Fuzzy-set Qualitative Comparative Analysis Research Articles

Implementation in the European Union. A concept structural meta-study of environmental and social policy

ABSTRACT The implementation of EU law has been investigated since the 1980s without pinpointing any general explanatory mechanisms, while most studies focus on highly specific empirical analysis without going beyond basic conceptual descriptions. Theoretically, this paper proposes an alternative comparative framework to conceptualize and analyze differentiated policy implementation based on concept structural considerations. Empirically, existing case studies are compared in a meta-study by transferring their statements on explanatory conditions and outcomes into a parsimonious, procedural model. This approach enables a theory-guided, systematic comparison of qualitative case studies which has long been considered a desideratum in the implementation literature. The paper addresses the question under which conditions correct implementation (i.e. transposition and application) of EU directives occurs. Starting from a literature assessment, explanatory patterns are extracted and formalized as set-theoretic conditions connected to transposition and application as outcomes. The resulting concept structural model links the conceptual and explanatory levels of the underlying concepts. Using fuzzy set QCA, cases from environmental and social policy directives are assessed empirically based on case study data. The results largely confirm the expectation that only a conjunction of willingness- and ability-related conditions leads to correct implementation, particularly conjunctions of favourable attitudes and compatible institutional structures or capacities.

Exploring the relationships between digital transformation, organizational slack and business performance: a configurational approach

PurposeThe survival of companies today hinges on their adaptability and flexibility, with digital transformation (DT) and organizational slack (OS) playing crucial roles. Despite their recognized importance, these factors are often studied separately. This study aims to explore how OS facilitates DT and evaluate their synergies and trade-offs to improve performance.Design/methodology/approachUsing data from the European Manufacturing Survey, structural equation modeling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA), we investigate causal relationships and possible combinations between different dimensions of OS and DT that contribute to business performance.FindingsWe confirmed the positive effect of OS and DT on business performance, highlighting the importance of organizational over technological factors. While not definitively establishing OS as a precursor to DT, our findings underscore the need for human and operational slack to improve performance, especially in less technology-intensive contexts.Research limitations/implicationsOur findings evidence that decision-makers should integrate OS with DT initiatives to improve the firm’s competitiveness. However, it is worth noting that while OS seems essential in low-tech shopfloors, its importance is lower in high-tech environments. Furthermore, within the possible combinations, managers should promote operational slack and digitalization, as it seems fundamental to improve business performance.Originality/valueThis article contributes to the management field in three ways. First, it clarifies controversies by providing evidence of the positive roles of DT and OS as drivers of competitiveness for manufacturing firms. Second, we verify that OS is not directly linked to DT, challenging existing assumptions. Third, it investigates the combinations of OS and DT that drive business performance improvement, emphasizing their synergies and trade-offs.

Sociopolitical context and COVID-19 fatality rates in OECD countries: a configurational approach

BackgroundThe effectiveness of crisis response can be influenced by various structural, cultural, and functional aspects within a social system. This study uses a configurational approach to identify combinations of sociopolitical conditions that lead to a high case fatality rate (CFR) of COVID-19 in OECD countries.MethodsA Fuzzy set qualitative comparative analysis (QCA) is conducted on a sample of 38 OECD countries. The outcome to be explained is high COVID-19 CFR. The five potentially causal conditions are level of democracy, state capacity, trust in government, health expenditure per capita, and the median age of population. A comprehensive QCA robustness test protocol is applied, which includes sensitivity ranges, fit-oriented robustness, and case-oriented robustness tests.ResultsNone of the causal conditions in both the presence and negation form were found to be necessary for high or low levels of COVID-19 CFR. Two different combinations of sociopolitical conditions were usually sufficient for the occurrence of a high CFR of COVID-19 in OECD countries. Low state capacity and low trust in government are part of both recipes. The entire solution formula covers 84 percent of the outcome. Some countries have been identified as contradictory cases. The explanations for their COVID-19 CFR require more in-depth case studies.ConclusionsFrom a governance perspective, the weakness of government in effectively implementing policies, and the citizens’ lack of confidence in their government, combined with other structural conditions, serve as barriers to mounting an effective response to COVID-19. These findings can support the idea that the effects of social determinants of COVID-19 outcomes are interconnected and reinforcing.

