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Although past studies have suggested that business-to-business (B2B) interfirm relationship management contributes to a firm’s omnichannel integration, little research has been undertaken to reveal how that happens. This study aims to draw upon the relational view to propose a research model that associates interfirm information technology (IT) capability and interfirm trust with omnichannel integration through interfirm integration (i.e. authority integration and cooperative integration). Furthermore, this work considers a firm’s channel usage variety as the boundary condition of the interfirm integration’s influence.

The research model was examined using a seemingly unrelated regression of archival data and matched a survey of 324 Chinese omnichannel firms.

Interfirm IT capability positively relates to authority integration, and interfirm trust positively relates to cooperative integration. Authority integration and cooperative integration are both positively associated with omnichannel integration. A high level of channel usage variety strengthens the relationship between cooperative integration and omnichannel integration.

Prior literature has called for research on the factors influencing omnichannel integration within a B2B setting. This study answers this research call by examining interfirm IT capability, interfirm trust and interfirm integration as factors associated with omnichannel integration. This work also examines how channel usage variety regulates the relationship between interfirm integration and omnichannel integration.

The purpose of this study is to examine the underlying mechanisms of exploitative innovation and exploratory innovation between social media usage and organizational agility, and elucidate the moderating role of learning goal orientation (LGO) in the above relationships, based on adaptive structuration theory (AST).

Based on a multiple-respondent matched survey of 334 Chinese e-commerce firms, authors employed structural equation modeling to examine the correlations among social media usage, exploitative innovation, exploratory innovation and organizational agility. Hierarchical regression analysis was used to examine the moderating role of LGO.

This study's empirical findings demonstrate that exploitative innovation and exploratory innovation mediate the relationship between social media usage and organizational agility in different ways. Further, LGO positively moderates the relationship between social media usage for customer acquisition and exploratory innovation, as well as the relationship between social media usage for customer relationship and exploitative innovation.

Firms are advised to leverage different types of social media usage to facilitate exploitative innovation and exploratory innovation and promote organizational agility. In addition, LGO within a firm should be established to enhance the effects of social media usage on exploitative innovation and exploratory innovation.

This study adds to the literature on social media usage by proposing and examining exploitative innovation and exploratory innovation as explanatory mechanisms to facilitate organizational agility. This study further identifies LGO as a boundary condition of social media usage's effect on exploitative innovation and exploratory innovation. By contextualizing social media as advanced information technology, this study contributes to the contextualization of AST in the social media context.

According to relevant research, non-uniform speed has a significant impact on the vehicle-track systems. Up to now, research work on it is still very limited. In this paper, the PEM is adopted to further transform it into a deterministic process to solve the vehicle’s problem of running at a non-uniform speed.

The multi-body vehicle model has 10 degrees of freedom and the track is regarded as a finite long beam supported by lumped sleepers and ballast blocks. They are connected via linear Hertz springs. The vertical track irregularity is a Gaussian stationary process in the space domain. It is transformed into a uniformly modulated nonstationary random process in the time domain with respect to the non-uniform vehicle speed. By solving the equation of motion of the coupled vehicle-track system with the pseudo-excitation method, the pseudo-response and consequently the power spectral density and the standard deviation of the structural response can be obtained.

Two kinds of vehicle braking programs are taken in the numerical example and some beneficial conclusions are drawn.

The pseudo-excitation method (PEM) was used to perform the random vibration analysis of a coupled non-uniform speed vehicle-track system. Transforming the track irregularity into a uniformly modulated nonstationary random process in time domain with respect to the non-uniform vehicle speed was undertaken. The pseudo-response of the coupled system is solved by applying the Newmark algorithm with constant space integral steps. The random vibration transfer mechanism of the coupled system is fully discussed.

The purpose of this paper is to analyze the impact of different information source on consumer attitudes toward genetically modified food.

