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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.

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.

Due to their very different contexts, the responses made by property hosts to online reviews can differ from those posted by hotel managers. Thus, the purpose of this study is to investigate the determinants of the responding behavior of hosts on peer-to-peer property rental platforms.

This study applied a comprehensive framework based on the theory of planned behavior. Empirical models are constructed based on 89,967 guest reviews with their associated responses to reveal the responding pattern of property hosts.

Unlike hotel managers, property hosts are more likely to reply to positive than to negative reviews; moreover, when they do choose to respond to negative reviews, they are likely to do so negatively, in a “tit-for-tat” way. This study also finds that one reason for the difference of responding patterns between property hosts and hotel managers is the hosts’ lack of experience of consumer relationship management and service recovery.

This study provides a good start point for future theoretical development regarding effective responding strategy on peer-to-peer property rental platforms, as well as some useful implications for practitioners.

This study is an early attempt to analyze the impact of the particularity of emerging platforms on the responding behavior of service providers based on a comprehensive conceptual framework and empirical model thus provides a good starting point for the further investigation of effective response strategies on these emerging platforms.

This study aims to examine the effect of several types of ex post idiosyncratic deals (i-deals) on work–life balance and work well-being, focusing on the mediating effect of work–life balance on the relationship between ex post i-deals and work well-being as well as the moderating effect of gender on the relationship between ex post i-deals and work–life balance in the hospitality industry.

This study uses a questionnaire survey of 642 hotel managers from developed cities in China and analyze the data with structural equation modeling. This study also conducts on-site interviews among 20 hotel managers to support conclusions of the survey.

The results indicate that task i-deals as well as career and incentives i-deals significantly promote work–life balance, thereby indirectly improving work well-being. However, the impact of flexibility i-deals on work–life balance and work well-being is insignificant. The influence of career and incentives i-deals on work–life balance for males is slightly stronger than that for females.

This study has practical implications for hotel employers in terms of using various ex post i-deals to motivate and retain hotel managers by improving personal work–life balance and work well-being.

As one of early attempts to highlight the potential of i-deals to serve as solutions for work–life conflicts and unhappiness issues among hotel managers, this study provides novel insights into the mediating process between ex post i-deals and work well-being from the work–life balance perspective as well as distinct influences of various ex post i-deals on work–life balance for male and female managers.

The impact of a mixture of positive and negative media coverage on long-run hotel survival remains unknown. This paper aims to investigate how the mixed positive and negative media coverage, namely, inconsistent media coverage, influences long-run hotel survival.

A yearly panel data set covering 792 news-reported hotels in Guangdong province of China, over the period 2010–2020, is analyzed using an inconsistency analysis framework consisting of text mining and survival analysis. The estimates of exponential models on the same observations and Cox estimates on alternative observations are used for robustness checks.

The inconsistency calculation method proposed here can measure the controversy degree well. There exists a U-shaped relationship between inconsistency of media coverage and hotel longevity, and hotel survival is significantly reduced only when the degree of inconsistency is within the range of 17.8%–53.6%. The U-shaped relationship is moderated by negative hotel image and by online media coverage on hotel operation strategy topics.

This study provides suggestions for hotel managers to use media coverage inconsistency to increase long-run hotel survival in the digital era.

To the best of the authors’ knowledge, this paper is one of the first to investigate long-run hotel survival factors from the perspective of media coverage inconsistency. It also proposes a method to calculate the degree of media coverage controversy, which helps to quantify the relationship between the degree of inconsistency and hotel survival.

The prevalence of online review websites and the ever-growing difficulty of judging review quality result in the increasing need for consumers to reduce cognitive costs. Thus, the purpose of this study is to find out the determinants of review helpfulness based on a comprehensive theoretical framework and empirical model.

This study applied a comprehensive framework, including both review content quality and reviewer background, to investigate the determinants of review helpfulness. It also presents empirical models to further control factors around product features.

Consumers are more likely to give helpful votes to those informative and readable reviews accompanied by extreme ratings. Reviewers who disclose information, have a high reputation and report a poor experience are always identified as helpful. Consumers also tend to signal suggestions from users with a local cultural background as subjective and useless.

This study focuses on upscale hotels in China. Information registered on TripAdvisor was used presenting a residential address not nationality. Only few controlling factors available because of the limited information are shown on online review websites.

