관광지 만족도를 평가하는 관광지 선택속성에 관한 연구

Fuzzy Set Qualitative Comparative Analysis (fsQCA) is a methodology for obtaining linguistic summarizations from data that are associated with cases. It was developed by the social scientist Prof. Charles C. Ragin. fsQCA seeks to establish logical connections between combinations of causal conditions and an outcome, the result being rules that describe how combinations of causal conditions would cause the desired outcome. So, each rule is a possible path from the causal conditions to the outcome. The rules are connected by the word OR to the output. To actually apply fsQCA to some engineering data problems, there are some challenges that had to be overcome. We explain the challenges and how they have been overcome. We also illustrate the application of fsQCA to the well-known Auto MPG dataset to obtain causal combinations that explain Low MPG 4-cylinder cars.

Fuzzy Set Qualitative Comparative Analysis (fsQCA) is a methodology for obtaining linguistic summarizations from data that are associated with cases. It seeks to establish logical connections between combinations of causal conditions and an outcome, the result being rules that summarize the sufficiency between subsets of all of the possible combinations of the causal conditions (or their complements) and the outcome. The rules are connected by the word OR to the output. Each rule is a possible path from the causal conditions to the outcome. FsQCA rules involve words that are modeled using type-1 fuzzy sets (T1 FSs). Unfortunately, once the T1 FS membership functions (MFs) have been chosen, all uncertainty about the words that are used in fsQCA disappears, because T1 MFs are totally precise. Interval type-2 FSs (IT2 FSs), on the other hand, are first-order uncertainty models for words. In this paper, we extend fsQCA to IT2 FSs. More specifically, we develop IT2-fsQCA by extending the steps of fsQCA from T1 FSs to IT2 FSs. In order to illustrate the application of IT2-f5QCA we consider Ragin's Breakdown of Democracy example, which studies the effects of five causal conditions on the Breakdown of Democracy of 18 European countries between World Wars 1 and 2. We show results obtained for IT2-fsQCA and compare them with those obtained from fsQCA.

Fuzzy Set Qualitative Comparative Analysis (fsQCA) is a methodology for obtaining linguistic summarizations from data that are associated with cases. It was developed by the eminent sociologist Prof. Charles C. Ragin, but has, as of this date, not been applied by engineers or computer scientists. Unlike more quantitative methods that are based on correlation, fsQCA seeks to establish logical connections between combinations of causal conditions and an outcome, the result being rules that summarize (describe) the sufficiency between subsets of all of the possible combinations of the causal conditions (or their complements) and the outcome. The rules are connected by the word OR to the output. Each rule is a possible path from the causal conditions to the outcome. This paper, for the first time, explains fsQCA in a very quantitative way, something that is needed if engineers and computer scientists are to use fsQCA.

Fuzzy Set Qualitative Comparative Analysis (fsQCA) is a methodology for obtaining linguistic summarizations from data that are associated with cases. It was developed by the eminent social scientist Prof. Charles C. Ragin, but has, as of this date, not been applied by engineers or computer scientists. Unlike more quantitative methods that are based on correlation, fsQCA seeks to establish logical connections between combinations of causal conditions and an outcome, the result being rules that summarize (describe) the sufficiency between subsets of all of the possible combinations of the causal conditions (or their complements) and the outcome. The rules are connected by the word OR to the output. Each rule is a possible path from the causal conditions to the outcome. This chapter provides a high-level introduction to fsQCA.

Charles Ragin’s Fuzzy Set Qualitative Comparative Analysis (fsQCA) used for linguistic summarizations

The purpose of the study was to find out how the image of the destination and tourist satisfaction and how the influence of the image on tourist satisfaction in tourism destinations in Bengkulu Province. This research is a conclusive research study of 150 tourists to natural tourist destinations that are included in the Bengkulu Province Tourism Strategic Area Plan (TSAP). Tourist perception was developed to test the hypothesis of the relationship model or the effect of the impact of the destination image on tourist satisfaction. The data analysis methods used are descriptive analysis and multiple linear regression analysis. The findings of this study indicate that tourism destinations have an excellent image; this can be seen from the destination image components, including cognitive and affective images, which are in the excellent category. When viewed from tourist satisfaction towards natural tourist destinations, tourists have been satisfied with tourism destinations. Cognitive and affective images also positively affect tourist satisfaction with tourism destinations. The better the cognitive and affective image, the more tourist satisfaction at natural tourism destinations will increase.

The present research analyzes national corporate interlock networks and their causal conditions. The objective is two-fold: 1) to specify types of corporate networks, and 2) to pinpoint the causal configurations that give rise to each type of corporate network. First, corporate networks on basis of interlocking directorates are analyzed and compared using social network analysis to empirically derive a typology. The results show two types of corporate networks: cohesive corporate networks which are based on unification, centralization and strength ties; and dispersed corporate networks which are characterized by fragmentation, decentralization and single ties. Second, combinations of causal conditions that explain the emergence of each type of corporate networks are identified using fuzzy set qualitative comparative analysis (fsQCA). Finally, avenues of research on corporate interlock networks are suggested.

