Information technology has brought about significant changes in enterprises, and new work situations have led to new problems. Employee resistance to new technologies, their ability to learn, and their ability to utilize personal resources to improve work engagement in the face of technological pressure are important factors that companies need to consider when undergoing digital transformation. The influence mechanism of configuration effects on factors around employee work engagement has not been explored, and technostress creators have rarely been included in the configuration as influencing factors in previous studies. On the basis of the job demands-resources (JD-R) model and trait activation theory, this study explored the factors that affect employees’ work engagement at the level of job demands and personal resources. The fuzzy-set qualitative comparative analysis (fsQCA) method was used to investigate the influence of technical stressors, self-efficacy, and the Big Five personality traits on employees’ work engagement. Through a survey of 225 employees in the context of enterprise digital transformation, the results show three driving paths that promote employees’ work engagement: openness to experience conscientiousness, self-efficacy driven, and inhibition to technical stressors. The study also analyzed employees’ low work engagement state, which is driven by an inhibition of agreeableness and extraversion. This research enriches the study of factors influencing work engagement in the digital transformation of enterprises.

Despite the acknowledged importance of innovation for enterprises’ sustainable development, in comparison to technological innovation, research on market-based innovation is still in its nascent stage. It is unclear what factors will predict market-based innovation and how market-based innovation boosts innovation performance. Therefore, based on an adaptive marketing capabilities perspective and drawing on insights from the organizational ambidexterity literature, this study explored the relationships among enterprises’ marketing capabilities, market-based innovation and innovation performance. Data collected from 237 manufacturing enterprises in China were analyzed using hierarchical regression analysis and bootstrapping methods. The results showed that: (1) Marketing capabilities and market-based innovation activities are both ambidextrous. Specifically, marketing capabilities include marketing exploration capabilities and marketing exploitation capabilities, and market-based innovation includes exploratory market-based innovation and exploitative market-based innovation. (2) Ambidextrous marketing capabilities can enhance innovation performance significantly, with ambidextrous market-based innovation playing a partial mediating role in this relationship. Specifically, marketing exploration capabilities affect innovation performance through the partial mediating role of exploratory market-based innovation, whereas marketing exploitation capabilities affect innovation performance through the partial mediating role of exploitative market-based innovation. (3) Exploratory market-based innovation negatively moderates the relationship between exploitative market-based innovation and innovation performance, and exploitative market-based innovation also exerts a negative moderating effect on the exploratory market-based innovation–innovation performance association. These findings complement and enrich the ambidextrous capability (innovation) theory, helping manufacturing enterprises to better understand and deploy ambidexterity, and hence to achieve sustainability.

Purpose: This research paper examines how hub firm transformation and restructuring of network partnerships shape the development of industrial clusters in China.Design/methodology/approach: Questionnaire data were collected from 210 managers (response rate 70.9 percent) from the manufacturing industrial clusters in Eastern China.Findings: The results inform that a cluster’s hub firm transformation influences the evolution of the cluster. Though the hub firm may possess transformation capabilities, the cluster is likely to be weakened if network partnerships and resource synergy are not formed amongst the cluster members.Research limitations/implications: This paper, in examining the individual- and firm-level attributes of orchestration capability and their interactions, sheds light on the firm level and inter-firm level relationships between resources and innovation in an industrial cluster.Practical implications: To facilitate learning and the upgrading of firms within an industry cluster and promote a cluster’s innovation network, policymakers can initiate preferential policy measures to cultivate support to strategically transform a cluster’s hub firm, thus fostering cluster network growth.Originality/value: The paper studies the evolution of clusters by investigating the hub firm transformation and member firm interaction. Focusing on the inter-firm network interactions lends a richer understanding of the nuances of the evolution of industrial clusters in Asia.

This article focuses on the innovation and knowledge evolution of industry clusters. We examine the effects of the hub firm and the interaction of network member firms on the upgrading of the cluster. Our study is based on two patterns of knowledge learning and innovation, namely, STI (science, technology, and innovation) and DUI (doing, using, and interacting). This article adopts a knowledge diffusion simulation model to study the exchange of knowledge between cluster network actors in the context of small-world networks. The results indicate that we must pay close attention to the influence of hub enterprises on cluster evolution. Although hub companies may have certain innovation capabilities, if knowledge absorption problems among members are not properly resolved in the cluster network, the innovation performance of the local clusters is likely to be weakened, despite the success of the hub firm.

Effectively promoting employees’ intrapreneurial behavior has become the focus of enterprises. This study takes the middle and grassroots employees in enterprises as subjects and explores the configuration effect of multiple influencing factors on employees’ intrapreneurial behavior. Based on employee expectation theory and individual-environment matching theory, this study collates six influencing factors: entrepreneurial self-efficacy, entrepreneurial competence, task school level, perceived value, management support, and reward mechanism. A total of 163 samples were obtained, and the qualitative comparative analysis method based on fuzzy set was used to analyze the influence mechanism and result path of employees’ intrapreneurial behavior from the perspective of the interaction between individual factors and organizational factors. Six influencing paths of employees’ high intrapreneurial behavior were found, which can be divided into ability-driven and value-driven factors, revealing that the six factors can produce equivalent results in different configurations. Furthermore, five influencing paths of employees’ non-high intrapreneurial behavior were divided into three types: ability obstacle type, perception obstacle type, and value obstacle type. These have an asymmetric causal relationship with employees’ high intrapreneurial behavior. This study provides management support for effectively stimulating employees’ intrapreneurial behavior.