Search Results (41)

This study examines how the initiation of monetary compensation and the sincerity of apologies influence customers’ repurchase intentions after receiving products with minor defects, and how these effects are moderated by consumer pickiness and the e-store’s reputation. Two scenario-based, between-subjects online experiments were conducted in China via the Wenjuanxing online survey platform, with participants voluntarily taking part in exchange for monetary compensation. We propose that consumers have a higher repurchase intention when online customer service initiatively offers monetary compensation (vs. passive vs. no compensation) and that the effect of monetary compensation modes can be enhanced by a serious apology from customer service. Building on these findings, Study 1 (n = 330) reveals that picky consumers are more sensitive to the enhanced effect of initiative monetary compensation on repurchase intentions under serious apologies. Moreover, Study 2 (n = 537) confirms that consumers are more stringent in their expectations of high-reputation stores, whereas low-reputation stores can achieve similar positive effects with casual apologies that high-reputation stores only obtain through serious apologies. This study provides theoretical support for the importance of the initiation of actions and sincerity in service recovery and offers guidance for businesses dealing with picky consumers. Full article

Urbanization and the rapid growth of e-commerce have significantly increased delivery volumes in cities, creating challenges in terms of cost, efficiency, and sustainability in last-mile delivery (LMD). To address these challenges, this paper proposes an innovative methodological framework for selecting optimal delivery strategies in urban environments, grounded in the principles of collaboration. The framework integrates an Extended FullEx method, developed to calculate criteria weights while accounting for expert reputation based on education and experience, with the MARCOS multi-criteria decision-making (MCDM) method used to rank delivery strategies. The Extended FullEx method proposed in this paper differs from the original FullEx by providing two improvements. The first concerns the introduction of the normalization procedure in the calculation of experts’ reputations, while the second addresses the different scoring of educational degrees, providing a more precise mathematical basis for the process. Four collaborative delivery strategies are evaluated against twelve sustainability-related criteria identified through an extensive literature review. The proposed framework is applied to a real-life case study in Novi Sad, Republic of Serbia. Results indicate that the most suitable delivery strategy is a hybrid model that combines the use of a consolidation center with smaller urban delivery hubs, providing practical insights for enhancing the sustainability and efficiency of urban delivery. This study contributes both methodologically, by advancing MCDM techniques, and practically, by offering decision-makers a comprehensive tool that integrates subjective expert knowledge and objective criteria assessment in the selection of sustainable LMD solutions. Full article

With the rise of live-streaming services on e-commerce platforms, AI-powered virtual idols have demonstrated tremendous application potential and thus possess high commercial value. From the perspective of psychological distance, this study adopts the Stimulus–Organism–Response (S–O–R) theoretical framework to construct a research model of “AI-powered virtual idols–psychological distance–impulsive buying intention”. The model aims to explore how AI-powered virtual idols promote digital natives’ impulsive buying intention in the context of e-commerce live streaming. Furthermore, this study examines the moderating effect of technology readiness on the relationship between AI-powered virtual idols and psychological distance. The findings reveal that the level of intelligence of AI-powered virtual idols—including interactivity, anthropomorphism, homogeneity, and reputation—enhances digital natives’ impulsive buying intention by reducing psychological distance. For digital natives with lower technology readiness, the effect of AI-powered virtual idols in narrowing psychological distance is more pronounced. These findings enrich AI-driven consumer behavior models from a theoretical perspective and offer theoretical support and practical insights for developing AI-empowered digital marketing strategies tailored to the psychological traits and technological adaptability of digital natives. Full article

