A participative approach to program evaluation

Kocaoglu, Dundar F.

doi:10.1109/tem.1983.6448602

Cited by 113 publications

(75 citation statements)

References 3 publications

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“…There is group disagreement if the disagreement exceeds a value of 0.10 and a value of 0 would imply complete agreement among the experts [172]. The disagreement index is presented in Kocaoglu's work [93] and determined by the following equations:…”

Section: Disagreement and Clusteringmentioning

confidence: 99%

Development of a Technology Transfer Score for Evaluating Research Proposals: Case Study of Demand Response Technologies in the Pacific Northwest

Estep¹

2000

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Investment in Research and Development (R&D) is necessary for innovation,allowing an organization to maintain a competitive edge. The U.S. Federal Government invests billions of dollars, primarily in basic research technologies to help fill the pipeline for other organizations to take the technology into commercialization. However, as Lewis Duncan suggests, it is not about just investing in innovation, it is about converting that research into application. A cursory review of the research proposal evaluation criteria suggests that there is little to no emphasis placed on the transfer of research results. This effort is motivated by a need to move research into application.One segment that is facing technology challenges is the energy sector.Historically, the electric grid has been stable and predictable; therefore, there were no immediate drivers to innovate. However, an aging infrastructure, integration of renewable energy, and aggressive energy efficiency targets are motivating the need for research and to put promising results into application. Many technologies exist or are in development but the rate at which they are being adopted is slow.The goal of this research is to develop a decision model that can be used to identify the technology transfer potential of a research proposal. An organization can use the model to select the proposals whose research outcomes are more likely to move into application. The model begins to close the chasm between research and application -otherwise known as the "valley of death".ii A comprehensive literature review was conducted to understand when the idea of technology application or transfer should begin. Next, the attributes that are necessary for successful technology transfer were identified. The emphasis of successful technology transfer occurs when there is a productive relationship between the researchers and the technology recipient. A hierarchical decision model, along with desirability curves, was used to understand the complexities of the researcher and recipient relationship, specific to technology transfer. In this research, the evaluation criteria of several research organizations were assessed to understand the extent to which the success attributes that were identified in literature were considered when reviewing research proposals. While some of the organizations included a few of the success attributes, none of the organizations considered all of the attributes. In addition, none of the organizations quantified the value of the success attributes.The effectiveness of the model relies extensively on expert judgments to complete the model validation and quantification. Subject matter experts ranging from senior executives with extensive experience in technology transfer to principal research investigators from national labs, universities, utilities, and non -profit research organizations were used to ensure a comprehensive and cross-functional validation and quantification of the decision model.The quantified model was validated using a case study i...

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Section: Disagreement and Clusteringmentioning

confidence: 99%

Development of a Technology Transfer Score for Evaluating Research Proposals: Case Study of Demand Response Technologies in the Pacific Northwest

Estep¹

2000

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“…The Hierarchical Decision Model (HDM) [2] which is a variant of Saaty's Analytic Hierarchy Process (AHP) [3] is a widely-accepted multi-criteria decision-making tool.…”

Section: List Of Tablesmentioning

confidence: 99%

“…One such method is the Hierarchical Decision Model (HDM) proposed by Kocaoglu [2]. It is a variant of AHP.…”

Section: The Hierarchical Decision Model (Hdm) 13mentioning

confidence: 99%

Consistency Analysis for Judgment Quantification in Hierarchical Decision Model

Abbas¹

2000

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The objective of this research is to establish consistency thresholds linked to alpha () levels for HDM's (Hierarchical Decision Model) judgment quantification method.Measuring consistency in order to control it is a crucial and inseparable part of any AHP/HDM experiment. The researchers on the subject recommend establishing thresholds that are statistically based on hypothesis testing, and are linked to the number of decision variables and  level. Such thresholds provide the means with which to evaluate the soundness and validity of an AHP/HDM decision. The linkage of thresholds to  levels allows the decision makers to set an appropriate inconsistency tolerance compatible with the situation at hand. The measurements of judgments are unreliable in the absence of an inconsistency measure that includes acceptable limits.All of this is essential to the credibility of the entire decision making process and hence is extremely useful for practitioners and researchers alike. This research includes distribution fitting for the inconsistencies. It is a valuable and interesting part of the research results and adds usefulness, practicality and insight. The superb fits obtained give confidence that all the statistical inferences based on the fitted distributions accurately reflect the HDM's inconsistency measure.

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“…In addition, the pair-wise comparison is used to help make decisions, and Satty suggests using a 1-9 scale measurement and eigenvector [145]. While Kocaoglu suggests using 100 points between each pair [146].…”

Section: Analytic Hierarchy Process (Ahp)mentioning

confidence: 99%

“…In addition, the pair-wise comparison helps in making decisions, and Saaty specifies the use of the 1-9 scale measurement and eigenvector [145]. While Kocaoglu specifies the use of 100 points between each pair [146]. The 100 points are more convenient than the 1-9 scale because experts have more flexibility to determine between 100 points while 1-9 scale isn't as flexible [225].…”

Section: Introductionmentioning

confidence: 99%

Technology Assessment Model of Developing Geothermal Energy Resources for Supporting Electrical System: The Case for Oregon

Alshareef¹

2000

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The demand for energy is increasing worldwide. All applications contributed to increase the demand of all energy industry, and therefore the effect on the environment and the rise in pollution increased significantly. This is considered a large problem, and researchers focused their research on renewable energy for reducing the cost of energy in the future. Geothermal energy has significant impact as a source of electricity generation since it will not harm the environment. There are more than twenty countries that benefit from geothermal plants, which generate more than 6000 megawatts .Three alternatives of geothermal energy technology (GHP, Direct use of Geothermal Heat, and Geothermal Electricity) can be used for supporting electrical systems in Oregon. At the same time, the success of using the geothermal energy alternatives in Oregon relies on different goals for achieving the best geothermal development. Oregon has been ranked third in the potential use of geothermal energy after Nevada and California.The objective from the research study was to develop an assessment model framework that can be used for supporting cost effective renewable energy in Oregon by the development of geothermal energy sources. This research of study was done by using

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A participative approach to program evaluation

Cited by 113 publications

References 3 publications

Development of a Technology Transfer Score for Evaluating Research Proposals: Case Study of Demand Response Technologies in the Pacific Northwest

Development of a Technology Transfer Score for Evaluating Research Proposals: Case Study of Demand Response Technologies in the Pacific Northwest

Consistency Analysis for Judgment Quantification in Hierarchical Decision Model

Technology Assessment Model of Developing Geothermal Energy Resources for Supporting Electrical System: The Case for Oregon

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