Fuzzy-set method in comparative social policy: a critical introduction and review of the applications of the fuzzy-set method

This article critiques the Fuzzy-set Qualitative Analysis (fs/QCA) methodology by examining its applicability in three studies in the field of comparative social policy. In each of these three test cases, I focus on the validity of fuzzy-set’s claimed function—its ability to combine theoretic discourse and evidence analysis. All three studies investigate welfare state reform in the late twentieth century and apply fs/QCA: (1) “Welfare Reform in the Nordic Countries in the 1990s: Using Fuzzy-set Theory to Assess Conformity to Ideal Types,” (2) “States of Welfare or States of Workfare? Welfare State Restructuring in 16 Capitalist Democracies, 1985–2002,” and (3) “The Diversity and Causality of Welfare State Reforms Explored with Fuzzy-sets.” This article begins by discussing the ontology and epistemology of comparative social policy. The fuzzy set logic and set theoretic nature of social science theory is then discussed to align the ontology with fuzzy set methodology. Next, a more detailed introduction of fuzzy-set method (fs/QCA) is followed. This study suggests that fs/QCA is a unique and useful method for comparative social policy. It advances quantitative analysis by exploring cases configurationally and also advances the qualitative analysis by applying the fuzzy set logic and the principle of calibration.     

Qualitative comparative analysis (QCA): an application for the industry

This article examines the management in Colombian industrial sectors using qualitative comparative analysis (QCA). This method conceptualizes cases as combinations of attributes and use Boolean algebra to derive simplified expressions of combinations that lead to a specific outcome. In this analysis, we show the value of this method for studying the management in the industrial from different approaches.     

A review of integrated QCA and statistical analyses

Systematically combining quantitative and qualitative research approaches offers the potential for a more comprehensive and nuanced understanding of social scientific phenomena. With their strong opportunities for building, qualifying, and testing social scientific theories, methodological integrations thus enable researchers to make substantive contributions that would not have been possible with one method alone. In this article we demonstrate how the integration of Qualitative Comparative Analysis (QCA) and conventional statistical analysis offers researchers new opportunities for contributing to the social sciences. Whereas statistical analysis is variable-oriented and relies on correlational analysis to make comparisons across cases, QCA is based on set theory, is case oriented, and relies on Boolean algebra to make comparisons between cases. Drawing on the literature on the interdependency between theoretical contribution and methodology, we review studies that integrate QCA and statistical analysis to explain how the specific combination of these two approaches allows researchers to strengthen the theoretical contribution of their research. From our review we identify common challenges and provide solutions for integrating QCA and statistical analysis.     

A comprehensive conceptual and bibliometric study of person-centered methodologies

Person-centered approaches, such as latent profile analysis (LPA) and qualitative comparative analysis (QCA), have gained in popularity in organizational scholarship because of their ability to provide insight into how interrelations between a group of conditions can lead to a particular outcome. Despite the growing acceptance of person-centered approaches in social science research, traditional variable-centered approaches continue to prevail, although their dominance is increasingly questioned. This paper offers in-depth analysis of the current state of QCA and LPA from both a conceptual and a bibliometric perspective. This study thus aims to contextualize the role of person-centered methodologies in organizational scholarship. This aim is important, given the significance of exploring novel approaches to advance knowledge in organizational research. This paper provides scholars with quantifiable and readily comparable information on the use of these emerging but promising methods in organizational studies. Ultimately, this scientific contribution sheds light on the current and prospective applications of person-centered methods in research. Moreover, it offers scholars who are considering applying these methods objective analysis of the scientific production in this area thus far.

     

Relationship between entrepreneurial orientation and social performance in Spanish sports clubs. The effect of the type of funding and the level of competition

The entrepreneurial orientation and social role of sports clubs have recently become topics of great interest to academics and professionals. The aim of this study is to analyse the relationship between entrepreneurial orientation (EO) in sports clubs and their social performance (SP) and the effect that management variables such as the type of funding (public vs private) and the competition level (national vs regional) may have on this relationship. To compare the results, two complementary methodologies have been used to compare the results: linear models with moderation analysis and models based on qualitative comparative analysis (QCA). The study was carried out with a sample of 407 Spanish sports clubs. The instrument used to measure EO was an adaptation of the original Covin and Slevin (1989) approach, while the instrument used to measure SP is a validated scale of our own elaboration presenting good psychometric properties. The results found show a direct effect of the EO dimensions on the SP. In all cases, clubs with major public funding showed higher levels of prediction in SP. On the other hand, as far as QCA is concerned, no necessary condition was found, while the most important condition sufficient to obtain high levels of SP would be high levels of innovation, a high level of risk-taking, and low levels of proactivity in national sports clubs. In general, models based on qualitative comparative analysis (QCA) provide higher predictive values than linear regression models and include variables not considered in linear models.

