Qualitative Comparative Analysis Method Research Articles

Enhance health evidence quality in classification tasks: A triangulation approach utilizing case-based reasoning and process features.

Machine learning (ML) has enabled healthcare discoveries by facilitating efficient modeling, such as for cancer screening. Unlike clinical trials, real-world data used in ML are often gathered for multiple purposes, leading to bias and missing information for a specific classification task. This challenge is especially pronounced in healthcare because of stringent ethical considerations and resource constraints.This study proposed an integrated approach to enhance the quality of health evidence from a classification task for predicting Medicare's Diagnosis-Related Groups of ischemic heart disease (IHD) patients. Eligible participants were identified from the Medical Information Mart for Intensive Care IV (MIMIC IV), a publicly available hospital database. Six ML models were selected for model triangulation. Sequential triangulation was employed via Local Process Mining (LPM) and Qualitative Comparative Analysis (QCA). A total of 1545 IHD hospitalizations from 916 patients were identified from the MIMIC IV. Eight health process features were identified through LPM aligned with clinical knowledge. The correlation coefficients for process features, ranging from 0.24 to 0.42, are higher than those for non-process features ranged from 0.02 to 0.36. A total of 56 unique combinations were identified from the QCA, with 28 configurations having raw coverage lower than 1.0%. The overall model performance (i.e. weighted F1 and area under the curve scores) increased after adopting this integrated approach. The proportion of cases misclassified by any of the six models decreased by 47% after incorporating process features (from 5.29% to 2.91%) and further decreased to 0.0% after applying the QCA solutions. The integrated approach demonstrates its ability to enhance quality of a classification task through its clinical relevance, improved model performance, and reduced case-level error rates. However, more scalable QCA methods are needed for larger datasets. Developing health process feature engineering for broader applications can be a future direction.

Configuration Paths for High-Quality Development of Listed Companies Based on the TOE Framework: Evidence from China’s High-Tech Enterprises

In the context of dual-carbon goals, high-quality development has become an inevitable trend for technology enterprises. This study employs a dynamic Qualitative Comparative Analysis (QCA) method, based on the technology, organization, and environment (TOE) framework theory, and a configurational analysis perspective. Using panel data from Chinese listed high- and new-technology enterprises from 2013 to 2022 as the research sample, this study explores the combinatorial paths that drive high-quality development. The research findings are as follows: (1) The antecedent factors for high-quality development exhibit “multiple concurrent” characteristics, and a single condition does not constitute a necessary condition. (2) Based on the three driving paths for high-quality development, three models can be summarized under the synergistic effects of different antecedent conditions: “multi-factor influence type”, “green-innovation-led type”, and “digital-technology-driven type”. Regardless of the path, R&D investment and enterprise scale are indispensable driving factors. (3) Under specific objective endowment conditions, continuous digital transformation by enterprises can alleviate the challenges caused by market competition deficiencies. When enterprise executives possess a high level of green cognition, they can compensate for inadequate environmental regulations. Therefore, enterprises need to enhance scale and R&D investment, based on existing endowments, and shift from a single-factor influence concept to a comprehensive selection approach.

Measuring and Analysing the Impact Factors of China's Tourism Economic Resilience in the Context of a Major Shock

ABSTRACTMeasuring and exploring the tourism economic resilience and the impact of tourism shocks allows the depiction of patterns that may assist in the prediction of economic trends. The study utilises official statistics from data such as the China Statistical Yearbook from 31 Chinese provinces between 2020 and 2022. Results suggest that tourism economic resilience is generally low, and demonstrates a polarised phenomenon, with a pyramid structure showing a gradual increase in the number of provinces with high to low tourism economic resilience. From a geographical perspective, tourism economic resilience tends to exhibit a decreasing trend from east to west, with the ‘low resilience effect in the central region’ moving towards the western regions. Insufficient investment in tourism spending power and marketing were obstacles for tourism economic resilience within the obstacle model. A fuzzy‐set qualitative comparative analysis method derived four types of paths affecting tourism economic resilience: ‘infrastructure‐guaranteed’, ‘talent‐employment‐encouraging’, ‘innovation‐driven development’ and ‘market‐opening and interactive’. This study expands the application of niche theory in the field of socio‐economic resilience and constructs a new theoretical framework of resilience stratification, barrier model and path analysis. The research results provide important references for the government to optimise tourism economic policies, enterprises to improve market adaptability and regional coordinated development.

