Praveen Dhiman and Sangeeta Arora
Relying on social identity and social exchange perspectives, the present study aims to investigate the role of employee branding dimensions in stimulating employees’ brand…
Abstract
Purpose
Relying on social identity and social exchange perspectives, the present study aims to investigate the role of employee branding dimensions in stimulating employees’ brand citizenship behaviour (BCB) directly and indirectly through job satisfaction and affective brand commitment.
Design/methodology/approach
A field-survey method was used to target customer-contact employees of luxury chain hotels. Regression-based approach and bootstrap method (via PROCESS MACRO, Model 6) were applied to test the direct and indirect effects.
Findings
The results show that perceived external brand prestige has a strong direct effect on BCB. Through mediation analysis, this study observes that job satisfaction and affective brand commitment have significant mediation effects (i.e. individual, parallel and sequential) between employee branding dimensions and BCB. Analysing the results precisely, job satisfaction and affective brand commitment have the lowest sequential mediation effect and the greatest parallel mediation effect concerning the said relationships.
Originality/value
This study is novel in applying a three-path mediation model in the Indian hospitality context, considering a multi-dimensional perspective of employee branding to capture its diverse impact on BCB directly and indirectly through job satisfaction and affective brand commitment. Moreover, this study advances employee branding research by considering the under-investigated mediating (individual, parallel and sequential) role of job satisfaction and affective brand commitment.
Details
Keywords
Prasetyo Adi Nugroho, Nove E. Variant Anna and Noraini Ismail
This study sought to analyze the correlation between artificial intelligence (AI) and libraries and examine whether there were any shifts in research trends related to these two…
Abstract
Purpose
This study sought to analyze the correlation between artificial intelligence (AI) and libraries and examine whether there were any shifts in research trends related to these two topics during the coronavirus pandemic.
Design/methodology/approach
The study gathered secondary data from the Scopus website using the keywords “AI,” “library” and “repository,” from 1993 to 2022. Data were re-analyzed using the bibliometric software VOSviewer to examine the trending country's keyword relations and appearance and Biblioshiny to study the publication metadata.
Findings
Index keywords, such as “human,” “deep learning,” “machine learning,” “surveys” and “open-source software,” became popular during 2020, being closely related to digital libraries. Additionally, the annual scientific production of papers increased significantly in 2021. Words related to data mining also had the most significant growth from 2019 to 2022 because of the importance of data mining for library services during the pandemic.
Practical implications
This study provides insight for librarians for the implementation of AI to support repositories during the pandemic. Librarians can learn how to maximize the AI-based repository services in academic libraries during the pandemic. Furthermore, academic libraries can create policies for repository services using AI.
Social implications
This study can lead researchers, academicians and practitioners in conducting research on AI in library repositories.
Originality/value
As research on AI and digital repositories remains limited, the study identifies themes and highlights the knowledge gap existing in the field.