Digital Transformation of the Automotive Industry: An Integrating Framework to Analyse Technological Novelty and Breadth

References

• Anand, B. 2016. The Content Trap: A Strategist’s Guide to Digital Change. New York: United States Random House Publishers.
   Google Scholar
• Antons, D., E. Grünwald, P. Cichy, and T. Oliver Salge. 2020. “The Application of Text Mining Methods in Innovation Research: Current State, Evolution Patterns, and Development Priorities.” R&D Management 50 (3): 329–351. doi:10.1111/radm.12408.
   Web of Science ®Google Scholar
• Arthur, W. B. 2009. The Nature of Technology: What It is and How It Evolves. London, England: Penguin Books Limited.
   Google Scholar
• Bailey, D. E., S. Faraj, P. J. Hinds, P. M. Leonardi, and G. von Krogh. 2022. “We are All Theorists of Technology Now: A Relational Perspective on Emerging Technology and Organizing.” Organization Science 33 (1): 1–18. doi:10.1287/orsc.2021.1562.
   Web of Science ®Google Scholar
• Benner, M. J., and M. Tripsas. 2012. “The Influence of Prior Industry Affiliation on Framing in Nascent Industries: The Evolution of Digital Cameras.” Strategic Management Journal 33 (3): 277–302. doi:10.1002/smj.950.
   Web of Science ®Google Scholar
• Bergek, A., C. Berggren, T. Magnusson, and M. Hobday. 2013. “Technological Discontinuities and the Challenge for Incumbent Firms: Destruction, Disruption or Creative Accumulation?” Research Policy 42 (6): 1210–1224.
   Web of Science ®Google Scholar
• Blei, D. M., A. Y. Ng, and M. I. Jordan. 2003. “Latent Dirichlet Allocation.” Journal of Machine Learning Research : JMLR 3: 993–1022.
   Web of Science ®Google Scholar
• Bodrožić, Z., and P. S. Adler. 2022. “Alternative Futures for the Digital Transformation: A Macro-Level Schumpeterian Perspective.” Organization Science 33 (1): 105–125. doi:10.1287/orsc.2021.1558.
   Web of Science ®Google Scholar
• Brynjolfsson, E., and A. McAfee. 2014. The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. New York: W. W. Norton.
   Google Scholar
• Carlsson, B., and R. Stankiewics. 1991. “On the Nature, Function and Composition of Technological Systems.” Journal of Evolutionary Economics 1 (2): 93–118. doi:10.1007/BF01224915.
   Google Scholar
• Christensen, C. M., R. McDonald, E. J. Altman, and J. E. Palmer. 2018. “Disruptive Innovation: An Intellectual History and Directions for Future Research.” Journal of Management Studies 55 (7): 1043–1078. doi:10.1111/joms.12349.
   Web of Science ®Google Scholar
• Cirillo, V., L. Fanti, A. Mina, and A. Ricci. 2022. “New Digital Technologies and Firm Performance in the Italian Economy.” Industry and Innovation 1–30. doi:10.1080/13662716.2022.2055999.
   Web of Science ®Google Scholar
• Coccia, M. 2015. “General Sources of General Purpose Technologies in Complex Societies: Theory of Global Leadership-Driven Innovation, Warfare and Human Development.” Technology in Society 42: 199–226. doi:10.1016/j.techsoc.2015.05.008.
   Web of Science ®Google Scholar
• Coccia, M. 2017. “Sources of Disruptive Technologies for Industrial Change.” L’industria 38 (1): 97–120.
   Google Scholar
• Coccia, M. 2020. “Deep Learning Technology for Improving Cancer Care in Society: New Directions in Cancer Imaging Driven by Artificial Intelligence.” Technology in Society 60: 101198. doi:10.1016/j.techsoc.2019.101198.
   Web of Science ®Google Scholar
• Coccia, M., and J. Watts. 2020. “A Theory of the Evolution of Technology: Technological Parasitism and the Implications for Innovation Magement.” Journal of Engineering and Technology Management 55: 101552. doi:10.1016/j.jengtecman.2019.11.003.
