Search results

The purpose of this paper is to investigate if country development indicators, i.e. gross domestic product per capita (GDPPC), literacy rate, internet penetration and urban population, influence the generation of e-waste on a global level. The moderation effect due to differences between countries in terms of absence or presence of e-waste policy and level of development is also checked.

This is an archival study that builds upon data from United Nations (UN), World Bank and Global E-waste Statistics Partnership. The authors did a path analysis comprising mediation and multigroup analyses to decipher the proposed rese arch model containing data from 172 countries.

The results indicate that GDPPC, literacy rate, internet penetration and urban population do not directly influence the generation of e-waste. However, higher internet penetration in developing countries leads to higher e-waste, while higher literacy rates in developed countries suppress e-waste generation. When it comes to e-waste policy, a higher urban population without a regulatory legal framework boosts higher e-waste. The authors observed that higher internet penetration leads to higher e-waste in the presence of e-waste policy as well.

This is the first study to include economic well-being indicators in elaborating e-waste generation, on a global scale. No previous study has observed differences between countries nested in e-waste policy and level of development.

This study aims to, first, propose a valid and reliable scale to document the COVID-19 Pandemic Shopping Experience (CPSE) and, second, determine the impact of its variables on the postpurchase shopping experience (PPSE).

For scale development, published studies were scanned and the variables were shortlisted. These shortlisted variables were validated by 52 faculties from four universities in Saudi Arabia. Data were collected from 318 respondents to purify the CPSE Scale. In Study 2, a path analysis was performed on a sample of 354 respondents to determine the individual impact of each variable on PPSE.

A total of 14 items were found to be aligned under four variables, social distance (SD), shop hygiene, operational time and entertainment venues. SD was found to have the greatest influence on PPSE, followed by operational time and shop hygiene.

This research has important implications for retailers to initiate changes in store layout so that they can implement social distancing by physically marking stickers on the floors and by placing barricading on billing counters. Store hygiene can be ensured by making sanitizers and hand gloves available at the entry points, periodically cleaning the floor and sanitizing the premises. Rationing the operating time proved to be an effective tool to minimize the exposure time, thereby limiting consumers' time inside the store.

To the best of the authors’ knowledge, this is the first study to propose a full-scale measure of the customer shopping experience (SE) during a pandemic. This scale can be generalized to measure SE in similar situations.

The purpose of this paper is to determine the role of service quality (SQ), trust and commitment to customer loyalty (CL) for telecom service users. Further, the moderating role of gender, marital status and connection type within the model was tested.

A measurement model was created based on valid 615 responses from Indian TSUs for SQ, trust, commitment and loyalty with the help of partial least squares structural equation modeling (PLS-SEM). Multi-group analysis (MGA) was conducted to understand the moderating effect of marital status, gender and connection type within the model.

The results suggest that, out of five dimensions of SQ, only responsiveness, assurance and empathy have a significant positive relationship with both commitment and trust. Tangibility has a significant positive relationship with trust only. Both commitment and trust have a significant impact on loyalty. It was noticed that both commitment and trust act as mediators between three SQ dimensions (assurance, empathy and responsiveness) and CL. MGA revealed that empathy and responsiveness positively induce trust in telecom users who are single. Whereas, assurance increases commitment toward telecom service providers in married users. Assurance and empathy significantly contribute toward commitment and trust, respectively, in male users as compared to females. Empathy was found important for postpaid users for trust-building, whereas trust was found to be more important for prepaid users to stay loyal to the service provider.

This article contributes toward understanding the role of SQ, trust and commitment to CL moderated by marital status, gender and connection type in an integrated model concerning telecom service.

This study is the maiden attempt to understand the effect of specific human resource practices (HRPs) on employee retention (ER) with the mediation of job satisfaction (JS) and moderation of work experience (WE) and job hopping (JH) in the context of the textile industry.

This study adopted a quantitative methodology and applied quota sampling to gather data from employees (n = 365) of leading textile companies in India. The conceptual model and hypotheses were tested with the help of Partial Least Squares-Structural Equation Modelling (PLS-SEM).

