Search Results (52)

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

Manufacturing firms face intensifying pressure to achieve sustainability while remaining competitive under environmental stress, rapid technological change, and institutional uncertainty—challenges that are particularly acute in developing economies. Although Industry 5.0 has emerged as a human-centric and sustainability-oriented industrial paradigm, limited research explains how it can be systematically operationalized to enhance sustainable business performance. This study addresses this gap by developing an integrative conceptual framework linking Industry 5.0, Smart Circular Economy (SCE), and Green Human Resource Management (GHRM) within manufacturing contexts. Drawing on resource-based, dynamic capability, and institutional perspectives, the framework conceptualizes Industry 5.0 as a strategic digital orientation that enables circular resource orchestration and sustainability-aligned human capital systems. SCE and GHRM are positioned as complementary operational mechanisms that translate Industry 5.0 principles into organizational capabilities. Innovation capability is introduced as a mediating dynamic capability explaining how technological and human resource investments generate environmental, social, and economic performance outcomes. Digital maturity and policy support are incorporated as contextual moderators shaping transformation pathways in developing economies. The proposed model advances sustainability-oriented industrial transformation theory by integrating previously fragmented research streams into a coherent socio-technical capability architecture. It also offers actionable insights for managers and policymakers seeking to align digital industrial development with long-term sustainability objectives under conditions of institutional heterogeneity. Full article

Global supply chains face intensifying pressures from disruption, regulatory complexity, and sustainability mandates, requiring a shift toward more resilient and adaptive coordination. While artificial intelligence (AI) and blockchain have been recognised as complementary enablers, their implementation remains largely fragmented, existing as isolated tools linked by manual data exchange rather than integrated, programmable logic. This paper addresses this orchestration gap by proposing the Dynamic Resource Orchestration Framework for AI-Blockchain Integrated Supply Chains (DROF-AIBC). Grounded in Resource Orchestration Theory (ROT) and Dynamic Capabilities Theory (DCT), the framework provides a theoretical foundation for the strategic and autonomous orchestration of digital resources. Unlike classic supply chain orchestration, which focuses on the linear coordination of physical assets and legacy systems, DROF-AIBC conceptualises an “intelligent conductor” as a coordination mechanism combining AI-driven analytics and smart contract-based execution. This mechanism supports the configuration, optimisation, and monitoring of resources in response to changing external signals, effectively closing the loop between analytical insights and verifiable execution. The paper further substantiates how this autonomous capability serves as a foundational roadmap for the Industry 5.0 paradigm, embedding human-centricity through Explainable AI (XAI) to provide a “provenance of logic”, promoting circular economy sustainability, and fostering systemic resilience in turbulent environments. The framework aims to provide both a theoretical foundation and a practical roadmap for orchestrating AI and blockchain to advance resilient, sustainable and adaptive supply chains. Full article

Small- and medium-sized enterprises (SMEs) increasingly rely on digital technologies to sustain innovation, yet limited empirical evidence explains how business intelligence capabilities translate into superior innovation outcomes, particularly in emerging economy contexts. Addressing this gap, this study examines the direct and indirect effects of business intelligence capabilities on innovation performance by unpacking the mediating role of knowledge management capability and the moderating role of data-driven decision making within an integrated Resource-Based View and Knowledge-Based View framework. Conceptually, the study advances prior research by clarifying the complementary roles of these theoretical perspectives: the Resource-Based View explains what strategic digital resources firms possess, the Knowledge-Based View explains how these resources are transformed into organizational knowledge through knowledge management capability, and data-driven decision making explains when these capabilities are effectively converted into innovation outcomes. Data were collected through a survey of 316 owners and senior managers of small- and medium-sized hotels operating in Amman, Jordan, and analyzed using partial least squares structural equation modeling (PLS-SEM) as the primary analytical technique. The results indicate that business intelligence capabilities exert a significant positive effect on innovation performance, with this relationship largely transmitted through knowledge management capability, demonstrating that the value of business intelligence lies in its integration into organizational knowledge processes rather than in data availability alone. Moreover, data-driven decision making strengthens the relationship between business intelligence capabilities and innovation performance, functioning as an execution-level capability that enhances the conversion of digital and knowledge-based resources into innovation outcomes. To further validate the robustness of the findings, a post-hoc moderated mediation analysis using Hayes’ PROCESS macro version 4.2 was conducted as a confirmatory analysis. By conceptualizing business intelligence, knowledge management, and data-driven decision making as an interconnected socio-technical capability system, this study advances digital innovation theory and offers actionable insights for SME managers seeking to orchestrate capabilities for innovation under resource constraints. Full article

