Digital transformation is a critical challenge for commercial banks to achieve sustainable competitive advantages in the digital economy. However, conventional research focuses too much on constructing linear models to explain the non-linear relationships between and among the factors relevant to digital transformation. By adopting the configurational framework, we propose that the interactions between strategy and dynamic capabilities determine the paths of how digital transformation may succeed or fail. The fuzzy-set qualitative comparative analysis (fsQCA) of digital transformation practices by Chinese commercial banks shows that: (1) a single condition of strategic orientation or dynamic capabilities does not constitute the necessary condition for high digital transformation, yet market orientation plays a more general role in generating high digital transformation. (2) There are three configurational paths that can contribute to high digital transformation of commercial banks, such as sensing capability-driven paths dominated by strategic orientation, integrating capability-driven paths dominated by strategic orientation, and the market orientation-driven paths dominated by dynamic capabilities. (3) There are two configurational paths that lead to non-high digital transformation, which verifies the existence of the asymmetrical relationship compared to the configurational paths of high digital transformation; (4) In the pathways dominated by strategic orientation, there is a substitutive relationship between sensing capability and integrating capability. The findings make contributions to the literature on digital transformation and provide implications for the digital transformation of commercial banks.

Using the exogenous shock caused by the mandatory corporate social responsibility (CSR) information disclosure policy in 2008, this paper examines the impact of mandatory CSR information disclosure on the earnings management activities of listed firms in China from the perspective of external corporate regulation based on the Difference-in-Differences (DID) method. The results show that mandatory CSR information disclosure can significantly improve the quality of firms’ earnings management. The mechanism analysis shows that the policy’s enhancement of the effectiveness of external regulation by regulators and the media played an important role in curbing firms’ earnings management activities. The heterogeneity analysis shows that the inhibitory effect of mandatory CSR disclosure policy on firms’ earnings management activities is better in firms with lower analyst coverage and lower institutional ownership. The study further extends the mechanism of the impact of mandatory CSR disclosure on firms’ earnings management activities, and provides practical guidance on how to improve the quality of firms’ earnings management and enhance the efficiency of corporate governance.

Innovation ambidexterity has become a crucial strategic action for creating sustainable competitive advantages. This research provides novel insights by establishing a connection between performance gaps and innovation ambidexterity. We employ the organization’s resource acquisition and management perspective to construct and empirically assess a moderated mediation model that sheds light on the underlying process—through the dual-mediating path of network broadening (NB) and network deepening (ND) and the moderating role of resource orchestration capabilities. Using subjective surveys and objective-matched data from 362 Chinese listed firms, we confirm the positive-performance-gap-combined innovation ambidexterity relationship, and we find that NB and ND play a parallel mediating role between performance gap and balanced and combined innovation ambidexterity, with ND playing a stronger mediating role than NB. Furthermore, resource orchestration capabilities play a moderating role between NB and balanced and combined innovation ambidexterity, as well as between ND and balanced and combined innovation ambidexterity. These results contribute to the research on social network and ambidexterity literature and provide guidance on how to overcome firms’ performance dilemmas. However, our study has certain methodological limitations that constrain the implications of our results, offering intriguing opportunities for future research.

In the era of artificial intelligence, an increasing number of robots are entering the workplace as active contributors to organizational tasks. While robots can enhance employees' efficiency by complementing human capabilities, they may also lead to strong perceptions of threat among employees. Integrating the threat-rigidity and threat-flexibility theory, the study examines how perceived robot threat indirectly affects employees' proactive behavior through emotional exhaustion and cognitive flexibility, and how these indirect effects are contingent on human-robot interaction. Focusing on task-oriented workplace robots, the study employs a multi-wave, multi-source field survey and a scenario-based experimental design conducted in China. Results show that when human-robot interaction intensity is low, perceived robot threat increases emotional exhaustion and limits cognitive flexibility, thereby indirectly inhibiting employees' proactive behavior. When interaction intensity is high, the positive effect of perceived robot threat on emotional exhaustion is attenuated or even reversed, and its positive effect on cognitive flexibility is strengthened, with these pathways indirectly promoting employees' proactive behavior. By adopting a human-robot interaction lens, the study reveals the boundary conditions in which perceived robot threat yields divergent indirect effects on employee behavior, offering insights for organizations seeking to anticipate and manage the psychological impact of workplace robots.

The negative impact of disruption events (i.e., departure of key personnel, geopolitical conflicts) on normalized economic operations is self-evident. How complex product R&D networks maintain resilience under disruptions is an unavoidable management issue. Existing research has primarily focused on the effects of inter-organizational interactions under disruption events, while paying little attention to the diversity of multi-agent interactions in complex product R&D network and the deeper logic embedded within them. Combining the attention-based view and sequential attention logic, we take the resilience of complex product R&D networks as the dependent variable to study the selection effects of multi-agent interaction modes in complex product R&D networks under disruption events. A hierarchical linear regression was conducted on 427 questionnaire samples from the high-end equipment manufacturing industry. Empirical results show that complex product R&D networks are prone to two multi-agent interaction modes under disruption events: the focal firm-dominated mode and the multi-agent co-creation mode. Compared with the latter, focal firms show a stronger preference for the former mode in disruptions. Both multi-agent interaction modes contribute to enhancing network resilience. Further research shows that under first-order disruption events (i.e., departure of key personnel), both focal firm-dominated mode and the multi-agent co-creation mode serve as effective resilience governance strategies for complex product R&D networks, with the multi-agent co-creation mode being better than the focal firm-dominated mode. Under second-order disruption events (i.e., geopolitical conflicts), only the multi-agent co-creation mode emerges as an important mechanism for resilience governance of complex product R&D networks. The findings provide a theoretical foundation for complex product R&D networks to select the optimal multi-agent interaction mode to enhance resilience and effectively respond to disruption events.