Search Results (24)

Recently, the pre-positioned warehouse mode has gained popularity among fresh-product e-commerce, due to its proximity to customers, flexibility, and low operation and maintenance costs. However, product diversity and perishability cause higher inventory and transportation costs, and warehouse and distribution problems hinder the sustainability of the pre-positioned warehouses. This paper considers such key factors as product diversity, food spoilage, and transportation mode and investigates the warehousing and distribution strategy for fresh-product e-commerce’s central warehouse and pre-positioned warehouse. A warehousing and distribution two-stage model for the central warehouse and pre-positioned warehouse is proposed with the objective function, which minimizes the inventory maintenance cost, spoilage cost, and transportation cost, and is solved based on a genetic algorithm. The results serve as a reference for the replenishment and allocation decisions on different product categories in the pre-positioned warehouse mode and centralized purchase decisions at the central warehouse. Full article

The multi-depot vehicle routing problem with soft time windows (MDVRPSTW) has long been a focus in both academic and industrial circles. This paper proposes a deep reinforcement learning framework designed to enhance the efficiency and quality of MDVRPSTW solutions, addressing the limitations of traditional heuristic algorithms in large-scale complex scenarios. The framework first transforms the mathematical model into a sequential decision-making problem through a Markov decision process, then extracts path selection strategies using an encoder–decoder architecture based on attention mechanisms and graph neural networks, and employs unsupervised reinforcement learning for model training. Test results on the Solomon benchmark dataset demonstrate that for small-scale problems (N = 20), our method reduces solving time by over 96% compared to comparative algorithms, with the objective value difference from the generalized variable neighborhood search (GVNS) being less than 9%. For medium-to-large scale problems (N = 50/100), our method achieves a 27.7 to 96.3 percent improvement over GVNS, maintaining stable solution times within 3 to 10 s. Compared to exact algorithms and meta-heuristic methods, our approach reduces computational costs by 2–3 orders of magnitude while demonstrating strong adaptability to variations in the number of depots and vehicles. In summary, this method significantly outperforms baseline models in both solution quality and computational efficiency, providing an efficient end-to-end solution for MDVRPSTW in complex scenarios. Full article

Wet markets remain a cornerstone of fresh food retail in Chinese cities, continuously evolving alongside urbanization. However, the drivers and implications of their transformation at the city level remain underexplored. Drawing on government documents and survey data from Nanjing and Suzhou, this study reveals that China’s wet market evolution is characterized by incremental semi-formalization and upgrading, preserving their essential role in the food supply chain without displacing other retail formats. This transformation reflects shifting government attitudes, strategic urban planning for food security, and the effective integration of public and private interests. The hybrid governance model, which combines public oversight with private operation, has enhanced wet markets’ resilience, ensuring affordability, freshness, and social interaction. Their adaptability underscores a broader lesson: inclusive urban food systems require soft–hard infrastructure synergy, where physical upgrades coexist with social functions. In this paper, we argue that wet markets exemplify social infrastructure: they are not merely food hubs but spaces fostering civic life, cultural continuity, and equitable access. Their co-evolution with supermarkets and e-commerce challenges the “supermarketization” thesis, highlighting the importance of policy flexibility and localized governance. Our findings offer insights for Global South cities grappling with food system transitions, emphasizing the need to balance modernization with the preservation of informal economies’ social fabric. Full article

The growth of e-commerce has led to a rapid increase in user-generated content (UGC), attracting scholars’ attention as a new data source for investigating customer requirements. However, existing requirements analysis methods fail to integrate three critical requirement indicators: stated importance, derived importance, and performance. Using only one or two of these indicators inevitably has its limitations. This paper proposes a novel framework for analyzing and prioritizing customer requirements based on multi-source UGC. First, customer requirements are extracted from online reviews and questions & answers using non-negative matrix factorization. Next, aspect-level sentiment analysis and multi-source data fusion are employed to calculate dual importance and performance. Specifically, we developed an improved importance–performance analysis (IPA) model, named dual importance–performance analysis (Du-IPA), which integrates the three indicators to classify requirement types in a 3D cube with corresponding improvement strategies. Finally, by combining the three indicators, an improved prospect value and PROMETHEE-II are proposed using prospect theory to prioritize CRs for product service improvement. The effectiveness of the proposed method is demonstrated through a case study of fresh food in online retail. Full article

