在数字经济时代,绿色制造企业面临着应用数字技术实现资源优化的新机遇和新挑战。然而,在数字经济背景下,绿色制造企业进行资源配置与优化仍面临数字化基础设施不完善、数据孤岛、供应链脆弱性和资源浪费与利用率低等挑战。本文提出了...在数字经济时代,绿色制造企业面临着应用数字技术实现资源优化的新机遇和新挑战。然而,在数字经济背景下,绿色制造企业进行资源配置与优化仍面临数字化基础设施不完善、数据孤岛、供应链脆弱性和资源浪费与利用率低等挑战。本文提出了基于数字经济的资源优化策略,包括建立数字化基础设施,促进企业数字化转型;促进数据共享与整合,避免数据孤岛问题;构建弹性供应链,合理调配资源;应用数字技术,优化资源利用;优化要素配置,发展新质生产和加强人才培养与管理,应对市场挑战等策略。研究结果为企业在数字化转型中的资源优化提供了科学的决策依据,能为绿色制造企业在数字经济条件下进行资源配置与优化时提供一些参考,旨在推动绿色制造企业实现可持续发展,促进经济由高速增长向高质量发展转变,实现资源配置与优化技术的不断融合,为绿色制造的发展提供更多可能性。In the era of digital economy, green manufacturing enterprises are facing new opportunities and challenges in applying digital technology to achieve resource optimization. However, under the context of the digital economy, green manufacturing enterprises still face challenges such as imperfect digital infrastructure, data silos, supply chain fragility, and low resource waste and utilization rate for resource allocation and optimization. This paper proposes resource optimization strategies based on the digital economy, including the establishment of digital infrastructure to promote the digital transformation of enterprises. Promote data sharing and integration to avoid data silos;Build a flexible supply chain and rationally allocate resources;applying digital technologies to optimize the use of resources;Optimize the allocation of factors, develop new quality production, strengthen personnel training and management, and respond to market challenges. The research results provide a scientific basis for decision-making for the resource optimization of enterprises in the digital transformation, and can provide some references for green manufacturing enterprises to allocate and optimize resources under the conditions of digital economy, aiming to promote the sustainable development of green manufacturing enterprises, promote the transformation of the economy from high-speed growth to high-quality development, realize the continuous integration of resource allocation and optimization technology, and provide more possibilities for the development of green manufacturing.展开更多
数字经济与实体经济深入融合的背景下,针对电子商务行业物流资源供需矛盾及物流服务质量差异显著等问题,本文以一个电商平台、一个第三方卖家和消费者所组成的电子商务供应链为研究对象,并将市场竞争要素纳入考虑范畴,分别构建无物流资...数字经济与实体经济深入融合的背景下,针对电子商务行业物流资源供需矛盾及物流服务质量差异显著等问题,本文以一个电商平台、一个第三方卖家和消费者所组成的电子商务供应链为研究对象,并将市场竞争要素纳入考虑范畴,分别构建无物流资源共享和物流资源共享模式下的Stackelberg博弈模型,探究市场竞争下物流资源共享对电商平台和第三方卖家产品定价、市场需求和企业利润的影响。研究发现:1) 当市场竞争程度较小时,物流资源共享会扩大第三方卖家的市场需求,降低电商平台的市场需求。2) 当市场竞争程度较大时,物流资源共享将会提高博弈双方产品的销售单价。3) 当市场竞争程度为[0.57, 0.67]时,物流资源共享将会实现博弈双方收益的帕累托改进,实现博弈双方“共赢”。Under the background of the deep integration of the digital economy and the real economy, for the contradiction between the supply and demand of logistics resources in the e-commerce industry and the significant difference in the quality of logistics services, this paper takes the e-commerce supply chain composed of an e-commerce platform, a third-party seller and consumers as the object of study, and takes the elements of market competition into account, and constructs the Stackelberg game model under the mode of no logistics resource sharing and logistics resource sharing respectively. Stackelberg’s game model is constructed to investigate the effects of logistics resource sharing on product pricing, market demand and corporate profits of e-commerce platforms and third-party sellers under market competition. The study finds that: 1) When the degree of market competition is small, logistics resource sharing will expand the market demand of third-party sellers and reduce the market demand of e-commerce platforms. 2) When the degree of market competition is large, the sharing of logistics resources will increase the unit price of the products of both parties to the game. 3) When the degree of market competition is [0.57, 0.67], the sharing of logistics resources will realize the Pareto improvement of the benefits of both sides of the game, and realize the “win-win” situation of both sides of the game.展开更多