(1) Background: With the deep integration of e-commerce and video technology, live-streaming marketing has emerged globally and maintained rapid growth. However, most of the current research on live-streaming e-commerce marketing focuses on merchants’ sales strategies and consumers’ purchase intentions, and there is relatively little research related to the risks of live-streaming e-commerce marketing. Nevertheless, with the development of live-streaming e-commerce marketing and its integration with technologies such as artificial intelligence and virtual reality (VR), live-streaming e-commerce marketing still faces challenges such as unclear subject responsibility, difficulty in verifying the authenticity of marketing information, and uneven product quality. It also harbors problems such as the ethical misbehavior of AI anchors and the excessive beautification of products by VR technology. (2) Methods: This study systematically analyzes the scenarios of live-streaming marketing to elucidate the mechanisms of risk formation. Utilizing fault tree analysis (FTA) and risk checklist methods, risks are identified based on the three core elements of live-streaming marketing: “people–products–scenes”. Subsequently, the Delphi method is employed to refine the initial risk indicator system, resulting in the construction of a comprehensive risk indicator system comprising three first-level indicators, six second-level indicators, and 16 third-level indicators. A hesitant fuzzy multi-attribute group decision-making method (HFMGDM) is then applied to calculate the weights of the risk indicators and comprehensively assess the live-streaming marketing risks in live broadcast rooms of three prominent celebrity anchors in China. Furthermore, a detailed analysis is conducted on the risks associated with the six secondary indicators. Based on the risk evaluation results, targeted recommendations are proposed. This study aims to enhance consumers’ awareness of risk prevention when conducting live-streaming transactions and pay attention to related risks, thereby safeguarding consumer rights and fostering the healthy and sustainable development of the live-streaming marketing industry. (3) Conclusions: The results show that the top five risk indicators in terms of weight ranking are: Ethical Risk of the AI Anchor (A4), VR Technology Promotion Risk (F3), Anchor Reputation (A1), Product Quality (D1), and Logistics Distribution Service Quality (D2). The comprehensive live-streaming marketing risk of each live broadcast room is Y > L > D. Based on the analysis results, targeted recommendations are provided for anchors, MCN institutions, merchants, supply chains, and live-streaming platforms to improve consumer satisfaction and promote sustainable development of the live-streaming marketing industry. Full article

This study aims to describe and assess the impact of critical infrastructure (CI) cybersecurity issues on the sustainable development of smart cities. This study highlights the integration of PayTech systems into the broader CI landscape, highlighting their impact on maintaining economic stability and ensuring the smooth operation of city services. Key companies within smart regions, particularly those operating in the payment industries, are essential to maintaining the functionality of critical services. These companies facilitate the processing of services provided to citizens, enabling access to vital municipal services. As key players in the PayTech and online e-commerce sectors, they form a crucial part of modern critical infrastructure, operating within an ever-evolving digital environment. This study examines the recovery processes employed after cyberattacks, focusing on the differing perspectives of internal and external professionals. It identifies significant differences in the perceptions of recovery strategies among internal stakeholders, such as investor relations (IR) teams, reputation management (RM) experts, and Chief Information Security Officers (CISOs), who represent critical infrastructure companies. Additionally, it explores the roles of external auditors, who provide impartial emergency support and perform specialized recovery tasks. Importantly, this study underscores the current attitudes toward future information security strategies and their influence on the financial recovery and reputation of reliable companies following cyber incidents. This research contributes to the existing knowledge by shedding light on the perspectives of both a company’s internal and external specialists involved in the recovery process and cyber resilience strategies in critical infrastructure sectors. Full article

Reputation is shaped depending on factors such as the quality of products and services offered by a brand to its stakeholders, its reliability, and its innovative aspect in the eyes of stakeholders. The sustainability of a brand reputation depends on the brand creating a positive perception by fulfilling its social responsibilities and maintaining this perception in the long term. In this study, the brand reputation of Hewlett-Packard (HP) computers is evaluated through customer reviews. The data set in the study consists of 2012 customer reviews obtained from Hepsiburada, one of the most widely used e-commerce platforms in Turkey. Sentiment analysis and text mining artificial intelligence methods were used in the study. For sentiment analysis, the Naive Bayes method, which is one of the machine learning methods, was used, and the comments were divided into three groups as positive, negative, and neutral. In the study, 82% of the customer comments were positive, 11% were negative, and 7% were neutral. The fact that most of the comments consist of positive sentiments shows that HP Computer has a positive reputation in the eyes of stakeholders consisting of customers. Comments consisting of negative and neutral emotions show the aspects that the brand needs to improve. In the study, the text mining method emphasises the prominent features of the brand in the comments. This study makes an important contribution to the reputation assessment of brands and to ensuring sustainable brand reputation. Full article

Driven by the increase in mobile applications, this study tests a conceptual model which links antecedents of Food delivery applications (FDApps) and their effect on electronic trust (eTrust) and electronic loyalty (eLoyal). By adopting a quantitative approach, we employed a self-administered questionnaire distributed among 501 regular users of FDApps. Partial least squares path modeling was used to test seven hypotheses including direct, moderating, and mediating effects. The findings reveal that eTrust significantly contributes to fostering eLoyal. Additionally, eTrust mediates the relationships between electronic privacy (ePriv), electronic security (eSec), electronic payment (ePay), usability (ULY), electronic innovativeness (eInnov), and eLoyal. Moreover, reputation (RTN) has a positive moderating effect on the relationship between eTrust and eLoyal. The research explores the core elements linked to FDApps, with the goal of improving their business and marketing strategies while increasing consumer satisfaction, thereby boosting repurchase intentions. Therefore, it provides FDApps with insights on the required elements linked to a higher eLoyal. 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