As a sustainability-oriented mode of education, cross-border digital education has distinct advantages, including a low carbon footprint associated with decreased student and staff commute times and expanded accessibility for disadvantaged learners. However, the intrinsic mechanisms by which globally mobile talent, including international students and transnational professionals, utilize their global skills and networks to create sustainable EdTech entrepreneurial initiatives need further investigation. Based on dynamic capability theory and resource orchestration logic, this study examines how human and social capital shape entrepreneurial engagement through resource integration capability (RIC) via PLS-SEM analysis of data collected from 318 transnationally mobile actors. The study finds that neither form of capital has a direct association on entrepreneurial entry; instead, both are associated with entrepreneurial entry indirectly through RIC, allowing mobile talent to combine and allocate knowledge, networks, and digital technologies across institutional and cultural boundaries. The study examines how cross-border EdTech entrepreneurship works towards creating inclusive and equitable quality education, as well as global partnerships, through scalable, adaptable, and low-carbon educational services, while meeting objectives 4 and 17 of the UN Sustainable Development Goals. This study reveals the transformation process centered around RIC, highlighting the need to create innovative ecosystems that transition from talent attraction to talent empowerment. The findings underline the importance of RIC in translating global mobility into sustainable digital education solutions. Full article

Against the backdrop of the digital economy reshaping the global competitive landscape and the urgent demand for sustainable development, how data factors drive startups to break through resource constraints, achieve a niche leap, and realize long-term sustainable growth has become a critical issue of common concern in academia and policy circles. Drawing on resource orchestration theory and the dynamic capability view, this study constructs a theoretical framework of “Data Factor Allocation → Digital Capability Integration → Niche Leap → Sustainable Growth” and conducts an empirical test, using 412 technology-based startups as samples. The findings are as follows: (1) Data factor allocation (encompassing scenario-based access, lightweight tool penetration, and ecological sharing) exerts a significant inverted U-shaped relationship impact on both digital capability integration and the startup niche leap (range of quadratic term coefficients for core dimensions: −0.165~−0.203, p < 0.01), with turning points between 3.41 and 3.72 on a 5-point scale. Excessive data investment may trigger risks of capability hollowing and niche lock-in, hindering sustainable growth. (2) Digital capability integration (including technology application, resource coordination, and dynamic adaptation capabilities) plays a non-linear mediating role, with mediation proportions ranging from 18.7% to 32.4%. Among them, the technology application capability exhibits the highest transmission efficiency between lightweight tool penetration and the niche leap (32.4%), thereby promoting sustainable value creation. (3) The moderating effect of data governance maturity is heterogeneous: governance adaptability significantly strengthens the mediating path of the technology application capability (β = 0.187, p < 0.01) and security compliance enhances the transmission efficiency of the resource coordination capability (β = 0.165, p < 0.01), while the moderating effect of open sharing is insignificant. These findings provide a dynamic framework for the non-linear and sustainable leap of startups by integrating two core theories. They offer a decision-making basis for enterprises to optimize data allocation strategies (e.g., controlling allocation thresholds to avoid resource waste) and for governments to improve governance policies (e.g., data vouchers, trusted data spaces), thereby facilitating the implementation of the “Data Factor × Innovation and Entrepreneurship × Sustainable Development” initiative and promoting the sustainable growth of the digital economy ecosystem. Full article

Using the panel data of Chinese A-share firms from 2012 to 2023, we find that executives’ focus on digitalization is significantly and positively associated with corporate sustainability performance. The finding holds firm after a suite of endogeneity and robustness tests. Heterogeneity tests indicate that such a favorable impact is more salient for large enterprises, industry players with superior competitiveness, and entities situated in eastern China. The mechanism tests reveal that executives’ digital attention enhances corporate sustainable development by improving resource structuring capability, resource bundling capability, and resource leveraging capability. Additionally, financing constraints weaken, while media attention will enhance this promoting effect. Additional dimension-focused analyses demonstrate that the direct promotional impact of executives’ digital attention on corporate financial performance remains statistically insignificant, whereas it exerts a markedly positive catalytic effect on corporate environmental performance. This research offers novel theoretical interpretations and practical implications regarding the role of executive cognitive orientation in advancing corporate sustainable development against the backdrop of digital transformation. Full article