Managers of both hotels and online review websites need to focus on reviews and/or reviewers as KOLs who attract consumers’ attention and affect their subsequent decisions. A dialogue with those KOLs can be by focusing on responding to reviews with certain characteristics. A reward system for reviews and KOLs may benefit review quality on online review websites and reduce cognition costs.

This positivistic research design, with multilevel approach, presenting a comprehensive conceptual framework and empirical model not only considering review- and reviewer-related factors but also controlled factors in product or service level (hotel-related characteristics).

Few studies on hospitality firm survival consider the impact of online media exposure. This paper aims to investigate how the online news coverage of restaurants, characterized in terms of the number of articles, channel (Web page or mobile app), topic (operations or products) and consistency (mix of news tones), influences their survival.

A yearly panel data set covering 682 news-reported restaurants in Shanghai, China, over the period 2011–2019 is analyzed using a Cox model, and an extended cross-sectional data set containing 9,488 restaurants is used for robustness checks.

A larger number of online news articles, regardless of channel or topic, significantly improves restaurants’ chances of survival, and this positive impact of online exposure is greater if that news is published by mobile apps (rather than on Web pages) or reports topics related to operations (rather than products). Although, generally, news inconsistency is not good for restaurant survival, when the number of online news items is eight or more, inconsistency becomes good for survival.

This research guides restaurant operators to use news exposure in an online marketing environment to increase the firm’s chances of long-term survival.

Online media exposure has hitherto been ignored in the literature on the survival of hospitality firms. This paper provides a new perspective on hospitality firm survival and also contributes to the literature on media exposure by conceptualizing a unique factor, namely, the consistent online exposure.

Digital innovation requires organizations to reconfigure their information technology infrastructure (ITI) to cultivate creativity and implement fast experimentation. This research inquiries into ITI generativity, an emerging concept demoting a critical ITI capability for organizational digital innovation. More specifically, it conceptualizes ITI generativity across two dimensions—namely, systems and applications infrastructure (SAI) generativity and data analytics infrastructure (DAI) generativity—and examines their respective social and technical antecedents and their impact on digital innovation.

This research formulates a theoretical model to investigate the social and technical antecedents along with innovation outcomes of ITI generativity. To test this model and its associated hypotheses, a survey was administered to IT professionals possessing knowledge of their organization's IT architecture and digital innovation performance. The dataset, comprising responses from 140 organizations, was analyzed using the partial least squares technique.

Results reveal that both dimensions of ITI generativity contribute to digital innovation performance, with the effect of DAI generativity being more pronounced. In addition, SAI and DAI generativities are driven by social and technical factors within an organization. More specifically, SAI generativity is positively associated with the usage of a digital application services platform and IT human resources, whereas DAI generativity is positively linked to the usage of a data analytics services platform, data analytics services usability and data analytics human resources.

This research contributes to the literature on digital innovation by introducing ITI generativity as a crucial ITI capability and deciphering its role in digital innovation. It also offers useful insights and guidance for practitioners on how to build ITIs to achieve better digital innovation performance.

Effective inventory management is crucial for SMEs due to limited resources and higher risks like cash flow, storage space, and stockouts. Hence, the aim is to explore how technology and know-how can be integrated with inventory practices and impact operational performance.

The basis of the analysis was collecting papers from a wide range of databases, which included Scopus, Web of Science, and Google Scholar. In the first phase of the process, a search string with as many as nine related keywords was used to obtain 175 papers. It further filtered them based on their titles and abstracts to retain 95 papers that were included for thorough analysis.

The study introduced innovative methods of measuring inventory practices by exploring the impact of know-how. It is the first of its kind to identify and demonstrate how technical, technological, and behavioral know-how can influence inventory management practices and ultimately impact the performance of emerging SMEs. This study stands out for its comprehensive approach, which covers traditional and modern inventory management technologies in a single study.

The study provides valuable insights into the interplay between technical, technological, and behavioral know-how in inventory management practices and their effects on the performance of emerging SMEs in Industry 5.0 in the light of RBV theory.

The RBV theory and the Industry 5.0 paradigm are used in this study to explore how developing SMEs' inventory management practices influence their performance. This study investigates the effects of traditional and modern inventory management systems on business performance. Incorporating RBV theory with the Industry 5.0 framework investigates firm-specific resources and technological advances in the current industrial revolution. This unique technique advances the literature on inventory management and has industry implications.