The future Sixth-Generation (6G) wireless systems are expected to encounter emerging services with diverserequirements. In this paper, 6G network resource orchestration is optimized to support customized networkslicin...The future Sixth-Generation (6G) wireless systems are expected to encounter emerging services with diverserequirements. In this paper, 6G network resource orchestration is optimized to support customized networkslicing of services, and place network functions generated by heterogeneous devices into available resources.This is a combinatorial optimization problem that is solved by developing a Particle Swarm Optimization (PSO)based scheduling strategy with enhanced inertia weight, particle variation, and nonlinear learning factor, therebybalancing the local and global solutions and improving the convergence speed to globally near-optimal solutions.Simulations show that the method improves the convergence speed and the utilization of network resourcescompared with other variants of PSO.展开更多
E-business develops rapidly and attracts a large number of merchants and consumers in the past 20 years.Meanwhile,the debate over e-business mode and its critical success factors(CSFs)is a research hotspot in the indu...E-business develops rapidly and attracts a large number of merchants and consumers in the past 20 years.Meanwhile,the debate over e-business mode and its critical success factors(CSFs)is a research hotspot in the industry and the academia.In this study,we propose the CSFs framework of self-run e-business by combining systematic literature review,resource orchestration theory,and empirical firm survey.The quantitative method of content analysis is targeted at the interview data received from 90 managers of JD.com by software NVivo 11.We construct a self-run e-business CSFs framework and find out that the CSFs of self-run e-business are products,organization,and supply chain,respectively.In addition,this study compares different characteristics and their impact on performance in platform-type and self-run e-businesses.Firm managers can derive a better understanding and measurement of e-business activities.展开更多
With the advancement of technology,innovation ecosystems based on technological resources gradually emerge.However,little attention has been paid to the internal mechanisms driving the evolution of such ecosystems in ...With the advancement of technology,innovation ecosystems based on technological resources gradually emerge.However,little attention has been paid to the internal mechanisms driving the evolution of such ecosystems in extant literature.This study conducts a longitudinal case analysis of iFLYTEK's ecosystem-building process and finds that the evolution of a technological resource-driven innovation ecosystem comprises three stages:technological accumulation,technological openness,and technological empowerment.Each stage exhibits distinct technological characteristics that underpin different resource orchestration approaches and value co-creation models.In the technological accumulation stage,the company forms an integrated value-creation model by structuring resources.In the technological openness stage,a shared value co-creation model is shaped through resource capability development.In the technological empowerment stage,a model emerges via resource leveraging.Based on these findings,this study proposes a theoretical model of the evolution and value co-creation of technological resource-driven innovation ecosystems.This model not only enriches theoretical research on innovation ecosystems and resource orchestration but also provides practical insights for building other technological resource-driven innovation ecosystems.展开更多
The mechanisms by which value chains are reconfigured during corporate digital transformation have attracted growing attention from both academia and industry.Drawing on technology empowerment theory,we conduct a long...The mechanisms by which value chains are reconfigured during corporate digital transformation have attracted growing attention from both academia and industry.Drawing on technology empowerment theory,we conduct a longitudinal dual-case study of Huawei and Midea to explore the dynamic evolution mechanism of value chain reconfiguration during digital transformation.Specifically,this study aims to find the pathways through which value chain reconfiguration occurs,analyze the mechanisms of value transmission,and examine the similarities and differences in reconfiguration mechanisms between infrastructure-oriented and application-oriented enterprises.The findings reveal that digital technologies serve as the engine and driving force of value chain reconfiguration by empowering resource combinations that integrate data and traditional resources to enhance resource reconfiguration capabilities,innovating resource leverage approaches,and driving value chain reconfiguration.Based on these insights,we develop a research framework of "digital technologies→resource orchestration→value chain reconfiguration."Furthermore,the mechanism of value chain reconfiguration evolves across three stages,namely,digitalization,networking,and intelligentization.Given their different starting points,motivations,and depths of digitalization,infrastructure-oriented and application-oriented enterprises exhibit distinct mechanisms of value chain reconfiguration at different stages of digital transformation.These findings enrich the understanding of value chain reconfiguration in digital transformation and provide managerial implications for practitioners.展开更多
基金supported by the Social Scientific Research Foundation of China(21VSZ126).
