Recently, a novel coronavirus pneumonia (2019–nCoV) outbreak occurred in Wuhan, China, rapidly spreading first to the whole country, and then globally, causing widespread concern. From the perspectives of early warning and identification of risk, risk monitoring, and analysis, as well as risk management and handling, we propose corresponding solutions and recommendations, which include institutional cooperation, and to inform national and international policy-makers.

This study first analyzes the national and global infection status of the Coronavirus Disease that emerged in 2019 (COVID-19). It then uses the trend comparison method to predict the inflection point and Key Point of the COVID-19 virus by comparison with the severe acute respiratory syndrome (SARS) graphs, followed by using the Autoregressive Integrated Moving Average model, Autoregressive Moving Average model, Seasonal Autoregressive Integrated Moving-Average with Exogenous Regressors, and Holt Winter’s Exponential Smoothing to predict infections, deaths, and GDP in China. Finally, it discusses and assesses the impact of these results. This study argues that even if the risks and impacts of the epidemic are significant, China’s economy will continue to maintain steady development.

Purpose: Drawing on institution embeddedness and the resource-based view, the authors develop a theoretical framework and empirically examine how intra-national innovation ecosystems and environmental institutions impact logistics service providers' (LSPs) technological innovation (TI) and green practices.Design/methodology/approach: The authors test the theoretical framework based on survey data of 328 Chinese LSPs. Archival datasets complement the survey data.Findings: The research reveals that intra-national institutional forces of formal and informal environment-related institutions can mitigate LSPs' reliance on their firm-specific advantages when engaging in TI and green practices. Results from a three-way interaction indicate that intra-national innovation ecosystems positively moderate the effects of environmental institutions.Research limitations/implications: The research has three critical implications. First, the study reveals the contingency role of intra-national environment-related institutions and innovation ecosystems in shaping green logistics. Second, the study finds new results about the roles of informal environmental institutions. Finally, intra-national innovation ecosystems can override environmental institutions in influencing the green practices of LSPs.Originality/value: Taking a unique angle of institution embeddedness coupled with the resource-based view, the authors examined how intra-national ecosystems and environmental institutions impact LSPs' TI and green practices.

Peering through the lenses of the strategic intent perspective and strategic fit paradigm, in this study, we seek to examine the contingent conditions under which emerging market multinational enterprises (EMNEs) with strategic asset seeking (SAS) intent can achieve improved innovation performance. We developed a contingency model of how the relationship between SAS intent and innovation performance is contingent on the moderating effects of firms’ innovation capability and institutional quality in the host country, as well as on the synergistic interaction of independent moderating effects from these two factors. We combined survey data from 320 Chinese MNEs with archival data to test our hypotheses. Our results show that SAS intent can lead to positive innovation performance when (a) the investing firm has developed high levels of innovation capability, and (b) synergistic interactions exist between institutional quality and firms’ innovation capability regarding their moderating effect on the SAS intent-innovation performance link.

While technological advancements have significantly transformed the international services sector over the past decades, our understanding of their impact on international service enterprises’ corporate social responsibility (CSR) remains fragmented and underdeveloped. We address this gap by conducting a comprehensive three-stage literature review integrating human-led review methods with machine learning and artificial intelligence techniques. Our rigorous analysis mapped evidence from 51 articles published over the past 15 years, identifying fundamental links, conceptual clusters, and evolving research trends within the literature. Our findings provide a robust foundation for future research on the impact of advanced technologies on international service enterprises and their CSR, offering new evidence grounded in the latest analytic techniques and contributing novel insights into the technology—CSR relationship to the scholarly discourse of international services.