Online Q&A communities rely on mutual help, yet users vary in whether they return the help they receive. To investigate this phenomenon, this study draws on equity theory to distinguish between two dimensions of help received in virtual communities: volume and effort. Using a large-scale longitudinal dataset from Stack Overflow, this study employs fixed-effects models to test the hypotheses. The results show that receiving high-effort help is significantly more effective in motivating subsequent knowledge contributions than receiving a larger volume of help. Moreover, prior help provision moderates these effects: prior contributions amplify the negative impact of receiving a large volume of help while attenuating the positive impact of receiving high-effort help. This study offers new insights into current research by revealing the double-edged nature of received help in shaping voluntary knowledge sharing in online Q&A communities. These insights are also timely in the era of generative AI, shedding light on how users respond to received help in virtual communities.
Travel blind box is a product that combines blind boxes with traditional travel products on e-commerce platforms. E-commerce platforms leverage the mystery of travel blind boxes to attract a large number of consumers. However, this sense of mystery increases consumers' quality concerns regarding travel blind boxes. This study aims to clarify how mystery influences consumers' quality concerns, explaining the underlying mechanism based on Attribution Theory and Prospect Theory. Through an empirical study using a questionnaire method (N = 321), the following findings were obtained (1) mystery positively predicts quality concerns, (2) risk perception mediates the relationship between mystery and quality concerns, (3) personal luck belief moderates the path from mystery to quality concerns, as well as the path from mystery to risk perception.
Travel blind box is a product that combines blind boxes with traditional travel products on e-commerce platforms. E-commerce platforms leverage the mystery of travel blind boxes to attract a large number of consumers. However, this sense of mystery increases consumers' quality concerns regarding travel blind boxes. This study aims to clarify how mystery influences consumers' quality concerns, explaining the underlying mechanism based on Attribution Theory and Prospect Theory. Through an empirical study using a questionnaire method (N = 321), the following findings were obtained (1) mystery positively predicts quality concerns, (2) risk perception mediates the relationship between mystery and quality concerns, (3) personal luck belief moderates the path from mystery to quality concerns, as well as the path from mystery to risk perception.
As AI-powered chatbots become increasingly integrated into organizations, understanding the motivational factors that influence their continued use is essential for maximizing return on investment. While previous research has emphasized functional attributes, less attention has been paid to individual motivational orientations. This study integrates goal orientation theory into chatbot continuance research to explain how motivational dispositions shape evaluative pathways toward sustained use. Performance-approach orientation enhances perceptions of novelty value and hedonic attitude and maintains a direct positive link to continuance intention. In contrast, performance-avoidance orientation does not directly affect continuance; instead, it indirectly influences sustained use by strengthening utilitarian cognitive attitudes and performance expectancy. These distinct pathways demonstrate the pivotal role of goal orientation as an antecedent, driving either affective or utilitarian mechanisms in sustained chatbot use.
As AI-powered chatbots become increasingly integrated into organizations, understanding the motivational factors that influence their continued use is essential for maximizing return on investment. While previous research has emphasized functional attributes, less attention has been paid to individual motivational orientations. This study integrates goal orientation theory into chatbot continuance research to explain how motivational dispositions shape evaluative pathways toward sustained use. Performance-approach orientation enhances perceptions of novelty value and hedonic attitude and maintains a direct positive link to continuance intention. In contrast, performance-avoidance orientation does not directly affect continuance; instead, it indirectly influences sustained use by strengthening utilitarian cognitive attitudes and performance expectancy. These distinct pathways demonstrate the pivotal role of goal orientation as an antecedent, driving either affective or utilitarian mechanisms in sustained chatbot use.
In this article, the authors examine pertinent literature on digital platforms and serve multiple objectives. First, they present the notion of Digital Platform Business (DPB), which synthesizes diverse perspectives of platform researchers across disciplines. They then define DPB to precisely identify and conceptually distinguish digitally incarnated platform businesses from other businesses discussed in the extensive literature. Furthermore, the authors construct a morphological framework of the literature pertaining to DPBs, capturing its scope and variety in terms of dimensions and options. The framework identified 10 dimensions with corresponding options that succinctly capture the main themes studied. By organizing studies based on structural and thematic elements, the authors identified gaps, unexplored intersections, and potential areas for innovation. For researchers, the framework aids in thoroughly comprehending the notion of DPB as examined in the literature and promotes future study. For practitioners, it provides them with a thorough guide on designing and scaling DPBs.
