Skip to main content
SpringerLink
Log in

A four-factor model of knowledge agglomeration

  • Published:
Asia Pacific Journal of Management Aims and scope Submit manuscript

Abstract

This study develops a comprehensive four-factor model to analyze the factors that influence knowledge agglomeration. To test the model empirically, we use a dataset from firms in China’s digital industry and employ the structural equation model and RM-DEMATEL method to determine the relationship between these factors and their impact on knowledge agglomeration. We find that effectiveness, coupling, and talent synergy have significant positive impact on knowledge agglomeration. Instead, knowledge concentration has an inverted U-shaped relationship with knowledge agglomeration. In addition, knowledge concentration moderates the relationship between knowledge effectiveness, coupling, talent synergy, and knowledge agglomeration. Based on these findings, we construct a multi-dimensional indicator system that allows us to assess more extensively the roles of those factors, we find that knowledge concentration is a fundamental factor in this system. The density and speed of concentration and knowledge causality also play important roles. Our findings offer a theoretical framework for firms in developing their knowledge management strategies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Notes

  1. For example: knowledge agglomeration at Stanford University’s industrial Park. In 1953, Stanford provost Frederick Emmons Terman established the honors cooperative program, which allowed some electronics companies to send employees to Stanford for degrees to strengthen corporate ties with the university. In addition, the industrial affiliates Program was launched to provide companies with the scientific and technical results of related research projects. These two programs are based on the needs of companies to acquire knowledge and potential employees, and realize the knowledge agglomeration around Stanford University.

    Therefore, if an enterprise want to promote the effective agglomeration of knowledge resources and realize the real competitiveness, it is necessary to build a platform that can make knowledge resources efficiently agglomeration, and the essence of this knowledge agglomeration platform is an effective way of knowledge resources allocation.

  2. Abraham Flexner disputed Kodak’s founder, George Eastman’s view, that the radio invented by Guglielmo Marconi was the most useful invention, arguing that the theoretical contributions of Clark Maxwell and Heinrich Hertz were more useful. He wrote that although Maxwell’s theory of electromagnetism published in 1873 was entirely abstract mathematics, and Hertz in 1887 was not concerned about the practical value of his experiments on electromagnetic waves, these seemingly useless studies laid the foundation for later useful inventions, without which Marcony’s inventions would not have been possible.

  3. The “Statistical Classification of the Digital Economy and Its Core Industries (2021)” has been adopted at the 10th executive meeting of the National Bureau of Statistics on May 14, 2021. http://www.gov.cn/.

  4. Select the ratio of chi-square to degrees of freedom (CMIN/DF), root mean square error of approximation (RMSEA), goodness-of-fit index (GFI), comparative fit index (CFI), adjusted goodness-of-fit index (AGFI), Tucker-Lewis index (TLI), normed fit index (NFI), incremental fit index (IFI) to evaluate the fit of the model. CMIN/DF is between 1 and 3; RMSEA is less than .08; GFI, AGFI, TFI, IFI, CFI fit indicators are greater than .90.

  5. DEMATEL was proposed by Gabus and Fontela of Battelle Laboratories in the United States at a meeting in Geneva in 1971, aiming to analyze the relationship between various factors in a system. To overcome the limitations of the DEMATEL, the RM-DEMATEL combined the relationship graph and the BP artificial neural network model to construct the direct influence matrix. This method can simultaneously determine: 1) the classification of factors, 2) the degree of mutual influence between factors, and 3) the importance of each factor in the system.

  6. Supplement: The scope of digital knowledge (Resources) is vast, covering any resource that exists or is stored in digital format, regardless of its value or form.

References

  • Agarwal, R., Audretsch, D., & Sarkar, M. (2010). Knowledge spillovers and strategic entrepreneurship. Strategic Entrepreneurship Journal, 4(4), 271–283.

    Article  Google Scholar 

  • Aistleitner, M., Grabner, C., & Hornykewycz, A. (2021). Theory and empirics of capability accumulation: Implications for macroeconomic modeling? Research Policy, 50(6), 104258.

