Search Results (34)

Drug markets display varying levels of violence across urban contexts, and understanding the drivers behind these differences is essential for designing effective interventions. (1) Background: This study investigates why some cocaine markets are more violent than others, focusing on four cities: Ciudad Juárez, Pereira, Frankfurt, and Madrid. (2) Methods: Using fuzzy-set Qualitative Comparative Analysis (fsQCA), we examined complex configurations of institutional, social, and market-related factors. Data were collected through 56 semi-structured interviews and secondary sources from 2015 to 2020. (3) Results: The findings reveal that violence arises from specific combinations of factors rather than isolated variables. In Latin American cities, violence is associated with weak institutional control, dense criminal networks, high social vulnerability, and fragmented market structures. In contrast, European cities show lower levels of violence due to stronger institutions, effective law enforcement, and well-regulated markets. (4) Conclusions: Addressing violence in cocaine markets requires context-specific strategies that take into account institutional capacity, market dynamics, and broader social conditions. These findings challenge simplistic views of drug market violence and emphasize the need for tailored interventions to mitigate violence effectively. Full article

Digital transformation enhances the processes and efficiency of enterprise green innovation through technological empowerment, while the ESG framework guides the direction and value of such innovation via institutional norms. However, existing studies often examine digital transformation and ESG in isolation, resulting in insufficient exploration of their synergistic effects. Based on data from manufacturing high-tech enterprises, this study employs necessary condition analysis (NCA) and fuzzy-set qualitative comparative analysis (FsQCA) to systematically examine the synergistic effects of digital transformation and ESG on enterprise green innovation. The key findings are as follows: (1) While no single factor constitutes a necessary condition for high green innovation, the elements of social governance and digital management demonstrate universal applicability in enabling enterprises to achieve high levels of green innovation. (2) The dual-core-driven configuration achieves green innovation through the synergy between social governance and digital management, with its specific pathways varying according to the coordinated combinations of auxiliary factors. This delineates three distinct types, including compliance-oriented, environmentally empowered, and comprehensively balanced pathways. (3) The digitally driven configuration establishes an endogenous linkage between technological innovation and green development through the deep coupling of digital technology R&D and application. (4) The low green innovation configuration exhibits insufficient efficacy due to either isolated single elements or the absence of digital management, resulting in suboptimal green innovation performance. This study empirically demonstrates that the effective advancement of green innovation fundamentally relies on the endogenous dynamics of social governance, the technological underpinnings of digital management, and the systemic synergy among key elements, offering significant strategic implications for enterprises to develop differentiated green innovation approaches. Full article

Against the background of carbon emission reduction, this paper explores the driving factors of carbon footprint knowledge system toughness for building construction enterprises through the theory of constraints (TOC) and optimises the carbon footprint knowledge system toughness under static and dynamic perspectives, respectively. Under the static perspective, the fuzzy set qualitative comparative analysis method (fsQCA) is used to explore the development path of the carbon footprint knowledge system toughness for building construction enterprises, and the study finds three kinds of grouping paths. Under the dynamic perspective, system dynamics is used to analyse the causality of the driving factors of the carbon footprint knowledge system toughness and draw the causality diagram. The stock flow diagram is drawn according to the relationship between the factors, and G1 method is combined with the expert distribution to determine the weight of each factor, and then, the model equation is established to complete the construction of the system dynamics of the carbon footprint knowledge system toughness based on the control variable method of the four capabilities under the influence of the factors to simulate the comparison and to explore the extent of the influence of different factors on the carbon footprint knowledge system toughness. Through the two-dimensional analysis framework, we provide an integrated solution for path selection and dynamic regulation for building construction enterprises to help them achieve the adaptive optimisation of the carbon footprint knowledge system and promote the low-carbon transformation and sustainable development of the construction industry. Qualitative results show that three configuration paths affect resilience, with core factors including management, emission, predictive, and construction capabilities. Quantitative results indicate fsQCA overall consistency (0.861) and coverage (0.808); system dynamics simulation shows that management capability has the highest impact weight (0.355). Full article

From the perspective of organizational legitimacy acquisition, this study elucidates the sources and formation pathways of resource-based enterprises’ resilience in the face of institutional shocks. It explores the evolution of resilience with the improvement of the resource-based enterprises’ legitimacy under institutional constraints. Using the new mining rights of the resource-based enterprises as the measured variable of organizational resilience under institutional shocks, this study describes the adaptability of the resource-based enterprises to institutional change from the subdivision dimension of pragmatic legitimacy and moral legitimacy. A multi-period fuzzy-set Qualitative Comparative Analysis (fsQCA) approach is adopted, which takes Chinese mining enterprises listed on the Shanghai Stock Exchange as samples to obtain the formation pathways and dynamic evolution characteristics of the resilience of the resource-based enterprises under the institutional shocks of the “supply-side structural reforms” (2016–2019) and the “dual-carbon” goals (2020–2022). The results indicate that the differences of institutional shock strength and constraint degree promote different resilience formation mechanisms. The high intensity and hard constraints of the supply-side structural reforms promote the high-resilience pathways of the enterprises based on pragmatic legitimacy. The guiding and incentive orientation of the “dual-carbon” goals promote more improvement in the moral legitimacy of the enterprises, forming high-resilience pathways of “pragmatic legitimacy + moral legitimacy”. Under continuous institutional shocks, influence legitimacy has a universal effect on the formation of high resilience by the resource-based enterprises, and structural legitimacy, as the core condition of the high-resilience pathways, demonstrates continuity. By increasing the subdivision dimension of moral legitimacy and mitigating the limitations of pragmatic legitimacy, resource-based enterprises can achieve breakthroughs in their pathways to high resilience. This study provides valuable insights and guidance for resource-based enterprises seeking to overcome future institutional shocks and achieve resilient growth. Full article

The proliferation of social media has paradoxically facilitated the widespread dissemination of fake news, impacting individuals, politics, economics, and society as a whole. Despite the increasing scholarly research on this phenomenon, a significant gap exists regarding its dynamics in developing countries, particularly how predictors of fake news sharing interact, rather than merely their net effects. To acquire a more nuanced understanding of fake news sharing behavior, we propose identifying the direct and complex interplay among key variables by utilizing a dual analytical framework, leveraging Structural Equation Modeling (SEM) for linear relationships and Fuzzy-Set Qualitative Comparative Analysis (fsQCA) to uncover asymmetric patterns. Specifically, we investigate the influence of news-find-me orientation, social media trust, information-sharing tendencies, and status-seeking motivation on the propensity of fake news sharing behavior. Additionally, we delve into the moderating influence of social media literacy on these observed effects. Based on a cross-sectional survey of 1028 Haitian social media users, the SEM analysis revealed that news-find-me perception had a negative but statistically insignificant influence on fake news sharing behavior. In contrast, information sharing exhibited a significant negative association. Trust in social media was positively and significantly linked to fake news sharing behavior. Meanwhile, status-seeking motivation was positively associated with fake news sharing behavior, although the association did not reach statistical significance. Crucially, social media literacy moderated the effects of trust and information sharing. Interestingly, fsQCA identified three core configurations for fake news sharing: (1) low status seeking, (2) low information-sharing tendencies, and (3) a unique interaction of low “news-find-me” orientation and high social media trust. Furthermore, low social media literacy emerged as a direct core configuration. These findings support the urgent need to prioritize social media literacy as a key intervention in combating the dissemination of fake news. Full article

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

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

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

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

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