Research on the multi-factor driving paths of Chinese science-technology talents’ career calling: an ability-motivation-opportunity perspective

ABSTRACT Science-technology talents career calling is a vital driving force for technological progress and innovation. Enhancing the career calling among such professionals is crucial for building an innovative nation. Grounded in the AMO theory, this study uses the fuzzy-set Qualitative Comparative Analysis (fsQCA) method to investigate the interactive effects of career competence, role identity, challenge demand, responsible leadership, and collectivism climate on the driving mechanisms of career calling, based on a survey of 231 science & technology talents. The findings are as follows: Five configurations lead to a high career calling among Chinese science & technology talents, which can be summarized into three categories: ‘Responsible Leadership – Cognitive Sublimation’, ‘Competence Support – Challenge Stimulation – Team Collaboration’, and ‘Role Anchoring – Challenge Driven’. Two configurations result in a low career calling, summarized as ‘Insufficient Competence – Role Confusion – Lack of Responsibility’. Based on the Chinese context, this study deepens the understanding of the complex mechanisms underlying Science-technology talents’ career calling and broadens the perspective of career calling research. This study provides practical insights for optimizing the talent cultivation system and enhancing technological innovation capacity.

Business Innovation and Internationalisation in Female-Owned Businesses: A Fuzzy-set QCA Approach

Abstract Female entrepreneurship is increasingly important to create new jobs and contribute to countries’ social and economic growth. This paper aims to examine how innovation and internationalisation interact from a female entrepreneurship perspective. Our research was based on the fuzzy-set qualitative comparative analysis (fsQCA) method as a means of exploring the causal complexity between female entrepreneurship (condition), innovation, and internationalisation (conditions and outcomes). Our results suggest that female entrepreneurship alone is neither a sufficient nor a necessary condition for the outcome (high internationalisation or innovation). Nevertheless, the results indicate that female entrepreneurship is important in achieving a high level of internationalisation. This study provides policymakers with evidence of the gains of promoting female entrepreneurship in their respective countries. Our study advances knowledge in two ways. It explores the interplay between innovation and internationalisation from the perspective of female entrepreneurship. It applies fuzzy-set methods to the three concepts simultaneously.

Analyzing Antecedent Configurations of Group Emotion Generation in Public Emergencies: A Multi-Factor Coupling Approach.

To enhance emergency management and public opinion governance, improve the accuracy of forecasting group emotional responses, and elucidate the complex pathways of multi-factor coupling in the formation of group emotions, this study constructs a theoretical framework grounded in the social combustion theory. Through web scraping and text sentiment analysis, group emotional tendencies were measured in 40 public emergency cases from the past five years. Using the fuzzy-set qualitative comparative analysis (fsQCA) method, the study explored the coupling, configuration effect, and formation pathways of factors such as "burning substance", "accelerant", and "ignition" in the emergence of group emotions. The results reveal significant differences in the generation pathways of positive versus negative group emotion. Inter-group threat as a "burning substance" is more likely to trigger negative group emotion, while "accelerant" plays a pivotal role in shaping and guiding emotional responses. Notably, the government's response speed is critical for fostering positive emotions, whereas the emergence of rumors significantly contributes to the spread of negative group emotions. Additionally, the occurrence of stimulating events markedly increases the generation of negative group emotions. This study provides an important theoretical foundation and practical insights for the management and regulation of group emotions.

Designers' interpretations in the creation of digital ephemera on social media platforms using the Qualitative Comparative Analysis (QCA) method

Technology advancements have significantly impacted the speed and efficiency of the design process, leading to changes in content production and dissemination on digital platforms. Consequently, the attention span and relevance of these messages have become ephemeral. This new scenario involves the graphic designer creating messages for digital media, especially in virtual communities. Thus, first, we seek to establish a solid and comprehensive definition of digital ephemera within the context of graphic design. The methodology consists of data analysis through semi-structured interviews conducted with graphic designers from Tijuana and San Diego via conferencing platforms. The data collected is then analyzed using the Qualitative Comparative Analysis (QCA) method. This research aims to describe and analyze the phenomenon of designing messages with a 60-second lifespan on social media platforms. Therefore, a systematic approach and categorization of concepts are explored across the interconnected domains, ensuring a comprehensive definition of digital ephemera.

