Search Results (58)

E-commerce growth has reshaped consumer behavior and retail services, driving parcel demand and challenging last-mile logistics. Existing research predominantly relies on survey data and global regression models that overlook intra-urban spatial heterogeneity in shopping behaviors. This study bridges this gap by analyzing e-commerce demand’s spatial distribution from a retail service perspective, identifying key drivers, and evaluating implications for omnichannel strategies and logistics. Utilizing waybill big data, spatial analysis, and multiscale geographically weighted regression, we reveal: (1) High-density e-commerce demand areas are predominantly located in central districts, whereas peripheral regions exhibit statistically lower volumes. The spatial distribution pattern of e-commerce demand aligns with the urban development spatial structure. (2) Factors such as population density and education levels significantly influence e-commerce demand. (3) Convenience stores play a dual role as retail service providers and parcel collection points, reinforcing their importance in shaping consumer accessibility and service efficiency, particularly in underserved urban areas. (4) Supermarkets exert a substitution effect on online shopping by offering immediate product availability, highlighting their role in shaping consumer purchasing preferences and retail service strategies. These findings contribute to retail and consumer services research by demonstrating how spatial e-commerce demand patterns reflect consumer shopping preferences, the role of omnichannel retail strategies, and the competitive dynamics between e-commerce and physical retail formats. Full article

Background: As e-commerce expands and delivery services diversifies, understanding the factors that shape consumer preferences becomes critical to designing efficient and sustainable urban logistics. This study examines how perceived walkability influences consumers’ preferences for shopping channels (in-store or online) and delivery methods (home delivery versus pickup points). Method: The analysis is based on structural equation modeling and utilizes survey data collected from 444 residents of Belo Horizonte, Brazil. Results: The findings emphasize the importance of walkability in supporting weekday store visits, encouraging pickup for online purchases and fostering complementarity between different modes of purchase and delivery services. Perceived walkability positively affects the preference to buy in physical stores and increases the likelihood of using pickup points. Educated men, particularly those living in walkable areas, are the most likely to adopt pickup services. In contrast, affluent individuals and women are less likely to forgo home delivery in favor of pickup points. Conclusions: The results highlight the role of perceived walkability in encouraging in-person pickup as a sustainable alternative to home delivery, providing practical guidance for retailers, urban planners, and logistics firms seeking to align consumer convenience with sustainable delivery strategies. Full article

The rapid expansion of online grocery shopping has intensified the need for strategically located distribution hubs that ensure efficient and sustainable operations. Traditional location models emphasize economic and logistical factors but often neglect energy efficiency and environmental sustainability. This paper proposes a hybrid decision-making model that integrates the analytic hierarchy process (AHP) and the spherical fuzzy technique for order of preference by similarity to ideal solution (SFTOPSIS) to address the complexities of delivery hub location selection. The AHP is used to determine the relative importance of key decision-making criteria, including cost, accessibility, infrastructure, competition, and sustainability, while SFTOPSIS ranks the candidate locations based on their proximity to the ideal solution. Spherical fuzzy sets allow for a more nuanced treatment of uncertainty, improving decision-making accuracy in dynamic environments. The results demonstrate that this hybrid approach effectively manages incomplete and uncertain data, delivering a robust ranking of candidate locations. By incorporating sustainability as a key factor, this study provides a structured and adaptive framework for businesses to optimize logistics operations in the post-pandemic landscape. The proposed methodology not only enhances decision-making in location selection but contributes to the development of more resilient and sustainable supply chain strategies. Full article

Autonomous delivery services offer significant cost-saving benefits for logistics and e-commerce companies while helping mitigate environmental issues and urban traffic congestion. As these services become increasingly prevalent in China, understanding how user participation influences adoption decisions is crucial. This study analyzes attitudes and intention to use toward autonomous delivery by integrating factors such as sustainability and customer participation within the technology acceptance model. Notably, prior research has rarely included consumers aged 50 and older, despite their growing engagement with online shopping and delivery services in China. To address this gap, the present study incorporates data from this demographic to enhance representativeness. Employing SEM combined with multi-group analysis through AMOS 24.0, this study examined 526 valid survey responses. The results demonstrate that attitudes toward autonomous delivery systems are positively shaped by perceived usefulness, ease of operation, sustainability features, self-efficacy beliefs, and customer engagement levels. Moreover, user attitudes emerge as a significant predictor of behavioral intention to adopt such services. Additionally, technology-related anxiety and personal innovativeness levels were found to moderate the attitude–intention linkage. These insights establish a theoretical framework to guide future advancements in autonomous delivery system development, marketing strategy optimization, and academic exploration within this domain. Full article