Driving Paths and Evolution Trends of Urban Low-Carbon Transformation: Configuration Analysis Based on Three Batches of Low-Carbon Pilot Cities

In response to global climate challenges, urban low-carbon transformation has become a critical strategy for sustainable development. This study constructs a theoretical model for urban low-carbon transformation using the multi-level perspective framework. We focused on three batches of low-carbon pilot cities in China and employed fuzzy set qualitative comparative analysis to investigate the transformation pathways and impact mechanisms during the periods 2010–2012, 2012–2017, and 2017–2019. The results indicate that none of the six antecedent conditions is necessary for urban low-carbon transformation. Initially, the transformation is primarily driven by a pathway led by low-carbon industries. In the mid-stage, two pathways emerge: one dominated by the combination of low-carbon industries and research and development (R&D) human capital and another led by low-carbon consumption awareness and economic development levels. In the later stage, the influencing factors involve a combination across micro, meso, and macro levels, reflecting an increasingly diversified and intricate configuration. The regional industrial structure consistently plays a dominant role, while awareness of low-carbon consumption has grown over time. This study not only enhances our understanding of the underlying mechanisms but also provides practical policy recommendations for local governments to tailor their strategies for effective low-carbon transformation.

How can regional innovation ecosystems attain and maintain stable operation? - an investigation utilising NCA and fsQCA

ABSTRACT This study uses the Multi-Level Perspective (MLP) on socio-technical transitions to develop a theoretical model for analyzing the stable operation of regional innovation ecosystems. Focusing on 30 provinces in China, it employs Necessary Condition Analysis (NCA) and Fuzzy-set Qualitative Comparative Analysis (fsQCA) to systematically examine the configuration paths driving their stability. First, the findings reveal that innovation actors, resources, driving policies, industrial regulations, infrastructures, and the innovation environment are not individually necessary for stability. However, infrastructure is identified as a critical core condition. The study highlights a complex causal relationship and synergistic interplay among the six antecedent conditions. Second, the research identifies two paths to highly stable operation in regional innovation ecosystems: the ‘Innovation Actor + Infrastructure’ path and the ‘Infrastructure’ path. Finally, the results show that configurations for highly and non-highly stable operations exhibit causal asymmetry, indicating ‘different paths to the same destination.’ This study deepens theoretical insights into regional innovation ecosystems and offers actionable strategies for their stable operation.

Green transformation paths of resource-based cities in China from the configuration perspective

Green transformation is an unavoidable choice for resource-based cities (RBCs) that face resource depletion and environmental pollution. Existing research has focused primarily on specific RBCs, making it challenging to apply green transformation strategies universally across cities. The fuzzy set qualitative comparative analysis (fsQCA) is a combination of qualitative and quantitative analyses that can handle multiple concurrent causality problems and determine how different conditions combine into configurations and generate an outcome. Thus, to address this gap, in this study, we established a research framework for green transformation and utilized the fsQCA to examine the configurations of 113 RBCs in China. By incorporating the element of time, this study explored the dynamic evolution of solutions in 2013, 2016, and 2019. The main findings indicate that individual elements do not constitute the necessary conditions for improving the green transformation efficiency (GTE), and the systematic combination of multiple conditions is an effective path for realizing the improvement of the GTE in RBCs. Green transformation paths of RBCs exhibit the same destination through different paths. Additionally, the combination of system environment elements and system structure elements is both complementary and alternative. Differences in RBCs have led to various factor combinations and development paths, but there are some similarities in the key elements of the factor combinations at different stages. Economic environment, government support, and technological innovation are key factors that universally enhance the GTE in RBCs. These insights can assist city managers in formulating policies to drive green transformation and contribute to a better theoretical understanding of green transformation paths in RBCs.

