云制造下基于时空熵权TOPSIS和SOM聚类的区域绿色制造发展水平测度研究
Research on Regional Green Manufacturing Development Level Measurement Based on Temporal and Spatial Entropy Weighted TOPSIS and SOM Clustering in Cloud Manufacturing
DOI: 10.12677/ecl.2024.133589, PDF,   
作者: 张潇逸:贵州大学管理学院,贵州 贵阳;张人龙*, 刘小红*:贵州大学管理学院,贵州 贵阳;喀斯特地区发展战略研究中心,贵州 贵阳
关键词: 云制造绿色制造发展水平时空熵权TOPSISSOMCloud Manufacturing Green Manufacturing Development Level Spatio-Temporal Entropy Weight TOPSIS SOM
摘要: 当前,中国正经历以数字化和绿色化为主题的第四次工业革命时期。在数字经济腾飞,智能制造转型的浪潮中,各地制造业积极响应国家号召,涌现出不少新兴智能绿色制造企业。本文通过时空熵权TOPSIS评价法对2012~2021年中国30个省份的绿色制造水平进行了测度,构建了绿色排放、绿色质效、科技创新、资源利用、绿色治理五个维度的指标。研究发现:1) 在东、中、西部地区中,东部地区绿色制造发展水平常年处于领先水平,而中、西部地区相对较低,其中,“四绿”的建设发展是影响区域绿色制造发展水平的重要因素;2) 整体趋势显示,2012~2015年,不论是东部还是中西部地区,绿色制造发展指数呈下降趋势,直到2016年,“绿色制造”概念的提出及“四绿”建设扭转了这一趋势,缓解了经济发展与环境保护矛盾;3) 历年绿色制造发展水平可划分为四个梯队,第一梯队数量逐年增加,但第四梯队仍较高,主要集中在中、西部,尤其是西部,中、西绿色制造发展水平不足问题依然突出。最后,论文提出了云制造资源优化配置的管理建议。
Abstract: Currently, China is experiencing a period of the fourth industrial revolution themed on intelligence and greening. In the wave of digital economy taking off and smart manufacturing transformation, manufacturing industries around the world have actively responded to the national call, and many emerging smart manufacturing enterprises have emerged. This paper measures the green manufacturing level of 30 provinces in China from 2012 to 2021 through the spatio-temporal entropy weighted TOPSIS evaluation method, and constructs indicators in five dimensions: green emission, green quality and efficiency, scientific and technological innovation, resource utilization, and green governance. The study found that: 1) The development level of green manufacturing in the eastern region has been high, while the central and western regions are relatively low, and the construction of the “four greens” is an important factor influencing the development level of regional green manufacturing; 2) The overall trend shows that from 2012 to 2015, the green manufacturing development index in both eastern and central and western regions showed a downward trend, until 2016, when the concept of “green manufacturing” and the construction of the “four greens” reversed the trend and alleviated the contradiction between economic development and environmental protection; 3) The level of green manufacturing development in the past years can be divided into four echelons, with the first echelon increasing year by year, but the fourth echelon is still relatively low. The first echelon is increasing year by year, but the fourth echelon is still higher, mainly concentrated in the central and western parts of the country, especially in the west, where the problem of insufficient development level of green manufacturing in the central and western parts of the country is still prominent. Finally, the paper proposes management suggestions for optimizing resource allocation in cloud manufacturing.
文章引用:张潇逸, 张人龙, 刘小红. 云制造下基于时空熵权TOPSIS和SOM聚类的区域绿色制造发展水平测度研究[J]. 电子商务评论, 2024, 13(3): 4791-4806. https://doi.org/10.12677/ecl.2024.133589

参考文献

[1] Weissman, S.H. and Sekutowski, J.C. (1991) Environmentally Conscious Manufacturing: A Technology for the Nineties. AT & T Technical Journal, 70, 23-30. [Google Scholar] [CrossRef
[2] Sarkis, J. (2001) Manufacturing’s Role in Corporate Environmental Sustainability—Concerns for the New Millennium. International Journal of Operations & Production Management, 21, 666-686. [Google Scholar] [CrossRef
[3] 陈艳莹, 于千惠, 刘经珂. 绿色产业政策能与资本市场有效“联动”吗——来自绿色工厂评定的证据[J]. 中国工业经济, 2022(12): 89-107.
