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The purpose of this paper is to identify embedded communities among Medical Ethics scholars in France based on their position and strength of association in the social networks they form.

The author constructed a co-authorship network by linking two authors if they co-authored a paper. Once the co-authorship network was constructed, the author investigated the entire network quantitatively using standard research methods known as social network analysis. The author’s mechanism of community detection was via identification, i.e. communities were user-defined based on topological analysis.

The study identified that communities formed by trust (bonding or repeat connections) or by prestige (connection of well-connected scholars with those that are already well-connected) overlap each other, suggesting that trust and prestige may go hand in hand in sustaining communities. Structural holes within trust networks indicated that some actors played more of a broker role than did other actors.

The study uses Web of Science field based category to extract data. Although thorough cleaning of data has been performed, author disambiguation over a three decade period remains a limitation.

Although there have been numerous studies on mapping co-authorship networks, there has been limited work investigating the underlying communities formed by author associations. The results of this study should be of immense benefit to those studying the science of science and S&T policy.

Acknowledging the significance of perceived organizational support (POS) for employees’ performance, this study aims to examine the underlying mechanism of task performance in a COVID-19 pandemic-induced blended working (TPBW) environment and the role of perceived usefulness of digitalization (PUDBW) in the process.

Survey data collected from 204 managers of Indian public sector undertakings pursuing blended working for the first time were analyzed using structural equation modelling. A qualitative study on 31 such managers was also performed.

Although employees perceived an improvement in POS, PUDBW and TPBW (during the COVID pandemic) in comparison to the pre-COVID time when traditional work design was operational, yet the improvement in task performance was not directly influenced by POS. POS had a positive effect on PUDBW, which in turn positively affected TPBW. PUD acted as a mediator. A negative moderation effect of POS on the relationship between PUDBW and TPBW was found.

Findings of the study may help organizations and policymakers to focus on key enablers, such as organizational support and relevant digital initiatives, for ensuring better task performance by their employees during a blended working environment, even in difficult times as the COVID-19 pandemic.

This study, for the first time, examined the proposed relationships in a new work setting of blended working and explained the underlying mediation and moderation mechanisms in their relationships.

This study examines the role of Big Five personality traits namely openness to experience, conscientiousness, extraversion, agreeableness and neuroticism in regulatory-focused job crafting, i.e. promotion- and prevention-focused job crafting and their inter-relationships.

Survey data collected from 444 executives of Indian public sector energy companies were analysed using structural equation modelling.

Big Five personality traits differentially influence individuals' ways of managing job demands through promotion- and prevention-focused job crafting. These influences are easily identifiable in case of openness to experience, conscientiousness and neuroticism.

Findings of the study may help organizations in developing an effective recruitment, job designing and job allocation process, devise a framework for uncertainty management, encourage their employees to undertake personality-aligned job crafting to manage their ever-emerging jobs and enhance person–job fit.

This study, for the first time, provided a comparative influence of Big Five personality traits on both forms of regulatory-focused job crafting. These findings may be relevant for job demand management in a dynamic business environment.

This paper examines the relationships between regulatory-focused job crafting, i.e. promotion- and prevention-focused job crafting, person-job fit and internal employability and explores the direct and underlying mediation process using conservation of resources and job demands-resources theories.

Survey data collected from 425 executives of India based public sector enterprises were used to test hypotheses.

Promotion- and prevention-focused job crafting respectively had a contrasting relationship with needs-supplies fit. The relationship with demands-abilities fit was statistically significant only in the case of prevention-focused job crafting. These two job crafting forms respectively had a positive and a negative effect on internal employability, both directly as well as indirectly through person-job fit.

Employees can pursue promotion-focused job crafting and avoid prevention-focused job crafting to improve their person-job fit as well as internal employability which subsequently may have multiple favourable outcomes at an organizational and individual level.

The study, for the first time, empirically investigates the differential role of individuals' efforts in the form of promotion- and prevention-focused job crafting, in influencing internal employability and explains its underlying mechanism through person-job fit. These interrelationships may have important implications for employees' job demand management process and job choices.

This paper aims to identify key theoretical cornerstones and research trends in the apparel industry. It also compares theoretical bases with those of the general research domain in technology adoption literature and, thus, provides future policy guidelines for practitioners and research gaps for further studies.

Documents were collected from the Web of Science (core collection) database using systematic methods. The bibliometric coupling and co-citation analyses were conducted using VOSviewer software to construct theoretical cornerstones and research trends in the apparel industry.

Literature in the apparel industry focuses mainly on the diffusion of innovation and the theory of reasoned action. Hence, the literature lacks investigations of technology–organization–environment and institutional theories for technology adoption in the apparel industry. This study also traces six clusters of prevalent research trends: radiofrequency identification, virtual-try on technology for e-commerce, computer-aided design, Industry 4.0 technologies, virtual-try on technology in design and information technology.

