Search Results (424)

Fan growth serves as a critical performance indicator for the sustainable development of livestreaming e-commerce (LSE). However, existing research has paid limited attention to this topic. This study investigates the unique interactive advantages of LSE over traditional e-commerce by examining how interactivity drives fan growth through the mediating role of user retention and the moderating role of anchors’ facial attractiveness. To conduct the analysis, real-time data were collected from 1472 livestreaming sessions on Douyin, China’s leading LSE platform, between January and March 2023, using Python-based (3.12.7) web scraping and third-party data sources. This study operationalizes key variables through text sentiment analysis and image recognition techniques. Empirical analyses are performed using ordinary least squares (OLS) regression with robust standard errors, propensity score matching (PSM), and sensitivity analysis to ensure robustness. The results reveal the following: (1) Interactivity has a significant positive effect on fan growth. (2) User retention partially mediates the relationship between interactivity and fan growth. (3) There is a substitution effect between anchors’ facial attractiveness and interactivity in enhancing user retention, highlighting the substitution relationship between anchors’ personal characteristics and livestreaming room attributes. This research advances the understanding of interactivity’s mechanisms in LSE and, notably, is among the first to explore the marketing implications of anchors’ facial attractiveness in this context. The findings offer valuable insights for both academic research and managerial practice in the evolving livestreaming commerce landscape. Full article

The integration of artificial intelligence (AI), big data analytics, and blockchain technologies within the digital economy presents transformative opportunities for promoting low-carbon urban development. However, a systematic understanding of how these digital innovations influence urban carbon mitigation remains limited. This study addresses this gap by proposing two research questions (RQs): (1) What are the key success factors for artificial intelligence, big data, and blockchain in urban carbon emission reduction? (2) How do these technologies interact and support the transition to low-carbon cities? To answer these questions, the study employs a hybrid methodological framework combining the decision-making trial and evaluation laboratory (DEMATEL) and interpretive structural modeling (ISM) techniques. The data were collected through structured expert questionnaires, enabling the identification and hierarchical analysis of twelve critical success factors (CSFs). Grounded in sustainability transitions theory and institutional theory, the CSFs are categorized into three dimensions: (1) digital infrastructure and technological applications; (2) digital transformation of industry and economy; (3) sustainable urban governance. The results reveal that e-commerce and sustainable logistics, the adoption of the circular economy, and cross-sector collaboration are the most influential drivers of digital-enabled decarbonization, while foundational elements such as smart energy systems and digital infrastructure act as key enablers. The DEMATEL-ISM approach facilitates a system-level understanding of the causal relationships and strategic priorities among the CSFs, offering actionable insights for urban planners, policymakers, and stakeholders committed to sustainable digital transformation and carbon neutrality. Full article

In the context of eco-friendly e-commerce, understanding the psychological and experiential mechanisms that drive consumers’ online purchasing behavior is essential for promoting sustainable platform development. This study aims to fill a critical gap in the literature by examining how social interaction, entertainment, and sales promotion influence consumers’ purchase intentions through the mediating roles of perceived value and immersive flow experience. Grounded in the Stimulus–Organism–Response (S-O-R) theoretical framework, we developed a structural model and conducted an empirical analysis using survey data collected from 438 online shoppers. Data analysis was conducted using SPSS and AMOS through SEM. The results show that social interaction and sales promotion significantly enhance both perceived value and flow experience, which in turn positively influence consumers’ purchase intentions. However, entertainment exhibits a negative and significant effect on perceived value and does not significantly affect flow experience, indicating that hedonic content may not always translate into perceived usefulness or deep engagement. Moreover, the influence of social interaction on flow experience was also found to be negative and significant, suggesting that not all forms of interaction necessarily lead to immersive experiences. These findings highlight the complex psychological dynamics in digital consumption. This study contributes original insights by integrating psychological engagement mechanisms with the goal of digital sustainability, offering practical implications for online retailers aiming to enhance user engagement and platform longevity through experience-driven strategies. Full article