    Article  Google Scholar 

  • Ansoff, H. I. (1957). Strategies for diversification. Harvard Business Review, 35(5), 113–124.

    Google Scholar 

  • Antonelli, C., & Colombelli, A. (2015). The knowledge cost function. International Journal of Production Economics, 168, 290–302.

    Article  Google Scholar 

  • Argote, L., & Ingram, P. (2000). Knowledge transfer: A basis for competitive advantage in firms. Organizational Behavior and Human Decision Processes, 82(1), 150–169.

    Article  Google Scholar 

  • Auerswald, P. E., & Branscomb, L. M. (2003). Valleys of death and darwinian seas: Financing the invention to innovation transition in the United States. The Journal of Technology Transfer, 28(3/4), 227–239.

    Article  Google Scholar 

  • Autry, C. W., & Griffis, S. E. (2008). Supply chain capital: The impact of structural and relational linkages on firm execution and innovation. Journal of Business Logistics, 29(1), 157–173.

    Article  Google Scholar 

  • Bhagat, R. S., Kedia, B. L., Harveston, P. D., & Triandis, H. C. (2002). Cultural variations in the cross-border transfer of organizational knowledge: An integrative framework. Academy of Management Review, 27(2), 204–221.

    Article  Google Scholar 

  • Boisot, M. H. (1995). Is your firm a creative destroyer? Competitive learning and knowledge flows in the technological strategies of firms. Research policy, 24(24), 489–506.

    Article  Google Scholar 

  • Brachos, D., Kostopoulos, K., Eric Soderquist, K., & Prastacos, G. (2007). Knowledge effectiveness, social context and innovation. Journal of Knowledge Management, 11(5), 31–44.

    Article  Google Scholar 

  • Burrell, E., & Brauner, E. (2021). Knowing and sharing: Transactive knowledge systems and psychological safety. Organisationsberatung, Supervision, Coaching, 28, 303–317.

    Article  PubMed Central  Google Scholar 

  • Chadwick, C., Super, J. F., & Kwon, K. (2015). Resource orchestration in practice: CEO emphasis on SHRM, commitment-based HR systems, and firm performance. Strategic Management Journal, 36(3), 360–376.

    Article  Google Scholar 

  • Chang, Y. Y., Gong, Y., & Peng, M. W. (2012). Expatriate knowledge transfer, subsidiary absorptive capacity, and subsidiary performance. Academy of Management Journal, 55(4), 927–948.

    Article  Google Scholar 

  • Che, Z., Wu, C. Q., Qu, W. S., & Zhang, N. C. (2023). How does multidimensional interaction of knowledge transfer affect digital innovation capability? Knowledge Management Research & Practice. https://doi.org/10.1080/14778238.2023.2261892

  • Chen, Y., Liu, J., Li, Y., Sadiq, R., & Deng, Y. (2015). RM-DEMATEL: A new methodology to identify the key factors in PM 2.5. Environmental Science and Pollution Research, 22(8), 6372–6380.

    Article  CAS  PubMed  Google Scholar 

  • Chuang, C. H., Jackson, S. E., & Jiang, Y. (2016). Can knowledge-intensive teamwork be managed? Examining the roles of HRM systems, leadership, and tacit knowledge. Journal of Management, 42(2), 524–554.

    Article  Google Scholar 

  • Chyi, Y. L., Lai, Y. M., & Liu, W. H. (2012). Knowledge spillovers and firm performance in the high-technology industrial cluster. Research Policy, 41(3), 556–564.

    Article  Google Scholar 

  • Cimon, Y. (2004). Knowledge-related asymmetries in strategic alliances. Journal of Knowledge Management, 8(3), 17–30.

    Article  Google Scholar 

  • Coenen, L., Benneworth, P., & Truffer, B. (2012). Toward a spatial perspective on sustainability transitions. Research Policy, 41(6), 968–979.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Conner, K. (1991). A historical comparison of resource-based theory and five schools of thought within industrial organization economics: Do we have a new theory of the firm? Journal of Management, 17(1), 121–154.

