Online Reviews: What Drives Consumers to Use Them

The antecedents of customer satisfaction in the live-streaming commerce of green agricultural products

Live-streaming technology has been widely adopted to promote the sale of green agricultural products. Based on the literature regarding electronic commerce and customer satisfaction, this article integrates expectation-disconfirmation theory and the SERVQUAL model to investigate the antecedents of customer satisfaction and the routes along which the former drives the latter in the live-streaming commerce of green agricultural products. Our results demonstrate that most consumers are satisfied with the live-streaming commerce of green agricultural products, with an overall satisfaction degree of medium to high. In addition, a total of four antecedents are identified, namely commodity, live-streaming platforms, live-streaming contents and supporting services. Among the variables relevant to commodity, "commodity brand building" has the highest weight. Meanwhile, the corresponding variables for live-streaming platforms, live-streaming contents and supporting services are "interface design", "live-streaming atmosphere" and "privacy protection", respectively. Furthermore, live-streaming platforms are found to have the strongest direct influence on customer satisfaction, while commodity is found to have the strongest indirect and total influence on customer satisfaction. The theoretical and managerial implications are discussed at the conclusion of this article.

Information Adoption Patterns and Online Knowledge Payment Behavior: The Moderating Role of Product Type

The development of online knowledge payment platforms in recent years has increased their respective market value by nurturing content resources and improving content ecology. Yet, the underlying factors of knowledge seekers’ payment behaviors and their information adoption mechanisms are poorly understood. Based on the information adoption model, this study develops a research model to examine the relationship between information adoption patterns and knowledge seekers’ payment behavior, and explore the moderating effect of product type on this relationship. To test the research model and hypotheses, we used a multi-analytic approach combining text and regression analysis on a sample of 4366 social Q&A data collected from Quora+ between August 2021 and August 2022. We further classified the product types into utilitarian and hedonic, and compared the differences in influence paths between product types. The results show that the completeness, vividness, and relevance of the product description have a significant positive impact on knowledge payment behavior. The reputation, experience, and integrity of the knowledge provider have a positive impact on knowledge payment behavior. Compared to utilitarian knowledge products, the payment behavior for hedonic products is more related to the reputation and experience of the knowledge provider. This study provides insights into the factors that influence online knowledge payment behavior and practical guidance for the development of online knowledge payment services and platforms.

The Relationship Between Persuasion Cues and Idea Adoption in Virtual Crowdsourcing Communities

Building on the elaboration likelihood model (ELM) and absorptive capacity, this study develops a four-dimensional model of idea adoption in Virtual Crowdsourcing Communities (VCCs) and examines the influence of different persuasion cues on idea adoption. The research model was tested using hierarchical logistic regression based on a dataset from the Tableau community. The results show that both community recognition of users and community recognition of ideas are positively related to idea adoption. Proactive user engagement has a significant positive impact on idea adoption, while reactive user engagement has no significant impact. Idea content quality, represented by idea length and supporting arguments, has an inverted U-shaped relationship with idea adoption. Community absorptive capacity positively moderates the curvilinear relationship between idea content quality and idea adoption. These results contribute to a better elucidation of the persuasion mechanisms underlying idea adoption in VCCs, and thus provide important implications for open innovation research and practice.

Dynamic Restaurants Quality Mapping Using Online User Reviews

Millions of users post comments to TripAdvisor daily, together with a numeric evaluation of their experience using a rating scale of between 1 and 5 stars. At the same time, inspectors dispatched by national and local authorities visit restaurant premises regularly to audit hygiene standards, safe food practices, and overall cleanliness. The purpose of our study is to analyze the use of online-generated reviews (OGRs) as a tool to complement official restaurant inspection procedures. Our case study-based approach, with the help of a Python-based scraping library, consists of collecting OGR data from TripAdvisor and comparing them to extant restaurants’ health inspection reports. Our findings reveal that a correlation does exist between OGRs and national health system scorings. In other words, OGRs were found to provide valid indicators of restaurant quality based on inspection ratings and can thus contribute to the prevention of foodborne illness among citizens in real time. The originality of the paper resides in the use of big data and social network data as a an easily accessible, zero-cost, and complementary tool in disease prevention systems. Incorporated in restaurant management dashboards, it will aid in determining what action plans are necessary to improve quality and customer experience on the premises.