دانلود مقاله ISI انگلیسی شماره 17404
عنوان فارسی مقاله

انتخاب پرتفوی متعادل از پروژه های "تحقیق و توسعه" با وابستگی های متقابل:یک روش مبتنی بر آنتروپی متقاطع

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
17404 2014 10 صفحه PDF سفارش دهید 9100 کلمه
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Selecting balanced portfolios of R&D projects with interdependencies: A Cross-Entropy based methodology
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Technovation, Volume 34, Issue 1, January 2014, Pages 54–63

کلمات کلیدی
& انتخاب نمونه کارهای تحقیق و توسعه پروژه - مقادیر پرتفوی - ریسک تجزیه و تحلیل - وابستگی های بین منابع - آنتروپی متقاطع -
پیش نمایش مقاله
پیش نمایش مقاله انتخاب پرتفوی متعادل از پروژه های "تحقیق و توسعه" با وابستگی های متقابل:یک روش مبتنی بر آنتروپی متقاطع

چکیده انگلیسی

The intensive growth of technology makes firms rely on research and development (R&D) activities in order to adapt to technology changes in an ever-changing and uncertain environment. Due to R&D budget constraints and limited resources, firms are often forced to select a subset of all candidate projects by means of project portfolio selection techniques mitigating the corresponding risks and enhancing the overall value of portfolio. Projects' interdependencies and types were rarely considered in existing models of R&D portfolio selection that may result in selecting wrong projects. This flaw hinders the projects alignment with corporate objectives and strategy and leads to excessive risk and missing the promised values. In this paper, a balanced set of R&D project evaluation criteria was proposed. Next, to construct R&D project portfolio, a 0–1 nonlinear mathematical programming method for balancing portfolio values and risks was proposed, in which research projects' interdependencies, types and other constraints were all considered. Finally, a Cross-Entropy algorithm was developed to solve the proposed model and results were reported. The algorithm proved to be very effective in terms of solution quality and computational time. The proposed algorithm especially suits large scale instances while exact approaches are doomed to fail.

مقدمه انگلیسی

Increasing complexity of technologies along with their rapid growth is forcing firms to rely on research and development (R&D) as a survival tool to achieve a strong competitive position in future. The importance of R&D as one of the main contributors to sustainable growth in highly industrialized economies is undisputable among economists, especially in the context of the modern knowledge based economies (Santamaría et al., 2010). Considering these leading factors, there has been an increasing interest in the area of portfolio selection of R&D projects, in recent years.

نتیجه گیری انگلیسی

The increasing complexity of technologies and globalization of markets are forcing many firms to rely on R&D as a source of strategy for long-term growth in response to these developments. In such a situation, managers have to manage R&D projects much more effectively than the past. R&D project portfolio selection is a rather complex task using various tools to choose among large number of feasible projects considering various project values versus risks, interdependencies and other constraints. In this paper, a 0–1 nonlinear integer programming model was proposed which met all the mentioned facets. This model considered objective of maximizing R&D project portfolio values while taking into account various types of R&D projects, uncertain nature of these projects and their interdependencies. This research showed the facility with which an R&D manager can construct the organizations' R&D project portfolio by accurate assessment of the key variables affecting portfolio values. In addition to making the proposed model more compatible with real world, the distinguished types of R&D project portfolio risks were considered a term of model objective function. Additional benefit of the extended model was to include all types of research which would be an enhancement to the R&D project portfolio selection process.

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