Search Results (8)

This study examines how different types of experienced harm influence trust in sellers and platforms in secondhand, platform-mediated markets. Drawing on attribution theory, we distinguish between fulfillment harm and integrity harm and investigate how these two forms of harm differentially affect seller trust and platform trust. Using data from the Consumer Market Evaluation Index on secondhand marketplaces, we find that both fulfillment and integrity harm are negatively associated with seller trust and platform trust compared to no-harm experiences. When both types of harm occur together, trust deterioration becomes more pronounced. Importantly, fulfillment harm is primarily associated with lower seller trust, whereas integrity harm is more strongly related to platform trust. These findings indicate that trust redistribution depends on attributional evaluations regarding causal locus and controllability. This study contributes to the existing literature by demonstrating how attribution processes allocate trust among multiple market actors and by revealing how different types of failures are attributed to these market actors. Moreover, the findings provide practical guidance for platform governance and seller behavior by highlighting the importance of targeted safeguards in sustaining trust in platform-mediated marketplaces. Full article

With the increasing prominence of sustainable consumption and the rising influence of Generation Z in the fashion market, secondhand fashion e-commerce platforms have become essential carriers of green fashion. Although AI-assisted recommendation mechanisms are widely embedded in these platforms, their psychological and behavioral effects on users’ continuous use and social engagement remain insufficiently examined. To address this gap, this study incorporates the Stimulus–Organism–Response (SOR) framework to investigate the psychological reaction pathways and behavioral intentions of Generation Z users within Human-AI Collaboration-enabled green e-commerce environments. Three AI-driven service stimuli—Human-AI Collaborative Recommendation Perception, AI Interaction Transparency, and Perceived Personalization—were conceptualized as stimulus variables; Psychological Immersion, Emotional Triggering, Cognitive Engagement, and Platform Trust were modeled as organism variables; and Continuous Use Intention and Social Sharing Intention served as behavioral response variables. Based on 498 valid samples analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), the results demonstrate strong empirical support for all proposed hypotheses. Specifically, AI-driven stimuli significantly and positively influence psychological responses, which subsequently strengthen users’ continuous usage and social sharing intentions. This research provides theoretical insights for developing Human-AI Collaboration-enabled service systems that balance efficiency and emotional resonance on green e-commerce platforms, and offers practical implications for promoting sustainable fashion values among younger consumers. Full article

Digital platforms in fashion e-commerce are progressively shaping sustainable consumption practices. This research explores the interplay between consumer behaviors toward recycled and second-hand fashion, and the adoption of digital platform-driven innovations. The analysis is based on a structured questionnaire and an online survey of 1000 consumers conducted in 2025, employing a combination of descriptive and inferential statistical techniques, including both cluster and factor analysis. The findings suggests that demographic factors—particularly age, education, and gender—significantly shape consumer attitudes toward digital innovations in fashion e-commerce apps. The analysis also confirms that the perceived effectiveness of AI and AR tools is significantly correlated with an increased interest in circular fashion options, including second-hand marketplaces and recycled clothing. The study emphasizes the strategic importance of platform features in fostering conscious fashion choices, thereby offering practical insights for retailers aiming to harmonize technological innovation with sustainability goals. Full article

With the rise of sustainable innovation, digital platforms have emerged as key facilitators in the second-hand e-commerce recycling market. This study investigates the entry strategies of profit-oriented and ESG-driven platforms, focusing on their sustainable innovation efforts, entry conditions, and cooperation strategies with recyclers in both monopolistic and duopolistic recycling markets. By developing and analyzing a two-stage Stackelberg model, we derive several key managerial and theoretical insights. First, in a monopolistic market, we delineate the sustainable innovation cost thresholds necessary for platform entry. While both platform types contribute to enhancing recycling volume, consumer surplus, and social welfare, their entry conditions remain mutually exclusive, reflecting their fundamentally different sustainability approaches. A profit-oriented platform can only enter when sustainable innovation costs are low, whereas an ESG-driven platform requires higher levels of innovation investment to balance consumer surplus, environmental benefits, and profitability. Second, in a duopolistic market, we explore three distinct cooperation strategies for profit-oriented and ESG-driven platforms: (1) exclusive cooperation with a low-expertise recycler, (2) exclusive cooperation with a high-expertise recycler, and (3) simultaneous cooperation with both recyclers. We further identify the optimal cooperation strategy based on entry feasibility, profit maximization, and the conditions necessary to achieve a “win-win” outcome. This study sheds light on how profit-oriented and ESG-driven digital platforms strategically enter the recycling market through sustainable innovation, offering insights into their cooperation strategies, market competition, and broader implications for sustainable platform ecosystems. Full article

