Search Results (39)

Individual willingness to pay (WTP) for green energy plays a vital role in mitigating climate change. Based on social cognitive theory (SCT), which emphasizes the dynamic interaction among individual cognition, behavior and the environment, this study develops a theoretical model to identify factors influencing green energy WTP. The study is based on 585 valid questionnaire responses from urban areas in China and uses Structural Equation Modeling (SEM) to reveal the linear causal path. Meanwhile, fuzzy-set Qualitative Comparative Analysis (fsQCA) is utilized to identify the combined paths of multiple conditions leading to a high WTP, making up for the limitations of SEM in explaining complex mechanisms. The SEM analysis shows that social trust, social networks, and social norms have a significant positive impact on individual green energy WTP. And this influence is further transmitted through the mediating role of environmental self-efficacy and expectations of environmental outcomes. The FsQCA results identified three combined paths of social capital and environmental cognitive conditions, including the Network–Norm path, the Network–efficacy path and the Network–Outcome path, all of which can achieve a high level of green energy WTP. Among them, the social networks are a core condition in every path and a key element for enhancing the high green energy WTP. This study promotes the expansion of SCT, from emphasizing the linear role of individual cognition to focusing on the configuration interaction between social structure and psychological cognition, provides empirical evidence for formulating differentiated social intervention strategies and environmental education policies, and contributes to sustainable development and the green energy transition. Full article

Against the backdrop of digital transformation, this study constructs an analytical framework for the influence mechanism of the data-driven dynamic capabilities of foreign trade SMEs from the perspective of digital intelligence immunity, aiming to clarify the complex relationships among influencing factors and multi-combination paths for capability improvement. The research employs the fuzzy AHP-DEMATEL method to quantify the complex influence relationships among factors and uses fsQCA to analyze the configuration paths of high-level data-driven dynamic capabilities. Results show that digital intelligence management and analysis, digital intelligence supervision and early warning, and digital intelligence ecosystem are key drivers of data-driven dynamic capabilities, with digital intelligence talents serving as a guarantee and digital foundation as a foundation. The study identifies the following two core paths for forming high-level capabilities: “management–talent–ecology collaboration” and “early warning–technology–mechanism enhancement.” It concludes that foreign trade SMEs should strengthen digital intelligence management and ecological construction, improve early warning mechanisms, and adopt multi-pronged approaches to build data-driven dynamic capabilities, providing a theoretical basis for their digital transformation and capability upgrading. Full article

In order to cope with the multimodal changes led by the digital era, enterprises urgently need to promote the construction of new-quality productive forces (NQPFs) through digital transformation. NQPFs take digital technology empowerment as the core driving force and emphasize the dynamic matching and synergy between the new-quality elements (digital infrastructure, digital talents, data resources, and diversified ecology) and the new-quality capabilities (digital dynamic capabilities) so as to unleash the innovation potentials of different production modes. Based on resource orchestration theory, this study constructs a “resource-capability-value creation” framework for digital empowerment (D-RCV) and employs fuzzy set qualitative comparative analysis (fsQCA) to examine 205 enterprise samples. Results reveal that enhanced innovation performance stems from digital empowerment at both resource and capability levels, generating three configurational paths: collaborative symbiosis, resource optimization, and data-driven approaches. These paths emerge through the interaction of resources and capabilities under different conditions. This study contributes by proposing a digital empowerment framework and exploring multiple pathway choices for new-quality productivity development. The findings provide theoretical insights for enterprise innovation research and practical guidance for innovation management strategies. Full article

In a business environment with rapidly growing digital technologies, knowledge management (KM) capability is an indispensable source for enterprise innovation activities. Nevertheless, there is limited understanding of the specific KM capability that leads to sustainable business model innovation (SBMI). This study therefore aimed to investigate the internal relationship between KM capability and SBMI by leveraging dynamic capability theory. A hierarchical regression analysis (HRA) and a fuzzy set qualitative comparative analysis (fsQCA) are used to analyze a sample of 115 Chinese innovative enterprises. The results indicate that organizational structure promotes information technology by improving human capital, and that information technology then stimulates collaboration depth by expanding collaboration breadth, thereby driving SBMI. Specifically, human capital, information technology, collaboration breadth, and collaboration depth play significant chain-mediating roles in the relationship between organizational structure and SBMI. This study contributes to the literature on KM and innovation management, extends the use of low-order and high-order dynamic capabilities in DCT, and assists managers in developing SBMI effectively. Full article

