PurposeOrganisations are becoming increasingly invested in artificial intelligence (AI), and many face challenges in helping employees adapt to these new technologies. This study aims to consolidate and synthesise the existing literature to underscore the importance of understanding employees’ experiences in AI-enabled work environments and the potential impact on their psychological well-being. Design/methodology/approachThe review employed a structured process of searching, screening and synthesising studies, as proposed by Tranfield et al. (2003). The study selection followed PRISMA, and thematic analysis was used to analyse 137 articles to identify significant patterns and concepts. FindingsThis study identifies six key themes. 1. Present State of AI-Employee-AI Collaboration: Defining Employee Roles and Guest Experiences in Hospitality 5.0; 2. AI Transforming the Employee Experience; 3. AI Integration and Its Impact on Employee Psychological Well-Being in the Hospitality Sector; 4. Implications of Employee Experience on Employee Psychological Well-Being; 5. Importance of Embracing AI in Hospitality; and 6. Theoretical Frameworks for Employees’ Acceptance of AI in the Workplace. Together, these themes show both how AI empowers and limits employees, highlighting the importance of employee-centred methods. Originality/valueThis review provides a unified synthesis of how AI reshapes employee experience and psychological well-being in hospitality, explicitly linking two constructs that have remained under-theorised in prior research. This study concludes with a research agenda of six key areas to advance understanding of human–AI collaboration and employee experience, and also offers strategic guidance for practitioners managing Industry transformations in Hospitality 5.0.

This study examines inefficiencies in the Himalayan Kiwi supply chain, highlighting challenges such as inadequate infrastructure, substandard packaging, and limited adoption of advanced farming practices. The WINGS (Weighted Influence Non-linear Gauge System) approach is used in the study to rank and analyzes barriers to supply chain efficiency and resilience. WINGS enables a thorough review of interconnected elements, providing significant insights into the most critical issues affecting supply chain effectiveness. The report discusses several logistical issues, including insufficient infrastructure, inefficiencies in the packing process, and farmers' lack of cutting-edge farming methods. The study indicates that addressing these restrictions through targeted interventions can improve logistical performance, reduce post-harvest losses, and increase farmer profitability. The WINGS technique offers a robust foundation for lawmakers, infrastructure developers, and logistics specialists to prioritize concerns and make decisions. This study will help in incorporating farmer feedback, doing regional comparative studies, and utilizing emerging technology to improve Agri-logistics systems.

Agricultural systems are increasingly facing critical challenges due to terrestrial contaminants that are known as microplastic (MP) and Nano plastic (NP). These minute particles have been scientifically demonstrated to infiltrate soil, water, and air, primarily as a consequence of agricultural practices like the use of plastic mulches, fertilizers, and different systems of irrigation. These particles can penetrate deeper soil profiles, altering microbial activities, nutrient cycling, and soil physical properties. Uptake of MPs and NPs by fruit crops adversely impact food safety, yield, growth, and production. This review comprehensively cover a range of horticultural divisions (strawberries, apples, pears, and citrus), vegetable sector (tomatoes, cucumbers, and peppers), root sector (carrots and radishes), and floriculture sector. There is still some heated debate on the temporary or permanent hoarding power of MPs and NPs in soils, but little information is available on the mechanisms behind MP and NP transportation, biodegradation, and uptake by plants, despite their prevalence. The review typically contains information on the disposal and modes of MP and NP in an agricultural system, as well as the nature of interaction and their general implications on plant and soil health and, by extension, human health and food security. The finding highlights the need for sustained research to develop effective mitigation strategies that reduce the adverse impacts of plastic pollutants, thereby enhancing sustainability and resilience of crop production systems.

