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How Does Digital Technology Affect Industrial Change?An Exploration Based on Meta-analysis Technology |
Zheng Diwen1,Xie Weihong1,2,Li Zhongshun2,Luo Jianbin1 |
(1.School of Management,Guangdong University of Technology;2.School of Economics,Guangdong University of Technology,Guangzhou 510520,China) |
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Abstract In the current era, digital technology has changed the production processes, business models and industrial organizations, and even subverted the basic assumptions of many innovative theories. Digital technology supports the development of industry, and its supporting ability plays a key role in the process of forming industrial change. Especially in today's digital economy era, with the unpredictable market supply and demand and increasingly fierce competition among merchants, enterprises urgently need to keep exploring new market opportunities for profit growth and find a way that is in line with their own digital transformation in order to cope with the general trend of industrial change, and the use of digital technology plays an important role in this process. Therefore, it is a historical mission to explore how digital technology affects industrial change. What can be done to explore the influence mechanism of digital technology on industrial change? What are the common theories to explore the influence mechanism of digital technology on industrial change? Through what kind of mechanism does digital technology affect industrial change? What is the intensity of these influence mechanisms? #br#Within the analytical framework of long-wave theory of technological innovation (technological innovation—organizational change—labor employment—government supervision-industrial reform), this paper explores the influence mechanism of digital technology on industrial change. First of all, the research hypothesis is deduced based on the relevant theory and research; secondly, the literature is screened and coded according to the research paradigm of meta-analysis technology. Finally, the meta-analysis is carried out, including publication bias analysis, main effect analysis, moderating effect analysis, multiple regression analysis and sensitivity analysis, etc.#br#Firstly the influence mechanism of digital technology on industrial change consists of three levels: : the organizational level includes financial factors, innovation factors, performance factors, production and operation factors; the labor force level includes employment factors and labor force status factors; the policy level includes policy factors. Regardless of the degree of heterogeneity, there is a significant correlation between the main effect of digital technology on industrial change and the moderating effect of its influence mechanisms.#br#Secondly the impact of each mechanism is not consistent, for high correlation, moderate correlation and low correlation are involved. Environmental governance performance, regional innovation performance, total factor labor productivity, technological innovation capability, regional innovation, change of business model and factor mismatch at the organizational level; employment information, employment quality and urban and rural income at the labor level, and institutional and cultural heterogeneity at the policy level play important roles in analyzing the impact mechanism of digital technology on industrial change. The mismatch between policy attention and talent system is presented in the moderate influence mechanism of digital technology on industrial change. Finally, the inclusive nature of digital inclusive finance, green technology innovation, production speed, digital change and policy orientation play a weak role in analyzing the influence mechanism of digital technology on industrial transformation. Although these factors belong to a weak mechanism in the analysis of the influence mechanism of digital technology on industrial change, it should be noted that these mechanisms may have a stronger or weaker impact in analyzing the impact of digital technology on industrial change in different situations.#br#Thirdly in the existing empirical research, the main theories used to explore the influence mechanism of digital technology on industrial change are Schumpeter's innovation theory, empowerment theory, service-oriented logic theory, technological change, and labor demand theory, adaptive structure theory, technology long-wave theory and so on. In addition, there is the need to look forward to the following aspects: (1) the research on the specific process and forms of industrial change affected by digital technology; (2) the research on the government management strategy of digital technology; (3) the research on the impact of digital technology on industrial change in the context of China. This study provides a reference value for further deepening vertical-related research and situational-related research in the future.#br#
