{"title":"Stratified network mapping decision making technique based decision support framework for R&D budget allocation in South Korea","authors":"Selvaraj Geetha, JeongHwan Jeon","doi":"10.1016/j.seps.2023.101579","DOIUrl":null,"url":null,"abstract":"<div><p>In this research work, we proposed and developed a stratified network mapping (SNM) decision making method and used it to improve the industry–university specialization in R&D in each region selected in this study. The proposed method considers the influence of criteria on and their priority in alternatives performance evaluation process. By analyzing the influence of these criteria on decision-making, we can easily improve the performance of alternatives. The SNM gives a clear understanding of each alternatives performance efficiency level. It explores possible and inefficient states and high-level influence states in inefficient states. Narrowly using multi-criteria decision-making methods to rank alternatives does not improve the performance of alternatives. The proposed method helps rank alternatives and improve the performance level of alternatives in each state. We analyzed the R&D investment of central and local governments of South Korea. It is an attempt to invigorate and facilitate R&D collaboration using a decision support model. We analyzed industry–academia research networks and enhanced the efficiency of the research.</p></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"87 ","pages":"Article 101579"},"PeriodicalIF":6.2000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Socio-economic Planning Sciences","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0038012123000794","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
In this research work, we proposed and developed a stratified network mapping (SNM) decision making method and used it to improve the industry–university specialization in R&D in each region selected in this study. The proposed method considers the influence of criteria on and their priority in alternatives performance evaluation process. By analyzing the influence of these criteria on decision-making, we can easily improve the performance of alternatives. The SNM gives a clear understanding of each alternatives performance efficiency level. It explores possible and inefficient states and high-level influence states in inefficient states. Narrowly using multi-criteria decision-making methods to rank alternatives does not improve the performance of alternatives. The proposed method helps rank alternatives and improve the performance level of alternatives in each state. We analyzed the R&D investment of central and local governments of South Korea. It is an attempt to invigorate and facilitate R&D collaboration using a decision support model. We analyzed industry–academia research networks and enhanced the efficiency of the research.
期刊介绍:
Studies directed toward the more effective utilization of existing resources, e.g. mathematical programming models of health care delivery systems with relevance to more effective program design; systems analysis of fire outbreaks and its relevance to the location of fire stations; statistical analysis of the efficiency of a developing country economy or industry.
Studies relating to the interaction of various segments of society and technology, e.g. the effects of government health policies on the utilization and design of hospital facilities; the relationship between housing density and the demands on public transportation or other service facilities: patterns and implications of urban development and air or water pollution.
Studies devoted to the anticipations of and response to future needs for social, health and other human services, e.g. the relationship between industrial growth and the development of educational resources in affected areas; investigation of future demands for material and child health resources in a developing country; design of effective recycling in an urban setting.