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The aim of this chapter is to review and illustrate a step-by-step guideline in conducting fuzzy-set Qualitative Comparative Analysis (fsQCA) in tourism and hospitality studies. As an emerging method, fsQCA is simultaneously quantitative and qualitative in nature which makes it an appropriate method for social science disciplines including tourism and hospitality area because of complex nature of relationships between multiple variables where theories and models are underdeveloped. Unlike conventional statistical techniques, fsQCA is an asymmetrical analysis technique that provides a holistic view and interrelationships among several conditions using Boolean algebra. The fsQCA analyses produce comprehensive assessment by revealing causal combinations of antecedents to predict an outcome; and identify sufficient configurations (i.e., causal combinations and recipes) and necessary condition/s. By utilizing this method, researchers would be able to produce complex, comprehensive, and robust results.

This study aims to propose guidelines for the joint use of partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to combine symmetric and asymmetric perspectives in model evaluation, in the hospitality and tourism field.

This study discusses PLS-SEM as a symmetric approach and fsQCA as an asymmetric approach to analyze structural and configurational models. It presents guidelines to conduct an fsQCA based on latent construct scores drawn from PLS-SEM, to assess how configurations of exogenous constructs produce a specific outcome in an endogenous construct.

This research highlights the advantages of combining PLS-SEM and fsQCA to analyze the causal effects of antecedents (i.e., exogenous constructs) on outcomes (i.e., endogenous constructs). The construct scores extracted from the PLS-SEM analysis of a nomological network of constructs provide accurate input for performing fsQCA to identify the sufficient configurations required to predict the outcome(s). Complementing the assessment of the model’s explanatory and predictive power, the fsQCA generates more fine-grained insights into variable relationships, thereby offering the means to reach better managerial conclusions.

The application of PLS-SEM and fsQCA as separate prediction-oriented methods has increased notably in recent years. However, in the absence of clear guidelines, studies applied the methods inconsistently, giving researchers little direction on how to best apply PLS-SEM and fsQCA in tandem. To address this concern, this study provides guidelines for the joint use of PLS-SEM and fsQCA.

Fuzzy-set qualitative comparative analysis (fsQCA) is explored as a transformative tool rooted in complexity theory, shedding light on uncertainties shaping real-world decisions in tourism, with a focus on its application in the hospitality domain.

This study systematically evaluates fsQCA’s application in hospitality and tourism research, employing bibliometric analysis to scrutinize the published literature since its induction in 2011. The research seeks to understand the evolving usage by qualitatively reviewing impactful studies based on total citations.

The study reveals the ascendancy of fsQCA as a predominant approach in hospitality and tourism studies, particularly in illuminating decision-making paradigms in key sectors like destination and hotel selections and entrepreneurial orientations. However, an absence of fsQCA applications in gastronomy and wine tourism is identified, signaling uncharted territories for future inquiry.

Theoretical implications include paradigm shifts to complexity theory, configural analysis and asymmetric algorithms. Practical implications involve improved decision-making and tailored marketing, benefiting industry practitioners. Limitations include potential academic bias, while future research suggests exploring sub-sectors, sustainability and emerging technologies.

This study identifies gaps in the fsQCA application and pioneers its examination within the hospitality domain, offering a unique perspective on understanding intricate relationships and configurations among variables. The study emphasizes the efficacy of asymmetric methodologies in elucidating behavioral nuances in hospitality and tourism, providing a foundation for future inquiries to expand horizons and unravel the nuanced applications of fsQCA in this research domain.

Research in entrepreneurship is increasingly exploring how archetypes, taxonomies, typologies, and configurations can help scholars understand complex entrepreneurial phenomena. We illustrate the potential for set-theoretic methods to inform this literature by offering best practices regarding how qualitative comparative analysis (QCA) can be used to explore research questions of interest to entrepreneurship scholars. Specifically, we introduce QCA, document how this approach has been used in management research, and provide step-by-step guidance to empower scholars to use this family of methods. We put a particular emphasis on the analytical procedures and offer solutions to dealing with potential pitfalls when using QCA-based methods and highlight opportunities for future entrepreneurship research.

The purpose of this paper is to explore the configuration of factors affecting the accuracy of triage decision-making. The contribution of the work is twofold: first, it develops a protocol for applying a fuzzy-set qualitative comparative analysis (fsQCA) in the context of triage decision-making, and second, it studies, through two pilot cases, the interplay between individual and organizational factors in determining the emergence of errors in different decisional situations.

The methodology adopted in this paper is the qualitative comparative analysis (QCA). The fuzzy-set variant of QCA (fsQCA) is implemented. The data set has been collected during field research carried out in the Emergency Departments (EDs) of two Italian public hospitals.

The results of this study show that the interplay between individual and contextual/organizational factors determines the emergence of errors in triage assessment. Furthermore, there are some regularities in the patterns discovered in each of the investigated organizational contexts. These findings suggest that we should avoid isolating individual factors from the context in which nurses make their decisions.

Previous research on triage has mainly explored the impact of homogeneous groups of factors on the accuracy of the triage process, without considering the complexity of the phenomenon under investigation. This study outlines the need to consider the not-linear relationships among different factors in the study of triage’s decision-making. The definition and implementation of a protocol to apply fsQCA to the triage process in EDs further contributes to the originality of the research.

The purpose of this paper is to build on recent efforts occurring within business-to-business (B2B) marketing research to advance methodological developments. As phenomena within B2B relationships have become increasingly complex, marketing scholars have begun to point out the limitations associated with correlation-based methodological approaches and highlight the need for new developments in this area. One such development is the fuzzy set qualitative comparative analysis (fsQCA).