The findings of a path analysis revealed that compensation and performance appraisal (CPA) have the highest impact on JS followed by employee work participation (EWP). On the other hand, EWP had the highest impact on ER followed by grievance handling (GRH). The study revealed that JS significantly mediates between HRPs like CPA and ER. During Multi-group analysis (MGA) it was found that the importance of EWP and health and safety (HAS) was more in employee groups with higher WE, but it was the opposite in the case of CPA. In the case of JH behavior, the study observed that EWP leads to JS in loyal employees. Similarly, JS led to ER, and the effect was more pronounced for loyal employees.

In the context of the Indian textile industry, this work is the first attempt to comprehend how HRPs affect ER. Secondly, it confirmed that JS is not a guaranteed mediator between HRPs and ER, it could act as an insignificant, partial or full mediator. Additionally, this study establishes the moderating effects of WE and JH in the model through multigroup analysis.

This exploratory study aims to discover the different forms of challenges encountered by school stakeholders, including students, teachers, parents and management due to the coronavirus disease 2019 (COVID-19) pandemic.

Qualitative methodology was deployed for the study. A purposive sampling technique was used to select the respondents for a semi-structured interview. Data were examined using interpretative phenomenological analysis (IPA).

It was found that each stakeholder faced four different challenges: mental distress, physical immobility, financial crunches and technological concerns. Findings suggest that teachers are experiencing higher financial, technological and physical challenges as compared to other stakeholders followed by parents.

This paper discusses the major challenges faced by each stakeholder along with the opportunities. These findings will be useful for educationists, regulatory authorities, policymakers and management of educational institutions in developing countries to revisit their policy frameworks to develop new strategies and processes for the smooth implementation of remote learning during a period of uncertainty.

Digital technologies emerged as innovative avenues for launching new products, advertising brands, increasing customer awareness and thus leaving a remarkable impact on the online marketplace. The present study analyzed the effects of crucial antecedents of AR interactive technology on customers' behavior toward AR-based e-commerce websites.

Convenience sampling was used to collect primary data from 357 iGen respondents aged 16–22 years; residing in New Delhi and the NCR region of India and examined using the structural equation modeling technique.

Results revealed that technology anxiety and virtuality significantly influence customers' attitudes and behavioral intentions toward AR-based e-commerce websites. However, interactivity and innovativeness remain non-significant. Additionally, non-significant moderating effects were identified for the moderators, i.e. trust and need for touch. At the same time, gender has a significant moderating effect only for the association between technology anxiety and attitude toward AR-based e-commerce websites.

The study summarizes numerous theoretical and managerial implications for AR-based website designers and policymakers, followed by the crucial limitations and directions for future research.

The present research provides a significant understanding of the e-commerce industry by providing valuable insights about young iGen consumers' perceptions of AR-based e-commerce websites.

Measuring service quality in online retail is critical. The purpose of this paper is to put in foreground key methodological issues of prevailing research related to scale development for the measurement of service quality in the context of online retail.

Content analysis of 30 research papers sourced from prestigious databases has been done to detect defects within research and sampling methods, survey administration, item generation and purification, dimensionality analysis, reliability and validity assessment. Also observations regarding dimensionality of online service quality constructs have been highlighted.

Study revealed deficiencies in sample size and composition, quantitative orientation in research methods, leniency in item generation/purification and negligent assessment of reliability and validity. It was found that e-service quality is multidimensional in nature and there is no consensus on number and nature of dimensions, although security/privacy, website design, reliability, responsiveness and information emerged as most cited dimensions. Electronic and traditional service quality dimensions displayed analogy in direct or adapted form.

This paper is first to highlight key methodological issues of prevailing research on e-service quality scale development in context of online retail. Implications for researchers and managers are summarized at the end of the study.

Introduction: The world is passing through a technology explosion phase where one technology is being replaced by another very quickly. Emerging technologies play more important roles in the insurance sector directly or indirectly. These technologies have a high potential to change the insurance paradigm.

