Search Results (293)

The grocerant represents an emerging hybrid retail–foodservice format integrating grocery shopping, prepared meals, and in-store dining. Although practically significant, the academic literature remains limited and dispersed. This PRISMA-informed semi-systematic review synthesizes 16 studies—including direct grocerant research and adjacent work on retail innovation, prepared foods, and digital food retail—to clarify the current state of knowledge. The review followed structured database searches, citation tracking, title/abstract screening, and full-text eligibility assessment. Three main perspectives emerged. First, consumer-focused studies emphasize customer experience, food healthiness, multidimensional perceived value (functional, hedonic, social, and financial), brand prestige, in-store dining behavior, and loyalty. Second, strategic research positions grocerants within retail format innovation and competitive convergence between grocery and restaurant sectors. Third, operational perspectives link grocerants to prepared-food systems, retail food environments, and omnichannel transformation. Major gaps include limited operational and comparative research, geographic concentration, and weak digital integration. The review suggests that grocerants function as evolving systems where convenience, experience, branding, and digital transformation converge. Full article

Given the global increase in beef consumption, cull dairy cows are an underutilized resource, mostly destined for low-value ground beef, despite their potential for premium cuts. This review summarizes recent evidence on pre- and post-mortem strategies specifically aimed at improving meat quality in cull dairy cows, addressing a topic that has been little studied. Finishing diets notably increased intramuscular fat by 112% after 4 months of feeding, enhanced carcass yield, and reduced shear force. Wet aging can improve tenderness by approximately 30% during the first 7 days when combined with finishing diets at a lower operating cost, whereas dry aging enhances intense flavors, albeit with greater losses due to dehydration. Innovations such as vascular rinsing and mechanical tenderizing show promising results, although their adoption is limited by technical requirements and costs. The implementation of these strategies can generate economic benefits by revaluing discarded meat (≈25% higher retail price) and sustainability by reducing waste in livestock systems. However, heterogeneity in breed, age, and management requires adapted approaches. Additional studies integrating productive, sensory, and economic aspects, as well as research on consumer acceptance, are needed to facilitate their adoption on an industrial scale and contribute to more efficient and sustainable meat production. Full article

This case study aimed to benchmark the healthiness, equity, and environmental sustainability of a large, urban Australian university food environment through two audits conducted in 2022 and 2025. Two cross-sectional audits were completed at a large urban university campus using the Uni-Food tool, which assesses 68 best practice indicators across three components: policy, campus facilities, and food retail outlets. Four assessors independently conducted the audits with excellent inter-rater reliability (Cohen’s Kappa = 0.89). Final scores out of 100 were calculated using weighted domains. Descriptive and inferential statistics were used to compare changes over time. In 2025, the university achieved a score of 52%, up from 48% in 2022, indicating medium compliance with best practice standards. Findings highlight that scores differed modestly but there were persistent gaps in university food policy and practice. Specifically, the policy component remained low (48%), demonstrating strong overall planning but a lack in food retail policy and monitoring systems. The campus component scored moderately (63%), with various nutrition knowledge-building opportunities and environmental sustainability initiatives available but heavy promotion of unhealthy foods at campus events. The food retail component scored lowest overall (36%), especially as there was a lack of adequate nutrition information provided at food outlets. Continued investment in policy development, campus-wide strategies, and food retail innovation is essential to create healthier, more equitable, and environmentally sustainable food environments in tertiary settings. Full article

This study investigated the effects of red grape pomace powder (GPP) on spontaneously fermented salamis produced from the meat of retired cows and young bulls of the Cinisara dairy breed. The use of GPP and meat from these animal categories was motivated by the valorization of low-commercial-value agri-food resources and the enhancement of sustainable local production chains. Plate count analyses showed typical fermentation dynamics, with lactic acid bacteria (LAB), coagulase-negative staphylococci, and yeasts reaching approximately 7 log CFU/g, and confirmed the absence of major foodborne pathogens. Illumina sequencing further characterized the bacterial community, identifying Latilactobacillus as the dominant genus at the end of ripening, with relative abundance (RA) of up to 65% in GPP-enriched trials. Physicochemical analyses showed progressive changes during ripening, including weight loss, pH decrease, color development, and increased proteolysis. GPP supplementation contributed to the stabilization of a*, chroma, and hue values, while reducing lightness during ripening. Oxidative stability measurements showed that GPP derived polyphenols effectively limited oxidative reactions, especially secondary lipid oxidation. GPP also modulated the volatile profile by increasing ester formation and introducing plant-derived compounds. Sensory evaluation revealed higher color intensity and aroma in enriched salamis, along with higher bitterness and lower structural homogeneity, especially in those produced from retired cows. Consumer surveys conducted in two retail settings indicated strong interest in this innovation, with over 80% of respondents willing to pay a 10–20% price premium. Overall, GPP emerges as a promising functional ingredient for enhancing, diversifying, and valorizing fermented salamis produced from dairy cattle meat, supporting both product innovation and sustainability-oriented strategies. Full article