Consumer behavior has changed considerably over time. In recent decades, people have used resources at a rate that exceeds the total consumed throughout history. This paper aims to address the determinants of the smartphone purchase decision, emphasizing gender differences, price influence, and previous online shopping experience. The methodology used combines a bibliometric review of the literature to identify major trends in consumer behavior research and a quantitative research survey that provides insight into consumer behavior in the smartphone purchase process. The survey highlights brand preferences, purchase patterns, product selection criteria, and the influence of socioeconomic factors on the purchase decision, identifying the determinants of online versus physical store purchase decisions among young consumers in the northeastern, east, and southeastern regions of Romania. Thus, our analysis aims to identify the variables influencing consumer preferences and to assess the statistical significance of these differences using quantitative methods and relevant statistical tests. The collected data came from a valid sample of 456 respondents for the general analysis and 271 valid cases for the online shopping analysis. The analysis shows that gender is a significant predictor of online purchase decisions, with men being 2.65 times more likely to purchase a smartphone online than women. The collected data were analyzed using t-tests, Chi-square tests, and logistic regression to assess the influence of variables on online smartphone purchase intention. Full article

Background: Extensive research highlights the economic benefits of collaboration among parcel delivery service providers, yet mutually advantageous cooperative arrangements remain limited in Hungary’s online shopping sector. Service providers typically prefer to operate independently rather than cooperate with competitors. However, the COVID-19 pandemic significantly altered industry dynamics, leading to increased collaboration. Methods: Against this backdrop, this study explores two key research questions. First, it examines the role of economic narratives in shaping market dynamics. Second, it investigates the cognitive biases influencing decision-makers during the pandemic, based on an analysis of Hungary’s parcel delivery sector. Semi-structured interviews were conducted with key actors in the logistics industry, and the data were analyzed using abductive thematic analysis. Results: The findings reveal that specific economic narratives, such as those emphasizing efficiency and safety, indirectly influenced market mechanisms during the COVID-19 pandemic. Notably, the shift in consumer demand towards contactless parcel lockers created new incentives for collaboration. Additionally, this study demonstrates that decision-makers exhibited cognitive biases such as risk aversion, which affected their willingness to cooperate. Conclusions: The research concludes that strong economic incentives can override these biases, fostering collaboration among service providers. Full article

The COVID-19 pandemic has reshaped various aspects of life, influencing consumer behaviors and economic activities worldwide. This paper delves into the shifts in consumer preferences and shopping patterns for gardening products and services during and after the pandemic era. Through nationwide online surveys conducted from 2020 to 2022, we analyze changes in time spent and expenses on gardening and identify key demographic and pandemic-related factors influencing these behaviors during the pandemic era. We employed both generalized and standard ordered logistic regression models to assess the impact of various variables on the ordinal dependent variable. The findings reveal a significant surge in both time spending on home gardening activities and money invested in gardening products and services, especially among individuals who considered gardening beneficial for well-being and as a family activity. Notably, the preference for online shopping and mail delivery for gardening supplies emerged as a prominent trend during the pandemic, accompanied by a significant increase in the purchase of fruit plants, vegetable plants, and seeds, indicating that primary motivation for gardening was self-food consumption. These insights provide valuable guidance for businesses in the green industry, informing production, marketing practices, and economic recovery efforts post-COVID-19. Full article

Education and knowledge are essential for fostering sustainable living, which helps to protect our planet and promote health and socio-economic development. This study investigated sustainable living knowledge and behaviours among the general Italian population. A 40-item questionnaire was created to assess knowledge, awareness, and attitudes in eight domains: house, energy, food, personal care, shopping, transportation, waste, water and other consumption. The questionnaire was distributed online between January and June 2023. A multiple logistic regression model was performed to assess the relationships between all the variables surveyed. Among the 420 people who participated (66% female, median age of 39 years), 76% had a higher-level education degree and 72% had never participated in a sustainability initiative. Knowledge about sustainability was lower in the domains of shopping (70.6%) and transportation (85.0%). The fewest behaviours carried out/products used were found in the domains of personal care (31.3%) and transportation (47.8%). Positive associations were found between the use/adoption of sustainable items and knowledge about sustainability (aOR: 1.38, CI: 1.35–1.41) and previous inherent educational activities (aOR: 1.04, CI: 1.03–1.06). Age, region of residence and urbanisation context were factors that discontinuously influenced the implementation of the considered items for transportation and food. Improvements are needed to close the gap between knowledge and action, especially in the domain of personal care. A better understanding of the factors that play a role in the non-use of transportation will help to develop measures to promote sustainability and societal wellbeing. Full article

