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Social media use is prevalent today, but there is a possibility that it might go out of control and cause negative consequences. Furthermore, by using social media at work, businesses may develop their networks, communicate in a productive manner and ultimately expand the efficiency. The purpose of this study is to investigate the effect of social media use (SMU) on job performance (JP) through sequential mediators such as social capital dimensions (SC), self-efficacy (SE), job satisfaction (JS) and knowledge sharing (KS) in Indian Public Universities.

Serial mediation model has been used in the study to analyse the relationship. Data is collected from teaching faculty (n = 702) who use social media in Indian public universities. The study has assessed the association between variables using structural equation modelling.

The findings suggest that the dimensions of SC, SE, JS and KS sequentially mediated the effect of SMU on JP. In light of the results, the SMU specifies prerequisites for the development of various dimensions of SC. Similarly, the rest of the mediating constructs further affect the other constructs, which ultimately positively affect JP. The final result shows that the indirect effect between social media use and job performance is positive and significant.

The study provides practical suggestions for university administration regarding the use of social media for teaching faculty.

No research has been done regarding social media use affecting the job performance of teaching faculty through serial mediation in public universities. In this respect, this study represents an original attempt to conduct such research.

In the context of green development in China, the circumstance in which Environmental, Social and Governance (ESG) ratings function has changed. As an important external governance mechanism of sustainable development, ESG ratings can also be a two-edged sword for the implementation of carbon emission reduction. This research examines the connection of ESG ratings and corporate carbon emission reduction in the context of green development. This present study postulates that the impact of ESG ratings on carbon emission reduction performance in the context of green development is inverted U-shaped.

To obtain empirical evidence for the hypotheses proposed, this study makes an empirical test based on the two-way fixed effects model. The data is taken from listed Chinese manufacturing firms between 2012 and 2021.

The study reveals that there is a significant inverted U-shape relationship between ESG ratings and carbon emission reduction performance in the context of green development. Managerial myopic behaviour plays a positive moderating role in the above relationship. In addition, it makes the inflection point of inverted U-shaped curve move to left. Heterogeneity analyses show that the above inverted U-shaped relationship is more significant for firms that don’t hire CEO with environmental protection background or big four accounting firms.

In the background of green development, this study helps to understand dual influence of ESG ratings on corporate carbon emission reduction deeply. It is beneficial to guide enterprises to utilize ESG ratings mechanism reasonably, thus enhancing the effectiveness of carbon emission reduction. This study provides decision-making reference for government to accelerate low-carbon transformation in microcosmic field.

Several chaotic system-based encryption techniques have been presented in recent years to protect digital images using cryptography. The challenges of key distribution and administration make symmetric encryption difficult. The purpose of this paper is to address these concerns, the novel hybrid partial differential elliptical Rubik’s cube algorithm is developed in this study as an asymmetric image encryption approach. This novel algorithm generates a random weighted matrix, and uses the masking method on image pixels with Rubik’s cube principle. Security analysis has been conducted, it enhances and increases the reliability of the proposed algorithm against a variety of attacks including statistical and differential attacks.

In this light, a differential elliptical model is designed with two phases for image encryption and decryption. A modified image is achieved by rotating and mixing intensities of rows and columns with a masking matrix derived from the key generation technique using a unique approach based on the elliptic curve and Rubik’s cube principle.

To evaluate the security level, the proposed algorithm is tested with statistical and differential attacks on a different set of test images with peak signal-to-noise ratio, unified average changed intensity and number of pixel change rate performance metrics. These results proved that the proposed image encryption method is completely reliable and enhances image security during transmission.

The elliptic curve–based encryption is hard to break by hackers and adding a Rubik’s cube principle makes it even more complex and nearly impossible to decode. The proposed method provides reduced key size.

In recent years, there has been significant interest in adopting XR (extended reality) technologies such as VR (virtual reality) and AR (augmented reality), particularly in retail. However, extending activities through reality-mediation is still mostly believed to offer an inferior experience due to their shortcomings in usability, wearability, graphical fidelity, etc. This study aims to address the research gap by experimentally examining the acceptance of metaverse shopping.

This study conducts a 2 (VR: with vs. without) × 2 (AR: with vs. without) between-subjects laboratory experiment involving 157 participants in simulated daily shopping environments. This study builds a physical brick-and-mortar store at the campus and stocked it with approximately 600 products with accompanying product information and pricing. The XR devices and a 3D laser scanner were used in constructing the three XR shopping conditions.

Results indicate that XR can offer an experience comparable to, or even surpassing, traditional shopping in terms of its instrumental and hedonic aspects, regardless of a slightly reduced perception of usability. AR negatively affected perceived ease of use, while VR significantly increased perceived enjoyment. It is surprising that the lower perceived ease of use appeared to be disconnected from the attitude toward metaverse shopping.

This study provides important experimental evidence on the acceptance of XR shopping, and the finding that low perceived ease of use may not always be detrimental adds to the theory of technology adoption as a whole. Additionally, it provides an important reference point for future randomized controlled studies exploring the effects of technology on adoption.

This study aims to examine whether companies adopt digital platforms for corporate whistleblowing systems (CWSs), as more substantive corporate social responsibility (CSR) initiatives, by following the existing practices of their industry peers (competitive pressure) and/or geographical location peers (legitimacy pressure).

This study identifies 446 focal companies in the European Economic Area that introduced new CWSs during 2017–2021. Then, the peers are defined as companies with existing CWS practices that are similar in size to each focal company. Using a quantitative approach, this study uses a logistic regression model.