Mapping the healthcare logistics and supply chain management in times of crisis

PurposeThis study aims to investigate the relationship between patient satisfaction (PS) and the parameters in healthcare and supply chain management (HLSCM).Design/methodology/approachThe structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) method have been employed to identify correlation and possible configuration of causal factors that influence PS, including lack of resilience (LS), lack of visibility (LV), cost management (CM) and integration and interoperability (II).FindingsThe results from SEM confirmed that PS is highly correlated with lack of visibility, CM and II as critical parameters. Moreover, fsQCA findings state that the configuration of high levels of both resilience and lack of visibility, as well as high levels of II, are crucial for PS.Research limitations/implicationsThe researchers also identified the configuration of factors that lead to low PS. The study’s results could assist healthcare providers in improving their supply chain operations, resulting in more effective and efficient healthcare service delivery and ultimately improving PS.Originality/valueThe fsQCA method used in the study provides a more nuanced understanding of the complex interplay between these factors. The inclusion of supply chain management characteristics as parameters in the evaluation of PS is a novel aspect of this research. Previous studies largely focused on more traditional factors such as physical care, waiting times and hospital amenities. By considering supply chain management factors, this study provides insights into an under-explored area of PS research, which has important implications for healthcare providers looking to improve their operations and PS.

How to achieve sustainable operation of transport infrastructure development: a case study of 30 transport infrastructure projects in China

Transport infrastructure projects are distinguished by their high levels of investment, lengthy construction periods, and reliance on government subsidies during operation. These factors have far-reaching impacts, not only on the sustainable operation and success of the projects themselves, but also on the orderly functioning of society and the sustainable development of the economy. As such, it is of paramount importance to thoroughly investigate the sustainable operation of transport infrastructure. This paper examines the impact of sustainable operation on transport infrastructure by analysing 30 projects in China’s transport infrastructure sector. The study employs the qualitative comparative analysis method. To achieve the aim of this paper, we identified five dimensions for assessing a project’s sustainability. These include the economic environment of the construction site, operational market demand, government support capacity, and enterprise management level. This analysis offers valuable guidance for future engineering projects. Finally, the study identified seven strategies for achieving sustainable operation of the project. The findings revealed that the economic development status, population size, and government subsidies of the construction site do not effectively promote sustainable operation of the project. Rather, they can hinder enterprises’ market competitiveness. The study’s results can assist decision-makers in determining the feasibility of implementing sustainable management practices in the new project. Examine the factors that influence the achievement of sustainable business while enhancing the operational efficiency of ongoing initiatives. This research aims to produce a valuable addition to risk assessments in sustainable operation research and the advancement of transportation infrastructure reduction.

How Does the Digital Innovation Ecosystem Enable Green Regional Development? A Dynamic QCA Study in China

The impact of digital empowerment on green innovation is increasingly evident, enabling various subjects to improve the integration of innovation elements and enhance innovation efficacy across a broader temporal and spatial scope. A comprehensive examination of the mechanisms that underlie this process is required. This paper constructs the ‘elements-subjects-environments’ research framework of digital innovation ecosystems, collecting data from 30 provinces in China from 2017 to 2021 and using green total factor productivity (GTFP) to evaluate the level of green regional development. In this study, the dynamic qualitative comparative analysis (QCA) method is employed to analyze the intricate causal mechanisms and configurations of green regional development that are driven by digital innovation ecosystems from both temporal and spatial perspectives. The results show that: (1) green regional development requires the interaction of multiple elements, subjects, and the environment, and a single condition does not constitute a necessary condition; (2) there are four pathways with different configurations for high-level green development: data elements-driven enterprise application innovation, data elements-driven enterprise-user co-creation, data elements-driven multi-collaborative innovation, and digital environment-driven university basic innovation; (3) the temporal and spatial dimensions of China’s green regional development pathways are heterogeneous: the significance of data elements in fostering green regional development is increasing; the multi-collaborative innovation configuration is facilitating the green development of the eastern and central regions, whereas the western and northeastern regions are progressing at a relatively slow pace. This study provides theoretical and practical insights to promote the integration of digital innovation and green development.