Exploring the action mechanisms and enhancement pathways of the resilience of agricultural product green supply chains is conducive to strengthening the system’s risk resistance capacity and providing decision support for achieving the “dual carbon” goals. Based on theories such as dynamic capability theory and complex adaptive systems, this paper constructs a resilience framework covering the three stages of “steady-state maintenance–dynamic adjustment–continuous evolution” from both single and multiple perspectives. Combined with 768 units of multi-agent questionnaire data, it adopts Structural Equation Modeling (SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA) to analyze the influencing factors of resilience and reveal the nonlinear mechanisms of resilience formation. Secondly, by integrating configurational analysis with machine learning, it innovatively constructs a resilience level prediction model based on fsQCA-XGBoost. The research findings are as follows: (1) fsQCA identifies a total of four high-resilience pathways, verifying the core proposition of “multiple conjunctural causality” in complex adaptive system theory; (2) compared with single algorithms such as Random Forest, Decision Tree, AdaBoost, ExtraTrees, and XGBoost, the fsQCA-XGBoost prediction method proposed in this paper achieves an optimization of 66% and over 150% in recall rate and positive sample identification, respectively. It reduces false negative risk omission by 50% and improves the ability to capture high-risk samples by three times, which verifies the feasibility and applicability of the fsQCA-XGBoost prediction method in the field of resilience prediction for agricultural product green supply chains. This research provides a risk prevention and control paradigm with both theoretical explanatory power and practical operability for agricultural product green supply chains, and promotes collaborative realization of the “carbon reduction–supply stability–efficiency improvement” goals, transforming them from policy vision to operational reality. Full article

Against the backdrop of sustainable development and from a macro perspective, this paper focuses on the cultural and tourism industry, measures its sustainable development efficiency, analyzes influencing factors, and systematically explores improvement paths. Based on the theoretical perspective of sustainable development, this study has constructed an evaluation index system for measuring the sustainable development level of the cultural and tourism industry across four dimensions, as follows: cultural and tourism economic construction, cultural and tourism basic resources, social basic support, and ecological environment quality. The range entropy value was adopted to measure the sustainable development level of the cultural and tourism industry in 31 provinces of China from 2006 to 2023. The results show that the sustainable development level of China’s cultural and tourism industry is generally low, but shows an increasing trend. In terms of the annual growth rate of regional scores, the trend is as follows: North China (7.05%) > Central South (6.00%) > East China (5.97%) > Southwest (5.03%) > Northwest (4.56%) > Northeast (2.94%). This indicates considerable room for improvement in the future. Furthermore, this study used kernel density estimation to analyze the distribution dynamics and evolution trends of the sustainable development level of the cultural and tourism industry and its scores at all levels, revealing differences in development levels among provinces and regions. Finally, this study has innovatively adopted the fsQCA method to explore improvement paths for the sustainable development level of the cultural and tourism industry, and identified three implementation paths: “openness–human resources–consumption–environment-driven”, “human resources–consumption–environment-driven”, and “openness–environment-driven”. By constructing a multi-condition combination model, this study breaks through the limitations of traditional single-factor analysis and reveals multiple concurrent causal relationships in complex situations. This approach showcases the differentiated development models of each province under the interacting effects of multi-dimensional factors, and provides policymakers with a basis for precise policy implementation “tailored to local conditions and multi-dimensional collaboration”. Full article

