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Although various booking platforms have been contributing to the dramatic growth of hotel industry, little research has been conducted to understand consumer psychological processes and behaviors in online hotel booking. To fill this gap, the current study examines the effect of switching barriers (switching cost and alternative attractiveness) on consumers' decision postponement and repurchase intention. Additionally, the moderating effect of time pressure in different phases of booking decision is investigated.

A total of 352 samples was collected through an online platform. Data analysis was conducted via Amos 23 (structural equation modeling) and SPSS 24 (descriptive analysis and PROCESS macro).

Results show that switching cost and alternative attractiveness are two significant drivers of decision postponement and repurchase intention. Meanwhile, time pressure only has a significant moderating effect on the relationship between switching cost and decision postponement.

The findings of this research reveal that hotel operations need to implement strategies to prevent customers' delayed booking decisions and overcome the influence of time pressure on customer decision-making.

These findings stress the importance of consumer perceptions of switching barriers and time span when making hotel reservations online. Hotel practitioners are encouraged to provide multiple human–computer interaction applications to attract novice consumers and increase their familiarity with booking process.

This paper examines the relationships between bank switching and both customer vulnerability and consumer-oriented policies (financial education and disclosure practices).

The analysis employs microdata from the Special Eurobarometer on Financial Products and Services, for 24 European nations. It carries out a probit estimation on the factors explaining propensity of bank switching, focusing on three characteristics associated with customer vulnerability: an advanced age, low educational attainment and residence in a rural or a relatively poor region.

The authors report that the probability of bank switching is significantly lower for three groups of vulnerable customers: the elderly, the less educated and those living in deprived regions. Further the authors identify that national financial education policies and disclosure practices have no significant effects on bank switching.

Based on these results, the authors propose more targeted policies recognising customers' heterogeneity are required to increase bank switching behaviour.

This paper exploits a unique source of information on bank switching behaviour and customer characteristics across European nations. These data are complemented with information about consumer financial education policies and disclosure practices from the World Bank and geographical, market and regulatory factors at the regional and national levels. The paper contributes to two academic areas. First, it presents further evidence on heterogeneity of bank customer switching behaviour, addressed at improving the understanding of customer vulnerability in banking services. Second, it examines the efficacy of consumer-oriented policies (financial literacy and disclosure practices) in encouraging bank switching.

This study aims to synthesize and integrate findings from diverse research on the antecedents and moderators of customer loyalty in the banking sector. Through a comprehensive meta-analysis, the research seeks to understand the primary drivers of bank loyalty and the potential cultural, economic and social indicators that might influence these relationships.

A rigorous meta-analysis was conducted, analyzing 275 studies with 1,365 effect sizes involving over 134,000 bank customers from more than 50 countries. The research evaluated the effect sizes of the main relationships between loyalty antecedents and consequences and assessed the influence of cultural, economic and social moderators.

The study identified key antecedents of bank loyalty, with responsiveness, privacy, commitment, trust and empathy being paramount. Cultural dimensions, such as individualism and masculinity, significantly moderate the relationships between trust and loyalty. The human development index (HDI) was also identified as a significant economic moderator, particularly influencing the relationship between satisfaction and bank loyalty.

This research offers a holistic view of bank loyalty, bridging gaps from conflicting findings in prior literature. Examining a vast array of studies across diverse cultural and economic contexts provides empirical generalizations about bank loyalty behavior, offering valuable insights for academia and the banking industry.

This study aims to understand the reasons for individuals switching from traditional banks to Internet-only banks and examine how switching intentions differ between Generation X and Generation Z. Notably, Generation Z, being digital natives, exhibits distinct characteristics compared to Generation X, who often referred to as digital immigrants. Given the technology-driven nature of Internet-only banks, a multi-group analysis between these two generations was conducted.

This study utilizes Bansal’s push–pull–mooring model as a framework to analyze switching intention. The study collected survey data from 383 Korean participants, consisting of 198 participants from Generation Z and 185 participants from Generation X.

