Search results

This study aims to analyze and discuss the impact of corporate social responsibility (CSR) on firms’ performance, as well as to examine the interplay between CSR and the economy, society and innovation.

This paper collects data from 420 manufacturing firms across various geographical regions in China. By using a structural equation model, the paper investigates the impact of CSR on enterprise innovation, customer management capability, market competitiveness (MC) and firm financial performance.

The findings demonstrate that CSR performance positively contributes to enhancing the level of enterprise innovation, as well as customer management capability and market competitiveness. Furthermore, it assists enterprises in improving market competitiveness and elevating customer management capabilities. Thus, CSR can have a positive effect on the firm financial performance.

The outcomes presented in this paper offer valuable evidence regarding the influence of implementing CSR on different aspects of enterprise performance and innovation. Moreover, it provides practical recommendations for enterprises seeking to transition towards low-carbon practices and upgrade their manufacturing industry.

Independent directors are important corporate decision participants and makers. Based on the Chinese cultural background, this paper interprets the listing order of independent directors as independent directors’ status, exploring their influence on the corporate research and development (R&D) behavior.

This paper studies A-share listed firms in China from 2008 to 2018 as the sample. The main method is ordinary least square (OLS) regression. We also use other methods to deal with endogenous problems, such as the firm fixed effect method, change model method, two-stage instrumental variable method, and Heckman two-stage method.

(1) Higher independent directors’ status attribute to more effective exertion of supervision and consultation function, and positively enhance the corporate R&D investment. The increase of the independent director’ status by one standard deviation will increase the R&D investment by 4.6%. (2) The above effect is more influential in firms with stronger traditional culture atmosphere, higher information opacity and higher performance volatility. (3) High-status independent directors promote R&D investment by improving the scientificity of R&D evaluation and reducing information asymmetry. (4) The enhancing effect of independent director’ status on R&D investment is positively associated with the firm’s patent output and market value.

This paper contributes to understanding the relationship between the independent directors’ status and their duty execution from an embedded cultural background perspective. The findings of the study enlighten the improvement of corporate governance efficiency and the healthy development of the capital market.

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.

The primary objective of this study is to understand the motivational process of the nurses who were engaged in COVID care and performed organizational citizenship behavior (OCB) without caring about their own lives. This study also aims to investigate the consequences of such OCB on life satisfaction when the situation continues for a longer period.

For the study’s first objective, an online cross-sectional survey was conducted on 236 critical care nurses from 18 states of India extending over the period from March 2021 to November 2021, when the country passed through the second wave of COVID-19 infection. For the second objective, a longitudinal study compared the life satisfaction level during and post-COVID by giving a one-year gap (November 2022).

The findings of this study reveal that during this COVID period, nurses were strongly performing OCB through their organizational and professional commitment, but one year later, they were identified with a low level of life satisfaction.

Research on nurses has already categorized the profession under high emotional labor. Research also reveals that an individual’s emotional labor strategy (deep acting or surface acting) determines job satisfaction. However, under the COVID situation, nurses have displayed an extraordinary level of OCB by placing their own life at risk. Analysis of this study indicates that the OCB within the nurses during the COVID period originated from their commitment, not from the emotional labor strategy, which they used to select as a coping mechanism. However, one year later, it has affected their mental health and lowered their life satisfaction.

Intimate partner violence (IPV) is a prevalent public health issue impacting women’s physical and mental health and psychosocial walks of life across cultures and societies. Despite this, many women continue to stay in such relationships. This study aims to examine, from a constructionist perspective, why women stay in abusive marriages and what factors prevent them from taking appropriate actions. Also, women’s experiences of surviving IPV were explored.

Using a descriptive qualitative research method, the authors recruited and interviewed 17 women from northern India. The data were analysed thematically.

The underlying themes that emerged in response to the research questions were the lack of family support, societal ideals, the culture of normalizing violence, fear, love and hope and emotional turmoil. The reason for women not to leave abusive marriages corresponds to the broader social constructions of marriage and women’s perceived positions in family and society.

Research on women’s decision to stay in abusive relationships is limited, especially from the Global South. This study generates fresh evidence on the subject matter, specifically from the Indian context. The study result contributes uniquely by approaching the problem of staying in an abusive relationship from a social constructionist perspective. This study has implications for policy and psychosocial interventions to bring progressive changes in the lives of women experiencing IPV.

Considering rapid digitalization development, this study examines the impacts of digital technology innovation on social responsibility in platform enterprises.

The study applies the event study method and cross-sectional regression analysis, taking 168 digital technology innovations for social responsibility issued by 88 listed platform enterprises from 2011 to 2022 to study the impact of digital technology innovations for social responsibility announcements of different announcement content and platform attributes on the stock market value of platform enterprises.

The results show that, first, the positive stock market reaction is produced on the same day as the digital technology innovation announcement. Second, the announcement of the platform’s public social responsibility and the announcement of co-innovation and radical innovation bring more positive stock market reactions. In addition, the announcements mentioned above issued by trading platforms bring more positive stock market reactions. Finally, the social responsibility attribution characteristics of the announcement did not have a significant differentiated impact on the stock market reaction.

Most scholars have studied digital technology innovation for social responsibility through modeling rather than second-hand data to empirically examine. This study uses second-hand data with the instrumental stakeholder theory to provide a new research perspective on platform social responsibility. In addition, in order to explore the different impacts of digital technology innovation on social responsibility, this study has classified digital technology innovation for social responsibility according to its social responsibility and digital technology innovation characteristics.

