Search results

The digital transformation in the banking industry has brought about complexity and competitiveness which has made differentiation challenging for banks. Complemented by consumer empowerment through high accessibility of information on the internet, this has led to a phenomenon known as switching behavior. The purpose of this review is to examine the determinants governing switching behavior among bank customers. This review highlights the importance of research which looks beyond pre-adoption behavior by examining post-adoption behavior; what happens after initial technology acceptance.

This review examines 44 journal articles researching switching behavior published between 1995 and 2022 in top journals. From a synthesis of literature, a conceptual framework for analysis and understanding switching behavior is presented.

Although various scholars have investigated switching behavior among bank customers, there are few studies which provide a comprehensive review and research classifications in this area. This review classifies key determinants of switching behavior into socio-demographic factors, situational triggers, influential triggers and reactional triggers. Structural equation modelling is the most common research methodology utilized in reviewed articles. The literature review reveals that mediators and moderators are less commonly deployed compared to determinants. Findings also indicate switching behavior studies still lack theory-driven conceptual frameworks.

This paper is the first systematic literature review on switching behavior research among bank customers spanning across 28 years in top academic journals. It integrates insights from 44 relevant research papers through publication trends. This review identifies key research gaps and provides future research directions.

The purpose of this paper is to test and compare different conceptual approaches for perceived value in a service context.

Perceived value is an outcome construct that results from various benefits received and sacrifices devoted to achieve a particular exchange of a service. The paper compares three different modeling approaches (Type 1, Type 2, and Type 4) for perceived value using data from an in‐flight survey. The questionnaire covered topics such as perceived service quality and overall satisfaction, price perception, customer value, and customer retention.

The theoretical discussion repeatedly emphasizes that only the formative modeling of perceived value fits the arguments put forward in the existing literature. This study replicates and extends a study by Lin et al. in the airline service context. The paper reports details about the impact of the proposed seven “get” and “give” components, together with an analysis of the consequences perceived value has on satisfaction, loyalty, and word‐of‐mouth.

The findings suggest extensions and improvements concerning measurement and conceptual issues.

Perceived value shows a substantial effect on behavioral consequences. Service operations must observe the perception of atmospherics emerging from the main service encounters next to considering functional aspects.

Misconceptualizations of multi‐item constructs are well known. However, critical discussions and empirical tests are still scarce in the tourism field. This paper tests and compares different conceptual approaches for perceived value in a service context.

This chapter enhances insights into destination image and competitor assessments by extending the research framework of perception-based market segmentation by two perspectives: allowing generating individual sets of competitors and contrasting two stages of travel experience: pre- and after trip. The empirical study is based on two samples of leisure travelers: a mix of international travelers who just finished their trip to Thailand and a group of European travelers interested in visiting Thailand. Against conventional assumptions though supporting more recent findings on destination decision making the majority of travelers did not identify any direct competitor.

Destination recommender systems need to become truly human‐centric in their design and functionality. This requires a profound understanding of human interactions with technology as well as human behavior related to information search and decision‐making in the context of travel and tourism. This paper seeks to review relevant theories that can support the development and evaluation of destination recommender systems and to discuss how quantitative research can inform such theory building and testing.

Based on a review of information search and decision‐making literatures, a framework for the development of destination recommender systems is proposed and the implications for the design and evaluation of human‐centric recommender systems are discussed.

A variety of factors that influence the information search and processing strategies that influence interactions with a destination recommender system are identified. This reveals a great need for data‐driven models to inform recommender system processes.

The proposed framework provides a basis for future research and development in the area of destination recommender systems. The paper concludes that the success of a specific destination recommender system will depend largely on its ability to anticipate and respond creatively to transformations in the personal and situational needs of its users. Such system intelligence needs to be based on empirical data analyzed with sophisticated quantitative methods. The importance of recommender systems in tourism marketing is also discussed.

Relationship marketing requires a thorough understanding of the long‐run perspective of the supplier‐customer interaction. The concept of customer loyalty can be applied to emphasize the behavioural and attitudinal aspects of this interaction. This study investigates the antecedents of future customer loyalty in the commercial airline industry by applying structural models under four prototypical past loyalty conditions. These conditions are based on behavioural and situational descriptors and labelled in analogy to Day’s compositional approach. It is shown that the superiority of relative attitudes claimed by Dick and Basu cannot be confirmed. Corporate image of the service provider is, along with service quality and customer satisfaction, a powerful and illustrative component for explaining future customer loyalty. When comparing the a priori defined conditions (low, latent, spurious, and true loyalty) it turns out that the structural evaluative differences can be partially interpreted by the phenomena which are described as affective and calculative commitment in the literature. However, it is claimed to consider situational factors such as the character of the buying and decision‐making process in much more detail.

Academic researchers love multi‐category answer formats, especially five‐ and seven‐point formats. More than a decade ago Josef Mazanec concluded that these formats may not the best choice, and that simple binary‐answer options are preferable in some empirical survey contexts. The purpose of the present study is to investigate empirically Mazanec's hypothesis in the context of the measurement of evaluative beliefs relating to fast‐food restaurants.

The authors conducted an online experiment that asked respondents to assess evaluative beliefs relating to fast‐food brands using either a forced binary (n=100) or a seven‐point answer format (n=100). The authors also measured preferences for each of the fast‐food restaurants, user friendliness, and recorded the actual completion times for the survey.

The results indicate that the full binary answer format outperforms the popular seven‐point multi‐category format with respect to stability, concurrent validity, and speed of completion.

Given the demonstrated strengths of full binary measures, they should be used more by both practitioners and academics when measuring evaluative beliefs.

This study provides empirical evidence of the strong performance of the forced binary‐answer format for the measurement of evaluative beliefs, and thus challenges current measurement practice among academics and practitioners.