[4] 杨俊峰, 张添硕, 周长波, 凌黎明, 王曦. “双碳”目标背景下我国绿色制造体系建设路径研究[J]. 中国环境管理, 2022, 14(6): 75-80.
[5] 李金华. 中国绿色制造、智能制造发展现状与未来路径[J]. 经济与管理研究, 2022, 43(6): 3-12.
[6] 曹裕, 李想, 胡韩莉, 万光羽, 汪寿阳. 数字化如何推动制造企业绿色转型?——资源编排理论视角下的探索性案例研究[J]. 管理世界, 2023, 39(3): 96-112, 126, 113.
[7] Salem, A.H. and Deif, A.M. (2017) Developing a Greenometer for Green Manufacturing Assessment. Journal of Cleaner Production, 154, 413-423. [Google Scholar] [CrossRef
[8] 林志炳, 陈莫凡, 李钰雯. 考虑绿色制造及企业社会责任行为的零售商自有品牌策略研究[J]. 管理工程学报, 2023, 37(1): 216-224.
[9] 邵帅, 范美婷, 杨莉莉. 经济结构调整、绿色技术进步与中国低碳转型发展——基于总体技术前沿和空间溢出效应视角的经验考察[J]. 管理世界, 2022, 38(2): 46-69, 4-10.
[10] 游建民, 张伟. 国家生态文明试验区绿色制造绩效评价及影响因素研究——以贵州为例[J]. 贵州社会科学, 2018(12): 120-128.
[11] 李志鹏, 欧阳玉凤, 杨浩昌. 区域绿色制造发展指数测度及其时空演变特征分析[J]. 统计与决策, 2022, 38(20): 11-15.
[12] 王鸣涛, 叶春明. 基于熵权TOPSIS的区域工业绿色制造水平评价研究[J]. 科技管理研究, 2020, 40(17): 53-60.
[13] 黄晓杏, 余达锦, 刘亦晴. 区域绿色创新系统成熟度指标体系的构建与评价[J]. 统计与决策, 2019, 35(21): 45-49.
[14] Valenzuela-Venegas, G., Salgado, J.C. and Díaz-Alvarado, F.A. (2016) Sustainability Indicators for the Assessment of Eco-Industrial Parks: Classification and Criteria for Selection. Journal of Cleaner Production, 133, 99-116. [Google Scholar] [CrossRef
[15] 魏艳华, 王丙参, 朱琳. 基于时空熵权TOPSIS评价法的经济高质量发展水平测度——以广东省为例[J]. 统计与决策, 2023, 39(8): 91-95.
[16] 中国工程院绿色制造发展战略研究课题组. 推进绿色制造 建设生态文明——中国绿色制造战略研究[J]. 中国工程科学, 2017, 19(3): 53-60.
[17] 陶永, 李秋实, 赵罡. 面向产品全生命周期的绿色制造策略[J]. 中国科技论坛, 2016(9): 58-64.
[18] 钟玥, 陈伟栋. “工业工程 + 绿色制造”战略研究体系的构建[J]. 中国管理信息化, 2018, 21(23): 131-134.
[19] 汪凌, 邹建辉, 刘淑敏. 中国绿色经济发展水平测度、动态演进及空间效应研究[J]. 统计与决策, 2023, 39(18): 97-102.
[20] 明翠琴, 陈雷, 钟书华. 中国绿色增长综合评价指标体系的构建及实证[J]. 科技管理研究, 2021, 41(10): 76-86.
[21] 王曰芬, 徐天傲, 岑咏华. 绿色发展理念支撑的生态文明建设综合评价指标体系构建及应用[J]. 智库理论与实践, 2023, 8(4): 52-63.
[22] 李晔, 陈奕延, 李群. 中国城市群绿色发展水平测度与效率评价[J]. 统计与决策, 2023, 39(17): 126-131.
[23] 朱梦菲, 陈守明, 邵悦心. 基于AHP-TOPSIS和SOM聚类的区域创新策源能力评价[J]. 科研管理, 2020, 41(2): 40-50.