School of Economics and Management, Beijing Information Science & Technology University, Beijing, China.
School of Management, Dalian University of Finance and Economics, Dalian, China.
PLoS One. 2023 Apr 10;18(4):e0283655. doi: 10.1371/journal.pone.0283655. eCollection 2023.
With the deepening of a new round of technological revolution and industrial reform, digital technology has been continuously innovated and widely penetrated into various economic fields. The digital economy (DE) is gradually becoming the focus of China's economic development planning and a new engine to enhance national strength. Evaluating the development level of DE in various regions is conducive to timely discover the shortcomings in China's DE development, as well as provide an important basis for putting forward corresponding policy suggestions. This investigation established a hybrid multi-criteria decision making (MCDM) model for evaluating DE development of 31 provincial level regions in China ranging from 2015 to 2020. Firstly, the evaluation indicator system is established from digital infrastructure, integrated development, social benefits, innovation ability, and electronic-commerce dimensions containing 17 quantitative sub-criteria based on Fuzzy-Delphi method. Secondly, integrated weights of 17 sub-criteria from 2015 to 2020 are computed in terms of objective weights calculated by the anti-entropy weight (AEW) approach from 2015 to 2020 and subjective weights obtained via the best-worst method (BWM). Thirdly, MARCOS model is applied to evaluate the DE development degree of various regions in China ranging from 2015 to 2020. Case analysis illustrates that the DE development of Guangdong, Jiangsu, Zhejiang, and Beijing always maintain in the top four from 2015 to 2020, while the southwest and northwest regions in China are obviously fall behind others. And the DE development degree of various regions is primarily affected under the integrated development performance, innovation ability performance, and social benefits performance. Therefore, the backward regions should emphasize the development of software industry and information technology industry. The robustness of the proposed MCDM model combining Fuzzy-Delphi, AEW, BWM and MARCOS is discussed employing three similarity coefficients of rankings. And it is verified that the proposed MCDM model has superior robustness and validity in evaluating DE development.
随着新一轮科技革命和产业变革的深入发展，数字技术不断创新，广泛渗透到经济社会各领域全过程。数字经济（DE）逐渐成为中国经济发展规划的重点，是增强国家实力的新引擎。评估各地区 DE 的发展水平，有利于及时发现中国 DE 发展中的不足，为提出相应的政策建议提供重要依据。本研究建立了一个混合多准则决策（MCDM）模型，用于评估中国 2015 年至 2020 年 31 个省级行政区的 DE 发展水平。首先，根据模糊德尔菲法（Fuzzy-Delphi method）从数字基础设施、综合发展、社会效益、创新能力和电子商务五个维度建立了包含 17 个定量子准则的评价指标体系。其次，根据 2015 年至 2020 年的反熵权重（AEW）法计算客观权重和最佳最差法（BWM）获得的主观权重计算 17 个子准则的综合权重。第三，应用 MARCOS 模型评估中国 2015 年至 2020 年各地区的 DE 发展水平。案例分析表明，2015 年至 2020 年，广东、江苏、浙江和北京的 DE 发展始终保持在前四，而中国西南和西北地区明显落后于其他地区。而且，各地区的 DE 发展程度主要受综合发展绩效、创新能力绩效和社会效益绩效的影响。因此，落后地区应重视软件产业和信息技术产业的发展。通过三个排名相似度系数对所提出的融合 Fuzzy-Delphi、AEW、BWM 和 MARCOS 的 MCDM 模型的稳健性进行了讨论，并验证了该模型在评估 DE 发展方面具有优越的稳健性和有效性。
