Subhajit Pahari

Conventional approaches to customer segmentation, static and retrospective by nature, fail to adequately capture rapid consumer shifts in dynamic market environments. Drawing from dynamic capabilities theory, this article reconceptualizes segmentation as an adaptive, capability‐driven practice rather than as a passive classification exercise. Using a sequential mixed‐methods approach comprising qualitative insights from industry practitioners and quantitative validation via structural equation modelling, this study affirms and extends the dynamic capabilities of sensing, seizing, and reconfiguring. The findings reveal that customer understanding, market scanning, and data integration capabilities (sensing) drive the capability to process big data, which, in turn, improves data interpretation competency and strengthens agile strategic capability (seizing), as well as enhancing data‐driven positioning effectiveness to support real‐time segmentation reconfiguration (reconfiguring). In contrast, data and information processing overload and organizational inertia showed the hypothesized directional weakening of these capability pathways, though none of the three interaction effects reached statistical significance, which positions both as directionally suggested rather than statistically confirmed constraints on the transition from passive to adaptive segmentation practices. Marketers can thus leverage the actionable insights from this study to implement real‐time segmentation and sustain competitive advantage in dynamic, rapidly evolving markets.

As e-commerce platforms increasingly adopt augmented reality (AR), understanding how immersive technologies influence consumer wellbeing has become essential. Drawing on the stimulus-organism-response (S-O-R) model and cognitive appraisal theory, this article develops and empirically tests a framework that examines how AR features shape affective satisfaction, buyer empowerment, emotional wellbeing, and purchase intention. A mixed-methods design was employed, involving qualitative interviews and a cross-national survey of AR users. Findings indicate that personalized interactivity and usability realism strengthen immersive experiences and perceived value, which subsequently drive emotional outcomes and behavioral intentions. Moderating effects of perceived artificial intelligence (AI) intrusiveness and AR-related anxiety suggest that psychological discomfort can diminish satisfaction’s impact on purchase intention. Overall, the study integrates cognitive and emotional psychological pathways to extend digital marketing theory and offers actionable insights for designing e-commerce experiences that support consumer wellbeing and ethical engagement, understood as the protection of consumer autonomy, privacy, and psychological comfort during immersive shopping, in e-commerce.

Purpose: This study investigates how algorithmic opacity (ALOP) and inadequate AI governance influence perceptions of digital redlining (PRDL), financial anxiety (FNAX) and trust erosion, leading to withdrawal from traditional banking. The paper further explores how community well-being and empowerment may mitigate these adverse impacts among residents of remote regions in North America and Europe. Design/methodology/approach: Study 1 followed a sequential mixed-methods design, in which 32 in-depth interviews were conducted across eight peripheral areas in the Global North: Nunavut, Yukon, Appalachia, Northern Maine, the Highlands and Islands of Scotland, Lapland, Galicia and the Eastern Carpathians. Study 2 surveyed 575 participants to test a Technology Threat Avoidance Theory (TTAT)–Stimulus-Organism-Response (S-O-R) model through confirmatory factor analysis and structural equation modelling, examining psychological pathways and moderating effects. Findings: Results show that opaque algorithms and poor governance potentially amplify PRDL and FNAX, eroding institutional trust and promoting withdrawal behaviour. However, community empowerment can weaken these effects. In well-connected, digitally literate communities, residents view algorithmic shortcomings as a systemic issue rather than a personal failure, thereby maintaining trust and engagement through shared learning and local collaboration. Originality/value: The study extends TTAT and S-O-R frameworks to AI-mediated financial services and offers a cross-regional perspective on AI's psychological impact in marginal contexts. It demonstrates that sustainable digital inclusion depends not only on transparent algorithms but also on human-centred governance and empowered communities, highlighting collective resilience as a practical countermeasure to ALOP and financial exclusion.

This research explored the psychological and behavioral resistance of consumers toward AI‐enabled personalization in the contexts of e‐commerce and quick commerce (Q‐commerce). Though advanced AI technologies offer benefits such as efficiency and convenience, consumers report concerns about emotional manipulation, information overload, and diminished consumer autonomy. Using the Technology Threat Avoidance Theory (TTAT) and the Stimulus–Organism–Behavior–Consequence (SOBC) model, we have explained how AI‐related stimuli may evoke consumer resistance. We used a mixed‐methods approach. In Study 1, we conducted in‐depth interviews with 18 Indian consumers to identify the dominant factors of resistance, and in Study 2, we surveyed 487 consumers. We validated and tested the proposed framework using Confirmatory Factor Analysis (CFA) and structural equation modelling (SEM). Findings show that emotional manipulation and information overload increase consumers' threat perception of AI and psychological reactance. These, in turn, lead to resistance intentions, platform avoidance, and brand distrust. However, brands' CSR initiatives and human oversight throughout the process can weaken the relationship between resistance behaviors and brand distrust. In short, our findings suggest that consumer resistance to AI is a patterned response to emotional and ethical concerns‐ not a direct rejection of AI. This study provides helpful insights for managers, designers, and policymakers to develop more transparent and responsible AI systems in the context of e‐commerce and Q‐commerce.

