Bindu Chhabra and Pallavi Pandey
Drawing upon the conservation of resource (COR) theory, the purpose of this paper is to explore the mediating role of knowledge hiding in the relationship between job insecurity…
Abstract
Purpose
Drawing upon the conservation of resource (COR) theory, the purpose of this paper is to explore the mediating role of knowledge hiding in the relationship between job insecurity and two dimensions of thriving at work, i.e. learning and vitality. The study further aims to investigate the moderating role of benevolent leadership in the aforementioned mediating relationship by applying the moderated mediation framework.
Design/methodology/approach
The sample for the study consisted of employees working in service sector in India. The hypotheses were tested with two wave survey data collected from 365 employees during the COVID-19 pandemic when the Indian Government was lifting phase wise restrictions. Data was analyzed using mediation and moderated mediation analyses on PROCESS v 3.0 macro.
Findings
Results showed that knowledge hiding mediated the relationship between job insecurity and both dimensions of thriving at work. Further, benevolent leadership was seen to moderate the mediated relationship providing support for the moderated mediation framework.
Practical implications
The results highlight the significance of providing benevolent leadership training to the managers to help them cope with the anxiety arising out of job insecurity. Further, employees need to be cautioned regarding the deleterious effects of knowledge hiding, which can impede their own learning and vitality.
Originality/value
To the best of the authors’ knowledge, this is the first study to investigate the mediating role of knowledge hiding in the relationship between job insecurity and thriving. Further, the role played by benevolent leadership in mitigating the harmful effects of job insecurity especially during COVID-19 pandemic is a unique contribution of the study.
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Pallavi Pandey, Saumya Singh and Pramod Pathak
Research investigating turnover intention among frontline employees in the Indian retail industry is scarce. The purpose of this paper is to explore factors affecting withdrawal…
Abstract
Purpose
Research investigating turnover intention among frontline employees in the Indian retail industry is scarce. The purpose of this paper is to explore factors affecting withdrawal cognitions among front-end retail employees in India.
Design/methodology/approach
Semi-structured interviews were conducted to explore the factors responsible for developing turnover intentions among the front-end employees. Data were analyzed using the ground theory approach.
Findings
Qualitative investigation revealed nine factors (abusive supervision, favoritism, perceived job image, insufficient pay, work exhaustion, perceived unethical climate, organization culture shock, staff shortage and job dissatisfaction) are responsible for developing turnover intention among front-end employees in the Indian retail industry.
Originality/value
The study uncovers antecedents of turnover intention among front-end employees in the relatively neglected Indian retail sector through a qualitative technique. Theoretical contributions, managerial implications, limitations and direction for future research are discussed.
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Pallavi Ghanshyala Vyas and Satish Pandey
The purpose of this study is to investigate the relationship of social networking sites (SNSs) use, bridging social capital (BSC) and job satisfaction (JS) with knowledge sharing…
Abstract
Purpose
The purpose of this study is to investigate the relationship of social networking sites (SNSs) use, bridging social capital (BSC) and job satisfaction (JS) with knowledge sharing (KS) of employees. With the advent of social media and its technologies, it becomes opportune for organizations and practitioners to understand if the technology has usefulness for its employees.
Design/methodology/approach
After a thorough literature review, a research model was proposed and tested to identify the possible relationship between the variables. The results were validated using appropriate research tools such as hierarchical regression.
Findings
SNS use, BSC and JS were found to be positively associated with KS and the three variables together influenced KS more favorably. However, there was no significant association of SNS use with JS and BSC of employees, unlike past research conducted in the context of different countries.
Research limitations/implications
The authors identified the workplace implications of SNSs use in enabling KS and also the positive impact of losing network ties and JS of employees in enhancing KS.
Practical implications
These findings can provide insight to managers on the importance of SNSs and the formation of lose – tie networks for aiding in KS.
Originality/value
The study is the first to explore the BSC dimension in the context of SNS use and KS and propose a model to identify the association between SNS use, JS, BSC and KS in a single study.
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Durgesh Agnihotri, Kushagra Kulshreshtha, Vikas Tripathi and Pallavi Chaturvedi
The study aims to examine the customers' revisit intention toward the green restaurants after service failure based upon service failure attributions. The study further intends to…
Abstract
Purpose
The study aims to examine the customers' revisit intention toward the green restaurants after service failure based upon service failure attributions. The study further intends to investigate the moderating effect of green self-identity on customers' post-service failure behavioral intentions.
Design/methodology/approach
A self-administered questionnaire was distributed to 327 participants who had experienced service failure while dining in green restaurants. The study draws upon the prevailing literature to examine the relationship among the constructs using structural equation modeling (SEM).
Findings
The findings of the study have confirmed that service failure has an adverse effect on customers' revisit intention toward the green restaurants. However, customers with green self-identity appear less anxious about service failure as findings indicate customers revisit green restaurant even after service failure.