The findings indicate that low satisfaction and discomfort are factors that push people to leave traditional banks. Specifically, Generation Z shows a significantly higher inclination to leave traditional banks due to discomfort. On the other hand, relative advantage, compatibility, observability and trialability are factors that pull people to switch to Internet-only banks. Generation X is more likely to consider adopting Internet-only banks when compatibility is high and complexity is low.

This study is the first to explore unique motivators for Generation Z, such as their discomfort with interpersonal interactions in the retail banking sector. These findings challenge earlier research emphasizing human interaction’s importance in technology adoption, offering insights into their future adoption of contactless services.

Switching behavior is predominantly seen in the consumer buying behavior of the mobile industry. This research aims to identify the factors influencing consumers to switch from their present mobile service provider. The consumer of the mobile industry operates in a dynamic and ever-changing environment that is difficult to predict, so this paper aims to focus on these issues.

The selection of factors was made with the help of qualitative study and quantitative research methods for further findings; with the help of a structured questionnaire, a total of 514 valuable responses were collected to get the results. Exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and structural equation modeling (SEM) were used to analyze the data.

The finding shows that technology and edge-on-competition (TEC) and pricing have a negative influence on customer switching behavior. The switching cost (SC) is the most significant factor and has a positive impact, while service encounter failure (SEF) also positively impacts switching behavior.

The findings provide important implications for consumers switching brands if they are finding alternative offers that are cost-effective and SEF from service providers

The study of one of the largest mobile markets is learning lessons for other markets around the world. This study will be helpful for mobile service provider companies in their branding and marketing strategies. This study will also be helpful to practitioners, educators and researchers in understanding the consumer behavior of mobile users.

The learning of the largest mobile market will be a great learning lesson for other mobile markets around the world. Consumer behavior will help marketers follow ethical practices and make their strategy so a consumer does not switch brands and remain satisfied with the existing brand.

The study provides unique learning for practitioners, educators and researchers to understand the consumer behavior of mobile users. This will help marketers create factors that stop consumers from switching brands and develop strategies to retain customers.

This study aims to investigate the role of three customer equity drivers on customer repurchase intent in business-to-business (B2B) markets. It also explores the interconnected nature of equity drivers, specifically, the effects of brand equity and value equity on relationship equity. Further, it investigates how perceived switching costs moderates the interrelationships between customer equity drivers. The authors explore the interrelationships between the customer equity drivers in a B2B context involving commodity products in a developing market.

Data collection was done from a pool of 184 institutional customers of a lubricant brand in a developing market. The sample had representations of buyer organizations across sectors, namely, automobile, cement, metal, fertilizer, railway, defence and mining, etc. The final data were subjected to partial least squares-based structural equation modeling to test the hypothesized model.

The study found a direct effect of brand equity, and value equity on relationship equity and an indirect effect on repurchase intent, namely, relationship equity. Perceived switching cost was found to moderate the interaction between brand equity and relationship equity as well as between value equity and relationship equity. The direct effect of relationship equity on repurchase intent was also significant.

The study implies that B2B firms should ground their marketing program on these customer equity drivers, especially when dealing with commodity products. The absence of any of these drivers would be detrimental in customer retention. The study also establishes the relevance of switching cost(s) and its impact on the underlying dynamics between the different equity drivers in the context of commodity products. The customer equity drivers along with switching costs, if managed well, may become switching barriers for customers and eventually would ensure recurring revenue through repeat purchases.

To the best of the authors’ knowledge, this is one of the first studies that focuses on the disaggregated effect of customer equity on customer outcomes in the B2B context. Furthermore, this study investigates how perceived switching costs moderates the interrelationships between customer equity drivers in the industrial sales context in an emerging market.

Farmers in India are hesitant to adopt organic farming (OF) despite high demand for organic products and favorable policy measures to encourage the practice. Therefore, this study aims to assess the OF adoption barriers faced by Indian farmers using a systematic method of multi-criteria decision making (MCDM).

The authors explored eighteen barriers to OF adoption by conducting a literature survey and discussion with experts on OF. Then the authors used a combined method of Grey Decision Making Trial and Evaluation Laboratory (DEMATEL) and Interpretive Structural Modeling (ISM) methodology to rank the barriers and analyze their interactions.

