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This study aims to identify the key hotel characteristics and facilities that significantly influence customer satisfaction based on Google review scores. By applying decision tree analysis, the research seeks to determine which aspects, such as service quality, hotel facilities and location, play pivotal roles in shaping customer experiences. The objective is to provide professional with practical recommendations to improve service quality and cultivate enduring customer loyalty.

The research used a data set collected from Hotels.com, featuring various characteristics of 802 hotels in Izmir Province. Decision tree analysis was conducted using Classification and Regression Tree algorithm to explore the relationship between hotel characteristics and facilities with customer satisfaction.

The analysis revealed that the number of rooms is the primary factor influencing hotel ratings, with proximity to the airport and hotel classification also being significant. Additional factors such as public transportation distance and laundry services were important, while facilities such as ATMs, beach access and spas showed no significant impact on customer satisfaction. These findings emphasize the importance of core facilities and accessibility.

This study contributes to the literature by offering a novel approach, using decision tree analysis to assess hotel customer satisfaction with structured data. It provides practical implications for hotel managers, enabling them to make data-driven improvements to achieve customer satisfaction. The integration rules created by the decision tree model into hotel management systems can enhance operational efficiency and competitive advantage in the hospitality industry.

This research addressed online customer-to-customer (C2C) incivility during digital service recovery.

To examine the effectiveness of managerial responses to online C2C incivility post a restaurant service failure, a 2 (Managerial response: general vs specific) x 2 (Failure severity: high vs low) quasi-experimental design was employed. A pretest was conducted with 123 restaurant consumers via Amazon Mechanical Turk, followed by a main study with 174 restaurant consumers. Taking a mixed-method approach, this research first asked open-ended questions to explore how participants perceived the restaurant’s motivation for providing a generic versus a specific response. Hayes’ (2013) PROCESS procedure was then performed for hypotheses testing.

The results revealed significant interaction effects of managerial responses and failure severity on perceived online service climate and revisit intention, mediated by trust with managerial responses.

This research yielded unique insight into C2C incivility management literature and industry practices in the context of digital customer service recovery.

The research aimed to identify factors influencing customer loyalty in the use of mobile telecommunication services in Vietnam, focusing on two dimensions “attitudinal loyalty” and “behavioral loyalty.”

Based on survey data collected from 820 in two of Vietnam’s major cities users, Hanoi and Ho Chi Minh City, the data were processed using SPSS and AMOS software.

The study identified four factors affecting customer loyalty to mobile telecommunication services, with perceived service quality directly impacting both attitudinal and behavioral loyalty. Corporate image and perceived switching costs influenced attitudinal loyalty, while trust affected behavioral loyalty. Moreover, perceived service quality indirectly influenced attitudinal loyalty through corporate image and perceived switching costs.

The study only focuses on a limited number of factors influencing mobile telecommunications service user loyalty, its restricted geographical sample from only Hanoi and Ho Chi Minh City, and the simplification of perceived switching costs without considering their various components, such as psychological, financial and procedural costs, which could provide more comprehensive experimental and theoretical insights.

The study reveals that customer loyalty in Vietnam’s mobile telecommunications sector is linked to the relationship between attitude toward the service provider and continued usage behavior, categorizing customer groups into genuine loyalty, latent loyalty, feigned loyalty and disloyalty. It suggests that service providers should focus on improving service quality and cultivating a positive, transparent corporate image to bolster customer trust, foster stable relationships and remain competitive in the market.

The research model combines Oliver’s (1999) theory of loyalty with Aydin and Özer’s (2005) research model, focusing on perceived service quality, corporate image, trust and perceived switching costs, examining their relationships with both behavioral and attitudinal loyalty simultaneously.

Technology serves as a key catalyst in shaping society and the economy, significantly altering customer dynamics. Through a deep understanding of these evolving behaviors, a service can be tailored to address each customer's unique needs and personality. We introduce a strategy to integrate customer complaints with their personality traits, enabling responses that resonate with the customer’s unique personality.

