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This paper aims to serve as an important guide for more rigorous quantitative research in tourism and hospitality.

This paper relies on comments from several methodological experts in the field, as well as the authors’ main observation of the literature.

This paper identifies ten important areas of concern. In each of these areas, the authors provide recommendations for best practices.

There are certainly other issues and concerns that are not covered in this paper. However, the issues addressed can be applied or generalized to most methodological contexts.

This paper does not present results from original research but provides interesting and comprehensive recommendations for more rigorous quantitative research.

This paper aims to present several Bayesian specification tests for both in- and out-of-sample situations.

The authors focus on the Bayesian equivalents of the frequentist approach for testing heteroskedasticity, autocorrelation and functional form specification. For out-of-sample diagnostics, the authors consider several tests to evaluate the predictive ability of the model.

The authors demonstrate the performance of these tests using an application on the relationship between price and occupancy rate from the hotel industry. For purposes of comparison, the authors also provide evidence from traditional frequentist tests.

There certainly exist other issues and diagnostic tests that are not covered in this paper. The issues that are addressed, however, are critically important and can be applied to most modeling situations.

With the increased use of the Bayesian approach in various modeling contexts, this paper serves as an important guide for diagnostic testing in Bayesian analysis. Diagnostic analysis is essential and should always accompany the estimation of regression models.

This paper introduces more advanced panel data specifications that would exploit heterogeneity and allow for arbitrary forms of autocorrelation and heteroskedasticity in the error terms.

In line with Assaf and Tsionas (2019a, 2019b), this paper builds on the Mundlak device to propose panel data models to allow for random slope coefficients, as well as time slope coefficients. This paper allows for arbitrary heteroskedasticity and autocorrelation, thus mitigating possible model misspecification. This paper develops and estimates the model in a Bayesian framework. This paper’s methods can be generalized to many nonlinear models including limited dependent variable models.

This paper compares several competing models such as a classical panel data model, which has only firm effects. This paper also examines the role of standard deviations in the formation of firm effects and time effects in the Mundlak device. This paper clearly shows that our framework introduces the best flexibility and model fit.

This paper illustrates the importance of using more flexible models (i.e. unit-specific and time-varying coefficients) for future estimation of panel data in the field.

This paper discusses techniques that will improve panel data estimation in the hospitality and tourism literature.

The purpose of this note is to describe the concept of regression trees (RTs) for hospitality data analysis.

RT is an effective non-parametric predicting modelling approach that would free researchers from the need to force a certain functional form. The method does not require normalization or scaling of data.

The authors illustrate how RTs can be used to find a model that would result in the best prediction.

A common challenge facing hospitality researchers is to estimate a regression model with the correct specification. RTs can help researchers identify the best explanatory model for prediction.

This paper describes the concept of RTs for the modelling of hospitality data.

This paper aims to focus on addressing endogeneity using instrument-free methods. The authors discuss some extensions to well-known techniques.

This paper discusses some attractive methods to address endogeneity without the need for instruments. The methods are labeled are “harmless” in the sense that instruments are not needed and the distributional assumptions are kept to a minimum or they are replaced by more flexible semi-parametric assumptions.

Using a hospitality application, the authors provide evidence about the effectiveness of these techniques and provide directions for their implementation.

Finding valid instruments has always been a key challenge for researchers in the field. This paper discusses and introduces methods that free researchers from the need to find instruments.

The paper discusses techniques that are introduced from the first time in the tourism literature.

This paper aims to identify drivers of efficiency and their influence on airline performances in South Africa. Unfortunately, the methods currently used to measure airline efficiency fail to address the heterogeneity problem, which blurs inefficiency.

To remedy the heterogeneity problem, this paper adopts the meta-frontier framework to identify drivers of efficiency. The interesting feature of the model is that it ensures that heterogeneous airlines are compared based on one homogeneous technology. The model is tested using a panel data sample of nine South African airlines, which operated from 2015 to 2018.

The paper demonstrates that structural drivers, namely, “aircraft size”, and “airline ownership” and one executional driver, namely, “the cost structure” significantly influence (p < 0.05) airline efficiency thereby corroborating evidence from some prior studies.

First, because of the small size of the industry, fewer airlines and a lack of detailed data, the study could not consider other important factors such as optimal routing and network structure. Second, a more rigorous analysis over a period of time would yield better understanding about the growth of the industry in South Africa and recognise the variation in the influence of drivers of efficiency on airline performances over time.

