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Convergence and interdisciplinarity in innovation management: a review, critique, and future directions

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  • Fredrik Hacklin
  • Martin W. Wallin

Abstract

Knowledge integration in the interstices between different disciplinary fields is becoming a critical challenge to innovation management. As disciplines converge into new hybrid fields, such as information and communication technology or nano-biotechnology, it ultimately creates winners and losers, be they new firms that displace incumbents or individual scientists better positioned to reap rewards from new targeted grants. While received literature recognizes the importance of interdisciplinarity, little is known about its theoretical and conceptual antecedents. To meet this challenge, we first review and critique the literature on interdisciplinarity from a knowledge-based perspective, and, second, identify challenges for innovation management and formulate implications for further research. In particular, we outline how individual and team-level heterogeneity should be addressed. By adopting such a micro-level perspective, innovation management can embrace heterogeneity and effectively unlock the true value of interdisciplinary knowledge.

Suggested Citation

  • Fredrik Hacklin & Martin W. Wallin, 2013. "Convergence and interdisciplinarity in innovation management: a review, critique, and future directions," The Service Industries Journal, Taylor & Francis Journals, vol. 33(7-8), pages 774-788, May.
  • Handle: RePEc:taf:servic:v:33:y:2013:i:7-8:p:774-788
    DOI: 10.1080/02642069.2013.740471
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    Cited by:

    1. Lee, Hyunmin, 2023. "Converging technology to improve firm innovation competencies and business performance: Evidence from smart manufacturing technologies," Technovation, Elsevier, vol. 123(C).
    2. Seongkyoon Jeong & Jong-Chan Kim & Jae Young Choi, 2015. "Technology convergence: What developmental stage are we in?," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(3), pages 841-871, September.
    3. Zhang, Gupeng & Wang, Xiao & Duan, Hongbo & Zheng, Leven J., 2021. "How do new entrants’ pre-entry technological backgrounds impact their cross-industry innovation performances? A retrospective study of the mobile phone vendors," Technovation, Elsevier, vol. 100(C).
    4. Hilda Bø Lyng & Eric Christian Brun, 2018. "Knowledge Transition: A Conceptual Model of Knowledge Transfer for Cross-Industry Innovation," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 15(05), pages 1-23, October.
    5. Joon Hyung Cho & Jungpyo Lee & So Young Sohn, 2021. "Predicting future technological convergence patterns based on machine learning using link prediction," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5413-5429, July.
    6. Geum, Youngjung & Kim, Moon-Soo & Lee, Sungjoo, 2016. "How industrial convergence happens: A taxonomical approach based on empirical evidences," Technological Forecasting and Social Change, Elsevier, vol. 107(C), pages 112-120.
    7. Kim, Namil & Lee, Hyeokseong & Kim, Wonjoon & Lee, Hyunjong & Suh, Jong Hwan, 2015. "Dynamic patterns of industry convergence: Evidence from a large amount of unstructured data," Research Policy, Elsevier, vol. 44(9), pages 1734-1748.
    8. Sick, Nathalie & Bröring, Stefanie, 2022. "Exploring the research landscape of convergence from a TIM perspective: A review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    9. Kim, Hongbum & Shin, Dong-Hee & Lee, Daeho, 2015. "A socio-technical analysis of software policy in Korea: Towards a central role for building ICT ecosystems," Telecommunications Policy, Elsevier, vol. 39(11), pages 944-956.
    10. Yugang He, 2022. "A Study on the Dynamic Relationship between Wealth Gap and Economic Growth in China," European Journal of Marketing and Economics Articles, Revistia Research and Publishing, vol. 5, July -Dec.
    11. Heo, Pil Sun & Lee, Duk Hee, 2019. "Evolution patterns and network structural characteristics of industry convergence," Structural Change and Economic Dynamics, Elsevier, vol. 51(C), pages 405-426.
    12. Sajad Ashouri & Anne-Laure Mention & Kosmas X. Smyrnios, 2021. "Anticipation and analysis of industry convergence using patent-level indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5727-5758, July.
    13. Kim, Tae San & Sohn, So Young, 2020. "Machine-learning-based deep semantic analysis approach for forecasting new technology convergence," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    14. Oviedo-García, M. Ángeles, 2016. "Tourism research quality: Reviewing and assessing interdisciplinarity," Tourism Management, Elsevier, vol. 52(C), pages 586-592.
    15. Hyeokseong Lee & Namil Kim & Kiho Kwak & Wonjoon Kim & Hyungjoon Soh & Kyungbae Park, 2016. "Diffusion Patterns in Convergence among High-Technology Industries: A Co-Occurrence-Based Analysis of Newspaper Article Data," Sustainability, MDPI, vol. 8(10), pages 1-18, October.
    16. Jae Young Choi & Seongkyoon Jeong & Kyunam Kim, 2015. "A Study on Diffusion Pattern of Technology Convergence: Patent Analysis for Korea," Sustainability, MDPI, vol. 7(9), pages 1-24, August.
    17. Kim, Yong Jin & Lee, Duk Hee, 2020. "Technology convergence networks for flexible display application: A comparative analysis of latecomers and leaders," Japan and the World Economy, Elsevier, vol. 55(C).
    18. Hilda Bø Lyng & Eric Christian Brun, 2020. "Innovating with Strangers; Managing Knowledge Barriers Across Distances in Cross-Industry Innovation," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 17(01), pages 1-33, February.

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