Practical implications
The study provides a clear indication to the managers of the green restaurants that a better understanding of service failure attributions may facilitate in preventing service failure in a prompt and reasonable manner. It will not only contribute to building the brand reputation, but also ensure that customers stay with the brand for a longer duration.
Originality/value
The study is unique in a way that it is the first of its type to establish a relationship between service failure attributions and customer satisfaction in the emerging South Asian market, such as India in the context of green restaurants. Besides, this is the only study to use green self-identity as a moderator between the relationships of customer satisfaction and revisit intention.
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Pallavi Datta, Sathiyaseelan Balasundaram, Rekha Hitha Aranha and Vijaya Chandran
The learning objectives are intended to stimulate the students’ comprehension of the various challenges faced by Indian startups in the digital ecosystem. With the changing…
Abstract
Learning outcomes
The learning objectives are intended to stimulate the students’ comprehension of the various challenges faced by Indian startups in the digital ecosystem. With the changing working dynamics in organizations around the globe, managers are expected to explore unconventional business models to facilitate operational growth. The case study is a valuable resource for graduate students to enhance and evolve their critical thinking and solution-oriented skills as forthcoming managers of digital businesses. Students should be able to analyze the case, respond to the questions and evaluate the consequences of workplace flexibility, moonlighting and its applicability in an organizational context. With the Indian Government introducing schemes such as the Digital India initiative and Startup India, it is predicted that numerous startups will opt for digital business standards and a remote work approach. The case bridges classroom theories and a real-life digital company to help students connect with emerging market scenarios.
Case overview/synopsis
During the digital era, India witnessed a shift in companies’ work culture, which amplified when COVID-19 hit the country. Organizations started to work remotely and experienced the numerous benefits it brought. The comfort of working from home was greater for digital businesses whose significant operations could be performed online. However, is it really that productive for digital companies to telecommute? The case illustrates how a digital company, Career Pandit, formed in 2018, unfurls and expands its business and further highlights the challenges the pandemic raised concerning people management. In addition to the discussion, the purpose of the case is to determine the implication of workplace flexibility and moonlighting and how Indian startups cope with the uncertain future challenges it brings.
Complexity academic level
Under graduate and postgraduate students.
Supplementary materials
Teaching notes are available for educators only.
Subject code
CSS 6: Human Resource Management.
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Pallavi Srivastava, Trishna Sehgal, Ritika Jain, Puneet Kaur and Anushree Luukela-Tandon
The study directs attention to the psychological conditions experienced and knowledge management practices leveraged by faculty in higher education institutes (HEIs) to cope with…
Abstract
Purpose
The study directs attention to the psychological conditions experienced and knowledge management practices leveraged by faculty in higher education institutes (HEIs) to cope with the shift to emergency remote teaching caused by the COVID-19 pandemic. By focusing attention on faculty experiences during this transition, this study aims to examine an under-investigated effect of the pandemic in the Indian context.
Design/methodology/approach
Interpretative phenomenological analysis is used to analyze the data gathered in two waves through 40 in-depth interviews with 20 faculty members based in India over a year. The data were analyzed deductively using Kahn’s framework of engagement and robust coding protocols.
Findings
Eight subthemes across three psychological conditions (meaningfulness, availability and safety) were developed to discourse faculty experiences and challenges with emergency remote teaching related to their learning, identity, leveraged resources and support received from their employing educational institutes. The findings also present the coping strategies and knowledge management-related practices that the faculty used to adjust to each discussed challenge.
Originality/value
The study uses a longitudinal design and phenomenology as the analytical method, which offers a significant methodological contribution to the extant literature. Further, the study’s use of Kahn’s model to examine the faculty members’ transitions to emergency remote teaching in India offers novel insights into the COVID-19 pandemic’s effect on educational institutes in an under-investigated context.
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Pallawi Baldeo Sangode and Sujit G. Metre
The purpose of this paper is to identify various risks in the power distribution supply chain and further to prioritize the risk variables and propose a model to the power…
Abstract
Purpose
The purpose of this paper is to identify various risks in the power distribution supply chain and further to prioritize the risk variables and propose a model to the power distribution industry for managing the interruptions in its supply chain. To accomplish this objective, a case of a major power distribution company has been considered.
Design/methodology/approach
Failure mode and effects analysis (FMEA) analysis has been done to identify the potential failure modes, their severity, and occurrence and detection scores. Then an interpretive structural model (ISM) has been developed to identify and understand the interrelationships among these enablers followed by MICMAC analysis, to classify the risk variables in four quadrants based on their driving and dependency powers.
Findings
The results of this study exhibit that technical failure in the information and technology system, the use of improper equipment, poor maintenance and housekeeping in the internal operations are the major risk drivers. Exposure to live wires and commercial loss in power supply has strong dependence power.
Research limitations/implications
This study is limited to a single power distribution company and not the whole power distribution sector.
Practical implications
This study suggests the managers of the power distribution company develop an initial understanding of the drivers and the dependent powers on the supply chain risks.