    Article  Google Scholar 

  • Cummings, J. L., & Teng, B. S. (2003). Transferring R&D knowledge: The key factors affecting knowledge transfer success. Journal of Engineering and Technology Management, 20(1–2), 39–68.

    Article  Google Scholar 

  • Davis, J. P., & Aggarwal, V. A. (2020). Knowledge mobilization in the face of imitation: Microfoundations of knowledge aggregation and firm-level innovation. Strategic Management Journal, 41(11), 1983–2014.

    Article  Google Scholar 

  • Di Cintio, M., Ghosh, S., & Grassi, E. (2017). Firm growth, R&D expenditures and exports: An empirical analysis of italian SMEs. Research Policy, 46(4), 836–852.

    Article  Google Scholar 

  • Drucker, P. F. (1993). The rise of the knowledge society. The Wilson Quarterly, 17(2), 52–72.

    Google Scholar 

  • Drucker, P. F. (2002). They’re not employees, they’re people. Harvard Business Review, 80(2), 70–77.

    PubMed  Google Scholar 

  • Duanmu, J., & Fai, F. M. (2007). A processual analysis of knowledge transfer: From foreign MNEs to Chinese suppliers. International Business Review, 16(4), 449–473.

    Article  Google Scholar 

  • Filatotchev, I., Liu, X., Lu, J., & Wright, M. (2011). Knowledge spillovers through human mobility across national borders: Evidence from Zhongguancun Science Park in China. Research Policy, 40(3), 453–462.

    Article  Google Scholar 

  • Flexner, A., & Dijkgraaf, R. (2017). The usefulness of useless knowledge. Princeton University Press.

    Book  Google Scholar 

  • Fores, B., & Camison, C. (2016). Does incremental and radical innovation performance depend on different types of knowledge accumulation capabilities and organizational size? Journal of Business Research, 69(2), 831–848.

    Article  Google Scholar 

  • Foss, N. J. (1996). Knowledge-based approaches to the theory of the firm: Some critical comments. Organization Science, 7(5), 470–476.

    Article  Google Scholar 

  • Gao, F., Li, M., & Clarke, S. (2008). Knowledge, management and knowledge management in business operations. Journal of Knowledge Management, 12(2), 3–17.

    Article  Google Scholar 

  • Gaviria-Marin, M., Merigo, J. M., & Popa, S. (2018). Twenty years of the journal of knowledge management: A bibliometric analysis. Journal of Knowledge Management., 22(8), 1655–1687.

    Article  Google Scholar 

  • Govindarajan, V., & Kopalle, P. K. (2006). Disruptiveness of innovations: Measurement and an assessment of reliability and validity. Strategic Management Journal, 27(2), 189–199.

    Article  Google Scholar 

  • Grant, R. M. (1996). Toward a knowledge-based theory of the firm. Strategic Management Journal, 17, 109–122.

    Article  Google Scholar 

  • Grant, R. M., & Baden-Fuller, C. (2004). A knowledge accessing theory of strategic alliances. Journal of Management Studies., 41(1), 61–84.

    Article  Google Scholar 

  • Gray, P. H., & Meister, D. B. (2004). Knowledge sourcing effectiveness. Management Science, 50(6), 821–834.

    Article  Google Scholar 

  • Grimpe, C., & Kaiser, U. (2010). Balancing internal and external knowledge acquisition: The gains and pains from R&D outsourcing: R&D outsourcing. Journal of Management Studies, 47(8), 1483–1509.

    Article  Google Scholar 

  • Haans, R. F., Pieters, C., & He, Z. L. (2016). Thinking about U: Theorizing and testing U-and inverted U-shaped relationships in strategy research. Strategic Management Journal, 37(7), 1177–1195.

    Article  Google Scholar 

  • Haas, M. R., & Hansen, M. T. (2007). Different knowledge, different benefits: Toward a productivity perspective on knowledge sharing in organizations. Strategic Management Journal, 28(11), 1133–1153.