We propose a strategy to incorporate customer complaints with their personality traits, enabling responses that reflect the customer’s unique personality. Our approach is twofold: firstly, we employ the customer complaints ontology (CCOntology) framework enforced with multi-class classification based on a machine learning algorithm, to classify complaints. Secondly, we leverage the personality measurement platform (PMP), powered by the big five personality model to predict customer’s personalities. We develop the framework for the Indonesian language by extracting tweets containing customer complaints directed towards Indonesia's three biggest e-commerce services.

By mapping customer complaints and their personality type, we can identify specific personality traits associated with customer dissatisfaction. Thus, personalizing how we offer the solution based on specific characteristics.

The research enriches the state-of-the-art personalizing service research based on captured customer behavior. Thus, our research fills the research gap in considering customer personalities. We provide comprehensive insights by aligning customer feedback with corresponding personality traits extracted from social media data. The result is a highly customized response mechanism attuned to individual customer preferences and requirements.

This research investigates the role of customer involvement (CINV) in customer relationship management (CRM) dimensions and customer retention (CR) in Ghana’s hotel industry.

This quantitative-based explanatory research obtained primary data via structured questionnaires from 277 hotel customers in Ghana, processed it with SmartPLS4.0 software, and analysed it with structural equation modelling.

CRM dimensions (CRM-based technology, managing knowledge and personalisation of services) and CINV positively affect CR. Also, CINV partially mediates the interactions between the CRM dimensions and CR in Ghana’s hotel industry.

The study is geographically limited to hotels in Ghana and conceptually limited to three CRM dimensions, CINV and CR. Methodologically, the study was limited to the quantitative approach. However, our outcomes imply that hotels in Ghana that invest in relevant CRM dimensions would improve CR. CRM-CR association can also be improved through CINV.

The study outcomes imply that when Ghanaian hotels implement the CRM dimensions and foster active CINV, their customers’ retention will improve significantly. Hence, CRM and CINV are prerequisites for enhancing CR in Ghana’s hotel industry.

The study offers valuable contributions to the current literature on CRM, consumer behaviour and hospitality management, especially in a developing economy context. Its novel contribution, the mediating role of CINV, would advance CRM studies in the hospitality sector.

This study explores how predictor variables (value congruence and customer–AI-assisted exchanges) lead tourism businesses to meet customer needs through contactless technology and enhance their willingness to pay more.

The research model was designed from the perspective of consumer-brand relationships and acceptance of AI device use. This study collected and analyzed 647 valid questionnaires using the structural equation modeling (SEM) approach.

The findings indicate that value congruence and customer-AI-assisted exchanges (CAIX) affect intimacy. Intimacy affects satisfaction and the willingness to pay more for contactless technological services. Moreover, brand trust and sensory brand experience play a role in moderating contactless technological services.

Effective interactions between customers and AI-assisted services significantly contribute to overall satisfaction. When AI systems can understand and respond appropriately to customer queries, needs, and preferences, they enhance customer experience and satisfaction levels, increasing overall customer satisfaction with AI services.

Research on showrooming has focused on investigating its antecedents, motivators and characteristics, leaving a gap regarding its consequences. Our study intends to build a comprehensive framework to examine the role of showrooming behaviour on showrooming satisfaction and customer loyalty while exploring its antecedents.

Data collection took place in Brazil through an electronic form distributed on social media, reaching 393 people. After eliminating responses from those who had no showrooming experience, the final sample consisted of 310 respondents. The questions captured the costs and benefits of showrooming, internet savviness, showrooming behaviour, satisfaction with showrooming and customer loyalty (i.e. repurchase intention and positive word-of-mouth). We performed partial least squares data analysis by means of the statistical package Smart PLS 4.

The results show that showrooming behaviour is positively influenced by internet savviness and the perceived benefits of showrooming but not by the perceived costs of showrooming. In addition, showrooming behaviour positively influences satisfaction with showrooming and customer loyalty (i.e. repurchase intention and positive word-of-mouth). Finally, we identify satisfaction with showrooming as a mediator between showrooming behaviour and customer loyalty.

