Qualitative Comparative Analysis Research Articles

Multiple Paths to Green Building Popularization Under the TOE Framework—A Qualitative Comparative Analysis of Fuzzy Sets Based on 26 Chinese Cities

Green buildings are a crucial element in achieving sustainable development. The use of green buildings can save energy and reduce greenhouse gas emissions. Promoting the widespread adoption of green buildings has become a significant concern in many countries or regions. Although previous studies have identified a range of key factors influencing the promotion of green buildings, further analysis of the combination of these critical factors needs to be conducted. Therefore, based on the technology–organization–environment (TOE) framework, this study utilizes the fuzzy-set qualitative comparative analysis (fsQCA) method to analyze survey data from 26 cities in China, resulting in four high-level configuration paths for the widespread adoption of green buildings. The results indicate that (1) achieving high levels of widespread adoption of green buildings does not depend on any single factor; instead, it relies on the collaborative interaction of multiple elements across technological, organizational, and environmental dimensions; (2) the potential substitution relationships between conditional variables among different configurations within the TOE framework indicate that science and technology expenditure and gross domestic product play more significant roles in the path combinations for the promotion of green buildings; (3) through the study of the substitutive relationships of four configuration paths, it was found that when a city faces challenges in the widespread adoption of green buildings, such as an insufficient number of green building technology patents or underdeveloped green finance incentive systems, it can still achieve efficient green building adoption by formulating corresponding policies and enhancing cultural value guidance for groups like developers, contractors, and consumers. Conversely, the same is true. This paper explores the combination of critical factors in green building adoption, providing insights into addressing the differing foundational conditions of cities in the process.

Shining light on the shadows: The role of corruption control in the relationship between board composition and SDG disclosure

AbstractThis paper investigates how corruption control moderates the relationship between board composition and Sustainable Development Goals (SDG) disclosure. We analyze a sample of 269 companies from Mediterranean capitalism countries (Portugal, Greece, Italy, Spain, Malta, and Cyprus) combining a symmetric method (panel data analysis) and an asymmetric approach (fuzzy‐set qualitative comparative analysis). Our findings show that larger boards enhance SDG disclosure and female presence negatively impacts SDG disclosure. Corruption control is a driver of SDG disclosure, and the effect of board size on SDG disclosure is greater when companies are operating in countries with low rates of corruption. This the first paper that investigates the relationship between board composition and SDG disclosure, highlighting the moderating effect of controlling corruption at the country level. Managers should be aware that some board characteristics drive greater SDG disclosure. Additionally, governments can support SDG disclosure by combating corrupt practices in their countries, and by creating support mechanisms for companies to incorporate SDGs into business strategies.

A comparative analysis of national dementia plans: preventive strategies in five European countries

Abstract Background About 8.5% of people aged +65 live with dementia in Europe. Preventive measures can avert up to 40% of cases. The aim of the study is to analyse National Dementia Plans (NDP) in Europe, to elicit how much dementia prevention is considered a priority and whether policies are evidence-based. Methods A qualitative comparative analysis was performed between NDPs of countries with the best healthy life expectancy in the elderly in Europe. The NDPs of France, Ireland, Italy, Spain, and Sweden were included. The consensus on actions and elements of prevention policies was evaluated, according to the WHO recommendations and to Cheung’s framework designed for evaluating chronic diseases policies. Results All the NDPs prioritised early diagnosis, public awareness, and community engagement for dementia risk reduction. They fostered the development of information system for data collection and established committees for progress monitoring. However, not all NDPs defined timelines for policy implementation and most of them expired years ago. NDPs included prevention research agenda, but their preventive actions did not address alcohol consumption, traumatic brain injury, and air pollution, representing 3 well-known risk factors attributable for the 15% of preventable cases. Neither integration of dementia with other chronic disease preventive strategies was present and a clear allocation of funds for NDPs always missed. Conclusions NDPs partially address risk factors of preventable cases. All countries need to update their NDPs, integrating new scientific evidence and allocating clear financial funds. This can potentially prevent millions of new cases, decreasing the burden of disease and improving the sustainability of health systems. Key messages • NDPs do not target adequately dementia in Europe. • New evidence-based preventive policies, including most recent identified risk factors, would have a clear impact on burden of disease and health systems’ sustainability.

