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This paper aims to examine mixed methods research (MMR) that appeared in eight tourism and hospitality journals (“Annals of Tourism Research”, “Tourism Management”, “Journal of Travel Research”, “Journal of Sustainable Tourism”, “International Journal of Contemporary Hospitality Management”, “International Journal of Hospitality Management”, “Journal of Hospitality Marketing and Management” and “Journal of Hospitality and Tourism Research”) from 1998 to 2019.

This review paper was a mixed methods design and was conducted in three phases. In the first phase, a content analysis was performed to determine if each article could be classified as non-empirical, qualitative, quantitative or mixed methods. In the second phase, descriptive statistics was used to present the number and characteristics of MMR articles. In the third phase, the contributions of MMR to addressing particular issues in tourism and hospitality studies were investigated.

This study identified 753 mixed methods articles, wherein 482 articles (64%) were published in the chosen tourism publication outlets and 271 (36%) in the chosen hospitality publication outlets. MMR studies having a dominant focus on specific methods (459 articles; 61%) outnumbered those having an equal focus on the qualitative and quantitative parts (294 articles; 39%). In case one method was dominant, this was typically the quantitative. Sequential data collection was prevalent in most of the cases (94.2%). The contributions of MMR to addressing generic and specific research problems were also analyzed.

This is the first comparison of MMR in major tourism and hospitality journals.

Presents survey data used to determine how university librarians in Nigeria utilize quantitative methods in decision making in diverse areas such as personnel management, acquisition, storage and circulation of information materials. A stratified random sampling method was used to select 22 out of 35 university librarians. The survey results indicate that four (18.19 per cent) respondents have good knowledge of quantitative methods, i.e. its use and application in decision making; whereas as high as 18 (81.8 per cent) are hardly aware of, and have not used these statistical tools in decision making in university libraries. The research study uncovers factors that hinder the utilization of quantitative methods such as lack of understanding of the subject; a traditionally held view of librarianship as not requiring such statistical analysis; inadequate time for its teaching and acquiescence; dislike for intellectualism in resolving library problems; and disproportionate views of top practitioners on the concept of decision making. Submits that it would augur well for library practice at a high level if university libraries could use and apply quantitative methods in their work situations. This could ideally be learned and perfected through special courses. workshops, management seminars or formal academic programmes. Adequate exposure of respondents through continuing education would enhance proper utilization of quantitative methods in decision making in university libraries thereby guaranteeing efficiency, effectiveness and quality library services to library clientele, as well as enhancing the librarian’s own standing and image among academic peers.

Students in the marketing discipline have been reported to struggle with quantitative methods. This paper aims to focus on whether it is possible to increase student confidence and reduce anxiety with quantitative data analysis even when limited teaching resources are available. It reports on two half-day initiatives to teach quantitative methods that followed the principles of integration of method into a substantive course (as opposed to stand-alone course) and hands-on approach (as opposed to using a theoretical and hands-off approach).

Over the course of three semesters, 92 students that took part of the sessions answered a survey where they reported their basic understanding, confidence, practical abilities and anxiety with quantitative methods.

The results indicate significant improvements in self-reported basic understanding, confidence, practical abilities and anxiety. Further analysis indicated that neither gender nor previous statistical background had an impact on perceived benefit with the initiative.

In all, the study indicates that integration and hands-on approaches may be beneficial to reduce anxiety and increase confidence with quantitative data analysis, even when this initiative is limited in time and resources.

The study presents an approach to reducing anxiety and increasing confidence with quantitative data analysis. Teaching initiatives like this may be beneficial in situations when students experience high levels of statistics anxiety.

The purpose of this paper is to shed light on the threats to quality in mixed methods accounting research, wherein quantitative and qualitative approaches are combined in data collection, analysis and interpretation.

The paper is framed according to three perspectives. The authors first synthesize the threats to validity and reliability in quantitative and qualitative parts of mixed methods research using the quality standards of each; they then introduce an integrative framework of mixed methods research quality by Teddlie and Tashakkori. Thereafter, they address the specific threats to quality that come to the fore when inferences from the quantitative and qualitative components of the study are combined to form meta‐inferences using a legitimation framework by Onwuegbuzie and Johnson.

