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Uncovering the dynamics of market convergence through M&A

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  • Aaldering, Lukas Jan
  • Leker, Jens
  • Song, Chie Hoon

Abstract

Despite the significance of converging markets as a new competitive paradigm to change how organizations function and produce value, little attention has been devoted to investigating the evolutionary path of market convergence and understanding the potential of its market development in the future. In this paper, the extent to which the biotechnology industry shows tendencies to converge with adjacent market segments is explored. By taking both a retrospective and forward-looking perspective, the study intends to shed light on the dynamics of the convergent evolution beyond the mere technological dimension. Based on the real-world examples of M&A transactions, an M&A interaction network was constructed to analyze the dynamics of market convergence and to visualize the causal relationships among market segments by using the DEMATEL approach. Furthermore, a link prediction algorithm was applied to predict future converging patterns. By simultaneously considering the past and imagining the future, the study offers a holistic, intuitive understanding of the interrelationships of the entire network. The findings show that the technology convergence has evolved into market convergence. The proposed framework can provide input for decision makers for effective R&D planning to anticipate developments and to coordinate the related activities.

Suggested Citation

  • Aaldering, Lukas Jan & Leker, Jens & Song, Chie Hoon, 2019. "Uncovering the dynamics of market convergence through M&A," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 95-114.
  • Handle: RePEc:eee:tefoso:v:138:y:2019:i:c:p:95-114
    DOI: 10.1016/j.techfore.2018.08.012
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    as
    1. Karvonen, Matti & Kässi, Tuomo, 2013. "Patent citations as a tool for analysing the early stages of convergence," Technological Forecasting and Social Change, Elsevier, vol. 80(6), pages 1094-1107.
    2. Bruno Cassiman & Massimo G. Colombo (ed.), 2006. "Mergers and Acquisitions," Books, Edward Elgar Publishing, number 4072.
    3. Lee, Mingook & Lee, Sungjoo, 2017. "Identifying new business opportunities from competitor intelligence: An integrated use of patent and trademark databases," Technological Forecasting and Social Change, Elsevier, vol. 119(C), pages 170-183.
    4. Han, Eun Jin & Sohn, So Young, 2016. "Technological convergence in standards for information and communication technologies," Technological Forecasting and Social Change, Elsevier, vol. 106(C), pages 1-10.
    5. Sung-Seok Ko & Namuk Ko & Doyeon Kim & Hyunseok Park & Janghyeok Yoon, 2014. "Analyzing technology impact networks for R&D planning using patents: combined application of network approaches," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 917-936, October.
    6. Tijssen, Robert J. W., 1992. "A quantitative assessment of interdisciplinary structures in science and technology: Co-classification analysis of energy research," Research Policy, Elsevier, vol. 21(1), pages 27-44, February.
    7. Luigi Naldini, 2015. "Gene therapy returns to centre stage," Nature, Nature, vol. 526(7573), pages 351-360, October.
    8. Nemet, Gregory F. & Johnson, Evan, 2012. "Do important inventions benefit from knowledge originating in other technological domains?," Research Policy, Elsevier, vol. 41(1), pages 190-200.
    9. Caviggioli, Federico, 2016. "Technology fusion: Identification and analysis of the drivers of technology convergence using patent data," Technovation, Elsevier, vol. 55, pages 22-32.
    10. Hyojeong Lim & Yongtae Park, 2010. "Identification of technological knowledge intermediaries," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(3), pages 543-561, September.
    11. Yunqing Zhu & Charles Romain & Charlotte K. Williams, 2016. "Sustainable polymers from renewable resources," Nature, Nature, vol. 540(7633), pages 354-362, December.
    12. Leo Sleuwaegen & Giovanni Valentini, 2006. "Trends in Mergers and Acquisitions," Chapters, in: Bruno Cassiman & Massimo G. Colombo (ed.), Mergers and Acquisitions, chapter 2, Edward Elgar Publishing.
    13. 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.
    14. John Hagedoorn & Geert Duysters, 2002. "External Sources of Innovative Capabilities: The Preferences for Strategic Alliances or Mergers and Acquisitions," Journal of Management Studies, Wiley Blackwell, vol. 39(2), pages 167-188, March.
    15. Ying-Chyi Chou & Chia-Han Yang & Ching-Hua Lu & Van Thac Dang & Pei-An Yang, 2017. "Building Criteria for Evaluating Green Project Management: An Integrated Approach of DEMATEL and ANP," Sustainability, MDPI, vol. 9(5), pages 1-17, May.
    16. Marianna Makri & Michael A. Hitt & Peter J. Lane, 2010. "Complementary technologies, knowledge relatedness, and invention outcomes in high technology mergers and acquisitions," Strategic Management Journal, Wiley Blackwell, vol. 31(6), pages 602-628, June.
    17. Cefis, Elena & Marsili, Orietta, 2015. "Crossing the innovation threshold through mergers and acquisitions," Research Policy, Elsevier, vol. 44(3), pages 698-710.