Purpose While veganism is becoming a new cultural trend, related research is limited. Therefore, this study uses the PPM framework to introduce the new concept of vegan hotels and investigates the impact of push, pull, and mooring (PPM) factors on customers’ behavioral intentions. Design/methodology/approach This study examined the effects of PPM factors for vegan hotels on the intention to visit such a hotel. These PPM factors were explored using a qualitative approach, and the three hypotheses were verified using structural equation modeling (SEM). Then, necessary conditions were verified to identify various combinations of causal conditions that determine the intention to visit a vegan hotel using fuzzy set qualitative comparative analysis (fsQCA). Findings This study explored 10 PPM factors for vegan hotels using the PPM framework. The results revealed that pull factors had a positive effect on the intention to visit a vegan hotel, whereas push factors and mooring factors did not have a statistically significant effect. Moreover, four combinations of causal conditions that determine the intention to visit a vegan hotel were presented. Research limitations/implications This study proposed a conceptual model explaining the behavioral responses of customers toward vegan hotels using the PPM framework and prove the model through empirical analysis. The suggested theoretical and practical implications provide critical and meaningful insights for practitioners and researchers specializing in studying hotels. Originality/value This study proposed a new concept of vegan hotels that, to the best of our knowledge, does not exist in the existing literature using the PPM framework. PPM factors for vegan hotels were explored using a qualitative approach, and their impact on customer behavioral intentions was verified using a quantitative approach. The optimal combinations of PPM factors for vegan hotels was also presented using fsQCA.

Quantitative studies in marketing are dominated by variance-based approaches. These have limitations for understanding macromarketing outcomes that often derive from different combinations of causal conditions, and where factors productive of the same outcome may be different from those impeding it. In this paper we draw on set-theoretic theory and propose qualitative comparative analysis (QCA) as an analytical method able to complement and extend macromarketing research programs. Fuzzy-set QCA is used to explore combinations of conditions influencing COVID vaccine adoption, with readers provided with detailed guidance through the process and current best practices. We consider a number of important but often neglected issues in fuzzy-set QCA; outlining how to conduct robustness checks, appropriateness of a two-step approach, identifying individual cases with specific conditions for further analysis, and examining the problems and opportunities provided by irrelevant cases and contradictions. A summary of macromarketing issues that may benefit from QCA, and recommended practices for conducting a QCA, are provided.

Multinational enterprises (MNEs) are increasingly off-shoring some of their R&D to emerging markets, including China. Much of the extant literature on MNEs' investments in R&D facilities abroad analyses technological and institutional factors at the national level, typically using regressions to examine how host-country institutions influence foreign MNEs' outlays. It, therefore, tends to downplay the importance of sub-national and non-technology-related institutions, and how configurations of home- and host-country institutions interact to influence R&D commitments abroad. Drawing on the global factory model and the Varieties of Capitalism approach, we identify five causal conditions that may influence MNEs' R&D commitments abroad. Conducting an abductive fuzzy-set qualitative comparative analysis, we find four combinations of causal conditions are sufficient to explain substantial R&D commitments in different Chinese provinces. The combination of local corruption and provincial R&D intensity is important, as are the MNE's home-country stock-market capitalization to GDP ratio and minority investor protection. We contribute to the literature on MNEs' investments abroad by extending the importance of sub-national institutions to include those not directly related to technology. We also reveal how combinations of institutions (rather than individual ones acting independently) from the MNE's home and host contexts explain MNEs' R&D commitments in Chinese provinces.

Online reviews are crucial to understanding tourist satisfaction (TSA) in the digital tourism era. This study deconstructs the factors leading to high TSA performance in reviews, offering guidance for long-term economic benefits for destinations and businesses. Building on the three-factor theory, we create a framework utilizing text mining, affective distribution computing, and fuzzy-set qualitative comparative analysis (fsQCA) to identify patterns driving high TSA. We employ topic modeling to extract destination attributes from reviews, quantifying their performance through affective distribution computing. An enhanced Kano model classifies tourist needs based on emotional expressions in reviews. We investigate how basic, performance and excitement attributes interact and influence TSA. Additionally, we apply the coupling coordination degree model (CCDM) to analyze attribute interconnections within configurations. Our results show that no single attribute leads to specific outcomes; relatively, high TSA results from a combination of attributes. This study identifies three normative causal recipes and is the first to clarify the complex interactions in satisfaction management within the three-factor theory framework, addressing a significant knowledge gap. Ultimately, our operational guidelines aim to sustain the economic vitality of the tourism industry. First published online 14 July 2025

