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| Key Influencing Factors of Digital Entrepreneurial Business Model Innovation in Big Data-Driven Context：An Exploratory Research Using Discourse Analysis Approach |
| Li Wenbo |
| (College of Economics and Management, Zhejiang Normal University, Jinhua 321004, China) |
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Abstract In the era of big data, humanity has entered the period of digital technology revolution, and digital economy has become the main theme of current economic development across the world. As a product of the era of digital economy, the digital entrepreneurship driven by big data is attracting increasing attention. However, case studies show that the practice of digital entrepreneurship business model innovation in big data-driven context is presenting a very different picture. Therefore, it is an important topic to deeply investigate the key influencing factors behind the innovation of digital entrepreneurship business models in big data-driven context. At the theoretical level, existing studies have answered the question of digital entrepreneurship business model innovation in two dimensions, which are the horizontal expansion along the value chain centered on big data and the vertical expansion of business model innovation. However, compared with the practice of big data-driven digital entrepreneurship business model innovation, the existing results are weak in the study of key influencing factors, mainly because the existing studies focus on examining the direct influence of each independent explanatory variable on digital entrepreneurship business model innovation, and less precisely portray the logical association of each influencing factor. In this context, based on the efficiency of discourse analysis techniques in studying exploratory propositions, this paper focuses on the polymorphic practices of digital entrepreneurship business model innovation around the big data-driven context, systematically distills the key factors influencing digital entrepreneurship business model innovation, and aims to improve the understanding of the appropriateness of digital entrepreneurship business model innovation research in the big data-driven context.#br# The discourse analysis methods are uesd to conduct empirical research, and eight digital startups are selected as case study samples based on diverse business model innovations, applications in the field of big data and the amount of data media coverage. Both first-hand and second-hand discourse collection methods are adopted to ensure the reliability and validity of the discourse analysis. The number of valid discourse pool utterances constituted by the two approaches was 860, and NVIVO 8 software was used to assist the initial concept extraction work, and the consistency error was determined by calculating Cohen's Kappa coefficient.#br# This study introduces discourse analysis technology into the field of digital entrepreneurship business model innovation research, and provides an in-depth analysis of the kernel issue of influencing factors in big data-driven context. In the big data-driven context, digital entrepreneurship business model innovation should be promoted from both the external data context and the internal subjectivity behavior of enterprises, and enterprises should systematize their data mining capabilities, promote them from hardware and software, technology and management, pay attention to the integration of online and offline channels to promote business model innovation, and focus on differentiated business models in niche markets. On the one hand, the research results enlighten enterprises on data mining capability from the technical perspective, such as data integration capability and data system configuration;on the other hand, they inspire the adaptive behavior of enterprises in business model innovation from the perspective of management, such as knowledge penetration and embedded learning.#br# This paper addresses the key issue of digital entrepreneurship business model innovation by systematizing the influencing factors into two story lines，including "big data-driven scenario → data mining capability → digital entrepreneurship business model innovation" and "network shared resources → enterprise adaptation behavior → digital entrepreneurship business model innovation". The research results not only further deepen the path explanation of digital entrepreneurship business model innovation, but also make up for the lack of research on business model innovation in big data-driven context from both technical and managerial perspectives, and enrich the strength of big data-driven explanation of business model innovation. In the part of discourse model refinement, the adjacency matrix and the reachability matrix are applied as the analysis tools of discourse component association, which is an extension of the methodological level. The discourse analysis tools adopted in this paper provide a new analytical perspective for the study of combining big data and business model innovation, and it also provides a new analytical path for the study of enterprise business model innovation under the big data-driven context.#br#