Climate variability fundamentally realigns the processes by which mining-derived contaminants are generated, transported, and transformed at major scales, from mineral surface to watershed hydrology. Synthesizing the mechanistic architecture of the climate-mining-water nexus, the review shows that non-stationary hydroclimatic forcing wherein historical precipitation return periods, temperature baselines, and streamflow statistics no longer reliably predict future conditions invalidates the steady-state conditions of traditional water quality predictions. Coupled thermal hydrological geochemical biological atmospheric interactions produce behaviors that emerge at thresholds, hysteresis, and contaminant pulses, which reductionist frameworks overlook. Predictive capacity, therefore, calls for bidirectional, not parallel, integrative approaches to monitoring and modelling for observatories that discriminate within competing conceptual models and reactive transport frameworks that integrate multi-platform data in the face of formal uncertainty quantification. Adaptive management will need to replace static designs with decision architectures robust to deep uncertainty for signpost-based triggers, flexible infrastructure, and iterative learning. Facing up to the nexus will be a transdisciplinary fusion of molecular mechanisms to watershed outcomes, which can sustain prudent stewardship of waters influenced by mining during the age of accelerating climate change.

PurposePrevious studies are focused on stakeholders’ identification and classification in context of sustainability marketing strategies and were not able to perform the stakeholder prioritization in this context. Thus, the present study aims to prioritize stakeholders related to sustainability marketing. Design/methodology/approachThe objective of the study is accomplished using the analytic hierarchy process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). A dataset of 12 India-based experts, representing multiple sectors was employed to capture a diverse and multi-industry perspective. FindingsFindings of the study revealed that economic stakeholders are more important for organizations than environmental and social stakeholders. The stakeholder entities falling under these categories are also prioritized. Originality/valuePrevious studies restricted themselves to stakeholder identification or classification, this study performs emetically validated prioritization of stakeholders. This study contributes to stakeholder theory in sustainability marketing and provides actionable insights for resource allocation and stakeholder management.

Purpose-The cold chain (CC) is critical in preserving perishable goods across multiple industries. Insufficient infrastructure, along with other challenges, contributes to extensive food wastage. Although numerous studies have focused on the challenges of the CC, an integrated framework is required to prioritize and tackle these challenges. Design/methodology/approach-The empirical research utilizes a conscious capitalism perspective and employs multi-criteria decision-making methods, specifically fuzzy analytic hierarchy process, Fuzzy Technique for Order Preference by Similarity to Ideal Solution and the best-worst method to analyse various factors affecting the cold supply chain (CSC). Findings-The findings of this research emphasize that implementing best practices, forming partnerships and alliances and government initiatives are significant non-information technology (IT) solutions. Automating data collection, integrating logistics management systems and creating integrated platforms are notable IT solutions for addressing CSC challenges. These findings align with the recent focus on sustainability in the CCs. Originality/value-The current study contributes a novel integrated framework and seeks to fill the existing gap by analysing issues and proposing solutions to mitigate the adverse effects of these issues on the CC. The study attempts to further build upon prior research by extending it through the utilization of a unified model with a focus on sustainability.

In Central India, land-use and land-cover (LULC) transitions have intensified over the last three decades, driven by agricultural expansion, mining activity, and peri-urban growth. This study evaluates spatio-temporal LULC change dynamics (1994-2023) and projects future scenarios (2040-2060). In this study, we used a predictor-screened Cellular Automata (CA) integrated with the Artificial Neural Network (ANN) (CA-ANN) framework. Landsat-derived LULCC maps achieved high classification reliability (kappa = 0.87-0.97). Between 1994 and 2023, forest cover declined by 0.91%, primarily transitioning to agricultural and scrubland classes, while built-up and barren land expanded steadily. Model validation yielded a kappa value of 0.87, indicating strong agreement between simulated and observed LULC patterns. Future projections indicate continued contraction of scrubland (-1.94%) and forest (-1.19%) by 2060, accompanied by an increase in built-up (+1.32%), agricultural (+0.58%), and barren land (+1.63%). Land degradation vulnerability index (LDVI) mapping revealed that over half of the study area falls within moderate to high vulnerability zones, particularly across forest-agriculture transition belts and mining corridors. This integrated modelling framework provides spatially explicit evidence to guide restoration prioritization, landscape planning, and monitoring efforts aligned with land degradation neutrality targets.

