This study builds on previous discussion of an important area for both academics and academic journals – the issue of reviewers inappropriately asking for (or “coercing”) citation of their own work. That situation creates an opportunity for (hopefully a small number of) academics to engage in unethical behaviour, often with the goal of increasing their citation count. This study aims to draw attention to this often-overlooked issue, critically considering potential reviewer motivations and offering possible remedies.
This study reviews literature and critically discusses this issue, offering a typology for coercive citation suggestions and sharing previously unpublished commentary from Editors of leading journals.
This study provides a typology of reviewer motivations for coercing citations, suggests potential remedies and considers the positive and negative impacts of these suggestions.
This study identifies an area known from multiple discussions to be important to academics and Editors, where many want changes in journals’ practices. In response, this study provides recommendations for easy changes that would decrease the opportunity for unethical behaviour by reviewers and also, for some journals, improve the quality of reviews.
As internet banking service marketing platforms continue to advance, customers exhibit distinct behaviors. Given the extensive array of options and minimal barriers to switching to competitors, the concept of customer churn behavior has emerged as a subject of considerable debate. This study aims to delineate the scope of feature optimization methods for elucidating customer churn behavior within the context of internet banking service marketing. To achieve this goal, the author aims to predict the attrition and migration of customers who use internet banking services using tree-based classifiers.
The author used various feature optimization methods in tree-based classifiers to predict customer churn behavior using transaction data from customers who use internet banking services. First, the authors conducted feature reduction to eliminate ineffective features and project the data set onto a lower-dimensional space. Next, the author used Recursive Feature Elimination with Cross-Validation (RFECV) to extract the most practical features. Then, the author applied feature importance to assign a score to each input feature. Following this, the author selected C5.0 Decision Tree, Random Forest, XGBoost, AdaBoost, CatBoost and LightGBM as the six tree-based classifier structures.
This study acclaimed that transaction data is a reliable resource for elucidating customer churn behavior within the context of internet banking service marketing. Experimental findings highlight the operational benefits and enhanced customer retention afforded by implementing feature optimization and leveraging a variety of tree-based classifiers. The results indicate the significance of feature reduction, feature selection and feature importance as the three feature optimization methods in comprehending customer churn prediction. This study demonstrated that feature optimization can improve this prediction by increasing the accuracy and precision of tree-based classifiers and decreasing their error rates.
This research aims to enhance the understanding of customer behavior on internet banking service platforms by predicting churn intentions. This study demonstrates how feature optimization methods influence customer churn prediction performance. This approach included feature reduction, feature selection and assessing feature importance to optimize transaction data analysis. Additionally, the author performed feature optimization within tree-based classifiers to improve performance. The novelty of this approach lies in combining feature optimization methods with tree-based classifiers to effectively capture and articulate customer churn experience in internet banking service marketing.
Low-income consumers’ perceptions of access and inclusion in financial services, remain underresearched. To fill this gap, the purpose of this study, is to investigate elements of low-income consumers’ informal and formal financial service experiences, from their personal experience.
Mixed methods using data collected from low-income consumers in Latin America, reveal a spectrum of consumer perceptions making up access, inclusion and social dependence within financial service experiences. Scales, grounded in the consumer experience, are developed, validated and used to test a model of consumers’ service inclusivity perceptions.
Service costs, information and documentation difficulty, convenience and social dynamics influence low-income consumers’ perceptions of financial service inclusivity.
Analysis reveals differentiation in the impact of aspects of low-income consumers’ experiences between formal and informal financial services. Working directly with this unique population exposes the nuance of their financial service experiences.
This research provides a more holistic perspective on low-income consumers’ financial service experience and provides contextually relevant scales with robust psychometric properties. Services marketers can use this research to inform design and evaluation of financial service offerings for low-income consumers.
This research contributes to study of the wellbeing of low-income consumers by providing understanding of their financial service experiences from their point-of-view and providing contextually-relevant, empirically validated tools for future inquiry.
The e-services market is expected to reach nearly $500bn globally by 2028. As this marketplace grows, customer-to-customer interactions (CCIs) occurring through virtual channels will likely increase. Consequently, the purpose of this research is to examine how the context in which CCI’s occur (i.e. virtual vs in-person) and the frequency of their occurrence affects customer identification, leading to increased customer engagement and more favorable purchase behaviors.