   Web of Science ®Google Scholar
• Dąbrowska, J., A. Almpanopoulou, A. Brem, H. Chesbrough, V. Cucino, A. Di Minin, F. Giones, et al. 2022. ”Digital Transformation, for Better or Worse: A Critical Multi-Level Research Agenda.” R&D Management 52 (5): 930–954. doi:10.1111/radm.12531.
   Web of Science ®Google Scholar
• Daniele, R., D. Hicks, and B. R. Martin. 2015. “What is an Emerging Technology?” Research Policy 44 (10): 1827–1843.
   Web of Science ®Google Scholar
• Dosi, G. 1984. Technical Change and Industrial Transformation: The Theory and an Application to the Semiconductor Industry. London: Palgrave Macmillan UK.
   Google Scholar
• Dougherty, D., and D. D. Danielle. 2012. “Digital Science and Knowledge Boundaries in Complex Innovation.” Organization Science 23 (5): 1467–1484. doi:10.1287/orsc.1110.0700.
   Web of Science ®Google Scholar
• Eggers, J. P., and K. Francis Park. 2018. “Incumbent Adaptation to Technological Change: The Past, Present, and Future of Research on Heterogeneous Incumbent Response.” The Academy of Management Annals 12 (1): 357–389. doi:10.5465/annals.2016.0051.
   Web of Science ®Google Scholar
• Eklund, J., and R. Kapoor. 2019. “Pursuing the New While Sustaining the Current: Incumbent Strategies and Firm Value During the Nascent Period of Industry Change.” Organization Science 30 (2): 383–404. doi:10.1287/orsc.2018.1229.
   Web of Science ®Google Scholar
• Gawer, A. 2021. “Digital Platforms’ Boundaries: The Interplay of Firm Scope, Platform Sides, and Digital Interfaces.” Long range planning 54 (5): 102045. doi:10.1016/j.lrp.2020.102045.
   Web of Science ®Google Scholar
• George, G., E. C. Osinga, D. Lavie, and B. A. Scott. 2016. “Big Data and Data Science Methods for Management Research.” Academy of Management Journal 59 (5): 1493–1507. doi:10.5465/amj.2016.4005.
   Web of Science ®Google Scholar
• Grillitsch, M., T. Hansen, L. Coenen, J. Miörner, and J. Moodysson. 2019. “Innovation Policy for System-Wide Transformation: The Case of Strategic Innovation Programmes (SIPs) in Sweden.” Research Policy 48 (4): 1048–1061. doi:10.1016/j.respol.2018.10.004.
   Web of Science ®Google Scholar
• Grimmer, J., M. E. Roberts, and B. M. Stewart. 2022. Text as Data: A New Framework for Machine Learning and the Social Sciences. New Jersey: Princeton University Press.
   Google Scholar
• Hanelt, A., R. Bohnsack, D. Marz, and C. Antunes Marante. 2021. “A Systematic Review of the Literature on Digital Transformation: Insights and Implications for Strategy and Organizational Change.” Journal of Management Studies 58 (5): 1159–1197. doi:10.1111/joms.12639.
   Web of Science ®Google Scholar
• Hannigan, T. R., R. F. J. Haans, K. Vakili, H. Tchalian, V. L. Glaser, M. Shaoqing Wang, S. Kaplan, and P. Devereaux Jennings. 2019. “Topic Modeling in Management Research: Rendering New Theory from Textual Data.” The Academy of Management Annals 13 (2): 586–632. doi:10.5465/annals.2017.0099.
   Web of Science ®Google Scholar
• Iansiti, M., and K. R. Lakhani. 2020. Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World. Boston, MA: Harvard Business Review Press.
   Google Scholar
• Kallinikos, J., A. Aaltonen, and A. Marton. 2013. “The Ambivalent Ontology of Digital Artifacts.” MIS Quarterly 37 (2): 357–370. doi:10.25300/MISQ/2013/37.2.02.
