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| Antecedent Configuration of Digital Transformation and Its Performance:Empirical Evidence from Chinese Manufacturing Listed Companies |
| Li Lei1,2,Yang Shuili1,Chen Na1 |
| (1.School of Economics and Management, Xi'an University of Technology, Xi'an 710054, China;2.Business School, Gansu University of Political Science and Law, Lanzhou 730070, China) |
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Abstract With the deepening of a new round of global technological revolution and industrial change, digital technologies represented by artificial intelligence (AI) and big data are booming and have quickly become new drivers for China's economic transformation and growth. However, compared with the robust development of digital industrialization, China's industrial digitalization is relatively lagging behind. Especially at the microeconomic level, many traditional manufacturing enterprises struggle to transform their operations to the new digital business models and have no idea how to realize digital transformation. Moreover, in terms of the digital transformation effect, most enterprises fail to achieve the expected results in practice. Thus it has become the focus of common concern in both theoretical and practical circles of how to improve the digital transformation performance of enterprises. However, existing studies have investigated the net effect of individual factors on digital transformation through regression analysis more often, lacking systematic research from a configuration perspective and failing to distinguish the differences in the influence of digital transformation on enterprise performance driven by various paths. Therefore, on the basis of the technology-organization-environment (TOE) theoretical framework, this study creatively combines fuzzy set qualitative comparative analysis (fsQCA) with the propensity score matching (PSM) method to analyze and test the antecedent configuration and transformation performance of enterprise digital transformation.#br#The research period of this paper is set to be 2018-2020, and the Chinese A-share listed manufacturing enterprises are taken as the initial research samples. As the data on enterprise digital transformation performance is used to be delayed by one period, the research period of fsQCA specifically includes 2018 and 2019. Considering that digitalization includes digital industrialization and industrial digitalization, and the focus of this paper is on the digitalization sample of traditional manufacturing industry, hence the samples of enterprises whose main business involves digital industrialization such as artificial intelligence and computer communication are excluded. In addition, in order to improve the reliability of research results, the samples of ST and PT enterprises, abnormal financial data and missing data are removed in turn. By the end,with 1715 samples of Chinese listed A-share manufacturing enterprises, this paper identifies the key factors influencing their digital transformation from technology, organization, and environment. The digital transformation level of enterprises is measured by the textual analysis method, and empirical analysis is conducted by fsQCA and PSM. The study focuses on two questions:Which conditions (configurations) can trigger a high level of digital transformation? Does digital transformation driven by different paths have the same effect on enterprise performance.#br#The research results indicate that the successful digital transformation of manufacturing enterprises is not driven by a single condition but is the result of a synergistic linkage of technical, organizational, and environmental conditions. There are 4 types of configurations that drive the digital transformation of enterprises, which can be summarized into 3 adaptation models:the model explained by regional digital infrastructure alone (environment-driven); the model explained by enterprises'technology management capability and digital infrastructure together (internal and external synergy); and with attention allocation as the core condition, the model explained by a combination of digital investment, financial security, and peer competitive pressure (opportunity perception). The environment-driven and opportunity-perception models cannot significantly improve enterprise performance, whereas the internal and external synergistic models can positively influence enterprise performance.#br#Within the TOE theoretical framework, this paper examines the key drivers influencing the digital transformation of manufacturing enterprises by fsQCA and summarizes three types of conditional configurations driving their digital transformation, which enriches the literature on the factors influencing digital transformation from a configuration perspective. Moreover, the impact of digital transformation driven by different paths on enterprise performance is examined by PSM. The findings are conducive to explaining why digital transformation brings differential economic consequences, while providing a reference for the paths that enterprises can follow to implement digital transformation at the practical level.#br#
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Received: 08 April 2022
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