While the explosive growth in e-commerce stresses urban logistics systems, city planners lack of fine-grained data in order to anticipate and manage the resulting freight flows. Using a three-stage analytical approach combining descriptive zonal statistics, hotspot analysis and different regression modeling from univariate to geographically weighted regression, this study integrates one year of parcel deliveries from a leading courier with open spatial layers of land-use zoning, census population, mobile-signal activity and household income to model last-mile demand across different land use types. A baseline linear regression shows that residential population alone accounts for roughly 30% of the variance in annual parcel volumes (2.5–3.0 deliveries per resident) while adding daytime workforce and income increases the prediction accuracy to 39%. In a similar approach where coefficients vary geographically with Geographically Weighted Regression to capture the local heterogeneity achieves a significant raise of the overall R² to 0.54 and surpassing 0.70 in residential and institutional districts. Hot-spot analysis reveals a highly fragmented pattern where fewer than 5% of blocks generate more than 8.5% of all deliveries with no apparent correlation to the broaden land-use classes. Commercial and administrative areas exhibit the greatest intensity (1149 deliveries per ha) yet remain the hardest to explain (global R² = 0.21) underscoring the importance of additional variables such as retail mix, street-network design and tourism flows. Through this approach, the calibrated models can be used to predict city-wide last-mile demand using only public inputs and offers a transferable, privacy-preserving template for evidence-based freight planning. By pinpointing the location and the land uses where demand concentrates, it supports targeted interventions such as micro-depots, locker allocation and dynamic curb-space management towards more sustainable and resilient urban-logistics networks. Full article

Although product environmental information serves as an effective tool for promoting green consumption which is a critical lever for advancing broader sustainability goals, its varied impacts across product categories (durable goods vs. fast-moving consumer goods) and the underlying mechanisms remain unexplored. Grounded in the theory of consumption values (TCV), this study investigated the heterogeneous effects and mediating pathways of such information through a comparative analysis of representative products: organic milk (fast-moving consumer goods, FMCGs) and energy-efficient air conditioners (durable goods). The results show the following: (1) epistemic value, which exhibits the strongest association with product environmental information, demonstrates significantly different influence patterns between purchases of green durable goods and green FMCGs across both online and offline channels; (2) in the e-commerce context, green FMCG consumption is mainly driven by product environmental information through the mediating effect of conditional value. For green durable goods, product environmental information influences green consumption through multiple pathways including functional value, conditional value, and epistemic value. This study extends the classic theory of consumption values, and the results suggest that differentiated information strategies of emphasizing conditional value for FMCGs and integrating multi-dimensional values for durables can optimize green consumption promotion. Such strategies hold substantial potential to strengthen the green development of the omnichannel retailing sector, reinforcing its contribution to reaching sustainability objectives. Full article

Growing awareness of sustainable development and green consumer concerns is driving the market expansion for green agriculture products. E-commerce live streaming gives rural enterprises a new channel through scenario-building and interaction, while agro-tourism integration combines resources to generate a variety of promotion scenarios. This study examines the effects of external stimuli, including social networks, resource endowment, infrastructure, and the characteristics of e-commerce streamers, on the perception, trust, perceived value, and purchase intention of green consumption. It is based on the SOR (Stimulus–Organism–Response) theoretical model and focuses on e-commerce live streaming in the agriculture-tourism integration scenario. According to a structural equation modeling (SEM) analysis of 350 consumer questionnaires, these external stimuli primarily influence purchase intention through perceived value, trust, and green consumption cognition, with resource endowment having the most significant impact. The effects of infrastructure on perceived value and streamer attractiveness on green consumption cognition are not statistically significant. This research not only broadens the use of the SOR model in the emerging field of agritourism integration but also offers rural businesses theoretical backing and useful guidance to maximize e-commerce live marketing and enhance agritourism integration. Full article

This study aimed to investigate the future trajectories of last-mile delivery (LMD), and their implications for sustainable urban logistics and smart city planning. Through a Delphi-based scenario analysis targeting the year 2030, this research draws on inputs from a two-round Delphi study with 52 experts representing logistics, academia, and government. Four key thematic areas were explored: consumer demand and behavior, emerging delivery technologies, innovative delivery services, and regulatory frameworks. The projections were structured using fuzzy c-means clustering, and analyzed through the Technology Acceptance Model (TAM) and Innovation Diffusion Theory (IDT), supporting a systemic understanding of innovation adoption in urban logistics systems. The findings offer strategic insights for municipal planners, policymakers, logistics service providers, and e-commerce stakeholders, helping align infrastructure development and regulatory planning with the evolving needs of last-mile logistics. This approach contributes to advancing resilient, low-emission, and inclusive smart city ecosystems that align with global sustainability goals, particularly those outlined in the UN 2030 Agenda for Sustainable Development. Full article