This study uses a literature review to examine the use of fsQCA in B2B marketing research.

First, the current manuscript presents the benefits that the application of fsQCA can offer to market researchers investigating B2B phenomena. Second, the paper presents the current state of fsQCA use within B2B marketing. Third, it suggests possible marketing B2B research topics that can be explored using fsQCA.

The study highlights the benefits of fsQCA, presents the current state of fsQCA use within B2B marketing and offers a rich future research agenda for B2B marketing scholars. This agenda can also help spur additional method developments in the discipline.

The aim of this chapter is to introduce a methodology that enables researchers to employ a set of systematic comparative tools and techniques in their multiple case study research that allow them to move from drawing loose comparisons towards a more formalised type of analysis, while simultaneously paying attention to within-case complexities. This methodology stands between the qualitative and the quantitative methods and helps researchers to build middle-range theories (Mjoset, 2001) from small to intermediate numbers of cases. This methodology encompasses a number of techniques including crisp and fuzzy set-theoretic qualitative comparative analyses, which have been used in a wide range of social science disciplines. However, these techniques have not received sufficient attention from higher education scholars.

The purpose of this paper is to revisit the conceptualization and measurement of entrepreneurial intentions. Significant studies anchored in the Theory of Planned Behavior use causal statistical approaches to entrepreneurial intentions. This methodological approach, leads to the conclusion that there is a single pathway for all groups of people to achieve business start-up. Even though theory suggests approaches by women entrepreneurs to start a business may be influenced by different factors from those influencing men, results are inconclusive in these analyses. The authors argue that methodological preferences for linear, causal analytical approaches limit the understanding of gender similarities and differences in the business start-up process. The authors propose that when considering diverse samples, it is unreasonable to assume there is only a single pathway leading to business start-up.

Building on fuzzy-set Qualitative Comparative Analysis (fsQCA) and data set of 2,038 respondents, the authors investigate factors predicting the intentions to start a business and evaluate the alternative conjunctive paths that emerge.

The fsQCA results shows that the relationship among conditions leading to entrepreneurial intentions is complex and is best represented as multiple and conjectural causation configurations. In other words, there are multiple significant pathways (refers to equifinality) that predict intentions to start a business start-up, and there are significant differences by gender.

This study is one of the first to examine the roll of gender as a sperate condition in the analysis. This paper offers implications for theory and future research and highlights the complexity of this domain.

Given the complexity of building information modeling (BIM) adoption decisions in small- and medium-sized enterprises (SMEs) in the Architecture, Engineering and Construction (AEC) industry, understanding BIM adoption decision-making through the net effect of a single factor on BIM adoption decisions alone is limited. Therefore, this paper analyzed the co-movement effect of managers' psychological factors on the BIM adoption decisions from the perspective of managers' perceptions. The purpose is to let managers have a deep understanding of their BIM adoption decisions, and put forward targeted suggestions for the AEC industry to promote the adoption of BIM by SMEs.

Data from 192 managers in SMEs collected by the questionnaire were used in a fuzzy set qualitative comparative analysis (fsQCA). Due to the limitations of fsQCA in making the best use of the data used, as a complement to fsQCA, necessary conditions analysis (NCA) was used to analyze the extent to which necessary conditions influenced the outcome.

(1) NCA analysis shows that high perceived resource availability (PRA) and high performance expectancy (PE) are necessary conditions for high BIM adoption intention (AI). (2) fsQCA analysis shows that high PE is the single core condition for high AI. fsQCA analysis identifies three configurations of managers' psychological factors, reflecting three types of managers' decision preferences, namely benefit preference, loss aversion and risk avoidance, respectively. Different decision preferences may lead to different BIM adoption strategies, such as full in-house use, partial in-house/outsourcing and full outsourcing of BIM processes. (3) High perceived risk (PR) and low perceived business value of BIM (PBV) are the core conditions for low AI.

This paper expands on the application of fsQCA to context of BIM adoption decisions. Based on the results of fsQCA analysis, this paper also establishes the relationship between managers' decision-making psychology and BIM adoption strategy choice and analyzes the impact of different decision biases on BIM adoption strategy choice. It concludes with suggestions for encouraging managers to adopt BIM and for avoiding decision-making bias.

Organizations nowadays require services supplied by shared service centers (SSCs) to achieve organizational responsiveness. Previous contributions focused on distinct qualitative-explorative factors for explaining successful SSC implementation but failed to consider the interdependencies and combined effects between factors.

Drawing on complexity and configuration theories, this research employed a fuzzy-set qualitative comparative analysis (fsQCA). A unique dataset of 121 international firms was obtained to examine the combined effects of five conditions (factors), namely, modularization, standardization, decision-rights, portfolio and customer-orientation .

The findings show that multiple configurations of conditions (or solutions) can lead to successful SSC implementation. The fsQCA results indicated that portfolio and standardization are perceived as core conditions in all configurations. Firms that focus on portfolio and continuous evaluation of customer-orientation are more likely to be successful. Furthermore, in some configurations, the size of the firm size matters.

The cross-sectional survey data might be a potential limitation. In future research, a more extensive survey can be collected to help generalize the results.

Success factors are dependent on the SSC configuration. Standardization, portfolio management and regular evaluations of changing customer services by executive management are needed.

To the best of the authors' knowledge, there is no academic study that examines SSC implementation based on salient conditions using a configurational thinking approach. As such, the findings of the research allow us to better understand the causal complexity and interdependencies between essential SSC factors.