Successful technology transfer requires identifying the goals of the industry, technologies needed, technological resources, transfer methods and factors affecting it, how to absorb and develop it, and to do any of these requires the use of relevant specialists. Without the use of experts in this field, the transfer of the desired technology is usually incomplete and inappropriate and at a distance from the original goal. Technology transfer is a complex and difficult process, and without the necessary study, it is not only not useful, but may, in addition to wasting capital and time, weaken national technology. The technology transfer process has some precautionary and preventive scales that must be addressed before considering the technology transfer model. These factors include: Awareness of the important and basic factors required for technology transfer, knowing the factors of technology transfer failure in the past and continuous search for the appropriate technology to obtain the appropriate internal position and communication with existing and older technologies. In this study, we will use a weighted arithmetic mean to rank and evaluate the final factors affecting technology transfer. Operating room medical equipment was considered as a case study. The results showed that "application", "selection and appropriateness" and "organizational factors" ranked first to third.
{"title":"Identifying the Factors Affecting the Transfer of Operating Room Medical Equipment Technology and Prioritizing Them Using the Weighted Mean Method","authors":"H. Eghbali, Masoud Ahmadvand","doi":"10.2139/ssrn.3786352","DOIUrl":"https://doi.org/10.2139/ssrn.3786352","url":null,"abstract":"Successful technology transfer requires identifying the goals of the industry, technologies needed, technological resources, transfer methods and factors affecting it, how to absorb and develop it, and to do any of these requires the use of relevant specialists. Without the use of experts in this field, the transfer of the desired technology is usually incomplete and inappropriate and at a distance from the original goal. Technology transfer is a complex and difficult process, and without the necessary study, it is not only not useful, but may, in addition to wasting capital and time, weaken national technology. The technology transfer process has some precautionary and preventive scales that must be addressed before considering the technology transfer model. These factors include: Awareness of the important and basic factors required for technology transfer, knowing the factors of technology transfer failure in the past and continuous search for the appropriate technology to obtain the appropriate internal position and communication with existing and older technologies. In this study, we will use a weighted arithmetic mean to rank and evaluate the final factors affecting technology transfer. Operating room medical equipment was considered as a case study. The results showed that \"application\", \"selection and appropriateness\" and \"organizational factors\" ranked first to third.","PeriodicalId":240300,"journal":{"name":"DecisionSciRN: Multi-Criteria Decision-Making (MCDM) Methods (Topic)","volume":"184 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125835165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
It is yet to be determined whether the firms’ operational inefficiency is reflected on the Corporate Social Responsibility (CSR) engagement approach. This paper aims to examine this association and specifically analyzes to which of the dimensions of CSR operational inefficiency is more closely related. Operational inefficiency is assessed using Data Envelopment Analysis (DEA) via dynamic inefficiency approach that accounts for the confounding role of adjustment costs related with firms’ investments. Using a sample of U.S. firms in a variety of sectors from 2004 to 2015, we find that lower dynamic inefficiency occurs in firms with a higher commitment to CSR activities. We also find that dynamic inefficiency is negatively related to firms’ engagement in social and corporate governance dimensions of CSR, whereas it is positively associated with the environmental dimension of CSR. In addition, dynamically inefficient companies have higher level of CSR concerns and lower of CSR strengths. The results are robust to endogeneity issues.
{"title":"Corporate Social Responsibility and Operational Inefficiency: A Dynamic Approach","authors":"Encarna Guillamón-Saorín, M. Kapelko, S. Stefanou","doi":"10.2139/ssrn.3148746","DOIUrl":"https://doi.org/10.2139/ssrn.3148746","url":null,"abstract":"It is yet to be determined whether the firms’ operational inefficiency is reflected on the Corporate Social Responsibility (CSR) engagement approach. This paper aims to examine this association and specifically analyzes to which of the dimensions of CSR operational inefficiency is more closely related. Operational inefficiency is assessed using Data Envelopment Analysis (DEA) via dynamic inefficiency approach that accounts for the confounding role of adjustment costs related with firms’ investments. Using a sample of U.S. firms in a variety of sectors from 2004 to 2015, we find that lower dynamic inefficiency occurs in firms with a higher commitment to CSR activities. We also find that dynamic inefficiency is negatively related to firms’ engagement in social and corporate governance dimensions of CSR, whereas it is positively associated with the environmental dimension of CSR. In addition, dynamically inefficient companies have higher level of CSR concerns and lower of CSR strengths. The results are robust to endogeneity issues.","PeriodicalId":240300,"journal":{"name":"DecisionSciRN: Multi-Criteria Decision-Making (MCDM) Methods (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126997658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Muhammad Fawad Ahmad, M. Ishtiaq, K. Hamid, Muhammad Usman Khurram, A. Nawaz
This research is performed for dealing with some of the important working capital management policies and efficiency regarding to manufacturing sector of Pakistan. For this purpose data from 37 firms have been taken for the period 2009-2014. Data envelopment analysis (DEA) and Tobit regression analysis has been performed to achieve the objective of this study. DEA results indicate that only fifteen companies require increase in inputs to attain better output whereas six companies require decrease in the input. However sixteen companies have to consistent with their existing proportionate of inputs to sustain the output maximization. Tobit regression analysis concludes that average collection period has significant negative impact on efficiency and current ratio, gross working capital turnover ratio and financial leverage ratio have positive significant impact on efficiency.