The study examines the dilemma faced by consumers in balancing the concepts of sustainability and luxury in the context of self‐gifting. The research is based on the Affect‐Behavior‐Cognition (ABC) framework and the Consumer‐Brand Identification (CBI) theory, which seeks to understand how the perceived sustainability–luxury fit and brand ethicality influence emotional reactions and consumer behavior after purchase. A mixed‐methods design with two phases has been employed. The first phase consists of extensive interviews with participants from three countries: India, the UK, and Australia. In the second phase, we verified a conceptualized model using surveys with 470 consumers, employing confirmatory factor analysis and structural equation modeling. The results highlight that a fit between sustainability and luxury, as well as brand ethicality, can enhance sustainability‐induced brand attachment and eco‐luxury pride, which in turn drive self‐gifting intentions, post‐purchase impact actions, electronic word‐of‐mouth, and consumer well‐being. Brand transgression history deteriorates, whereas long‐term orientation reinforces these affect–behaviour relationships. Thus, besides managerial implications, the study advances sustainable luxury theory by positioning sustainability as an emotional and identity‐based driver of consumer behaviour through the integration of the ABC and CBI frameworks.

Purpose: This study investigates the minimalist approach of Gen Z, which diverges from traditional minimalist ideals that emphasize curated and meaningful consumption. Gen Z’s minimalism is deeply rooted in sustainability, self-expression and social identity, promoting intentional living by focusing on what truly matters and eliminating unnecessary excess.Design/methodology/approach: Grounded in self-determination theory, this research employs a mixed-method approach combining netnography with a quantitative survey involving 316 respondents. This comprehensive analysis aims to uncover the factors influencing Gen Z’s distinct minimalist behaviors.Findings: The study presents three key insights. First, the concept of voluntary simplicity, representing older minimalist notions, is found to be irrelevant in the fashion context, highlighting a shift in minimalist values. Second, contrary to common beliefs, minimalism does not significantly impact emotional well-being, suggesting that its psychological benefits may be overstated. Lastly, social crowding negatively moderates the relationship between minimalism and social connectedness, indicating that higher levels of social connections can diminish the sense of community often associated with minimalist lifestyles.Research limitations/implications: The study is limited by its focus on a specific demographic and geographic area, which may affect the generalizability of the findings. Future research could explore minimalist behaviors in other contexts and among different age groups to provide a broader understanding.Originality/value: This research provides fresh insights into Gen Z’s minimalist practices, emphasizing their motivations around sustainability, self-expression and social identity. It explores how their approach to minimalism intersects with fashion, contributing to a deeper understanding of contemporary consumption trends and intentional living among younger generations.

This research article aims to investigate the factors that affected the mental health of tea workers during the COVID-19 pandemic. The study provides essential insights into the psychological factors affecting tea workers during this critical time. Data were collected through semi-structured questionnaires from 532 tea workers in the north-eastern region of India. The collected data were analysed using confirmatory factor analysis and structural equation modelling approaches. The study found that all the factors investigated significantly impacted employee stress during the COVID-19 pandemic. However, safety perception and contagion risk were found to have the strongest influence on stress, followed by unknown and information overload, social exclusion and humiliation, monetary loss and job uncertainty, and quarantine and restraint. Additionally, the study confirms that stress at the onset of the COVID-19 pandemic can lead to depression among tea workers, which is also related to insomnia and relationship troubles. Investigating the various dimensions of COVID-19 stressors among tea workers is crucial for the government and management to understand the root causes of the problem. By understanding the contributing factors to mental health issues, we can develop appropriate interventions to support the well-being of tea workers, providing a blueprint for mitigating the potential adverse effects of future pandemics.

Purpose: This study investigates advertising avoidance behavior among consumers, specifically in the realm of meta-platforms. It explores the impacts of digital burnout, advertising clutter, perceived advertising risk, and goal impediment on cognitive and behavioral ad avoidance. Design/methodology/approach: With a sample of 410 respondents, the research employs a comprehensive analysis approach with SEM and CFA, integrating Avoidance Motivation Theory. It examines direct and indirect influences on ad avoidance, mediated by consumer emotions and attitudes. The study highlights the moderating role of content quality in shaping these relationships. Findings: Significant links were found between digital burnout, clutter, perceived advertising risk, and goal impediment with cognitive and behavioral ad avoidance. The study emphasizes the importance of content quality and suggests strategies that focus on emotional resonance, user alignment, and reduced intrusion. Practical implications: For advertisers and marketers in digital spaces, the findings recommend strategies promoting healthy technology usage, streamlined advertising content, transparent communication aligned with user goals, and emotionally resonant campaigns to mitigate ad avoidance behaviors. Social implications: Understanding consumer sentiments aids policymakers in creating conducive advertising models, benefiting both consumers and businesses. This enhances user experiences in digital environments. Originality/value: The paper distinctively applies the Avoidance Motivation Theory to the context of avoiding social media advertisements, thereby uncovering the causes of negative consumer emotions and attitudes, and highlighting the crucial role of content quality as a means to counteract these adverse reactions.