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This study aims to examine the dynamic bidirectional causality between oil price (OIL) and stock market indexes in net oil-exporting (Russia) and net oil-importing (China) countries.

The authors use monthly data for the period starting from October 1995 to October 2021. In this study, the bootstrap rolling-window Granger causality approach introduced by Balcilar et al. (2010) and the probit regression model are performed in order to identify the bidirectional causality.

The results show that the causal periods mainly occur during economic, financial and health crises. For oil-exporting country, the results suggest that any increase (decrease) in the OIL leads to an appreciation (depreciation) in the stock market index. The effect of the stock market on OIL is more relevant for the oil-importing country than that for the oil-exporting one. The COVID-19 consequences are demonstrated in the impact of oil on the Russian stock market. The probit regression shows that the US financial instabilities increase the probability of causality between OIL and stock market indexes in Russia and China.

The dynamic relationship between the variables must be taken into account in investment decisions. As financial instabilities in the USA drive the relationship between oil and stocks, investors should consider geopolitical, economic and financial elements when constructing their portfolios. Shareholders are required to include other assets in their portfolios since oil–stock relationship is highly risky.

This study provides further evidence of the bidirectional oil–stock causal link. Additionally, it examines the impact of financial instabilities on the probability that the OIL and the stock market index cause each other through the Granger effect.

In times of crisis, innovation management and specifically Research and Development (R&D) investments are critical to temper company losses and stimulate higher revenues. Environmental policies, for their potential to stimulate environmental innovations and efficient management of resources, may hold a magnifying role in this relationship. By relying on the distinction between regulatory policies and institutional incentives, this paper argues about the moderating role of environmental policies between a firm's R&D expenses and its performance.

Hypotheses are tested on data collected from a sample of small and medium-sized Chinese enterprises after the 2008 financial crisis.

Findings reveal positive moderating effects of both regulatory pressures and institutional incentives, with a more significant effect of government support. The highest impact is reached when both these types of policies are present.

The theoretical and methodological relevance of this distinction, the importance of an appropriate mix of environmental policies in policymaking and their resilience building role in stimulating environmental innovations in the aftermath of crises are discussed.

This study aims to examine whether the age and tenure of the chair of the board of directors are related to research and development (R&D) investment in China.

This study uses A-share manufacturing firms that traded on the Shanghai and Shenzhen stock exchange between 2009 and 2018. This study uses OLS regressions, controls for self-selection bias, and uses an instrumental variable to alleviate the concern of endogeneity.

This study finds that chair tenure has a negative relationship with R&D investment. This study does not find a significant relationship between chair age and R&D investment.

This study contributes to corporate governance and strategic management literature by highlighting chair tenure as a new factor affecting R&D investments. It also adds a significant contribution to the limited literature on the chair’s role in strategic decisions. Moreover, companies that are eager to strengthen corporate governance and maintain sustained innovation may reconsider the chair tenure. Given that many proposals for board governance reform explicitly stress the importance of limiting board tenure, this study contributes to policymakers by providing evidence in support of these proposals.

This study investigated the asymmetric effects of changes in policy uncertainty on real sector variables in Brazil, China, India and South Africa.

The study used the nonlinear autoregressive distributed lag (NARDL) modeling framework.

The results showed that both in the long run and short run, rising uncertainty not only increases consumer prices significantly in these economies, but also impedes aggregate and sectoral output growths, and deters investment, employment and private consumption. Contrary to economic expectation, the results also showed that in the long run, declining uncertainty impedes aggregate and sectoral output growths in these economies, and significantly hinders employment in South Africa and Brazil. This suggests that in the long run, economic agents in these economies somewhat behave as if uncertainty is rising. The authors also found significant asymmetric effects in the response of real sector variables to uncertainty both in the long run and short run, which justifies the choice of NARDL framework for this study.

The sample is limited to Brazil, India, China and South Africa. While Brazil, India and China are three of the most prominent large emerging market economies, South Africa is the largest emerging market economy in Africa.

To lessen the adverse effects of policy uncertainty observed in the results, there is need for sound institutions and policy regimes that can promote predictable policy responses in these economies so that policy neither serves as a source of uncertainty nor as a channel through which the effects of other shocks are transmitted.

Apart from using the NARDL framework to capture the asymmetric effects of policy uncertainty, this study also accounted for the sectoral effects of uncertainty in emerging markets.

This study aims to analyze the determinants influencing Chinese manufacturing companies in implementing lean manufacturing (LM).

The determinants to be explored in this study consist of technological, organizational and environmental (TOE) dimensions. A questionnaire survey was conducted on Chinese manufacturing companies, and 208 samples were analyzed.

The findings show that the relative advantage of LM and organizational support have significantly positive effects on Chinese manufacturing firms’ adoption of LM. The complexity of LM, quality of human resources, organizational readiness, customer pressure, international situation, governmental support and environmental uncertainty do not have significant effects.

This paper contributes to the literature by using the TOE model to explore the factors influencing LM adoption in the Chinese manufacturing industry.

Based on the perspective of knowledge management capability, this paper aims to reveal the internal mechanism of the digital empowerment of mobile social platforms to improve the operational performance of Chinese traditional retail enterprises. Such improvements have crucial theoretical value and practical implications for Chinese traditional retail enterprises to achieve transformation and sustainable development.

This study applied the typical analysis method, selected China’s leading mobile social platform, WeChat, as a typical case, and observed and analyzed the public data of the traditional retail industry and social platforms and interviews with relevant enterprises. On this basis, this study used the inductive and deductive methods of qualitative research to conduct an in-depth analysis of the mechanism by which WeChat’s digital empowerment improves the operational performance of Chinese traditional retail enterprises. It also discussed the critical role and path knowledge management capabilities play in this mechanism.

