Management Development Institute

Industry 5.0 drives a deeper fusion between advanced intelligent systems and human creativity, positioning immersive technologies as essential components of modern innovation. Digital Twins and the Metaverse enable highly interactive, data rich environments where physical processes can be simulated, optimized, and experienced virtually. With support from AI, IoT, blockchain, and high speed networks, organizations can design business models that prioritize adaptability, co creation, and meaningful user engagement. Consumers participate directly in virtual testing, collaborative design sessions, and service interactions, creating continuous feedback loops that refine products and experiences. These immersive ecosystems strengthen operational reliability, reduce development risks, and open opportunities for sustainable value creation across industries. By offering transparent, secure, and accessible digital spaces, immersive technologies help companies develop human centered, resilient, and future ready business strategies aligned with the goals of Industry 5.0.

Purpose Advanced technologies such as additive manufacturing (AM) play a critical role in transforming the healthcare sector by enabling sustainable and resilient solutions that improve patient services and operational efficiency. Yet, the adoption of AM in the healthcare sector is limited. Understanding the knowledge drivers behind its adoption is crucial for its successful implementation and better healthcare performance. This study aims to explore how effective knowledge processes impact innovation, resilience, sustainability and enhanced service quality in healthcare organisations. Design/methodology/approach Drawing on the dynamic capabilities theory, the motivating factors for AM adoption are identified from the literature and verified with industry experts using the fuzzy Delphi method. Then the factors are ranked and categorised into cause-and-effect using different multicriteria decision-making methods. Subsequently, the rationale for the cause-and-effect linkages has been explained using a qualitative approach. Findings This study presents a knowledge-driven decision-support framework that demonstrates how AM facilitates environmental sustainability, operational resilience and performance improvement. Healthcare organisations can leverage this knowledge-structured guidance to make informed decisions aligned with regulatory sustainability mandates. Originality/value Existing studies examine AM in healthcare through separate lenses (e.g. resilience, sustainability and performance) without explaining how organisations can integrate these objectives in practice. This study addresses that gap by developing a knowledge-driven decision-support framework that links knowledge processes and dynamic capabilities to AM adoption pathways, thereby offering actionable and innovative strategies for healthcare organisations.

ABSTRACT AI‐based recommender systems shape many consumer decisions, but users often have limited information about why a recommendation is presented. This paper examines how explainable AI (XAI) design influences consumers' follow‐through, and when these effects are stronger. We conceptualize XAI design along two dimensions: explanation level (high vs. low diagnostic detail) and explanation type (process‐oriented vs. outcome‐oriented), and we examine boundary conditions across recommendation context (product vs. content). Four scenario‐based, between‐subjects experiments were conducted with Prolific participants who reported familiarity with recommendation systems (total N = 1080). Study 1 establishes the baseline effect: high (vs. low) explanation level increases intention to follow the recommendation, and the effect is robust under divided attention. Study 2 shows that the benefit of higher explanation level is context‐dependent, with stronger effects in content recommendations than in product recommendations. Study 3 shows that explanation type also shapes the effect of explanation level on follow‐through, with process‐oriented explanations producing a larger advantage for high (vs. low) explanation level than outcome‐oriented explanations. Study 4 tests the proposed mechanisms in a 2 × 2 × 2 design and finds that explanation level affects follow‐through primarily through trust and psychological ownership, with these indirect effects stronger in content (vs. product) contexts and under process‐oriented (vs. outcome‐oriented) explanations. Together, the findings specify how explanation level, explanation type, and context jointly determine when XAI increases follow‐through, and they identify trust and psychological ownership as mechanisms through which explanation design translates into consumer action.

ABSTRACT The rising pursuit of carbon neutrality coupled with institutional pressure has compelled the marginalized communities and industries at the forefront to strive toward net‐zero targets. The European climate policy and Paris agreement have emerged as a cornerstone to achieve net‐zero emissions in industrial firms. The circular economy capabilities and supply chain digitalization (ScD) hold immense potential to diminish carbon emissions, achieve net‐zero performance, and sustainable development goals (SDGs). This research has proposed a conceptual framework to examine the effect of circular economy capabilities in linking environmental dynamism (EnD) and institutional pressures to achieve net‐zero performance. Additionally, the moderation of ScD has been investigated for this framework. This research amalgamated the concept of resource‐based, institutional, and dynamic capability theories to analyze antecedents for net zero performance. Investigation is done using a survey of three hundred forty‐one respondents working in the manufacturing sector of India. Data analysis is done using partial least square structural equation modelling. The findings highlight a positive relationship of EnD and institutional pressure with circular economy capabilities in advancing net‐zero performance of the organization. Results show that ScD positively moderates the relationship between EnD, the development of circular economy‐based capabilities, and net‐zero based performance. The blend of theoretical underpinnings and practical insights provides a strategic roadmap for policymakers and practitioners to mitigate environmental issues using circular economy capabilities and digitalized supply chain in the era of climate urgency.