Shaping innovation pathways: Metaverse application configurations in high-technology small- and medium-sized enterprises

The emergence of Industry 4.0, characterized by rapid technological change and fierce competition, challenges technology firms to make strategic innovation decisions. Central to this is the metaverse, a hybrid virtual space combining virtual reality, augmented reality, and the internet. Recognizing that the implications of metaverse applications extend beyond individual organizations, this research examines its adoption configurations. Using the Technology Acceptance Model (TAM) and the Technology-Organization-Environment (TOE) framework, we analyze survey data from 116 high-technology small and medium-sized enterprises in China using fuzzy-set qualitative comparative analysis (fsQCA). Our research reveals that no isolated factor within the TAM-TOE framework solely affects innovation decision-making. Instead, we identify three configurations that enhance decision-making quality and three that increase its speed, leading to improved innovation performance. In this way, this research advances the understanding of technology adoption configurations in the innovation processes of young tech firms.

Sustainable Development of Digital Cultural Heritage: A Hybrid Analysis of Crowdsourcing Projects Using fsQCA and System Dynamics

Cultural heritage crowdsourcing has emerged as a promising approach to address the challenges of digitizing and preserving cultural heritage, contributing to the sustainable development goals of cultural preservation and digital inclusivity. However, the long-term sustainability of these projects faces numerous obstacles. This study explores the key configurational determinants and dynamic evolutionary mechanisms driving the sustainable development of cultural heritage crowdsourcing projects, aiming to enhance their longevity and impact. An innovative integration of fuzzy-set qualitative comparative analysis (fsQCA) and system dynamics (SD) is employed, drawing upon a “resource coordination–stakeholder interaction–value co-creation” analytical framework. Through a multi-case comparison of 18 cultural heritage crowdsourcing projects, we identify necessary conditions for project sustainability, including platform support, data resources, knowledge capital, and digitalization performance. The study reveals multiple sufficient pathways to sustainability through configurational combinations of participant motivation, innovation drive, social capital, and social impact. Our system dynamics analysis demonstrates that crowdsourcing project sustainability exhibits significant nonlinear dynamic characteristics, influenced by the interaction and emergent effects of the resource–participation–performance chain. This research offers both theoretical insights and practical guidance for optimizing crowdsourcing mechanisms and sustainable project operations, contributing to the broader goals of sustainable cultural heritage preservation and digital humanities development. The findings provide a roadmap for policymakers and project managers to design and implement more sustainable and impactful cultural heritage crowdsourcing initiatives, aligning with global sustainability objectives in the digital age.

Exploring configurations of digital servitization capabilities for value creation: An fsQCA approach

Digital servitization is the process by which manufacturing firms transition from offering products to offering solutions that integrate products with services and digital technologies. Although previous studies have looked into the capabilities necessary for this transition, several topics need further exploration to advance the research field. The central issue is how digital servitization capabilities create value for the firm, followed by the need for a comprehensive and updated perspective on digital servitization capabilities to properly explain this relationship. Moreover, the effectiveness of different service delivery capabilities, the role of manufacturing capabilities in the offering of digital services, and how digital servitization capabilities evolve are topics that also need to be clarified. To address these issues, the present study developed a theoretical framework comprising four digital servitization capabilities (Integration, Provision, Orchestration, and Manufacturing) and conducted a multiple case study involving 24 Brazilian manufacturing firms. Employing a configurational approach, fuzzy-set Qualitative Comparative Analysis (fsQCA) was used to analyze the data. The findings reveal that two configurations of digital servitization capabilities enable value creation: Integration, Provision, and Manufacturing or; Integration, Orchestration, and Manufacturing. The study demonstrates that each configuration represents a different way of operationalizing the same digital servitization strategy, advancing the knowledge on the relationship between digital servitization and value creation.