The widespread use of data in e-commerce has facilitated the implementation of different pricing strategies for platforms and merchants. However, the excessive use of algorithms for differential pricing has sparked discussions about fairness and price discrimination, disrupting the platform trading system. To address this challenge, we adopt an evolutionary game approach to analyze the evolutionary strategies of all parties from the perspective of platform CSR. It is based on a special type of e-commerce platform trading in which major merchants have data analytics capabilities. We construct an evolutionary game model considering reputation and punishment, explore the impact of different situations and factors on the system’s evolutionary stability strategy, and conduct its verification via simulation experiments. The results show that long-term reputation is the internal driving force for platforms to fulfill responsibilities. The joint punishment of collusion is the external binding force. Consumer complaints are key to restricting merchants’ integrity operation. Moreover, penalties imposed by e-commerce platforms can help eradicate price discrimination. This study provides a new perspective to solve price discrimination in the digital era. Measures based on reputation and punishment can guide platforms to fulfill other social responsibilities. Full article

Brand reputation directly influences customer trust and decision-making. A good reputation can lead to greater customer loyalty, commitment, and advocacy. This study aims to understand the effects of brand reputation on customer trust and loyalty and to determine how brands can protect their reputation. This study, which was conducted on the iPhone 11 sample by obtaining statistical data from customer reviews, can be adapted and used by researchers and companies that want to measure brand reputation. In this study, customer reviews for the iPhone 11 phone on the Trendyol e-commerce site, the largest e-commerce platform in Turkey, are analyzed using sentiment analysis and machine learning methods. While 85 percent of customers are satisfied with the iPhone 11, 13 percent are dissatisfied with it. The neutral comment rate of 2 percent indicates that some customers do not express a clear positive or negative opinion about the product. In the comments of customers who bought the iPhone 11, there are those who express satisfaction with the quality, technical features, performance, and price/performance ratio of the product, as well as those who express significant complaints about delivery, quality, price, and customer service. Neutral comments generally focus on the product itself, price, quality, shipping, and packaging, and make informative evaluations. A sustainable reputation is based on the extent to which an organization embraces ethical principles, social responsibility, and sustainable practices throughout its operations and business relationships. Brands can improve, protect, and increase their brand reputation by considering and analyzing the thoughts and feelings of their customers. For this, they should develop policies and strategies to reinforce their strong features and improve their faulty and deficient features. Full article

Fraud exists on both legitimate e-commerce platforms and illicit dark web marketplaces, impacting both environments. Detecting fraudulent vendors proves challenging, despite clients’ reporting scams to platform administrators and specialised forums. This study introduces a method to differentiate sellers reported as scammers from others by analysing linguistic patterns in their textual traces collected from three distinct cryptomarkets (White House Market, DarkMarket, and Empire Market). It distinguished between potential scammers and reputable sellers based on claims made by Dread forum users. Vendor profiles and product descriptions were then subjected to textometric analysis for raw text and N-gram analysis for pre-processed text. Textual statistics showed no significant differences between profile descriptions and ads, which suggests the need to combine language traces with transactional traces. Textometric indicators, however, were useful in identifying unique ads in which potential scammers used longer, detailed descriptions, including purchase rules and refund policies, to build trust. These indicators aided in choosing relevant documents for qualitative analysis. A pronounced, albeit modest, emphasis on language related to ‘Quality and Price’, ‘Problem Resolution, Communicationand Trust’, and ‘Shipping’ was observed. This supports the hypothesis that scammers may more frequently provide details about transactions and delivery issues. Selective scamming and exit scams may explain the results. Consequently, an analysis of the temporal trajectory of vendors that sheds light on the developmental patterns of their profiles up until their recognition as scammers can be envisaged. Full article

