Deepak Halan

E-commerce is critical for managing increased customer demand and maintaining operational efficiency during disruptions such as natural disasters, health crises, and political instability. Despite this, little is known about how crisis-driven market changes influence dynamic capabilities, technology adoption, and customer experience (CX). This study provides insights into how e-tailers can leverage technology to enhance the CX for first-time online shoppers (FTOS). Given the limited literature on FTOS, which differs from repurchasers, three studies were conducted using a multi-method approach. Study 1 involved an environmental scan of 109 news articles and journal papers for practical insights. Study 2 consisted of in-depth interviews (IDIs) with senior managers working full-time for e-tailers, while Study 3 involved IDIs with FTOS. Findings reveal that e-tailers adapt to crises by leveraging technology to bridge demand–supply gaps through dynamic demand forecasting and improved last-mile delivery. They also use advanced technologies to provide personalised and immersive experiences, helping narrow the gap between offline and online shopping for FTOS. This study contributes to theory with a conceptual framework, with empirically grounded, theory-informed propositions linked to the Resource-Based Theory (RBT) and CXM frameworks, to explore how e-tailers leverage crisis-led capabilities to enhance FTOS experience. It conceptualises a new understanding of how e-tailers adapt to enhance FTOS CX amidst crises which can serve as a springboard for future research. The insights from an empirically grounded conceptual framework and propositions, offer managerial implications for e-tailers and other service providers.

The fashion industry is resource-intensive and causing pollution, waste, and resource depletion. Sustainable fashion arose to reduce these environmental and social harms. This study examines key factors that influence user satisfaction with sustainable fashion apps. Latent Dirichlet allocation topic modeling was applied to 84,188 user reviews of sustainable fashion apps on the Google Play Store. The analysis identifies ten key factors, including app performance, service experience, and shipping, that influence user satisfaction. These are linked to the Delone and McLean Information Systems success model to evaluate their impact on post-usage satisfaction through multiple regression analysis. The study presents a novel methodology that combines text mining and regression analysis, providing unique insights into user satisfaction with sustainable fashion apps. It improves sustainable fashion marketing literature and offers practical guidance for application development to boost user satisfaction.

With the growing complexities of the external environment and the increasing competition, it is becoming more important for firms to measure their success and impact. Marketing analytics is playing a key role in measuring and optimizing the success and impact of various marketing activities. This chapter explores the role of marketing analytics, from the initial data collection to advanced predictive insights stage. Diverse techniques, and applications have been discussed which organisations can use to evaluate the return on investment (ROI) apart from other key metrics. Marketing analytics enables businesses to decode very large quantities of data, optimize marketing efforts, and finally drive business growth. This chapter delves into the evolution of data mining and the different types of marketing data that can be data mined, while emphasising on big data. A number of businesses are using big data in predicting customer lifetime value (LTV) amongst other applications. Customer touchpoints are rich sources of data and their management is vital to improve customer relationships. This chapter also discusses various types of customer touchpoints and their better management and optimization. With the growing importance of social media, it is vital to examine customer-centric impact using sentiment analysis.

Green supply chain management (GSCM) focuses on embedding eco-conscious practices into conventional supply chain processes to achieve sustainability goals. Recent advancements in artificial intelligence (AI) have provided innovative solutions to many challenges faced by supply chain networks. AI technologies, ranging from predictive analytics to intelligent automation, enhance decision-making, optimize resource use, and boost environmental performance throughout the supply chain. We conducted a thematic literature review on achieving GSCM with AI, and this chapter examines the key themes that emerged. The managerial implications of GSCM with AI across industries were found to be a major theme. GSCM aligns closely with the United Nations’ 2030 Agenda for Sustainable Development by directly contributing to the realization of various sustainable development goals (SDGs); hence, this study also has social implications. This chapter also explores the transformative impact of AI on GSCM, detailing its advantages, challenges, and future trends, as well as the innovations driving the evolution of sustainable supply chains. In the future, AI and green energy initiatives could lead to a paradigm shift in GSCM, allowing organizations to build very sustainable and resilient supply chains. A limitation of this study is the certain search words that were used to locate papers, articles, books, and reports on AI and GSCM.

This empirical study aims to provide a conceptual framework for the antecedents of continuous purchase intention (CPI) of organic personal care products (OPCPs). Organic products are considered mor...

Its a good idea and attempt, however there are several shortcomings * The authors should substantiate their claims with data across the paper - for eg “They were all facing a decline in terms of sales as the impact of the uncertainties during COVID...

Purpose: This study explores coopetition opportunities between e-tailers and brick-and-mortar (BM) retailers and provides a conceptual framework. These opportunities may be triggered by events such as social distancing causing crises (SDCC).Design/methodology/approach: A grounded theory based approach was used wherein 119 news articles and 48 academic papers are the main sources of data to analyse the real-world responses. A typical qualitative methodology, including open and axial coding, was used. To further analyse the insights obtained, six in-depth interviews were conducted.Findings: Non-customer-interfacing-based coopetition, such as small BM stores serving as e-marketplace sellers and customer-interfacing-based coopetition, such as large BM stores serving as showrooms, are some potential coopetition opportunities.Research limitations/implications: The majority of the available studies dwell more on offline retailers developing online channels. This study investigates the opposite situation and conceptualises a new understanding of how e-tailers and BM retailers can work together more harmoniously. This study can be used as a springboard by academicians for future research on a larger scale. Five research propositions are offered that can guide hypothesis generation. Development of case studies and consulting services for the industry are the other research opportunities.Practical implications: Social distancing as a measure may vanish from the world with time; however, social distancing's implications are still pertinent given that new diseases, including new variants of pandemic potential, could continue to emerge. The study puts forward propositions based on theoretical dimensions and second-order themes derived from first-order categories. These propositions are about the drivers of coopetition and the opportunities with both large and small BM stores that e-tailers can leverage during a crisis, given that launching e-tailers' own BM stores demands large investments. This study has social and economic implications too.Originality/value: This study investigates coopetition, an important trend but lacking adequate research. Whilst only few studies examine coopetition from a crises' perspective, this study investigates develops a new understanding of coopetition opportunities between e-tailers and BM retailers. This study adds to the scarce literature how such opportunities may be triggered by events such as SDCC.

Purpose: This paper studies the impact of social distancing causing crises (SDCC) such as pandemics in its early stages on e-tailers demand and supply side operations and provides a conceptual framework for adaptation.Design/methodology/approach: A grounded theory-based approach has been used, wherein journal papers and news articles are the key data sources. Standard qualitative methodology, including open, axial and selective coding has been followed.Findings: The study provides second order themes derived from first-order categories, the theoretical dimensions and their interrelationships on how e-tailers need to adapt to variations in online buying behaviour, manage manpower shortage and daily necessities inventory shortage, during SDCC. Panic buying emerges as a key disrupting factor as it has multiple repercussions on demand and supply side operations of e-tailers.Research limitations/implications: Exploratory qualitative research such as this is helpful in early development of a research stream and paves the way for future quantitative studies.Practical implications: This study makes a valuable contribution on e-tailers adaptation to SDCC with significant managerial implications. There are social, economic and policy implications too. For academicians, this study provides a conceptual framework and serves as a springboard for future research.Originality/value: The study is unique as perhaps it is one of the first to study e-tailers adaptation to SDCC. It contributes to a body of the literature which is currently scarce but expected to grow exponentially in the coming years.