Improving forest carbon sink efficiency (FCSE) is the key to mitigating climate change and achieving sustainable forest resource management in China. However, current research on FCSE remains predominantly focused on static perspectives and singular linear effects. Based on panel data from 30 provinces (autonomous regions and municipalities) in China from 2008 to 2022, this study integrated the super-efficiency Slack-Based Measure (SBM)-Malmquist–Luenberger (ML) model, spatial autocorrelation analysis, and dynamic fuzzy set qualitative comparative analysis (fsQCA) to reveal the spatiotemporal differentiation characteristics of FCSE and the multi-factor synergistic driving mechanism. The results showed that (1) the average value of the FCSE in China was 1.1. Technological progress (with an average technological change of 1.21) is the core growth driver, but the imbalance of technological efficiency change (EC) among regions restricts long-term sustainability. (2) The spatial distribution exhibited a U-shaped gradient pattern of “eastern—southwestern”, and the synergy effect between nature and economy is significant. (3) The dynamic fsQCA identified three sustainable improvement paths: the “precipitation–economy” collaborative type, the multi-factor co-creation type, and “precipitation–industry-driven” type; precipitation was the universal core condition. (4) Regional differences exist in path application; the eastern part depends on economic coordination, the central part is suitable for industry driving, and the western part requires multi-factor linkage. By introducing a dynamic configuration perspective, analyzing FCSE’s spatiotemporal drivers. We propose a sustainable ‘Nature–Society–Management’ interaction framework and region-specific policy strategies, offering both theoretical and practical tools for sustainable forestry policy design. Full article

Background/Objectives: Cyber intimate partner violence (CIPV) in adolescents is influenced by individual and relational factors, including psychopathic traits, antisocial and law-violating behaviors, child-to-parent violence, and dating violence. This study examines predictors of cyber aggression, cyber control perpetration, cyber victimization, and received cyber control using hierarchical regression models (HRMs) and fuzzy-set Qualitative Comparative Analysis (fsQCA). Method: A total of 207 Spanish adolescents (M = 16.18; SD = 1.52) aged 14–18 years completed measures of psychopathy (P-16), antisocial behavior (ECADA), child-to-parent violence (CTS2), and dating violence (CADRI), together with Violence in Adolescent Relationships on Social Media (e-VPA). Results: HRM showed that child-to-parent violence and experienced dating violence were common predictors across cyber aggression, cyber victimization, and received cyber control. Cyber control perpetration was mainly influenced by psychopathy and perpetrated dating violence. fsQCA revealed multiple pathways leading to high levels of CIPV, combining psychopathy, antisocial behaviors, and family and partner violence. However, cyber aggression perpetration could not be analyzed due to insufficient variability. Conclusions: The findings suggest that CIPV might stem from complex interactions between individual traits and offline relational violence. Prevention efforts should address both family dynamics and dating violence to mitigate cyber aggression and victimization in adolescent relationships. Full article

As an emerging marketing tool, virtual influencers (VIs) have attracted increasing scholarly attention. However, existing research predominantly adopts linear causal analysis models, which fail to capture the complex, nonlinear interaction between consumers and VIs. Grounded in the 5W communication model and utilizing a fuzzy-set qualitative comparative analysis (fsQCA), this study systematically explores how different configurational paths influence consumer engagement, drawing on empirical data from 205 participants. The findings reveal that (1) the synergy of entertainment, information, and credibility is a core prerequisite for achieving high engagement; (2) two equivalent paths—namely, the technology-driven path (media richness + content synergy) and the cognition-driven path (technology acceptance + content synergy)—lead to high engagement, both with a solution consistency of 0.98; and (3) the joint absence of content, media richness, and audience cognition results in low engagement. Theoretically, this study challenges traditional linear approaches by validating causal asymmetry and revealing configurational interdependencies among communication elements. It also extends the Media Richness Theory (MRT) and the Technology Acceptance Model (TAM) into the context of virtual influencer (VI) marketing. Practically, the proposed dynamic configuration model offers marketers a novel framework for optimizing VI campaigns through resource-adaptive strategies. Full article