The analysis reveals that “Lack of knowledge and information,” “lack of financial capacity of farmers’ and “lack of institutional support” are the cause (independent) barriers that significantly impact other barriers. The top three effect (dependent) barriers are “lack of availability of organic inputs,” “personal characteristics such as age, attitudes and beliefs” and “lack of premium pricing,” which are affected by the other barriers.

This research work will help the decision makers understand the barriers to OF adoption in India and their interrelationships. The proposed framework enables them to focus on the high-priority independent barriers, which will subsequently impact the other dependent barriers.

Previous research on OF adoption barriers lacked a multifaceted scientific approach, which is necessary because OF is a complex system and needs a thorough investigation to assess the interaction between the barriers. The research attempts to fill this gap and addresses the complex nature of adoption barriers.

This study aims to predict customer churn in resort hotels by calculating the churn probability of repeat customers for future stays in the same hotel brand.

Based on the recency, frequency, monetary (RFM) paradigm, random forest and logistic regression supervised machine learning algorithms were used to predict churn behavior. The model with superior performance was used to detect potential churners and generate a priority matrix.

The random forest algorithm showed a higher prediction performance with an 80% accuracy rate. The most important variables were RFM-based, followed by hotel sector-specific variables such as market, season, accompaniers and booker. Some managerial strategies were proposed to retain future churners, clustered as “hesitant,” “economy,” “alternative seeker,” and “opportunity chaser” customer groups.

This study contributes to the theoretical understanding of customer behavior in the hospitality industry and provides valuable insight for hotel practitioners by demonstrating the methods that facilitate the identification of potential churners and their characteristics.

Most customer retention studies in hospitality either concentrate on the antecedents of retention or customers’ revisit intentions using traditional methods. Taking a unique place within the literature, this study conducts churn prediction analysis for repeat hotel customers by opening a new area for inquiry in hospitality studies.

This study aims to investigate the effect of financial satisfaction (FS) on customer loyalty in the banking industry.

The study followed an explanatory research design using responses from 334 respondents from commercial banks in Tanzania. A stepwise regression analysis was used to validate the relevance of the study model.

The results indicate a positive and statistically significant association between customer loyalty and FS with levels of assets (β = 0.598, p < 0.001), savings (β = 0.186, p < 0.001) and debts (β = 0.065, p < 0.001). Of the three dimensions of FS, the level of assets had the strongest contribution to customer loyalty, followed by the level of savings and debts, in that order.

The study used a model of FS that was linked to customer loyalty in the Tanzanian banking industry. It is recommended that the model be tested in other environments to increase the generalizability of the findings.

This study provides an alternative way for banks to strengthen customer loyalty by enhancing FS.

The FS model (Joo and Grable, 2004) and the social exchange theory (Blau, 1964) are used in this study to propose a model of customer loyalty in the banking industry. Customer loyalty and FS have not been connected in prior studies.

The success of sharing economy (SE) platforms has made it attractive for many firms to adopt this business model. However, the inherent weaknesses of these platforms, such as their unstandardized service quality, the burden of maintenance on resource owners and the threat of multi-homing, have become increasingly apparent. Previous prescriptions for addressing these weaknesses, however, are limited because they do not account for factors such as compliance costs and information asymmetry, and tend to solve the problem on only one side of the platform at the expense of the others. By exploring the strategies deployed and actions undertaken across the development of Xbed, a successful accommodation-sharing platform in China, this study aims to explore an alternative solution that would overcome the aforementioned weaknesses without the corresponding compromises.

The authors conducted a case study consisting of secondary data and interviews with 15 informants who were representatives of Xbed's top management, organizational IT functions and its various business units.

The authors identified three inherent weaknesses that may be found in SE business models and how these weaknesses can be overcome without compromising other stakeholders through an auxiliary platform. The authors also discuss the advantages, characteristics, deployment and nature of auxiliary platforms.

This model contributes an in-depth view of establishing and nurturing auxiliary platforms to complement a primary SE platform. Owners and managers of SE platforms may use our model as the basis of guidelines for optimizing their platforms' development, thereby extending the benefits of SE to more stakeholders.