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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.

The focus of this study is on analyzing influencing factors of antisocial travel-related behaviors – in particular road rage. Building on the concept of redirection, the current chapter develops a theory of natural and planned redirection to derive starting points for demarketing antisocial behaviors. A fuzzy set qualitative comparative analysis (fsQCA) with survey data from 6,811 consumers from the DDB Life Style Study is used to gain insights into the individuals behind road rage. Results show that specific kinds of anti- and prosocial behavior associate with high and low levels of road rage, respectively. The study finds that these prosocial behaviors may function as natural redirection mechanisms and prevent or reduce road rage. Thereby, the findings extend previous analyses of road rage and allow for deriving theoretical and policy implications.

This chapter describes the complementary benefits of model-building and data analysis using algorithm and statistical modeling methods in the context of unobtrusive marketing field experiments and in transforming findings into isomorphic-management models. Relevant for marketing performance measurement, case-based configural analysis is a relatively new paradigm in crafting and testing theory. Statistical testing of hypotheses to learn net effects of individual terms in MRA equations is the current dominant logic. Isomorphic modeling might best communicate what executives should decide using the findings from algorithm and statistical models. Data testing these propositions here uses data from an unobtrusive field experiment in a retailing context and includes two levels of expertise, four price points, and presence versus absence of a friend (“pal” condition) during the customer-salesperson interactions (n = 240 store customers). The analyses support the conclusion that all three approaches to modeling provide useful complementary information substantially above the use of one or the other alone and that transforming findings from such models into isomorphic-management models is possible.

This chapter explores the integrative effects of individual psychology and social context in explaining why managers would behave in socially responsible ways. To identify how factors at different levels of analysis combine to shape attitudes toward social responsibility, I apply fuzzy-set qualitative comparative analysis (fsQCA) to survey and archival data from 335 managers of overseas subsidiaries of three Dutch corporations. Attention to the simultaneous effects of individual psychological factors, the organizational context, and the broader social context offers a configurational perspective on the micro and macrofoundations of social responsibility.

This chapter proposes moving beyond relying on the dominant logic of multiple regression analysis (MRA) toward thinking and using algorithms in advancing and testing theory in accounting, consumer research, finance, management, and marketing. The chapter includes an example of testing an MRA model for fit and predictive validity. The same data used for the MRA is used to conduct a fuzzy-set qualitative comparative analysis (fsQCA). The chapter reviews a number of insights by prominent scholars including Gerd Gigerenzer’s treatise that “Scientists’ tools are not neutral.” Tools impact thinking and theory crafting as well theory testing. The discussion may be helpful for early career scholars unfamiliar with David C. McClelland’s brilliance in data analysis and in introducing business research scholars to fsQCA as an alternative tool for theory development and data analysis.

Purpose – To theorize and research the conditions under which a high-profile social movement organization (SMO) receives newspaper coverage advantageous to it.

Design/methodology approach – To explain coverage quality, including “standing” – being quoted – and “demands” – prescribing lines of action – we advance a story-centered perspective. This combines ideas about the type of article in which SMOs are embedded and political mediation ideas. We model the joint influence of article type, political contexts and “assertive” SMO action on coverage. We analyze the Townsend Plan's coverage across five major national newspapers, focusing on front-page coverage from 1934 through 1952, using fuzzy-set qualitative comparative analyses (fsQCA).

Findings – We find that only about a third of the Townsend Plan's front-page coverage was initiated by its activity and very little of it was disruptive. The fsQCA results provide support for our arguments on coverage quality. Disruptive, non-institutional action had no specific influence on standing, but its absence was a necessary condition for the SMO expressing a demand; by contrast, assertive action in combination with movement-initiated coverage or a favorable political context prompted the publication of articles with both standing and demands.

Research limitations/implications – The results suggest greater attention to a wider array of SMO coverage and to the interaction between article type, SMO action, and political context in explaining the quality of coverage. However, the results are likely to apply best to high-profile SMOs.

Originality/value – The paper provides a new theory of the quality of newspaper coverage and finds support for it with fsQCA modeling on newly collected data.

This chapter shows how configurational approaches can be a valuable inquiring system for examining and understanding complex messy phenomena in the area of digital business strategy in turbulent environments such as digital ecodynamics. Digital ecodynamics is defined as the holistic confluence among environmental turbulence, dynamic capabilities, and IT systems – and their fused dynamic interactions unfolding as an ecosystem. With fuzzy-set qualitative comparative analysis (fsQCA) we analyze firm-level field survey data and describe how IT systems, organizational dynamic capability and environmental turbulence simultaneously combine to result in multiple configurations, which have different causal structures to produce competitive firm performance. This equifinality shows how configurational approaches can create new practical insights in digital ecodynamics by suggesting multiple strategic options from which organizations can choose the best solution that fits their context.

This chapter describes and tests the principles of configural theory in the context of hospitality frontline service employees’ happiness-at-work and managers’ assessments of these employees’ quality of work performances. The study proposes and tests empirically a configural asymmetric theory of the antecedents to hospitality employee happiness-at-work and managers’ assessments of employees’ quality of work performance. The findings confirm and go beyond prior statistical findings of small-to-medium effect sizes of happiness-performance relationships. The method includes matching cases of data from surveys of employees (n = 247) and surveys completed by their managers (n = 43) and uses qualitative comparative analysis via the software program fsQCA.com. The findings support the four principles of configural analysis and theory construction: recognize equifinality of different solutions for the same outcome; test for asymmetric solutions; test for causal asymmetric outcomes for very high versus very low happiness and work performance; and embrace complexity. The theory and findings confirm that configural theory and research resolves perplexing happiness–performance conundrums. The study provides algorithms involving employees’ demographic characteristics and their assessments of work facet-specifics which are useful for explaining very high happiness-at-work and high quality-of-work performance (as assessed by managers) – as well as algorithms explaining very low happiness and very low quality-of-work performance.

The identification of country-specific advantages for business activities is one of the most crucial issues of strategic management and international business literatures. We address this issue by examining location-specific conditions for a successful generic medicines industry within 24 European countries. The findings of our fuzzy-set qualitative comparative analysis show that there are no necessary conditions for the high performance or absence of the high-performance industry. By revealing the causal complexity related to the issue, however, we show that the high performance or lack of it results from a configuration of conditions. Specifically, we identify two sufficient causal configurations to both outcomes. These findings provide clear implications for generic medicines industry firms who are planning location choices of their operations. In addition, this study provides a methodological advancement to explain and understand which country elements matter more, for what outcomes, and under what conditions.