Search Results (459)

In recent years, cross-border e-commerce and digital trade activities in transition economy countries and regions have continued to grow. Based on resource orchestration theory and empowerment theory, this paper examines the influence mechanism of digital leadership on international entrepreneurial performance and investigates the moderating effect of platform support. Analyzing survey data from 227 Chinese cross-border e-commerce enterprises using structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA), the study finds that: (1) Digital leadership positively influences the international entrepreneurial performance of cross-border e-commerce enterprises through the mediating roles of brand management capability and product innovation capability; (2) Platform support plays a positive moderating role in the relationship between brand management capability and international entrepreneurial performance in cross-border e-commerce; (3) Platform support moderates the mediating effect of brand management capability in the relationship between digital leadership and international entrepreneurial performance of cross-border e-commerce enterprises; (4) Based on fsQCA analysis, two antecedent configurations for achieving high international entrepreneurial performance in cross-border e-commerce are identified. These findings hold significant theoretical implications for research on cross-border digital platforms and international new ventures, while also providing robust empirical support for enterprises seeking to achieve international entrepreneurial success through the implementation of digital strategies. Full article

In the era of digital economy, manufacturing industry transcends geographical space to build virtual networks. Revealing the complex network characteristics and driver paths of virtual agglomeration is of great significance for accelerating the digitalization of manufacturing. First, this paper explains the formation mechanism and proposes the model of virtual agglomeration; moreover, the paper identifies complex network characteristics. Finally, this paper constructs a driving path framework based on the “Technology–Organization–Environment” theory, and uses fuzzy set qualitative comparative analysis to identify paths. The results show that the technological platform foundation plays a core role in enhancing the level of virtual agglomeration. Differentiated combinations of organizational and environmental conditions also have a positive impact. This study provides theoretical support and practical reference for cities to accelerate virtual agglomeration according to local conditions. Full article

The electronic and electrical architecture of vehicles has rapidly evolved to centralized. At present, there is no unified consensus on the R&D strategy of the platform in the industry, and there is also a lack of a quantitative decision-making framework that can be implemented. This study takes the centralized architecture platform as the research object, constructs a two-stage analysis framework of “advanced constraint screening-cost quantitative evaluation”, uses a fuzzy-set qualitative comparative analysis method to screen feasible R&D strategy combinations that meet the requirements of the architectural advancement, builds a total cost of ownership evaluation system around the software and hardware elements related to the architecture platform, and systematically analyzes the optimal cost R&D strategy combinations of car enterprises with different mass production scales under the two scenarios of Multi-Box and One-Board. The research results show that adaptive platform middleware and framework middleware are the core necessary elements to realize the advanced architecture; the amortization cost of architecture is negatively correlated with the scale of mass production, and the cost of in-house R&D is highly dependent on large-scale amortization; and there are differentiated optimal solutions in the framework selection and R&D strategy combination of automakers with different mass production scales. This study can provide quantitative reference and practical guidance for R&D decision making of centralized architecture platform for automakers. Full article

While GenAI is transforming education, it remains unclear how it shapes students’ behavior, especially concerning AI literacy. The purpose of this study is to examine which factors positively affect students’ learning behavior and whether AI literacy moderates this effect, using the COM-B model. An online survey of 438 participants was analyzed using covariance-based structural equation modeling (CB-SEM) and fuzzy-set qualitative comparative analysis (fsQCA). The CB-SEM results indicate that independent learning ability, receptive ability, learning environment, AI support equipment, and both intrinsic and extrinsic motivations significantly shape student learning behavior. Notably, AI literacy moderates the relationship between GenAI and learning behavior. Furthermore, fsQCA reveals seven configurations of these factors that favorably impact learning behavior. Together, these findings provide theoretical and practical insights for universities, highlighting actionable ways universities can support students’ adoption of GenAI. Full article