    Article  Google Scholar 

  • Haken, H. (2004). An introduction. In Synergetics. Springer. https://doi.org/10.1007/978-3-662-10184-1_1

  • Hamel, G. P., Doz, Y., & Prahalad, C. K. (1989). Collaborate with your competitors and win. Harvard Business Review, 67, 133–139.

    Google Scholar 

  • Hansen, T., & Coenen, L. (2015). The geography of sustainability transitions: Review, synthesis and reflections on an emergent research field. Environmental Innovation and Societal Transitions, 17, 92–109.

    Article  Google Scholar 

  • Henderson, R., & Cockburn, I. (1994). Measuring competence? Exploring firm effects in pharmaceutical research. Strategic Management Journal, 15(Supplement S1), 63–84.

    Article  Google Scholar 

  • Jacobides, M. G., Cennamo, C., & Gawer, A. (2018). Towards a theory of ecosystems. Strategic Management Journal, 39(8), 2255–2276.

    Article  Google Scholar 

  • Jasimuddin, S. M., Connell, N., & Klein, J. H. (2012). Knowledge transfer frameworks: An extension incorporating knowledge repositories and knowledge administration. Information Systems Journal, 22(3), 195–209.

    Article  Google Scholar 

  • Jayaram, J., & Pathak, S. (2013). A holistic view of knowledge integration in collaborative supply chains. International Journal of Production Research, 51(7), 1958–1972.

    Article  Google Scholar 

  • Jehn, K. A., Nrthcraft, G. B., & Neale, M. A. (1999). Why differences make a difference: A field study of diversity, conflict, and performance in workgroups. Administrative Science Quarterly., 44(4), 741–763.

    Article  Google Scholar 

  • Jiang, J. H., & Ning, H. Y. (2011). Empirical study on knowledge transfer validity in supply chain based on four-dimension model. R&D Management (Chinese), 23(5), 118–127.

    Google Scholar 

  • Jones, N. B., & Mahon, J, F. (2012). Nimble knowledge transfer in high velocity/turbulent environments. Journal of Knowledge Management, 16(5), 774–788.

    Article  Google Scholar 

  • Kale, P., Singh, H., & Perlmutter, H. (2000). Learning and protection of proprietary assets in strategic alliances: Building relational capital. Strategic Management Journal, 21(3), 217–237.

    Article  Google Scholar 

  • Katila, R., & Ahuja, G. (2002). Something old something new: A longitudinal study of search behavior and new product introduction. Academy of Management Journal, 45(6), 1183–1194.

    Article  Google Scholar 

  • Khan, Z., Hussain, M., Shahbaz, M., Yang, S., & Jiao, Z. (2020). Natural resource abundance, technological innovation, and human capital nexus with financial development: A case study of China. Resources Policy, 65, 101585.

    Article  Google Scholar 

  • Khanna, T., Gulati, R., & Nohria, N. (1998). The dynamics of learning alliances: Competition, cooperation, and relative scope. Strategic Management Journal, 19(3), 193–210.

    Article  Google Scholar 

  • Kogut, B., & Zander, U. (1992). Knowledge of the firm, combinative capabilities, and the replication of technology. Organization Science, 3(3), 383–397.

    Article  Google Scholar 

  • Latif, K. F., Afzal, O., Saqib, A., Sahibzada, U. F., & Alam, W. (2021). Direct and configurational paths of knowledge-oriented leadership, entrepreneurial orientation, and knowledge management processes to project success. Journal of Intellectual Capital, 22(1), 149–170.

    Article  Google Scholar 

  • Lechner, C., & Dowling, M. (2003). Firm networks: External relationships as sources for the growth and competitiveness of entrepreneurial firms. Entrepreneurship & Regional Development, 15(1), 1–26.

    Article  Google Scholar 

  • Lee, K. H., & Saen, R. F. (2012). Measuring corporate sustainability management: A data envelopment analysis approach. International Journal Production Economics, 140(1), 219–226.