{"title":"Data Envelopment Analysis and Tobit Analysis for Firm Efficiency in Perspective of Working Capital Management in Manufacturing Sector of Pakistan","authors":"Muhammad Fawad Ahmad, M. Ishtiaq, K. Hamid, Muhammad Usman Khurram, A. Nawaz","doi":"10.2139/ssrn.2911577","DOIUrl":"https://doi.org/10.2139/ssrn.2911577","url":null,"abstract":"This research is performed for dealing with some of the important working capital management policies and efficiency regarding to manufacturing sector of Pakistan. For this purpose data from 37 firms have been taken for the period 2009-2014. Data envelopment analysis (DEA) and Tobit regression analysis has been performed to achieve the objective of this study. DEA results indicate that only fifteen companies require increase in inputs to attain better output whereas six companies require decrease in the input. However sixteen companies have to consistent with their existing proportionate of inputs to sustain the output maximization. Tobit regression analysis concludes that average collection period has significant negative impact on efficiency and current ratio, gross working capital turnover ratio and financial leverage ratio have positive significant impact on efficiency.","PeriodicalId":240300,"journal":{"name":"DecisionSciRN: Multi-Criteria Decision-Making (MCDM) Methods (Topic)","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127592076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This is a course material from the book Investment Decision Making. For Firm and Project Valuation. The book is originally in Spanish and is untitled as Decisiones de inversion. Para la valoracion financiera de proyectos y empresas. Chapter 12 studies the problem of making decisions under risk and uncertainty. We present basic ideas on sensitivity analysis for one and several variables, game theory, decision trees, cardinal utility theory and Montecarlo simulation. We include some new subjects such as the Analytical Hierarchical Process, AHP and the Analytic Network Process, ANP, methods Developer by professor Thomas L. Saaty and a very short introduction to financial and real options.
这是《投资决策》一书中的课程材料。公司和项目评估。这本书最初是用西班牙语写成的，并没有命名为《倒置的决定》。Para - value - value - value - value - value - value - value - value第12章研究了风险和不确定性下的决策问题。本文介绍了单变量和多变量敏感性分析、博弈论、决策树、基数效用理论和蒙特卡罗模拟的基本思想。我们包括一些新的科目，如分析层次过程，AHP和分析网络过程，ANP，方法开发由托马斯L. Saaty教授和一个非常简短的介绍金融和实物期权。
{"title":"12 Decision Making Under Uncertainty","authors":"Ignacio Vélez-Pareja","doi":"10.2139/SSRN.882886","DOIUrl":"https://doi.org/10.2139/SSRN.882886","url":null,"abstract":"This is a course material from the book Investment Decision Making. For Firm and Project Valuation. The book is originally in Spanish and is untitled as Decisiones de inversion. Para la valoracion financiera de proyectos y empresas. Chapter 12 studies the problem of making decisions under risk and uncertainty. We present basic ideas on sensitivity analysis for one and several variables, game theory, decision trees, cardinal utility theory and Montecarlo simulation. We include some new subjects such as the Analytical Hierarchical Process, AHP and the Analytic Network Process, ANP, methods Developer by professor Thomas L. Saaty and a very short introduction to financial and real options.","PeriodicalId":240300,"journal":{"name":"DecisionSciRN: Multi-Criteria Decision-Making (MCDM) Methods (Topic)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131095335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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