Little research is done on theoretical cornerstones on technology adoption in the apparel industry. This study looks into the theoretical bases for technology adoption, research trends in the apparel supply chain and calls for future research necessities.

This paper aims to evaluate the impact of automation on job displacement and reshoring in the apparel industry. It also compares with predictions on the same subject matter by the existing literature and, thus, provides future research agenda for further studies.

Primary data were collected through 27 semi-structured in-depth interviews. The grounded theory was used for thematic and network analyzes, which traced the drivers and barriers, as well as the impact of automation and reshoring.

Initially, automation decreases human interactions in any specific production section. However, it increases productivity, quality and cost advantages, which invoke growth and further employment in clothing firms. The employment of unskilled workers decreases in the long run when automation is well adopted in the system. Automation does not stimulate reshoring but may support relocation initiatives of production sites around the centers of global value chains (GVCs). This GVC-based relocation may create job displacement in apparel manufacturing nations in Asia while bringing employment opportunities to Sub-Saharan African countries, Europe and North America.

Little empirical research has been conducted on the impact of automation on the apparel industry. This study predicts that human interventions will dominate the sewing of fashionable and sophisticated apparel products while automation may replace many human workers for basic garment items in the foreseeable future.

The outset of the COVID-19 pandemic caused disruptions of all forms in the supply chain globally for almost two and a half years. This study identifies various challenges in the effective functioning of the existing supply chain during COVID-19. The focus is to see the disruptions impacting the energy storage supply chains.

The procedure entails a thorough analysis of scholarly literature pertaining to various supply chain interruptions, confirmed and verified by experts working in an energy storage company in India. These experts also confirmed the occurrence of more disruptive factors during their interviews and questionnaire survey. Moreover, this process attempts to filter out the relevant causal disruption factors in an energy storage company by using the integrated approach of qualitative and quantitative methodologies.

The results provide practical insights for the company management in planning and devising new strategies to manage supply chain disruptions. Supply chains for companies in other industry sectors can also benefit from the proposed framework and results in making them more robust to counter future disastrous events.

The study provides an easily adaptable decision framework to different industries by closely examining supply chain disruptions and identifying associated causes for building a robust supply chain focused on the energy storage sector. It examines four disruption dimensions and investigates possible outcomes and impacts of disruptions.

Cloud-based enterprise resource planning (ERP) enables an organization to pay for the services they need and removes the need to maintain information technology infrastructure. The purpose of this paper is to empirically test the role of cloud-based ERP services on the performance of an organization. Here, the performance is categorized as supply chain performance and organizational performance that comprises of financial performance and marketing performance. Contingent resource-based view (RBV) theory was used to develop a theoretical framework in which supply base complexity (SBC) acts as a moderating variable on the relationship between cloud ERP and the performance.

Contingent RBV theory is used to explain the relationship between all identified variables in this paper. Partial least squares (PLS) based on structural equation modeling (SEM) is used to empirically test our theoretical framework.

The PLS-SEM analysis of 154 respondents supports the contingent RBV theory. Six hypotheses – out of the eight hypotheses formulated in this paper – are supported by data.

Given this study was conducted in India where the potential of cloud ERP has not been fully implemented yet, the results may reflect more of perceived usefulness of this technology. The authors have attempted to understand the effect of SBC as a moderator in the relationship between cloud ERP and organizational performance which may not be the only moderator affecting this relationship among other potential moderators.

This paper empirically validates the theoretical framework based on the contingent RBV theory as it mitigates the static nature of the resource-based view approach suggested in the seminal article of Barney (1991).

This paper aims to examine the link between information systems (IS) agility, HR performance management systems and job satisfaction using organizational information processing theory. The objective of this study answers the following questions: How does use of different IS agility impact HR systems and job satisfaction? What are the connecting pathways by which IS agility affects HR systems and job satisfaction?

The authors developed a theoretical framework based on the organizational information processing theory and collected primary data through an online-based questionnaire. Following these procedures, the authors analyzed the data using structural equation modeling (SEM).

SEM analysis of the data from 150 respondents supports the organizational information processing theory. The authors proposed eight hypotheses, and only one was rejected.

The data were collected from South Africa only, which is an emerging economy, and these cross-sectional data were gathered from the perspectives of the respondents.

The present paper empirically tests the conceptual model through the lens of organizational information processing theory.

This study aims to find the level of gender-based assortativity in the association of researchers and investigate if gender has influence over social capital of researchers and their research performance in the context of a multi-ethnic nation, such as Malaysia.

Social network analysis is used as a primary research method to analyse the associations between the authors. Mann-Whitney test is used for testing the significant differences in research performance and social capital based on gender.

The assortative mixing patterns of 187 researchers revealed positive assortativity, meaning that more authors preferred to co-author with authors of their gender. No influence of gender was seen on the social capital of authors. However, gender did significantly influence the research productivity of authors.

This is one of the first studies that attempts to find the influence of gender on collaborative associations of researchers in Malaysia.