Purpose – This paper aims to examine the critical elements for female chefs in overcoming the glass ceiling in a relevant sector of the hospitality industry: haute cuisine. Design – It is based on an empirical study. We surveyed 202 cooks and chefs from France, the US and Spain. Methodology – The data were analysed using fuzzy set qualitative comparative analysis (fsQCA). The fsQCA identifies patterns or combinations of causal conditions that lead to an outcome to evaluate the variety of conditions that produce high career expectations among female professional chefs. Approach – Although the status of women in the hospitality industry has received academic attention, there is still a gap in research on gender discrimination in haute cuisine, specifically regarding the factors that enable for women’s advancement to chef. Findings – Six variables were identified that impact female chefs’ career advancement (entrepreneurial attitude, mentoring, career expectations, workplace environment, skills learned on the job, and their perception of a glass ceiling). The results show that entrepreneurial attitude is a critical enabler for the career advancement of female chefs. This factor is moderated by incumbents’ skills acquired in the workplace, combined with adequate mentoring, which facilitates the absence of a harsh environment perception by female chefs. Originality of the research – The theoretical framework developed for this study contributes to the literature on female entrepreneurship in haute cuisine and its contribution to overcoming gender barriers to advancement in the sector.

Purpose This study aims to formulate propositions based on combinations of causal conditions that lead to high or low financial anxiety among European students, particularly in Poland and Czechia. Design/methodology/approach The data for this study were collected in September 2023 from 265 undergraduate and graduate students with their income at one university in Poland and three in Czechia. Students’ views on financial anxiety were explored using a seven-item Likert scale. This study uses fuzzy set qualitative comparative analysis (fsQCA), an emerging marketing research technique. Findings There are specific factors that may cause increased financial anxiety among young adults in Poland and Czechia, leading to the following key findings: (1) A mix of factors such as perceived lack of financial knowledge, being female, living with parents, having a low monthly income, single status and working a few hours or not at all is linked to higher financial anxiety. (2) Experiencing financial anxiety is also likely when there is low financial knowledge, female gender, living away from parents, single status and a high number of work hours. (3) The combination of low financial literacy, female gender, living with parents, being single and working more hours can elevate financial anxiety. Originality/value This study expands the scope of personal financial research by examining how cultural, socioeconomic and psychological factors affect students’ financial anxiety in two European countries that were infrequently studied in this context. It contributes to identifying the drivers of increased and diminished financial anxiety among young adults in Poland and Czechia.

In order to survive and gain competitive advantages in the post COVID-19 pandemic, tourism destinations should plan their business strategy by focusing on customer expectation. A number of research have studied tourist satisfaction, particularly, hotels and transports, however there is limited investigation with tourist attractions which have different prominence from other tourism service providers. The purpose of this study was to identify the tourists’ satisfaction components for tourist attractions by adopting an opinion mining technique and using the zero-shot text classification method. The total of 40,000 online tourists’ reviews from 40 tourist attractions in Thailand, that were posted up thought TripAdivisor.com between 2010 and 2021, were analyzed. The research findings reveal six components of tourist attraction satisfaction (TATSAT) model that includes 1) ambiance, 2) hospitality, 3) price, 4) accessibility, 5) cleanliness, and 6) security. All attributes of TATSAT model are generated from tourists’ point of view and was analyzed by the focus group discussion with five tourism experts from both academics and practitioners. This model expands the idea of HOLSAT and SERVQUAL by focusing on the tourist attraction business sector. The results can serve academics and practitioners in the research and improvement of tourist satisfaction to maximize competitive advantages for tourist attraction sector in the future.

Under pressure from international buyers and local government, garment suppliers in Bangladesh have intensified their efforts to improve work conditions in their factories. Available studies have identified a range of interdependent organizational factors leading to improved OHS outcomes using large-N statistical studies and estimating average effect sizes. Yet, with such interdependence among organizational factors, no study has yet identified and compared combinations of organizational factors or pathways across a set of cases examining OHS outcomes. In this paper, we use small-N fuzzy set qualitative comparative analysis to identify combinations of organizational factors leading to improved OHS performance in the garment industry of Bangladesh. Fourteen cases were selected through purposeful sampling aiming to maximize the variations in causal conditions and output, which facilitates the identification of pathways among the selected garment suppliers. Based on the available studies, we identified and coded five organizational factors (causal conditions) to examine their influence on OHS performance. Results reveal two distinct pathways leading to improved OHS performance. Common to the two pathways are three causal conditions: Accountability, Auditing, and Training. In addition, to the three common causal conditions, pathway 1 and pathway 2 include respectively Leadership and Buyers, revealing two distinct approaches to improve OHS performance among garment suppliers. Contrary to the expectations in the literature, our study indicates that long-term relationships and partnerships with international buyers is the main driver for improved OHS performance in pathway 2, thus compensating for the absence of active leadership and management commitment.