Amid growing global concerns over environmental degradation, food security, and climate change, organic farming has emerged as a key pillar of sustainable agriculture. This scientometric analysis of global research from 2003 to 2023 examined trends across 11,561 publications, revealed an annual growth rate of 8.8 % and an average of 24.27 citations per document, emphasizing the growing significance of organic farming in both academic and practical spheres. Scientific collaborations across 33,576 authors, with an average of 4.4 co-authors per paper, underscore the interdisciplinary and international scope of organic farming research. The USA, Germany, and Italy played a major role in advancing the field of organic farming through publications in highimpact journals, facilitating the rapid and effective communication of research findings. The Scientometric analysis further revealed that the key research areas of organic farming include soil fertility, biological pest control, climate-resilient practices, and socioeconomic aspects. Emerging interest in precision agriculture and digital tools suggests a shift towards technologically enhanced organic farming. However, the concerns relating to the scalability and economic viability of organic farming practices, particularly for smallholders, remain critical challenges. This analysis offers strategic insights to inform future research directions, policy development, and sustainable agricultural transformation.

PurposeThere is a lack of studies exploring how artificial intelligence (AI) enables operational excellence, which justifies the successful integration of AI and how it can be connected to circular economy (CE). This study aims to examine how AI-driven operational excellence enables resource utilization to facilitate the CE transition.Design/methodology/approachIn total, 12 enablers were identified through literature, and using the Fuzzy-DEMATEL technique, their cause-effect analysis and prominence rating are conducted.Findings"Improved transparency, coordination and trust", "improved forecast of demand and other uncertain supply chain (SC) parameters", "accurate real-time information flow", "decision support for specialized CE-based business models" and "improved eco-accounting of SC impacts" are identified as the most prominent enablers.Originality/valueThese enablers will help enterprises identify specific use cases of AI in CE-based business models, thereby accelerating adoption and improving resource utilization and circularity. The study's findings will assist managers and practitioners in understanding the operational aspects of how AI contributes to enhanced resource circularity.

This study is a blend of theoretical applications that provides an insight into the complete supply chain system of the sugar industry. This study conducted in India, covered the states of Uttar Pradesh and Uttarakhand. Some unique characteristics were identified with respect to the sugar industry in India. The main aim of this study was to understand the role of different supply chain partners like sugarcane farmers, millers, distributors (includes brokers, wholesalers, and retailers) and other stakeholders of the sugar industry. This will bring radical improvement to the system at different stages/levels i.e. farmers’ level, procurement level, sugar production level, and distribution level. The researchers, academia, industrialists, and policy makers will definitely understand the real-time working structure and business environment of the sugar supply chain system in Uttar Pradesh and Uttarakhand, probably similar for other states too.

Untreated wastewater, including both municipal and industrial wastewater, contaminates soil, surface water, and groundwater, posing a serious environmental risk. Innovative, economical, renewable, and ecologically safe wastewater treatment solutions are currently required. In order to improve wastewater treatment, a number of methods, including ion exchange, co-precipitation, adsorption, membrane separation, oxidation, and biochemical processes, are now being investigated for the production of bioactive components from vegetables. To remove impurities from wastewater, a variety of adsorbents are developed and used among which, bioadsorbents derived from waste biomass stand out for being economical, sustainable, renewable, and environmentally safe. This review examines vegetable-based biomass waste as a low-cost adsorbent for waste water treatment. Vegetable waste has garnered a lot of attention due to its abundance, high biocellulose content (21