The escalation of geopolitical tensions has forced global manufacturers to reconfigure their supply chains. While Digital Transformation (DT) is widely touted as a primary driver of resilience, traditional variance-based research often assumes a symmetric, linear relationship that applies universally across firms. This study challenges this assumption through the lens of Complexity Theory. Viewing supply chains as Complex Adaptive Systems (CASs), we employ Fuzzy-Set Qualitative Comparative Analysis (fsQCA) on a stratified sample of 928 manufacturers in a geopolitical high-risk zone (Taiwan). We identify equifinal pathways to Organizational Resilience, revealing a fundamental asymmetry between organizational types. The results suggest that while large enterprises rely on a resource-intensive strategy—which we term the “Digital Fortress” configurational metaphor (combining high digital maturity and agility as a core condition)—SMEs can achieve high resilience through an “Agile Dodger” configuration, leveraging operational agility and niche positioning without necessitating high digital maturity. This study contributes to the systems literature by mapping the “topology of resilience” and offering tailored configurational pathways that complement traditional variance-based perspectives in volatile ecosystems. Full article

Green innovation is central to industrial ecological transition, yet heavily polluting firms often exhibit low-quality green innovation investment. Grounded in the government–enterprise–research–intermediary Quadruple Helix innovation ecosystem framework, this study integrates Necessary Condition Analysis (NCA) and fuzzy set qualitative comparative analysis (fsQCA) to examine 66 publicly listed heavily polluting manufacturing firms in China. The results show that fiscal subsidies and environmental taxes are necessary but not sufficient conditions for achieving high-quality green innovation investment. Moreover, high-quality outcomes arise through three equifinal pathways: the Government–Intermediary Dual-Drive Model, the Government–Enterprise–Intermediary Co-Directional Model, and the Government–Enterprise Symbiotic Model. Six configurations lead to non-high-quality green innovation investment, which cluster into Resource-Scarcity and Regulatory-Constrained models. A favorable macro environment further strengthens high-quality outcomes. These findings clarify how policy instruments and multi-actor collaboration jointly shape green innovation investment quality and provide actionable implications for heavily polluting firms and policymakers seeking sustainable development. Full article

Under the dual strategic imperatives of carbon neutrality and digital transformation, the power industry plays a pivotal role in advancing green and low-carbon development. Green Total Factor Productivity (GTFP) provides a comprehensive measure of efficiency in the power sector under energy and environmental constraints. Using panel data from 31 Chinese provinces over the period 2012–2023, this study employs a super-efficiency Slacks-Based Measure (SBM) model, kernel density estimation, standard deviation ellipse analysis, the Gini coefficient, and fuzzy-set Qualitative Comparative Analysis (fsQCA) to systematically examine the spatiotemporal evolution, regional disparities, and digital-driven improvement pathways of power industry GTFP. The results indicate that national power-sector GTFP exhibits a fluctuating upward trend, accompanied by pronounced regional heterogeneity. A distinct spatial pattern has emerged, characterized by rapid improvement in the western region, relative stability in the eastern region, contraction in the central region, and persistent lagging in the northeastern region. Spatially, the distribution has evolved from an initial east–west dual-core structure to a three-tier gradient pattern led by the west, stabilized in the east, and depressed in the central region. Kernel density estimation reveals a clear multi-peak polarization trend, while standard deviation ellipse analysis shows a relatively stable spatial center with continuously expanding dispersion along the northeast–southwest axis. Further analysis demonstrates that interregional differences remain the primary source of overall inequality, with rapidly widening intraregional disparities in the western region. Configurational analysis identifies five digital-economy-driven pathways to high GTFP, highlighting that no single optimal configuration exists. Instead, multiple combinations of technological, organizational, and environmental conditions jointly facilitate GTFP enhancement. These findings provide empirical evidence to support differentiated and precision-oriented policy design for promoting coordinated digital transformation and green development in China’s power industry. Full article

