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This paper mainly focuses on how to induce all members to represent members' true preferences for supply and demand matching of E-commerce platform in order to generate stable matching schemes with more social welfare of Multi-agent Matching Platform (MMP) and individually stable advantages than traditional methods.

An MMP is designed. Meanwhile, a true preference inducing method, Lower-Bid Ranking (LBR), is proposed to reduce the number of false preferences, which is helpful to solve the problem that too much false preferences leads to low efficiency of platform operation and supply and demand matching. Then, a systematic model of LBR-based Stable Matching (SM-LBR) is proposed.

To obtain an ideal transaction partner, the adequate preference ordering and modifying according to market environment is needed for everyone, and the platform should give full play to the platforms' information advantages and process historical transaction and cooperation data. Meanwhile, the appropriate supply and demand matching is beneficial to improve the efficiency and quality of platform operation, and the design of matching guidance mechanism is essential.

The numerical experiments show that, the proposed model (SM-LBR) can induce members to represent the model's true preferences for stable matching and generate effective matchings with more social welfare of MMP and individually stable advantages than traditional methods, which may provide necessary method and model reference for the research of stable matching and E-commerce platform operation.

From the perspective of two-sided review systems, this study aims to investigate how guests’ prior reputation influences their subsequent satisfaction on Airbnb.

This study applied a conceptual framework based on social capital theory to explain the effect of guests’ reputation decided by hosts’ prior evaluations on their subsequent satisfaction. The authors collected 96,204 guest reviews posted for 17,325 properties on Airbnb and used the review polarity to measure guest satisfaction. All historical evaluations generated by hosts for each guest were collected and treated as a proxy of guest reputation. Ordinary least squares regressions were conducted to estimate the effect of guests’ reputation on their subsequent satisfaction.

Results show that guests whose historical evaluations have higher valences or larger variations tend to be more satisfied in their subsequent bookings. However, the number of reviews that guests received from hosts in the past does not influence their subsequent satisfaction.

This study provides new insights into the hospitality literature by identifying the influencing factors of guest satisfaction on peer-to-peer rental platforms from the perspective of two-sided review systems. Results also present practical implications to property owners and website designers to gain a deeper understanding of the determinants of guest satisfaction and the consequences of social interactions between hosts and guests.

This study is a novel attempt that analyzes the effect of guests’ reputation on their satisfaction with subsequent bookings based on two-sided review systems on peer-to-peer rental platforms. Thus, this study provides a starting point for investigating how two-sided review systems affect use behavior on peer-to-peer rental platforms.

Online reviews have become increasingly important and numerous studies have noted the effect of social factors on the review provision of users. The purpose of this study is to investigate how hometowner contributions, which are defined as prior reviews posted by users from the same city, affect the quality of reviews by focal users.

Based on the theories of competitive altruism, pure altruism and reciprocity, as well as several social influence theories, a conceptual framework is constructed to explain user contribution behavior. In addition, empirical models are established based on 831,737 reviews of 919 hotels on Tripadvisor.

The quality of reviews by hometowners can significantly motivate subsequent users to contribute high-quality reviews. This positive effect is stronger than the effect of previous contributions by non-hometowners. The effect of hometowner contribution is amplified in users with limited review-posting experience and/or in those from countries with a considerable cultural distance from the target destination.

This study provides the hospitality literature with new insights into the effect of social factors on the review provision of users in the context of online hotel review websites. The results also present numerous practical implications for online travel communities.

This study is an early attempt to analyze the effect of prior hometowner contributions on the subsequent contribution decisions of focal users. Thus, this study provides a satisfactory starting point for determining whether the review provision of focal users can be affected differently by prior contributions from their peers from different categories.

Building on a small body of work, the authors' study aims to investigate some important antecedents of online review characteristics in the Chinese restaurant industry.

Using a data set of restaurant reviews collected from a most popular review platform in China, the authors conduct a series of analyses to examine the influence of travel experience and travel distance on travelers' review characteristics in terms of review rating and media richness. The moderating effect of restaurant price on the influence is also investigated.

Travelers with a longer travel distance and more travel experience tend to provide higher and lower online ratings, respectively, which can be explained by the construal level theory (CLT) and the expectation-confirmation theory (ECT), respectively. Furthermore, these strong feelings can then induce travelers to post enriched reviews with more pictures, more words and more affective words to release consumption tension. Besides, restaurant price can moderate these relationships.

Distinguished from most studies which mainly focus on the consequences of online review characteristics or antecedents of review helpfulness, the authors pay attention to the effects of travelers' individual differences in terms of travel distance and travel experience on travelers' online reviewing behavior. In addition to review rating, the authors also focus on media richness in terms of visual and textual information. The authors' research findings can benefit restaurant consumers and managers for their online word-of-mouth utilization and management.