The data used in this study are obtained from a large-scale nationwide consumers' survey in urban China conducted by the China Center for Agricultural Policy, Peking University, in 2020. A descriptive analysis between information sources and consumer attitudes toward GM food was conducted. Based on the collected data, an econometric model on the determinants of consumer attitudes was constructed and used for analysis.

This study shows that the impact of new media is currently no different than that of traditional media, indicating that the media campaign successfully reduced the spread of rumors and misinformation regarding GM food. Moreover, this study also shows that consumers whose main information source regarding GM foods is school hold more positive feelings toward such food.

This study contributes to the existing literature by examining the impact of information source on consumer attitudes toward GM food. To reverse consumers' negative attitudes, China has launched a widespread media campaign since the first decade of the 2000s. Results of this study show that authorities' efforts to manage and surveil new media have yielded the desired outcome.

Option pricing theory enables computation of the price of an option using different variables associated with the underlying security and options contract. The purpose of this study is to assess research trends that emerged in the field of option pricing. This study reviews existing literature of the option pricing domain, both qualitatively and quantitatively, and identifies potential themes for future research.

This study adopts bibliometric analysis method to explore literature published in the option pricing domain. As part of bibliometric analysis, this study considers both descriptive and network analysis to assess publication trends. For descriptive analysis, the “bibliometrix” package proposed by Aria and Cuccurullo (2017) is used and for network analysis, VOS viewer (Van Eck and Waltman, 2017) and Gephi (Bastian et al., 2009) are used.

This study identifies research trends, top researchers, articles, journals and contributions from institutions and countries in the option pricing domain. It identifies four clusters that show different directions and also focuses on past studies on the same subject. It explores research gaps by performing an in-depth analysis of existing literature on option pricing and suggests the way forward for research in this area.

To the best of the authors’ knowledge, no previous studies have attempted to analyze the literature published in the option pricing domain. This study fulfils this research gap by conducting a comprehensive analysis of studies in the option pricing area. This study identifies quality research work published in the domain, research trends, contribution by most relevant researchers, contributions across geographies and institutions and the connections among these aspects. This study also identifies important themes and provides directions for future research.

The intensity of carbon emissions has led to the serious problem of global warming, and the consequences in terms of climatic disasters are gaining increasing attention worldwide. As the energy sector is responsible for most global emissions, developing clean energy is crucial to combat climate change. This study aims to examine the relationship between corporate governance and renewable energy (RE) consumption and explore the interaction between RE production and RE use.

The study adopts an econometric framework of a panel model, followed by the robustness check using alternative methods, including logit regressions. The bivariate probit model is used to analyze the interaction between the decision to use and the decision to produce RE. The analysis is based on a sample of 3,896 firms covering 45 countries worldwide.

The results reveal that appropriate governance mechanisms positively impact RE consumption. These include the existence of a sustainability committee; environmental, social and governance-based compensation policy; financial performance-based compensation; sustainability external audit; transparency; board gender diversity; and board independence. Firms with appropriate governance mechanisms are more likely to produce and use RE than others. Finally, while RE use positively impacts firm value and environmental performance, the authors find no significant effect on current profitability.

This study goes beyond previous research by exploring the impact of multiple governance mechanisms. To the best of the authors’ knowledge, this is also the first study examining the relationship between RE use and firm value. Overall, the findings suggest that RE transition requires, first of all, establishing appropriate governance mechanisms within companies.

This paper aims to investigate the long-run financial and environmental performance of corporate green bond issuers, worldwide.

The data includes 259 corporate green bond issuers from 2013 to 2020. The authors adopt the matching approach, using the nearest neighbor method to select the control firms. The event-time approach is used to examine corporate green bond issuers’ long-run stock market performance, and robustness tests are conducted using the calendar-time method. The authors examine green bond issuers’ long-run environmental performance and carbon dioxide (CO₂₎ emissions using difference-in-differences estimations.

In contrast with the earlier long-run event studies, our results reveal that multiple-time issuers, and issuers operating in industries where the natural environment is financially material, perform financially in the long term relative to the control firms. The authors also document that corporate green bond issuers reduce their CO₂ emissions, and improve their resource use efficiency and environmental performance, in the long run.

