Fuzzy-set Qualitative Comparative Analysis Research Articles

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.

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.

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.

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.

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.

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.

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.

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.

Identifying the antecedents for the green transformation of resource-exhausted cities in China

To address the issue of green transformation in resource-exhausted cities, this study employs the Policy Modeling Consistency (PMC) index model to carry out a comprehensive analysis of the effectiveness of support policies execution at both central and local levels, covering 16 policies at the different administrative levels. Meanwhile, utilizing the fuzzy-set Qualitative Comparative Analysis (fsQCA) method, the study investigates the interaction mechanisms and effects of various internal and external factors in the context of policy coordination, from the perspective of green transformation condition configurations. The findings reveal that the overall effect of supporting policies for resource-exhausted cities in China is generally commendable. Moreover, there is a notable characteristic that “the lower the administrative level, the higher the quality of the support policies”. Notably, organizational, technological, environmental, and policy conditions alone cannot solely facilitate the green transition of resource-exhausted cities. Instead, it is the harmonious configuration of these antecedents that drives successful green transformation. Additionally, the configuration of antecedent conditions for green transformation exhibits the heterogeneity of different types. Specifically, the eastern region primarily relies on technological innovation and production process improvement, while the central region focuses on both production process improvement and support policy combinations. By contrast, the western region primarily emphasizes support policy combinations and the fostering of environmental conditions. Furthermore, the green transformation of resource-exhausted cities with coal and oil types mainly depends on the combination of policy support and technological innovation. Metal, forestry, and other types of resource-exhausted cities rely on the upgrading and advancement of industrial structures. In the grouped analysis of administrative level, innovation capability, and distance to the provincial capital city, cities with higher administrative levels, higher innovation capabilities, and closer proximity to the provincial capital city are more likely to achieve green transformation. Thereby, this study emphasizes the critical role of support policies and the identification of effective pathways in promoting the green transformation of resource-exhausted cities.

Organizational purpose and employee motivation: an fsQCA analysis

PurposeOrganizational Purpose (OP) has become increasingly important in the organizational context. This research focuses on how OP can contribute to employee motivation, using personal and institutional OP factors and considering the importance of employee motivation toward organizational success.Design/methodology/approachTo conduct the research, we selected a branch of a leading multinational company in the chemical sector. Based on data collected through a questionnaire sent out to employees and using fuzzy-set Qualitative Comparative Analysis (fsQCA), we identified combinations of individual and institutional OP factors leading to high (or low) employee motivation.FindingsThe results reveal that individual and institutional OP factors synergistically promote high employee motivation. The employees' contribution to the OP and the integrity of the organization’s leadership are two key motivating factors.Practical implicationsOrganizations struggle to develop sustainable competitive advantages in an ever-competitive environment. Focusing on the “why” instead of the “how” may help organizations differentiate and achieve higher employee motivation. This research clarifies how to turn purpose into an asset to improve employee motivation.Originality/valueThe conclusions highlight the need to share the OP through leadership actions and the importance of helping workers recognize the OP and its values, integrate them into their actions and feel how they contribute to its achievement.

How does brand authenticity influence brand loyalty? Exploring the roles of brand attachment and brand trust

PurposeThe study aims to delve into the interactive relationships among brand authenticity, brand attachment, brand trust and brand loyalty using the ERC authenticity framework, exploring the potential mechanisms and different configurations affecting brand loyalty through brand authenticity.Design/methodology/approachAbout 446 valid samples were collected through an online survey of Chinese consumers of international sports brands. Structural equation modeling (SEM) and fuzzy set qualitative comparative analysis (fsQCA) were employed to test the research hypotheses.FindingsSEM results indicate significant positive correlations among brand true-to-ideal authenticity, true-to-fact authenticity and true-to-self authenticity. All dimensions of brand authenticity exert notable positive impacts on brand attachment, brand trust and brand loyalty. Brand true-to-ideal authenticity, true-to-fact authenticity and true-to-self authenticity not only directly influence consumer brand loyalty but also indirectly affect it through brand attachment and brand trust; fsQCA results reveal five heterogeneous configurations to predict brand loyalty.Originality/valueThis study not only uses SEM to validate the structural relationships among the three dimensions of brand authenticity and their linear relationships with brand attachment, brand trust and brand loyalty but also uses fsQCA to identify nonlinear relationships between concepts. It extends complexity theory to the research field of brand authenticity–brand loyalty. Furthermore, based on the research results, this study provides management suggestions for brand managers and marketers.

