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Research on the Mechanism of How Manufacturing Enterprise Innovation Process Is Drivern by Digital Transformation Scenario
Zhang Pei, Yang Dandan
2026, 38 (2):
274-288.
Manufacturing enterprises, with their rich production data, complex production scenarios, close supply chain partnerships, and customized product demands, have developed a unique advantage in scenario-driven innovation. However, existing literature has not provided sufficient explanations on how manufacturing enterprises achieve scenario-driven innovation. From both the perspectives of scenarios and knowledge, this study focuses on the differential impact of scenario-specific characteristics and the evolving relationship between human-machine knowledge elements on innovation outcomes during the digital transformation process of manufacturing enterprises. A case study is conducted based on the ongoing digital transformation practices of a business printing enterprise. The research findings are as follows: First, a scene can be deconstructed into two parts: temporal-spatial constraints and the content of the demand scenario. Among them, the temporal-spatial constraints form the basic components of the scene, while the characteristics of the scene content are key to influencing the interactive behaviors and patterns of the subjects within the scene, exhibiting features of both determinacy and complexity. Second, the realization of scenario-driven innovation mainly focuses on three aspects: reshaping scenario content, optimizing scenario content, and deriving scenario content. Behind this lies the continuous interaction between the subject and the business within the scenario content dimension, which further leads to changes in scenario characteristics (both spatial-temporal and content dimensions). Third, based on the characteristics of scenario content and innovation behaviors, three types of digital transformation-driven innovation outcomes in manufacturing enterprises are identified: efficiency-oriented, expert-oriented, and expansion-oriented innovation models. During this process, three changes in knowledge elements occur: substitutability, complementarity, and combinatorial diversity. The research has significant theoretical and practical value for understanding scenario elements and their role in driving the innovation process.
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