A technology portfolio optimization model considering staged financing and moratorium period under uncertainty

被引:2
|
作者
Shaverdi, Marzieh [1 ]
Yaghoubi, Saeed [2 ]
机构
[1] Iran Univ Sci & Technol, Sch Progress Engn, Tehran, Iran
[2] Iran Univ Sci & Technol, Sch Ind Engn, Tehran, Iran
关键词
Technology portfolio optimization; Staged financing; Moratorium period; Stochastic model; Sample average approximation (SAA); DATA ENVELOPMENT ANALYSIS; PROJECT PORTFOLIO; SUPPLIER SELECTION; MANAGEMENT; FRAMEWORK;
D O I
10.1051/ro/2020036
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
Technology commercialization needs a large amount of financial resources and governments in developed and developing countries play a critical role in resource allocation to the technology commercialization, especially through "Technology Development Funds (TDFs)". But, because of resource limitations, determining high priority technologies with higher impact on the country's innovative performance and the optimal resource allocation to technology development is very important for science and technology policymakers. "Technology portfolio planning" has been developed and applied in this regard. Accordingly, a two-phase decision-making framework has been proposed. At the first phase, the priorities of technology fields are determined by using the best-worst method (BWM) and at the second phase, a two-stage stochastic technology portfolio planning model is developed by considering technological projects' risks and export market, as one of the important factor in the "Global Innovation Index" (GII) ranking. It also has been considered technology fields' priorities, staged-financing, moratorium period, reinvestment strategy, and technology readiness levels (TRL) in allocating financial resources to technological projects The main advantages of our proposed model are considering uncertainty and early signaling about under performing technological projects Due to the uncertain nature of the problem, our solution methodology is based on the Sample Average Approximation (SAA). In order to demonstrate the applicability of this model, a real case study and its computational results are presented.
引用
收藏
页码:S1487 / S1513
页数:27
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