ABSTRACT Food loss and waste (FLW) in agricultural perishable food supply chains (APFSCs) remains a persistent barrier to food security, environmental sustainability and rural economic development, particularly in emerging economies. Prior studies have documented various operational, technological, and infrastructural bottlenecks and this limited empirical work clarifies the specific capabilities that are necessary, which are sufficient, and the ones which exert their influence only in specific combinations to reduce FLW in business‐to‐business (B2B) APFSCs. Grounded in the contingent resource‐based view (CRBV), this study examines how capability deficits, contextual constraints and inter‐organisational dynamics jointly shape FLW outcomes in India's rural APFSCs. To address the inherent causal complexity of FLW, the study adopts an integrated tri‐method approach combining partial least squares structural equation modelling (PLS‐SEM), necessary condition analysis (NCA), and fuzzy‐set qualitative comparative analysis (fsQCA). Data from 333 valid responses across diverse APFSC actors, including farmers, wholesalers, processors, distributors and cold storage operators. PLS‐SEM is used to construct and validate latent constructs while minimising measurement error. Latent scores feed into NCA to identify bottleneck conditions, and into fsQCA to uncover non‐linear, equifinal capability configurations associated with high FLW. The findings reveal that FLW emerges not from isolated deficiencies but from interdependent, context‐contingent capability gaps, including inadequate cold‐chain infrastructure, weak digital information systems, insufficient training, limited coordination mechanisms and fragmented marketing linkages. Several capabilities function as necessary but not sufficient, while others act as sufficient only within particular configurations, highlighting the asymmetric and complementary nature of capability effects. These insights extend CRBV by demonstrating that capability value depends on institutional conditions, actor interdependencies and minimum resource thresholds. The study contributes a nuanced causal explanation of FLW reduction and offers actionable guidance for managers and policymakers regarding the prioritisation and orchestration of operational, technological and relational capabilities in emerging rural B2B agri‐food systems.

The conceptual and linguistic properties of figurative and conventionalized metaphors in English, and incorporates the conceptual knowledge of cognitive linguistics, psycholinguistics and computational analysis. With the Kaggle Metaphor Detection VUA-WSD Augmented Dataset, one can classify metaphors as either figurative or conventionalized to analyze variations in conceptual mapping diversity, frequency and interpretive complexity. It has been found that figurative metaphors have more diversity in terms of source-target domain mappings, are more creative and novel, whereas conventionalized metaphors are more frequent and processed with reduced cognitive effort because of their established use. Significant differences between the two types are statistically proved by using Chi-square and t-tests, which proves the role of metaphor as a linguistic and cognitive phenomenon. The results are applicable to both language teaching and improving awareness of metaphorical patterns and to computational linguistics, by improving NLP-based metaphor detection systems. Also, it is psycholinguistics, which shows an effect of the type of metaphor on cognitive processing and gives guidance on future experimental verification and cross-linguistic research.

Purpose This study aims to investigate how perceived organizational justice affect workplace dynamics, focusing on their cascading effects on workplace loneliness, knowledge hiding and psychological well-being. Drawing on cognitive appraisal theory, this study proposes that perceived organizational justice can trigger negative emotional responses such as loneliness, which in turn may exacerbate defensive behaviors like knowledge hiding and reduce psychological well-being. Design/methodology/approach This study used a two-wave, time-lagged design, which yielded a sample size of 216 full-time employees. The final data was analyzed using SPSS and AMOS. Findings The results revealed a negative association between perceptions of organizational justice and workplace loneliness. Workplace loneliness was positively related to knowledge hiding and negatively related to psychological well-being. The analysis of indirect effects indicated that perceptions of organizational justice negatively affect knowledge hiding through workplace loneliness, while its relationship with psychological well-being was positive. Originality/value By advancing an understanding of the social and emotional mechanisms underlying justice perceptions, this study contributes to the organizational justice literature and provides actionable insights for fostering fair, inclusive and supportive workplaces to mitigate knowledge hiding and enhance employee well-being.

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Type of the article: Research ArticleAbstractThe study explores the evolving role of customer loyalty within mobile shopping applications in the context of the Indian market, where the rapid growing penetration of smart phones and mobile commerce adoption poses more challenges and opportunities to mobile commerce companies. Therefore, this study aimed to investigate the effect of confirmation, hedonic motivation, and price saving orientation on perceived usefulness, customer satisfaction, and eventually loyalty by integrating Expectation-Confirmation Theory (ECT) and Technology Acceptance Model (TAM). Data were collected through an online survey of 535 Indian smartphone users who had prior mobile shopping experience. Utilizing partial least squares structural equation modelling, this study examines the relationships among confirmation, perceived usefulness, customer satisfaction, and loyalty. The results show that perceived usefulness and satisfaction are important mediators in the confirmation of (β = 0.188, p < 0.001), hedonic motivation (β = 0.134, p < 0.001), and price-saving orientation β = 0.291, p < 0.001) towards customer loyalty. Customer satisfaction (β = 0.457, p < 0.001) was the most crucial determinant of loyalty among the predictors tested. Price-saving orientation showed significant impact on both satisfaction (β = 0.390, p < 0.001) and the perceived usefulness (β = 0.271, p < 0.001), reflecting Indian consumer’s economic nature. In contrast, hedonic motivation (β = 0.012, p = 0.389) was not significant as a predictor of satisfaction, but it had an indirect impact on loyalty via perceived usefulness, indicating the conjoined effect of emotional and utilitarian motives. These findings enhance the theoretical understanding by extending Expectation-Confirmation Theory within the context of mobile commerce and provide actionable insights for developers and marketers striving for user retention by aligning customer expectations and offering both value and enjoyment through the app.