This paper develops a novel government reserve strategy, employing a blockchain-supported second-hand E-commerce platform, specifically designed to mitigate the depreciation and expiration of disaster relief supplies. Utilizing the newsvendor model and convex optimization techniques, this study evaluates the efficacy of a rotational strategy for optimal pre-positioning of supplies, considering the dynamic conditions of supply chain performance. Additionally, the paper demonstrates how blockchain technology significantly enhances the traceability of supplies, which is crucial for effective supply management. Empirical data analysis reveals that exceeding a critical price threshold on the platform not only augments the government’s optimal reserve levels but also substantially decreases operational costs. In scenarios where the supply chain is well coordinated, optimal reserve quantities are affected by variables such as the likelihood of disaster events, the success rate of sales, and a supply traceability index. This research extends the application of blockchain and E-commerce technologies within disaster management supply chains and offers new insights and practical approaches for improving E-commerce practices in this context. Full article

The rapid development of China’s e-commerce industry has led to the rise of China’s second-hand car e-commerce. With the increasingly rich trust theory and the rapid development of e-commerce platforms, the issue of online consumer trust has attracted more and more scholars’ attention. This paper takes China’s B2C second-hand car e-commerce platforms as an example, combines the second-hand car research conclusions and consumer trust theory, and conducts a systematic study on the formation of consumer trust in second-hand car e-commerce platforms. Based on the trust of individual consumers, system environment, website/APP and platform companies, this paper explores the influencing factors of consumer trust and constructs the influencing factors model of trust formation. The empirical study was conducted by using the structural equation model and multiple regression to verify the degree of fitting of the theoretical hypothesis and the model. The research results have a certain reference value for the development of second-hand car e-commerce platforms. Full article

Online secondhand resale platforms are a booming industry involving the growing recognition of various economic, environmental, and recreational benefits in buying and selling used items. This preliminary study explores technology-based strategies for online secondhand platforms, which contributed to the resale industry’s steady growth and digital transformation. Through a variety of literature, this study established a basis for developing research on technological innovations in online resale platforms. A mixed method was used to collect both quantitative and qualitative data to investigate and understand the features of resale e-commerce. Case studies of four online secondhand resale platforms specializing in general goods and fashion helped identify a variety of technological strategies that were later analyzed based on the technology acceptance model (TAM). Survey data from respondents in their twenties and thirties living in South Korea indicated features that promote safe transactions, engaging user experience and user interface design, and individual compatibility as most effective in influencing users’ resale platform usage. Features that involve high technology, such as virtual reality and machine learning, had the least impact on users’ usage. Data gathered from follow-up interviews showing the recurring theme of unfamiliarity with the technological features corroborated the survey findings. Analyzing qualitative data from expert interviews generated key concepts in future trends in online resale platform strategies, including effective data management. Based on this study’s findings, the digitalization and onlineization of the online secondhand resale industry are likely to continue with the implementation of various strategies that contribute to users’ perceptions of usefulness, ease-of-use, and enjoyment, increasing users’ satisfaction and, hence, the actual usage of these platforms. The proliferation of secondary e-commerce will facilitate a shared culture that values sustainable consumption in online platforms and promote sustainability in the retail industry. Full article

Web Content Management Systems (WCMS) play an increasingly important role in the Internet’s evolution. They are software platforms that facilitate the implementation of a web site or an e-commerce and are gaining popularity due to its flexibility and ease of use. In this work, we explain from a tutorial perspective how to manage WCMS and what can be achieved by using them. With this aim, we select the most popular open-source WCMS; namely, Joomla!, WordPress, and Drupal. Then, we implement three websites that are equal in terms of requirements, visual aspect, and functionality, one for each WCMS. Through a qualitative comparative analysis, we show the advantages and drawbacks of each solution, and the complexity associated. On the other hand, security concerns can arise if WCMS are not appropriately used. Due to the key position that they occupy in today’s Internet, we perform a basic security analysis of the three implement websites in the second part of this work. Specifically, we explain vulnerabilities, security enhancements, which errors should not be done, and which WCMS is initially safer. Full article