Social implications
Through prioritization, identification of drivers and the dependent risks, the losses in the power distribution supply chain can be minimized.
Originality/value
Various failures in the power distribution have been studied in the past, but they have not investigated the supply chain risks in the power distribution of a power distribution company.
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Laxmi Pandit Vishwakarma and Rajesh Kumar Singh
Introduction: Artificial intelligence (AI) is being extensively used to solve complex problems in the industry. AI provides several benefits such as providing visibility in the…
Abstract
Introduction: Artificial intelligence (AI) is being extensively used to solve complex problems in the industry. AI provides several benefits such as providing visibility in the processes, reducing time, improving accuracy, saving time, helping in the decision-making process, etc. Due to the range of benefits of AI technologies, organisations readily adopt this technology. However, there are several challenges that the organisation faces during the implementation of AI. These challenges are in context to human resource (HR) development for successful implementation of AI across different functions and are discussed in this chapter.
Purpose: Although we know that AI technology is widely accepted in human resource management (HRM) due to its various benefits. But the organisations face many challenges during the implementation of AI. The focus of the study is to explore the literature on AI in HRM, identify the challenges of implementing AI and provide potential future research direction based on a systematic literature review.
Methodology: To explore the literature on AI in HRM, the study undertakes a systematic literature review. The study identifies, analyse and classifies the literature to provide a holistic view of HR challenges in implementing AI. The study is built on a review of 47 documents, including the articles, book chapters and conference papers using the Scopus database for the past 10 years (2012–27 January 2022).
Findings: The study provides an overview of the documents published in Scopus in this area through a systematic literature review. The study reveals that a significant amount of growth in the publication has been shown in the past 10 years. The maximum and continuous growth is shown after 2017. The maximum number of papers are published in India, the USA and China. The study identifies major eight challenges of AI implementation in HRM. The study also provides a secondary case to deep dive in this area based on a systematic literature review.
Research Limitation/Implication: The challenges identified in the study are not empirically tested. Each of the identified challenges should be empirically examined. This study has expanded the body of knowledge of AI in HRM. This study will help the academicians and practitioners work on the identified challenges and help the organisations ease in adopting AI.
Originality/Value: This study represents the first work that integrates AI implementation challenges in HRM.
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Adriana AnaMaria Davidescu and Eduard Mihai Manta
Purpose: The study’s objective is to look at the link between money laundering and economic and financial performance, emphasising the effectiveness of the literature and possible…
Abstract
Purpose: The study’s objective is to look at the link between money laundering and economic and financial performance, emphasising the effectiveness of the literature and possible later research directions using science mapping, which allows for scientific knowledge analysis.
Need for the Study: This study is related to a better understanding of the field’s historical evolution in terms of publications.
Methodology: This study used bibliometric approaches to analyse a sample of 660 studies from the Web of Science between 1994 and 2022, concentrating on keywords, author, paper, journal, and subject analysis. This study focused on performance analysis and scientific mapping of articles using the R package.
Findings: The empirical results indicated that the research field’s primary issues include corporate governance, fraud, machine learning, fraud detection, financial fraud, financial statement, corruption, earnings management, ethics, governance, financial reporting, bankruptcy, internal control, or performance. M. S. Beasly, D. B. Farber, E. M. Fich, R. Romano, and A. Shivdasani are the most well-known authors on the issue of money laundering and financial and economic performance. At the same time, the most typical journals are the Journal of Business Ethics, Journal of Money Laundering Control, Accounting Review, Journal of Financial Economics, and Journal of Corporate Finance.
Practical Implications: This study will act as a guide for researchers of various fields to evaluate the development of scientific publications in a particular theme over time, especially for those who are in the field of money laundering and financial performance.
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Shivani Agarwal, Apoorv Gupta and Puja Roshani
Introduction: Artificial intelligence (AI) has now become an integral part of every aspect of the corporate sector. AI may be a massive branch of computing connected to building…
Abstract
Introduction: Artificial intelligence (AI) has now become an integral part of every aspect of the corporate sector. AI may be a massive branch of computing connected to building devices smart enough and capable of performing tasks that usually require human intelligence. Integrating AI with human resources (HR) practices will improve organisations, as these applications can analyse, predict, and diagnose to support HR teams for taking better decisions.
Purpose: This chapter throws light upon the current scenario of awareness of AI and machine learning (ML) and their impact on the industry of HR. This chapter tries to describe the usage of AI in our current world and the impact of AI in the field of HRM in organisations.
Methodology: The true possibility of AI and ML in HRM has been analysed with the help of pie charts, bar charts, and histograms with the segmenting of results and interpretations. Various frequently asked questions have been answered, and a sample population has also been surveyed on their viewpoints regarding specific areas.
Findings: This chapter concludes that HR experts see the best potential in analytics, attendance, recruitment, attendance management, and compensation/payroll. AI will significantly diversify the HR sector. HR professionals need to think outside of their function.