With the increasing constraints of resource and environmental factors and the prominent issues of regional development imbalance, how to scientifically measure the level of agricultural sustainable development and reveal its spatial-temporal differentiation patterns has become a key scientific question that urgently needs to be addressed in optimizing land use layout and promoting rural revitalization. This study takes the human-land spatial systems coupling theory as the core framework and constructs an evaluation index system for agricultural sustainable development covering five dimensions: economy, society, resources, ecology, and technology. Based on provincial panel data in China from 2001 to 2024, the entropy method is employed to measure agricultural sustainable development, while Dagum’s Gini coefficient, kernel density estimation, and convergence models are applied to analyze its spatial–temporal evolution. Furthermore, the fuzzy-set qualitative comparative analysis (fsQCA) method is introduced to identify multi-factor configurational driving pathways. The results indicate that the overall level of agricultural sustainable development in China shows a steady upward trend, exhibiting a regional gradient pattern characterized by “central region leading, eastern region steadily advancing, and western region gradually catching up”. The overall disparity presents a weak convergence trend, with inter-regional differences as the primary source, although their contribution is gradually declining. The development structure has evolved from regional fragmentation to a more complex spatial interaction pattern. The overall distribution shifts rightward with evident stage-based differentiation, accompanied by significant positive spatial dependence, with “high–high” and “low–low” clustering coexisting over the long term. Convergence analysis shows that σ-convergence exists at the national level. After accounting for spatial effects, significant absolute β-convergence is observed in the eastern and western regions, while the central region does not exhibit significant convergence. Conditional β-convergence further confirms the existence of regional convergence trends, although the convergence speeds vary. The fsQCA results indicate that agricultural sustainable development is not driven by a single factor but by multiple configurational pathways formed through the interaction of various conditions. These findings provide empirical evidence for optimizing agricultural spatial layout, strengthening land factor support, and promoting regionally coordinated agricultural sustainable development. Full article

Achieving high-quality employment for retired athletes is essential for promoting the holistic development of athletes and accelerating the construction of a strong sports nation. From the perspective of capital collaboration, this study develops a comprehensive analysis framework by incorporating human capital, social capital, and psychological capital to systematically investigate the influencing factors and configuration pathways for high-quality employment of retired athletes. Utilizing Necessary Condition Analysis (NCA) and fuzzy-set Qualitative Comparative Analysis (fsQCA), this study discovers three main findings. First, no single condition variable independently constitutes the necessary condition for high-quality employment. Second, three configuration pathways for achieving high-quality employment are identified, including human capital–social capital synergy, human capital–psychological capital synergy, and human capital–social capital–psychological capital integration. Third, vocational skill, as a component of human capital, emerges as an important condition in configurations associated with high-quality employment. Based on the findings, this research recommends improving the athlete security policy system, promoting the accumulation of human capital, strengthening the development of psychological capital, constructing diverse social support networks, and optimizing the pathways for retired athletes to achieve high-quality employment. These aims will support retired athletes in navigating career transitions effectively while securing stable and high-quality employment. Full article

As artificial intelligence (AI) changes educational practices, understanding what sustains pre-service teachers’ generative AI use beyond initial adoption becomes important. However, existing research mainly focuses on initial acceptance rather than continuance intention, which is a more realistic indicator for sustainable technology integration. This study drew on an integrated framework including psychological (GAI anxiety, GAI self-efficacy), contextual (facilitating conditions, social influence), and perceptual factors (perceived ease of use, perceived usefulness) to examine pre-service teachers’ continuance intention toward GAI in future teaching. Survey data from 549 Chinese pre-service teachers were analyzed using structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA). Results showed that GAI self-efficacy had the strongest positive associations with both perceived ease of use and perceived usefulness. GAI anxiety negatively influenced both perceptions. However, facilitating conditions did not significantly relate to perceived usefulness. The fsQCA identified six configurational pathways clustered into the following three patterns: intrinsic value driven, efficacy capability driven, and external support driven. These findings suggest that teacher education programs should prioritize building GAI self-efficacy and supportive peer environments and not focus solely on infrastructure provision. Full article

While existing research analyzes AI’s impact on platform enterprises’ competitive advantages from technological or organizational perspectives, it fails to adequately account for how multiple factors combined shape competitive advantages. From the perspective of situated AI theory, this study examines how the combinations among AI application characteristics, situated AI activities, platform enterprise attributes, and environmental characteristics collaboratively build platform enterprises’ competitive advantages. Drawing on panel data from Chinese listed platform enterprises and employing fuzzy-set Qualitative Comparative Analysis (fsQCA), this study reveals that (1) AI technology innovation and recasting AI are necessary conditions for platform enterprises to establish competitive advantages; (2) AI-enabled competitive advantages emerge from three types of configurations, the situated AI dominance type, the situated AI subsidiary type, or the collaborative drive type; (3) the AI-enabled combinations result in competitive advantages by three paths, AI internalization, AI leverage, and AI collaboration; and (4) the AI-enabled competitive advantages are more likely to be achieved by innovation platforms than by transaction platforms. These research findings fill the knowledge gap in AI-enabled competitive strategy, enrich the literature on situated AI theory, and offer practical guidance for platform enterprises’ AI applications. Full article