What Kind of Institutional Configuration Incentivizes Farmers’ Behavior in Ecological Value Co-Creation of Cultivated Land?

Innovating institutional incentives and promoting multiple-subject interaction and cooperation to create ecological value of cultivated land are practical requirements for the sustainable protection of cultivated land and high-quality development of agriculture and rural areas. We performed a survey questionnaire of 862 farmers in the Wuhan Metropolitan Area and used the fuzzy set qualitative comparative analysis (fsQCA) method to explore the institutional configuration effect of farmers’ behavior in the ecological value co-creation of cultivated land (FBEVCCL). The institutional configuration characteristics of the ecological value co-creation of cultivated land was analyzed, and we propose institutional optimization suggestions for the ecological value co-creation of cultivated land. The research results demonstrated the following: (1) A single institutional element does not constitute a necessary condition for the FBEVCCL, and it is necessary to analyze the institutional configuration effect. (2) Four institutional configurations lead to high-level FBEVCCL. Both formal and informal configurations have important impacts on the FBEVCCL, but the guidance, subsidies, and constraints of formal institutions are often the core driving factors, complemented by the shaping of farmers’ values to jointly enhance the FBEVCCL. The formal institutions of publicity and guidance, rewards and subsidies, and disciplinary constraints can to some extent replace each other. (3) The three institutional configurations lead to low-level FBEVCCL, and the lack of informal and formal institutions for incentives and punishments is the main reason for low-level FBEVCCL. In the future, we should further standardize the reward and punishment mechanism, enhance farmers’ green production skills, and sustainably enhance the behavior of farmers in the ecological value co-creation of cultivated land.

An FsQCA and NCA Analysis on the Drivers and Comprehensive Impact Analysis of the Implementation of Digital Twins

The adoption of digital technology is one of the key processes in the digital transformation of China's construction industry. As a representative digital technology in the digital transformation process of Construction 4.0, digital twin technology has attracted widespread attention in various fields, and its practical application is also growing rapidly. However, its implementation in the construction industry (CI) still faces major challenges. Although previous studies have made significant progress in understanding the drivers and barriers to the implementation of digital twins (DTs) in the CI, these studies have neglected to explore the comprehensive impact of various factors, and the configuration relationship between them remains unclear. This study uses a quantitative method to conduct a questionnaire survey to obtain 33 case sample data. Necessary condition analysis (NCA) and fuzzy set qualitative comparative analysis (FsQCA) methods are used for antecedent configuration analysis. The results show that: (1) The successful deployment of DTs in the CI does not depend on any single determinant, but is the adaptive result of the synergistic effect of multiple antecedent variables; (2) Six critical factors affecting the implementation of DTs in China's CI are identified, which can be summarized into four different causal paths or configurations, which are conducive to the implementation of DTs in China's CI. This study further explores and clarifies the comprehensive impact of antecedent variables on the implementation of DTs in China's CI provides a reference for the practice of digital transformation in the CI.

Driving Product Innovative Performance Through Network Connections: A Study Based on the fsQCA Approach

To explore how firms’ network connections improve product innovative performance (PIP) for sustainable development, this study takes 230 firms involved in product innovation as the research object, and uses the fuzzy-set qualitative comparative analysis (fsQCA) method to explore how strong ties, bridging ties, technology exchange, technology transfer, and innovation resource interaction can stimulate product innovative performance. This study has found that firms have three configurations to achieve high product innovative performance and two configurations to achieve non-high product innovative performance. Only appropriately matched types of strong ties, bridging ties, technological exchange, technological transfer, and innovation resource interaction can promote product innovative performance. The findings enrich the theoretical understanding of the relationships among network connections, knowledge flow, innovation resource interaction, and product innovative performance.