Do green practices and technologies mediate lean manufacturing’s impact on industrial performance? Evidence from the European manufacturing survey

Purpose This study aims to analyze the mediating role that green practices (GPs) and green technologies (GTs) play in the relationship between lean manufacturing (LM) and industrial performance (IP). It is suggested that GPs and GTs are crucial for transforming lean routines into enhanced performance that simultaneously meet current environmental requirements. Design/methodology/approach The hypotheses are tested using a mixed methodology, which includes a partial least squares structural equation modeling approach and a fuzzy-set qualitative comparative analysis (fsQCA) applied to a multisectoral sample from three European countries (Spain, Sweden and Croatia). Findings The results confirm that GPs mediate the relationship between LM and IP; however, in the case of GTs, this mediation does not appear to occur, although GTs emerge as a peripheral condition in the subsequent fsQCA. These findings highlight the need to avoid an exclusively technocentric approach and underscore the importance of implementing green organizational practices alongside technology investments to achieve successful lean initiatives. Practical implications It seems clear that managers should apply GPs, combined with LM, to improve sustainability and efficiency and should apply GTs once a more mature lean-green culture has been established. Originality/value In recent years, the scientific community has increasingly focused on the impact of implementing GPs and GTs on IP within LM plants. However, to the authors’ knowledge, no study has yet analyzed the combined effect of both initiatives. This paper seeks to address this gap by examining, in aggregate, the moderating effect of GPs and GTs on IP in LM plants.

Exploring the Combinatorial Effects of Collaborative Factors Leading to Higher Degree of Co‐Production

ABSTRACTThis study investigates the collaborative factors conducive to co‐production in public services, utilizing Ansell and Gash's framework and fuzzy set qualitative comparative analysis (fsQCA) across 18 cases from the Collaborative Governance Case Database (CGCD). It identifies incentive as a necessary condition for co‐production, revealing three sufficient pathways to co‐production: managed, led, and self‐organized co‐production. The findings advance our understanding of the specific collaborative configurations that can achieve higher degree of co‐production, offering an “incentive‐structure‐behavior” framework and practical insights for policy makers seeking to enhance public service co‐production.

The Driving Factors and Path Selection for the Development Level of China’s Mariculture—A Dynamic Analysis Based on the TOE Framework

Mariculture is a key practice to promote the supply-side reform of fishery, and it is of strategic significance to explore the causes and paths of its high-level development. Based on the TOE (Technology-Organization-Environment) theoretical framework and the configuration methodology, this paper adopts the dynamic qualitative comparative analysis (QCA) method and panel data from 10 coastal provinces and cities in China from 2013 to 2021 to explore the configuration effects of six antecedents, namely, the intensity of technology promotion, investment in scientific research, personnel specialization, industry intensification, nearshore water quality, and offshore pollution discharge, along temporal and spatial dimensions, on the level of mariculture development. The results show that (1) individual driving factors do not constitute the necessary conditions for a high level of mariculture industry development, but the necessity of the three conditions—research funding, industry intensification and nearshore seawater quality—shows a general increasing trend; and (2) the results of the path analysis show that a total of seven configuration paths for a high level of development are generated, which can be further classified into “organization-led and technology synergistic”, “technology-organization-environment multiple-driven type”, and “technology-environment dual-driven type”. Based on the panel data, this study explores the impact of spatial and temporal changes in factor combinations on the development level of mariculture and provides a theoretical basis and practical insights for the development of locally adapted execution pathways.

Research on the Configuration Path of Innovation Performance of Strategic Emerging Enterprises

As vehicles for implementing innovation-driven strategies, the strategic emerging industries are crucial for enhancing national competitiveness and sustainable development. Improving innovation performance in these industries has been a central focus of academic research. Notably, existing studies have primarily analyzed the net effects from a single perspective. This study examined 261 strategic emerging Chinese enterprises listed on the A-share market. Utilizing the Technology–Organization–Environment framework and fuzzy set qualitative comparative analysis, this study explores the impact paths and mechanisms of the coupling configurations of technology, organization, and environment to enhance enterprises’ innovation performance from a configuration perspective. We discovered that, first, no single antecedent condition is necessary to achieve high enterprise innovation performance. However, increasing the level of digital transformation and intensity of innovation investments universally results in high innovation performance. Second, the technological, organizational, and environmental conditions exhibit “multiple concurrency”, forming diverse configurations that drive enterprise innovation performance; hence, the driving paths of enterprise innovation performance are varied. Third, four schemes exist for achieving high innovation performance in strategic emerging enterprises: environment-driven under technological dominance, technology–organization driven type, organization-driven under technological–environmental dominance, and technology–organization–environment co-driven type. Exploring the synergistic paths driving innovation performance from a configuration perspective enhances our understanding of the complex interactions among multiple factors in improving such performance. This provides significant theoretical and practical implications for enterprises aiming to improve their innovation performance.

