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Positive reviews can enrich the favorable impression of peer-to-peer accommodation products, and seizing this impression is vital for hosts. This study aims to focus on hosts’ response strategies to positive reviews and their effects.

This study categorizes hosts’ response strategies to positive reviews into cordial and tailoring responses. This study empirically analyzes the influence of these response strategies on subsequent review volumes using 1,283 valid listings and zero-inflation negative binomial regression models.

While hosts use cordial responses more, tailoring responses are more likely to drive subsequent reviews. In addition, when the host chooses entirely shared accommodation or sets a high price, the facilitating effect of the two response strategies on subsequent reviews weakens.

This study enriches the knowledge system on managerial responses by proposing two specific response strategies to positive reviews that can be adopted by peer-to-peer accommodation hosts and by finding the promoting impact of these strategies on subsequent review volumes.

This study recommends that peer-to-peer accommodation hosts adopt cordial and tailoring responses to encourage subsequent consumer reviewing behavior.

As an early attempt to explore hosts’ responses to positive reviews and their impacts on subsequent review volumes, this study provides valuable insights into further research on positive review response strategies in the digital space.

This study aims to focus on understanding how the characteristics of the bed and breakfast (B&B) host responses to online reviews impact the subsequent business performance of review volume, including volume, timeliness and length of responses.

The study constructs a theoretical framework to model for the relationships among characteristics of the B&B host responses, heterogeneity of B&B houses and subsequent reviews. The model is then examined by an econometric model using data from Ctrip.com.

Prompt and lengthy responses to online reviews increase the number of subsequent reviews, and the effects are larger for higher level houses. The main theoretical contribution is to build a model explaining how multiple attributes of the host responses can affect business performance and how these effects are moderated by the class levels of B&B houses, which are empirically tested by real data.

This study highlights managerial implications of host responses for online B&B business practices. For the higher-quality B&B houses, based on price and reviews, lengthy and timely responses are necessary, as tourists expect increased customer service from these hosts.

The research provides insights in understanding the mechanism of B&B host responses on subsequent reviews. To the best of the authors’ knowledge, this is the first study to demonstrate the moderating effect of price and volume of online reviews on responses.

共享民宿房主对在线评论的反应如何影响后续评论：房屋等级的调节效应

本研究旨着重探讨民宿房主对网上评论的回应特性如何影响评论量的后续经营绩效, 包括回复数量、及时性和回复的长度。

方法 -- 本研究首先构建理论框架, 对民宿房主的在线回应特征、民宿房屋的异质性特征与后续评论之间的关系进行建模。该模型通过一个计量经济学模型对从携程网收集的数据进行了检验.

研究结果 -- 本研究的结果显示, 对在线旅游评论提供及时和冗长的回复, 可能会增加未来的预订数量, 从而增加后续的评论,并且这个影响随着房屋等级的提高而增加。本文的主要理论贡献是建立一个模型来解释房屋主人在线回应的多重属性如何影响他们的经营绩效, 以及这些影响是如何被房屋等级所调节的,并通过真实数据对理论进行了验证。

研究意义 -- 该研究有助于将研究重点从在线评论和口碑转移到管理层的回应效应。我们的研究结果印证了之前的研究关于评论量可以影响口碑信息说服力及其他口碑相关特征（如管理层回应）影响的结论。

管理启示 -- 本研究的结果, 向民宿房主提供了具体的管理启示, 为网上民宿商业管理提供参考。对于价格更高、在线声誉较高的B&B房屋, 应提供更多及时的回应, 因为游客期望得到更友好的客户服务。

原创性 -- 这项研究提供了关于民宿房主在线回应对后续评论量影响机制的探索。并将是首次尝试验证价格和在线评论量对在线回复影响的调节作用。

Entendiendo cómo las respuestas de los dueños de establecimientos de B&B a las opiniones de los turistas en línea promoverán las opiniones subsiguientes: Los efectos moderadores del nivel de clase de los establecimientos de B&B

Resumen

Propósito -- Este estudio se centra en comprender cómo las características de las respuestas de los anfitriones de alojamientos B&B influyen en el rendimiento empresarial de volumen de reseñas; esto incluye el número de respuestas, la puntualidad de la respuesta y la duración de la misma.

