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The purpose of this paper is to appraise methodological rigor in the application of discriminant analysis (DA) in export-focused research and to offer guidelines for future studies.

The sample includes 89 empirical peer-reviewed studies, comprising 102 models published over the period 1979-2014. Content analysis and vote counting are used to evaluate each of these studies.

This review highlights major flaws in the application of DA in export research. The shortcomings are self-evident particularly concerning suitability of DA for research context, completeness in the reporting of descriptive results, and validity and reliability of predictive results.

The study takes the position that the lack of methodological rigor may be undermining the eminence of knowledge in exporting, and this has extensive implications for both researchers and practitioners.

This review outlines steps to assess methodological rigor associated with DA and offers guidelines for scholars seeking to enhance rigor in future research.

This study aims to conduct a systematic review and critically analyze the sentiment analysis literature in hospitality and tourism from methodological (data sets and analyzes) and thematic (topics, theories, key constructs and their relationships) perspectives.

Qualitative thematic review and quantitative systematic review were performed on 70 papers obtained from hospitality and tourism categories of two databases, namely, Web of Science and Scopus.

A total of 5 topics and 27 sub-topics were identified and the major theme is market intelligence. Sentiment variables were investigated not only as independent but also as dependent variables. The customer rating is the most investigated dependent variable, whereas moderators and mediators were rarely tested. Most reviewed studies did not use theory. The findings from the methodological review show that analysis of big data was rare. Moreover, testing the performance of sentiment analyzes was uncommon, and only one paper tested the performance of aspect/feature extraction.

This study extends prior review studies by providing a comprehensive view of how knowledge and methodologies of sentiment analysis have developed. The identified themes and key constructs serve as a solid base for future knowledge advancement. Future research directions on sentiment analysis are also provided.

To the best of the authors’ knowledge, this study is the first comprehensive methodological and thematic review of sentiment analysis in hospitality and tourism. Based on the identified findings, the authors propose several directions for future research.

Review articles play a special role in the scientific literature by analysing and synthesizing recent work on a given topic. It is assumed that authors of review articles selectively cite relevant literature of the highest quality. These traits have suggested that articles frequently cited in reviews might be important, high quality articles for a subject literature. A method based on citation analysis has been proposed as a quality filtering system for medical literature.

The purpose of this study is to present a systematic methodological review of the application of field experiments in the domain of marketing research. By performing this study, the authors seek to offer necessary advice and suggestions to marketing scholars interested in the application of field experiments and to promote the adoption of field experiments as a preferred methodological choice among scholars in this domain.

A total of 315 field experiments published in the ten leading marketing journals in the past five decades were analyzed in this systematic methodological review. This study examines various aspects of field experiments, including the research profile of existing research, different trends and topics related to field experiments, choice of research questions, methods of observations, unobtrusive data collection, types of interventions and outcome variables.

This study identified various trends and topics, categories of manipulations, types of limitations and important considerations in designing field experiments and offered necessary advice on the future of field experiments in marketing research.

This study provides a complete roadmap for future marketing scholars to adopt field studies in their research plans. The systematic summary of limitations and the checklist will be helpful for the researchers to design and execute field studies more effectively and efficiently.

This review study offers a complete roadmap for marketing scholars who are interested in adopting field experiments in their research projects. The discussion of trends and topics, manipulations, limitations, design considerations and checklist items for field experiments offers relevant insights to marketing scholars and may help them design and execute field experiments more effectively and efficiently.

To the best of the authors’ knowledge, this study is the first of its kind to provide a comprehensive methodological review of field experiments published in leading marketing journals throughout the past five decades. This study makes novel and unique contributions to both theory and literature on field experiments in the marketing discipline.

Purpose – Exploration of the methodological aspects of male sex work is rather limited. Without a strong methodological toolkit to draw from, research in male sex work will not be able to accurately capture changes in the dynamic sex work environment. Thus, the author provides a comprehensive review of methods in male sex work along with a broad spectrum of methodological insights through which future research can be advanced.

Methodology/approach – Drawing from two studies that the author conducted in the male independent escorting space, this chapter provides a range of methodological insights and offers avenues for future research.

Findings – This chapter reviews the methods used in male sex work research over the years and details the lack of research on methodological inquiry in the field.

Originality/value – With the increasing normalization and dynamism of male sex work, it is necessary for the research to provide methodological guidance for the next wave of studies in the field. The recommendations and research directions proposed herein are hoped to have implications for research in the larger sex work context.

This paper aims to identify specific challenges and opportunities when crafting literature reviews of qualitative accounting research. In addition, it offers potential remedies to frequent challenges when conducting such reviews.

This piece is based on recent methodological advice on conducting literature reviews and my own experience when conducting and publishing reviews that primarily cover qualitative accounting research.

