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This study argues that online user comments on social media platforms provide feedback and evaluation functions. These functions can provide services for the relevant departments of organizations or institutions to formulate corresponding public opinion response strategies.

This study considers Chinese universities’ public opinion events on the Weibo platform as the research object. It collects online comments on Chinese universities’ network public opinion governance strategy texts on Weibo, constructs the sentiment index based on sentiment analysis and evaluates the effectiveness of the network public opinion governance strategy adopted by university officials.

This study found the following: First, a complete information release process can effectively improve the effect of public opinion governance strategies. Second, the effect of network public opinion governance strategies was significantly influenced by the type of public opinion event. Finally, the effect of public opinion governance strategies is closely related to the severity of punishment for the subjects involved.

The theoretical contribution of this study lies in the application of image repair theory and strategies in the field of network public opinion governance, which further broadens the scope of the application of image repair theory and strategies.

This study expands online user comment research to network public opinion governance and provides a quantitative method for evaluating the effect of governance strategies.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-05-2022-0269

Online food delivery service has evolved swiftly and stretched the bounds of the catering business. In the gig economy, being a food delivery rider draws employees with the promise of flexibility and independence. To this end, the purpose of this paper is to explore the main themes shared in online reviews by food delivery riders and which of these themes are linked to positive and negative ratings.

The authors used 729 employee reviews posted on the Glassdoor website. In addition, they used content analysis to examine reviews of Uber Eats online food ordering company shared by food delivery riders on an online platform.

The results of this study include seven main themes: “earning,” “customers,” “orders,” “tips,” “car,” “flexible schedule” and “app” (navigation). Positive concepts are associated with “earning,” “orders,” “tips” and “flexible schedule.” Negative themes are linked to the “app” (navigation), “car” and “customers.”

Management should consider online reviews as employees’ opinions and voices. Specifically, management should provide financial support to employees for car maintenance, offer insurance for income stability and arrange training programs to enable them to use several tip-enhancing behaviors.

No research has been conducted using online reviews from an employment search engine to investigate employees’ experiences of online food delivery. To the best of the authors’ knowledge, this study is one of the first attempts using user-generated content from an employment search engine to explore employees’ experiences.

We investigate the joint impacts of three trust cues – content, sentiment and helpfulness votes – of online product reviews on the trust of reviews and attitude toward the product/service reviewed.

We performed three studies to test our research model, presenting participants with scenarios involving product reviews and prior users' helpful and unhelpful votes across experimental settings.

A high helpfulness ratio boosts users’ trust and influences behaviors in both positive and negative reviews. This effect is more pronounced in attribute-based reviews than emotion-based ones. Unlike the ratio effect, helpfulness magnitude significantly impacts only negative attribute-based reviews.

Future research should investigate voting systems in various online contexts, such as Facebook post likes, Twitter microblog thumb-ups and up-votes for article comments on platforms like The New York Times.

Our findings have significant implications for voting system-providers implementing information techniques on third-party review platforms, participatory sites emphasizing user-generated content and online retailers prioritizing product awareness and reputation.

This study addresses an identified need; that is, the helpfulness votes as an additional trust cue and the joint effects of three trust cues – content, sentiment and helpfulness votes – of online product reviews on the trust of customers in reviews and their consequential attitude toward the product/service reviewed.

Leveraging lobbying theory, the authors analyze responses to the American Institute of Certified Public Accountants (AICPA) proposal suggesting the removal of state and local governmental accounting from the content tested on the uniform certified public accountant (CPA) examination. Furthermore, the authors compare the responses to a prior exam content review to place the uniqueness of the more recent response in perspective.

The authors examine 181 comment letters obtained from the AICPA website. In addition, the relative concentration of governmental entities across the USA is studied for correlation with the response rate.

Consistent with lobbying theory, the authors find that participating governmental entities overwhelmingly argued for the retention of governmental accounting. In contrast, most other groups of respondents (accounting firms, state societies, etc.) had at least one letter that agrees with the removal of the content.

