IEEE Transactions on
Special Issue: Strategies to reach convergence: A multiple perspectives assessment
Dr. Francesco, SKEMA Business School – Université Côte d’Azur, GREDEG, France email@example.com
Dr. Sungjoo Lee, Ajou University, firstname.lastname@example.org
Dr. Nathalie Sick, University of Technology Sydney, Nathalie.Sick@uts.edu.au
Prof. Stefanie Bröring, Universität Bonn, email@example.com
Dr. Luca Mora, Edinburgh Napier University, firstname.lastname@example.org
The etymology of the verb converge has its roots in the Late Latin (c.a. 1690s) meaning ‘to incline together’ (from com– ‘together’ + vergere ‘to bend’). It describes either multiple discernable items moving towards union or the merging of distinct technologies, devices or industries into a unified whole (Curran et al. 2010). Convergence is already taking place in a number of industries, such as biopharma, nutrition products, health care, energy, media and communications, smart cities and telecommunications equipment industry (Hacklin et al., 2013; Wirtz, 2001; Hsu and Prescott, 2017; Mora et al., 2018; Paroutis et al., 2014). This evolutionary process is opening up new business and growth opportunities and it also: (1) changes the way in which customers perceive new products and technology functionalities (Lee et al., 2013); (2) forces companies to rethink their business models (Wirtz et al., 2016) and supply chain strategies (Revilla and Sáenz, 2014; Nazli Wasti and Liker 1999); and (3) paves the way to leverage upon intangible characteristics, like new meanings (Verganti, 2008), reshaping the concept of radicalness in specific industries. In addition, the speed to which convergence occurs may have strategic influence on how specific technological sectors redesign the competitive landscape. The blurring of the boundaries between industries has become a pervasive and growing phenomenon (Bröring et al., 2006), that research is not paying sufficient attention on. Notwithstanding its relevance, academic literature providing insights into convergence is rather scarce and not able to advice firms on how to manage the challenges it generates (e.g., Bröring et al. 2006; Curran et al. 2010; Jeong and Lee 2015). Overall, four types of convergence may be identified: scientific, technological, market, and industrial (Curran et al. 2010).
Scientific convergence entails distinct scientific disciplines that are beginning to cite each other and collaborate (Curran et al. 2010). Coccia and Wang (2016) argue that, over long time periods, institutional research collaboration plays an important role in shaping the scientific landscape and its intersections, and that the latter can pave the way to breakthroughs. Coccia and Bozeman (2016) expands upon that by building an allometric model through which they unveil patterns of collaboration within and between disciplines. An additional contribution to the debate on scientific convergence is also provided by the many studies investigating interdisciplinarity in science through bibliometrics (see for example Small 2010, Chi and Young 2013, and Leydesdorff and Rafols 2009)
Technology convergence occurs when the distance between applied science and technology development decreases (Kim and Lee, 2017; Curran et al. 2010; Gopalakrishnan et al. 2003). To provide some examples of the studies carried out in this domain: (1) Han and Sohn (2016) focus on the determinants of the convergence in standards related to information and communication technologies (ICTs); (2) Jeong and Lee (2015) provide an overview of the drivers of technological convergence using data from government-supported R&D projects in Korea; (3) Karvonen and Kässi (2013) generate novel patent analysis methods to find ways for anticipating the early stages of technological convergence; and (4) Borés et al. (2003) focus on the economic and strategic motivations inspiring firms to catch up the technological convergence in the ICT sector.
Market convergence materializes as soon as new product-market combinations emerge (Curran et al. 2010; Linton 2002). Schmidt et al. (2016) find a link between the exploitation of customer-specific synergies and the endogenous market convergence, while Griffith (2011) develops a multi-level institutional approach to shed light on market segments convergence effects. In addition, Gill and Lei (2009) assess market convergence in the electronics sector by looking at the role of new functionalities added to products.
