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Engaging in webcare, i.e. responding to online reviews, can positively affect consumer attitudes, intentions and behavior. Research is often scarce or inconsistent regarding the effects of specific webcare strategies on business performance. Therefore, this study tests whether and how several webcare strategies affect hotel bookings.

We apply machine learning classifiers to secondary data (webcare messages) to classify webcare variables to be included in a regression analysis looking at the effect of these strategies on hotel bookings while controlling for possible confounds such as seasonality and hotel-specific effects.

The strategies that have a positive effect on bookings are directing reviewers to a private channel, being defensive, offering compensation and having managers sign the response. Webcare strategies to be avoided are apologies, merely asking for more information, inviting customers for another visit and adding informal non-verbal cues. Strategies that do not appear to affect future bookings are expressing gratitude, personalizing and having staff members (rather than managers) sign webcare.

These findings help managers optimize their webcare strategy for better business results and develop automated webcare.

We look into several commonly used and studied webcare strategies that affect actual business outcomes, being that most previous research studies are experimental or look into a very limited set of strategies.

To promote the success of peer-to-peer accommodation, this study examines the effects of online host–guest interaction as well as the interaction's boundary conditions of listing price and reputation on listing popularity.

Using 330,686 data collected from Airbnb in the United States of America, the authors provide empirical evidence to answer whether social-oriented self-presentation and response rate influence listing popularity from the perspective of social exchange theory (SET). In addition, the authors investigate how these two kinds of online host–guest interactions work with listing price and reputation to influence listing popularity.

The results reveal the positive association between online host–guest interaction and listing popularity. Notably, the authors find that listing price strengthens but listing reputation weakens the positive effects of online host–guest interactions on listing popularity in peer-to-peer accommodation.

This study is the first attempt to adopt SET to explain the importance of online host–guest interactions in influencing listing popularity as well as examine the moderating role of listing price and reputation on the above relationship.

The article investigates different types of strategies for managing user-generated content (UGC) and provides some insights into their implications.

A unique sample of Italian hotels with current and prospective customers in the digital environment is investigated. A taxonomy of user-provider interactions mediated by UGC is developed. A mixed approach was designed to meet the study aims. Firstly, an exploratory factor analysis was performed in order to illuminate different strategies of UGC and electronic word-of-mouth (E-WOM) management. Secondly, a cluster analysis was implemented in order to explain hoteliers' behavior toward users' contents.

The study results suggested the existence of three clusters, which reflected three different types of interactions between hotels and customers in the digital domain. Interestingly, most of Italian hotels were found to adopt a reductionist approach to UGC and E-WOM management, turning out to be ineffective to exploit them for the purpose of quality improvement and hospitality service excellence.

Hotels were found to be largely unaware of the importance of UGC and web-based communication with customers to improve their digital business strategy. Tailored management approaches are needed to realize the full potential of hotels' online content responsiveness for the purpose of value co-creation and service co-production.

This is one of the first studies investigating the strategic and management perspectives embraced by hotels to handle their interactions with customers in the digital arena.

Free knowledge sharing in the online health community has been widely documented. However, whether free knowledge sharing can help physicians accumulate popularity and further the accumulated popularity can help physicians attract patients remain unclear. To unveil these gaps, this study aims to examine how physicians' popularity are affected by their free knowledge sharing, how the relationship between free knowledge sharing and popularity is moderated by professional capital, and how the popularity finally impacts patients' attraction.

The authors collect a panel dataset from Hepatitis B within an online health community platform with 10,888 observations from April 2020 to August 2020. The authors develop a model that integrates free knowledge sharing, popularity, professional capital, and patients' attraction. The hierarchical regression model is used to for examining the impact of free knowledge sharing on physicians' popularity and further investigating the impact of popularity on patients' attraction.