Omni-channel retailing is a novel form that combines online, offline, and mobile channels to provide consumers with a seamless shopping experience. Nevertheless, the implementation of omni-channel retailing necessitates effective logistics support. Hence, the quality of logistics services is critical for omni-channel retailing services. This research aims to investigate logistics service quality (LSQ) and its impact on consumer satisfaction by combining the decomposed SERVQUAL framework, Kano model and hierarchical regression analysis. A total of 460 valid responses were obtained. Building upon the SERVQUAL framework, this study presents a comprehensive framework for evaluating omni-channel retail logistics service quality. Using the Kano model, 11 logistics service quality attributes were categorised into three categories: must-be, one-dimensional, and attractive, based on their respective impact on satisfaction. The results of the hierarchical regression analysis confirm that the attributes belonging to the must-be category exert the most significant influence on satisfaction. The findings add to theoretical studies of omni-channel retailing LSQ and provide insights for omni-channel retailers and logistics service providers. Full article

This study leverages approximately 7500 reviews from Skytrax to explore the determinants of airport service quality and their influence on passenger recommendations. The dataset includes various features such as terminal cleanliness, terminal seating, terminal signs, food and beverages, airport shopping, WiFi connectivity, and airport staff. The research employs a comprehensive methodology encompassing statistical data analysis, predictive modelling, and interaction effects analysis. The descriptive analysis of time-series data highlighted trends and fluctuations in service quality and recommendations, providing insights into temporal dynamics. Multiple machine learning models, including logistic regression, Random Forest, SVM, KNN, Gradient Boosting, and Neural Networks, were developed in this study and cross-validated for airport recommendation based on Skytrax’s online reviews. Among others, Gradient Boosting emerged as the most accurate model with an 88.15% mean accuracy. Interaction effects revealed significant combined influences, such as terminal cleanliness and terminal seating, on passenger recommendations. This multifaceted approach offers robust insights into factors influencing airport recommendations and guides improvements in airport management to enhance passenger satisfaction. Future work will focus on a general-purpose machine learning framework and its toolbox development for airport service quality analysis based on online reviews from various sources. Full article

Online retail of agricultural products is an emerging form of online shopping that has enormous value for researching sustainable agricultural product logistics and the sustainability of e-commerce. By reviewing these practices in China, this paper summarizes three models of online retail of agricultural products: community group buying, prepositioned warehousing, and a mixed model in which the former two are carried out simultaneously. This paper considers the uncertainty of demand and applies the newsboy model to obtain the expected profit function of the three models. The paper proves that the objective functions of the optimization models are all convex functions of the supply capacity. The optimal supply strategy and the expression for each business model are then derived. Next, the intervals for enterprises to choose the profit-optimal business model are given and visually demonstrated through graphs. These findings lead to managerial insights: in economically underdeveloped regions, it is appropriate for enterprises to conduct community group buying businesses; in economically developed regions, it is appropriate for enterprises to conduct prepositioned warehouse businesses; and in regions with average economic development, it is appropriate for enterprises to conduct both businesses. Finally, this paper verifies the optimal supply strategy for the online retail model for agricultural products through numerical experiments and sensitivity analyses for different cost parameters. Full article

