Search results

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 research delineates the interdependencies between e-service quality (e-SQ), product quality (PQ) and food biosafety measures (FBM) in shaping consumer satisfaction and loyalty within the online food delivery services (OFDS) landscape. Anchored by the technology acceptance model (TAM) and the theory of planned behavior (TPB), the study integrates these frameworks to examine how perceived service efficiency, reliability, product appeal and biosafety protocols contribute to overall consumer trust and repurchase intentions.

Surveys were conducted on several 100 online food delivery app users, ages 20 to 64, in major cities in Colombia, which provided data for structural equation modeling analysis.

The analysis revealed that reliable, responsive service and appealing food presentation significantly influence consumer perceptions of behind-the-scenes safety protocols during delivery. Strict standards around mitigating contamination risks and verifiable handling at each point further engender trust in the platform and intentions to repurchase among users. The data cement proper food security as pivotal for customer retention.

Quantitatively confirming biosafety’s rising centrality provides an impetus for platforms to integrate and promote integrity, safety and traceability protection as a competitive differentiator.

The study’s originality lies in its comprehensive exploration of the OFDS quality attributes and their direct impact on consumer loyalty. Besides, it offers valuable insights for both academic and practical implications in enhancing service delivery and marketing strategies.

This study aims to identify the dimensions of satisfaction in the halal tourism literature by analyzing the identified antecedents and outcomes. The study aims to synthesize the current empirical findings in halal tourism. Additionally, this study provides a comprehensive understanding of the factors that lead to halal traveller satisfaction.

Using a meta-analysis approach, this paper synthesizes the fragmented and conflicting findings of 56 quantitative studies focusing on satisfaction and its antecedents and consequences in the halal tourism context. Data from 145 relationships representing an aggregate sample size of 21,173 were used. Additionally, this study extends the analysis by incorporating contemporary factors such as the impact of COVID-19, sample size and gender as moderators.

The findings indicate that both physical characteristics and psychological aspects are positively related to satisfaction. Further, this study reported that endorsement and revisit intention are the significant consequences of satisfaction. Lastly, this study identifies the significant moderating effect of the COVID-19 pandemic, sample size and gender on the relationship between satisfaction and its antecedents/consequences.

Global halal tourism industry caters to Muslim and non-Muslim tourists across the globe; this article identifies the contributing factors of satisfaction in the halal tourism context. Policymakers can adapt according to their needs and preferences.

This study provides cumulative evidence to the literature regarding the relationship between satisfaction and its antecedents/consequences in halal tourism. This is the first meta-analysis study on the mentioned topic, making significant theoretical, managerial and methodological contributions to halal tourism research.

This study aims to explore the challenges faced by the tourism and hospitality industry following the COVID-19 pandemic and to propose effective strategies for recovery and resilience of this sector.

The study analysed the challenges encountered by the tourism and hospitality industry post-pandemic and identified key strategies for overcoming these challenges. The study utilised the modified Delphi method to finalise the challenges and employed the Best-Worst Method (BWM) to rank these challenges. Additionally, solution strategies are ranked using the Criteria Importance Through Intercriteria Correlation (CRITIC) method.

The study identified significant challenges faced by the tourism and hospitality industry, highlighting the lack of health and hygiene facilities as the foremost concern, followed by increased operational costs. Moreover, it revealed that attracting millennial travellers emerged as the top priority strategy to mitigate the impact of COVID-19 on this industry.

This research contributes to understanding the challenges faced by the tourism and hospitality industry in the wake of the COVID-19 pandemic. It offers valuable insights into practical strategies for recovery. The findings provide beneficial recommendations for policymakers aiming to revive and support these industries.

This study aims to develop a customer-centric model based on an online customer experience (OCE) construct relating to e-loyalty, e-trust and e-satisfaction, resulting in improved Net Promoter Score for Indian digital banks.

This study used an online survey method to gather data from a sample of 485 digital banking users, from which usable questionnaires were obtained. The obtained data were subjected to thorough analysis using partial least squares structural equation modelling to further investigate the research hypotheses.

The main factors determining digital banks’ OCE were perceived customer centrality, perceived value and perceived usability. Additionally, relevant constructs were evaluated using importance-performance map analysis.

This study used convenience sampling for the urban population using digital banking services; therefore, the outcome may be generalized to a limited extent. To further strengthen digital banking, it would be valuable to imitate studies in other countries.

There is a lack of research on digital banking and OCE in India; thus, this study will help rectify this issue while providing valuable insights. This study differs from others in that it examines the connections between online customer satisfaction, loyalty, trust and the bottom line of financial institutions using these factors as dependent variables instead of traditional measures.

This paper aims to examine the impact of the COVID-19 pandemic on the private label food products, specifically assessing the stability and changes in factors influencing purchasing decisions, and comparing pre-pandemic and post-pandemic datasets.

The study employs the Extra Tree Classifier method, a robust quantitative approach, to analyse data collected from questionnaires distributed among two distinct consumer samples. This methodological choice is explicitly adopted to provide a clear classification of factors influencing consumer preferences for private label products, surpassing conventional qualitative methods.

Despite the profound disruptions caused by the COVID-19 pandemic, this research underscores the persistent hierarchy of factors shaping consumer choices in the private label food market, showing an overall stability in consumer behaviour. At the same time, the analysis of individual variables highlights the positive increase in those related to product quality, health, taste, and communication.

The use of online surveys for data collection may introduce a self-selection bias, and the non-probabilistic sampling method could limit the generalizability of the results.