This study finds that companies are more likely to adopt digital CWS if their country peers (not, industry peers) have done so, especially the ones operated in countries where governments build CSR partnerships with companies through cooperative consensus. However, the role of country peers is less prominent when companies have CSR committees.

This study shows the importance of country norms over competitive pressure in CSR. Nevertheless, the results offer additional insights for policy-makers by showing that country regulations mandating CWSs are not significant in promoting the adoption of digital CWS nor reducing the role of country peers.

Providing CWSs with digital platforms may show corporate commitment to better preventing social misconduct and improving social responsibility.

While most literature focuses on the role of industry peers and/or community peers in a single-country setting, this study examines the role of country peers specifically on digitalization regarding CSR and governance.

This paper aims to explore how a new type of workplace training program can be created that truly enables participants to move from words to action. Recognizing the need to understand trainee–work environment dynamics the authors criticize training efforts that center on targeted learning events, instead highlighting the role of preparation and following up. In doing so, the authors tackle the lack of guidance practitioners experience when designing and implementing workplace training programs.

The authors present action research on a pilot workplace training program focused on wellbeing in an academic work setting. The data collection draws from the case study tradition. The authors collect data through interviews (21), field notes of participant observation (3 occasions), participant-produced written materials and a feedback survey.

The authors find that restorative practices, workplace mediation and reteaming enhance the participants’ perceptions of self-efficacy and agency. Throughout the training program, facilitators observe the dynamics of the situation and take part in discussions to encourage exploration and reflection. Thus, facilitators likely need a coaching mindset.

The theoretical contribution stems from an in-depth exploration of trainee–work environment dynamics and novel insights brought to workplace training from adjacent fields of research. The authors introduce a framework for planning participatory workplace training and organizational development programs, which answers a call from practitioners.

This study aimed to address a gap in subcontractor management by focusing on previously unexplored complexities surrounding subcontractor management in developing countries. While past studies concentrated on selection and relationships, this study delved into how effective subcontractor management impacts project success.

This study used the Bayesian Network analysis approach, through a meticulously developed questionnaire survey refined through a piloting stage involving experienced industry professionals. The survey was ultimately distributed among participants based in Accra, Ghana, resulting in a response rate of approximately 63%.

The research identified diverse components contributing to subcontractor disruptions, highlighted the necessity of a clear regulatory framework, emphasized the impact of financial and leadership assessments on performance, and underscored the crucial role of main contractors in Integrated Project and Labour Cost Management with Subcontractor Oversight and Coordination.

Previous studies have not considered the challenges subcontractors face in projects. This investigation bridges this gap from multiple perspectives, using Bayesian network analysis to enhance subcontractor management, thereby contributing to the successful completion of construction projects.

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

This study aims to examine the effect of supervisor developmental feedback on employee silence behaviour by developing a moderated mediation model. The model focuses on the mediating role of role breadth self-efficacy and high activated positive affect underpinning the relationship between supervisor developmental feedback and employee silence behaviour, and the moderating role of interdependent self-construal.

The two-wave survey was conducted among 265 employees. Structural equation modelling was conducted to test the mediation and moderation mediation hypotheses.

Results indicated that high activated positive affect mediated the negative relationship between supervisor developmental feedback and employee silence behaviour. The authors also found that interdependent self-construal moderated the relationship between supervisor developmental feedback and role breadth self-efficacy, as well as the indirect effect of supervisor developmental feedback on employee silence behaviour via role breadth self-efficacy.

This empirical study provides preliminary evidence of the mediating role of breadth self-efficacy and high activated positive affect in the negative relationship between supervisor developmental feedback and employee silence behaviour. The moderated mediation results further show that the mediation of role breadth self-efficacy between supervisor developmental feedback is contingent on individual interdependent self-construal, such that the mediation effect is significant among individuals with high interdependent self-construal, but the mediation effect of high activated positive effect is independent of individual interdependent self-construal. The findings further extend boundary conditions (interdependent self-construal) that may constrain the effect of supervisor developmental feedback on role breadth self-efficacy and high activated positive affect. The research makes considerable contributions to the cognitive-affective personality system theory by specifying the cognitive and affective mechanisms between supervisor developmental feedback and employee silence behaviour, as well as the boundary conditions.

By applying the American Customer Satisfaction Index (ACSI) model to virtual art exhibitions, this research aims to reveal insights into the factors impacting visitor satisfaction and electronic word-of-mouth (e-WOM). Furthermore, the investigation of exhibition promotion seeks to understand how external factors contribute to the overall visitor experience in virtual art exhibitions.

With advancements in virtual communication technology and the transformative impact of the COVID-19 pandemic in recent years, there has been a notable surge in the popularity of virtual art exhibitions based on the Internet. This study uses the ACSI model to examine visitor satisfaction and e-WOM in virtual art exhibitions. Additionally, it explores the influence of exhibition promotion on the ACSI model.

Key findings revealed that 1) both promotion efforts and e-WOM exhibited significant relationships with the ACSI model, and 2) most of the relationships within the ACSI model were consistent with previous research outcomes.

This study extends the ACSI model’s application to virtual art exhibitions, enhancing its relevance. Additionally, it addresses the knowledge gap concerning the direct impact of promotion on audience expectations and its relationship with the ACSI model in virtual art exhibitions. Furthermore, the research explores the influence of customer satisfaction on electronic word-of-mouth in exhibitions, offering valuable insights for exhibition evaluation systems. The study serves as a guide, providing data and models for researchers investigating virtual art exhibitions.