The authors find that the quantity of articles acted as the heuristic cue and the quality of articles acted as the systematic cue have positive effect on physicians' popularity, and this effect is strengthened by physicians' professional capital. Furthermore, physicians' popularity positively influences their patients' attraction.

This study reveals the aggregation of physicians' popularity and patients' attraction within online health communities and provides practical implications for managers in online health communities.

Compared to traditional (domestic) e-commerce consumers, cross-border electronic commerce (CBEC) consumers may face greater information asymmetry in the CBEC purchase process. Given this background, however, the literature has paid limited attention to the informational antecedents that influence consumers' perceptions of transaction costs and their CBEC purchase intentions. To fill this gap, this study integrates the elaboration likelihood model (ELM) and transaction cost theory (TCT) to develop a model for exploring how product (website informativeness, product diagnosticity and website interactivity as the central route) and external (country brand, website policy and vendor reputation as the peripheral route) informational antecedents affect consumers’ evaluations of transaction costs in terms of uncertainty and asset specificity and their CBEC purchase intentions.

This study employs a survey approach to validate the model with 766 Generation Z CBEC consumers based on judgment sampling. The partial least squares (PLS) technique is adopted for data analysis.

The results show that all the proposed central and peripheral informational antecedents reduce consumers’ perceptions of uncertainty and asset specificity, which in turn negatively influences their CBEC purchase intentions.

Through this investigation, this study increases our understanding of how product and external informational antecedents affect consumers’ evaluations of transaction costs, which subsequently determine their CBEC purchase decisions. This study offers theoretical contributions to existing CBEC research and has practical implications for CBEC organizations and managers.

The study aims to provide a detailed definition of Destination Cultural Reputation while also exploring its impact on tourist satisfaction through an investigation of the dynamics between these two elements. Additionally, the potential moderating role of on-site engagement in sustainable activities has been investigated, examining whether satisfaction prompts tourists to exhibit behaviors such as the intention to return and recommend the cultural destination.

To achieve these objectives, a survey and a structural equation model, based on a sample of 647 visitors to an important UNESCO World Heritage site (i.e. Urbino), have been adopted.

Findings confirm tourists’ recognition of the destination’s cultural reputation, supporting its relationship with visitor satisfaction. Additionally, tourist satisfaction is positively associated with destination loyalty. However, on-site sustainable activities negatively moderate the relationship between destination reputation and tourist satisfaction. This suggests that a favorable cultural reputation should align with quality sustainable activities in the destination to prevent tourist dissatisfaction.

The paper offers valuable practical insights for destination managers and policymakers aiming to enhance appeal and sustainability.

The study contributes to enhancing the understanding of the complex relationship between reputation, satisfaction, and loyalty in cultural destinations. In addiction it measures the reputation of tourist destination through the specific cultural dimension.

This study investigates the service quality dimensions of hotel resorts in renowned beach destinations of Thailand. It also explores the relationship between review text sentiment expressed in online platforms and the satisfaction ratings provided for those reviews.

The study employs a two-step analysis approach: first, supervised and unsupervised machine learning via support vector machine (SVM) and latent Dirichlet allocation (LDA) are used to identify service quality dimensions, and second, SmartPLS with PROCESS macro is applied to analyze the moderating roles of quality signals and reviewer’s experience on the relationship between sentiment and satisfaction rating. The dataset comprises 102,179 online reviews from TripAdvisor, focusing on 187 selected hotels rated from 3 to 5 stars.

Eight service quality dimensions were identified, including leisure activities, tangibles and surroundings, reliability, responsiveness, service process, food, empathy and ambience. The study underscores that the service process stands as the sole dimension exhibiting negative sentiment. Furthermore, the analysis revealed a robust positive association between sentiment of review texts and satisfaction, and reviewers’ experience and brand affiliation influenced the relationship between customer sentiment and satisfaction.

Hotel managers should focus efforts on maintaining tangible aspects while enhancing existing service quality level of other dimensions, particularly those related to intangible elements. Independent hotels might implement quality audit to ensure that service quality gaps are monitored.