TOE Configuration Analysis of Smart City Construction in China Under the Concept of Sustainable Development

The construction of smart cities is an effective path for sustainable urban development. Determining how to build smart cities and choose effective development models has attracted attention from all walks of life. Consequently, determining how to promote the development of smart cities and how to choose effective development models has also attracted attention. This paper takes 77 prefecture-level cities in China as case studies to explore the impact of technology, organization, and environment on the high-level development of smart cities. In this study, the fsQCA (fuzzy set-based qualitative comparative analysis) method was used to explore the configuration effects of three types of factors. The main findings are as follows: Firstly, no single factor among the three categories is a necessary condition for the high development level of smart cities, indicating that relying solely on technological conditions cannot build high-level smart cities. Secondly, the path of development of a smart city can be summarized into three modes: Both organizational and industrial environment type, both governance and cultural environment type, and balanced development type. Finally, among the three modes, the government’s digital governance capability and industrial environment play a crucial role in achieving a high level of development in smart cities. This article examines the development of smart cities from a systems perspective and provides useful, practical insights for the construction of smart cities.

How to accurately evaluate and effectively improve the performance of provincial green development in China? An improved integrated method

Evaluating and improving the performance of green development (GD) is essential for the government to formulate sustainable development policies. This study first analyzes the connotation and structures of GD from systemic perspective. Secondly, based on the two-stage eco-inefficiency (TE) model, non-cooperative theory, the correlation coefficient and standard deviation, and fuzzy set qualitative comparative analysis method (fsQCA), an improved integrated method, i.e., ITNE-fsQCA, is proposed. Thirdly, the validity and accuracy of ITNE-fsQCA are verified using the data from 30 Chinese provinces in 2020, and the results are compared with those obtained from TE and two-stage non-cooperative eco-inefficiency (TNE). Finally, the driving types and configuration pathway are discussed based on ITNE-fsQCA. The results show that: (1) compared to TE and TNE, ITNE-fsQCA helps to avoid the overestimation/underestimation of inefficiency in complex systems; (2) there are 8 configuration pathways that can effectively improve GD performance in 30 Chinese provinces in 2020, and these pathways are categorized into 4 driving types; (3) the enhancement of green technology innovation plays a crucial role in provincial sustainable development; and (4) the provincial GD inefficiencies in China are manifest various combinatorial forms. These findings provide the government with innovative ideas and methodologies for formulating sustainable development policies.

Exploring the antecedents of knowledge transfer among stakeholders in green building projects: From the configuration perspective

With the rapid development of green buildings around the world, knowledge transfer among stakeholders is of great significance in promoting the innovation and application of green building technologies. However, due to the complexity and specificity of green building projects, current studies have not fully established a comprehensive understanding of how elements from various dimensions (i.e., subject, relationship, context, and activity) collectively impact knowledge transfer among stakeholders in green building projects. Therefore, this study aims to explore the key factors that affect knowledge transfer among stakeholders in green building projects and how these factors work together to enhance the effectiveness of knowledge transfer (EKT). Firstly, the key factors influencing knowledge transfer were pinpointed: cognitive differences, connection strength, organizational climate, information technology capability, transmit willingness, receive willingness, perceived policy support, and richness of transfer channels. Then, an examination of the collected valid samples was conducted through configuration analysis utilizing the fuzzy set qualitative comparative analysis (fsQCA) method. The findings reveal five configurations, categorized as strong connection-driven, policy support-driven, and both-driven. Lastly, some combination strategies were outlined for different categories to assist green building companies in enhancing EKT. This study not only enhances the existing green building literature by developing a framework of factors that influence knowledge transfer among stakeholders, but also provides a reference for corporate executives to choose the best strategies to enhance EKT in green building projects.

