14(S2), 95–112.

    Google Scholar 

  • Levitt, B., & March, J. (1988). Organizational learning. Annual Review of Sociology, 14, 319–340.

    Google Scholar 

  • Matzler, K., Veider, V., Hautz, J., & Stadler, C. (2015). The impact of family ownership, management, and governance on innovation. Journal of Product Innovation Management, 32(3), 319–333.

    Google Scholar 

  • McGrath, R. G. (2001). Exploratory learning, innovative capacity, and managerial oversight. Academy of Management Journal, 44(1), 118–131.

    Google Scholar 

  • Mohr, J. J., & Sarin, S. (2009). Drucker’s insights on market orientation and innovation: Implications for emerging areas in high-technology marketing. Journal of the Academy of Marketing Science, 37(1), 85–96.

    Google Scholar 

  • Moorman, C., & Miner, A. S. (1997). The impact of organizational memory in new product performance and creativity. Journal of Marketing Research, 34(1), 91–106.

    Google Scholar 

  • Moorman, C., & Miner, A. S. (1998a). The convergence of planning and execution: Improvisation in new product development. Journal of Marketing, 62(3), 1–20.

    Google Scholar 

  • Moorman, C., & Miner, A. S. (1998b). Organizational improvisation and organizational memory. Academy of Management Review, 23(4), 698–723.

    Google Scholar 

  • Morgan, N. A. (2012). Marketing and business performance. Journal of the Academy of Marketing Science, 40(1), 102–119.

    Google Scholar 

  • Morgan, N. A., & Rego, L. L. (2006). The value of different customer satisfaction and loyalty metrics in predicting business performance. Marketing Science, 25(5), 426–439.

    Google Scholar 

  • Nakata, C., Rubera, G., Im, S., Pae, J. H., Lee, H. J., Onzo, N., & Park, H. (2018). New product creativity antecedents and consequences: Evidence from South Korea, Japan, and China. Journal of Product Innovation Management., 35, 939–959. https://doi.org/10.1111/jpim.12436.

    Article  Google Scholar 

  • Nohria, N., & Gulati, R. (1996). Is slack good or bad for innovation? Academy of Management Journal, 39(5), 1245–1264.

    Google Scholar 

  • Nonaka, I. (1994). A dynamic theory of organizational knowledge creation. Organization Science, 5(1), 14–37.

    Google Scholar 

  • O’Brien, J. P., & David, P. (2014). Reciprocity and R&D search: Applying the behavioral theory of the firm to a communitarian context. Strategic Management Journal, 35(4), 550–565.

    Google Scholar 

  • Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903.

    Google Scholar 

  • Posen, H. E., & Levinthal, D. A. (2012). Chasing a moving target: Exploitation and exploration in dynamic environments. Management Science, 58(3), 587–601.

    Google Scholar 

  • Prabhu, J., Chandy, R. K., & Ellis, M. E. (2005). The impact of acquisitions on innovation: Poison pill, placebo, or tonic? Journal of Marketing, 69(1), 114–130.

    Google Scholar 

  • Reitzig, M. (2003). What determines patent value?: Insights from the semiconductor industry. Research Policy, 32(1), 13–26.

    Google Scholar 

  • Rindfleisch, A., Malter, A. J., Ganesan, S., & Moorman, C. (2008). Cross-sectional versus longitudinal survey research: Concepts, findings, and guidelines. Journal of Marketing Research, 45(3), 261–279.

    Google Scholar 

  • Sethi, R., Smith, D., & Park, C. (2001). Cross-functional product development teams, creativity, and the innovativeness of new consumer products. Journal of Marketing Research, 38(1), 73–85.

    Google Scholar 

  • Singh, J. V. (1986). Performance, slack, and risk taking in organizational decision making. Academy of Management Journal, 29(3), 562–585.

    Google Scholar 

  • Sinkula, J. M. (1994). Market information processing and organizational learning. Journal of Marketing, 58(1), 35–45.

    Google Scholar 

  • Slater, S. F., & Narver, J. C. (1995). Marketing orientation and the learning orientation. Journal of Marketing, 59(3), 63–74.

    Google Scholar 

  • Slater, S. F., & Narver, J. C. (2000). Intelligence generation and superior customer value. Journal of the Academy of Marketing Science, 28(1), 120–127.

    Google Scholar 

  • Slater, S. F., Hult, G. T. M., & Olson, E. M. (2007). On the importance of matching strategic behavior and target market selection to business strategy in high-tech markets. Journal of the Academy of Marketing Science, 35(1), 5–17.

    Google Scholar 

  • Sood, A., & Tellis, G. J. (2005). Technological evolution and radical innovation. Journal of Marketing, 69(3), 152–168.

    Google Scholar 

  • Srinivasan, R. (2006). Dual distribution and intangible firm value: Franchising in restaurant chains. Journal of Marketing, 70(3), 120–135.

    Google Scholar 

  • Stanko, M. A., Bohlmann, J. D., & Molina-Castillo, F. J. (2013). Demand-side inertia factors and their benefits for innovativeness. Journal of the Academy of Marketing Science, 41(6), 649–668.

    Google Scholar 

  • Stock, R. M., & Reiferscheid, I. (2014). Who should be in power to encourage product program innovativeness, R&D or marketing? Journal of the Academy of Marketing Science, 42(3), 264–276.

    Google Scholar 

  • Stock, R. M., & Zacharias, N. A. (2011). Patterns and performance outcomes of innovation orientation. Journal of the Academy of Marketing Science, 39(6), 870–888.