This study develops a comprehensive carbon footprint assessment model that integrates forward and reverse logistics to evaluate and compare greenhouse gas emissions from online and offline apparel sales channels in China, with a particular focus on high return rates. The model quantifies emissions from transportation, packaging, storage, and operations, incorporating return and exchange logistics. The system boundary is limited to enterprise-controllable sales-phase activities and excludes consumer travel. Three sales models are compared: factory-to-consumer (F2C), traditional business-to-consumer (B2C) e-commerce, and brick-and-mortar retail (BMR). Within this defined boundary, BMR exhibits the lowest carbon footprint (0.296 kg CO₂e/item), followed by F2C (0.408 kg CO₂e/item) and B2C (0.602 kg CO₂e/item). Packaging dominates online emissions (55–57%), whereas store operations are the main contributor to offline emissions (43%). Return rates are identified as a decisive factor, accounting for over 31% of e-commerce emissions and potentially increasing them by 171.3% under extreme scenarios. Sensitivity analysis reveals that trunk line distance (factory to warehouse) has a greater impact on emissions than last-mile return route optimization. Relocating the factory closer to consumers reduces B2C transport emissions by 72.3%, whereas replacing conventional packaging with recycled plastic reduces total B2C emissions by 46.0%. These findings provide channel-specific sustainability strategies: return reduction and packaging innovation for online channels, and energy efficiency improvements for physical stores. These results are conditional on the defined system boundary. If consumer travel by private car were included, the relative advantage of offline channels would diminish or could reverse. Full article

Food waste prevention and reduction are some of the important initiatives to improve the environmental sustainability of food systems. The global agenda of the United Nations provides a framework of targets and actions against food waste to which the European Union (EU), within the “Farm to Fork” strategy, aims to contribute. In this context, evaluating the impacts of food prevention measures is of great importance for supporting policies. This LCA analyzes the impact of classic lasagna from cradle to grave, through a generic food case study, prepared by food shops in Bologna (Northern Italy). Four scenarios are simulated, comparing the impacts of some end-of-life alternatives for the management of leftover lasagna (landfilling, composting, and redistribution with the digital application of the circular start-up “Squiseat”) versus the ideal scenario where no leftover lasagna is assumed. The results show that the preparation of classic lasagna generates non-negligible impacts on the analyzed LCA categories due to some of its ingredients, such as Bolognese sauce and Parmigiano Reggiano, and their associated production processes. For this reason, it is important to prevent classic lasagna leftovers from being wasted. The comparison of the four scenarios shows that redistribution is the scenario with the lowest impacts in all the investigated impact categories, including global warming (6.24 kg CO₂ eq./kg of lasagna). The impacts are also lower than the ideal scenario due to the assumption of more sustainable means of transport. Normalization of characterized results confirms that Global Warming (GW) is only one of the most relevant impact categories in the life cycle of classic lasagna. The results have practical implications for raising awareness concerning the impacts of food production throughout the whole life cycle and the need for preserving the value of food by avoiding waste. Moreover, this study also shows that a reduction in the impact is a shared outcome that could be achieved by the joint efforts of all the stakeholders involved in the life cycle of food. In this regard, urban centers are confirmed to be important hubs of circular and more sustainable innovation. Finally, the LCA enriches the current research by investigating redistribution through the relationship of the food shop–virtual intermediate–consumer. So far, the prevalent focus of the LCA research allows us to assess the redistribution of collected surplus food from retailers and its delivery to the consumers by means of physical intermediaries and related infrastructures (e.g., food hubs, food banks, and food emporiums). Full article