Textual emotion recognition (TER) has significant commercial potential since it can be used as an excellent tool to monitor a brand/business reputation, understand customer satisfaction, and personalize recommendations. It is considered a natural language processing task that can be used to understand and classify emotions such as anger, happiness, and surprise being conveyed in a piece of text (product reviews, tweets, and comments). Despite the advanced development of deep learning and particularly transformer architectures, Arabic-focused models for emotion classification have not achieved satisfactory accuracy. This is mainly due to the morphological richness, agglutination, dialectal variation, and low-resource datasets of the Arabic language, as well as the unique features of user-generated text such as noisiness, shortness, and informal language. This study aims to illustrate the effectiveness of large language models on Arabic multi-label emotion classification. We evaluated GPT-3.5 Turbo and GPT-4 using three different settings: in-context learning, emotional stimuli prompt, and fine-tuning. The ultimate objective of this research paper is to determine if these LLMs, which have multilingual capabilities, could contribute to enhancing the aforementioned task and encourage its use within the context of an e-commerce environment for example. The experimental results indicated that the fine-tuned GPT-3.5 Turbo model achieved an accuracy of 62.03%, a micro-averaged F1-score of 73%, and a macro-averaged F1-score of 62%, establishing a new state-of-the-art benchmark for the task of Arabic multi-label emotion recognition. Full article

E-commerce platforms incorporate reputation systems that allow buyers to rate sellers after transactions. However, existing reputation systems face challenges such as privacy leakage, linkability, and multiple rating attacks. The feedback data can inadvertently expose user information privacy because they reveal the buyers’ identities and preferences, which deters a significant number of users from providing their ratings. Moreover, malicious actors can exploit data analysis and machine learning techniques to mine user privacy from the rating data, posing serious threats to user security and trust. This study introduces ARS-Chain, a pioneering and secure blockchain-driven anonymous reputation-sharing framework tailored for e-commerce platforms. The core of ARS-Chain is a dynamic ring addition mechanism with linkable ring signatures (LRS), where the number of LRS rings is dynamically added in alignment with the evolving purchase list, and LRS link tags are constructed with the LRS rings and item identifiers. Further, a consortium blockchain is introduced to store these anonymous ratings on e-commerce platforms. As a result, ARS-Chain ensures full anonymity while achieving cross-platform reputation sharing, making rating records unlinkable, and effectively countering multiple rating attacks. The experimental results confirm that ARS-Chain significantly enhances user information privacy protection while maintaining system performance, having an important impact on the construction of trust mechanisms for e-commerce platforms. Full article

The general requirements of China’s rural revitalization strategy are industrial prosperity, ecological livability and rich life. However, the traditional livestock breeding model has struggled to balance the dual requirements of production development and ecological protection, and it is urgent to inject new impetus and explore new development paths. At present, e-commerce has become a bridge between pastoral areas and cities, herdsmen and consumers. E-commerce participation is not only an important starting point for herdsmen to increase the added value and profit space of livestock products, but also an effective way to change the original breeding behavior based on the premise of destroying grassland. Therefore, this paper presents an in-depth study on the issue of e-commerce enabling grassland ecological restoration, aiming to provide more scientific and effective guidance for e-commerce to be used to achieve a win–win situation in economy and ecology. Therefore, based on the data of 271 herdsmen in pastoral areas of Inner Mongolia, we used the OLS model and the two-stage least squares (2SLS) method to identify the direct impact of herdsmen’s e-commerce participation on grassland utilization pressure. The empirical results show that e-commerce participation can significantly decrease the grassland utilization pressure. The conclusion was still valid after alleviating endogeneity and conducting a robustness test. The results of a mechanism analysis suggest that the reduction effect of e-commerce participation on grassland utilization pressure is mainly due to price incentive, reputation incentive and place identity. Subjective norms can strengthen the inhibitory effect of e-commerce participation on grassland utilization pressure. Furthermore, a heterogeneity analysis demonstrates that e-commerce participation has a better, decreased impact on the grassland utilization pressure on the banners of China’s rural e-commerce demonstration county program. Under a counterfactual assumption, if herdsmen who can participate in e-commerce choose not to do this, their grassland utilization pressure will increase. Full article

Entrepreneurship is the readiness and ability of an organization, primarily a new business, to develop, organize, and conduct its business to make a profit despite uncertainties. Social commerce (s-commerce) assists consumers to buy products online. However, few studies have investigated the influence of entrepreneurship and online platform capability on consumers’ online purchase decisions. Academicians, researchers, and practitioners are also increasingly interested in understanding how the s-commerce environment influences entrepreneurship and online purchase decisions. Against this background, this study set out to examine this phenomenon. Using information adoption models and contagion theory as well as the input from the literature review, a theoretical model was developed. Such a model was tested with a factor-based PLS-SEM approach by analyzing the responses of 342 respondents. The results find that electronic WOM (e-WOM) credibility, predicted by online e-WOM content and platform credibility, and impacted by online reputation, could significantly influence consumers’ online purchase decisions. The study also finds that both positive and negative valance of eWOM as well as entrepreneurship significantly influence eWOM credibility, which in turn positively influences consumers’ purchase decisions when using online platforms. Full article