As a key factor driving economic growth, the connotation and extension of new quality productivity have been expanding. This has a profound impact on the path of total factor productivity improvement. Therefore, this paper combines the qualitative comparative analysis (QCA), necessary conditions analysis (NCA), and data envelopment analysis (DEA) methods and adopts a group study to analyze the driving mechanism of total factor productivity (TFP) enhancement in 30 provinces in China from the perspective of new quality productivity. The study finds that (1) a single new quality productivity component does not constitute a necessary condition for TFP; (2) three new types of ecological factors can drive regions to realize high total factor productivity, including innovation-driven, green-led, and service-embedded factors, reflecting the complex mechanism of high-quality development in China’s provinces; and (3) the high factor productivities of the eastern, central, and western regions are clearly differentiated, with different grouping paths, which are manifested in the ”leading” development of the east, the “following” development of the center, and the “accompanying” development of the west, revealing the regional “leading” development and the “accompanying” development and showing the diversified path of regional high-quality development.This study not only deepens our understanding of the relationship between new quality productivity and total factor productivity in theory, but also provides scientific basis and decision support for different regions to formulate differentiated high-quality development strategies empirically. Full article

The “Ten-Year Fishing Ban” policy in the Yangtze River Basin aims to restore ecological diversity but poses significant challenges for the fishermen in their transition to alternative livelihoods. This study focuses on fishermen who worked on Poyang Lake, using the sustainable livelihood framework and the theory of planned behavior, combined with fuzzy-set qualitative comparative analysis (fsQCA) and descriptive statistics, to explore the interaction effects of livelihood capital, ecological cognition, and compensation policies on fishermen’s behavioral responses. Key findings include the following: natural, financial, and psychological capital are core drivers of enhanced ecological cognition, with combined effects significantly increasing sensitivity to policy and environmental changes through pathways like “ecological transition drive”, “knowledge adaptation support”, and “multi-cooperation synergy”. Attitude, perceived behavioral control, and compensation policy transparency are crucial for positive responses, while social norms and policy fairness can compensate for individual motivation deficits, forming pathways like “ecological drive-policy recognition” and “norm drive-social support”. Current issues such as low compensation standards, insufficient retraining, and gender differences limit policy effectiveness. Optimizing measures like differentiated fishing permits, dynamic compensation mechanisms, and cultural empowerment are needed to balance ecological protection and social equity. The study suggests enhancing financial and psychological capital, improving vocational training systems, and increasing policy transparency to provide theoretical and practical references for sustainable global fisheries management. Full article

Agricultural production faces the dual challenge of increasing output while ensuring efficient resource utilization and environmental sustainability amid escalating global climate change and relentless increases in human demand. This study used provincial panel data from China from 2001 to 2022 to address these challenges. It systematically evaluated the dynamic evolution of agricultural green total factor productivity (AGTFP) by selecting “resources” and “energy” as core input factors and adopting a dual-output approach focused on “economic” and “low-carbon” outcomes. This study thoroughly analyzed the synergistic mechanisms of factors such as natural endowment, agricultural technology, economic development, and environmental regulation, exploring their impact on AGTFP enhancement through the innovative application of the dynamic fuzzy-set qualitative comparative analysis (fsQCA) method. There was a significant upward trend in AGTFP across China, indicating notable progress in green agricultural development. Additionally, three pathways promoting AGTFP improvement were identified: resource–economy-driven, technology–policy-guided, and multifactor-synergy. Simultaneously, two modes constraining AGTFP enhancement were uncovered: economy–policy suppression and human capital–economy suppression, highlighting the pivotal role of regional economic development and the conditionality of converting natural resource advantages. Moreover, the contributions of these pathways to AGTFP exhibited notable temporal dynamics. Major economic events, such as the 2008 financial crisis and policy shifts, including the 2012 “Ecological Civilization” strategy, significantly altered the effectiveness of existing configurations. Our analysis of regional heterogeneity revealed distinct geographical patterns, with the resource–economy-driven model predominantly observed in central regions and the technology–policy-guided and multi-factor-synergy models more prevalent in central and eastern regions. These findings highlight the importance of formulating differentiated policies tailored to the specific needs and stages of development in different regions. Specifically, enhancing the synergy between resource management and economic development, optimizing technology–policy integration, and promoting coordinated multisectoral development are critical to fostering sustainable agricultural practices. This research provides crucial empirical evidence for shaping targeted policies that can drive green agricultural development across diverse regional contexts. Full article