End–edge–cloud collaboration enables significant improvements in system resource utilization by integrating heterogeneous resources while ensuring application-level quality of service (QoS). However, achieving efficient collaborative decision-making in such architectures poses critical challenges within dynamic and complex computing network environments, including dynamic resource allocation, incentive alignment between cloud and edge entities, and multi-objective optimization. To address these issues, this paper proposes a dynamic resource optimization framework for complex cloud–edge collaborative networks, decomposing the problem into two hierarchical decision schemes: cloud-level coordination and edge-side coordination, thereby achieving adaptive resource orchestration across the End–edge–cloud continuum. Furthermore, leveraging differential game theory, we model the dynamic resource allocation and cooperation incentives between cloud and edge nodes, and derive a feedback Nash equilibrium to maximize the overall system utility, effectively resolving the inherent conflicts of interest in cloud–edge collaboration. Additionally, we formulate a joint optimization model for energy consumption and latency, and propose an Improved Discrete Artificial Hummingbird Algorithm (IDAHA) to achieve an optimal trade-off between these competing objectives, addressing the challenge of multi-objective coordination from the user perspective. Extensive simulation results demonstrate that the proposed methods exhibit superior performance in multi-objective optimization, incentive alignment, and dynamic resource decision-making, significantly enhancing the adaptability and collaborative efficiency of complex cloud–edge networks. Full article

Driven by the national policy of total water resources control and efficiency improvement, the behavior of water resource utilization reduction by firms is widespread, which may have an impact on the value of firms. This study integrates dynamic capability theory and signaling theory to construct a dual-path analytical framework, systematically investigating the impact of water utilization reduction on firm value and its intrinsic mechanisms. Based on data from Chinese A-share listed companies spanning 2012–2023, fixed-effect models, mediation-effect tests, and heterogeneity analysis are employed for empirical verification. The results reveal that water utilization reduction exerts a significant dual-path promoting effect on firm value: it enhances financial performance (ROA) primarily through technological innovation, reflecting the process of resource orchestration and dynamic capability construction; concurrently, it boosts market performance (Tobin’s Q) mainly by improving ESG performance as a signaling channel, mirroring the capital market’s positive pricing of green signals. Further heterogeneity analysis indicates that these effects are more pronounced during the policy deepening stage, in non-water-intensive industries, and in humid/sub-humid regions. This study contributes theoretical support and empirical evidence for firms’ green transformation and the formulation of differentiated water resource policies by the government, highlighting the synergistic development of high-quality economic growth and ecological civilization construction. Full article

Microservices as an emerging architectural approach have been widely applied in the development of online applications. However, in large-scale service systems, frequent data communications, complex invocation dependencies, and strict latency requirements pose significant challenges to efficient microservice orchestration. In addition, microservices need to frequently access the database to achieve data persistence, creating a mutual dependency between the two, and this symmetry further increases the complexity of service orchestration and coordinated deployment. In this context, the strong coupling of service deployment, database layout, and request routing makes effective local optimization difficult. However, existing research often overlooks the impact of databases, fails to achieve joint optimization among databases, microservice deployments, and routing, or lacks fine-grained orchestration strategies for multi-instance models. To address the above limitations, this paper proposes a joint optimization framework based on the Database-as-a-Service (DaaS) paradigm. It performs fine-grained multi-instance queue modeling based on queuing theory to account for delays in data interaction, request queuing, and processing. Furthermore this paper proposes a proximal policy optimization algorithm based on multi-stage joint decision-making to address the orchestration problem of microservices and database instances. In this algorithm, the action space is symmetrical between microservices and database deployment, enabling the agent to leverage this characteristic and improve representation learning efficiency through shared feature extraction layers. The algorithm incorporates a two-layer agent policy stability control to accelerate convergence and a three-level experience replay mechanism to achieve efficient training on high-dimensional decision spaces. Experimental results demonstrate that the proposed algorithm effectively reduces service request latency under diverse workloads and network conditions, while maintaining global resource load balancing. Full article

The integration of digitalization and sustainability has become a prevailing trend in China’s current economic and social development. However, existing research rarely focuses on how emerging technology enterprises achieve responsible innovation through digital sustainability orientation. Based on resource orchestration theory, this study investigates the impact of digital sustainability orientation on responsible innovation, and explores the mediating role of resource orchestration and the moderating role of scientific ties, using a sample of 287 emerging technology enterprises. The empirical results show that: digital sustainability orientation positively influences responsible innovation; resource orchestration mediates the relationship between digital sustainability orientation and responsible innovation; scientific ties positively moderates the relationship between digital sustainability orientation and resource orchestration, and also positively moderates the mediating effect of resource orchestration on the relationship between digital sustainability orientation and responsible innovation. Furthermore, heterogeneity analysis reveals that the leading role of the sustainability orientation is greater than the enabling role of the digital orientation. This research clarifies the theoretical relationship and mechanism between digital sustainability orientation and responsible innovation, and offers practical guidance for emerging technology enterprises to promote responsible innovation. Full article