The impact of multimodal information features of short sales videos on consumer engagement behavior: A multi-method approach

In the emerging business model of short video commerce, consumers can engage in short sales videos by liking, commenting, and sharing. Compared with traditional shopping contexts, consumer engagement behavior in short video commerce settings is affected quickly and simultaneously by text, audio, and visual information, but the extant literature lacks sufficient exploration of the effects of such multimodal information. Based on the multimodal theory and signaling theory, this study aims to investigate the role of multimodal information including textual sentiment score, audio spectrum and visual effects of short sales videos on consumer engagement behavior. We collect 4292 veridical short sales videos from short video platform Douyin, while based on a multi-method approach of multiple regression analysis (MRA) and fuzzy set qualitative comparative analysis (fsQCA), it is found that the multimodal information features of short sales videos contribute to the promotion of consumer engagement behavior, and the cross-modal configurational solutions to enhance engagement is not unique. This study bridges the gap in the existing literature by capturing the impact of multimodal information features on consumer engagement behaviors and their asymmetric effects, which also provides practical implications for sellers and marketers on attracting consumers to engage in short video commerce.

Longitudinal Study of Bereavement Outcomes Among Palliative Caregivers Mourners: Psychological Profiles in Prolonged Grief and Psychopathology.

Prolonged grief (PG) is a mental health condition characterized by severe distress following a loss. This study examines the roles of attachment styles, social support, stressful life events (SLEs), and pre-existing psychopathology in predicting PG and post-bereavement psychopathology among 74 caregivers of palliative patients. Using validated assessment tools, the study employed hierarchical regression and fuzzy-set qualitative comparative analysis (fsQCA) to identify predictors of prolonged grief and psychological outcomes over six months. Results showed that pre-existing psychopathology and PG risk predicted post-bereavement psychopathology, though not PG itself. Low social support and high SLEs were linked to worse outcomes, while strong social support and low stress predicted positive outcomes. These findings highlight the importance of multiple interacting factors in understanding grief and emphasize the need for interventions that enhance social support, manage stress, and address mental health conditions to reduce psychological distress in bereaved caregivers.

Unveiling the complexity of civil service effectiveness index: An asymmetric and ANN modeling

Unraveling the factors influencing civil service effectiveness becomes imperative in an era marked by escalating demands for efficient governance. This study attempts to meet this necessity by delving into the complex dynamics among core executive functions, mission support facilities, service delivery functions, and attributes, aiming to elucidate their collective impact on civil service effectiveness. Utilizing a unique methodological blend of Fuzzy-set Qualitative Comparative Analysis (fsQCA) and Artificial Neural Networks (ANN), it delves into the relationships among core executive functions, mission support facilities, service delivery functions, and attributes within the International Civil Service Effectiveness (InCiSE) Index framework. The research uses a configurational model that optimizes CSE and assesses the relative importance of various components. The study reveals significant correlations among the variables. It indicates that all CSE indicators influence but are not equally important in triggering the effectiveness of civil service administration. Key configurations, such as integrating strategic governance with mission support functions and high-level strategy with operational execution, are critical for enhancing civil service effectiveness. It underscores the importance of prioritizing core executive functions and attributes to improve civil service administration. Theoretically, the study enriches contingency theory and contributes to the civil service and administration literature by integrating a configurational approach with machine learning insights. Practically, it provides actionable insights for governance improvement, promoting the application of innovative methodologies in public service to enhance organizational environment and civil service capacities. Original in its approach, this study fills a gap in the literature by applying a hybrid fsQCA-ANN model to explore the configurational and construct ranks influencing civil service effectiveness, offering an inclusive analysis that triangulates qualitative and quantitative data. The findings indicate that civil service effectiveness is highly complex because of its process, involvement of diverse backgrounds of civil servants, critical understanding about the key pillars of good governance and service delivery mechanism. Thus, the findings advance academic understanding and provide practical strategies for policymakers and practitioners to foster better governance through targeted interventions that enhance transparency, accountability, and responsiveness in civil service organizations.