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Received: 20 June 2022
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[1] YOO Y. Computing in everyday life: a call for research on experiential computing[J]. MIS Quarterly, 2010,34(2):213-231. [2] 邢小强, 周平录, 张竹, 等. 数字技术、BOP商业模式创新与包容性市场构建[J]. 管理世界, 2019,35(12):116-136. [3] 谢卫红,林培望,李忠顺, 等.数字化创新:内涵特征、价值创造与展望[J].外国经济与管理,2020,42(09):19-31. [4] 谢卫红,李忠顺,李秀敏, 等.数字化创新研究的知识结构与拓展方向[J].经济管理,2020,42(12):184-202. [5] CHENG M, SHAO Z, GAO F, et al. The effect of research and development on the energy conservation potential of China's manufacturing industry: the case of east region[J]. Journal of Cleaner Production, 2020, 258(4):1-13. [6] KENNEY M,ROUVINEN P,SEPPALA T,et al. Platforms and industrial change[J]. Industry and Innovation, 2019,26(8):871-879. [7] 李英杰, 韩平. 数字经济发展对我国产业结构优化升级的影响——基于省级面板数据的实证分析[J]. 商业经济研究, 2021,40(6):183-188. [8] 卢洪友, 陈思霞. 第三产业技术进步与技术效率的财政政策效应实证分析[J]. 广东商学院学报, 2009,24(3):74-80. [9] 沈运红, 黄桁. 数字经济水平对制造业产业结构优化升级的影响研究——基于浙江省2008—2017年面板数据[J]. 科技管理研究, 2020,40(3):147-154. [10] ZHANG C. An empirical study on the impact of digital economy development on the upgrading and optimization of industrial structure[C]//E3S Web of Conferences. EDP Sciences, 2021, 275-276. [11] 孟庆时, 余江, 陈凤, 等. 数字技术创新对新一代信息技术产业升级的作用机制研究[J]. 研究与发展管理, 2021,33(1):90-100. [12] LING S, HAN G, AN D, et al. The impact of green credit policy on technological innovation of firms in pollution-intensive industries: evidence from China[J]. Sustainability, 2020,12(11):1-16. [13] SHEN L, FAN R, WANG Y, et al. Impacts of environmental regulation on the green transformation and upgrading of manufacturing enterprises[J]. International Journal of Environmental Research and Public Health, 2020,17(20):1-14. [14] 包晨晨, 于思淼. 企业兼并重组来源于技术内生——来自中国上市公司的经验证据[J]. 经济体制改革, 2016,15(5):184-189. [15] PRADHAN R P, ARVIN M B, NAIR M, et al. Short-term and long-term dynamics of venture capital and economic growth in a digital economy: a study of European countries[J]. Technology in Society, 2019,57(5):125-134. [16] ARDOLINO M, RAPACCINI M, SACCANI N, et al. The role of digital technologies for the service transformation of industrial companies[J]. International Journal of Production Research, 2018,56(6):2116-2132. [17] 王文倩, 张羽. 金融结构、产业结构升级和经济增长——基于不同特征的技术进步视角[J]. 经济学家, 2022,42(2):118-128. [18] ZHANG L, LONG R, CHEN H, et al. Performance changes analysis of industrial enterprises under energy constraints[J]. Resources Conservation and Recycling, 2018,136(12):248-256. [19] ZHOU L, JIANG Z, GENG N, et al. Production and operations management for intelligent manufacturing: a systematic literature review[J]. International Journal of Production Research, 2022,60(2):808-846. [20] ROMERO-SILVA R, HERNANDEZ-LOPEZ G. Shop-floor scheduling as a competitive advantage: a study on the relevance of cyber-physical systems in different manufacturing contexts[J]. International Journal of Production Economics, 2020,224(4):1-54. [21] 黎继子, 李柏勋. 集群式供应链大规模定制化运作模式分析——以晋江鞋业产业集群为例[J]. 科研管理, 2007,34(6):167-174. [22] 洪银兴. 科技创新中的企业家及其创新行为——兼论企业为主体的技术创新体系[J]. 中国工业经济, 2012,29(6):83-93. [23] 郝凤霞, 江文槿, 楼永. 劳动力流动与地区制造业升级——基于转移升级和转型升级角度[J]. 产经评论, 2021,38(6):90-109. [24] 张峰, 殷秀清. 劳动力供给要素变迁对制造业转型升级影响的统计检验[J]. 统计与决策, 2020,36(4):91-95. [25] 王冬, 吕延方. 数字技术影响实体经济就业的非线性效应研究[J]. 现代管理科学, 2021,40(8):110-120. [26] 王文. 数字经济时代下工业智能化促进了高质量就业吗[J]. 经济学家, 2020,32(4):89-98. [27] DUMAN M C, AKDEMIR B. A study to determine the effects of industry 4.0 technology components on organizational performance[J]. Technological Forecasting and Social Change, 2021,167(5):1-14. [28] HUNTER J E, SCHMIDT F. Methods of meta-analysis: correcting error and bias in research findings [M]. Sage, 2004. [29] HIGGINS J, THOMPSON S G, DEEKS J J, et al. Measuring inconsistency in meta-analyses[J]. British Medical Journal, 2003,327(12):557-560. [30] COHEN J. Statistical power analysis for the behavioral sciences[M]. New York: Academic Press, 1977.
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