Finally, industrial convergence is the fusion of firms or industry segments (Curran et al. 2010; Bröring et al. 2006; Choi and Valikangas, 2001), resulting from a complex series of events unfolding over time and starting with convergence occurring in science, technology, and then market. Such a complexity, for instance, can entail either knowledge recombination dynamics in closely related fields (Gruber et al. 2013; Appio et al., 2017a), or searching mechanisms (Hohberger, 2014; Appio et al., 2017b) whereby agents try to scout new intersections and generate new fields of investigation, establishing strategic collaborations with partners having distant technological expertise (Simon and Sick, 2016), or deploying acquisition strategies through alliances (Hsu and Prescott, 2017). Specifically, Geum and co-authors (2015) provide empirical evidence of successful Korean cases of industrial convergence by outlining a first taxonomy; Preschitschek and co-authors (2013) assess the convergence of industries by measuring the semantic similarity of the patents within specific technological fields finding inconsistencies in using only IPC co-classification analyses; Christensen (2011) looks at the trajectories of complementary convergence claiming the importance of mergers and acquisitions as a central means for realizing convergence; Katz (1996) discusses about the formation of new industry segment out of convergence in telecommunications and computer industries.
Despite their overall value in addressing some knowledge gaps limiting the current understand of convergence, existing contributions still provide scant evidence of the potential strategic interplay between the four types of convergence. Time has come to push forward the horizon of possible methods, techniques, and frameworks assessing the strategies to reach convergence from the four perspectives mentioned above.
Authors may consider – but not be limited to – the following:
- Characteristics of strategies leading to convergence
- micro-foundation dynamics and processes
- the importance of the temporal dimension
- life-cycle perspective
- Insights on the determinants of convergence
- specialization and diversification strategies
- internal and external searching strategies
- strategic collaboration practices
- knowledge recombination
- network practices
- complexity theory
- Insights on the outcomes of convergence
- emergence of general purpose technologies
- emergence of radical innovations
- generation of new markets and industries
- market disruptions
- Generation of new – or validation of existing – typologies and taxonomies
- different levels or domains
- new criteria or perspectives
- technology-humanity convergence
- Indicators for assessing convergence
- social network
- New approaches to monitor convergence
Notes for Prospective Authors:
Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere.
Conference papers may only be submitted if the paper has been completely re-written and if appropriate written permissions have been obtained from any copyright holders of the original paper.
Manuscripts should be submitted through the publisher’s online system. Submissions will be reviewed according to the journal’s rigorous standards and procedures through double-blind peer review by at least two qualified reviewers.
Please prepare the manuscript according to IEEE-TEM’s guidelines (http://ieee-tmc.org/tem-guidelines) and submit to the journal’s Manuscript Central site (https://mc.manuscriptcentral.com/tem-ieee). Please clearly state in the cover letter that the submission is for this special issue.
- Interested authors send abstracts by January 31st, 2020
- Decisions on acceptance of abstracts by March 30th, 2020
- Papers submitted by August 31st, 2020
Appio, F.P., Martini, A., and Fantoni, G. 2017a. The light and shade of knowledge recombination: insights from a general-purpose technology. Technological Forecasting and Social Change, 125, 154-165.
Appio, F.P., Martini, A., Messeni Petruzzelli, A., Neirotti, P., and B. Van Looy. 2017b. Search mechanisms and innovation: an analysis across multiple perspectives. Technological Forecasting and Social Change, 120, 103-116.
Borés, C., Saurina, C., and Torres, R. 2003. Technological convergence: a strategic perspective. Technovation 23 (1), 1-13.
Bröring, S., Cloutier, L.M., and Leker, J. 2006. The front end of innovation in an era of industry convergence: evidence from nutraceuticals and functional foods. R&D Management 36 (5), 487-498.
Chi, R., and Young, J. 2013. The Interdisciplinary Structure of Research on Intercultural Relations: A Co-citation Network Analysis Study. Scientometrics, 96(1), 147-171.
Choi, D., and Valikangas, L. 2001. Patterns of strategy innovation. European Management Journal 19 (4), 424-429.