In the social media era, “trial by media” has evolved into widespread public participation in “trial by public opinion,” posing complex challenges to procedural justice. Existing research often focuses on macro-theory or linear effects, lacking exploration into the meso-level mechanisms of how multiple conditions combine. To address this gap, this study employs fuzzy-set Qualitative Comparative Analysis (fsQCA) to systematically examine how nine antecedent conditions—including case attributes, dissemination features, and socio-emotional structures—combine to trigger trial by public opinion, based on 22 high-profile Chinese judicial cases from 2014 to 2025. The findings reveal no single necessary condition but five sufficient causal paths, which converge into three core configurations: the “Collective Moral Outrage” configuration (triggered by heinous crimes), the “Reactive Confrontation” configuration (arising from public power disputes), and the “Collective Speculation” configuration (catalyzed by factual ambiguity). Moving beyond the binary debate of “whether influence occurs,” this study constructs a configurational theoretical framework that elucidates the heterogeneous pathways and underlying socio-psychological dynamics behind the formation of public opinion trials. The conclusions provide empirical and theoretical insights for developing precise judicial communication, public guidance, and governance strategies tailored to different risk types in the digital age. Full article

As robotaxis transition from technological validation to commercial operation, converting first-time tryers into long-term users becomes pivotal for achieving sustainable development. Existing research mainly examines factors affecting initial adoption intention for robotaxis from a net-effect perspective, yet little is known about the factors affecting continuance intention and their nonlinear causal mechanisms. This study integrates the Expectation–Confirmation Model (ECM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) to construct a systematic analytical framework and employs fuzzy-set Qualitative Comparative Analysis (fsQCA) for configurational analysis. Using survey data from 327 users in China with actual robotaxi experiences, the findings unveil four factor configurations driving high continuance intention and two causing non-high continuance intention. Regarding the interplay of factors driving high continuance intention, post-usage usefulness, satisfaction, and perceived safety constitute a complementary mechanism, whereas expectation confirmation and personal innovativeness form a substitutive mechanism that depends on the specific patterns of factor configurations. This study contributes to the robotaxi adoption literature by extending the research context to the post-adoption phase, developing a tailored theoretical framework, and applying a configurational approach rooted in complex systems analysis paradigms. The findings offer implications for governments to formulate synergistic policy mixes and for robotaxi companies to design user retention strategies. Full article

This study uses panel data from 30 Chinese provinces spanning 2010–2023. It applies Fuzzy Set Qualitative Comparative Analysis (fsQCA) to examine how different aspects of Smart Logistics affect New Quality Productive Forces. Analysis covers three areas: overall configuration, changes over time, and regional differences. The findings show: (1) New Quality Productive Forces develop from the interaction of Smart Logistics factors, not just one. System coordination limits development more than hardware does. (2) There is a strong link between Smart Logistics and New Quality Productive Forces. The connection moves from basic support to innovation and then to broader ecosystem development. (3) Regions differ: Eastern areas benefit from digital tools and innovation; central areas rely on system change and efficiency; Western areas focus on building up basics and capabilities. Full article

Corporate risk-taking, crucial for sustainable development, is shaped by the interplay of multiple institutional logics. However, existing research lacks a systematic understanding of how government, market, and technology logics collectively drive corporate risk-taking. This study addresses this gap by employing fuzzy-set Qualitative Comparative Analysis on data from Chinese intelligent manufacturing firms to explore the configurational pathways leading to high risk-taking. Our analysis reveals three distinct pathways: (1) An innovation-driven transformation pathway, characterized by a strong synergy between government and technology logics, with market logic playing a supplementary role. (2) A green transformation pathway, where government logic dominates, supported by market and technology logics in a hierarchical structure. (3) A resource synergy pathway, marked by the high-level integration of all three logics for strategic breakthroughs. Theoretically, this study advances institutional theory by developing an integrative framework that moves beyond a single-logic perspective, revealing the synergistic and substitutive relationships among multiple logics. Practically, our findings provide managers with a configurational roadmap for strategically aligning with institutional forces to enhance risk-taking capacity. Full article