   Web of Science ®Google Scholar
• Kapoor, R., and T. Klueter. 2021. “Unbundling and Managing Uncertainty Surrounding Emerging Technologies.” Strategy Science 6 (1): 62–74. doi:10.1287/stsc.2020.0118.
   Web of Science ®Google Scholar
• Kneeland, M., M. Schilling, and S. A. Barak. 2020. “Exploring Uncharted Territory: Knowledge Search Processes in the Origination of Outlier Innovation.” Organization Science 31 (3): 535–557. doi:10.1287/orsc.2019.1328.
   Web of Science ®Google Scholar
• Kwon, Seokbeom, X. Liu, A. L. Porter, and J. Youtie. 2019. “Research Addressing Emerging Technological Ideas Has Greater Scientific Impact.” Research Policy 48 (9): 103834. doi:10.1016/j.respol.2019.103834.
   Web of Science ®Google Scholar
• Lanzolla, Gianvito, A. Lorenz, E. Miron-Spektor, M. Schilling, G. Solinas, Tucci, C. L. 2020. “Digital Transformation: What is New if Anything? Emerging Patterns and Management Research.” Academy of Management Discoveries 6 (3): 341–350.
   Web of Science ®Google Scholar
• Lebovitz, S., H. Lifshitz-Assaf, and N. Levina. 2022. “To Engage or Not to Engage with AI for Critical Judgments: How Professionals Deal with Opacity When Using AI for Medical Diagnosis.” Organization Science 33 (1): 126–148. doi:10.1287/orsc.2021.1549.
   Web of Science ®Google Scholar
• Lee, J., and N. Berente. 2012. “Digital Innovation and the Division of Innovative Labor: Digital Controls in the Automotive Industry.” Organization Science 23 (5): 1428–1447. doi:10.1287/orsc.1110.0707.
   Web of Science ®Google Scholar
• Lopez-Vega, H., and N. Lakemond. 2022. “Tapping into Emerging Markets: EMNEs’ Strategies for Innovation Capability Building.” Global Strategy Journal 12 (2): 394–417. doi:10.1002/gsj.1429.
   Web of Science ®Google Scholar
• Lopez-Vega, H., F. Tell, and W. Vanhaverbeke. 2016. “Where and How to Search? Search Paths in Open Innovation.” Research Policy 45 (1): 125–136.
   Web of Science ®Google Scholar
• Malerba, F. 1992. “Learning by Firms and Incremental Technical Change.” The Economic Journal 102 (413): 845–859. doi:10.2307/2234581.
   Web of Science ®Google Scholar
• Martynov, A. 2020. “Technological Footprint Similarity and Firm Performance.” Strategic Organization:1476127019898191.
   Google Scholar
• McAfee, A., and E. Brynjolfsson. 2017. Machine, Platform, Crowd: Harnessing Our Digital Future. W. W. Norton.
   Google Scholar
• McKenny, A. F., H. Aguinis, J. C. Short, and A. H. Anglin. 2018. “What Doesn’t Get Measured Does Exist: Improving the Accuracy of Computer-Aided Text Analysis.” Journal of Management 44 (7): 2909–2933. doi:10.1177/0149206316657594.
   Web of Science ®Google Scholar
• Menz, M., S. Kunisch, J. Birkinshaw, D. J. Collis, N. J. Foss, R. E. Hoskisson, and J. E. Prescott. 2021. “Corporate Strategy and the Theory of the Firm in the Digital Age.” Journal of Management Studies 58 (7): 1695–1720. doi:10.1111/joms.12760.
   Web of Science ®Google Scholar
• Nambisan, S., K. Lyytinen, A. Majchrzak, and M. Song. 2017. “Digital Innovation Management: Reinventing Innovation Management Research in a Digital World.” MIS Quarterly 41 (1): 223–238. doi:10.25300/MISQ/2017/41:1.03.