Metodología -- En primer lugar, el estudio construye un marco teórico para establecer un modelo de relación entre las características de las respuestas de los anfitriones de alojamientos, heterogéneos de alojamientos B&B y las revisiones posteriores. A continuación, el modelo es examinado por un modelo econométrico a partir de los datos recogidos en ctrip.com.

Resultados -- Se ha demostrado que las respuestas rápidas y extensas a las reseñas en línea pueden aumentar potencialmente el número de reseñas posteriores, y tuvieron un mayor impacto en las viviendas de gran altura. La principal contribución teórica de este trabajo es construir un modelo para explicar cómo los múltiples factores de la respuesta de los anfitriones pueden afectar a su rendimiento empresarial y cómo estos efectos son moderados por las nivel de los alojamientos B&B, través de los datos reales de la prueba empírica.

Implicaciones prácticas -- Proporciona una referencia para la práctica empresarial de los alojamientos B&B en línea, al informar sobre las implicaciones específicas de gestión para los anfitriones de alojamientos B&B. En el caso de las casas de alojamientos B&B de mayor nivel, con precios más altos y más reseñas en línea, se deberían dar más respuestas oportunas, ya que los turistas esperan de los anfitriones un servicio de atención al cliente más amable.

Originalidad -- La investigación permite comprender el mecanismo de las respuestas de los anfitriones de alojamientos B&B en las reseñas posteriores. Sería el primer intento de demostrar el efecto moderador del precio y el volumen de las reseñas en línea sobre el impacto de las respuestas.

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.

This paper aims to investigate textual characteristics of customer reviews that motivate companies to respond (sentiment negativity and sentiment deviation) and how aspects of these company responses (response intensity, length and tailoring) affect subsequent customer review quality (comprehensiveness and readability) over time.

Leveraging a large data set from a leading app website (Shopify), the authors combine text mining, natural language processing (NLP) and big data analysis to examine the antecedents and outcomes of online company responses to reviews.

This study finds that companies are more likely to respond to reviews with more negative sentiment and higher sentiment deviation scores. Furthermore, while longer company responses improve review comprehensiveness over time, they do not have a significant influence on review readability; meanwhile, more tailored company responses improve readability but not comprehensiveness over time. In addition, the intensity (volume) of company responses does not affect subsequent review quality in either comprehensiveness or readability.

This paper expands on the understanding of online company responses within the digital marketplace – specifically, apps – and provides a new and broader perspective on the motivations and effects of online company responses to customer reviews. The study also extends beyond the short-term focus of prior works and adds to literature on long-term effects of online company responses to subsequent reviews. The findings provide valuable insights for companies (especially those with apps) to enhance their online communication strategies and customer engagement.

This study aims to measures the effects of managerial response on consumer electronic word-of-mouth (eWOM) and hotel performance.

A sample of 56,284 consumer reviews and 10,793 managerial responses for 1,045 hotels was retrieved from TripAdvisor, along with 30,232 performance records matched to these hotels on a quarterly basis.

This study finds that managerial response leads to an average increase of 0.235 stars in the TripAdvisor ratings of the sampled hotels, as well as a 17.3 per cent increase in the volume of subsequent consumer eWOM. Moreover, managerial response moderates the influence of ratings and volume of consumer eWOM on hotel performance.

This study offers a practical model that enables hotel managers to orchestrate social media marketing approaches and efforts toward an optimal social media strategy.

This study differs from extant literature that has extensively focused on consumer reviews by providing a new perspective of management intervention in the social media context. By examining the interplay of managerial response and consumer eWOM at the individual hotel level, this study provides empirical evidence of managerial response affecting hotel performance through the increased ratings and volume of consumer eWOM. This study also offers insights into the practical importance of crafting intervention opportunities to cultivate the continued engagement of consumers on social media and increased hotel performance.