本研究创建了一个新的直播招聘平台用户满意度评价模型,使用了可拓基元理论和可拓优度评价方法进行构建,并通过权重因子判断法为各评价指标分配了权重,以确保评估的准确性和客观性。通过一项实际案例的测试,验证了这种评价体系的实用性...本研究创建了一个新的直播招聘平台用户满意度评价模型,使用了可拓基元理论和可拓优度评价方法进行构建,并通过权重因子判断法为各评价指标分配了权重,以确保评估的准确性和客观性。通过一项实际案例的测试,验证了这种评价体系的实用性和效果。This study establishes a new user satisfaction evaluation model for live broadcasting recruitment platforms. It is constructed using the theory of extension primitives and the extension superiority evaluation method. The evaluation indicators are assigned weights through the weight factor judgment method to ensure the accuracy and objectivity of the assessment. The practicality and effectiveness of this evaluation system are verified through a test of an actual case.展开更多
随着电子商务的迅速发展,B2C电商平台在零售市场中占据了重要地位。尽管平台用户的满意度评估已取得较丰富的成果,但传统的评价方法在权重分配方面仍存在局限性。基于中国顾客满意度指数模型从用户期望、感知质量、感知价值、顾客满意...随着电子商务的迅速发展,B2C电商平台在零售市场中占据了重要地位。尽管平台用户的满意度评估已取得较丰富的成果,但传统的评价方法在权重分配方面仍存在局限性。基于中国顾客满意度指数模型从用户期望、感知质量、感知价值、顾客满意度和顾客忠诚度等五个方面构建评价指标体系;采用可拓优度评价法确定各评价指标的权重并构建B2C电商平台用户满意度的评价模型;利用京东、淘宝和拼多多等三大电商平台的用户满意调查数据验证该评价模型的合理性。With the rapid development of e-commerce, B2C e-commerce platforms have taken a significant position in the retail market. Although substantial progress has been made in evaluating user satisfaction on these platforms, traditional evaluation methods still have limitations in terms of weight distribution. This study constructs an evaluation index system based on the Chinese Customer Satisfaction Index (CCSI) model, covering five aspects: user expectations, perceived quality, perceived value, customer satisfaction, and customer loyalty. The evaluation model of user satisfaction for B2C e-commerce platforms is developed by determining the weight of each evaluation index using the Extension Optimum Degree Evaluation Method. The rationality of this evaluation model is verified using user satisfaction survey data from three major e-commerce platforms: JD.com, Taobao, and Pinduoduo.展开更多
文摘在数字经济时代,绿色制造企业面临着应用数字技术实现资源优化的新机遇和新挑战。然而,在数字经济背景下,绿色制造企业进行资源配置与优化仍面临数字化基础设施不完善、数据孤岛、供应链脆弱性和资源浪费与利用率低等挑战。本文提出了基于数字经济的资源优化策略,包括建立数字化基础设施,促进企业数字化转型;促进数据共享与整合,避免数据孤岛问题;构建弹性供应链,合理调配资源;应用数字技术,优化资源利用;优化要素配置,发展新质生产和加强人才培养与管理,应对市场挑战等策略。研究结果为企业在数字化转型中的资源优化提供了科学的决策依据,能为绿色制造企业在数字经济条件下进行资源配置与优化时提供一些参考,旨在推动绿色制造企业实现可持续发展,促进经济由高速增长向高质量发展转变,实现资源配置与优化技术的不断融合,为绿色制造的发展提供更多可能性。In the era of digital economy, green manufacturing enterprises are facing new opportunities and challenges in applying digital technology to achieve resource optimization. However, under the context of the digital economy, green manufacturing enterprises still face challenges such as imperfect digital infrastructure, data silos, supply chain fragility, and low resource waste and utilization rate for resource allocation and optimization. This paper proposes resource optimization strategies based on the digital economy, including the establishment of digital infrastructure to promote the digital transformation of enterprises. Promote data sharing and integration to avoid data silos;Build a flexible supply chain and rationally allocate resources;applying digital technologies to optimize the use of resources;Optimize the allocation of factors, develop new quality production, strengthen personnel training and management, and respond to market challenges. The research results provide a scientific basis for decision-making for the resource optimization of enterprises in the digital transformation, and can provide some references for green manufacturing enterprises to allocate and optimize resources under the conditions of digital economy, aiming to promote the sustainable development of green manufacturing enterprises, promote the transformation of the economy from high-speed growth to high-quality development, realize the continuous integration of resource allocation and optimization technology, and provide more possibilities for the development of green manufacturing.