Severe weather in hilly regions like the Eastern Himalayas poses significant risks to life and natural resources due to complex and varied topography within small geographic areas. This study explores the integration of Dual-Polarization Weather Radar (DWR) data into the Weather Research and Forecasting (WRF) model to evaluate the performance of two data assimilation techniques (3DVar and 4DVar) in predicting heavy rainfall events. Reflectivity and radial velocity measurements from an X-Band DWR were assimilated to quantitatively assess their impact on precipitation forecasts. Simulations were conducted for two heavy rainfall events in August 2023 at spatial resolutions of 9-km and 3-km, each over three days. Forecast accuracy was measured using Root Mean Square Error (RMSE) and RSR, where lower values indicate better performance. Results show that decreasing grid spacing from 9-km to 3-km improves prediction accuracy. RMSE for RH at 9 km_CTRL is 8.09 % and for 3 km_CTRL is 7.10 %. Similarly, for T2 at 9 km_CTRL, RMSE is 3.38oC, and for 3 km_CTRL is 2.71oC. RMSE for precipitation at 9 km_CTRL is 20.80 mm and for 3 km_CTRL is 12.78 mm. The lowest RMSE is observed for the 4DVar experiment for all three variables, where RMSE is 8.50 %, 2.54oC, and 2.66 mm for RH, T2 and precipitation. RSR value is lowest for the 3 km_4DVar experiment as compared to other experiments for all the variables. These findings highlight that integrating radar data via 4DVar assimilation markedly improves heavy rainfall forecasting, especially at higher resolutions. This approach holds strong potential to support disaster management and mitigation efforts in the vulnerable Himalayan region.

PurposeThe cold chain system is vital for food safety, public health, and sustainability. However, it still faces challenges in sustainable practices, especially in quality assurance, waste reduction, and efficiency. This study uses bibliometric and systematic review methods to trace the field's development over 25 years, identify gaps in global benchmarking, and propose practical performance metrics. Applying SPAR-4 and bibliometric tools, the study finds growing academic interest in cold chains since 2010 and stresses the need for standardized global indicators. A new KPI framework is presented to enable cross-regional comparisons and guide future research and policy.Design/methodology/approachThe study presents a comprehensive bibliometric analysis of research on cold chain management published over the last 25 years. In addition, the SPAR-4 framework is applied to ensure methodological rigor in the systematic literature review process. Drawing on publications spanning 2000 to 2025, the analysis traces the evolution and trajectory of cold chain management research and examines its implications for business and logistics practices.FindingsBibliometric results show that cold chain publications experienced an 88% annual increase in citations from 2010 to 2025, compared with 2000-2009, highlighting rising academic interest. Most research centers on vaccine and food supply chains. The review also notes the absence of standardised global indicators for evaluating the cold chain. It suggests key dimensions: sustainability, safety and quality, operational performance, capacity, and integration with broader supply chains.Originality/valueThis study provides a comprehensive synthesis of cold chain management research, highlights key limitations in existing approaches, and identifies priority areas for future investigation. By proposing a structured KPI framework, it provides practical guidance to support the adoption and evaluation of sustainable cold-chain management practices.

Vanadium (V) is a naturally occurring trace metal in the environment, with augmented emancipation mainly owing to industrial and mining activities, and has escalating issues with ecological and toxicological impacts. Although at low concentrations (< 2 mg/L), V can promote plant growth, at higher concentrations (≥ 2 mg/L), it exerts significant phytotoxic effects, comprising a 40% reduction in chlorophyll content and 30% inhibition of root elongation in various crop species. The environmental and biogeochemical behavior of V(V) is governed by redox potential, pH, organic matter, and mineral interplay, with V(V) accepted as the most versatile and lethal form. A primary mechanism of V toxicity is oxidative stress, which results from excessive reactive oxygen species (ROS) generation and disrupts cellular homeostasis in both terrestrial and aquatic organisms. There are critical information gaps, particularly regarding the establishment of reliable environmental quality standards, clarification of molecular mechanisms of V(V) detoxification and tolerance in organisms, and the feasibility of leveraging plant-based systems for V(V) phytoremediation. This review delineates the need for scientific studies to address these research gaps, underscoring the need for integrated biogeochemical and physiological studies to deepen our understanding of V(V) dynamics in soil–plant systems and to support effective environmental management strategies.