    Google Scholar 

  • Stock, R. M., Six, B., & Zacharias, N. A. (2013). Linking multiple layers of innovation-oriented corporate culture, product program innovativeness, and business performance: A contingency approach. Journal of the Academy of Marketing Science, 41(3), 283–299.

    Google Scholar 

  • Subramanian, A., & Nilakanta, S. (1996). Organizational innovativeness: Exploring the relationship between organizational determinants of innovation, types of innovations, and measures of organizational performance. Omega, 24(6), 631–647.

    Google Scholar 

  • Szymanski, D. M., Kroff, M. W., & Troy, L. C. (2007). Innovativeness and new product success: Insights from the cumulative evidence. Journal of the Academy of Marketing Science, 35(1), 35–52.

    Google Scholar 

  • Tan, J., & Peng, M. W. (2003). Organizational slack and firm performance during economic transition: Two studies from a emerging economy. Strategic Management Journal, 24(13), 1249–1263.

    Google Scholar 

  • Tyre, M., & von Hippel, E. (1997). The situated nature of adaptive learning in organizations. Organization Science, 8(1), 71–83.

    Google Scholar 

  • Vorhies, D. W., Orr, L. M., & Bush, V. D. (2011). Improving customer-focused marketing capabilities and firm financial performance via marketing exploration and exploitation. Journal of the Academy of Marketing Science, 39(5), 736–756.

    Google Scholar 

  • Weerawardena, J., Mort, G. S., Salunke, S., Knight, G., & Liesch, P. W. (2015). The role of the market sub-system and the socio-technical sub-system in innovation and firm performance: A dynamic capabilities approach. Journal of the Academy of Marketing Science, 43(2), 221–239.

    Google Scholar 

  • Wu, J., & Tu, R. (2007). CEO stock option pay and R&D spending: A behavioral agency explanation. Journal of Business Research, 60(5), 482–492.

    Google Scholar 

  • Wuyts, S., Dutta, S., & Stremersch, S. (2004). Portfolios of interfirm agreements in technology-intensive markets: Consequences for innovation and profitability. Journal of Marketing, 68(2), 88–100.

    Google Scholar 

  • Yang, H., Phelps, C., & Steensma, H. K. (2010). Learning from what others have learned from you: The effects of knowledge spillovers on originating firms. Academy of Management Journal, 53(2), 371–389.

    Google Scholar 

  • Zahra, S. A., & George, G. (2002). Absorptive capacity: A review, reconceptualization, and extension. Academy of Management Review, 27(2), 185–203.

    Google Scholar 

  • Zhao, M. (2006). Conducting R&D in countries with weak intellectual property rights protection. Management Science, 52(8), 1185–1199.

    Google Scholar 

  • Zhou, K., Yim, B., & Tse, D. (2005). The effects of strategic orientations on technology- and market-based breakthrough innovations. Journal of Marketing, 69(2), 42–60.

    Google Scholar 

  • Zollo, M., & Winter, S. (2002). Deliberate learning and the evolution of dynamic capabilities. Organization Science, 13(3), 339–351.

    Google Scholar 

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Acknowledgements

The third author acknowledes the financial support of the National Natural Science Foundation of China(71573079).

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Authors and Affiliations

  1. School of Economics and Management, Beijing Jiaotong University, Beijing, China

    Li Zuo

  2. Farmer School of Business, Miami University, 800 E. High Street, Oxford, OH, 45056, USA

    Gregory J. Fisher

  3. School of Business Administration, Hunan University, Changsha, Hunan Province, China

    Zhi Yang

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  1. Li Zuo
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Appendix

Appendix

Items and constructs

Factor loading

Experimental Learning (coefficient alpha: 0.85, average variance extracted: 0.63)

1. Our firm stresses the importance of learning from R&D experimentation.

0.85

2. Our firm often experiments with different development approaches and methods to enhance our R&D knowledge.

0.75

3. Our firm encourages employees to try different development methods to enhance our R&D knowledge, even though the outcomes of these methods are uncertain.

0.81

4. Our firm regards failures of R&D experimentation activities as learning experiences, rather than development costs.

0.76

5. We gain a great deal of knowledge through our repeated trial-and-error R&D processes.

0.78

Adaptive Learning (coefficient alpha: 0.84, average variance extracted: 0.62)

1. Our firm emphasizes the importance of tracking the R&D activities by industry leaders.

0.82

2. Our firm encourages researchers and developers to adjust their skills and knowledge to catch up with industry leaders.

0.87

3. We adapt our R&D approaches to follow technological opportunities pursued by industry leaders.

0.72

4. Our firm continuously improves our innovation knowledge to face industry leaders.

0.79

5. We consistently keep track of the differences we have with industry leaders.

0.73

Environmental Dynamism (coefficient alpha: 0.81, average variance extracted: 0.60)

1. In the market, customers’ preferences change quickly over time.

0.88

2. Market demand and consumer tastes have been unpredictable.

0.69

3. Actions of competitors have been highly unpredictable.

0.74

4. The competition of our firm is changing very rapidly.

0.77

5. It is very difficult to forecast where technology will be in the next five years.

0.82

Model Fit Indices: chi-square (d.f. = 87): 134.87; GFI: .92; CFI: .97; NFI: 0.90; RMSEA: .05

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Zuo, L., Fisher, G.J. & Yang, Z. Organizational learning and technological innovation: the distinct dimensions of novelty and meaningfulness that impact firm performance. J. of the Acad. Mark. Sci. 47, 1166–1183 (2019). https://doi.org/10.1007/s11747-019-00633-1

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