文摘数字经济与实体经济深入融合的背景下,针对电子商务行业物流资源供需矛盾及物流服务质量差异显著等问题,本文以一个电商平台、一个第三方卖家和消费者所组成的电子商务供应链为研究对象,并将市场竞争要素纳入考虑范畴,分别构建无物流资源共享和物流资源共享模式下的Stackelberg博弈模型,探究市场竞争下物流资源共享对电商平台和第三方卖家产品定价、市场需求和企业利润的影响。研究发现:1) 当市场竞争程度较小时,物流资源共享会扩大第三方卖家的市场需求,降低电商平台的市场需求。2) 当市场竞争程度较大时,物流资源共享将会提高博弈双方产品的销售单价。3) 当市场竞争程度为[0.57, 0.67]时,物流资源共享将会实现博弈双方收益的帕累托改进,实现博弈双方“共赢”。Under the background of the deep integration of the digital economy and the real economy, for the contradiction between the supply and demand of logistics resources in the e-commerce industry and the significant difference in the quality of logistics services, this paper takes the e-commerce supply chain composed of an e-commerce platform, a third-party seller and consumers as the object of study, and takes the elements of market competition into account, and constructs the Stackelberg game model under the mode of no logistics resource sharing and logistics resource sharing respectively. Stackelberg’s game model is constructed to investigate the effects of logistics resource sharing on product pricing, market demand and corporate profits of e-commerce platforms and third-party sellers under market competition. The study finds that: 1) When the degree of market competition is small, logistics resource sharing will expand the market demand of third-party sellers and reduce the market demand of e-commerce platforms. 2) When the degree of market competition is large, the sharing of logistics resources will increase the unit price of the products of both parties to the game. 3) When the degree of market competition is [0.57, 0.67], the sharing of logistics resources will realize the Pareto improvement of the benefits of both sides of the game, and realize the “win-win” situation of both sides of the game.
文摘本研究创建了一个新的直播招聘平台用户满意度评价模型,使用了可拓基元理论和可拓优度评价方法进行构建,并通过权重因子判断法为各评价指标分配了权重,以确保评估的准确性和客观性。通过一项实际案例的测试,验证了这种评价体系的实用性和效果。This study establishes a new user satisfaction evaluation model for live broadcasting recruitment platforms. It is constructed using the theory of extension primitives and the extension superiority evaluation method. The evaluation indicators are assigned weights through the weight factor judgment method to ensure the accuracy and objectivity of the assessment. The practicality and effectiveness of this evaluation system are verified through a test of an actual case.
文摘随着电子商务的迅速发展,B2C电商平台在零售市场中占据了重要地位。尽管平台用户的满意度评估已取得较丰富的成果,但传统的评价方法在权重分配方面仍存在局限性。基于中国顾客满意度指数模型从用户期望、感知质量、感知价值、顾客满意度和顾客忠诚度等五个方面构建评价指标体系;采用可拓优度评价法确定各评价指标的权重并构建B2C电商平台用户满意度的评价模型;利用京东、淘宝和拼多多等三大电商平台的用户满意调查数据验证该评价模型的合理性。With the rapid development of e-commerce, B2C e-commerce platforms have taken a significant position in the retail market. Although substantial progress has been made in evaluating user satisfaction on these platforms, traditional evaluation methods still have limitations in terms of weight distribution. This study constructs an evaluation index system based on the Chinese Customer Satisfaction Index (CCSI) model, covering five aspects: user expectations, perceived quality, perceived value, customer satisfaction, and customer loyalty. The evaluation model of user satisfaction for B2C e-commerce platforms is developed by determining the weight of each evaluation index using the Extension Optimum Degree Evaluation Method. The rationality of this evaluation model is verified using user satisfaction survey data from three major e-commerce platforms: JD.com, Taobao, and Pinduoduo.
