Purpose -The paper aims to examine the antecedents and consequence of casino employees' ethical behavior. In particular, it proposes that both distributive and procedural justice have positive influences on such behavior, which in turn positively affects workers' job satisfaction. The paper aims to help casino management pinpoint areas for enhancing and promoting employees' ethical behavior so as to benefit industry stakeholders. Design/methodology/approach -A questionnaire was designed based on a literature review and preliminary conversations with 37 casino employees. These were distributed to frontline casino employees working in the slot and table games departments. Exploratory factor analysis and path analysis were employed to test the proposed model. Findings -The paper shows that casino employees' ethical behavior was positively influenced by both procedural and distributive justice, with the former a slightly stronger motivator. Of the three proposed determinants of casino employees' job satisfaction, distributive justice had the most strongly positive effect. Practical implications -This paper suggests that action could be taken by management to enhance employees' perception of both distributive and procedural justice to motivate ethical behavior. Furthermore, casino managers should be aware that distributive justice plays a more important role than procedural justice and ethical behavior in enhancing casino employees' job satisfaction. In making decisions, they should consider outcome fairness to demonstrate distributive justice. Originality/value -Currently, to the best of the authours' knowledge, there is no study linking both distributive and procedural justice with employees' ethical behavior and job satisfaction within a single framework. In addition, there is no research evaluating how organizational justice influences employees' ethical behavior when interacting with customers. This paper fills this gap.

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Purpose – The purpose of this study is to reflect on Bowen and Chen’s study and provide insight for researchers to help them build loyalty models that will fit the consumer behavior of Millennials and managers as they build customer loyalty with Millennials. In 2001, Bowen and Chen developed and implemented a research framework for hotel managers to identify attributes that will increase customer loyalty. Since 2001, a major shift has taken place: demographically, as Baby Boomers retire and pass on, Millennials will become the dominant generational segment. Design/methodology/approach – The authors use a review of literature to accomplish its purpose. Findings – The authors argue that the loyalty models developed for Boomers will not be a good fit for Millennials. Three propositions are presented in the paper to help researchers develop models that will explain the customer loyalty of Millennials. Research limitations/implications – Implications are presented for researchers wishing to investigate the antecedents and consequences of loyalty for Millennials. Practical implications – The transition from Boomers to Millennials creates a number of opportunities and challenges for managers, which are discussed in the paper. Originality/value – There has been a dearth of empirical research on customer loyalty models developed for Millennials. This paper is a commentary on past models developed for Boomers and the transition needed to develop models for Millennials. It is hoped this dialogue will spawn research that develops loyalty models for Millennials.

Demand fluctuation accounts for an important consideration in a restaurant's daily operational decisions. Good short-term planning and management require accurate forecasts of daily demand. The objective of this study is three-fold: (1) to apply, evaluate, and compare different methods of forecasting customer counts for an on-premises buffet restaurant of a local casino in Las Vegas, (2) to describe and propose a combined forecasting approach for this casino buffet restaurant, and (3) to explore the concept of revenue and capacity management for this buffet restaurant. Eight forecasting models were tested and evaluated by two common error measures. The results suggest that a double moving average model was the most accurate model with the smallest MAPE and RMSPE. Extensive discussions on forecasting and planning/management in buffet operations are provided along with recommended future research.

PurposeThe study aims to analyze guest comments on the Uber Eats food delivery app (FDA) in the USA during the April–June 2020 COVID-19 pandemic lockdown period. Three aspects influencing customer satisfaction with the FDA were evaluated in this study: (1) performance on the app, (2) product quality and (3) service quality.Design/methodology/approachOne thousand customer comments posted on the Uber Eats Google Play app from April 1 to June 30, 2020 were analyzed in this study. The text mining technique was applied to discover the hidden, but meaningful patterns from the unstructured text. Content analysis was applied to systematically analyze the text into organized categories and themes.FindingsAmong the three dimensions evaluated in this study, the most important dimension regarding customers' perceptions toward the FDA was the service quality dimension (40.02%), followed by the FDA's performance dimension (39.43%) and the product quality dimension (20.54%) was least important. Additionally, customers' perceptions towards the three dimensions were all unfavorable and there were more negative comments than the positive comments: FDAs (P/N = 0.728), product quality (P/N = 0.60) and service quality (P/N = 0.865).Originality/valuePrevious studies investigating FDAs assessed solely the performance of the app. However, customers' experience of a food delivery service is comprised of multiple components including the app, the restaurant and the delivery driver. To fill the void, this study evaluated a third-party app performance, product quality and service quality to capture the totality of customers' food delivery service experience.