The author chart three typical advantages and three typical use cases of literature reviews of qualitative accounting research, as well as the typical process steps and outputs of such reviews. Along with these process steps, The author identifies three overarching specific challenges when conducting such reviews and discusses potential remedies. Overall, this paper suggests that literature reviews of qualitative accounting research feature idiosyncratic challenges but offer specific opportunities at the same time.

To the best of the authors’ knowledge, this paper is among the first to offer advice on the specific challenges and opportunities when conducting literature reviews of qualitative accounting research.

Cross-language qualitative research has gained momentum worldwide; yet, there is still a lack of consensus to guide researchers in ensuring the trustworthiness of the research. Several methodological dilemmas related to language differences between researchers and participants should be carefully addressed. Therefore, this study aims to (1) review qualitative literature addressing cross-language, (2) produce a list of methodological criteria and recommendations from the reviewed literature and (3) evaluate systematically published cross-language qualitative researches using the list.

This study employed a summative content analysis of 35 published curriculum and pedagogy researches from 2000–2018 that viewed language differences as methodological issue. A list of 20 criteria or recommendations was constructed and used to evaluate the selected researches.

The findings revealed that majority of the researches lacked understanding of language differences between researchers and participants causing multiple inconsistencies in reporting methodological issues. Failure to address these methodological issues could risk the trustworthiness of the data and the overall rigor of the research.

This study highlights the importance to minimize methodological issues related to language differences. It is hoped that the list of criteria or recommendations proposed by this study could support other cross-language qualitative researchers in overcoming these methodological dilemmas.

This paper aims to review the existing literature systematically so as to contribute towards a better understanding of methodological problems of the classical statistical techniques, artificially intelligent expert systems and theoretical approaches to solve the corporate failure syndrome.

This paper presented a systematic review of 83 articles reporting 137 prediction failure models published within 1966-2012 in scholarly reviewed journals in four main disciplines, namely, accounting, finance, banking and economics. The authors performed the systematic literature review with five main sources, namely, Science Direct, Google Scholar, Wiley Interscience, Metalib, Web of Science and Business Source Complete of the Social Sciences. The review modified the approaches used by Aziz and Dar (2006), Ravi and Ravi (2007) and Balcaen and Ooghe (2006).

The results indicate significant body of prior literature on prediction of corporate failure, but a theoretically sound, highly accurate, simple and widely used corporate failure prediction model for stakeholders has yet to be developed.

This paper contributes towards a systematic understanding of the methodological problems associated with the statistical, artificially intelligent expert systems and theoretical approaches to solve the corporate failure prediction problems faced by firms in 11 countries.

Many higher education institutions are investigating the possibility of developing predictive student success models that use different sources of data available to identify students that might be at risk of failing a course or program. The purpose of this paper is to review the methodological components related to the predictive models that have been developed or currently implemented in learning analytics applications in higher education.

Literature review was completed in three stages. First, the authors conducted searches and collected related full-text documents using various search terms and keywords. Second, they developed inclusion and exclusion criteria to identify the most relevant citations for the purpose of the current review. Third, they reviewed each document from the final compiled bibliography and focused on identifying information that was needed to answer the research questions

In this review, the authors identify methodological strengths and weaknesses of current predictive learning analytics applications and provide the most up-to-date recommendations on predictive model development, use and evaluation. The review results can inform important future areas of research that could strengthen the development of predictive learning analytics for the purpose of generating valuable feedback to students to help them succeed in higher education.

This review provides an overview of the methodological considerations for researchers and practitioners who are planning to develop or currently in the process of developing predictive student success models in the context of higher education.

This study aims to establish a model for rapid and accurate emotion recognition in restaurant online reviews, thus advancing the literature and providing practical insights into electronic word-of-mouth management for the industry.

This study elaborates a hybrid model that integrates deep learning (DL) and a sentiment lexicon (SL) and compares it to five other models, including SL, random forest (RF), naïve Bayes, support vector machine (SVM) and a DL model, for the task of emotion recognition in restaurant online reviews. These models are trained and tested using 652,348 online reviews from 548 restaurants.

The hybrid approach performs well for valence-based emotion and discrete emotion recognition and is highly applicable for mining online reviews in a restaurant setting. The performances of SL and RF are inferior when it comes to recognizing discrete emotions. The DL method and SVM can perform satisfactorily in the valence-based emotion recognition.

These findings provide methodological and theoretical implications; thus, they advance the current state of knowledge on emotion recognition in restaurant online reviews. The results also provide practical insights into intelligent service quality monitoring and electronic word-of-mouth management for the industry.

This study proposes a superior model for emotion recognition in restaurant online reviews. The methodological framework and steps are elucidated in detail for future research and practical application. This study also details the performances of other commonly used models to support the selection of methods in research and practical applications.