The study utilizes online reviews to predict hospital service outcomes by employing an optimization framework that incorporates four key healthcare dimensions: patient care, medical treatment, facilities, and staff efficiency. This approach combines real-time, user-generated feedback with advanced analytical techniques, providing a robust model for assessing hospital performance. The model predicts Bayesian inference to determine posterior distributions for parameters, including previous information and estimating uncertainty in predictions. The duality optimization method improves predicted accuracy by reducing error while accounting for parameter uncertainty. The hospital review dataset is derived from 5,548 hospital reviews in Thailand. The outcome of this study offers practical insights for hospital administrators and policymakers and enhances hospital operations, patient satisfaction, and strategic decision-making in the Thai healthcare sector by integrating probabilistic modeling with optimization techniques.
The study aims to assess factors influencing the adoption of digital financial services by micro, small, and medium enterprises (MSMEs) and to evaluate the organizational benefits they derive from fintech integration. The framework for this study was the combination of the technology–organization–environment and technology acceptance model; survey questionnaire was used to collect data from 52 business owners and managers at MSMEs in Saudi Arabia. The variables considered in this study included relative advantage, security, trust, complexity, technology readiness, top management support, organizational competence, competition intensity, vendor quality, government engagement, regulation, ease of use, regulation, and perceived usefulness that affect fintech adoption by MSMEs in Saudi Arabia. The findings show that all studied variables positively affect the adoption of fintech services by MSMEs in Saudi Arabia, except for complexity, security, trust, and vendor quality. Additionally, participating organizations generally have a favorable perception of the fintech services provided.
The study aims to assess factors influencing the adoption of digital financial services by micro, small, and medium enterprises (MSMEs) and to evaluate the organizational benefits they derive from fintech integration. The framework for this study was the combination of the technology-organization-environment and technology acceptance model; survey questionnaire was used to collect data from 52 business owners and managers at MSMEs in Saudi Arabia. The variables considered in this study included relative advantage, security, trust, complexity, technology readiness, top management support, organizational competence, competition intensity, vendor quality, government engagement, regulation, ease of use, regulation, and perceived usefulness that affect fintech adoption by MSMEs in Saudi Arabia. The findings show that all studied variables positively affect the adoption of fintech services by MSMEs in Saudi Arabia, except for complexity, security, trust, and vendor quality. Additionally, participating organizations generally have a favorable perception of the fintech services provided.
The study formulated a research model grounded in Expectation Confirmation Theory, specifically examining the role of e-commerce experience in customer satisfaction and loyalty within the context of Pinduoduo. Hypothesized relationships were established between the core dimensions of e-commerce experience and the e-commerce customer engagement triad. To analyze the gathered data and evaluate the research hypotheses, structural equation modeling was employed. The research findings indicate that the core dimensions of e-commerce experience, namely e-commerce user interface quality, information quality, security risk avoidance perception, and privacy perception, exert positive influences on both customer satisfaction and trust. Moreover, the study reveals a positive relationship between customer satisfaction, trust, and customer loyalty. These findings have significant implications for e-commerce platform operators, highlighting the importance of enhancing customer experiences and building stronger customer relationships through targeted improvements in these critical factors.
The study formulated a research model grounded in Expectation Confirmation Theory, specifically examining the role of e-commerce experience in customer satisfaction and loyalty within the context of Pinduoduo. Hypothesized relationships were established between the core dimensions of e-commerce experience and the e-commerce customer engagement triad. To analyze the gathered data and evaluate the research hypotheses, structural equation modeling was employed. The research findings indicate that the core dimensions of e-commerce experience, namely e-commerce user interface quality, information quality, security risk avoidance perception, and privacy perception, exert positive influences on both customer satisfaction and trust. Moreover, the study reveals a positive relationship between customer satisfaction, trust, and customer loyalty. These findings have significant implications for e-commerce platform operators, highlighting the importance of enhancing customer experiences and building stronger customer relationships through targeted improvements in these critical factors.
The integration of artificial intelligence (AI) into online platforms has revolutionized the co-creation landscape, particularly in the fashion industry, where AI designers swiftly generate personalized products based on consumer preferences. This research extends the technology acceptance model to explore consumer perspectives and inclinations regarding AI-generated fashion items. The framework incorporates perceived utility, perceived simplicity, perceived risk, attitudes toward AI, and fashion engagement. Data were gathered through an online survey, and exploratory and confirmatory factor analyses were conducted to validate the model. The study highlights the significance of the model use and recommends improvements such as testing usability, gathering user feedback, providing clear instructions, and ensuring easy access to customer support. Meanwhile, the findings indicate that fashion enthusiasts are less likely to accept AI-driven design services, due to a need for transparency or better functionality.
The rapid growth in e-commerce has created challenges in last mile delivery, including rising costs, environmental concerns, and increasing customer expectations. Various last mile delivery (LMD) technologies have been adopted to address the issues. However, existing studies on LMD technologies are fragmented across different geographical contexts and focus on a wide range of technologies. The motivations for utilising LMD technologies also vary. Therefore, there is a need for a comprehensive analysis of current research to identify trends and propose future research agendas on LMD technologies in e-commerce. A bibliometric review of 605 publications from Scopus was conducted to address these gaps. The findings indicate that most studies focus on three common themes: sustainability, delivery efficiency, and emerging technological innovations. The emerging technological innovations remain an underexplored theme. Future research agendas should focus on integrating intelligent technologies with emerging delivery vehicles to improve sustainability and efficiency within LMD.