Background: This study examines how AI-driven metaverse integration enhances sustainable manufacturing performance in Jordan’s industrial sector, with particular emphasis on the mediating role of digital supply chain resilience. Grounded in resource orchestration theory (ROT), the research explains how digital twin systems, predictive AI analytics, and virtual collaboration technologies jointly support sustainability through improved supply chain agility, responsiveness, and continuity. Methods: Data were collected from 500 industrial managers, of which 415 valid responses were analyzed using partial least squares structural equation modeling (PLS-SEM). Results: The findings indicate that AI-powered metaverse dimensions have significant and positive effects on sustainable manufacturing performance, both directly and indirectly through digital supply chain resilience. The mediation analysis confirms that resilience serves as a critical mechanism linking metaverse-based technology adoption to sustainability outcomes. Conclusions: The study highlights the strategic importance of integrating advanced digital and virtual technologies into supply chains to address sustainability challenges, particularly in emerging economies such as Jordan. By extending resource orchestration theory to the metaverse context, this research contributes to theory development and offers practical insights for industrial managers seeking to leverage digital transformation as a source of sustainable competitive advantage. Full article

This article integrates diverse strands of theory and empirical research to combine views on economic complexity and entrepreneurial ecosystems in the context of mountain regions, focusing on the role of orchestrator platforms in shaping innovation and growth. Mountains are often marginal, dispersed, and loosely integrated areas that suffer from scarce opportunities for resource combination and interaction at the basis of the innovative process. The research relies on the case study of the European Alps, combining multiple sources of data—surveys, interviews, and ethnographic studies—to highlight the strengths and weaknesses of the mountain ecosystems. Orchestrator platforms emerged as the central actors in the innovative network that overcomes the difficulties and constraints of the mountains. The article provides a comprehensive perspective on how economic complexity can drive development in mountain regions, offering both theoretical and practical contributions to the broader discourse on entrepreneurship and regional growth. Full article

This study investigates the interplay of advanced manufacturing technologies (AMT), digital commerce, circular economy intensity, and digital maturity on innovation outcomes among Spanish manufacturing firms in the post-pandemic era. Drawing on resource orchestration theory and survey data from 1813 companies, the analysis employs regression and mediation techniques to assess direct and indirect effects on product and process innovation. Findings reveal that AMT adoption leads to modest, context-dependent improvements in process innovation, while effects on product innovation are limited or negative; e-commerce adoption alone does not predict substantial innovation gains, and jointly adopting these technologies rarely produces amplifying results. Greater circular economy intensity mediates a negative relationship with process innovation, indicating possible resource trade-offs between sustainability initiatives and innovation goals. Digital maturity inconsistently strengthens positive impacts and can further moderate innovation outcomes in interaction with circular economy practices. Notably, economic benefits from circular economy practices are concentrated in export-oriented firms and not widely distributed in the sample. These findings challenge assumptions that digital and green transformations universally enhance innovation, advocating for tailored policy and organizational strategies that account for sectoral and contextual differences. Full article

Many green technology innovations developed by academic institutions struggle to cross the “Valley of Death” (VoD), failing to achieve commercialization. Boundary-spanning green technology search (BGTS), as an inter-organizational mechanism facilitating the interaction of green technology knowledge between firms and external stakeholders, can bridge the gap between green scientific research and the commercialization of green products. Drawing on the resource orchestration theory and recombinant search theory, this study empirically analyzed data from 313 Chinese manufacturing enterprises to explore the pathway through which BGTS promotes green product development performance (GPDP) and examines the chain mediating role of knowledge coupling and green technology commercialization capability (GTCC), as well as the moderating role of digital technology adoption and product complexity. The findings reveal that the relationship between BGTS and GPDP is sequentially mediated first by knowledge coupling and then by GTCC. Digital technology adoption positively moderates the BGTS-GPDP relationship. Product complexity moderates the BGTS-GPDP relationship in an inverted U-shape. This study elucidates the micro-mechanism underlying the commercialization of green technologies, providing both theoretical insights and practical guidance for the green and high-quality transformation of manufacturing enterprises. Full article