Background: The growth of parcel volumes in urban areas, largely driven by e-commerce, has increased the complexity of pickup and delivery operations. To meet demands for cost efficiency, flexibility, and sustainability, CEP (Courier, Express, and Parcel) operators increasingly outsource segments of their last-mile networks. Methods: This study proposes a novel multidimensional cost model for outsourcing, integrating five key variables: transport unit type (parcel/pallet), service phase (pickup/delivery), vehicle category, powertrain type, and delivery point type. The model applies correction coefficients based on internal operational costs, further adjusted for location and service quality using a bonus/malus mechanism. Results: Each cost component is calculated independently, enabling full transparency and route-level cost tracking. A real-world case study was conducted using operational data from a CEP operator in Bosnia and Herzegovina. The model demonstrated improved accuracy and fairness in cost allocation, with measurable savings of up to 7% compared to existing fixed-price models. Conclusions: The proposed model supports data-driven outsourcing decisions, allows tailored cost structuring based on operational realities, and aligns with sustainable last-mile delivery strategies. It offers a scalable and adaptable tool for CEP operators seeking to enhance cost control and service efficiency in complex urban environments. Full article

In response to the challenges of urbanization, digitalization, and the e-commerce surge intensified by the COVID-19 pandemic, Smart Urban Logistics (SUL) has become a key framework for addressing last-mile delivery issues, congestion, and environmental impacts. This study introduces a System Dynamics (SD)-based approach to investigate how urban logistics and access management policies may interact. At the center, there is a Causal Loop Diagram (CLD) that illustrates dynamic interdependencies among fleet composition, access regulations, logistics productivity, and environmental externalities. The CLD is a conceptual basis for future stock-and-flow simulations to support data-driven decision-making. The approach highlights the importance of route optimization, dynamic access control, and smart parking management systems as strategic tools, increasingly enabled by Industry 4.0 technologies, such as IoT, big data analytics, AI, and cyber-physical systems, which support real-time monitoring and adaptive planning. In alignment with the Industry 5.0 paradigm, this technological integration is paired with social and environmental sustainability goals. The study also emphasizes public–private collaboration in designing access policies and promoting alternative fuel vehicle adoption, supported by specific incentives. These coordinated efforts contribute to achieving the objectives of the 2030 Agenda, fostering a cleaner, more efficient, and inclusive urban logistics ecosystem. Full article

As environmental issues become increasingly prominent, the sustainable practices of enterprises, especially measures at the product level, have garnered widespread attention from scholars. Although numerous studies have explored suppliers’ sales strategies for green products, they often overlook the scenario where suppliers simultaneously sell both green and non-green products.This study focuses on the sales mode selection strategies of suppliers when providing green and non-green products through e-commerce platforms. Utilizing a game model, we analyze the equilibrium strategies between suppliers and e-commerce platforms, and conduct sensitivity analyses to evaluate the impact of key parameters on decision-making. The results reveal that there are significant differences in the strategic preferences of suppliers and e-commerce platforms. However, when commission rates are moderate and green products incur high production costs, these preferences tend to align, leading to Pareto optimal outcomes. Additionally, our findings demonstrate that adopting differentiated sales modes for the two product types can effectively mitigate the problem of double marginalization, thereby enhancing the efficiencyof supply chains. These insights provide valuable guidance for e-commerce platform managers and suppliers in making decisions on sales models for managing multiple types of products. Full article

Driven by the rapid expansion of e-commerce in China, there is a growing demand for high-efficiency, sustainability-oriented logistics solutions in rural regions, particularly for the time-sensitive distribution of perishable agricultural commodities. Traditional logistics systems face considerable challenges in these geographically complex regions due to limited infrastructure and extended travel distances. To address these issues, this study proposes an intelligent cooperative delivery system that integrates automated drones with conventional trucks, aiming to enhance both operational efficiency and environmental sustainability. A mixed-integer linear programming (MILP) model is developed to account for the diverse terrain characteristics of rural China, including forest, lake, and mountain regions. To optimize distribution strategies, the model incorporates an improved Fuzzy C-Means (FCM) algorithm combined with a hybrid genetic simulated annealing algorithm. The performance of three transportation modes, namely truck-only, drone-only, and truck–drone integrated delivery, was evaluated and compared. Sustainability-related externalities, such as carbon emission costs and delivery delay penalties, are quantitatively integrated into the total transportation cost objective function. Simulation results indicate that the cooperative delivery model is especially effective in lake regions, significantly reducing overall costs while improving environmental performance and service quality. This research offers practical insights into the development of sustainable intelligent transportation systems tailored to the unique challenges of rural logistics. Full article