Urban commercial restructuring, driven by the closure of traditional supermarkets and the expansion of new-format superstores, creates a large-scale spatial reallocation challenge requiring scientific location-allocation methods. Traditional heuristic algorithms such as Genetic Algorithm (GA) struggle with discrete spatial optimization under 400+ candidate sites and complex geographic mask constraints: they converge slowly and easily fall into local optima. This study proposes a Deep Reinforcement Learning (DRL) framework named GeoPPO (Geospatial Proximal Policy Optimization) to address this gap. Using Xi’an’s retail restructuring as a case setting—427 candidate locations and multidimensional geographic features—the approach models spatial constraints via a gridded environment encoded as a five-channel state tensor. Key innovations include a dynamic action-constraint mechanism that masks invalid actions based on boundary rules and competition avoidance, and a curriculum learning strategy that enables stable convergence. The framework fills the need for methods that handle hard spatial constraints in large-scale location-allocation. Tests demonstrate rapid convergence within 1,000 epochs, achieving 75% average demand coverage—2.7% and 5.5% higher than GA and Particle Swarm Optimization (PSO), respectively. Ablation experiments confirm that Vanilla PPO without dynamic action masking fails to produce feasible solutions. The framework offers a feasible technical path for handling highly dynamic urban facility spatial configuration with geographic mask constraints. Full article

Background: The COVID-19 pandemic disrupted global dairy supply chains and threatened business continuity from farms to retail outlets. There is limited understanding of how operational-level managerial decisions supported resilience in this perishable sector. Methods: This study applies a systematic literature review based on PRISMA 2020 guidelines. It analyses 21 peer-reviewed studies published between 2019 and 2025 across 19 countries. Results: The findings identify 8 primary supply chain challenges. Adaptive responses are classified into traditional and innovative managerial adaptations. Traditional adaptations rely on established practices such as production adjustments, cross-training, and product reallocation to stabilise short-term performance. Innovative adaptations involve structural and analytical approaches such as network optimisation, digital coordination, and scenario planning to support long-term resilience. The results also reveal differences between developed and developing economies. Conclusions: Resilient dairy supply chains require both operational continuity and structural innovation. This study proposes a sector-specific classification of managerial adaptations and highlights directions for future research. Full article

This study presents the first comprehensive assessment of a bacteriophage P100-activated edible whey-protein solution (WPS) applied to the rind of Sicilian Canestrato Fresco (SCF) cheese. Beyond evaluating its anti-Listeria efficacy in pre- and post-packaging contamination contexts, the work investigates the coating’s effects on chemical composition, volatilome, sensory properties, and consumer responses, including willingness to pay. To assess anti-Listeria activity, all samples were stored at 4 °C for 30 days. Contamination was carried out either before or after coating application, depending on the specific treatment. Listeria monocytogenes was monitored at 0, 1, 3, 7, 15, and 30 days of refrigerated storage. The active coating reduced the pathogen from approximately 3 log CFU/g to undetectable levels (0 log CFU/g) within 3 days, whereas the untreated controls reached about 5 log CFU/g after 30 days. WPS-coated cheeses showed no significant changes in chemical composition (moisture ~33%, protein ~29%, fat ~33%) or fatty acid profile compared to traditional SCF. The volatilome was dominated by hexanoic and butanoic acids and ethyl esters, without significant differences between coated and control samples, as confirmed by Smart Nose^® analysis. Sensory evaluation by trained assessors demonstrated that the bioactive coating did not alter the traditional sensory profile of SCF cheese. A consumer survey conducted with 240 participants from two retail formats revealed significant differences in product familiarity and perceived food safety, while openness to innovation and willingness to pay were similar. More than 90% of respondents were willing to pay a 10% price premium. Overall, phage-based edible coatings appear to be edible, renewable, and biodegradable packaging alternative to improve cheese safety without compromising quality. Full article