    Article  Google Scholar 

  • Leonard, D., & Sensiper, S. (1998). The role of tacit knowledge in group innovation. California Management Review, 40(3), 112–132.

    Article  Google Scholar 

  • Levin, D. Z., & Cross, R. (2004). The strength of weak ties you can trust: The mediating role of trust in effective knowledge transfer. Management Science, 50(11), 1463–1613.

    Article  Google Scholar 

  • Li, B. Z., Yin, S., Zeng, J. W., & Luo, X. F. (2020). Cooperative innovation mechanism and dynamic evolution of integrated supply chain based on SEM and B-Z reaction——The perspective of relationship quality of integrated supply chain. Chinese Journal of Management Science, 28(2), 166–177.

    Google Scholar 

  • March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–87.

    Article  Google Scholar 

  • Marks, M. A., Zaccaro, S. J., & Mathieu, J. E. (2000). Performance implications of leader briefings and team-interaction training for team adaptation to novel environments. Journal of Applied Psychology, 85(6), 971–986.

    Article  CAS  PubMed  Google Scholar 

  • Maskell, P. (2001). Towards a knowledge-based theory of the geographical cluster. Industrial and Corporate Change, 10(4), 921–943.

    Article  Google Scholar 

  • McDermott, R. (1999). Why information technology inspired but cannot deliver knowledge management. California Management Review, 41(4), 103–117.

    Article  Google Scholar 

  • Meier, L. L., & Spector, P. E. (2013). Reciprocal effects of work stressors and counterproductive work behavior: A five-wave longitudinal study. Journal of Applied Psychology, 98(3), 529–539.

    Article  PubMed  Google Scholar 

  • Menon, A., & Varadarajan, P. R. (1992). A model of marketing knowledge use within firms. Journal of Marketing, 56, 53–71.

    Article  Google Scholar 

  • Merali, Y. (2000). Individual and collective congruence in the knowledge management process. The Journal of Strategic Information Systems, 9(2–3), 213–234.

    Article  Google Scholar 

  • Molden, L. H., & Clausen, T. H. (2021). Playing 3D chess, or how firms can thrive under complexity: The mediating role of innovation capabilities in the use of innovation input. Journal of Business Research, 125, 1–13.

    Article  Google Scholar 

  • Mom, T. J. M., Van Den Bosch, F. A. J., & Volberda, H. W. (2007). Investigating managers’ exploration and exploitation activities: The influence of top-down, bottom-up, and horizontal knowledge inflows. Journal of Management Studies, 44(6), 910–931.

    Article  Google Scholar 

  • Mowery, D. C., Oxley, J. E., & Silverman, B. S. (1998). Technological overlap and interfirm cooperation: Implications for the resource-based view of the firm. Research Policy, 27(5), 507–523.

    Article  Google Scholar 

  • Mowery, D. C., Oxley, J. E., & Silverman, B. S. (1996). Strategic alliances and interfirm knowledge transfer. Strategic Management Journal, 17(S2), 77–91. https://doi.org/10.1002/smj.4250171108

    Article  Google Scholar 

  • Murmann, J. P. (2003). Knowledge and competitive advantage: The coevolution of firms, technology, and national institutions. Cambridge University Press.

    Book  Google Scholar 

  • Nelson, R. R., & Winter, S. G. (1982). An evolutionary theory of economic change. Harvard University Press.

    Google Scholar 

  • Nerkar, A., & Paruchuri, S. (2005). Evolution of R&D capabilities: The role of knowledge networks within a firm. Management Science, 51(5), 771–785.

    Article  Google Scholar 

  • Nickerson, J. A., & Zenger, T. R. (2004). A knowledge-based theory of the firm: The problem-solving perspective. Organization Science, 15(6), 617–632.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Numprasertchai, S., & Igel, B. (2004). Managing knowledge in new product and service development: A new management approach for innovative research organisations. International Journal of Technology Management, 28(7/8), 667–684.

    Article  Google Scholar 

  • Porter, M. E. (1990). The competitive advantage of nations. Free Press.

