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大数据驱动制造企业与物流企业协同发展的实证研究
引用本文:张季平,陶君成,尤美虹.大数据驱动制造企业与物流企业协同发展的实证研究[J].中国流通经济,2020(2):3-14.
作者姓名:张季平  陶君成  尤美虹
作者单位:嘉兴学院商学院;武汉东湖学院
基金项目:广东省高校人文社会科学创新强校项目“珠三角地区第三方物流的全球供应链网络嵌入研究”(2017WTSCX129)
摘    要:大数据和大数据技术的快速发展和应用,为制造企业和物流企业的生存和发展带来了新的机遇和挑战,如何运用大数据和大数据技术推动制造企业与物流企业有效协同,成为当前理论界和实业界关注的焦点。为探究大数据驱动制造企业与物流企业协同发展的内在机理,可基于大数据可挖掘性、价值性、真实性、多样性等主要特性,构建大数据驱动制造企业与物流企业协同发展概念模型并提出研究假设,进而运用结构方程模型对研究假设进行验证。研究结果发现,大数据的价值性、真实性、多样性对制造企业发展水平具有显著正向影响,而可挖掘性对其正向影响不显著;大数据的真实性、可挖掘性、多样性对物流企业服务水平具有显著正向影响,而价值性对其正向影响不显著;大数据的可挖掘性、真实性对制造企业与物流企业协同程度具有显著正向影响,而多样性、价值性对其正向影响不显著,不过价值性可以通过影响制造企业发展水平产生间接影响作用。这与目前我国制造企业、物流企业运用新一代信息技术驱动自身转型升级尚处于起步阶段存在很大关系。未来,随着科学技术的进步以及制造企业智能化与高端物流的发展,大数据将在驱动制造企业与物流企业协同方面发挥显著重要作用,最终促使制造企业与物流企业形成长期稳定的协同发展关系。

关 键 词:大数据  物流企业  制造企业  协同程度  高端物流

An Empirical Study on the Co-development of Manufacturing Enterprises and Logistics Enterprises Enabled by the Big Data
ZHANG Ji-ping,TAO Jun-cheng,YOU Mei-hong.An Empirical Study on the Co-development of Manufacturing Enterprises and Logistics Enterprises Enabled by the Big Data[J].China Business and Market,2020(2):3-14.
Authors:ZHANG Ji-ping  TAO Jun-cheng  YOU Mei-hong
Institution:(Jiaxing University,Jiaxing,Zhejiang314001,China;Wuhan Donghu University,Wuhan,Hubei430071,China)
Abstract:The rapid development and application of the Big Data and Big Data technologies have brought manufacturing and logistics enterprises both opportunities and challenges. How to use the Big Data and Big Data technologies to promote collaboration between manufacturing and logistics enterprises is important theoretically and practically. To explore the internal mechanism of how the Big Data enables the co-development between manufacturing and logistics enterprises,through literature review,the authors summarize the main characteristics of the Big Data,namely:mining,value,veracity,and variety;and based on the conceptual model of the Big Data enabling manufacturing and logistics enterprises co-development,some research hypotheses are proposed,and the structural equation model is used to verify the research hypotheses. The results show that:(1)value,veracity,and variety have positive impacts on the manufacturing enterprises’ development,while the mining has no significant positive impact;(2) mining,veracity,and variety have positive impacts on the logistics enterprises’ service level,while the value has no significant positive impact;and(3)mining and veracity have positive impacts on the co-development of manufacturing and logistics enterprises,while value and variety have no significant positive impacts,but value can have an indirect impact by affecting the development of manufacturing enterprises. And all these results are determined by the primary stage of new generation IT application to the transformation and upgrading of China’s manufacturing and logistics enterprises. In the future,with the development of science and technology and the smart manufacturing and high-end logistics,the Big Data will play more important role in promoting the collaboration between manufacturing and logistics enterprises,which will in turn promote the long-term collaboration between manufacturing and logistic enterprises.
Keywords:big data  logistics enterprises  manufacturing enterprises  co-development  high-end logistics
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