Digital Public Infrastructure (DPI) is the backbone of India’s digital growth. The DPI makes the lives of the people easy and also made the businesses flourish with advanced monetary transaction methods. Similar to any other big project, the DPI also faces lot of challenges. This paper tries to highlight some of the major challenges faced by the DPI. To identify these challenges, the inputs of 12 experts from various streams were obtained and using the Analytical Hierarchy Process (AHP), the important challenges are prioritized. One the major challenges found is the consumer trust and inclusion of all the sections of the society. Socio-Technical Systems (STS) theory has been deliberated to assess and relate the findings of the analysis, which can be assimilated with societal and environmental factors. The study also provides inputs to make the implementation of DPI environmentally sustainable and aid in achieving the Sustainable Development Goals (SDGs).

Cold chain structures today, especially post-COVID-19, must ensure that they can meet the ever-increasing requirements of customers while also ensuring the safety and quality of products for the end consumer. In order to improve cold chain performance, this study primarily analyses the critical success factors (CSFs). The total interpretive structural modelling technique was exercised to construct contextual links amongst the isolated elements and then categorized into various groups on the basis of driving force and dependence through the application of Cross-Impact Matrix Multiplication Applied to a Classification (MICMAC). The Total Interpretive Structural Modelling (TISM) model emphasizes the significance of infrastructure, awareness and integration, which are the foundational factors leading to responsiveness and sustainability. MICMAC analysis established that to enhance the success of the digital cold chain, it is imperative that infrastructure, awareness, integration, traceability, safety and quality are enhanced. Enhancing these CSFs will bring about enhanced responsiveness and a sustainable digital cold chain. Decision-makers and strategists in the supply chain domain can focus on crucial factors leading to effective choices and maximize value for businesses. Although the field is still in its stage of evolution, the study aims to contribute to the expanding information on digitally-led cold network. This study is among the few to look at success elements that are essential to raising cold chain performance and establishes the framework for additional study in this area.

ABSTRACT The increasing concentration of antimony (Sb) in the environment has raised significant concerns throughout the globe owing to its potential toxicity. It enters the ecosystem mainly through anthropogenic activities, including coal mining, industries, leaching, urbanization, and the weathering of the parent rocks. This literature review provides an in‐depth overview of the sources of Sb contamination, its speciation and bioavailability in the soil–plant system, as well as the mechanisms governing its uptake and sequestration by the plants. The Sb toxicity adversely affects numerous characteristics of plant physiology, such as seed germination, plant growth, nutrient uptake, and interferes with the photosynthetic system. The review also examines various remediation strategies for Sb, evaluating their efficiency, economic, and applicability in different environmental contexts. These methods inclusively restore degraded land by reinstating the production and its ecosystem service value. The findings of this review offer valuable insights into the potential novel approaches for mitigating the Sb pollution, thereby improving the management of Sb contaminated soils and reducing associated ecological and human health risks.

Microplastics (MPs) have infiltrated soil–water–sediment systems pervasively through terrestrial, freshwater and marine compartments, leading to lingering pollution while secondary microplastics account for the most environmental loads including wastewater treatment plants, agricultural plastics, landfill leachate and tire wear as major diffuse sources. The transport of MPs proceeds via coupled hydrodynamic–particle interactions, heteroaggregation with suspended sediments and biofouling processes that contribute to sedimentary burial with resuspension dynamics serving as a long-term reservoir storing the legacy burdens and sustain trophic exposure long after primary emissions. Ecotoxicological evidence replaces MPs as inert vectors with bioactive disruptors which are activated via hierarchical stress pathways that induce oxidative stress, immunomodulation and metabolic impairments with the polymer-specific toxicity and temperature-dependent effects. Direct dietary exposure pathways are established by both trophic transfer and pathways for crop uptake through apoplastic and symplastic routes with having human health implications detected in atherosclerotic plaques, placental tissue and multiple organ compartments, showing mechanistic evidence of mitochondrial dysfunction and inflammatory signalling. The removal efficiencies in current mitigation technologies are high, but current contamination cannot be reversed, hence the need for a shift from end-of-pipe remediation to source-directed regulation. Critically collating the range from the environmental sources to the nutritional effects, the review uncovers salient gaps in knowledge, notably around nanoplastic identification, crop transfer coefficients and sediment-inclusive risk modelling and establishes a cohesive platform to inform future knowledge and policy direction within the One Health space.