This study contributes an examination of the moderating roles of quality signals and reviewer’s experience on the relationship between review sentiment and satisfaction rating in online reviews.

The case is a secondary sourced case. Information for the case was found from news articles and interviews.

David’s Bridal was a privately held corporation generating $1.3bn in annual revenue and employing over 12,000 employees. David’s Bridal filed bankruptcy not once but twice. This case examines the bridal industry and the environmental factors that led to the two bankruptcies. Bridal dresses are at the top of wedding categories. Environmental factors causing bankruptcy included online competition, reputation as seen through the eyes of the consumer, COVID, and supply chain challenges. David’s Bridal first looked to Jim Marcum to turn the corporation around and when this failed, they created a new management team after the second bankruptcy to save the company.

The case is designed as an interdisciplinary case for undergraduate leadership, advanced accounting or undergraduate strategy courses. The case was tested in MGMT 330: Leading People in Organizations. This case is appropriate for junior- and senior-level students.This case will be used in ACCT 402: Advanced Accounting – a senior-level course. The case gives perspective on going concern opinions and the strategic implications of bankruptcy.Possible textbooks▪ Christensen, T., Cottrell, D. and Budd, C. (2023). Advanced Financial Accounting (13th ed.). McGraw-Hill.▪ Hoyle, J., Schaefer, T. and Doupnik, T. (2024). Advanced Accounting (15th ed.). McGraw-Hill▪ Rothaermel, F. T. (2024). Strategic Management (6th ed.). McGraw-Hill

Online open innovation platforms provide opportunities for product users to participate in the innovation process and contribute their ideas to the platform. Nonetheless, they also present a significant challenge for platform managers, who select high-quality innovations from a massive collection of information with diverse quality.

In this study, the authors employed a machine learning method to automatically collect a real dataset of 2,276 innovations and 30,004 detailed comments from the online platform of IdeaExchange and then conducted empirical experiments to verify the study hypothesis.

Results show that extraversion, conscientiousness and openness to experience positively and directly influenced the quality of their innovation. Furthermore, an individual's social network position mediated among extraversion, neuroticism, conscientiousness and openness to experience and the quality of an innovation.

Results showed that extraversion, conscientiousness and openness to experience positively and directly influenced the quality of their innovation. Furthermore, an individual's social network position mediated among extraversion, neuroticism, conscientiousness, openness to experience and the quality of innovations.

This study combined the Big Five personality traits theory and social network theory to examine the association between user intrinsic personality traits, social network position and the quality of their innovative ideas in the context of online innovation platforms. Additionally, the findings provide new insights for platform managers on how to select high-quality innovation information by considering user personality traits and their social network position.

By conducting a longitudinal study, this study aims to investigate how the role of hotel attributes in destination competitiveness changed through the stages of pre-, amid and recovery from the crisis.

First, the latent Dirichlet allocation method was used to identify hotel attributes from 15,137 online reviews, and then a sentiment analysis was performed to determine tourist satisfaction with the subject attributes. Second, separate asymmetric impact competitor analyses were conducted for the three stages of the crisis, and their results were compared with understand how the role of the hotel attributes changed throughout the crisis.

The results revealed that the impacts of hotel attributes on tourist satisfaction and destination competitiveness differed significantly at each stage of the crisis.

This research expands the existing literature by offering valuable insights by elucidating the changing characteristics of hotel attributes at each crisis stage. The results extend the body of knowledge in destination management by providing evidence on the validity of asymmetric impact competitor analysis.

To fully understand the impact of a crisis (e.g. COVID-19) on destination competitiveness with a focus on the hotel sector, this research conducted a longitudinal study that covers three stages of the crisis (i.e. pre-, amid and post-crisis). Moreover, unlike previous studies, this research considers the asymmetric relationships between service attributes and overall tourist satisfaction, as well as competitors’ information.