    18. Lü, Linyuan & Zhou, Tao, 2011. "Link prediction in complex networks: A survey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(6), pages 1150-1170.
    19. Iain Cockburn & Rebecca Henderson & Scott Stern, 1999. "Balancing Incentives: The Tension Between Basic and Applied Research," NBER Working Papers 6882, National Bureau of Economic Research, Inc.
    20. We Shim & Oh-jin Kwon & Yeong-ho Moon & Keun-hwan Kim, 2016. "Understanding the Dynamic Convergence Phenomenon from the Perspective of Diversity and Persistence: A Cross-Sector Comparative Analysis between the United States and South Korea," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-29, July.
    21. Sang M. Lee & David L. Olson & Silvana Trimi, 2010. "Strategic innovation in the convergence era," International Journal of Management and Enterprise Development, Inderscience Enterprises Ltd, vol. 9(1), pages 1-12.
    22. Lee, Misuk & Cho, Youngsang, 2015. "Consumer perception of a new convergence product: A theoretical and empirical approach," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 312-321.
    23. Arsia Amir Aslani & Vincent Mangematin, 2010. "The future of drug discovery and development: Shifting emphasis towards personalized medicine," Grenoble Ecole de Management (Post-Print) hal-00749148, HAL.
    24. Lee Fleming, 2001. "Recombinant Uncertainty in Technological Search," Management Science, INFORMS, vol. 47(1), pages 117-132, January.
    25. David Liben‐Nowell & Jon Kleinberg, 2007. "The link‐prediction problem for social networks," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(7), pages 1019-1031, May.
    26. Hsin-Hung Wu & Ya-Ning Tsai, 2012. "An integrated approach of AHP and DEMATEL methods in evaluating the criteria of auto spare parts industry," International Journal of Systems Science, Taylor & Francis Journals, vol. 43(11), pages 2114-2124.
    27. Ebers, Mark & Powell, Walter W., 2007. "Biotechnology: Its origins, organization, and outputs," Research Policy, Elsevier, vol. 36(4), pages 433-437, May.
    28. Wim Vanhaverbeke & Geert Duysters & Niels Noorderhaven, 2002. "External Technology Sourcing Through Alliances or Acquisitions: An Analysis of the Application-Specific Integrated Circuits Industry," Organization Science, INFORMS, vol. 13(6), pages 714-733, December.
    29. 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.
    30. Bornkessel, Sabine & Broering, Stefanie & Omta, S.W.F. (Onno), 2016. "Cross-industry Collaborations in the Convergence Area of Functional Foods," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 19(2), pages 1-24, May.
    31. Desyllas, Panos & Hughes, Alan, 2010. "Do high technology acquirers become more innovative?," Research Policy, Elsevier, vol. 39(8), pages 1105-1121, October.
    32. Jacob, Jojo & Duysters, Geert, 2017. "Alliance network configurations and the co-evolution of firms' technology profiles: An analysis of the biopharmaceutical industry," Technological Forecasting and Social Change, Elsevier, vol. 120(C), pages 90-102.
    33. Song, Chie Hoon & Elvers, David & Leker, Jens, 2017. "Anticipation of converging technology areas — A refined approach for the identification of attractive fields of innovation," Technological Forecasting and Social Change, Elsevier, vol. 116(C), pages 98-115.
    34. Clive-Steven Curran & Jens Leker, 2009. "Employing Stn Anavist To Forecast Converging Industries," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 13(04), pages 637-664.
    35. Bum Soo Chon & Junho Choi & George Barnett & James Danowski & Sung-Hee Joo, 2003. "A Structural Analysis of Media Convergence: Cross-Industry Mergers and Acquisitions in the Information Industries," Journal of Media Economics, Taylor & Francis Journals, vol. 16(3), pages 141-157.
    36. Hyunseok Park & Janghyeok Yoon, 2014. "Assessing coreness and intermediarity of technology sectors using patent co-classification analysis: the case of Korean national R&D," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 853-890, February.
    37. Arsia Amir Aslani & Vincent Mangematin, 2010. "The future of drug discovery and development: Shifting emphasis towards personalized medicine," Post-Print hal-00749148, HAL.
    38. Wang, Yichuan & Kung, LeeAnn & Byrd, Terry Anthony, 2018. "Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations," Technological Forecasting and Social Change, Elsevier, vol. 126(C), pages 3-13.
    39. Bruno Cassiman & Reinhilde Veugelers, 2006. "In Search of Complementarity in Innovation Strategy: Internal R& D and External Knowledge Acquisition," Management Science, INFORMS, vol. 52(1), pages 68-82, January.
    40. Lee, Won Sang & Han, Eun Jin & Sohn, So Young, 2015. "Predicting the pattern of technology convergence using big-data technology on large-scale triadic patents," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 317-329.
    41. Stuart, Toby E. & Ozdemir, Salih Zeki & Ding, Waverly W., 2007. "Vertical alliance networks: The case of university-biotechnology-pharmaceutical alliance chains," Research Policy, Elsevier, vol. 36(4), pages 477-498, May.
    42. Wonchang Hur, 2017. "The patterns of knowledge spillovers across technology sectors evidenced in patent citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 595-619, May.
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    Cited by:

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    3. Lee, Hyunmin, 2023. "Converging technology to improve firm innovation competencies and business performance: Evidence from smart manufacturing technologies," Technovation, Elsevier, vol. 123(C).
    4. Jinho Choi & Nina Shin & Hee Soo Lee, 2020. "Exploring the Dynamics between M&A Activities and Industry-Level Performance," Sustainability, MDPI, vol. 12(11), pages 1-24, May.
    5. 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).
    6. Jinho Choi & Nina Shin & Yong Sik Chang, 2021. "Strategic Investment Decisions for Emerging Technology Fields in the Health Care Sector Based on M&A Analysis," Sustainability, MDPI, vol. 13(7), pages 1-20, March.
    7. Paolo Calvosa, 2023. "The Life Cycle of Converging Industries: The Evolution of the Tablet Sector and Its Impact on Competitive Dynamics," International Journal of Business and Management, Canadian Center of Science and Education, vol. 16(11), pages 1-76, February.
    8. Seo, Wonchul & Afifuddin, Mokh, 2024. "Developing a supervised learning model for anticipating potential technology convergence between technology topics," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    9. Ioannis Anagnostopoulos & Anas Rizeq, 2021. "Conventional and neural network target‐matching methods dynamics: The information technology mergers and acquisitions market in the USA," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 28(2), pages 97-118, April.
    10. Chie Hoon Song, 2021. "Exploring and Predicting the Knowledge Development in the Field of Energy Storage: Evidence from the Emerging Startup Landscape," Energies, MDPI, vol. 14(18), pages 1-20, September.
    11. Aaldering, Lukas Jan & Song, Chie Hoon, 2021. "Of leaders and laggards - Towards digitalization of the process industries," Technovation, Elsevier, vol. 105(C).
    12. Shao, Bohua & Asatani, Kimitaka & Sasaki, Hajime & Sakata, Ichiro, 2021. "Categorization of mergers and acquisitions using transaction network features," Research in International Business and Finance, Elsevier, vol. 57(C).

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