  • Porter, M. E. (1998). Clusters and the new economics of competition. Harvard Business Review, 76(6), 77–90.

    CAS  PubMed  Google Scholar 

  • Regnér, P., & Edman, J. (2014). MNE institutional advantage: How subunits shape, transpose and evade host country institutions. Journal of International Business Studies, 45(3), 275–302.

  • Roper, S., & Love, J. H. (2018). Knowledge context, learning and innovation: An integrating framework. Industry and Innovation, 25(4), 339–364.

    Article  Google Scholar 

  • Rothaermel, F. T., & Deeds, D. L. (2004). Exploration and exploitation alliances in biotechnology: A system of new product development. Strategic Management Journal, 25, 201–221.

    Article  Google Scholar 

  • Santoro, G., Bresciani, S., & Papa, A. (2020). Collaborative modes with cultural and creative industries and innovation performance: The moderating role of heterogeneous sources of knowledge and absorptive capacity. Technovation, 92–93, 102040.

    Article  Google Scholar 

  • Schmidt, C. G., Yan, T. T., Wagner, S. M., & Lucianetti, L. (2022). Performance implications of knowledge inputs in inter-organizational new product development projects: The moderating roles of technology interdependence. International Journal of Production Research., 60(20), 6048–6071.

    Article  Google Scholar 

  • Scuotto, V., Santoro, G., Bresciani, S., & Del Giudice, M. (2017). Shifting intra- and inter-organizational innovation processes towards digital business: An empirical analysis of SMEs. Creativity and Innovation Management, 26(3), 247–255.

    Article  Google Scholar 

  • Serenko, A. (2013). Meta-analysis of scientometric research of knowledge management: discovering the identity of the discipline. Journal of Knowledge Management, 17(5), 773–812. https://doi.org/10.1108/JKM-05-2013-0166

    Article  Google Scholar 

  • Shin, D., Konrad, A., & M. (2017). Causality between high-performance work systems and organizational performance. Journal of management, 43(4), 973–997.

    Article  Google Scholar 

  • Simonin, B. L. (1999). Ambiguity and the process of knowledge transfer in strategic alliances. Strategic Management Journal, 20(7), 595–623.

    Article  Google Scholar 

  • Singh, S. K., Gupta, S., Busso, D., & Kamboj, S. (2021). Top management knowledge value, knowledge sharing practices, open innovation and organizational performance. Journal of Business Research, 128, 788–798.

    Article  Google Scholar 

  • Sofka, W., & Grimpe, C. (2010). Specialized search and innovation performance: Evidence across Europe. R&D Management, 40(3), 310–323.

    Article  Google Scholar 

  • Strambach, S. (2017). Combining knowledge bases in transnational sustainability innovation: Micro dynamics and institutional change. Economic Geography, 93(5), 500–526.

  • Subramaniam, M., & Youndt, M. A. (2005). The influence of intellectual capital on the types of innovative capabilities. Academy of Management Journal, 48(3), 450–463.

    Article  Google Scholar 

  • Szulanski, G. (1996). Exploring internal stickiness: Impediments to the transfer of best practice within the firm. Strategic Management Journal, 17(S2), 27–43.

    Article  Google Scholar 

  • Tallman, S., Jenkins, M., Henry, N., & Pinch, S. (2004). Knowledge, clusters, and competitive advantage. Academy of Management Review, 29(2), 258–271.

    Article  Google Scholar 

  • Tanriverdi, H., & Venkatraman, N. (2005). Knowledge relatedness and the performance of multibusiness firms. Strategic Management Journal, 26(2), 97–119.

    Article  Google Scholar 

  • Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509–533.

    Article  Google Scholar 

  • Tsoukas, H. (1996). The firm as a distributed knowledge system: A constructionist approach. Strategic Management Journal, 17, 12–25.

    Article  Google Scholar 

  • Tsoukas, H., & Vladimirou, E. (2001). What is organizational knowledge? Journal of Management Studies, 38(7), 973–993.