The authors' analysis not only indicates a wide range of threats to the validity and reliability of mixed methods research in a range of categories, but also clarifies how the three perspectives described in this paper are linked and supplement each other.

Methodological research published in English over the last decade is emphasized to create an approach to assess mixed methods accounting research. The frameworks analyzed could still be studied in greater detail. Additional perspectives on the validity and reliability of mixed methods research could also be studied and developed.

This paper furthers our understanding of such new developments in methodological research, which may be of great importance to those conducting or evaluating empirical research.

Based on a comprehensive synthesis, this paper presents and analyzes theoretical frameworks potentially useful for scholars, students and practitioners. It focuses on both traditional and novel areas of validity and reliability in mixed methods research.

Taking stock of extant hospitality and tourism research using social network analysis approaches, this study highlights why using either quantitative or qualitative approaches to examine social networks can be misleading and generate potentially biased findings. Indeed, purely qualitative and purely quantitative studies display limitations. The purpose of this study is to provide methodological insights by suggesting that mixed methods can be suitably used, depending on the specific research questions.

The study consists of an analysis and critical discussion of the methods used in a number of papers leveraging social network approaches to study social networks in tourism and hospitality. The authors describe the benefits and limitations of each method studies considered are examined based on a number of aspects.

More than half of the studies classified as network studies adopt quantitative designs and quantitative methods including statistical analyses and observational data. Mixed methods study is a minority and they are almost never labeled as mixed methods. A relevant portion of qualitative studies increasingly embeds a number of rudimentary statistical analyses. With an example, the authors also discuss that purely quantitative or purely qualitative methods can lead to discrepant results, and thus, the authors encourage scholars to embrace mixed method research designs such as explanatory or exploratory sequential designs. Advanced researchers might attempt in the future to embrace transformative, embedded or multiphase mixed methods.

This study is based on academic papers and research published before 2019. A rich research agenda is designed.

This study contributes to explore the way social networks have been dealt with in tourism and hospitality research so far, by advancing a proposal to adopt mixed methods in the form of explanatory or exploratory sequential designs. To the best of the knowledge, it is the first study addressing methodological pitfalls in extant network-based research within the tourism and hospitality domain.

This study demonstrates integration within a mixed-methods case study of construction phenomena, whilst ensuring reliability and validity. This is in view of the established philosophical challenges in theory generation, whereby qualitative and quantitative methods are underpinned by divergent, almost incompatible, paradigmic assumptions.

The study uses a sample case study research on the phenomenon of cost overruns, supported by a coherent flow of well-articulated philosophical arguments to idealise the logic of integration. Issues of reliability and validity were resolved along these lines, by incorporating applicable criteria from both the qualitative and qualitative strands. A detailed outline and rationalisation of the stepwise approach to achieving integration are provided, from the point of design conceptualisation, data collection, analysis and further down to theory generation.

The study generated two level-1 theories by collecting numerical data on cost overruns, geotechnical index parameters and textual data on the geotechnical practices. Another level-1 theory was generated in reflexive adaptation to unanticipated social constructs emerging from the qualitative data. All level-1 theories from the quantitative and qualitative strands were triangulated to yield two “level-2 theories”: A log-regression model and a cognitive map. The approach to integration is thus explanatory sequential, and concurrent (at the second stage of transformation in the generation of level-2 theories).

The study empirically reinforces that ontological flexibility, achievable through the use of thoughtfully designed integrated mixed-methods case studies, permits the investigation of multidimensional construction phenomena in innovative ways, relevant to provide holistic theoretical and practice-based contributions.

The study practically signposts a bespoke stepwise approach to integration, in a mixed-methods case study of construction phenomena, against the contextual backdrop of its relative novelty and lack of studies delving in-depth into the theoretical nitty-gritty.