Two studies were conducted to test the proposed models and hypotheses. The sample for Study 1 is comprised of college students taking in-person or online classes (n = 290). In Study 2, members of an online brand community (n = 125) were surveyed. Hypotheses were tested using structural equation modeling (SEM).
Overall, results support a mediation effect such that CCI context (virtual vs in-person) affects customer engagement and purchase behaviors via customer identification. Specifically, Study 1 finds that customer engagement behaviors (CEBs) are greater for in-person CCIs due to the frequency of interactions and heightened identification between customers. Study 2 further examines the CCI frequency-identification link and finds that customer-firm identification is the only form of identification that affects CEBs and purchase behaviors.
Limited customer engagement research has examined the effects of CCIs on CEBs, and research has rarely compared in-person to virtual CCI contexts. This paper addresses these shortcomings by testing the effects of in-person and virtual CCIs on CCI frequency, identification and CEBs. This research fills another important gap in the literature by considering the unique effects of specific dimensions of customer identification on CEBs and purchase behaviors.
This study aims to investigate the impact of virtual museum tours on intentions to visit on-site museums. Furthermore, the role of an authentic virtual tour experience and its drivers is examined.
The results of two studies, a field study in collaboration with one of the most renowned museums in Austria (n = 227) and an online survey (n = 153), were analyzed with a series of mediation models.
Visual appeal and narrative quality were significant drivers of an authentic virtual tour experience. Curiosity mediated the positive effect of virtual tour usage intention on on-site museum visit intention.
Although virtual reality has been considered a promising marketing tool in tourism, no research has explored the drivers of an authentic virtual tour experience. The findings of this study not only add new insights into the role of a virtual tour’s visual appeal and narrative quality in generating authentic experience and thus prompting virtual tour usage intentions but also demonstrate that virtual tours positively impact on-site visit intentions driven by curiosity.
This study aims to investigate the impact of customers’ delight on the likelihood of frontline employees (FLEs) receiving expressions of gratitude from customers, as well as the subsequent effects on their customer-focused and coworker-focused behaviors. Additionally, it examines how customer orientation moderates the relationship between FLE’s likelihood of receiving customer gratitude expressions and their performance behaviors.
The study used a sample from a Canadian retailer specializing in the sale of artistic and creative materials for artists, crafters and hobbyists. Longitudinal data was collected through a survey administered to frontline employees, unit managers and customers, spanning 7 assessment waves over a 12-month period. In total, the data set comprised 1,609 individual observations and 3,533 customers nested within 35 business units. The hypotheses were tested by using a multilevel longitudinal modeling approach.
This research has yielded important insights. First, significant relationships emerged between enhanced customers’ delight and an increased likelihood of FLEs receiving expressions of gratitude from customers. Second, gratitude expressions received from customers were found to be positively associated with prosocial behaviors toward both customers and coworkers. Third, the findings indicate that the impact of receiving customer gratitude expressions on FLEs’ performance behaviors is more pronounced for employees with a high level of customer orientation.
This study highlights the importance of investing in relationship-building strategies aimed at enhancing customers’ delight. This can motivate customers to express their gratitude toward service employees and to elicit higher prosocial behaviors from employees.
This study offers theoretical insights into gratitude, customer behaviors and employee performance in the retail industry. A pivotal contribution of this study to marketing literature lies in its paradigm shift, redirecting attention from the traditional examination of firm-customer relationships to a nuanced exploration of customer–employee relationships.
This paper aims to utilize an extended involvement-commitment and trust commitment model to examine post-consumption decisions related to food delivery app use.
A self-administered online survey was used to collect data from food delivery app users in the USA.
Findings validate a favorable role of perceived app security and menu description on trust in app recommendations. Trust was found to be positively related to involvement, commitment and willingness to provide feedback. The positive moderating role of perceived convenience and rewards and incentives was also confirmed in relation to consumers’ trust in app recommendations, and involvement and commitment
A key contribution of this study includes the development of a comprehensive model to understand postconsumption decisions related to the usage of food delivery apps. To the best of the authors’ knowledge, this study is also the first to unveil the antecedent and moderating factors related to food delivery app users’ willingness to provide feedback, share personal data and to pay more.
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