文摘The future Sixth-Generation (6G) wireless systems are expected to encounter emerging services with diverserequirements. In this paper, 6G network resource orchestration is optimized to support customized networkslicing of services, and place network functions generated by heterogeneous devices into available resources.This is a combinatorial optimization problem that is solved by developing a Particle Swarm Optimization (PSO)based scheduling strategy with enhanced inertia weight, particle variation, and nonlinear learning factor, therebybalancing the local and global solutions and improving the convergence speed to globally near-optimal solutions.Simulations show that the method improves the convergence speed and the utilization of network resourcescompared with other variants of PSO.
基金supported in part by the National Natural Science Foundation of China(2020187)the China Futures Association 17th Joint Research Project(2024370050)+1 种基金the Jinling Institute of Technology High-level Talent Research Fund Project(JIT-B-202404)the Anhui Huishang Futures Technology Center Incubation Project(HSQHBSHZ2023-02).
文摘E-business develops rapidly and attracts a large number of merchants and consumers in the past 20 years.Meanwhile,the debate over e-business mode and its critical success factors(CSFs)is a research hotspot in the industry and the academia.In this study,we propose the CSFs framework of self-run e-business by combining systematic literature review,resource orchestration theory,and empirical firm survey.The quantitative method of content analysis is targeted at the interview data received from 90 managers of JD.com by software NVivo 11.We construct a self-run e-business CSFs framework and find out that the CSFs of self-run e-business are products,organization,and supply chain,respectively.In addition,this study compares different characteristics and their impact on performance in platform-type and self-run e-businesses.Firm managers can derive a better understanding and measurement of e-business activities.
基金supported by the major project of the National Social Science Fund of China(No.21&ZD119)the project of the National Natural Science Foundation of China(No.72072181,72272064)the Fundamental ResearchFunds for the Central Universities(No.23JNQMX15).
文摘With the advancement of technology,innovation ecosystems based on technological resources gradually emerge.However,little attention has been paid to the internal mechanisms driving the evolution of such ecosystems in extant literature.This study conducts a longitudinal case analysis of iFLYTEK's ecosystem-building process and finds that the evolution of a technological resource-driven innovation ecosystem comprises three stages:technological accumulation,technological openness,and technological empowerment.Each stage exhibits distinct technological characteristics that underpin different resource orchestration approaches and value co-creation models.In the technological accumulation stage,the company forms an integrated value-creation model by structuring resources.In the technological openness stage,a shared value co-creation model is shaped through resource capability development.In the technological empowerment stage,a model emerges via resource leveraging.Based on these findings,this study proposes a theoretical model of the evolution and value co-creation of technological resource-driven innovation ecosystems.This model not only enriches theoretical research on innovation ecosystems and resource orchestration but also provides practical insights for building other technological resource-driven innovation ecosystems.
基金supported by the general project of the National Natural Science Foundation of China(No.71972086)the key research project of Heilongjiang Provincial Economic and Social Development(No.21216).
文摘The mechanisms by which value chains are reconfigured during corporate digital transformation have attracted growing attention from both academia and industry.Drawing on technology empowerment theory,we conduct a longitudinal dual-case study of Huawei and Midea to explore the dynamic evolution mechanism of value chain reconfiguration during digital transformation.Specifically,this study aims to find the pathways through which value chain reconfiguration occurs,analyze the mechanisms of value transmission,and examine the similarities and differences in reconfiguration mechanisms between infrastructure-oriented and application-oriented enterprises.The findings reveal that digital technologies serve as the engine and driving force of value chain reconfiguration by empowering resource combinations that integrate data and traditional resources to enhance resource reconfiguration capabilities,innovating resource leverage approaches,and driving value chain reconfiguration.Based on these insights,we develop a research framework of "digital technologies→resource orchestration→value chain reconfiguration."Furthermore,the mechanism of value chain reconfiguration evolves across three stages,namely,digitalization,networking,and intelligentization.Given their different starting points,motivations,and depths of digitalization,infrastructure-oriented and application-oriented enterprises exhibit distinct mechanisms of value chain reconfiguration at different stages of digital transformation.These findings enrich the understanding of value chain reconfiguration in digital transformation and provide managerial implications for practitioners.
