Information technology service management (ITSM) driven by artificial intelligence (AI), i.e., AITSM, is likely to change business models and enterprise operations substantially, setting off a wave of enterprise AI transformation. Empowerment from AI has brought new vitality and challenges to ITSM capabilities, and enterprises must start thinking about how the capability of AITSM can be reactivated to shape the resilience of business models and meet survival needs in complex and ever-changing environments. To systematically achieve the development of enterprise business model resilience under AITSM, this study combines the actual situation of ITSM and enterprise AI transformation practice and then deconstruct it into three sub-research questions along the primary line of driver identification–model construction–paradigm optimization. We retrieve high-quality literature in the field of information systems from common databases and discuss the topics of AITSM and business model resilience. This study finds that future research should focus on forming an accurate description of the resilience demand of business models in the current era, and thus, better explain the value cocreation process between AITSM and business units. In addition, future research should emphasize the dynamic and strategic nature of business model resilience to study the continuous optimization of business models with the help of AITSM.

In recent years, both industry professionals and scholars have shown increased interest in the ability of big data management capabilities (BDMCs) to drive green innovation, emphasizing their potential in fostering environmentally sustainable practices. While many studies highlight the positive influence of big data technology on green innovation, there is a notable gap in understanding the managerial process required for such innovation. Moreover, the roles of green dynamic capabilities and environmental turbulence in this context are underexplored. This study aims to contribute to the existing literature by examining the mechanisms and boundary conditions of the relationship between BDMCs and green innovation. We gathered data from 266 Chinese manufacturing enterprises using questionnaires and analyzed the results using Partial Least Squares Structural Equation Modeling (PLS-SEM). Our findings indicate that, despite the inherent qualities of BDMCs such as rarity, applicability, nonreplicability, and non-substitutability, their influence on green innovation is reduced in the absence of effective green dynamic capabilities. Furthermore, our study suggests that environmental turbulence does not weaken the influence of BDMCs on green dynamic capabilities; rather, it amplifies the effects of BDMCs on green dynamic capabilities and their impact on two types of green innovation. This study provides new insights for manufacturing enterprises aiming to achieve green transformation. We also discuss the theoretical and practical implications of the research, along with its limitations.

This research examines the linkage between entrepreneurial orientation and sustainable innovation. Research shows that the effects of entrepreneurial orientation on the exploitation and exploration of sustainable innovation are significantly positive, whereby absorptive capacity acts in a significant mediating role. The interaction between entrepreneurial orientation and absorptive capacity helps organizations overcome organizational inertia and strengthen the sustainability of innovation. By introducing the absorptive capacity theory and the view of organizational inertia, we have conducted empirical research on 392 Chinese environmentally friendly companies that have passed China’s national high-tech enterprise certification. We verified the relevant hypotheses in our framework in a structural model analysis using Mplus. To further look at the interaction terms of potential and realized absorptive capacity, we used PROCESS in SPSS to evaluate the conditional effects of absorptive capacity on coefficient paths between entrepreneurial orientation and the two types of innovation. The results show that entrepreneurial orientation improves the absorptive capacity of organizations, thereby promoting their sustainable innovation. Furthermore, based on the theory of sustainable innovation, we proved the positive impact of realized and potential absorptive capacity on the exploitation and exploration of sustainable innovation. Organizations could balance exploitation and exploration to implement sustainable innovation by adjusting their potential and realized absorptive capacities. Our results can help environmentally friendly organizations adjust the combination of entrepreneurial orientation and absorptive capacity to overcome organizational inertia, manage exploitation and exploration, and implement sustainable innovation.