To the authors’ knowledge, this is the first study that looks at the long-run effect of corporate green bond issuance on firms’ stock market performance. It has the particularity to document that corporate green bond issuance is beneficial for investors and positively affects the environment. Our findings help us understand that firms do not issue green bonds for greenwashing.

This paper aims to automatically obtain the implant parameter from the CBCT images to improve the outcome of implant planning.

This paper proposes automatic simulated dental implant positioning on CBCT images, which can significantly improve the efficiency of implant planning. The authors introduce the fusion point calculation method for the missing tooth's long axis and root axis based on the dental arch line used to obtain the optimal fusion position. In addition, the authors proposed a semi-interactive visualization method of implant parameters that be automatically simulated by the authors' method. If the plan does not meet the doctor's requirements, the final implant plan can be fine-tuned to achieve the optimal effect.

A series of experimental results show that the method proposed in this paper greatly improves the feasibility and accuracy of the implant planning scheme, and the visualization method of planting parameters improves the planning efficiency and the friendliness of system use.

The proposed method can be applied to dental implant planning software to improve the communication efficiency between doctors, patients and technicians.

This study aims to explore the impact of carbon neutral announcements on “stock market value” of publicly listed companies in China.

The event study approach is adopted. Market, market-adjusted, Carhart four-factor model and a cross-sectional regression model are employed to examine the impacts of carbon neutral announcements on “stock market value” of Chinese companies based on data from 188 carbon neutral announcements.

Carbon neutral announcements positively impact Chinese shareholder value. Carbon neutral announcements at the strategic level have a more positive and significant impact on Chinese stock market value. Innovative carbon neutral announcements do not significantly cause Chinese stock market reactions. Companies have more positive and significant stock market reactions when the companies make carbon neutral announcements that reflect high supply chain network resilience and heterogeneity and strong supply chain network relationships.

The findings uncover the business value of carbon neutral activities and provide operations managers in developing countries insights into how to improve enterprises' market value by actively implementing carbon neutral activities.

This paper is the first trial to apply an event study to examine the relationship between carbon neutral announcements and Chinese stock market value from the perspective of announcement level and type and supply chain networks. This paper introduces corporate reputation theory and enriches the application of corporate reputation theory in the field of low-carbon environmental protections and supply chains.

This study aims to exploit Tobin’s Q model of investment to examine the relationship between corporate governance and green innovation.

The study is based on a sample of 3,896 firms from 2002 to 2021, covering 45 countries worldwide. The authors adopt Tobin’s Q model to conceptualize the relationship between corporate governance and investment in green research and development (R&D). The authors argue that agency costs and financial market frictions affect corporate investment and are fundamental factors in R&D activities. By limiting agency conflicts, effective governance favors efficiency, facilitates access to external financing and encourages green innovation. The authors analyzed the causal effect by using the system-generalized method of moments (system-GMM).

The results reveal that the better the corporate governance, the more the firm invests in green R&D. A 1%-point increase in the corporate governance ratings leads to an increase in green R&D expenses to the total asset ratio of about 0.77 percentage points. In addition, an increase in the score of each dimension (strategy, management and shareholder) of corporate governance results in an increase in the probability of green product innovation. Finally, green innovation is positively related to firm environmental performance, including emission reduction and resource use efficiency.

The findings provide implications to support managers and policymakers on how to improve sustainability through corporate governance. Governance mechanisms will help resolve agency problems and, in turn, encourage green innovation.

Understanding the impact of corporate governance on green innovation may help firms combat climate change, a crucial societal concern. The present study helps achieve one of the precious UN’s sustainable development goals: Goal 13 on climate action.

This study goes beyond previous research by adopting Tobin’s Q model to examine the relationship between corporate governance and green R&D investment. Overall, the results suggest that effective corporate governance is necessary for environmental efficiency.