While the letter writers appear to be successful in retaining the governmental accounting content on the CPA exam, the majority of the detailed content has been placed within a specialized area on the new version of the CPA exam, expected to be deployed in 2024. This means that fewer CPA candidates will be exposed to governmental accounting than under the current regime. It has implications for governmental units seeking qualified candidates to fill their staffing needs especially as fewer universities offer governmental accounting courses.

The paper attempts to discuss the optimal pricing decisions under the decentralized and centralized decision and analyze the influence of online reviews and in-sale service on dual-channel supply chain. Finally, the authors design a two-part tariff coordination mechanism.

To deal with this pricing conflict problems of dual-channel supply chain consisting of dominant manufacturer and a retailer, considering the fact that online reviews and in-sale service are important factors on consumers’ purchase decisions, the authors establish some basic models and exploit them to discuss the optimal pricing decisions under the decentralized and centralized decision and analyze the influence of online reviews and in-sale service on dual-channel supply chain. Finally, the authors design a profit-sharing coordination mechanism.

The results show that the optimal online direct selling price is positively correlated with product perceived quality obtained from online reviews and negatively correlated with the in-sale service. The traditional retail price is positively correlated with the in-sale service and weakly correlated with online reviews. For the manufacturer and retailer, whether decentralized decision or coordination contract, their profits increase with the increase of the in-sale service in a certain range and quality perceived from spontaneous online reviews. Online reviews and in-sale service are important factors on consumers’ purchase decisions. Positive in-sale services and online reviews can provide consumers with a better shopping experience, thereby promoting their enthusiasm for shopping and improving their quality of life. The two-part tariff coordination mechanism improves the profits of the manufacturer and the traditional retailer, respectively, through the transfer fee.

The proposed approach can well analyze the channel conflicts and pricing problems between retailers and manufacturers with respect to product offline price and online price. The analysis and results can inform decision-making for manufacturers and retailers.

Generation Z (Gen-Z), sometimes known as “digital natives”, represents the first generation to become immersed in digital communication. In a multicultural environment, this study aims to explore which types of factors are most beneficial in connection with Gen-Z’s impulsive purchase behaviour.

This study adopts an exploratory sequential mixed-method design, incorporating both qualitative and quantitative approaches. In Study 1, focus group discussions are conducted to address “why” and “how” questions, whereas Study 2 uses a quantitative method to test the hypothetical model. The model is assessed using structural equation modelling. This study used the stimulus–organism–response (SOR) framework in the context of Instagram.

Building on Mehrabian and Russell’s (1974) concept and focus group discussions, Study 1 introduces a novel SOR model tailored to Instagram. In Study 2, the model is tested, and results confirm most hypotheses, except for three. Factors such as aesthetic appeal, scarcity promotions and discounted prices stimulate impulse buying behaviour in Gen-Z. Positive emotional responses evoked by these factors also influence impulse buying, whereas the impact of negative emotional responses is found to be insignificant.

This mixed-methods study enhances the theoretical understanding of Gen-Zers’ impulse buying behaviour by highlighting the influence of diverse independent variables. By using the SOR framework, it reveals the intricate emotional aspects impacting impulsive purchase decisions. The research provides new insights into online impulsive buying behaviour, particularly relevant to consumer psychology and behavioural economics among young collectivist consumers.

In this study, the authors examine how organizational-, systems- and interpersonal-level trust may be required for a smooth functioning of the firms in the sharing economy (SE). The research objective is to explore the trust-building mechanisms of Airbnb, a leading SE organization, and its aim to foster generalized trust. An investigation of the Airbnb's promotion of different trust-building mechanisms will allow to evaluate their effectiveness in how they can help overcome scepticism and distrust between the transacting parties. Consequently, the authors can develop a unique theoretical perspective on generalized trust in SE environments and better understand any trust-related barriers preventing SE transactions.