Identifying factors that influence the use of pathogen genomics in Australia and New Zealand: a protocol

IntroductionPathogen genomics, where whole genome sequencing technologies are used to produce complete genomic sequences of pathogens, is being increasingly used for infectious disease surveillance and outbreak response. Although proof-of-concept studies have highlighted the viability of using pathogen genomics in public health, few studies have investigated how end-users utilize pathogen genomics in public health. We describe a protocol for a study that aims to identify key factors that influence the use of pathogen genomics to inform public health responses against infectious diseases in Australia and New Zealand.MethodsWe will use qualitative comparative analysis (QCA), a case-oriented methodology that systematically compares and analyses multiple cases (or ‘units of analysis’), to identify multiple pathways leading to the use of pathogen genomics results in public health actions. As part of the process, we will develop a rubric to identify and define the use of pathogen genomics and individual factors affecting this process. Simultaneously, we will identify cases where pathogen genomics has been used in public health across Australia and New Zealand. Data for these cases will be collected from document review of publicly available and confidential documents and semi-structured interviews with technicians and end-users and summarized in a case report. These case reports will form the basis for scoring each case on the extent of the use of pathogen genomics data and the presence or absence of specific factors such as the ease of extracting essential information from pathogen genomics reports and perceptions toward pathogen genomics. Using the scores, cases will be analyzed using QCA techniques to identify pathways leading to the use of pathogen genomics data. These pathways will be interpreted alongside the cases to provide rich explanations of the use of pathogen genomics in public health.DiscussionThis study will improve our understanding of the key factors that facilitate or hinder the use of pathogen genomics to inform public health authorities and end-users. These findings may inform ways to enhance the use of pathogen genomics data in public health.

The effect of urban resilience on social stability under external disaster strikes--Evidence from China during COVID-19 pandemic

The robustness of civil society plays a pivotal role in shaping the aftermath of disasters. Following the COVID-19 pandemic, the question arises: why did some cities witness widespread resident protests, while others remained relatively calm? Certain theoretical studies have suggested that urban economic disruptions stemming from external disasters can significantly undermine social stability, yet these studies lack empirical validation of the underlying mechanisms. This research endeavors to explore the factors within urban resilience that influence social stability during major public events, a topic that has received scant attention in existing empirical studies.Utilizing data from the Chinese General Social Survey (2021), this study introduces an empirical causal analysis framework integrating the "entropy value method" and "fuzzy-set Qualitative Comparative Analysis (fsQCA)" to investigate the following: (1) The univariate test reveals that the consistency level of all conditions is below 0.9, indicating that no single-dimensional factor alone can enhance social stability. (2) The absence of urban economic resilience emerges as a critical conditional variable contributing to non-high levels of social stability, thereby serving as the primary driver of social instability. (3) Group analysis identifies three distinct pathways through which urban resilience impacts social stability: the "economic-ecological-resource" support path, the "economic-ecological-risk" mitigation path, and the "economic-ecological-challenge" resolution path.

Regional Development Policies in Afghanistan and Neighboring Countries: A Comparative Analysis

This essay explores the regional development policies applied in Afghanistan and its neighboring countries using a comparative qualitative analysis method. It focuses on infrastructure development, human capital investment, regional integration, and technological innovation policies. It compares development policies in China, Iran, Pakistan, and Afghanistan highlighting key projects which have fostered regional connectivity and economic growth. By comparing these policies, the essay evaluates how these initiatives have contributed to reducing regional disparities. This study aims to provide insights into how regional development policies can address Afghanistan’s socio-economic disparities and promote sustainable development. Despite notable successes, the research identifies ongoing challenges such as political instability, limited financial resources, and weak regional cooperation that impede further progress in Afghanistan. Key policy recommendations for Afghanistan include enhancing regional cooperation, investing in technological infrastructure, and developing human capital to achieve sustainable growth and stability.