The results have potential policy implications. First, as the market in South Africa is too small to operate with a smaller aircraft probably, for airlines that operate with smaller aircraft to operate efficiently they should first identify niche markets where they can have a route monopoly. Second, while all state-owned airlines are perfect statehood symbols that define and represent countries, most state carriers in South Africa are highly inefficient. The researcher recommends policymakers to privatise state airlines or seek equity partners. Many nationalised airlines have turned losses to profits in the run-up to privatisation. British Airways, once a large burden on the British taxpayer, is now one of the world’s most efficient airlines. After the privatisation of Air France and Iberia, all two turned from loss-making concerns into profitable airlines. It, therefore, makes no sense for the South African government to expect state carriers to pursue a commercial mandate with such political interference. The very notion of efficiency itself is at risk.

This paper is a first attempt to identify drivers of operational efficiency using a bootstrapped meta-frontier approach in the airline industry in South Africa. By applying the meta-frontier approach the paper ensures that all heterogeneous airlines are assessed based on their distance from a common and identical frontier.

The purpose of this paper, a critical reflection, is twofold. First, by comprehensively reviewing scale development procedures in hospitality research, a concerning lack of nomological validity testing is demonstrated. Second, the need for nomological validity testing is discussed and both conceptually and empirically reasoned.

This research systematically reviews scale development studies in three leading hospitality journals, including Cornell Hospitality Quarterly, International Journal of Contemporary Hospitality Management and International Journal of Hospitality Management over ten years (2012–2021) to analyze the completeness of scale development procedures. Specifically, the authors evaluate whether the reviewed studies engage in testing the nomological and predictive validity of the newly developed measures.

The results indicate a concerning gap in the current practices in hospitality research. Specifically, only 33.3% of the examined studies assess nomological validity. These findings collectively underscore the need for improving the comprehensiveness of scale development processes in hospitality research.

The study offers important implications for hospitality researchers. The paper provides an extensive discussion on the importance and benefits of testing for nomological validity in scale development studies, contributing to the completeness and consistency of scale development procedures in the hospitality discipline.

This research critically assesses prevalent, and widely accepted, scale development procedures in hospitality research. This research empirically demonstrates the neglect of nomological validity issues in scale development practices in hospitality research. Scale development is an essential scientific practice used to create a research instrument in a field of study, improving our understanding of a specific phenomenon and contributing to knowledge creation. Considering the significance of scale development in advancing the field of hospitality research, the validation procedures involved in the scale development processes are of utmost importance and should be thoroughly applied.

This paper aims to foster a new discussion on endogeneity in hospitality and tourism research.

This paper elaborates on some of the common sources of endogeneity and the methods available to address them.

The authors present a variety of methods that can be used to mitigate the endogeneity problem. The authors provide simulation evidence regarding the risk of incorrectly selecting instrumental variables. The authors also provide several important practical recommendations for future research.

There are other issues and methods of correcting for endogeneity, that is not covered in this paper. However, the paper focuses on issues and methods that can be generalized to most contexts.

The paper provides practical recommendations for more rigorous regression estimation.

The purpose of this paper is to measure the efficiency of UK airlines in light of all the recent industry challenges.

The study measured the technical efficiency of airlines through the innovative data envelopment analysis (DEA) bootstrap methodology.

Results based on a sample of recent input/output data indicated that the efficiency of UK airlines has continuously declined since 2004 to reach a value of 73.39 per cent in 2007. Factors which were found to be significantly and positively related to technical efficiency variations include airline size and load factor. The paper also highlights that factors such as increase in oil price and fierce market competition were also potential inefficiency determinants.

The findings of this paper provide a fresh link between airline performance and the current industry characteristics. UK airlines also have a major role in the European and international aviation sector, and thus a reflection on their efficiency could be of interest to private and public policy makers.

The paper focuses on a recent period and thus provide a fresh efficiency assessment of the airline industry. The study also extends the limited literature available on UK airlines.

Because of its omission of social influences, conventional animosity research has failed to sufficiently consider consumption context. To address this limitation, this research constitutes two interrelated parts: (a) investigating how normative influences (value-expressive and utilitarian influences) shape consumers’ animosity attitudes and purchase intentions; and (b) building on the normative influence perspective and separating consumption context into purchase (online vs. offline) and usage (private vs. public) contexts. The goal was to examine under the condition of preference conflict, how consumption contexts with different degrees of behavioral exposure affect purchase decisions.

One pretest, one survey and one experiment were conducted to empirically validate the proposed research model.

In an international crisis, consumers’ attitudes and behaviors were socially determined. Moreover, the online purchase with private usage (offline purchase with public usage) condition resulted in the highest (lowest) level of purchase intention.

This research pioneers in the animosity literature to identify the possibility of preference conflict in a situational international crisis, and to more delicately separate the conventional consumption context into purchase and usage contexts.