This research demonstrated that mobile social platforms empower Chinese traditional retail enterprises to build diversified digital channels, enhance the knowledge acquisition capability of enterprises and thus improve their performance; empower Chinese traditional retail enterprises to build digital community networks, enhance the knowledge diffusion capability of enterprises and thus improve their performance; and empower Chinese traditional retail enterprises to integrate online and offline businesses, enhance the knowledge integration capability of enterprises and thus improve their performance.

This study clarifies the internal mechanism of how the digital empowerment of mobile social platforms can improve the performance of Chinese traditional retail enterprises. This mechanism implies that knowledge management capabilities (knowledge acquisition, diffusion and integration capability) are the underlying logic for Chinese traditional retail enterprises to achieve higher performance levels. This has important practical implications for managers of Chinese traditional retail enterprises to leverage the digital infrastructure of mobile social platforms to achieve the sustainable development of enterprises.

This study provides an in-depth analysis of how the traditional retail industry uses digital social platforms to improve operational performance from the perspective of knowledge management capabilities, which can further promote the theoretical research and practical development of digitalization and knowledge management. At the same time, this study explored the research on the operational performance of Chinese traditional retail enterprises from the perspective of knowledge management capabilities and expanded the research on knowledge management in related fields. The authors have initially sorted out the impact of knowledge management capabilities on the operational performance of Chinese traditional retail enterprises in the digital era. This will help better understand the role and function of knowledge management in strategic transformation and expand the application of knowledge management theory.

This study aims to systematically reveal the complex interaction between uncertainty and the international commodity market (CRB).

A composite uncertainty index and five categorical uncertainty indices, together with wavelet analysis and detrended cross-correlation analysis, were used. First, in the time-frequency domain, the coherency and lead-lag relationship between uncertainty and the commodity markets were investigated. Furthermore, the transmission direction of the cross-correlation over different lag periods and asymmetry in this cross-correlation under different trends were identified.

First, there is significant coherency between uncertainties and CRB mainly in the short and medium terms, with natural disaster and public health uncertainties tending to lead CRB. Second, uncertainty impacts CRB more markedly over shorter lag periods, whereas the impact of CRB on uncertainty gradually increases with longer lag periods. Third, the cross-correlation is asymmetric and multifractal under different trends. Finally, from the perspective of lag periods and trends, the interaction of uncertainty with the Chinese commodity market is significantly different from its interaction with CRB.

First, this study comprehensively constructs a composite uncertainty index based on five types of uncertainty. Second, this study provides a scientific perspective on examining the core and diverse interactions between uncertainty and CRB, as achieved by investigating the interactions of CRB with five categorical and composite uncertainties. Third, this study provides a new research framework to enable multiscale analysis of the complex interaction between uncertainty and the commodity markets.

This study aims to investigate the perspective of corporate philanthropy during the coronavirus disease 2019 (COVID-19) in China for firms with various levels of corporate social responsibility (CSR). Specifically, the study appraises the impact of the COVID-19 pandemic on the stock returns and sustainable development of Chinese-listed companies and determines the likelihood of paying donations vis-à-vis firm reputation.

The study used data from 117 Chinese-listed firms engaged in philanthropy during the COVID-19 pandemic. The authors also utilized the stock returns and cash donation data, and owing to the cross-sectional data and continuous nature of dependent variables, they employed the ordinary least squares regression to test the research hypotheses.

The results show that irresponsible actions have a positive relationship with donations. The study particularly reveals that irresponsible firms have significant negative abnormal returns during the first wave of the COVID-19 pandemic.

To the best of our knowledge, this is the first empirical study to explore the perspective of corporate philanthropy during the COVID-19 pandemic for companies with different CSR levels. This study contributes to the empirical research on CSR and provides insights for managerial-cum-financial decisions to encourage managers of irresponsible firms to pursue philanthropic behaviors after crisis events.

Drawing on social capital theory, this study aims to explore the effect of corporate social responsibility (CSR) on organizational resilience. The research investigates the mediating role of relationship quality in the association of CSR with organizational resilience, and the moderating role of data-driven culture in the association between CSR and relationship quality.

Data were collected from Chinese agricultural firms with a sample of 241 senior or middle executives and structural equation modeling was used to test the research model and hypotheses.

The results indicate that CSR positively affects the relationship quality between agribusinesses and farmers, which in turn positively affects both proactive resilience and reactive resilience. Relationship quality has a partial mediating role in the association of CSR with proactive resilience and reactive resilience. Data-driven culture has a positive moderating effect on the relationship between CSR and relationship quality.

By arguing for CSR toward organizational resilience and analyzing its underlying mechanism, this study enriches the literature on CSR and organizational resilience and expands the existing knowledge on the roles of relationship quality and data-driven culture. This study also provides practical insights into how to improve organizational resilience.

This article aims to clarify the impact of stock market liberalization on corporate green technology innovation, analyze its mechanism from the perspectives of financing constraints and environmental management level and explore heterogeneity.

Using the panel data of Chinese enterprises from 2010 to 2020, this article adopts the multi-point difference-in-difference (DID) method to test the impact of stock market liberalization on enterprise green technology innovation and its conduction pathway.

The outcomes demonstrate that stock market liberalization contributes to the furthering of green technology innovation. The heterogeneity test reveals that this promotion is more pronounced for private companies, small-scale companies and companies with high information transparency. The mediating effect test shows that stock market liberalization boosts green technology innovation by alleviating corporate financing constraints and improving corporate environmental management.

This article elucidates the impact path of stock market liberalization on corporate green innovation based on alleviating corporate financing constraints and improving corporate environmental management levels. From the perspective of corporate green technology innovation, this article provides evidence from emerging market countries for the economic effects of capital market opening, which helps to further improve the level of green innovation.