    Article  Google Scholar 

  • Tzortzaki, A. M., & Mihiotis, A. (2014). A review of knowledge management theory and future directions. Knowledge and Process Management, 21(1), 29–41.

    Article  Google Scholar 

  • Von Krogh, G. (2003). Knowledge sharing and the communal resource. In M. Lyles, & M. Easterby-Smith (Eds.), Handbook of Organizational Learning and Knowledge Management. Blackwell Publishing.

  • Wang, W., & Lu, S. (2021). University-industry innovation community dynamics and knowledge transfer: Evidence from China. Technovation, 106(4), 102305.

    Article  Google Scholar 

  • Wang, X. H., Che, Z., Yu, H., & Wu, M. M. (2019). Network embedding, multi-channel knowledge gathering and innovation: The regulation effect of knowledge flow coupling. Nankai Business Review, 22(3), 28–39.

    Google Scholar 

  • Wu, W. W., & Lee, Y. T. (2007). Developing global managers’ competencies using the fuzzy DEMATEL method. Expert Systems with Applications, 32(2), 499–507.

    Article  Google Scholar 

  • Xie, X. M. (2015). An empirical study on multidimensional relationships between factors of synergic innovation of firms and their synergic degree. Science Research Management, 36(2), 69–78.

    Google Scholar 

  • Yayavaram, S., & Ahuja, G. (2008). Decomposability in knowledge structures and its impact on the usefulness of inventions and knowledge-based malleability. Administrative Science Quarterly, 53(2), 333–362.

    Article  Google Scholar 

  • Yetim, N., & Yetim, U. (2006). The cultural orientations of entrepreneurs and employees’ job satisfaction: The turkish small and medium sized enterprises (SMEs) case. Social Indicators Research, 77(2), 257–286.

    Article  Google Scholar 

  • Yu, F., Liu, M. X., Wang, L. F., & Li, L. (2019). Impact of knowledge couplings on manufacturing firms’ green innovation: The moderating effect of slack resources. Nankai Business Review, 22(3), 54–65.

    Google Scholar 

  • Zack, M. H. (1999). Developing a knowledge strategy. California Management Review, 41(3), 125–145.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Zhang, G., & Xu, Q. (2010). Knowledge agglomeration and regional innovation network. Science Press.

    Google Scholar 

  • Zhang, H. B., & Zhang, S. P. (2013). An empirical research on influence factors of knowledge transfer effectiveness in technology alliance. Studies in Science of Science, 31(7), 1041–1049.

    Google Scholar 

  • Zhang, J., Baden-Fulle, R. C., & Mangematin, V. (2007). Technological knowledge base, R&D organization structure and alliance formation: Evidence from the biopharmaceutical industry. Research Policy, 36(4), 515–528.

    Article  Google Scholar 

  • Zhao, C., & Wang, J. (2014). Research on SME growth system under uncertainty. Journal of Industrial Engineering and Engineering Management, 28(2), 108–113+107.

    Google Scholar 

  • Zhou, K. Z., & Li, C. B. (2012). How knowledge affects radical innovation: Knowledge base, market knowledge acquisition, and internal knowledge sharing. Strategic Management Journal, 33(9), 1090–1102.

    Article  Google Scholar 

  • Zhou, K. G., Lu, Y. Z., & Yang, H. S. (2017). Financing constraints, innovation ability and firm collaborative innovation. Economic Research Journal, 52(7), 94–108.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Management, Shandong University, Jinan, China

    Zhen Che & Changqi Wu

  2. Guanghua School of Management, Peking University, Beijing, China

    Xiaoxi Liu

Authors
  1. Zhen Che
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Changqi Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xiaoxi Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Changqi Wu.

Ethics declarations

Conflict of interest

The authors declare no conflict of interest.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Che, Z., Wu, C. & Liu, X. A four-factor model of knowledge agglomeration. Asia Pac J Manag (2024). https://doi.org/10.1007/s10490-024-09955-3

Download citation

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10490-024-09955-3

Keywords

Search

Navigation