With the increasing importance of e-commerce to the economy and people's lives, user-generated content, such as electronic word-of-mouth (eWOM) represented by online reviews, has exploded. On one hand, it is of great significance for review consumers (readers) to identify high-quality ones from a large number of existing reviews to assist their purchase decision. On the other hand, how to use appropriate strategies to make their published reviews more concerned by others is also important to review generators (reviewers). The purpose of this study is to understand the comprehensive relationship among review characteristics, review helpfulness and receiver attention.

This study uses the online movie reviews obtained from the most popular review platform in China to conduct multiple empirical analyses.

The results show that the review helpfulness plays a mediating role between the emotional characteristics of online reviews and the receiver attention, and such a mediating role is more significant among reviewers with rich review expertise. The reviewer's expertise also moderates the impact of review emotions on review helpfulness.

This work studies eWOM receiver involvement, which can ultimately impact product sales, but seldom be investigated in eWOM domain. Therefore, this research can enrich studies on eWOM and provide valuable practical implications as well.

Mobile health (mHealth) services are considered an important means of relieving the problems of the aging population. The efficiency of mHealth services can be enhanced by engaging more elderly users and guaranteeing their continued use. However, limited attention has been directed toward investigating elderly users' continuance intention regarding mHealth services. The purpose of this paper is to explain elderly users' continuance intention by investigating the contingent role of technology anxiety and health anxiety on affective trust and cognitive trust.

Survey data were collected from 232 elderly users to verify the research model and hypotheses based on structural equation modeling (SEM).

This study revealed that both affective and cognitive trust enhance elderly users' continuance intention regarding their use of mHealth services. Health anxiety strengthens the effect of cognitive trust but weakens the effect of affective trust with regard to continuance intention. Furthermore, technology anxiety strengthens the effect of affective trust but not the effect of cognitive trust with regard to continuance intention.

This study is one of the first to examine elderly users' continuance intention regarding mHealth services use from the perspective of affective and cognitive trust, thus enriching the extant literature on the use of mHealth services. Additionally, this study sheds light on the contingent effects of technology anxiety and health anxiety on affective and cognitive trust, which have been neglected by previous research.

There are two major strategies for short video advertising which are KOL (key opinion leader) endorsement and in-feed advertising. The authors aim to research the effectiveness of these two strategies for heterogeneous sellers.

The study employed a data set of users from Douyin. Using an endogenous treatment model, the study empirically examines the two strategies' effectiveness in attracting product traffic for online retailors at a short video app Douyin (TikTok).

The results show that the performance of in-feed advertising is higher when the seller's product is of lower price and when the seller has smaller cumulative video exposure. In addition, KOL endorsement is effective regardless of the product price, but performs better when the seller has larger cumulative video exposure.

To the best of the authors’ knowledge, this study is one of the first to explore the interaction effects of two major advertising strategies, KOL endorsement and in-feed advertising on short video platforms. The findings provide important theoretical contributions and practical implications.

This study aims to examine whether and how hotel class, attributes of the room, quality, location, cleanliness, and service influence room rates in hotels.

Regression models were developed for the hotel industry and for various grades of hotels.

Using data from New York, empirical findings suggest that room quality and location are important determinants of room price for the industry, but attributes that can influence room rates differ greatly among hotel segments.

Hotels can reap benefits from understanding customers' specific expectation of a market segment and seeking to provide amenities accordingly.

The quality of hotel attributes is evidenced through customer reviews on a travel advice website. The theory of the hierarchy of needs is supported in the hotel industry, namely, the ascending order of accommodation needs are the quality of a room, location, and service.

Based on the text mining tools, this paper aims to propose a new method to evaluate the subjectivity and objectivity of corporate social responsibility information disclosure.

The authors build up a text subjectivity evaluation model of corporate social responsibility reports through meta-analysis; a text mining is conducted to all sample CSR reports released by Chinese listed companies untill March 2016[1]. Furthermore, the authors made an overall and quantitative analysis of the situation which contained changing state, characteristics and abnormal value on the subjectivity and objectivity of information disclosure.

The results show that the subjectivity scores of social responsibility reports of Chinese listed companies are generally in a normal distribution. The diagram turns out to be a rising trend over the years and increases linearly from 2011 to 2013. Also, the industry heterogeneity and policy control are the main reasons for the formation of the differences, which are significant between different industries and different years.

This paper provides not only an important empirical basis for the research of corporate social responsibility but also a new idea for the non-financial information disclosure as well as objective evaluation of normative text.