Optimizing cell phone recycling process: Unraveling rational and emotional drivers of consumer recycling participation using PLS-SEM and fs-QCA

The rapid obsolescence of cell phones has led to significant challenges in electronic waste. Effective recycling processes are crucial to mitigate environmental impacts and recover valuable materials. However, consumer participation in obsolete cell phone (OCP) recycling remains suboptimal. The purpose of this research was to apply the Theory of Planned Behavior (TPB) to investigate the factors that influence the intention to recycle obsolete cell phones among Chinese consumers. By analyzing 621 valid survey responses using Partial Least Squares Structural Equation Modeling (PLS-SEM), the study identifies that attitude, perceived behavioral control, and subjective norm, as rational factors, significantly predict OCP recycling intention. Additionally, privacy concern and object attachment, as emotional factors, are found to reduce OCP recycling intention. Further analysis using Fuzzy-Set Qualitative Comparative Analysis (fs-QCA) pinpoints essential TPB configurations that enhance OCP recycling intention, highlighting that the absence of both privacy concern and object attachment contributes to high recycling intention. By introducing an emotional perspective, this study advances our understanding of the mechanisms underlying OCP recycling behavior. Strategic directions for improving cell phone recycling management are discussed.

A Fuzzy-Set Qualitative Comparative Analysis for Understanding the Interactive Effects of Good Governance Practices and CEO Profiles on ESG Performance

The impact of corporate governance mechanisms has been examined directly and independently, considering that such characteristics compete to explain environmental, social, and governance (ESG) performance. However, the nexus may be more complex than that suggested by most scholars, and more research is needed. This study applied a fuzzy-set qualitative comparative analysis to a sample of Spanish-listed companies in 2018–2020 to explore how good governance practices interact with CEO profiles to promote corporate sustainability practices. Our analysis discovered the importance of establishing sustainability committees and identified five pathways shaping governance practice bundles. Specifically, listed companies with a high code of good governance (GGC) compliance and a sustainability committee improve high ESG performance globally and for each ESG dimension. Furthermore, the effect is more relevant than the effect of the CEO profile, requiring either CEO duality (pathway 1) or extended CEO tenure (pathway 2). Concurrently, findings indicate three CEO profile configurations for GGC-neutral firms, providing companies with more flexibility in CEO selection. Two suggest that younger CEOs with longer tenure tend to be more motivated to engage in the G and S pillars (pathways 3 and 5). The third indicates that CEOs of older age and early tenure improve the E pillar (pathway 4).

Factors Affecting Location-Based Career Planning of Freelance Employees: An Asymmetric Analysis by OECD Member Countries

The growing interest in freelancing after the 1980s has led to the need to deepen the academic scope. Although there are various studies on freelancing, location-based studies have remained at a basic level. The study aims to identify the factors affecting the location-based career planning of freelancers in the context of OECD countries. In this context, the methodology of the research is a theoretical comparative qualitative analysis based on asymmetric analysis (Fuzzy Set QCA). The adequacy/requirements, configurations and country-specific clusters of effective conditions suitable for self-employment are revealed. According to the research findings, while all variables are found to be sufficient for the freelancing score in a singular sense, the absence of demand for freelancers reveals the absence of demand for the freelancing score as an absolute requirement. Based on the configuration results, specific results are found that could potentially suggest a model for freelancing status (FS) and non-freelancing status (~FS) of countries. Ultimately, the findings are instrumental in identifying the most favorable conditions and countries for freelancers. In this way, the research enables employees to plan their careers by taking into account the conditions that they deem important for them individually.

Unable to comply with regulations: How deterrent and social learning factors contribute to workplace safety violation.

Workplace safety violation is a significant challenge for global enterprises. However, prior studies have generated inconsistent findings, which calls for a holistic framework to reveal the complex causality between antecedent conditions and workplace safety violations in high-risk industries. By embracing deterrence theory and social learning theory, this study aimed to examine how punishment (i.e., perceived punishment certainty and perceived punishment severity), shame (i.e., perceived shame certainty and perceived shame severity) and coworker safety violations (CSV) combine into configurational causes of employee safety violations (ESV). A two-wave sampling approach was used to obtain 370 usable samples from various high-risk industries in China. The confirmatory factor analysis was performed to test construct validity, and an emerging fuzzy set qualitative comparative analysis (fsQCA) was conducted to explore the complex causality between ESV and its multiple antecedents. The fsQCA results indicate that no single antecedent condition is necessary for predicting high ESV, but three distinct configurations of multiple antecedents equivalently lead to high ESV. Among all configurations, a lack of perceived punishment severity, a lack of perceived shame certainty and severity, and high CSV play important roles in explaining ESV. This study represents a pioneering endeavor utilizing fsQCA to explore how different combinations of punishment, shame and social learning antecedents contribute to high ESV, which goes beyond previous research focusing on antecedents independently and offers new insights into interconnected antecedents of ESV and their complex causality.