     

Conservative solutions for progress: on solution types when combining QCA with in-depth Process-Tracing

Quality & Quantity - What is the most appropriate QCA solution type when engaging in a multimethod design that includes QCA and in-depth process-tracing (PT)? While either the intermediate or...     

Qualitative Comparative Analysis and robust sufficiency

Quality & Quantity - Some methodologists take the search target of Qualitative Comparative Analysis (QCA) to be causal INUS-conditions, others contend that QCA should instead be used to search...     

Contextual analyses with QCA-methods

Contextual analyses are essential in comparative research, as they investigate the importance of contextual conditions for causal relationships. During the last decades, an increasing number of comparative studies have also focused on how contextual conditions affect causal relationships. At the same time, new comparative methods have been developed based on set-theoretical logics. Two of the most prominent methods are csQCA and fsQCA, which are used in comparative studies with increasing frequency. However, the conventional design for contextual analysis is still based on quantitative methods and the use of interaction-factors. This article discusses why the use of interaction-factors is not suitable together with QCA-methods. Instead of the conventional design, the article presents an alternative design for contextual analyses with QCA-methods grounded on subgroup-design. Based on one recently-developed methodology comparative multilevel analysis (CMA), some guidelines for performing contextual analyses with two set-theoretical methods (csQCA and fsQCA) are presented. As illustrated with examples, the combination of CMA and QCA provides opportunities to use QCA for contextual analysis.     

Quantile forecasting with mixed-frequency data

We analyze the quantile combination approach (QCA) of Lima and Meng (2017) in situations with mixed-frequency data. The estimation of quantile regressions with mixed-frequency data leads to a parameter proliferation problem, which can be addressed through extensions of the MIDAS and soft (hard) thresholding methods towards quantile regression. We use the proposed approach to forecast the growth rate of the industrial production index, and our results show that including high-frequency information in the QCA achieves substantial gains in terms of forecasting accuracy.     

Conditions for policy implementation via co-production: the control of dengue fever in Brazil

In this paper, we identify the conditions that must be present for effective policy implementation using co-production. To this end, we investigated five cases in which co-production was used to combat the vector of dengue, the Aedes Aegypti mosquito, in Brazil. Data were analysed using content analysis and crisp-set QCA methods to identify the combination of conditions that explain successful outcomes. Five conditions were found to be necessary for effective implementation via co-production: technical, economic, normative, cognitive and structural. The contribution of this study is to provide empirical evidence with respect to the conditions that effectively lead to successful outcomes.     

Re‐Thinking Territorial Cohesion in the European Planning Context

The socio‐economic dimensions of cohesion have long been considered an integral part of Europeanization. However, recently a third dimension has been added to the Europe 2020 cohesion policy debate: territorial cohesion. Consequently this term is as yet undeveloped, resulting in a lack of consensus on how to define and interpret it. Such ambiguity represents a theoretical and empirical challenge to regional actors needing to respond to European Union (EU) directives while operationalizing the concept within their national and/or regional agendas. This article uses Portugal as a case study to examine how the concept of territorial cohesion is being interpreted and transposed from EU‐based to territorial‐based instruments and policy documents. First, we conducted a qualitative content analysis (QCA) of a selection of European and regional publications to compare their intrinsic discourses. This was followed by around 60 structured qualitative interviews, conducted with leading actors who had been instrumental in writing or implementing regional policy documents. On the basis of this dual analysis we conclude that, as a whole, the writers of the Portuguese strategic documents successfully transposed this concept, although perceptible differences exist between regions, as local actors have selectively redefined it to better suit their strategic priorities. These differences are debated with the aim of contributing to the design of effective public policies that facilitate inclusion, cohesion and Europeanization.     

动态环境与生命周期视角下人力资源管理策略对组织绩效的影响:基于模糊集定性比较分析

基于资源依赖理论,采用模糊集定性比较分析(fs/QCA)方法 ,探讨在动态环境下,处于不同生命周期的组织该采用何种人力资源管理策略(HRMP)才能有效提高组织绩效。对491个企业样本进行统计分析,本研究发现:(1)在环境动态性程度不高的情境下,处于成长期的企业实施控制型HRMP能帮助组织取得高绩效;(2)在环境动态性比较高的情境下,处于成长期的企业实施承诺型HRMP能帮助组织取得高绩效;(3)在环境动态性比较高的情境下,处于衰退期的企业需采用承诺与控制相混合的HRMP才能实现组织高绩效目标;(4)不论环境动态性程度如何,实施承诺型HRMP的成熟期企业将取得高绩效;(5)不论环境动态性程度如何,初创期企业采用承诺与控制相混合的HRMP能帮助组织取得实现高绩效目标。本研究的结论细化了不同类型HRMP实现高绩效的情境条件,这为企业人力资源管理策略在动态环境中的发展和应用提供具体的现实指导。     