Practical implications suggest that managers in the private label industry should prioritize enhancing quality control, ensuring effective communication, and dynamically adapting strategies to meet evolving consumer preferences, with a particular emphasis on quality and health attributes.

This study contributes to the existing body of literature by providing insights into the profound transformations induced by the COVID-19 pandemic on consumer behaviour, specifically in relation to their preferences for private label food products.

This study aims to explore the motivators of mothers’ experience on their engagement behavior in the case of baby care toiletries. Additionally, the role of Brand trust and commitment have also been evaluated.

The conceptual model was empirically tested based on the data collected through a survey using 320 samples from India and 431 samples from Sri Lanka. Data were analyzed using structural equation modeling.

Sensory and behavioral dimensions of brand experience can be considered as key drivers of brand trust and brand commitment among millennial mothers in the context of baby care toiletries. It was observed that brand trust had a significant positive impact on brand commitment. There was a significant relationship between brand trust, brand commitment and customer engagement. It was also inferred that brand loyalty is the consequence of customer engagement.

Marketers should gear up initiatives targeting new mothers through healthy aspects and genuine packaging to strengthen the mother’s trust through periodic uses of the product.

The present study is one of the unique empirical investigations that examine the antecedents of consumer engagement in the less researched context of high inherent risk products like baby toiletries.

This study aims to present a methodology and a system to support the technical and managerial issues involved in anomaly detection within the reverse logistics process of an e-commerce company.

A case study approach is used to document the company’s experience, with interviews of key stakeholders and integration of obtained evidence with secondary data.

The paper presents an algorithm and a system to support a more efficient and smart management of reverse logistics based on a set of anticipatory actions, and continuous and automatic monitoring of returned goods. Improvements are described in terms of a number of key performance indicators.

The analysis and the developed system need further applications and validations in other organizational contexts. However, the research presents a roadmap and a research agenda for the reverse logistics transformation in Industry 4.0, by also providing new insights to design a multidimensional performance dashboard for reverse logistics.

The paper describes a replicable experience and provides checklists for implementing similar initiatives in the domain of reverse logistics, in the aim to increase the company’s performance along four key complementary dimensions, i.e. time savings, accuracy, completeness of data analysis and interpretation and cost efficiency.

The main novelty of the study stays in carrying out a classification of anomalies by type and product category, with related causes, and in proposing operational recommendations, including process monitoring and control indicators that can be included to design a reverse logistics performance dashboard.

This study aims to identify the causes of the academia-industry divide in hospitality marketing research in the form of the “Research Devaluation Map” and offers ideas for discussion points and suggestions for change.

The conceptualization of the Research Devaluation Map was developed at an invitational thought-leadership conference. The authors were asked to produce a forward looking, critical reflection of hospitality marketing scholarship. The authors generated a preliminary idea and developed a methodology for its implementation. They then proposed a framework that explicated the divide between hospitality marketing research and industry practice and a list of discussion points regarding possible solutions.

The issues currently challenging the hospitality research field are found to include the choice of research topics (the “what”), the methods used in research (the “how”) and the systemic factors that shape the academic culture (the “systemic”). These three factors lead to a mutual devaluation of the academic–industry relationship in hospitality marketing, causing a schism between research and industry practice.

The Research Devaluation Map serves as a springboard for future research studies, providing a framework for naming and operationalizing the antecedents and results of the divide between hospitality marketing research and practice.

This paper takes a holistic look at the gaps in current hospitality marketing research and puts forth a framework to explain the roots of these issues. While certain of these issues are known to both researchers and practitioners, the originality of this paper lies in the creation of the Research Devaluation Map that identifies the causes and results of the disconnect between research and practice.

This study aims to understand the utility of personas and illustrate, through a case study, how a persona-building exercise in a Community Based Prevention Marketing (CBPM) training of community leaders elicited important insights that complemented findings from ongoing formative research on vaccine hesitancy in the Hispanic/Latino population in the USA during COVID-19 pandemic.

An exploratory concurrent parallel qualitative study design compared three personas created by community-based organization members (n = 37) to transcripts from five formative research focus groups (n = 30) from the same project. All participants in this study were recruited by the National COVID-19 Resiliency Network as part of their capacity-building and formative research activities. Grounded theory guided the content analysis.

This study found personas and focus groups to be complementary. A high degree of co-occurrence was observed when investigating the uptake of the COVID-19 vaccine under the categories of barriers, culture and communication. Between the two methods, the authors found strong associations between fear, disruption to the value system, work-related barriers, inaccessibility to health care and information sources and misinformation. Areas of divergence were negligible.

While personas provided background information about the population and sharing “how” to reach the priority population, focus groups provided the “why” behind the behavior, followed by “how”.

A community-driven persona-building process built on cultural community knowledge and existing data can build community capacity, provide rich information to assist in the creation of tailored messages, strategies and overall interventions during a public health crisis and provide user-centered, evidence-based information about a priority population while researchers and practitioners wait on the results from formative research.

This case study provided a unique opportunity to analyze the complementary effectiveness of two methods acting in tandem to understand the priority population: stakeholder-informed persona-building and participant-informed focus group interviews. Understanding their complementary nature addresses a time gap that often exists between researchers and practitioners during times of crises and builds on recommendations associated with bringing rigor into practice, promoting academic contribution to real-world issues and building collaborative partnerships. Finally, it supports the utility of a nimble tool that improves social marketers’ ability to know more about their audience for intervention design when time is of the essence and formative research is ongoing.