In the context of intensifying global competition, productive entrepreneurship plays an important role in industrial upgrading and sustainable economic development. This study explores how the institutional environment affects productive entrepreneurship through different allocation paths. By integrating multiple institutional logics and using PD-QCA (Panel Data fsQCA) methods, we examined data from 76 countries for the period 2012–2022. The results show that institutional complexity provides entrepreneurs with diversified opportunities and resources, but also brings decision-making challenges due to the conflict of institutional factors. We identified three main models: (1) Government-Market Collaborative Model: driven by government support and property rights protection. (2) Market-Led Model: financial support is crucial. (3) Three-Wheel Drive Model: combines property rights protection, market opening, and social norms that promote entrepreneurship. This study contributes to the literature by revealing the multidimensional effects of institutional complexity and provides practical implications for policymakers seeking to promote high-quality entrepreneurial activity. Limitations include the static nature of the data and the need to further explore dynamic institutional interactions over time. Full article

High-quality development has become one of the important goals pursued by Chinese enterprises at present, and innovation is an important channel to realize high-quality development. Effective collaboration stands out as a pivotal element for the success of new product development (NPD). There are a variety of control mechanisms applied to mitigate uncertainty and foster cooperation. Despite the importance of these controls, the interplay between formal and informal management controls in NPD has been underexplored in prior research. The goal of this study is to validate the relationship between formal and informal control in a new product development scenario, responding to the debate about whether there is a substitution effect or a complementary effect between the two. This study addresses this gap by initially employing ordinary least squares (OLS) regression analysis to examine the role of each management control. Subsequently, fuzzy set qualitative comparative analysis (fsQCA) is employed to identify strategies for achieving high NPD performance in Chinese manufacturing enterprises. The results from the OLS analysis demonstrate that all forms of management control, especially trust, are effective in the improvement of NPD performance, while the results from fsQCA confirm that there is a complementary effect between formal and informal control, suggesting that informal control cannot function well without formal control. This research illuminates the synergistic dynamics of management controls within an open innovation context and emphasizes the importance of integrating both formal and informal controls to optimize NPD performance. Full article

Digitalization offers an opportunity to narrow the economic gap between urban and rural areas; however, there are fragmented and competing explanations regarding its impact mechanisms. Responding to calls for research on the complex effects of digitalization, this paper, based on a contextual perspective and configurational theory, analyzes the impact of digitalization conditions embedded in contexts on the urban–rural income gap. The study, based on a sample of 274 prefecture-level administrative regions in China from 2014 to 2021, employs a Panel Fuzzy-Set Qualitative Comparative Analysis (Panel fsQCA) and Necessary Condition Analysis (NCA). The combined application of necessity analysis and sufficiency analysis reveals that certain digitalization conditions—such as digital infrastructure, digital industry, and digital finance—have a universal influence on the urban–rural income gap. Importantly, the sufficiency analysis demonstrates that the impact mechanisms of digitalization conditions exhibit configurational effects, varying with changes in contextual and conditional combinations. The models that significantly narrow the urban–rural income gap include (1) the “infrastructure–finance–governance” model, (2) the comprehensive digital transformation model, (3) the “technology–infrastructure–industry” model, and (4) the digital infrastructure transformation model. Among these, the comprehensive digital transformation model is the most universally effective. These configurations reflect the logic of completeness and substitutability and exhibit specific dynamic evolutionary trends and spatial distribution characteristics. These findings provide contextual and adaptable empirical insights for economies, including China, to implement targeted digital transformation strategies that effectively narrow the urban–rural income gap. For instance, economies can focus on developing comprehensive digital transformation in prosperous and open regions to reduce income gap. Full article