Growing environmental concerns and regulatory pressures are prompting firms to re-examine packaging design to advance sustainability. Focusing on eco-designed retail packaging in the new-style milk tea industry, this study investigates how specific attributes of eco-designed retail packaging influence consumers’ purchase intention. Data were collected from 425 university students in Wuhan. We measured eco-designed retail packaging (ECRP) with a six-dimension scale (functional, aesthetic, eco-materials, eco-information, eco-production, and innovation) and tested the mediating role of green perceived value (GPV) using structural equation modeling (SEM). Results show differentiated effects of ECRP dimensions on GPV and purchase intention. Functional design and clear eco-information increase both GPV and purchase intention, whereas using eco-materials while directly raising purchase intention reduces GPV. Aesthetics and innovation mainly operate through direct enhancement of purchase intention rather than via GPV. GPV mediates part of the effects of functional attributes, eco-materials, and eco-information on purchase intention. The findings imply that optimizing functionality, information clarity, and material choices in eco-designed retail packaging can simultaneously elevate GPV and purchase intention. As green packaging becomes an industry imperative, this study provides theoretical and practical guidance for sustainable packaging innovation and green industry development. Full article

In the modern era, demand forecasting enhances the decision-making tasks of industries for controlling production planning and reducing inventory costs. However, the dynamic nature of the fashion and apparel retail industry necessitates precise demand forecasting to optimize supply chain operations and meet customer expectations. Consequently, this research proposes the Formicary Zebra Optimization-Based Distributed Attention-Guided Convolutional Recurrent Neural Network (FZ-DACR) model for improving the demand forecasting. In the proposed approach, the combination of the Formicary Zebra Optimization and Distributed Attention mechanism enabled deep learning architectures to assist in capturing the complex patterns of the retail sales data. Specifically, the neural networks, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs), facilitate extracting the local features and temporal dependencies to analyze the volatile demand patterns. Furthermore, the proposed model integrates visual and textual data to enhance forecasting accuracy. By leveraging the adaptive optimization capabilities of the Formicary Zebra Algorithm, the proposed model effectively extracts features from product images and historical sales data while addressing the complexities of volatile demand patterns. Based on extensive experimental analysis of the proposed model using diverse datasets, the FZ-DACR model achieves superior performance, with minimum error values including MAE of 1.34, MSE of 4.7, RMS of 2.17, and R² of 93.3% using the DRESS dataset. Moreover, the findings highlight the ability of the proposed model in managing the fluctuating trends and supporting inventory and pricing strategies effectively. This innovative approach has significant implications for retailers, enabling more agile supply chains and improved decision making in a highly competitive market. Full article

Remote Indigenous communities experience persistent inequities in access to fresh and nutritious foods due to the fragility of perishable food supply chains (PFSCs). Disruptions across procurement, transportation, storage, retail, and limited local production restrict access to perishable foods, contributing to food insecurity and diet-related health risks. This scoping literature review synthesizes evidence from 84 peer-reviewed, grey, and unpublished sources across fourteen countries to map PFSC management (PFSCM) challenges affecting food access in remote Indigenous communities worldwide and to synthesize reported practices implemented to address these challenges. PFSCM challenges were identified across all supply chain levels, and five categories of reported practices emerged: PFSC redesign strategies, forecasting and decision-support models, technological innovations, collaboration and coordination mechanisms, and targeted investments. These findings informed the development of a multi-scalar conceptual framework comprising seven interconnected PFSCM clusters that organize how reported practices are associated with multiple food access dimensions, including quantity, affordability, quality, safety, variety, and cultural acceptability. This review contributes an integrative, system-oriented synthesis of PFSCM research and provides a conceptual basis to support future scholarly inquiry, comparative inquiry, and policy-relevant discussion of food access and health equity in remote Indigenous communities. Full article

Green fintech merges sustainable finance with data-intensive innovation, but national translations of EU rules can create regulatory risk. This study examines how such risk manifests in Central Europe and which policy tools mitigate it. We develop a three-dimension framework—regulatory clarity and scope, supervisory consistency, and innovation facilitation—and apply a comparative qualitative design to Hungary, Slovakia, Czechia, and Poland. Using a common EU baseline, we compile coded national snapshots from primary legal texts, supervisory documents, and recent scholarship. Results show material cross-country variation in labelling practice, soft-law use, and testing infrastructure: Hungary combines central-bank green programmes with an innovation hub/sandbox; Slovakia aligns with ESMA and runs hub/sandbox, though the green-fintech pipeline is nascent; Czechia applies a principles-based safe harbour and lacks a national sandbox; and Poland relies on a virtual sandbox and binding interpretations with limited soft law. These choices shape approval timelines, retail penetration, and cross-border portability of green-labelled products. We conclude with a policy toolkit: labelling convergence or explicit safe harbours, a cross-border sandbox federation, ESRS/ESAP-ready proportionate disclosures, consolidation of recurring interpretations into soft law, investment in suptech for green-claims analytics, and inclusion metrics in sandbox selection. Full article