Christensen, J.F. 2011. Industrial evolution through complementary convergence: the case of IT security. Industrial and Corporate Change 20 (1), 57-89.
Coccia, M., and L. Wang. 2016. Evolution and convergence of the patterns of international scientific collaboration. Proceedings of the National Academy of Sciences of the United States of America 113 (8), 2057-2061.
Coccia, M, and Bozeman, B. 2016. Allometric models to measure and analyze the evolution of international research collaboration. Scientometrics, in press.
Curran, C.-S., Bröring, S., and Leker, J. 2010. Anticipating converging industries using publicly available data. Technological Forecasting and Social Change 77 (3), 385-395.
Geum, Y., Kim, M.-S., and Lee, S. 2015. How industrial convergence happens: a taxonomical approach based on empirical evidences. Technological Forecasting and Social Change 107 (1), 112-120.
Gill, T., and Lei, J. 2009. Convergence in the high-technology consumer markets: not all brands gain equally from adding new functionalities to products. Marketing Letters 20 (1), 91-103.
Gopalakrishnan, S., Wischnevsky, J.D., and Damanpour, F. 2003. A multilevel analysis of factors influencing the adoption of internet banking. IEEE Transactions on Engineering Management, 50 (4), 413-426.
Griffith, D.A. 2010. Understanding multi-level institutional convergence effects on international market segments and global marketing strategy. Journal of World Business 45 (1), 59-67.
Gruber, M., Harhoff, D. and K. Hoisl. 2013. Knowledge recombination across technological boundaries: scientists vs engineers. Management Science 59 (4), 837-851.
Hacklin, F., B. Battistini, and G. Krogh. 2013. Strategic choices in converging industries. MIT Sloan Management Review 55 (1), 65-73.
Han, J.H., and S.Y. Sohn. 2016. Technological convergence in standards for information and communication technologies. Technological Forecasting and Social Change 106, 1-10.
Hohberger, J. 2014. Searching for emerging knowledge: The influence of collaborative and geographically proximate search. European Management Review 11 (2), 139-157.
Hsu, S.T., and J.E. Prescott. 2017. The alliance experience transfer effect: the case of industry convergence in the telecommunications equipment industry. British Journal of Management 28 (3), 425-443.
Jeong, S., and S. Lee. 2015. What drives technology convergence? Exploring the influence of technological and resource allocation contexts. Journal of Engineering and Technology Management 36 (April-June), 78-96.
Karvonen, M., and T. Kässi, 2013. Patent citations as a tool for analysing the early stages of convergence. Technological Forecasting and Social Change 80 (6), 1094-1107.
Katz, M.L. 1996. Remarks on the economic implications of convergence. Industrial and Corporate Change 5 (4), 1079-1095.
Kim, M., and Lee, S. 2017. Forecasting and identifying multi-technology convergence based on patent data: the case of IT and BT industries in 2020. Scientometrics, 111 (1), 47-65.
Lee, S., Lee, J.-H. and Garrett, T.C. 2013. A study of the attitude toward convergent products: a focus on the consumer perception functionalities. Journal of Product Innovation Management 30 (1), 123-135.
Leydesdorff, L., and Rafols, I. 2009. A Global Map of Science Based on the ISI Subject Categories. Journal of the American Society for Information Science and Technology, 60(2), 348-362.
Linton, J.D. 2002. Forecasting the market diffusion of disruptive and discontinuous innovation. IEEE Transactions on Engineering Management, 49 (4), 365-374.
Mora, L., Deakin, M., and Reid, A. 2018. Strategic principles for smart city development: a multiple case study analysis of European best practices. Technological Forecasting and Social Change, in Press.
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Preschitschek, N., H. Niemann, J. Leker, and M.G. Moehrle. 2013. Anticipating industry convergence: semantic analyses vs IPC co-classification analyses of patents. Foresight 15 (6), 446-464.
Revilla, E., and Sáenz, M.J. 2014. Supply chain disruption management: Global convergence vs national specificity. Journal of Business Research 67 (6), 1123-1135.