The authors employ a case study approach to investigate the research questions with the aim to fully understand the abstract and complex nature of trust. They focus on Airbnb as the company enjoys a leading market position, being a sharing economy firm. Moreover, the personal nature of accommodation sharing, which is the business of Airbnb, increases users' trust requirements, and so the company must take active steps to promote trust between the transacting parties. The authors adopt thematic analysis to execute the data analysis of the study's findings, which are derived from emergent themes and directed by the research objectives and relevant literature.

The results show that users of Airbnb are concerned about the danger of opportunistic hosts, although they are primarily motivated to use the company's services due to its economic benefits. Nevertheless, the success of Airbnb platform stems from the trust that the company has succeeded in establishing among its users, in particular interpersonal trust. Analysis reveals that generalized trust is fostered at an interpersonal level in the form of peer reviews, at an organizational level in terms of brand familiarity and at a systems level in regards to interface design.

The authors advance the argument that confidence to transact in the social economy stems from a combination of three levels of trust, including organizational-, systems- and interpersonal-level trust. These findings contribute to the body of trust research in information technology and people literature from its unique investigative setting, whilst simultaneously strengthening the primarily speculative research on SE with in-depth empirical evidence.

This study aims to examine the impact of online travel reviews (OTR) on tourists’ intention to travel based on the stimulus–organism–response (SOR) model. Further, it explored the mediating effects of tourist trust in OTR.

In this direction, this study proposes and empirically validates a conceptual model after collecting data from 299 Indian consumers. Proposed hypotheses were tested by applying the structural equation modelling technique. Bootstrapping method was used for mediation testing.

The findings revealed that various attributes of OTR exert differential impacts on travel intention. The study also confirmed the mediating role of tourist trust in OTR.

This study offers significant practical implications for travel marketers. To capitalize on OTR, travel marketers are recommended to develop an effective and efficient online reviews management system. This will improve the quality, valence, quantity and consistency of OTR, which in turn will enhance tourist trust in OTR, leading to improved travel intention.

No empirical evidence has been traced on how OTR enhances tourist trust in OTR and their travel intention. In support of this, the present study proposes and empirically validates an extensive model to comprehend the role of various drivers of OTR in improving tourist trust in OTR, leading to enhanced travel intention based on the SOR model.

This paper presents a review of the state of the art on the application of blockchain and smart contracts to the peer-review process of scientific papers. The paper seeks to analyse how the main characteristics of the existing blockchain solutions in this field to detect opportunities for the improvement of future applications.

A systematic review of the literature on the subject was carried out in three databases recognized by the research community (IEEE Xplore, Scopus and Web of Science) and the Frontiers in Blockchain journal. A total of 1,967 articles were initially found, and after the exclusion process, the 26 remaining articles were classified according to the following dimensions: System Type, Open Access, Review Type, Reviewer Incentive, Token Economy, Blockchain Access, Blockchain Identification, Blockchain Used, Paper Storage, Anonymity and Maturity of the solution.

Results show that the solutions are normally concerned on offering incentives to the reviewers' work (often monetary). Other common general preferences among the solutions are the adoption of open reviews, the use of Ethereum, the implementation of publishing ecosystems and the use of InterPlanetary File System to the storage of the papers.

There are currently no studies covering the main aspects of blockchain solutions in the field of scientific peer review. The present study provides an overall review of the topic, summarizing important information on the current research and helping new adopters to develop solutions grounded on the existing literature.

This case is about “Red”, a cross-border e-commerce platform developed from a community which was built to share overseas shopping experience. With sharp insights into the consumption behavior of urban white-collar women and riding on its community e-commerce advantage, “Red”, a cross-border e-commerce startup, pulled in three rounds of financing within just 16 months regardless of increasingly competitive market. On the other hand, well-established platforms such as T-mall International and Joybuy also stepped in, and their involvement will also speed up the industry integration and usher in a reshuffling period. Confronted with the “price war” started by those e-commerce giants, in what ways can “Red” adjust its shopping experience and after-sales services to enhance the brand value and sharpen its edge?