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AbstractTo date, minimal literature is based on a systems perspective to examine the ecosystems of the industrial chain and supply chain. To fill the gap, this study has employed a systems perspective in analysing issues related to the industrial chain–supply chain ecology. The term 'industrial chain–supply chain' emerged recently to reflect the current global manufacturing industry structure and a prevalent global supply chain. This study clarifies the concepts of industrial chain ecosystem and supply chain ecosystem, highlighting their similarities and distinctions. Additionally, the study outlines the process of value creation within the industrial chain–supply chain ecosystem, involving innovation in research, technology, products, systems and management, leading to technological breakthroughs and enhancements. A three‐stage model for the industrial chain–supply chain ecosystem is proposed, comprising the blueprint creation stage, the core technology breakthrough stage and the iterative ecosystem upgrade stage.

AbstractService‐oriented manufacturing (SOM) strategy is a new manufacturing mode by integrating servitization with the traditional manufacturing industry. As a vital paradigm of manufacturing transformation and upgrading, SOM is conducive to bringing new business opportunities to enterprises and thus increasing their competitive advantages, especially in the IT‐enabled industry. This study reviews the key drivers and significant developments in IT‐enabled SOM. An evaluation framework for IT‐enabled SOM is proposed to enrich the theoretical research related to SOM and provide a reference for the enterprises that aim to upgrade.

AbstractArtificial intelligence has been widely adopted for digital transformation and value creation for enterprises. However, studies about how participants can co‐create value in the AI innovation ecosystem are needed. Thus, this research proposed a comprehensive research model to examine the impact of value co‐creation in the AI innovation ecosystem for competitive advantage and innovation intelligibility with the mediating effect of dynamic capabilities and innovation capabilities. We collected data from 234 AI‐related manufacturers for the structural equation modelling analysis. Results show that (1) the AI innovation ecosystem can bring economic value and relationship value to enterprises; (2) impacts of economic value and relationship value on competitive advantage and innovation intelligibility are not significant; and (3) value co‐creation does not have a significant impact on competitive advantage and innovation intelligibility, and dynamic capabilities and innovation capabilities play the mediating role. Theoretical contribution, practical implication, limitation, and future research are presented.

PurposeThe purpose of this study is to verify whether digital transformation strategy (DTS) could improve the organizational performance and provide a comprehensive analysis for enterprises on the necessity of implementing digital transformation in the context of China and draw on the perspectives of "Skewed conflict," "minority dissent theory" and "too-much-of-a-good-thing." This study investigates the curvilinear moderating role of cognitive conflict between DTS and performance.Design/methodology/approachAn empirical investigation was used to collect a large sample data of Chinese enterprises' digital transformation. A multiple linear regression analysis with SPSS was used to test the proposed hypotheses such as the inverted U-shaped moderating effect of the cognitive conflict.FindingsIn the Chinese context, DTS has a positive relationship on the short- and long-term financial performance. Moreover, this relationship was moderated by cognitive conflict such that the relationship between DTS and short-term financial performance could be further enhanced under the moderate cognitive conflict; however, the relationship between DTS and long-term financial performance was considerably influenced for higher cognitive conflict.Originality/valueBased on the co-evolution of the information technology/information system (IT/IS) and business strategy, this study clarified the relationships among DTS, digital strategy and business and information technology strategies. By focusing on corporate strategy, this study further examined the effect of digital transformation on both short- and long-term financial performance. To further reveal the micro-psychological mechanisms underlying the effect of DTS on organizational performance, this study confirmed the inverted U-shaped moderating effect of the top management team's cognitive conflict. Therefore, this research provides a new theoretical perspective for future research in the field of IT/IS, DTS and digital strategy.

AbstractArtificial intelligence (AI) has emerged as a pivotal catalyst for industrial advancement and economic growth, fueling innovation across various sectors. It stands as a cornerstone in propelling the integrated evolution of cutting‐edge technologies like big data, cloud computing, blockchain, 5G/6G and industry 4.0. Consequently, AI has captured significant attention within academic and industrial spheres alike. This study conducts a comprehensive review of AI‐related research and models, offering systematic insights into its industrial applications and future trajectories. By providing valuable insights, this review serves as a crucial reference point for both researchers and practitioners navigating the dynamic landscape of AI innovation.