Purpose: In this chapter, we discuss emerging technologies such as artificial intelligence (AI), big data, blockchain, the internet of things (IoT), mobile technology, predictive analytics, social media, telematics, chatbots, low codes, and drones in the context of the insurance industry.

Methodology: To carry out our analysis, we searched for data using the keywords for each technology from the Web of Science (WoS) coral database. Certain inclusion and exclusion criteria were followed to select the articles for further analysis. R-studio was used for the data analysis and visualisation.

Findings: It was found that the highest number of research articles published are related to big data, followed by AI and social media. The first article on AI in insurance appeared in 1975. Social media is the highest cited new technology, whereas the low codes are the undiscovered paradigm for the insurance sector with no published research. Research on the impact of chatbots, drones, and mobile technology in the insurance industry is still at a nascent stage. We also noticed that the United States is leading the research on emerging technologies in the insurance sector.

Implications: This chapter audits the emerging technologies in the insurance sector and identifies technological areas with the highest, least, or no research, dominant journals, authors, and countries. This holistic overview empowers managers and academicians to decide the future course of action.

This chapter presents the e-marketing practices followed by the micro, small and medium enterprises (MSMEs) in India. It explored the owner-managers perceptions of MSMEs regarding their average expenditures, budget allocations, management, policy, sources of information, return on investment and their desire for formal training on e-marketing activities in future. Data were collected from 253 MSME owner-managers through an e-questionnaire. The researchers found that the majority of the MSME owner-managers allocate a monthly budget for e-marketing initiatives, and they have increased it over the past few years. However, the total expenditure on e-marketing activities is between 1% and 10% of their total marketing budget. These businesses are partly or fully outsourcing search engine optimization (SEO), display advertising and referral marketing, whereas other e-marketing activities are managed in-house. Generally, these MSMEs are not measuring the success of their digital marketing efforts. If they do it, they are not doing it in a professional manner. MSMEs were found to be slow in posting content and engaging their followers on social media. Surprisingly, two-third of the MSMEs that participated in this study did not show any desire to pursue courses in digital marketing. In conclusion, this study puts forward key implications to practitioners as well as to the government agencies that are involved in the promotion of information technology among MSMEs.

Introduction: In a world characterised by volatility, uncertainty, complexity, and ambiguity, change is the only constant. Over the years, human resource management (HRM) has evolved from conventional functions of hiring and firing to being a strategic partner in organisations. Similarly, there has been a paradigm shift in the landscape of artificial intelligence (AI) from being a mere searching tool to the design and development of intelligent robots. Over the years, AI has emerged into a collection of powerful technologies re-inventing different functional areas, including HRM. The application of AI in HRM is perceived as an optimistic opportunity since it ought to bring maximum value at minimum cost. AI focuses on building tools that exhibit human-level intelligence and discernment in making decisions.

Purpose: The purpose of this chapter is to draw deeper insights into the relevance of AI in different functional areas of HRM. Integrating AI into HRM functions such as talent acquisition, training and development, performance management, employee engagement, and the like can help leverage efficiency and create an engaging employee experience. In the wake of Industry 4.0, where digitalisation has become imperative, this chapter explores the integration of AI into specific HR functions for a synergistic competitive advantage in companies. The purpose of this chapter is to signify the integration of AI into four vital functions of HRM, namely talent acquisition, training and development, performance management, and employee engagement. The objective is to chart how companies integrate various AI tools in four specific HRM functions to enhance efficiency. Also, the companies willing to implement AI in their HR functions can refer to the case studies used as exemplars in the chapter.

Methodology: This conceptual chapter is based on the secondary sources, which also build upon case studies of different companies that have implemented AI-enabled solutions and integrated them into different HRM functions and processes per needs. This chapter utilises the conceptual framework of both AI and HRM functions to give deeper insight into the challenges and implementation of technology-enabled solutions.

Findings: AI is used in HRM functions to automate repetitive and operational tasks to shift the focus to more strategic aspects. Despite many advantages of AI and machine learning, very few companies are using it, and companies may integrate technology-enabled solutions based on the size and nature of business.