Consumer satisfaction critically determines the operational sustainability of fresh food e-commerce platforms, yet integrated investigations combining multi-source data remain scarce. This study develops a theory–data fusion framework to identify key satisfaction drivers in China’s fresh e-commerce sector. Utilizing Python-based crawlers, we extracted 1252 online reviews of Aksu apples from a certain fresh produce e-commerce platform alongside 509 validated questionnaires. Through systematic literature synthesis, three core dimensions—perceived value (price–performance balance), platform experience (interface usability), and perceived quality (freshness assurance)—were operationalized into measurable indicators. The final structural equation model reveals that perceived value, platform experience, and perceived quality all have significant positive impacts on consumer satisfaction. This study pioneers a methodological paradigm integrating computational text mining (Octopus Collector + SPSS Pro) with traditional psychometric scales, achieving superior model fit (RMSEA = 0.023, CFI = 0.981). These findings empower platforms to implement a precision strategy. The validated framework provides a theoretical basis for omnichannel consumer research while addressing the data-source bias prevalent in prior studies. Full article

With the acceleration of fresh food e-commerce development, cold chain logistics for agricultural products has increasingly become a research hotspot. However, limited by the number of orders accepted by enterprises, many cold chain transportation vehicles for agricultural products struggle to reach a full load. This undoubtedly increases transportation costs for agricultural product cold chain logistics enterprises. In order to reduce the cost of transportation and increase the profit of enterprises, this paper will adopt the strategy of building enterprise coalition based on cooperative game theory. By increasing the loading rate of transportation vehicles, it will increase the profit of enterprises. First, utilizing the minimization of overall dissatisfaction among players in profit allocation after coalition participation as the objective function, a model of the equal division contribution values of the trapezoidal fuzzy number will be constructed, which will be used as the profit allocation model for the players. Then, the solution of the model will be provided, and the properties including symmetry are analyzed. Second, by improving the loading rate of cold chain transport vehicles as the key and combining various parameters in the transportation stage of agricultural product cold chain logistics, the coalition profit will be calculated. Finally, using the solution of the equal division contribution value of the trapezoidal fuzzy number in the cooperative game as the allocation strategy, the obtained profit will be distributed to each enterprise participating in the coalition. The results show that when dealing with cooperative profit allocation problems in similar scenarios, the solutions of the equal division contribution value of the trapezoidal fuzzy number are highly reliable and adaptable. The method presented in this paper can not only increase the profit of enterprises but also minimize the overall dissatisfaction of all enterprises with the allocation result. Full article

The paper aims to analyze the consumer joint choice behavior on fresh food purchase channels and terminal delivery services during major public health events, with the purpose of revealing the underlying influencing factors and behavioral characteristics. First, based on random utility maximization theory, the cross-nested logit model is formulated, which takes into account the influence of socioeconomic attribute factors, service attribute factors, risk perception attribute factors and trust perception attribute factors. Second, a questionnaire survey is conducted, and the obtained data are used to estimate the model parameters and perform an elasticity analysis of the utility variables. The parameter estimation results demonstrate that in the context of major public health events, consumers consider adjusting their attitudes toward e-commerce platforms first when the utility variables are altered, and fresh food purchase channels are easily replaced for consumers who choose unmanned equipment home delivery. The elasticity analysis results suggest that consumers are more willing to buy fresh food through community group-buying channels, are more sensitive to the convenience of the purchase process and are less concerned with delivery time. Although person-to-person contact increases the risk of infection, consumers still prefer attended terminal delivery services. Furthermore, consumers least agree with the effectiveness of body temperature detection methods in public places but feel that an effective way to increase consumer trust in enterprises is to strengthen personnel protection measures. Full article