   Web of Science ®Google Scholar
• Nambisan, S., M. Wright, and M. Feldman. 2019. “The Digital Transformation of Innovation and Entrepreneurship: Progress, Challenges and Key Themes.” Research Policy 48 (8): 103773. doi:10.1016/j.respol.2019.03.018.
   Web of Science ®Google Scholar
• Raisch, S., and S. Krakowski. 2021. “Artificial Intelligence and Management: The Automation–Augmentation Paradox.” Academy of Management Review 46 (1): 192–210. doi:10.5465/amr.2018.0072.
   Web of Science ®Google Scholar
• Röder, M., A. Both, and A. Hinneburg. 2015. “Exploring the Space of Topic Coherence Measures.” In Proceedings of the Eighth ACM International Conference on Web Search and Data Mining, 399–408. Shanghai, China: Association for Computing Machinery.
   Google Scholar
• Salganik, M. J. 2018. Bit by Bit: Social Research in the Digital Age. New Jersey: Princeton University Press.
   Google Scholar
• Sjöö, K., J. Taalbi, A. Kander, and J. Ljungberg. 2014. “SWINNO: A Database of Swedish Innovations, 1970-2007.” In edited by no. 133 Lund Papers in Economic History. General Issues. Department of Economic History, Lund University.
   Google Scholar
• Stevens, K., P. Kegelmeyer, D. Andrzejewski, and D. Buttler. 2012. Exploring Topic Coherence Over Many Models and Many Topics. Paper presented at the Proceedings of the 2012 joint conference on empirical methods in natural language processing and computational natural language learning. Jeju Island, Korea. Association for Computational Linguistics.
   Google Scholar
• Svahn, F., L. Mathiassen, and R. Lindgren. 2017. “Embracing Digital Innovation in Incumbent Firms: How Volvo Cars Managed Competing Concerns.” MIS Quarterly 41 (1): 239–254. doi:10.25300/MISQ/2017/41.1.12.
   Web of Science ®Google Scholar
• Teece, D. J. 2018. “Profiting from Innovation in the Digital Economy: Enabling Technologies, Standards, and Licensing Models in the Wireless World.” Research Policy 47 (8): 1367–1387. doi:10.1016/j.respol.2017.01.015.
   Web of Science ®Google Scholar
• Thomas, L. D. W., and R. Tee. 2022. “Generativity: A Systematic Review and Conceptual Framework.” International Journal of Management Reviews 24 (2): 255–278. doi:10.1111/ijmr.12277.
   Web of Science ®Google Scholar
• Utterback, J. M., C. Pistorius, and E. Yilmaz. 2018. “The Dynamics of Competition and of the Diffusion of Innovations.“ MIT Sloan School Working Paper 5519: 18. http://hdl.handle.net/1721.1/117544
   Google Scholar
• Vial, G. 2019. “Understanding Digital Transformation: A Review and a Research Agenda.” The Journal of Strategic Information Systems 28 (2): 118–144. doi:10.1016/j.jsis.2019.01.003.
   Web of Science ®Google Scholar
• von Krogh, G. 2018. “Artificial Intelligence in Organizations: New Opportunities for Phenomenon-Based Theorizing.” Academy of Management Discoveries 4 (4): 404–409. doi:10.5465/amd.2018.0084.
   Web of Science ®Google Scholar
• Warner, K. S. R., and M. Wäger. 2019. “Building Dynamic Capabilities for Digital Transformation: An Ongoing Process of Strategic Renewal.” Long range planning 52 (3): 326–349. doi:10.1016/j.lrp.2018.12.001.
   Web of Science ®Google Scholar
• Yoo, Y. J., J. B. Richard, L. Kalle, and M. Ann. 2012. “Organizing for Innovation in the Digitized World.” Organization Science 23 (5): 1398–1408. doi:10.1287/orsc.1120.0771.
   Web of Science ®Google Scholar