Search Results (659)

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

We formulate the Quantum Information Copy Time (QICT) framework for conserved charges under strictly local quantum dynamics and isolate its logically strongest consequence. The theorem-level core is a receiver-optimised variational speed-limit inequality: after projection away from the conserved zero mode, the copy time is bounded from below by the inverse square root of a Liouvillian-squared receiver susceptibility times a local encoding seminorm. This statement is written in a finite-volume operator framework and does not require a diffusive ansatz. We then examine what follows only after additional infrared assumptions. Under a single diffusive slow-mode hypothesis, the variational inequality reduces to the practical scaling relation used in the benchmark computations. That reduction is treated as conditional and is stress-tested numerically rather than promoted by rhetoric. Within the anomaly-free Abelian span relevant for one Standard-Model-like generation, hypercharge selection is elevated to theorem-level status; by contrast, minimal gauge-algebra uniqueness remains explicitly conditional on additional model-selection axioms. The remainder of the manuscript is organised as an explicitly documented closure programme built on top of this core. In that closure, a gauge-coded QCA construction, a microscopic benchmark for the transport normalisation, and an electroweak matching convention are combined to produce a resonance-centred Higgs-portal singlet-scalar mass band together with direct-detection, invisible-width, and relic-consistency checks. These latter results are presented as model-dependent consequences of an explicit closure ansatz rather than as deductions from locality alone. 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

To explore whether the causal chain of “Industry–University–Government Integrated Innovation Ecosystem → Novel Energy Storage Technology Innovation → Dual-Control Energy Targets” can be achieved, this study analyzes panel data from 30 provinces, municipalities, and autonomous regions in China (excluding Tibet, Hong Kong, Macao, and Taiwan) from 2010 to 2022. By employing a complex mediation effect model combining dynamic Qualitative Comparative Analysis (QCA) and the dynamic panel system Generalized Method of Moments (GMM) model, this study identifies five configuration pathways for driving innovation in novel energy storage technologies within an integrated innovation ecosystem. These include two industry digitalization–university innovation resource-dominant pathways: a government-light and digitally driven “university–industry” resource-sharing and knowledge-conversion synergy, and an industry leadership pathway embedded with university collaborative innovation under a digitalization framework. Two policy-driven hybrid and industry–leadership synergistic pathways are also extracted: a growth pathway for policy-supported hybrid organizations under insufficient industry digitalization and a policy-driven innovation substitution pathway compensating for the absence of university niche roles. Additionally, a multidimensional collaborative development pathway is identified, reflecting comprehensive collaboration. In the dynamic panel system GMM model, all five pathways collectively suppress total energy consumption and energy intensity, while also indirectly driving the achievement of dual-control energy targets through innovation in novel energy storage technologies. Pathways driven by government-light and digitally facilitated collaboration, industry leadership, and comprehensive collaboration show significant direct negative effects on energy consumption and intensity. However, the policy-driven innovation substitution pathway exhibits limited contribution due to the absence of university innovation components, thereby failing to significantly advance regional dual-control energy goals. Full article

The agglomeration of the Unmanned Aerial Vehicle (UAV) industry is a key driver of the low-altitude economy. To understand how UAV industrial agglomeration emerges across cities with different socioeconomic foundations, this study investigates its dynamic configurational pathways. It develops an analytical framework that integrates the institutional environment, market conditions, and knowledge-based capabilities. Using panel data for 280 Chinese cities from 2017 to 2023, we apply panel data qualitative comparative analysis (QCA) to identify configurational pathways toward UAV industrial agglomeration. Seven socioeconomic conditions are considered: science and technology expenditure, policy support, infrastructure, social consumption level, financial development, urban innovation capacity, and human capital. The results show that UAV industrial agglomeration arises from the joint effects of multiple conditions, not from any single factor. We identify six pathways that are grouped into three archetypes: institution–knowledge-driven, institution–market-driven, and multidimensional synergistic configurations. The dominant pathways shift over time and differ across city sizes. These findings provide macro-level evidence on the mechanisms underpinning UAV industrial agglomeration. They also offer implications for strengthening the UAV industrial ecosystem. 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

Sustainable human resource management (HRM) has attracted growing attention as a new paradigm for enhancing organizational resilience. However, prior studies mainly examined the effects of individual practices, offering a limited explanation of how organizational resilience emerges as an integrated mechanism. To address this theoretical gap, we conceptualize sustainable HRM as an integral talent management process in which multiple practices operate interdependently and investigate the configurational mechanisms through which organizational resilience is generated in Japanese firms and discuss these from the perspective of socioformation. Based on six analytical dimensions derived from a tertiary literature review, we conducted a crisp-set qualitative comparative analysis (csQCA) using securities report data from 36 listed Japanese companies. The results revealed that organizational resilience is not achieved through a single best practice, but rather points to a new form of integrated human resource management aimed at sustainable value creation. From a socioformation perspective, employees are viewed not merely as productive inputs but as agents capable of continuous development through sustained investment in human potential. From this perspective, sustainable social development cannot be reduced to well-being or inclusion indicators alone but also encompasses ethical, collaborative, territorial, and interdisciplinary dimensions of transformation. The findings clarify the theoretical role of integral talent management in sustainable value creation and provide practical implications for human-centred management. 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