Online reviews are often likely to be socially influenced by prior reviews. This study aims to examine key review and reviewer characteristics which may influence the social influence process.

Restaurant review data from Yelp.com are analyzed using an ordered logit model and text mining approach.

This study reveals that prior average review rating exerts a positive influence on subsequent review ratings for the same restaurant, but the effect is attenuated by the variance in existing review ratings. Moreover, social influence is stronger for consumers who had a moderate dining experience or invested less cognitive effort in writing online reviews. Compared to reviewers classified by Yelp as “elite,” non-elite reviewers appear more susceptible to the social influence of prior average review rating.

This study provides guidelines for mitigating the social influence of prior reviews and improving the accuracy of online product/service ratings, which will eventually enhance business and the reputation of online review platforms.

The findings from this study contribute to the electronic word-of-mouth (eWOM) literature and social influence literature in terms of the bidirectional nature of social influence on eWOM.

This study aims to investigate how prior reviews posted by other consumers affect subsequent consumers’ evaluations and to what extent the review temporal distance can increase or reduce the social influence of prior reviews. In this study’s restaurant context, review temporal distance refers to the duration between dining time and review time of a dining experience.

The data of paired online restaurant reservations and reviews are analyzed using Ordered Logit Model. Two robustness checks are conducted to test the stability of the main estimation results.

The empirical results demonstrate that consumers’ restaurant evaluation is socially influenced by both the prior average review rating and number of prior reviews; review temporal distance has a direct negative effect on consumers’ restaurant evaluation; and review temporal distance increases the social influence of prior reviews.

This study suggests that online review matters. Both restaurants and the online review platforms should encourage consumers to share their experiences and post online reviews immediately after their consumption.

The study contributes to the literature on electronic word-of-mouth, social influence and psychological distance. First, the bi-directional nature of social influence on electronic word-of-mouth for experience-oriented product is documented. Second, for the first time, this study examines how review temporal distance could affect the social influence on consumers’ restaurant evaluation.

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.

This study explores the link between additional reviews, credibility, and consumers’ online purchasing behavior.

We employ a 2 × 2 between-subjects design to measure subjects’ purchasing behavior with versus without additional reviews and with important versus non-important attributes. A total of 529 valid questionnaires are collected from university students across 30 Chinese provinces.

The addition of negative reviews to a positive initial review enhances consumers’ perceived credibility of the reviewer and the overall review content. This effect is positively moderated by the attribute importance in additional reviews. Moreover, we find that as the time interval increases, consumers’ perceived credibility gradually increases but eventually decreases after reaching a certain threshold. In addition, the attribute importance in additional reviews negatively moderates the impact of perceived credibility on consumer purchasing behavior.

Existing studies on first and subsequent reviews mainly focus on the difference in perceived usefulness between the two. They do not examine how additional reviews affect potential customers’ perceived credibility and their purchase decision-making. This study bridges the gap between the word-of-mouth literature and marketing practices.

Experienced reviewers in general can produce high-quality product reviews, and thereby get more helpful votes. This paper explores the question that whether the depth and width of the reviewers' experience distribution have effects on the helpfulness of their reviews.

Adopting the restaurant review data from Yelp, the present paper classifies the restaurants in to different categories applying the Word2Vec technique, such as Asian or fast food. By evaluating the number of a user's historical reviews in a specific category, and the evenness of such distribution in different categories, the experience specialty and experience diversity are defined respectively.

The analysis shows that users specialised in a given category can produce more helpful reviews in that category. The users with diverse historical experience, i.e. have posted reviews for many categories, also can produce helpful reviews. In addition, the experience diversity shows a positive moderation effect on the influence of experience specialty. Thus, users with diverse experience while specialized in a particular category are the source of most helpful reviews.

While previous studies mostly consider the raw number of historical reviews as a reviewer's experience, we distinguish such experience by product category and focus on the width and depth of its distribution. The results not only shed lights on the mining of high-quality reviews and reviewers but also provide insights on the management of online review platforms and electronic marketing.