Logistics service quality (LSQ) plays a vital role in providing excellent customer experience, particularly in e-commerce. Using mobile devices for food and fresh product orders is very common, but delivering these products is very challenging. In this study, we aim to evaluate the factors influencing logistics service quality (LSQ) in the context of fresh product e-commerce. The relevant literature was reviewed and a preliminary survey among field experts was conducted to establish the proposed LSQ scale. A qualitative study was carried out on fresh product e-commerce customers. A survey involving 222 participants was analyzed, and an LSQ evaluation scale was formed and evaluated scientifically and empirically. Research results showed that reliability, convenience, freshness, and personnel contact quality are the four key dimensions of the LSQ scale in the e-commerce platform for fresh and perishable items. The results of the study can help the managers of e-commerce companies to understand the LSQ criteria that determine customer satisfaction and consequently make the appropriate LSQ improvements. Full article

Given the widespread adoption of fresh food e-commerce, this study aimed to explore the service quality attributes influencing utilitarian value, hedonic value, and impulsive buying behavior. A survey was conducted with 263 participants who had experience in purchasing fresh food online. Their responses were analyzed to test hypotheses using structural equation modeling. The findings reveal significant influences of information quality, ease of use, and problem resolution on utilitarian value. Additionally, ease of use, problem resolution, and trendiness were found to impact hedonic value. Problem resolution was a quality factor that affected both practical value and hedonic value, and its influence was found to be greater than that of other service quality factors. Hedonic value was also found to significantly affect impulsive buying behavior; however, utilitarian value did not exhibit a significant impact on impulsive buying behavior. The results provide useful theoretical and managerial implications in the field of fresh food e-commerce business. Full article

In the context of an evolving socio-economic landscape and rising living standards, the online market for fresh products, encompassing fruits, vegetables, meats, dairy, and eggs, has seen substantial growth, necessitating sophisticated logistics for e-commerce home delivery. This study tackles the distinct challenges of fresh product delivery, which demand rigorous adherence to climate conditions and product mix during transport, significantly influencing the operational strategies and scheduling of delivery platforms. To address these challenges, a comprehensive mathematical model was developed to optimize fresh food home delivery scheduling, focusing on reducing spoilage rates and accommodating the dynamic impact of environmental temperature changes. The model posits assumptions of a consistent and ample supply of fresh goods, standard initial quality loss, and efficient porter assignment for multi-category order combinations. It introduces three objective functions, targeting the minimization of fresh food loss, maximization of customer satisfaction, and reduction of distributor costs. The efficacy of the model and its genetic-algorithm-based solution method was assessed through numerical analysis and case studies, illustrating that the model enhances delivery efficiency and service quality across varying temperature conditions. This substantiates the critical role of environmental temperature management in optimizing fresh food delivery, offering a robust framework for advancing logistical operations in the perishable goods sector and ensuring quality and efficiency in fresh food e-commerce delivery. Full article

During the coronavirus disease 2019 (COVID-19) pandemic, non-face-to-face e-commerce has become a significant consumer channel for customers to buy fresh food. However, little is known about customer opinion changes in fresh food e-commerce (FFEC) products and services during COVID-19. This study investigated the changes in expectations and preferences of FFEC customers on products and services before and during the pandemic from online reviews through a text mining approach. We divided the pandemic into two phases, acute and recovery, and found that eight attributes affect customers’ opinions. Some logistic service-related attributes gained customer attention during the acute phase, but product-related attributes gained more attention in the recovery phase. Customers showed a great level of forgiveness on many attributes during the acute phase, but customers’ dissatisfaction was expressed during the recovery phase. Finally, the results of the comparative importance–performance analysis provide improvement strategies for FFEC and help optimize their resource allocation of FFEC and enhance sustainable operation capacity in the case of a crisis. Full article

Reducing farmland abandonment is crucial for food security. While the association between e-commerce proliferation and farmland abandonment at the village level has been discussed, the correlation at the farming household level remains unexplored. Utilizing 2020 survey data from 3831 rural households across 10 Chinese provinces, this study develops an “e-commerce–household–farmland abandonment” framework to explore the co-occurrence of e-commerce engagement with farmland abandonment, using econometric models. The findings reveal that e-commerce engagement significantly increases farmland abandonment, with implicit and explicit rates rising by 10.3% and 28.5%, respectively. It also shifts household incomes from planting to forestry, animal husbandry, and fisheries, leading households to reallocate labor away from agriculture, thereby intensifying abandonment. However, land transfer can alleviate this co-occurrence. This study also explores the variation in the association between e-commerce participation and farmland abandonment in relation to agricultural subsidies, economic development, and the presence of family farms. By elucidating the dynamics at the household level, this research offers fresh perspectives for developing countries to safeguard food security by curbing farmland abandonment. Full article