Exploring the dynamics of firm growth: the interplay of decision-making logic

Purpose This paper investigates how various emergent theoretical perspectives in entrepreneurship research, representing diverse decision-making logics, influence firm growth and evolution. It explores the interaction among decision-making logics, including experimentation, affordable loss, flexibility and pre-commitment as components of effectuation, alongside causation and bricolage and their synergistic effects on firm growth. Design/methodology/approach This study uses a multi-phase, discovery-oriented approach. Initially, insights from existing literature on decision-making logic were combined with in-depth interviews with 10 Iranian entrepreneurs within the food sector. This phase used alternative template research to evaluate the principles of effectuation, causation and bricolage within case study data depicting firm growth. Subsequently, a self-administered survey was developed based on these insights and distributed to 205 entrepreneurs in Iran. The survey data was analysed using fuzzy-set qualitative comparative analysis (fsQCA) to identify key factors and pathways influencing firm growth. Findings Using a discovery-oriented approach, this study formulates a comprehensive framework detailing decision-making logics that influence firm growth. Through fsQCA, 12 distinct paths are identified, highlighting the complex interplay of causation, effectuation and bricolage in high-growth firms within the food sector. Research limitations/implications This study has limitations. FsQCA identifies only logically sufficient combinations, suggesting potential for exploring alternative pathways in future research. Given COVID-19’s impact on the food sector, examining decision-making logic across diverse contexts and industries is advisable. Additionally, exploring how bricolage, causation and effectuation affect outcomes like new product development and innovation is essential in a growth-focused context. It is also important to consider environmental and organizational factors influencing growth. Originality/value This paper pioneers the examination of emerging theoretical paradigms in entrepreneurship and their impact on firm growth. It identifies critical configurations of causation, effectuation and bricolage, providing actionable insights for navigating dynamic business environments.

Relational antecedents of sharing and not sharing knowledge: a configurational approach

PurposeKnowledge sharing within organizations has significant benefits for group and organizational performance. This study aims to identify the combinations of individual and relational factors that influence high- and low-intensity knowledge sharing among workers using the ability-motivation-opportunities (AMO) framework.Design/methodology/approachThis research adopts a qualitative, set-theoretic approach, using fuzzy set qualitative comparative analysis (fsQCA) to analyse data collected from knowledge workers in an international corporation.FindingsOur findings show that knowledge sharing is fundamentally relational, meaning that the quality and history of interaction with co-workers affect the intensity of knowledge-sharing behaviour. All AMO dimensions prove important for sharing, although some of them can substitute one another. However, if there is a lack of ability and opportunity, employees will not share knowledge even if they are motivated by reciprocity.Practical implicationsThe results offer human resources and project management practice alternative combinations of individual and relational factors that can be used to streamline knowledge sharing, emphasizing the need to invest in building relationships among co-workers.Originality/valueThis study contributes to the literature by identifying configurations of core and peripheral conditions pertaining to abilities, motivation and opportunities that can facilitate or constrain knowledge-giving.

Stimulating tourists’ senses for sustainable destination development: Combining embodied cognition theory and the S-O-R model

Tourists’ environmentally responsible behavior (ERB) is crucial for the sustainable development of destinations, and the external environment can alter individuals’ cognition and behavior through sensory perception. To investigate the impact of the natural environment on tourists’ ERB, a conceptual model was developed and validated from a sensory perspective by integrating the embodied cognition theory and the stimulus-organism-response model. The results of structure equation modeling indicated that, with the exception of auditory perception, tourists’ perceptions through each sense influenced ERB to varying degrees, mediated by memorable tourism experiences (MTEs) and environmental awareness. Additionally, the fuzzy-set qualitative comparative analysis method was employed to identify five distinct configurations associated with high ERB. Notably, MTEs and environmental awareness, driven by sensory perceptions, emerged as critical factors. While all senses played a role, none alone could singularly determine high ERB. The findings reveal the mechanism through which sensory perception influences tourists’ ERB and offer practical insights for destinations to integrate tourism resources by aligning with tourists’ sensory experiences to promote sustainable tourism.

Thriving through innovation: Boosting green tech performance in China's new energy sector

In response to the challenges of sustainable development, green technological innovation (GTI) is considered as a key driver of high-quality growth. However, current research often lacks a comprehensive assessment of GTI's multidimensional performance and rarely explores improvement pathways from a structural perspective. This study evaluates the GTI performance of China's new energy sector using data from 62 listed companies between 2015 and 2021, employing a Back Propagation (BP) neural network model optimized by a genetic algorithm. Additionally, it explores performance enhancement paths through fuzzy set Qualitative Comparative Analysis (fsQCA). The findings indicate that: Industrial structure and human resource levels significantly boost GTI performance in the new energy sector; Optimizing and upgrading industrial structures plays a crucial role in GTI improvement; High Research and development (R&D) investment and human capital strengthen market competitiveness, leading to higher GTI levels; The development of GTI in the new energy sector exhibited a general upward trend, with notable differences across sub-industries and regions from 2015 to 2021. Based on these results, this study recommends differentiated industry support, targeted regional policies, and enhanced talent cultivation to improve GTI performance in China's emerging energy industry.