Yash Chawla

While environmental, social, and governance (ESG) practices are increasingly recognized as central to corporate strategy, the literature is characterized by divergent findings regarding whether ESG operates as a value-creating strategic asset or a compliance-driven cost center. To address this divergence, the study synthesizes and extends current knowledge on the multi-level dynamics and strategic choices that shape ESG adoption and its outcomes. Guided by the SPAR-4-SLR protocol, the study evaluates 378 documents using a triangulated, multi-method approach that integrates bibliographic coupling and keyword co-occurrence with an in-depth qualitative content analysis of the resulting thematic clusters. Moving beyond surface-level correlations, it identifies the conditions under which ESG investments create value rather than impose cost. It further clarifies how leadership characteristics and governance attributes reprioritize ESG to build organizational resilience during external shocks and geopolitical instability, a timely yet underexplored concern. The review also offers guidance for practice, indicating how managers might tailor resource allocation across ESG pillars and how integrating ESG with core business objectives can reduce information asymmetry and strengthen the capacity to recover from crises. Integrating these insights, the study develops a novel, proposition-driven conceptual framework grounded in testable propositions, providing a structured agenda for future empirical research and strategic decision-making.

Purpose: This study systematically explores the pathways through which smart packaging (SP) enhances logistics capabilities (LCs) to simultaneously address two key challenges for the circular economy (CE) – physical value and information loss. While the link between SP and circularity is recognised, the specific pathways through which item-level data reconfigures LCs and leads to circular outcomes remain underexplored. This paper clarifies these connections, detailing how and why SP serves as a foundational enabler for the strategic transition from reactive recovery to proactive circular supply chains. Design/methodology/approach: Following a theory-informed systematic literature review (SLR), 59 articles were analysed using axial coding and multi-layered framework synthesis. The research utilises packaging functionalities (PFs) and LCs as micro-level and macro-level units of analysis, respectively, while adopting the R-imperative framework as a strategic lens to map circular outcomes. Findings: The study identifies four thematic pathways: (1) proactive logistics management and dynamic optimisation, (2) autonomous and scalable reverse flows, (3) systemic trust and quality of material streams, and (4) collaborative value co-creation. The findings demonstrate that SP-enhanced LCs address the challenges of achieving circularity by mitigating physical value loss through functional preservation and information loss through item-level visibility. Information-management capabilities are the foundational antecedents allowing supply-management, demand-management, and coordination capabilities to mitigate the information asymmetry inherent in closed-loop systems. Originality/value: This research develops a novel multi-layered conceptual framework explaining the “how” and “why” behind SP-enabled higher-order circularity. It identifies the theoretical boundaries of logistics-led interventions, highlighting the limits of item-level intelligence in supporting design-led strategies like repair and refurbish.

This paper proposes a new framework for personalizing e-commerce, which integrates multivariate user interfaces (MultiUI) with AI-generated content (AIGC). By utilizing customer behavioral data, our approach customizes both the visual layout and product descriptions for specific customer segments. This addresses the current research gap that often overlooks the synergy between UI design and content personalization. We conducted an empirical study to demonstrate the effectiveness of this integrated approach, showing that personalized user interface variants significantly improve customer engagement and conversion rates. In addition, we explore the potential of AIGC by using behavioral clusters to generate customized product descriptions. This showcases how AI can improve the relevance and appeal of product information, contributing to a more engaging and effective e-commerce experience. Although our initial findings using a simplified approach with ChatGPT are promising, future research will focus on refining AIGC models by incorporating domain-specific knowledge and leveraging comprehensive customer behavior data to generate highly tailored product descriptions. This research advances information processing in e-commerce by demonstrating how AI can be used to extract valuable insights from customer data, adapt UI designs, and generate personalized content, ultimately leading to more profitable online shopping experiences. Experimental studies showed that only about 10% of the most popular words were repeated in the product descriptions generated for the three different clusters. At the same time, two-thirds of the most popular words were dominant in only one of the clusters, confirming the satisfactory degree of matching descriptions to the specifics of customer groups.

This study investigates the differential impact of Instagram influencers’ posts and stories on consumer decision-making across the five stages of the Engel-Kollat-Blackwell (EKB) model. Using a survey of 987 Instagram users, we examine how these two content formats influence need recognition, information search, alternative evaluation, purchase decision, and post-purchase behaviour. Our findings reveal that influencers primarily impact the early stages of the decision-making process, with stories being more effective than posts in triggering need recognition and facilitating information search. However, the influence diminishes in later stages, suggesting that other factors play a more significant role in the actual purchase and post-purchase evaluation. This study contributes to the literature on influencer marketing and consumer behaviour by extending the EKB model to the digital age and highlighting the unique ways in which different content formats can shape consumer journeys. The findings offer valuable insights for marketers and influencers seeking to optimise their Instagram strategies.

Using PLS-SEM, this article proposes and verifies a model among Gen Z that captures the relationship between attitudes towards the environmental ecosystem and green tourism, personal and social norms regarding pro-environmental behaviour, perceived behavioural control, perceived green image of destinations (PGID), behavioural intentions regarding green holiday destinations (GHD), and willingness to pay (WTP) more for visiting them. The paper also verifies whether intercultural differences exist in the relationships between these variables. The most important results indicate that (1) for Gen Z, the perceived green image of destinations has the strongest impact on intention to travel to green holiday destinations; (2) the proposed variables explain the willingness to visit green holiday destinations to a much greater extent than the WTP a higher price for such trips. This study contributes to the literature concerning generational changes in tourism, pro-environmental (transition) planning, and the growing green economy and marketing.