Amid the global push for agricultural green transformation, sustainable agriculture requires not only technological innovation but also market mechanisms that effectively incentivize green practices. Agricultural e-commerce is increasingly viewed as a potential driver of green technology diffusion among farmers. However, the extent and mechanism of e-commerce’s influence on farmers’ green production remain underexplored. Using survey data from 346 rural households in Inner Mongolia, China, this study develops a conceptual framework of “e-commerce participation–green cognition–green adoption” and employs propensity score matching (PSM) combined with mediation analysis to evaluate the impact of e-commerce participation on green technology adoption. The empirical results yield four main findings: (1) E-commerce participation significantly promotes the adoption of green production technologies, with an estimated 29.52% increase in adoption. (2) Participation has a strong positive effect on water-saving irrigation and pest control technologies at the 5% significance level, a moderate effect on straw incorporation at the 10% level, and no statistically significant impact on plastic film recycling or organic fertilizer use. (3) Compared to third-party sales, the direct e-commerce model more effectively promotes green technology adoption, with an increase of 21.64% at the 5% significance level. (4) Green cognition serves as a mediator in the relationship between e-commerce and green adoption behavior. This study makes contributions by introducing e-commerce participation as a novel explanatory pathway for green technology adoption, going beyond traditional policy-driven and resource-based perspectives. It further highlights the role of cognitive mechanisms in shaping adoption behaviors. The study recommends that policymakers subsidize farmers’ participation in e-commerce, invest in green awareness programs, and support differentiated e-commerce models to enhance their positive impact on sustainable agricultural practices. Full article

In the digital age, e-commerce has become a critical part of modern economies, shaping global economic growth and the pursuit of the Sustainable Development Goals (SDGs). This study uses robust statistical methods to explore the complex relationships between traditional trade, e-commerce, and key economic and sustainability indicators. The General Linear Model (GLM), factor analysis, and linear regression reveal that conventional trade remains vital for GDP growth, even though e-commerce clearly influences SDG performance. The study emphasizes the catalytic role of e-commerce in advancing sustainability by showing how treating it as a dependent variable speeds up SDG progress through Brown, Holt, and ARIMA forecasting models. Additionally, cluster analysis uncovers a strong link between higher SDG scores and increased e-commerce activity, with countries scoring better on sustainability often having more companies in the digital economy and earning more online. This research provides a comprehensive understanding of how e-commerce can support global sustainability goals, along with integrated policy recommendations that promote digital transformation and long-term environmental and social resilience. Full article

In the context of accelerating digitalization, this study investigates how electronic commerce performance is influenced by Web 2.0 instruments in the 27 EU member states. Analyzing literature reviews and performing our own bibliometric review, we identified a gap related to the measurable economic results of e-commerce. The scope of this study was to analyze the relationship between Web 2.0 tools and the level of turnover generated by e-commerce, applying robust econometric models based on panel data regression with random effects and fixed effects (Arellano–Bond). The results highlight that the online paid advertisement and social media usage variables have significant, positive effects on e-commerce performance, confirming the first and second hypotheses. “Use the enterprise’s blog or microblogs” and “use of multimedia content sharing websites” do not influence enterprises’ total turnover from e-commerce sales to a valid and statistically significant extent. Thus, the third and fourth hypotheses are not confirmed by the results of the research conducted, possibly due to limited innovation and platform ownership in Europe. This study makes a notable empirical and methodological contribution, embedding digital sustainability in the analysis, which implies that the findings can be used for updating e-commerce policies. Full article

Trade-in programs have become a vital mechanism for promoting sustainable consumption and reducing negative impacts on the environment, gaining substantial support from branders, e-platforms, and consumers in recent years. Concurrently, the emergence of professional recyclers has provided firms with viable alternatives for the outsourcing of recycling processes. To investigate the optimal leadership and recycling model with respect to trade-in operations, this study examines the strategy selection in a platform-based supply chain under a resale model. A two-period game-theoretic framework is developed, encompassing four models: self-recycling and outsourcing models under the leadership of the brander or platform. The main findings are as follows: (1) In markets characterized by a low consumer price sensitivity, both branders and platforms tend to choose the self-recycling model to capture the closed-loop value. In contrast, in highly price-sensitive markets, both parties exhibit a preference for “free-riding” strategies. (2) Once the recycling leader is determined, adopting a self-recycling model can lead to a relative win–win outcome in high price sensitivity contexts. (3) With a short product iteration cycle, both the brander and platform should strategically lower their prices in the first period, sacrificing short-term profits to enhance trade-in incentives and maximize long-term gains. (4) When the brander leads the recycling process, they should consider reusing the resources derived from old products; however, in platform-led models, the brander can only consider reusing the recycled resources in a low price sensitivity market. This study provides strategic insights for the sustainable development of the supply chain through the analysis of a game between a brander and an e-commerce platform, enriching the literature on CLSCs through integrating trade-in leadership selection and the choice to outsource, offering theoretical support for dynamic pricing strategies over multi-period product lifecycles. Full article