A mathematical approach to the boolean minimization problem

Any minimization problem involves a computer algorithm. Many such algorithms have been developed for the boolean minimizations, in diverse areas from computer science to social sciences (with the famous QCA algorithm). For a small number of entries (causal conditions in the QCA) any such algorithm will find a minimal solution, especially with the aid of the modern computers. However, for a large number of conditions a quick and complete solution is not easy to find using an algorithmic approach, due to the extremely large space of possible combinations to search in. In this article I will demonstrate a simple alternative solution, a mathematical method to obtain all possible minimized prime implicants. This method is not only easier to understand than other complex algorithms, but it proves to be a faster method to obtain an exact and complete boolean solution.     

Different algorithms,different models

Quality & Quantity - This study assesses the extent to which the two main Configurational Comparative Methods (CCMs), i.e. Qualitative Comparative Analysis (QCA) and...     

Barriers to women entrepreneurship. Different methods,different results?

Building on research by Akehurst et al. (Serv Ind J 32:2489–2505, 2012), this study analysed internal and external factors in women entrepreneurship and linked these factors to the barriers that women face when starting businesses. To do so, two contrasting statistical techniques were used: PLS and QCA. After analysing results from each of these techniques, we observed that family duties and difficulties in obtaining financing (both internal and external) were the main factors related to barriers faced by women entrepreneurs.     

Moving beyond the tensions in open environmental innovation towards a holistic perspective

This paper analyses factors determining open environmental innovation (EI) and explores the possibility of embracing their tensions to achieve integrated environmental strategic goals. Building on recent literature linking open innovation and EI, the study assumes open EI strategic goals as a multidimensional construct based on the “synergistic and interwoven nature” of four identified enabling factors, that is, partners, knowledge, benefits, and motivations. A fuzzy‐set qualitative comparative analysis (fsQCA) based on Boolean algebra is conducted to analyse a set of 186 European companies operating in the telecommunication and information and communication technology (ICT) service industries. Making important theoretical, managerial, and policy contributions, this paper offers insights into the key factors enabling open EI and the tensional relationships within and between them. In doing so, it captures the non‐linear effects among these factors and the strategic goals related to an open EI strategy. It also suggests how the paradox theory might help in addressing the tensional dilemma of open EI strategy.     

Two-step QCA revisited: the necessity of context conditions

Quality & Quantity - The so-called two-step QCA approach as formulated by Schneider and Wagemann (Eur J Polit Res 45(5):751–786, 2006) proposes a separation of conditions into two...     

Causal conditions for loneliness: a set-theoretic analysis on an adult sample in the UK

While age has been identified as a risk factor for loneliness, whether it is a necessary or sufficient condition for loneliness has never been examined. This is the first study that applies fuzzy-set QCA, a special type of set-theoretic method, to discover the necessary and sufficient causal conditions for loneliness, respectively, among adults in the UK, analysing the data collected from the UK sample of Round 6 of the European Social Survey (ESS, 2012, n = 2163). It firstly examines the configurations of five conditions: being female, old age, not living with spouse/partner, bad health, and not being frequently social with others. Gender was found neither a necessary nor a sufficient condition for loneliness, and old age was close to being a necessary condition and became necessary when united with any of the other conditions; the configuration of not living with spouse/partner and not healthy and not frequently social with others is a sufficient condition. Robustness of results was tested with two different conditions (a limiting illness and a confidante), and a separate analysis on the absence of loneliness was conducted. The effect of the unbalanced distribution of cases across different values of the outcome was highlighted as a source of uncertainty, and the results on the absence of loneliness are different from those on its presence.     

Independent directors and family firm performance: does one size fit all?

How will the presence of independent directors affect family business performance? This question is still theoretically debated and empirically inconclusive. Because family businesses are a group of heterogeneous companies with different levels of family involvement in the business, the purpose of this paper is to empirically explore how the combination of different family business governance structures jointly shape the effect of independent directors on family business performance in an understudied Collectivist cultural setting. Using Qualitative Comparative Analysis (QCA) on a sample of 74 Lebanese family firms this study finds that, depending on the family firm governance structure, the presence of independent directors on the board can lead to either positive or negative firm performance. Theoretical and practical implications are discussed.