In this study, the authors discuss whether the innovation characteristics of mobile payment (m-payment) explain user attitudes and intentions in a psychologically conflictual context regarding the locus of control of use decisions. The authors present the development of an instrument that fully integrates innovation diffusion theory with the technology acceptance model and analyze data collected with it from Brazilian m-payment users during the COVID-19 pandemic. With path analysis, the authors found that the innovation factors of perceived observability and perceived relative advantage respectively explain the attitudes and the intentions toward m-payment. None of the other innovation factors had explanatory power. Moreover, two expected relationships in voluntary use settings for the formation of attitudes were not supported, leading the authors to conclude that the locus of control in use decisions was ambiguous to the user. The findings contribute to research on innovation diffusion, technology acceptance, consumer studies, usage patterns, behavioral change, and on the debate about the voluntariness or mandatoriness of technology use.
In this study, the authors discuss whether the innovation characteristics of mobile payment (m-payment) explain user attitudes and intentions in a psychologically conflictual context regarding the locus of control of use decisions. The authors present the development of an instrument that fully integrates innovation diffusion theory with the technology acceptance model and analyze data collected with it from Brazilian m-payment users during the COVID-19 pandemic. With path analysis, the authors found that the innovation factors of perceived observability and perceived relative advantage respectively explain the attitudes and the intentions toward m-payment. None of the other innovation factors had explanatory power. Moreover, two expected relationships in voluntary use settings for the formation of attitudes were not supported, leading the authors to conclude that the locus of control in use decisions was ambiguous to the user. The findings contribute to research on innovation diffusion, technology acceptance, consumer studies, usage patterns, behavioral change, and on the debate about the voluntariness or mandatoriness of technology use.
This study applies the Stimuli-Organism-Response (S-O-R) Theory to examine the impact of brand heritage of social commerce sites on consumers' perceived privacy risk, and the impact of this perceived risk on brand equity and brand advocacy. This study extends brand heritage research by exploring brand heritage in a new context (social commerce sites). To test the hypotheses, an online survey was conducted, and a total of 321 responses were collected from Amazon users in the US. The data were analyzed by using the Partial Least Squares-Structural Equation Modelling (PLS-SEM). Findings revealed that the brand heritage of social commerce sites has a significant negative influence on consumers' perceived privacy risk, which in turn has a significant negative impact on brand equity and brand advocacy.
Small and medium enterprises (SMEs) generate 90% of employment and contribute more than 50% to the world product, where e-commerce (EC) is fundamental to their development. In this study, a systematic review of literature from indexed journals in Scopus and Web of Science is conducted, 73 primary studies are identified to answer the inquiry: What affects EC performance and how is it measured? Twenty-eight definitions for EC, 70 ways of understanding performance in three perspectives (financial, customer-market, and process), 51 metrics to measure them, and 74 factors that affect these were identified. However, there is a lack of studies on performance factors from its process as well as the metrics that contemplate other perspectives, such as technological innovation, social responsibility, and value co-creation. Additionally, studies on factors are oriented to the result but not to the process that generates said result, which means there is a gap to be studied.
As eCommerce has become widespread, the challenge of successfully navigating the returns process has grown perilous. The product returns issue is even more difficult for microenterprises that sell unique or custom products with fewer resources. The authors examined the impact of the antecedents of return policy leniency, specifically economic and social success factors. Using a web crawler over a 24-week period, the authors collected and analyzed data for a sample of 781 shops from Etsy, an eCommerce platform. Results indicate that the well-studied factor of sales, in addition to a new social factor – community dialogue – impacts an Etsy shop's return policy leniency.
This study sought to understand the factors driving the consumer adoption of a cryptocurrency, in particular Bitcoin, as an electronic payment (e-payment) system for electronic commerce (e-commerce) transactions within a developing economy such as South Africa. The advent of e-commerce has led to increased online transactions facilitated by e-payment systems, which can fall prey to opportunistic hackers. Cryptocurrencies have been pegged as a solution to this security issue. However, little is currently known around consumer propensity to use a cryptocurrency as an e-payment option, particularly within a developing economy. The investigated factors that could influence user adoption were based on literature and tested on a South African representative sample of 814 respondents. Of the factors identified from literature, the study found that “perceived usefulness and perceived ease of use,” “self-efficacy,” “awareness,” “trust,” and “security” have the most significant influence on South African consumers adopting a cryptocurrency as an e-payment system.
