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COVID-19 lockdown imposed by the government in India affected markets, factories, industries, construction sites, restaurants, transport services, etc. in which migrant workers were engaged. Migrant workers expected that after the imposition of the lockdown government will facilitate transportation facilities to their hometowns as they lost their jobs. But due to negligence from both the central and the state governments, neither transportation was arranged nor food, shelter or health facilities were arranged. This paper aims to investigate the causes of the death of migrant workers under the theoretical framework of negligence theory.

The authors have applied the content analysis method and collected 926 death cases of migrant workers from 28 Indian states. The researchers applied this technique as the newspapers in India are one of the largest and most useful sources to generate a report/record on migrant workers causes during the COVID-19 lockdown. During the lockdown period, due to lack of attention from the government, police atrocities, hunger and accidental cases increased which resulted in the death of migrant workers.

The finding of the study proves that during the first phase of COVID-19 lockdown the death cases of migrant workers increased due to negligence by the governments. The number of death cases of migrant workers has been analysed through applying negligence theory which included duty, breach, cause, in fact, proximate cause and harm which increased the death cases. It has been noticed that the central government without any prior notice-imposed lockdown all over India, in which all the states were not received any guidelines or communication which indicate what they have to do or how to handle the Covid-19 situation.

To the best of the authors’ knowledge, this is an original work of researchers which is basically based on negligence theory.

This study aims to understand the relationship between family incivility and employees' organisational citizenship behaviour. It also explores the mediating role of negative rumination and the moderating roles of workplace friendship and optimism.

To test the hypothesised relationships, 381 responses were collected from employees at two-time points. The hypothesised relationships were tested using process macros.

The results indicated that family incivility is negatively related to organisational citizenship behaviour and increases negative rumination. The study also established the mediating role of negative rumination in the relationship between family incivility and organisational citizenship behaviour. The study also supported the buffering role of workplace friendship and optimism in the relationship between family incivility and negative rumination.

The study findings extend the understanding of how a non-work stressor can influence employee behaviour in the organisation. The study findings provide valuable directions to mitigate family incivility's adverse effects and extend the existing body of knowledge.

The study is unique as it links family events to work outcomes. Only a few scholarly attempts were undertaken to understand the effect of family incivility on employees' work behaviours. By explaining the mechanism and conditions, the study has a unique value to the scholarship.

Data-driven marketing is a crucial part of digital transformation, revolutionising how businesses operate in emerging markets. By leveraging customer data, organisations can understand consumer behaviour, predict preferences and provide personalised experiences, contributing to sustainable growth with precision. However, navigating this landscape comes with its unique set of challenges.

This chapter guides readers through the intricacies of implementing data-driven marketing strategies, including data quality, privacy, ethics, data security and complex analytics models. The aim is to optimise marketing strategies, maintain ethical standards and build trust with customers within the framework of sustainable development.

The goal is to empower readers to leverage data-driven marketing for positive change in the ever-expanding domain of digital transformation for sustainable development in emerging markets.

Land value in urban areas in India is influenced by regulations, bylaws and the amenities associated with them. Planning interventions play a significant role in enhancing the quality of the neighbourhood, thereby resulting in a change in its value. Land is a distinct commodity due to its fixed location, and planning interventions are also specific to certain locations. Consequently, the factors influencing land value will vary across different areas. While recent literature has explored some determinants of land value individually, conducting a comprehensive study specific to each location would be more beneficial for making informed policy decisions. Therefore, this article aims to examine and identify the critical factors that impact the value of residential land in the National Capital Territory of Delhi, India.

The study employed a combination of semi-structured and structured interview methods to construct a Relative Importance Index (RII) and ascertain the critical determinants affecting residential land value. A sample of 36 experts, comprising property valuers, urban planners and real estate professionals operating within the National Capital Territory of Delhi, India, were selected using snowball sampling techniques. Subsequently, rank correlation and ANOVA methods were employed to evaluate the obtained results.

Location and stage of urban development are the most critical determinants in determining residential land values in the National Capital Territory of Delhi, India. The study identifies a total of 13 critical determinants.

A scenario planning approach can be developed to achieve an equitable distribution of values and land use entropy. A land value assessment model can also be developed to assist professional valuers.

There has been a lack of emphasis on assessing the impact of planning interventions and territorial regulation on land values in the context of Delhi. This study will contribute to policy decision-making by developing a rank list of planning-based determinants of land value.

The present research identifies and prioritizes the critical success factors (CSFs) for Lean 4.0 (L4.0) implementation in small and medium enterprises (SMEs). L4.0 integrates Lean principles with Industry 4.0 (I4.0) technologies, for instance wireless networks, Internet of things (IoT), big data, cloud computing (CC), etc., offering significant opportunities to enhance operational efficiency by reducing non-value-adding activities.

This research adopts the “Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL)” methodology to examine and assess the connections between CSFs for L4.0 implementation. Data were gathered from SMEs using qualitative and quantitative approaches to ensure comprehensive insights into the critical enablers of L4.0 adoption.

The study identifies Top Management Support and Commitment, Employee Training and Financial Capabilities as the most important CSFs for L4.0 adoption in SMEs. These factors significantly impact the adoption process, providing actionable insights for SME leaders to overcome challenges and optimize implementation strategies.

This study contributes to the growing knowledge of L4.0 by highlighting key CSFs relevant to SMEs, a sector often constrained by resources but crucial for economic development. The findings provide a practical roadmap for SME entrepreneurs to achieve operational excellence and competitiveness through effective L4.0 adoption.

Despite a significant rise in the adoption of online stock trading applications, the research on measuring and enhancing the service experience of customers is scarce. This paper aims to put forth a credible service performance measurement tool, APPQUAL, customized for stock trading applications.

The paper is based on a multi-method research using qualitative and quantitative research. Further, structural equation modeling is used to establish constructs for measuring service performance.

APPQUAL is conceived and built to measure the service performance of stock trading applications. The APPQUAL measures service performance based on five unique dimensions – Safety Accuracy, Performance, Support and Usability associated with the perceived e-service quality of stock trading applications.

This study extends measurement scales for service quality measurement for a relatively new service of online stock trading applications. The scales are adapted as well as built with the help of an iterative process. The methodology is in line with the previous academic research, and the new scales developed can lead to further extensions to scale for different services.

The APPQUAL tool developed as part of this study can be applied to assess service performance and perceived service quality of stock trading applications, which have leap frogged in terms of adoption but have also been met with criticism on poor customer experience. This study shall add to the body of knowledge of stock trading platforms to enhance service experience by targeting the right factors and underlying items. The efficacy and application of the tool have been demonstrated in this paper by applying it to Zerodha and Upstox, the two of the biggest online stock trading applications in India.

There is no research or tool available currently which focuses on the service quality of the new-age platform application of stock trading apps. This is especially glaring due to the large-scale adoption of these applications by Indian customers.