Unveiling the optimal configuration of impulsive buying behavior using fuzzy set qualitative comparative analysis and multi-criteria decision approach

Sudden and unplanned purchasing behavior is considered impulsive buying behavior. With the increasing popularity of social commerce platforms and shopping automation, people's tendency towards impulsive purchases has grown significantly. In this connection, the role of marketing influencers has crucially impacted the customers' purchasing decisions over the last decade. This study aims to investigate the effect of marketing influencers on impulsive buying behavior. In addition, the current study addresses a critical methodological problem by highlighting the optimal configuration provided by fuzzy set qualitative comparative analysis (fsQCA) using a multi-criteria decision approach (MCDM). Based on a survey of 672 users of live streaming commerce platforms in Malaysia, we examined impulsive buying behavior from the perspective of influencer marketing, cognitive trust, and affective trust in influencer. Partial Least Squares Structural Equation Modeling (PLS-SEM) results confirmed the influence of parasocial relationship, authenticity, expertise, trustworthiness, attractiveness, and influencer–follower congruence on impulsive buying behavior through cognitive trust in influencer, affective trust in influencer, and behavioral inertia. The fsQCA results provided 15 different configurations confirming the role of marketing influencers' characteristics in impulsive buying behavior. However, fsQCA analysis is unable to determine the optimal solution or configuration. To this end, the MCDM analysis complemented the fsQCA analysis by unveiling the optimal configuration, which was the ninth configuration. Furthermore, the combination of authenticity, expertise, trustworthiness, cognitive trust, affective trust is considered a key concept to increase impulsive buying behaviour regardless of the presence of a parasocial relationship.

Pathways to e-participation diffusion: A societal and governance perspective

E-participation diffusion is influenced by the interactions of multiple contextual factors. This study examines how societal dynamics and governance (i.e., national culture, economic prosperity, human capital, population size, online trust, and regulation) interact to produce high and low levels of e-participation diffusion. The study uses fuzzy-set qualitative comparative analysis (fsQCA) and necessary condition analysis (NCA) on a dataset of 88 countries collected from multiple sources. FsQCA reveals three paths for high e-participation diffusion (each includes either high online trust or high regulation combined with at least one additional condition) and a single path combining low online trust and regulation for low e-participation diffusion. NCA identifies that regulation, online trust, human capital, and economic prosperity are necessary conditions for high e-participation diffusion, while no necessary condition is identified for low e-participation diffusion. Uncovering casual mechanisms leading to high and low e-participation diffusion, the study contributes to the conversation on technology-mediated participatory governance interactions and guides decision makers in formulating targeted strategies to promote e-participation diffusion.

Knowledge exchanges for collaborative innovation and organizational effectiveness: insights from Indian enterprises

PurposeThis study aims to delve into the relationship between open innovation and organizational effectiveness, expanding upon previous research that primarily focused on the impact of open innovation on firm performance.Design/methodology/approachBased on data collected from top- and middle-level managers across diverse sectors in India, the authors examined the intricate dynamics of open innovation and its effects on organizational effectiveness. The authors took two approaches to examine the data; using structural equation modeling and using the fuzzy set qualitative comparative analysis (fsQCA) approach.FindingsThis empirical evidence underscores the potential advantages of adopting open innovation practices within organizations. The contribution extends to both theoretical and practical domains.Research limitations/implicationsTheoretically, this research enriches the literature on open innovation and organizational effectiveness by providing empirical substantiation for their interconnection.Practical implicationsFrom a practical perspective, the findings offer actionable insights for practitioners and organizational leaders, suggesting that embracing open innovation can significantly enhance organizational effectiveness, ultimately fostering improved performance and competitiveness. The findings also have implications for external stakeholders aiming to engage with innovation-driven organizations for purposes of commercialization and knowledge exchange.Originality/valueThis study advocates for incorporating inbound and outbound open innovation practices within strategic decision-making processes to achieve organizational effectiveness.