Schmidt, J., R. Makadok R., and T. Keil. 2016. Customer-specific synergies and market convergence. Strategic Management Journal 37 (5), 870-895.
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Small, H. 2010. Maps of science as interdisciplinary discourse: co-citation contexts and the role of analogy. Scientometrics 83 (3), 835-849.
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Guest Editor bios
Francesco Paolo Appio, Ph.D., is Head of the Business Research Group and Associate Professor of Innovation at SKEMA Business School – Université Côte d’Azur, GREDEG, France
He is visiting scholar at MIT Sloan School of Management and K.U. Leuven. He completed his Ph.D. in “Management” at Scuola Superiore Sant’Anna in Pisa. His main research interests deal with the determinants of scientific breakthroughs discoveries and radical technological inventions, as well as the innovation ecosystem dynamics. His work appears in journals such as Long Range Planning, Technological Forecasting and Social Change, Scientometrics, among others. He is currently guest editor of a special issue on Technological Forecasting and Social Change, Industrial Marketing Management, and European Journal of Innovation Management.
Sungjoo Lee received Ph.D. in industrial engineering from Seoul National University, Seoul, Korea, in 2007. She is currently an Associate Professor in industrial engineering at Ajou University, Suwon, Korea. Before joining Ajou University, she worked as a visiting scholar at the Centre for Technology Management, Institute for Manufacturing, University of Cambridge. Her research interests include technology roadmapping, patent engineering, and R&D planning in small and medium-sized enterprises. Her work appears in a number of journals including Research Policy, Scientometrics, Technovation, Technological Forecasting and Social Change, R&D Management, among others. She is currently an advisory editor of Research Policy.
Nathalie Sick is senior lecturer in technology management at the University of Technology Sydney, Australia. She served as assistant professor at the University of Münster, Germany and additionally led the interdisciplinary young research group innovation and technology management in energy storage with the Helmholtz-Institute Muenster. She received her PhD on innovation management from the University of Münster and holds diploma in Business Administration and Industrial Engineering. Her research interests are industry convergence as well as knowledge and technology transfer in interdisciplinary and cross industrial collaborations. Her work appears in journals such as Technological Forecasting and Social Change, Scientometrics and International Journal of Innovation Management, among others.
Stefanie Bröring received her Ph.D. on industry convergence from University of Münster, Germany including a research stay at the Department of Management and Technology, University of Quebec at Montreal, Canada. Since 2013 she is Full Professor for Technology and Innovation Management at the University of Bonn in Germany. Prior to academia she worked in the specialty chemicals industry and gained a wide array of experience working mainly in new business development-related functions. Her research focuses on technology and innovation management in the context of convergence, where she employs multiple methods reaching from patent analyses to elucidate patterns of convergence to consumer studies to understand the perception of novel technologies and resulting borderline products. Her work appears in journals like e.g. R&D Management, Technology Forecasting and Social Change, Creativity and Innovation Management.
Luca Mora is Lecturer in Entrepreneurship and Innovation at Edinburgh Napier University’s Business School. Luca received his PhD in Innovation Management and Product Development from Politecnico di Milano and his main research interests include: ICT-driven urban development; urban and regional innovation; smart city projects and strategies; Research and Innovation Strategies for Smart Specialisation (RIS3); strategic planning for smart cities and RIS3. He has co-authored several international publications on smart city development, which include the book “Smart City Development: From Theory to ICT-driven approach to urban sustainability” that Elsevier will be publishing in 2019. Luca was Principal Investigator in the one-year research project RESta(r)t: Roadmap for European Smart City Strategies and is currently Co-Investigator in the H2020 research project Online S3 (4,000,000€ research grant).
IEEE Transactions on Engineering Management is journal of the Technology and Engineering Management Society of IEEE, published quarterly since 1954. It is dedicated to the publication of peer-reviewed original contributions, by researchers and practitioners, regarding the theory and practice of engineering, technology, and innovation management.
Editor in Chief
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Professor and Director
Technology Management Doctoral Program
Department of Engineering and Technology Management
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