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Received: 17 August 2021
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| [1] MAYER-SCHONBERGER V,CUKIER K.Big data: a revolution that will transform how we live, work, and think[M].London:John Murray, 2013:15-20.[2] NIEMAND T,RIGTERING J,KALLMUENZER A,et al. Digitalization in the financial industry: a contingency approach of entrepreneurial orientation and strategic vision on digitalization[J]. European Management Journal, 2020, 39(3):317-326.[3] TIJS V, VEENSTRA A V. Governance of big data collaborations: how to balance regulatory compliance and disruptive innovation [J]. Technological Forecasting & Social Change, 2018, 129(4):330-338.[4] GOYAL M, HANCOCK M Q, HATAMI H. Selling into micro markets[J]. Harvard Business Review, 2012, 90(7):78-86.[5] MORABITO V. Big data governance[M].Berlin:Springer International Publishing, 2015:83-104.[6] CHEBBI I, BOULILA W, FARAH I R. Big data: concepts, challenges and applications[M].Berlin:Springer International Publishing, 2015:638-647.[7] BILLINGS K. Oracle takes you through the four phrases of achieving big data insight [R]. Intel IT Center, 2012.[8] ARENA R. Schumpeter and schumpeterian on competition: some policy implications[J]. Journal of Evolutionary Economics, 2017, 27(1):1-26.[9] MANYIKA J, CHUI M, BROWN B, et al. Big data: the next frontier for innovation, competition, and productivity [R]. McKinsey Global Institute, 2011: 20-25.[10] RUGGIERI S, PEDRESCHI D, TURINI F. Data mining for discrimination discovery[J]. Acm Transactions on Knowledge Discovery from Data, 2010, 4(2):1-40.[11] GOODARZIAN F, KUMAR V, ABRAHAM A . Hybrid meta-heuristic algorithms for a supply chain network considering different carbon emission regulations using big data characteristics[J]. Soft Computing, 2021, 25(11):7527-7557.[12] MAAS J B, FENEMA P C V, SOETERS J. ERP as an organizational innovation: key users and cross-boundary knowledge management[J]. Journal of Knowledge Management, 2016, 20(3):557-577.[13] ERNKVIST M. The double knot of technology and business-model innovation in the era of ferment of digital exchanges: the case of OM, a pioneer in electronic options exchanges[J].Technological Forecasting & Social Change, 2015, 99:285-299.[14] MARSHALL A, MUECK S, SHOCKLEY R. How leading organizations use big data and analytics to innovate[J]. Strategy & Leadership, 2015, 43(5):32-39.[15] OLUGBARA C T, IMENDA S N, OLUGBARA O O, et al. Moderating effect of innovation consciousness and quality consciousness on intention-behavior relationship in E-learning integration[J]. Education and information technologies, 2020, 25(1):329-350.[16] SALMELIN B. The horizon 2020 framework and open innovation ecosystems[J]. Journal of Innovation Management, 2013, 1(2):4-9.[17] VELU C. Evolutionary or revolutionary business model innovation through competition? the role of dominance in network markets[J]. Industrial Marketing Management, 2016, 53:124-135.[18] HEIKKILA M,HEIKKILA J.Collaborative business model innovation process for networked services[C]. International Conference on Electronic Commerce. Springer Berlin Heidelberg, 2013:133-147.[19] RICHEY R G, ADAMS F G, DALELA V. Technology and flexibility : enablers of collaboration and time-based logistics quality[J].Journal of Business Logistics, 2012, 33(1): 34-49.[20] CHESBROUGH H W. The era of open innovation[J]. Sloan Management Review, 2003, 44(3):35-41. [21] TORKKELI L, KUIVALAINEN O, SAARENKETO S, et al. Institutional environment and network competence in successful SME internationalization[J]. International Marketing Review, 2019, 36(1):31-55.[22] CAI S, ZHANG J. Exploration of credit risk of P2P platform based on data mining technology[J]. Journal of Computational and Applied Mathematics, 2020, 372(1):112718.[23] JORGENSEN M W, PHILLIPS L J. Discourse analysis: as theory and method [M].London:Sage, 2013: 30-35.[24] MAHMOODI K, MOHAMMADPUR A, REZAEI M. A discourse analysis of population policies in the context of politics in Iran[J]. Quality & Quantity, 2015, 49(5):1883-1895.[25] 曾锵. 大数据驱动的商业模式创新研究[J]. 科学学研究, 2019, 37(6):1142-1152.[26] SORESCU A. Data-driven business model innovation [J]. Journal of Product Innovation Management, 2017, 34(5):691-696.[27] ALVESSON M，KARREMAN D. Varieties of discourse: on the study of organizations through discourse analysis [J]. Human Relations, 2000, 53(9): 1125-1149.[28] BROWN G, YULE G. Discourse analysis [J]. Encyclopedia of Clinical Neuropsychology, 2012, 11(3):36-45. |
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