Embracing the Digital Network: How Net-Entrepreneurs Acquire Online Social Capital?—A Mixed Empirical Study Based on SEM-PLS and fsQCA

Online social capital is a determinant of success for net-entrepreneurs. However, there has been limited research on how net-entrepreneurs acquire online social capital through social media. Therefore, this study aims to explore whether different digital behaviors of net-entrepreneurs lead to differences in acquiring online social capital. We conducted empirical tests using partial least square structural equation method and fuzzy-set qualitative comparative analysis (fsQCA) based on survey data from 306 Chinese agricultural net-entrepreneurs. The results revealed that digital business card (profile and state self-disclosure) significantly influences bridging online social capital (BRSC) and bonding online social capital (BOSC). Certain subcomponents of digital information and digital communication serve as significant predictors of online social capital. Furthermore, the acquisition of BRSC has three distinct configurational conditions, while BOSC has four. This study provides valuable insights for net-entrepreneurs on utilizing different digital behaviors to acquire online social capital effectively.

Dynamic assessment and pathway optimization of agricultural modernization in China under the sustainability framework: An empirical study based on dynamic QCA analysis

Accelerating agricultural modernization is vital for achieving sustainable agricultural development and ensuring food security. This paper uses the comprehensive evaluation model to measure the level of agricultural modernization in 30 provinces of China from 2012 to 2022. It inspects analyzes the spatial-temporal characteristics and regional differences through the Moran Index and Dagum Gini coefficient. Lastly, based on the configuration perspective, the dynamic qualitative comparative analysis method (QCA) is used to clarify the multiple improvement paths of China's agricultural modernization. The results indicate the following. First, China's agricultural modernization level is not high but has the potential for rapid growth. Regarding spatial distribution, the eastern region has the highest agricultural modernization level, followed by the central region, while the western region has the lowest level, showing a “high-high-low-low” clustering characteristic. Second, the overall disparity in China's agricultural modernization level is fluctuating and declining, with regional differences being the primary source of the overall disparity. The largest difference is between the eastern and western regions. Within regions, the western region has the largest internal disparity, but this disparity is gradually decreasing, whereas the gap in agricultural modernization level within the eastern region is continuously expanding. Third, the paths to improve China's agricultural modernization consist of multiple antecedent conditions. From the configuration perspective, there are four paths to enhance China's agricultural modernization level. These include the dual-strategy approach of “technology and policy,” the comprehensive tri-strategy model of “technology, market, and policy,” the synergistic enhancement model combining “technology and market,” and the multi-faceted core-driven approach.

Examining the factors affecting sustained use in smart interactive cabinet design: A comparative analysis using SEM and fsQCA

Understanding the factors that contribute to sustained user use is critical to the design and marketing of smart interactive cabinets, which have gained great popularity in recent years. This study investigates the factors that impact users' intentions to continue using smart interactive cabinets and examines how these factors influence product design and marketing strategies. However, existing research has mainly focused on the development and performance evaluation of smart interaction technologies, with less attention paid to users' continued willingness to use smart interaction cabinets and their determinants. To address this gap, 304 valid samples were randomly collected for empirical analysis and hypothesis testing, and a questionnaire survey was administered to 304 young Chinese urban Chinese users born in the 1980s and 1990s. By synthesizing and analyzing the usage patterns and influencing factors among young consumers, the study employs a combination of covariance-based structural equation modeling (CB-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to evaluate the data.The analysis highlights the significance of perceived usefulness, ease of use, and innovation in predicting users' intentions to continue using smart interactive cabinets. This study offers insights into the factors influencing continued use and provides valuable guidance for manufacturers and marketers in designing and marketing smart interactive products to enhance user experience and satisfaction.

Factors Influencing Water Resource Levels under the Water Resource Carrying Capacity Framework: A Dynamic Qualitative Comparative Analysis Based on Provincial Panel Data