Research on the Driving Paths and Evolution of Digital Innovation in Intelligent Connected Vehicle Enterprises—A Configurational Analysis Based on Dynamic fsQCA

Intelligent connected vehicles (ICVs) are increasingly emerging as a pivotal driving force for promoting sustainable development in global transportation due to their outstanding performance in mitigating carbon emissions, alleviating traffic congestion, and enhancing travel efficiency. Enhancing the digital innovation capability of ICV enterprises is an imperative path to explore high-quality industry development and effectively respond to the latest technological revolution and industrial transformation. Based on the panel data from 20 listed companies in the ICV industry in China from 2019 to 2022, this study utilizes a fixed-base index and fuzzy set qualitative comparative analysis (fsQCA) method within the framework of technology–organization–environment (TOE) theory to investigate the influencing factors, driving paths, and temporal trends of digital innovation in ICV enterprises in China. The results show the following: (1) No single factor can constitute a sufficient condition for achieving a high level of digital innovation. (2) The level of digital innovation of ICV enterprises in China showed a fluctuating growth trend during 2019–2022. Digital infrastructure and market competition are the two critical factors for digital innovation, while technology and organizational conditions have become bottlenecks. (3) There are five driving paths of digital innovation in ICV enterprises in China, including the Entrepreneurial Navigation + Technology Accumulation Driving Path, R&D Advantage + Environment Driving Path, Application Oriented + Environment Driving Path, Knowledge Absorption Driving Path, and Total Factor Driving Path. (4) From 2019 to 2022, the digital innovation of ICV enterprises in China underwent two stages of evolution, namely “Knowledge Absorption + Government Promotion” to “Technology Embedded + Market Driven”. (5) A substitutive relationship exists between digital resource acquisition capabilities and digital infrastructure, which promotes digital innovation through different paths leading to the same goal. The findings of this study have important theoretical and practical implications for ICV enterprises in making scientific and reasonable digital innovation decisions, thereby fostering the sustainable development of the automotive industry.

Big data analysis of policy coordination paths based on latent dirichlet allocation model and fuzzy-set qualitative comparative analysis method

Big data analysis of policy coordination paths based on latent dirichlet allocation model and fuzzy-set qualitative comparative analysis method

A Study on the Antecedent Grouping Pattern of ESG Decoupling in New Energy Vehicle Manufacturing Companies

This study explores the decoupling phenomenon of listed companies in the new energy vehicle manufacturing category in terms of ESG (environmental, social, and corporate governance) by using fuzzy set qualitative comparative analysis (fsQCA) and necessity condition analysis (NCA) methods, and identifies four different groupings. These groupings reveal the complexity and diversity of firms' ESG performance and disclosure, including high gearing and low environmental commitment, high management compensation and low social responsibility, high media attention and selective disclosure, and high market competition and inadequate governance. The results of the study show that financial pressure, management incentives, media attention and market competition all significantly affect firms' ESG behavior. Based on this, policy and management recommendations are proposed, such as strengthening the regulation of ESG disclosure, incorporating ESG performance assessment in executive incentives, and balancing short-term financial goals with long-term sustainable development. Although this study reveals the complexity of ESG decoupling in new energy automobile manufacturing firms, the limitations of data source, sample scope and methodology still exist. Future research should expand the sample scope, conduct dynamic analysis, and synthesize multiple methods to deepen the understanding of corporate ESG decoupling behavior and provide scientific guidance for management and policy making.

Pathways and enhanced evaluation system for green low-carbon development across diverse Chinese regions.

Rapid economic growth in China has led to significant resource and environmental challenges, particularly in less economically developed regions. This study aims to identify effective strategies for achieving green, low-carbon development in these regions during the economic transition. We employed the Fuzzy-Set Qualitative Comparative Analysis (fsQCA) method to scrutinize the impact of economic, demographic, industrial, and technological factors on low-carbon development across a selection of Chinese provinces, including Qinghai, Hunan, Beijing, Shanghai, Tianjin, Hainan, and Chongqing. This approach facilitates a nuanced exploration of the multifaceted determinants of low-carbon progress within the regional contexts of China. The study identified three distinct paths to low-carbon development, each with unique prioritization characteristics. These paths are the traditional early low-carbon path, the semi-modernized mid-carbon path, and the post-modernized low-carbon path. Each path offers tailored strategies for less developed regions to enhance their environmental innovation capacity and global competitiveness. This research contributes a novel perspective for regional sustainable development in China by offering tailored low-carbon development strategies for less developed regions. The findings suggest that region-specific strategies, aligned with developmental stages and characteristics, are essential for ensuring balanced economic, social, and environmental development.