The acceleration of financial innovation and pro-crypto regulations in the digital asset space have spurred interest in cryptocurrencies among funds, and institutional and retail investors. Like any risky assets, investment in digital assets offers opportunities in terms of returns and challenges in terms of risk. However, unlike traditional assets, digital assets like cryptocurrencies are highly volatile. Accordingly, applying conventional single-criterion financial metrics for portfolio construction may not be sufficient as the method falls short in capturing the complex, multidimensional risk-return dynamics of innovative financial assets like cryptocurrencies. To address this gap, this study introduces a novel, integrated hybrid Multi-Criteria Decision-Making (MCDM) framework that provides a structured, transparent, and robust approach to cryptocurrency fund selection. The framework seamlessly integrates three well-established operations research methodologies: the Decision-Making Trial and Evaluation Laboratory (DEMATEL), the Analytic Network Process (ANP), and the Vlse Kriterijumsk Optimizacija I Kompromisno Resenje (VIKOR) algorithm. DEMATEL is utilized to map and analyze the intricate causal interdependencies among a comprehensive set of evaluation criteria, categorizing them into foundational “cause” factors and resultant “effect” factors. This causal structure informs the ANP model, which computes precise criterion weights while accounting for complex feedback and dependency relationships. Subsequently, the VIKOR algorithm is invoked to use these weights to rank cryptocurrency fund alternatives, delivering a compromise between optimizing group utility and minimizing individual regret. To illustrate the application and efficacy of the proposed method, a diverse set of 20 cryptocurrency funds is analyzed. From the analysis, it is shown that foundational criteria, such as “Fee (%)” and “Annualized Standard Deviation,” are the primary causal drivers of financial performance outcomes of funds. This proposed framework supports strategic capital allocation in a rapidly evolving domains of digital finance. Full article

As global climate change intensifies, research on low-carbon practices has become a critical component of sustainable tourism development. The carbon emission profile of ski tourism differs significantly from other tourism sectors. Ski resorts have a mountainous terrain and typically maintain relatively high levels of vegetation, endowing them with inherent advantages for pioneering low-carbon and sustainable tourism practices. However, the substantial energy demands associated with artificial snowmaking systems and advanced infrastructure pose significant challenges to reducing carbon emissions in ski resort operations. This study gathers first-hand data on sustainable tourism development in the Chongli ski resort—the region that hosted the 2022 Winter Olympics—through field investigations and interviews with key industry stakeholders. It develops a comprehensive framework accounting for carbon emissions in ski resorts by integrating input–output analysis with enterprise-level data, focusing on four core operational sectors: catering, skiing, wholesale and retail, and leasing and business services. Furthermore, this study examines the coupling relationship between carbon emissions and operating revenue. Using correlation and regression analyses, this study identifies the key drivers of carbon emissions across these operational departments within the ski tourism sector. The results indicate that carbon emissions from these four sectors in the Chongli ski resort exhibit periodic fluctuations with an overall upward trend year by year. Nevertheless, progress in low-carbon development is evident, suggesting that the resort is on a trajectory toward achieving peak carbon emissions and eventual carbon neutrality. The inclusion of natural endowments, market-scale effects, festival and special events, and capital investment in ski tourism collectively serve as crucial drivers for low-carbon sustainability in Chongli. Based on these findings, this study proposes targeted recommendations to support low-carbon sustainable development, offering scientific insights for similar Winter Olympics host cities. This study integrates top-down input–output analysis with bottom-up enterprise data, taking Chongli, the host city of the Winter Olympics, as a timely case study. It constructs a four-dimensional low-carbon development model based on the identification of key natural, social, and economic driving factors, and strengthens the reliability of the conclusion by relying on first-hand field research and operator interview data. Our study provides an analysis of methodological innovation, framework integrity, and solid empirical evidence that accounts for micro-scale carbon emissions in ski resorts. Full article