Most existing evaluation frameworks for water resource carrying capacity (WRCC) neglect the interdependencies between subsystems. To fill this gap, we introduce a dynamic qualitative comparative analysis (QCA) model to evaluate WRCC and apply it to a vital economic development corridor, the Yangtze River Economic Belt (YREB). Ecological, social, and economic subsystems are defined as condition subsystems, while the water resource subsystem is defined as the outcome subsystem. The entropy weight method is used to calculate and calibrate the comprehensive score of each subsystem. By analyzing the necessity of a single condition subsystem and the sufficiency of condition subsystem configuration via a dynamic QCA, we qualitatively analyze the impact extent and pathways of the ecological, social, and economic subsystems on the water resource subsystem within the WRCC framework. The results reveal generally stable water resource levels despite regional variances, thereby pinpointing the influence pathways, including ecological–social and ecological–economic configurations. The 2011–2015 period saw poor stability, which subsequently improved until 2019 before declining in 2020 in the YREB. The middle-reach urban cluster showed the highest stability, which was less impacted by condition subsystems. These findings could enable provinces and municipalities to tailor policies and enhance subsystem levels for better water resource management.

Understanding User Experience with Smart Home Products

ABSTRACT There has been a surge in the popularity of smart home products. Existing literature primarily focuses on the initial adoption of these products, with less attention given to the post-adoption stage. This has created a research gap in understanding user experience (UX) and the key dimensions of user satisfaction and dissatisfaction. This study aims to address this gap by examining both positive and negative user experiences with smart home products. Using robotic vacuum cleaners as a case study, we analyze key UX dimensions derived from their positive and negative reviews on Amazon.com that influence user satisfaction and dissatisfaction, respectively. Dimensions contributing to satisfaction include “functionality,” “smartness,” and “enhanced capacity (mopping feature).” In contrast, “insufficient smartness,” “poor customer service,” and “connectivity problems” are critical dimensions for user dissatisfaction. Notably, “smartness” serves as a double-edged sword, potentially leading to high satisfaction but also significant dissatisfaction if poorly implemented. Our analysis also includes a comparative examination of robotic vacuums with traditional vacuums, highlighting the different UX dimensions associated with each product type. Using fuzzy-set qualitative comparative analysis (fsQCA), we further examine the configurations of these UX dimensions that contribute to satisfaction and dissatisfaction. To generalize our findings, we applied our framework to smart thermostats and proposed a UX model for smart home products. Our findings not only fill the research gap in smart home literature but also offer valuable insights for practitioners in designing smart home products and developing marketing strategies. Our research method can be applied to understand user experience with various types of smart home products and other innovative technologies.

Examining the incentive effects of athlete compensation: a combined analysis using SEM and fsQCA

In the context of competitive sports, the evaluation of compensation incentive effectiveness is key to the optimization of compensation systems for athletes. This study creates a model of the athlete compensation incentive effect from single and multinomial grouping perspectives, combining empirical research (SEM) with fuzzy-set qualitative comparative analysis (fsQCA) based on a sample of 352 validated data. The results lead to two findings. First, athletes’ direct economic compensation, direct non-economic compensation, and indirect non-economic compensation have a significant positive effect on the incentive effect of compensation. Second, that the incentive effect of high compensation has two configurations, namely “economic value” and “economic environmental value.” It seems that the effective combination of compensation factors can enhance the motivation effect in a “different way.”

Complex factors combinations driving tea growers to adopt ecological agricultural practices in tea gardens

IntroductionThe implementation of ecological agriculture practices in Chinese tea gardens plays a vital role in mitigating N2O emissions and addressing environmental degradation. Nevertheless, a dearth of discourse exists regarding the intricacies surrounding farmers' adoption of tea garden ecological agriculture practices (TGEAP), particularly the complex interplay between adoption factors and outcomes.MethodsUsing data of 310 farmers, this study employed complexity theories and Stimulus-Organism-Response theories, and integrated Partial Least Squares Structural Equation Modeling and fuzzy-set Qualitative Comparative Analysis to explore the complex relationships between farmer characteristics, internal and external factors, and adoption of farmer.ResultsThe results show three influential paths in the Stimulus-Organism-Response model, and environmental protection attitude (EPA) and production expectation (PE) act as intermediaries. Notably, EPA exhibits a masking effect in one pathway. These paths linked closely to three farmer characteristics. Beyond the Stimulus-Organism-Response model, nine combinations lead to farmers' adoption, and four to non-adoption.DiscussionWe discover scenarios where opposing environmental states or age lead to adoption, explaining the masking effect. These combinations highlight how a favorable environment influences both adoption and non-adoption. We also discuss other combinations that lead to adoption or non-adoption. The study suggests that governments employ targeted incentives to facilitate tea farmers' transition in agriculture.