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The pandemic has severely affected sharing economy businesses specially ride-hailing services due to high levels of human-touch points. This research investigates the impact of COVID-19 infodemic, identification, and emotional support on intention to use ride-hailing. The authors further examine the moderating effects of internalization, compliance, social currency and informational support in the proposed conceptual model.

The data were collected from 412 respondents from Delhi in India, and hypothesized relationships were tested using hierarchical regression.

The results indicate that COVID-19 infodemic has a negative association with intention to use ride-hailing. Identification and emotional support show a positive association with intention to use ride-hailing. The results also support internalization and compliance as moderators between infodemic, identification and intention to use ride-hailing. Further, social currency and information support moderate the relationship between emotional support and intention to use.

This is the first research, which adds to the expanding literature on ride-hailing, especially during the post-pandemic period of “new normal”.

Big data and predictive analytics (BDPA) has received great attention in terms of its role in making business decisions. However, current knowledge on BDPA regarding how it might link organizational capabilities and organizational performance (OP) remains unclear. Drawing from the resource-based view, the purpose of this paper is to propose a model to examine how information technology (IT) deployment (i.e. strategic IT flexibility, business–BDPA partnership and business–BDPA alignment) and HR capabilities affect OP through BDPA.

To test the proposed hypotheses, structural equation modeling is applied on survey data collected from 159 Indian firms.

The results show that BDPA diffusion mediates the influence of IT deployment and HR capabilities on OP. In addition, there is a direct effect of IT deployment and HR capabilities on BDPA diffusion, which also has a direct relationship with OP.

Through this study, authors demonstrate that IT deployment and HR capabilities have an indirect impact on OP through BDPA diffusion.

One of the most decisive objectives of human resource management (HRM), essential for business performance, is to attract, maintain and engage a qualified workforce. This study aims to identify and prioritize the antecedents of employer branding, which are considered extremely important by potential applicants when they choose to join a particular employer.

The authors have adopted a popular multicriteria decision-making technique fuzzy analytical hierarchy process, to prioritize the identified antecedents. The modified Delphi techniques with the 22 experts have been conducted to validate the identified antecedents. Structured questionnaires were discussed, and their reliability was assessed using the expert’s opinion.

Results of this study indicate that potential applicants consider career advancement opportunities as the most important enabler that persuades them to join a particular employer. Future employees are also motivated to join if they are offered attractive compensation packages, which are distinct from competitors. Furthermore, corporate social responsibility is evolving as an antecedent of employer branding as potential candidates are attracted to employers who are socially responsible.

Employer branding can serve as a strategic HRM technique for any business seeking to attract, recruit, retain and involve outstanding employees, as the success of the organization is determined by how its image is built, communicated and promoted. This study provides insights for HR managers and practitioners who can think of developing an effective employer brand communication that offers a distinct and in-imitable image and reputation as an employer of choice.

This study is unique, as it offers meaningful visions to HR practitioners and experts for designing employer branding strategies for attracting potential applicants to join their organizations.

This study aims to investigate the determinants of cloud computing usage behavior by exploring trust, several trust antecedents, risk perceptions and the direct and mediating relationships of trust and perceived risk on the intention toward the behavior.

An online survey was administered to 1,228 cloud technology users. Using structural equation modeling, a proposed framework of 13 factors that have a direct and indirect influence on the usage behavior was introduced and tested.

It was observed that the intention toward the usage was influenced by trust and performance expectancy. Additionally, trust was affected by perceived accessibility and perceived technical support. The findings provided evidence on the diminished effect of perceived privacy and the insignificance of the mediating relationship of trust and perceived risk on the intention.

The study provides multiple implications for researchers by highlighting the concept of trust in this context and enriching their understanding of the relationship between risk and trust.

The research provides valuable guidelines for service providers toward introducing major concerns and the importance of dependable technical support.

This study contributes to the cloud computing literature by exploring the effect of perceived technical support on the usage and examining the relationship between trust and risk.