This study aims to explore the application scenarios of metaverse offices in organizations, including immersive work experiences, weak social networks and virtual meetings. Based on the exploration of this application scenario, this study discusses four levels of organizational change that will be brought about by the future metaverse office, such as the inter-enterprise ecological collaboration model, distributed autonomous organization, flexible leadership and individual belongingness. The metaverse office has some special advantages over traditional office models, but the metaverse office still raises some issues, such as privacy, security, addiction, equity and usability. These issues brake the widespread adoption of metaverse technologies. The study recommends that researchers take these issues into account in future metaverse research and development.

This study surveys the relevant literature by means of a literature review in order to analyze how metaverse technology can be applied to teleworking. Two databases including Web of Science (https://www.webofscience.com/) and Google Scholar (http://scholar.google.com) were selected for this study. Keywords such as “teleworking and metaverse” were used, and 18 publications were found to be relevant to the study. After excluding duplicates, less relevant and older literature, only 14 articles could be used as references for this study. Based on the exploration of this application scenario, this study discusses four levels of organizational change and issues that will be brought about by the metaverse office of the future.

It presents the application scenarios of the metaverse office in organizations, including immersive work experience, weak social networking and virtual meetings.

The pandemic triggers a desire for contactless working. The three main applications of the metaverse office also have a practical value which has been proven in some high-tech companies. It is foreseeable that an efficient, electronic and personalized office model will be enthusiastically adopted by society. Metaverse office will gradually step into people's view in the future.

The concept of the metaverse office has rarely been touched upon by theoretical research, although the technology is gradually becoming known. Even its application to teleworking has only recently been reached by some organizations.

In response to the challenge of reduced efficiency or failure of robot motion planning algorithms when faced with end-effector constraints, this study aims to propose a new constraint method to improve the performance of the sampling-based planner.

In this work, a constraint method (TC method) based on the idea of cross-sampling is proposed. This method uses the tangent space in the workspace to approximate the constrained manifold pattern and projects the entire sampling process into the workspace for constraint correction. This method avoids the need for extensive computational work involving multiple iterations of the Jacobi inverse matrix in the configuration space and retains the sampling properties of the sampling-based algorithm.

Simulation results demonstrate that the performance of the planner when using the TC method under the end-effector constraint surpasses that of other methods. Physical experiments further confirm that the TC-Planner does not cause excessive constraint errors that might lead to task failure. Moreover, field tests conducted on robots underscore the effectiveness of the TC-Planner, and its excellent performance, thereby advancing the autonomy of robots in power-line connection tasks.

This paper proposes a new constraint method combined with the rapid-exploring random trees algorithm to generate collision-free trajectories that satisfy the constraints for a high-dimensional robotic system under end-effector constraints. In a series of simulation and experimental tests, the planner using the TC method under end-effector constraints efficiently performs. Tests on a power distribution live-line operation robot also show that the TC method can greatly aid the robot in completing operation tasks with end-effector constraints. This helps robots to perform tasks with complex end-effector constraints such as grinding and welding more efficiently and autonomously.

Within the current institutional landscape, characterized by increased societal and governmental emphasis on environmental preservation, there is growing interest in the potential of digital transformation (DT) to advance the circular economy (CE). Nonetheless, the empirical substantiation of the connection between DT and CE remains limited. This study seeks to investigate the impact of DT on CE at the organizational level and examine how various institutional factors may shape this relationship within the Chinese context.

To scrutinize this association, we construct a research framework and formulate hypotheses drawing on institutional theory, obtaining panel data from 238 Chinese-listed high-tech manufacturing firms from 2006 to 2019. A regression analysis approach is adopted for the sample data.

Our regression analysis reveals a positive influence of DT on CE performance at the organizational level. Furthermore, our findings suggest that the strength of this relationship is bolstered in the presence of heightened regional institutional development and industry competition. Notably, we find no discernible effect of a firm’s political connections on the DT–CE performance nexus.

This study furnishes empirical evidence on the relationship between DT and CE performance. By elucidating the determinants of this relationship within the distinct context of Chinese institutions, our research offers theoretical and practical insights, thus laying the groundwork for subsequent investigations into this burgeoning area of inquiry.

The purpose of the study is to examine the efficiency of linear, nonlinear and artificial neural networks (ANNs), in predicting property prices.

The present study uses a dataset of 1,468 real estate transactions from 2020 to 2022, obtained from the Department of Property Taxes of Republic of Kosovo. Beginning with a fundamental linear regression model, the study tackles the question of overlooked nonlinearity, employing a similar strategy like Peterson and Flanagan (2009) and McCluskey et al. (2012), whereby ANN's predictions are incorporated as an additional regressor within the ordinary least squares (OLS) model.

The research findings underscore the superior fit of semi-log and double-log models over the OLS model, while the ANN model shows moderate performance, contrary to the conventional conviction of ANN's superior predictive power. This is notably divergent from the prevailing belief about ANN's superior predictive power, shedding light on the potential overestimation of ANN's efficacy.

The study accentuates the importance of embracing diverse models in property price prediction, debunking the notion of the ubiquitous applicability of ANN models. The research outcomes carry substantial ramifications for both scholars and professionals engaged in property valuation.

Distinctively, this research pioneers the comparative analysis of diverse models, including ANN, in the setting of a developing country's capital, hence providing a fresh perspective to their effectiveness in property price prediction.