After the initial life (which coincides with the origins of social research in the 1850s, and lasts until 1940s), mixed methods revive at the beginning of 1970s. However, this second life (or renaissance) receives the deleterious imprinting of quantitative methods. In fact, some of the old positivist assumptions are still reproduced and active in most of mixed methods research. This imprinting is traceable in the ambiguity (and purposive semantic stretching) of the term “qualitative”: from the 1990s, it encompasses almost everything (even approaches considered positivistic in the 1950s!). Whereby the semantical extension of the term “qualitative” has become a sort of Trojan horse for a new legitimation of many quantitative and positivist researchers: a great swindle. Today “qualitative” is nonsense and acts as a bug, which muddies the qualitative-quantitative debate. For this reason, it would be better to remove the bug (i.e. to discharge the term “qualitative” from the language of social research and methodology), reset and start over from the level of specific research methods, considering carefully and balancing their diversity before mixing them. The purpose of this paper is to outline two (complementary) ways of integration of methods (“mixed” and “merged”), arguing that “merged” methods realize a higher integration than “mixed” methods, because the former overcome some weaknesses of the latter.

A semantic and pragmatic analysis of the term “qualitative.”

In social and behavioral sciences, the second life of mixed methods has been heavily affected by old positivist and quantitative assumptions.

The term “qualitative” should be discharged from the language of social research and methodology.

The coveted integration in “mixed” methods, could be better pursed through “merged” methods.

Disentangling the strands of a debate (the qualitative-quantitative one) become muddy.

An alternative framework, to interpret the mixed methods history and their recent developments, has been proposed.

The purpose of this study is to examine the prevalence of mixed methods research across several business and management fields and to gauge the level of acceptance of mixed methods within these fields.

The methodology employed for this study involved synthesizing the findings from six large‐scale methodological scans of business and management discipline journals in seven fields: marketing, international business, strategic management, organizational behaviour, operations management, entrepreneurship and human resource management.

The study finds that quantitative studies dominate all seven fields (76 per cent of empirical articles) followed by mixed methods (14 per cent of empirical articles) and qualitative studies (10 per cent of empirical articles). In applying the framework for acceptance levels, it would seem there exists minimal acceptance of mixed methods across these fields.

The study has limitations related to the coverage of different disciplines and differences in sample sets. More extensive research is planned for the future and will involve an expanded mixed method prevalence rate study across additional business and management fields.

The growing use of mixed methods has practical implications for research training and capacity building within business schools. The study points to the need to develop research capacity through the introduction of postgraduate courses in mixed methods and advanced research skills training for existing researchers.

Mixed methods is a relatively new and emerging methodological movement. This paper attempts to gauge the use and level of acceptance of mixed methods across a diverse range of business and management discipline areas.

The purpose of this paper is to further the discussion on points made by Giampietro Gobo, provide additional information on the place of qualitative research in management, and question the space of merged methods.

Use a conversational approach as well as a review of qualitative vs quantitative research in three top tier journals for the years 2013-2016 (by a simple count).

Quantitative methods remain very much mainstream in management research, yet one finds that for one of the journals, space is evenly shared between qualitative and quantitative methods.

This is a viewpoint and does not offer a systematic review of all top tier management journals.

It is hope that with this viewpoint debate as to the space of qualitative research, and merged methods can be stimulated.

Accurate forecasting has become a challenge for companies operating in today's business environment, characterized by high uncertainty and short response times. Rapid technological innovations and e‐commerce have created an environment where historical data are often of limited value in predicting the future. In business organizations, the marketing function typically generates sales forecasts based on judgmental methods that rely heavily on subjective assessments and “soft” information, while operations rely more on quantitative data. Forecast generation rarely involves the pooling of information from these two functions. Increasingly, successful forecasting warrants the use of composite methodologies that incorporate a range of information from traditional quantitative computations usually used by operations, to marketing's judgmental assessments of markets. The purpose of this paper is to develop a framework for the integration of marketing's judgmental forecasts with traditional quantitative forecasting methods. Four integration methodologies are presented and evaluated relative to their appropriateness in combining forecasts within an organizational context. Our assessment considers human factors such as ownership, and the location of final forecast generation within the organization. Although each methodology has its strengths and weaknesses, not every methodology is appropriate for every organizational context.