Classifying and Validating Metahuman Service Quality Dimensions: A Mixed-Method Study

With the development and integration of artificial intelligence (AI) and virtual reality technology, metahuman powered by AI is gradually becoming an important force in service marketing. Considering the novel characteristics of metahuman services, this study aims to identify and validate the core dimensions of the metahuman service quality. Online review analysis, multiple regression analysis, and fuzzy-set Qualitative Comparative Analysis (fsQCA) were employed to analyze data in this study. The results show that nine dimensions of metahuman service quality, including stability, complementary, efficiency, continuous improvement, empathy, accessibility, personalization, cultural sociability, and fault tolerance, significantly contribute to customer satisfaction. Moreover, the results suggest that there are five multiple and equally effective combinations of metahuman service quality dimensions that can achieve high consumers’ satisfaction. This study contributes to the avatar literature by unveiling the complexity behind the adoption of AI-powered avatar. It also offers meaningful practical implications for marketing managers to optimize the combination of metahuman service quality.

Configuration paths of carbon emission efficiency in manufacturing industry

From the perspective of configuration, this paper takes the region of manufacturing efficiency as the explanatory variable, selects eight antecedent conditions, and applies fuzzy set qualitative comparative analysis (fsQCA) to study the paths and methods of improving manufacturing emission efficiency. The results of the study show that there are two configuration paths of carbon emission efficiency in manufacturing industry, namely, research frontier and technological innovation level and labour force structure, R&D investment, science and technology innovation level, manufacturing output value, and environmental regulation synergistic path.

One year of COVID-19: A longitudinal study of individual and relational factors of psychological adjustment of individuals living in a romantic relationship in Portugal during the COVID-19 pandemic.

This longitudinal study explored the impact of COVID-19 on individuals in romantic relationships. The sample spans three waves: first confinement (n = 52), deconfinement (n = 49), and second confinement (n = 26). The study tested sociodemographic factors, psychological adjustment (anxiety, depression, stress, well-being), COVID-19 threat perception, dyadic coping, and relationship quality. Results from repeated measures ANOVA and fuzzy set qualitative comparative analysis (fsQCA) models revealed a decline in anxiety, depression, and stress symptoms, coupled with improved relationship quality over time. Well-being and dyadic coping remained stable, while COVID-19 threat perception increased. QCA models emphasized the predictive power of initial mental states (anxiety, depression, stress, and well-being at W1) on subsequent adjustment. Notably, shorter relationship duration, healthcare worker status, and not having children, when combined with prior mental states, explained increased symptoms and diminished well-being. The study underscores the significance of addressing these factors in individuals navigating romantic relationships during the pandemic.

The multidimensional influence structure of college students’ online gamified learning engagement: A hybrid design based on QCA-SEM

In the post-epidemic era, gamification is widely recognized for its potential to enhance the asynchronous nature of college students' online learning interactions and mitigate efficiency deficits. However, the intrinsic structure and core conditions influencing online gamified learning engagement remain unclear. The challenge lies in understanding the mechanisms through which gamification alters learning behaviors. This study employs fuzzy set qualitative comparative analysis (FSQCA) for core condition identification and robustness testing, innovatively combining it with structural equation modelling (SEM). Drawing on the extended technology acceptance model (TAM) theory, this research delves deeply into the structural relationships that influence student engagement in online gamified learning. The evaluation reveals that immersive experience and habit are core conditions fostering high engagement among college students in online gamified learning. A lack of immersive experience leads to non-high engagement results. Structural equation modelling confirms the mediating role of immersive experience and habit in the effects of performance expectations and perceived fun in student engagement. Furthermore, the study substantiates the moderating influence of learning style on perceptual factors and normalizing elements and describes an interactive relationship between perceived behavioral control, subjective norms, and online gamification behavior. This research extends our understanding of perceptions, norms, and structural factors within a gamified learning environment. It uncovers the mechanisms of engagement from perception to normalization factors, highlighting the positive bidirectional influence of subjective cognition and objective factors on gamified learning and emphasizing the moderating role of learning style between perceptual factors and normalization elements. These findings provide a solid foundation for future research and practice in online gamified learning.