高新技术产业集群数字潜力测度算法研究

A. Babkin, L. Tashenova, D. Mamrayeva, P. Azimov
{"title":"高新技术产业集群数字潜力测度算法研究","authors":"A. Babkin, L. Tashenova, D. Mamrayeva, P. Azimov","doi":"10.1145/3372177.3373352","DOIUrl":null,"url":null,"abstract":"Industry 4.0, which is aimed at the global introduction of cyber-physical systems into industry, has determined further development pathways for cluster systems; one of the pathways is digitalization of business processes, which enables cutting costs significantly, manufacturing a high-tech innovative product, reducing time for communication between all the participants in the industrial cluster, revealing new sources for project funding, simplifying human work via relevant software and robotics adopted in the industry. All these factors become more urgent in the framework of functioning high-tech industrial clusters, which have not evolved only from the protocluster to the innovative active industrial cluster, but overtook their rivals by using these innovative available tools of the digital economy. In this paper the authors have presented a range of the most applicable methods to measure the digital potential of the industrial cluster (in regard to quantity, quality and mixed research methods); they have reviewed the literature that reveal the concept \"innovative potential\" of an industry enterprise and a cluster; the authors have considered 13 stages of digital potential measurement for the industrial cluster, including the following: identification of measurement parameters, classification of parameters by 6 subpotentials, expert evaluation of parameters, tabulation of the obtained expert survey results, selection of most significant parameters, final preparation of groups of factors, determination of a scale and units of measure for every selected factor to evaluate, collection of information from accessible sources, reduction of the received data to a unified measurement system, calculation of an integral index based on the developed scales, final stage includes guideline development. On the basis of the presented stages the authors worked out a relevant measurement algorithm, novelty and peculiarity of which imply allowance for indicators that characterize cluster digitalization (i.e. digital potential) when calculating a final integral value.","PeriodicalId":368926,"journal":{"name":"Proceedings of the 2019 International SPBPU Scientific Conference on Innovations in Digital Economy","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Development of Algorithm to Measure Digital Potential of High-tech Industrial Cluster\",\"authors\":\"A. Babkin, L. Tashenova, D. Mamrayeva, P. Azimov\",\"doi\":\"10.1145/3372177.3373352\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Industry 4.0, which is aimed at the global introduction of cyber-physical systems into industry, has determined further development pathways for cluster systems; one of the pathways is digitalization of business processes, which enables cutting costs significantly, manufacturing a high-tech innovative product, reducing time for communication between all the participants in the industrial cluster, revealing new sources for project funding, simplifying human work via relevant software and robotics adopted in the industry. All these factors become more urgent in the framework of functioning high-tech industrial clusters, which have not evolved only from the protocluster to the innovative active industrial cluster, but overtook their rivals by using these innovative available tools of the digital economy. In this paper the authors have presented a range of the most applicable methods to measure the digital potential of the industrial cluster (in regard to quantity, quality and mixed research methods); they have reviewed the literature that reveal the concept \\\"innovative potential\\\" of an industry enterprise and a cluster; the authors have considered 13 stages of digital potential measurement for the industrial cluster, including the following: identification of measurement parameters, classification of parameters by 6 subpotentials, expert evaluation of parameters, tabulation of the obtained expert survey results, selection of most significant parameters, final preparation of groups of factors, determination of a scale and units of measure for every selected factor to evaluate, collection of information from accessible sources, reduction of the received data to a unified measurement system, calculation of an integral index based on the developed scales, final stage includes guideline development. On the basis of the presented stages the authors worked out a relevant measurement algorithm, novelty and peculiarity of which imply allowance for indicators that characterize cluster digitalization (i.e. digital potential) when calculating a final integral value.\",\"PeriodicalId\":368926,\"journal\":{\"name\":\"Proceedings of the 2019 International SPBPU Scientific Conference on Innovations in Digital Economy\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2019 International SPBPU Scientific Conference on Innovations in Digital Economy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3372177.3373352\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2019 International SPBPU Scientific Conference on Innovations in Digital Economy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3372177.3373352","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

摘要

旨在将信息物理系统引入全球工业的工业4.0确定了集群系统的进一步发展路径;其中一个途径是业务流程的数字化,这可以显著降低成本,制造高科技创新产品,减少产业集群中所有参与者之间的沟通时间,揭示项目资金的新来源,通过行业中采用的相关软件和机器人简化人力工作。所有这些因素在高科技产业集群的运作框架中变得更加紧迫,高科技产业集群不仅从原始集群演变为创新的活跃产业集群,而且通过使用这些创新的数字经济可用工具超越了竞争对手。在本文中,作者提出了一系列最适用于衡量产业集群数字潜力的方法(在数量、质量和混合研究方法方面);他们回顾了揭示产业企业和集群“创新潜力”概念的文献;作者考虑了产业集群数字潜力测量的13个阶段,包括:确定测量参数,按6个子势对参数进行分类,对参数进行专家评价,将获得的专家调查结果制表,选择最显著的参数,最终编制因子组,确定要评价的每个选定因子的尺度和度量单位,从可访问的来源收集信息,将接收到的数据简化为统一的测量系统,在开发的量表基础上计算一个积分指标,最后阶段包括指南的制定。在提出的阶段的基础上,作者制定了一个相关的测量算法,其新颖性和独特性意味着在计算最终积分值时考虑到集群数字化特征指标(即数字潜力)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Development of Algorithm to Measure Digital Potential of High-tech Industrial Cluster
Industry 4.0, which is aimed at the global introduction of cyber-physical systems into industry, has determined further development pathways for cluster systems; one of the pathways is digitalization of business processes, which enables cutting costs significantly, manufacturing a high-tech innovative product, reducing time for communication between all the participants in the industrial cluster, revealing new sources for project funding, simplifying human work via relevant software and robotics adopted in the industry. All these factors become more urgent in the framework of functioning high-tech industrial clusters, which have not evolved only from the protocluster to the innovative active industrial cluster, but overtook their rivals by using these innovative available tools of the digital economy. In this paper the authors have presented a range of the most applicable methods to measure the digital potential of the industrial cluster (in regard to quantity, quality and mixed research methods); they have reviewed the literature that reveal the concept "innovative potential" of an industry enterprise and a cluster; the authors have considered 13 stages of digital potential measurement for the industrial cluster, including the following: identification of measurement parameters, classification of parameters by 6 subpotentials, expert evaluation of parameters, tabulation of the obtained expert survey results, selection of most significant parameters, final preparation of groups of factors, determination of a scale and units of measure for every selected factor to evaluate, collection of information from accessible sources, reduction of the received data to a unified measurement system, calculation of an integral index based on the developed scales, final stage includes guideline development. On the basis of the presented stages the authors worked out a relevant measurement algorithm, novelty and peculiarity of which imply allowance for indicators that characterize cluster digitalization (i.e. digital potential) when calculating a final integral value.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Regional differentiation of digital economy development in the Russian Federation Features of the analysis of business processes of the company (on the example of customer service in a travel agency) Digitalization of the educational process: problematic issues in the context of the development of the digital economy Developing a Cybersecurity Risk Analysis System for High-Tech Equipment in Machine Industry Evaluation of Digital Transformation of Government: Russian and international systems of indicators
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1