The rapid growth of e-commerce has led to an increase in the number of product returns in supply chains, which is both environmentally and economically challenging. E-commerce companies need to effectively manage product returns, as this has a direct impact on their reputation and consumer experience. Reducing returns is key to maintaining sustainable practices for online product sales. A significant increase in e-commerce transactions is also evident in Indonesia, which is the fourth largest country in the world. Despite the very large size of the market, research on e-commerce in the business-to-customer (B2C) market in Indonesia is underrepresented in the literature. The purpose of this paper is to identify key factors from the customer perspective that influence product returns in reverse logistics in Indonesian e-commerce. The novelty of this study stems from the focus on the customer perspective on product returns in the B2C market when shopping online and the spatial scope. Due to the uncertainty inherent in multi-criteria decision making, the analytic hierarchy process (AHP) method was used to rank factors and potential solutions derived from a critical literature review. As a result, the study provides a ranking of factors and alternatives for managing e-commerce returns in Indonesia. The results show that among Indonesian e-commerce customers, product quality (QP) was rated the highest, while (Pu) was rated the lowest. In terms of the alternatives that are the most suitable for improving the customer experience of e-commerce product returns in Indonesia, a clear returns policy (CRP) scored the highest, while the merchandise catalog (Cat) was rated as the lowest priority. Full article

As a product of the development of e-commerce over a specific period of time, the “new retail model” breaks the barriers between the traditional retail industry and e-commerce. Supported by Internet technology, it builds a new business model of “physical store + e-commerce + logistics” through the integration of online, offline, and logistics, which also leads to a great change in consumer behavior. Therefore, in order to meet consumer demand and achieve the long-term development of shopping malls, while taking into account the fair allocation of urban space resources, the indicators and methods of shopping mall site selection evaluation in the new retail era will be significantly different from traditional shopping mall site selection decisions. In this paper, the Wuhan East Lake Hi-Tech Zone is selected as the research object, and a comprehensive AHP-GIS assessment model is proposed. By investigating the impact of consumers’ behavioral changes on shopping mall location in the new retail era, a suitability evaluation system containing eight evaluation indicators is constructed, and the weights of each factor are determined using hierarchical analysis. At the same time, GIS is used to process the spatial analysis of the indicators, and combined with the weights of the factors, superposition analysis and quantitative research are carried out. Finally, based on the correlation analysis between ratings and customer flow, the suitability evaluation results are further supported in order to provide a more objective and scientific basis for the location of shopping malls from the perspective of the change in consumer behavior under the new retail model, and to put forward universal suggestions for the construction and development of shopping malls in the future. Full article

This study aims to provide valuable insights into consumer preferences for delivery services in online shopping in Chile. The COVID-19 pandemic has accelerated the evolution of delivery and logistics services, leading to increased competition among online stores. Chile, with its highly digitally enabled population and a competitive landscape of online retailers, serves as an ideal reference case for Latin America. By analyzing key delivery attributes such as delivery time, order arrival time range, compensation policies for delivery delays, and delivery prices, we offer valuable insights into consumer behavior. These insights will, in turn, inform the formulation of effective strategies within the online shopping industry. We examine the following aspects: (a) The willingness of consumers to pay for the service attributes; (b) The relative importance assigned to these attributes by consumers; and (c) The relationship between consumer preferences and socioeconomic characteristics. Using Multinomial Logit Models and a database from a Discrete Choice Experiment, we have discovered that the most significant attributes of delivery service are the time until product arrival and the existence of compensation in case of delivery delays. Additionally, we found that consumers are willing to pay more for the same delivery service if the product is large, as large products generally have higher prices. Furthermore, we observed that delivery time preferences vary by gender and for small products, and price sensitivity varies according to educational level, household size, and socioeconomic status. To the best of our knowledge, no previous research of this kind has been conducted for Chile. Full article

The rise of the e-commerce industry has markedly changed the global economy, providing customers with unparalleled access to goods and services. This study empirically examines online shoppers’ perceptions and preferences, focusing on their experiences with last-mile delivery (LMD) services and its impact on their shopping behaviour. This research employs machine learning classification and regression models for a large-scale analysis of customers’ responses, collected using an online survey in the main cities in Saudi Arabia, which is experiencing rapid e-commerce growth amidst a broader digital transformation. The findings highlight a strong consumer preference for timely LMD services, typically within a day of purchase, while noting dissatisfaction with exceedingly early delivery windows. The research emphasises the need to address customer dissatisfaction with delivery services to retain clientele, as many may switch retailers without informing the retailers. Additionally, a considerable trend towards preferring digital over cash-on-delivery payment methods was observed among online shoppers. Overall, this study provides valuable insights into the significant influence of LMD services on customer satisfaction and behaviour in the e-commerce sector. The use of robust machine learning models has revealed critical factors that can guide retailers and LMD providers in enhancing service delivery and customer experience, contributing to the broader discourse on e-commerce logistics efficiency and customer satisfaction. Full article