Given that the implications of showrooming behaviour on customer loyalty remain understudied, this work contributes to the marketing literature by demonstrating the influence of showrooming behaviour on satisfaction with showrooming and its consequential effect on customer loyalty. Moreover, we confirmed the mediating role of customer satisfaction in the relationship between showrooming behaviour and customer loyalty.

Underpinning social identity theory (SIT) and service-dominant logic (SDL), the current paper seeks to explore the effect of self-presentation on online brand advocacy (OBA). Furthermore, this paper investigates the mediating role of hedonic value and the moderating role of customer interaction with e-commerce websites (i.e. Amazon, Walmart and eBay).

Data were collected from customers of three e-commerce platforms (i.e. Walmart, Amazon and eBay) using a structured questionnaire – multi-group analysis applied on SmartPLS 4.4.

Self-presentation has a positive role in increasing hedonic value and its impact on OBA. The moderating effect of customer interaction on these relationships is also investigated and found to be significant.

Our findings underscore the significance of fostering inclusive online communities and favorable online settings. Existing findings are consistent with overarching objectives of digital empowerment and enhanced online interaction quality. This paper contributes to harmonious and collaborative digital societies by encouraging personalized experiences that foster a sense of belonging among diverse customers.

This paper adds to the existing body of knowledge by comparing customer behavior on three major e-commerce platforms, going beyond the traditional focus on a single platform. Drawing on SIT and SDL, this paper provides a distinct nomological framework for OBA that unifies disparate constructs, filling theoretical gaps in our understanding of online customer behavior.

The importance of the agri-food supply chain in both food production and distribution has made the issue of its development a critical concern. Based on configuration theory and congruence theory, this research investigates the complex impact of supply chain concentration on financial growth in agri-food supply chains.

The cluster analysis and response surface methodology are employed to analyse the data collected from 207 Chinese agri-food companies from 2010 to 2022.

The results indicate that different combination patterns of supply chain concentration can lead to different levels of financial growth. We discover that congruent supplier and customer concentration is beneficial for companies’ financial growth. This impact is more pronounced when the company is in the agricultural production stage of agri-food supply chains. Post-hoc analysis indicates that there exists an inverted U-shaped relationship between the overall levels of supply chain concentration and financial growth.

Our research uncovers the complex interplay between supply chain base and financial outcomes, thereby revealing significant ramifications for agri-food supply chain managers to optimise their strategies for exceptional financial growth.

This study proposes a combined approach of cluster analysis and response surface analysis for analysing configuration issues in supply chain management.

Self-presentation has emerged as a pivotal marketing strategy for service providers seeking to craft virtual images in the peer-to-peer (P2P) accommodation sector. However, the literature lacks an understanding of conversational self-presentation, which offers more informal and personal communication.

Drawing upon social interaction theory and uncertainty reduction theory, this study explores the impact of conversational self-presentation and its interplay with space sharing and review ratings on customer purchases.

Utilizing the fixed effects model on a panel dataset comprising 498,817 observations from Airbnb, we discover a positive association between conversational self-presentation and customer purchases. Furthermore, our analysis reveals that space sharing reinforces this positive effect, while review ratings tend to diminish it. A deeper mechanism analysis indicates that perceived authenticity plays a mediating role in the relationship between conversational self-presentation and customer purchases.

This study highlights the importance of conversational communication in enhancing host–guest relationships under information asymmetry. However, the proposed model can be extended to other accommodation-sharing platforms in various regions, identifying whether cultural differences exist in explaining the importance of conversational self-presentation.

Marketers are suggested to build a harmonious customer–brand relationship and achieve superior performance through effective online communication.

This study adds valuable insights to the literature about self-presentation, social interaction and customer behavior by revealing the significance of conversational self-presentation in driving the growth of P2P accommodation businesses.