The agricultural supply chain (ASC) in the hinterland refers to the entire post-harvest process of processing and distributing agricultural products in rural or secluded areas to be brought to big city markets. This scheme involves various stakeholders (farmers, trading centers, consumers), processes (logistics, storage, monitoring), and infrastructure (traffic and road systems, negative environmental emissions) to ensure the efficient flow of agricultural products from farms to consumers. The quality of life (QoL) in the hinterland can improve with the introduction of disruptive technologies, but no comprehensive studies have explored the QoL of individuals involved in the ASC–socioeconomic system of hinterland communities. This study elucidated and compared the diversified impacts of disruptive technologies brought by the Industrial Revolution 4.0 to the agricultural supply chain and their impacts on food security, sustainability, and climate change mitigation through the analysis of the related literature. This study also mapped out the role of disruptive technologies in the QoL of hinterland communities, particularly with respect to the farmers, trading center workers, and consumers. Points of discussion emerged with respect to precision agriculture, the Artificially Intelligent Internet of Things, big data analytics, blockchain, artificial intelligence, cyber-physical systems, robotics, automation, and e-commerce, and how these enabling technologies enhance fresh food supply and distribution and deliberately affect stakeholders’ life quality indexes through the analysis of situational case studies in India, South America, Malaysia, China, and Europe. The identification of these points of discussion was also achieved purely based on research performed on the related literature. The positive impacts of these technologies, such as the boosting of efficiency and the ensuring of a steady supply of fresh produce, ultimately improve the overall QoL. The technical insights from the studies were synthesized to develop new frameworks for QoL anchored in the agricultural supply chain (AgQoL) in the hinterland, and a six-dimensional network emphasizing the two trifectas of techno-socioenvironmental needs was established. Food-producing communities with a relatively high AgQoL should support food security in the region. Full article

The intense competition among fresh food e-commerce platforms in China has reduced the market share of the leading firms. This study aims to establish a model framework based on brand knowledge, perceived value, brand trust, and purchase intention to improve the market competitiveness of fresh food e-commerce platforms. Based on the analysis of 475 questionnaires using SmartPLS software, the results indicate that the established model framework provides an excellent explanation and forecasting (R² = 45.5%) for consumers’ intentions to purchase fresh food. The path analysis results of this study show that there are significant positive effects among the model variables. Among antecedent variables, brand image has the greatest influence on perceived value, perceived value has the greatest influence on brand trust, and brand trust has the most significant impact on purchase intention. Furthermore, perceived value and brand trust have noteworthy mediating and serial mediating effects on brand knowledge and purchase intention. These findings have important implications for theoretical and managerial practices in the context of fresh food e-commerce platforms, providing insights on how to enhance customer purchase intentions. Full article

One of the key indicators to measure the sustainability and resilience of a city during a public health crisis is how well it can meet the daily needs of its residents. During the COVID-19 lockdown in Shanghai in 2022, e-commerce shopping and delivery became the most important method for ensuring the city’s material supplies. This article uses the distribution data of a fresh e-commerce platform’s pre-warehouse and static population distribution data to establish a basic material supply system evaluation model for the city and explore its resilience potential. Focusing on the central urban area of Shanghai, this study uses a population heat map with geographic coordinates to reflect the static distribution of residents and obtains the distribution data of the e-commerce pre-warehouses. Using kernel density analysis, the relationship between the pre-warehouses and the residents’ needs is established. Through analysis, it was found that the supply capacity of fresh food in different areas of Shanghai during the lockdown could be categorized as insufficient, adequate, or excessive. Based on these three categories, improvement strategies were proposed. Finally, this article suggests establishing a scientific supply security system to promote urban sustainability and prepare for future challenges. Full article