{"title":"创新是改变企业生产力的因素:测量与解释问题","authors":"Y. Domnich","doi":"10.14530/se.2022.4.093-127","DOIUrl":null,"url":null,"abstract":"The purpose of this аrticle is to present the current state of empirical research in the field of assessing the impact of innovations on enterprise productivity, detailing the problems of statistical measurement of innovations and meaningful interpretation of accumulated results. To study a sample of scientific papers devoted to the quantitative analysis of the impact of innovations on productivity, the methods of multifactorial systematization, critical analysis, content analysis and synthetic generalization were used. The problems of statistical measurement and consistent interpretation are analyzed in the context of four levels: innovation as an economic phenomenon; innovation as a factor of productivity change in the economy of a particular country; innovation as a factor of comparative economic dynamics in the global scale and innovation as a factor of industrial development in Russia. Conclusions and Relevance. In the modern economy, innovations are an independent factor of production, different from scientific research, patented inventions, material and technical base and other factors. The impact of innovations is often insignificant against the background of other factors and (or) negative. Microeconomic studies carried out on the basis of the results of surveys of enterprises are strongly limited in terms of regional, sectoral and intertemporal coverage of the economy. The dominance of the subjective approach to measuring innovation and the CDM model to assess the relationship between innovation and productivity leads to the accumulation of less informative results. The analytical potential of mainstream approaches to the problem of assessing the impact of innovations on productivity is wearing out and it will not be possible to compensate for their weaknesses without losing comparability in the near future","PeriodicalId":54733,"journal":{"name":"Networks & Spatial Economics","volume":null,"pages":null},"PeriodicalIF":1.6000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Innovation As a Factor of Changing the Productivity of Enterprises: Measurement and Interpretation Issues\",\"authors\":\"Y. Domnich\",\"doi\":\"10.14530/se.2022.4.093-127\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The purpose of this аrticle is to present the current state of empirical research in the field of assessing the impact of innovations on enterprise productivity, detailing the problems of statistical measurement of innovations and meaningful interpretation of accumulated results. To study a sample of scientific papers devoted to the quantitative analysis of the impact of innovations on productivity, the methods of multifactorial systematization, critical analysis, content analysis and synthetic generalization were used. The problems of statistical measurement and consistent interpretation are analyzed in the context of four levels: innovation as an economic phenomenon; innovation as a factor of productivity change in the economy of a particular country; innovation as a factor of comparative economic dynamics in the global scale and innovation as a factor of industrial development in Russia. Conclusions and Relevance. In the modern economy, innovations are an independent factor of production, different from scientific research, patented inventions, material and technical base and other factors. The impact of innovations is often insignificant against the background of other factors and (or) negative. Microeconomic studies carried out on the basis of the results of surveys of enterprises are strongly limited in terms of regional, sectoral and intertemporal coverage of the economy. The dominance of the subjective approach to measuring innovation and the CDM model to assess the relationship between innovation and productivity leads to the accumulation of less informative results. The analytical potential of mainstream approaches to the problem of assessing the impact of innovations on productivity is wearing out and it will not be possible to compensate for their weaknesses without losing comparability in the near future\",\"PeriodicalId\":54733,\"journal\":{\"name\":\"Networks & Spatial Economics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Networks & Spatial Economics\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.14530/se.2022.4.093-127\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"OPERATIONS RESEARCH & MANAGEMENT SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Networks & Spatial Economics","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.14530/se.2022.4.093-127","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
Innovation As a Factor of Changing the Productivity of Enterprises: Measurement and Interpretation Issues
The purpose of this аrticle is to present the current state of empirical research in the field of assessing the impact of innovations on enterprise productivity, detailing the problems of statistical measurement of innovations and meaningful interpretation of accumulated results. To study a sample of scientific papers devoted to the quantitative analysis of the impact of innovations on productivity, the methods of multifactorial systematization, critical analysis, content analysis and synthetic generalization were used. The problems of statistical measurement and consistent interpretation are analyzed in the context of four levels: innovation as an economic phenomenon; innovation as a factor of productivity change in the economy of a particular country; innovation as a factor of comparative economic dynamics in the global scale and innovation as a factor of industrial development in Russia. Conclusions and Relevance. In the modern economy, innovations are an independent factor of production, different from scientific research, patented inventions, material and technical base and other factors. The impact of innovations is often insignificant against the background of other factors and (or) negative. Microeconomic studies carried out on the basis of the results of surveys of enterprises are strongly limited in terms of regional, sectoral and intertemporal coverage of the economy. The dominance of the subjective approach to measuring innovation and the CDM model to assess the relationship between innovation and productivity leads to the accumulation of less informative results. The analytical potential of mainstream approaches to the problem of assessing the impact of innovations on productivity is wearing out and it will not be possible to compensate for their weaknesses without losing comparability in the near future
期刊介绍:
Networks and Spatial Economics (NETS) is devoted to the mathematical and numerical study of economic activities facilitated by human infrastructure, broadly defined to include technologies pertinent to information, telecommunications, the Internet, transportation, energy storage and transmission, and water resources. Because the spatial organization of infrastructure most generally takes the form of networks, the journal encourages submissions that employ a network perspective. However, non-network continuum models are also recognized as an important tradition that has provided great insight into spatial economic phenomena; consequently, the journal welcomes with equal enthusiasm submissions based on continuum models.
The journal welcomes the full spectrum of high quality work in networks and spatial economics including theoretical studies, case studies and algorithmic investigations, as well as manuscripts that combine these aspects. Although not devoted exclusively to theoretical studies, the journal is "theory-friendly". That is, well thought out theoretical analyses of important network and spatial economic problems will be considered without bias even if they do not include case studies or numerical examples.