R&D Project Selection Strategy: an empirical study in Spain (original) (raw)
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Funding R&D projects is perhaps the most important task faced by large public organizations, in charge of promoting science and technology in different countries. However, most popular ways to solve this decision problem are based on too simple decision models and weak heuristics. In this paper a new methodology is presented to assist top level managers of those organizations during the project evaluation phase until the final decision. This methodology covers the following central points: a)a measure of the global impact and probability of success as main attributes to access the quality of a R&D project; b) a way to represent the knowledge, preferences and beliefs from the top level managers, and an approach to take into account that information in the evaluation process ; c) a way to update the beliefs of the top level managers by taking into account the experience of the whole organization; d) a numerical model of the quality of a project portfolio that can be used for improving final portfolios; e) an evolutionary algorithm to explore the set of portfolios searching for the very good solutions. We also discuss the functional structure of a software application which implements the proposed methods. In some examples of real size our proposal clearly outperforms traditional methods.
Funding R&D projects is perhaps the most important task faced by large public organizations, in charge of promoting science and technology in different countries. However, most popular ways to solve this decision problem are based on too simple decision models and weak heuristics. In this paper a new methodology is presented to assist top level managers of those organizations during the project evaluation phase until the final decision. This methodology covers the following central points: a)a measure of the global impact and probability of success as main attributes to access the quality of a R&D project; b) a way to represent the knowledge, preferences and beliefs from the top level managers, and an approach to take into account that information in the evaluation process ; c) a way to update the beliefs of the top level managers by taking into account the experience of the whole organization; d) a numerical model of the quality of a project portfolio that can be used for improving...
Methodology for increasing the adoption of R & D project selection models
R&D Management, 1973
Although some studies and experiences have shown that R & D project selection models can be potentially useful decision aids, their adoption and routine use is not widespread. This lack of usage may be a consequence of the lack of attention which model builders have traditionally given to the prevailing adoption attitudes of R & D managers. A design methodology centering around the measurement of adoption attitudes has been developed and used by the authors. The methodology consists of procedures for analyzing the organizational climate relative to project selection model usage, developing an acceptable model form relative to the organizational climate, and inducing the adoption of this model form within the climate. Three case applications of the methodology are described in which negative-to-positive shifts in adoption attitudes occurred and project selection models were adopted for long-term use. These results indicate that the use of this general methodology may lead to increased formal adoption and widespread usage of project selection model forms in R & D.
Telematics and Informatics, 1986
The research and development project selection decision is concerned with the allocation of resources to a set of proposals for scientific and engineering activities. The project selection process can be viewed as a multiple-criteria decision-making problem, within the context of the long-range and strategic planning process of the firm. The purpose of this paper is explore the applicability of several approaches, including the Analytic Hierarchy Process, for priority setting and resource allocation in the industrial R&D environment. The incorporation of these models into expert support systems for R&D project selection is discussed.
R&D and innovation project selection: can optimization methods be adequate?
This article proposes a comprehensive framework for R&D and innovation project selection under uncertainty and subject to real-world constraints applicable to the Brazilian electricity sector, using a combination of integer programming formulation and a PROMETHEE-based method. The objective is to contribute to this domain by offering an approach suitable for the challenges of this sector, but also applicable to other situations involving R&D and innovation investments under similar conditions. The manuscript presents applications using real data from an electricity company. It also compares the proposed method with similar approaches found in the literature such as PROMETHEE II and V. The application revealed the best performance of the proposed framework in dealing with the sector’s regulatory constraints, which emphasize the companies’ accomplishment with R&D and innovation expenditures obligations. In this way, although R&D and innovation project selection is not a typical case of optimization, under some particular regional, sector-based or organization boundaries this can be a better solution.
Intelligent Techniques for R&D Project Selection in Large Social Organizations
Abstract Funding R&D projects is perhaps the most important task faced by large public organizations, in charge of promoting science and technology in different countries. However, most popular ways to solve this decision problem are based on too simple decision models,and weak,heuristics. In this paper a new methodology,is presented to assist top level managers ,of those ,organizations during ,the project evaluation phase ,until the final decision. This methodology,covers the following central points: a)a measure ,of the ,global impact and probability of success ,as main attributes to access the quality of a R&D project; b) a way to represent the knowledge, preferences and beliefs from the top level managers, and an approach to take into account that information in the evaluation process ; c) a way,to update the beliefs of the top level managers,by taking into account the experience of the whole organization; d)a numerical ,model ,of the ,quality of a project ,portfolio that can be...
Assessment of companies practices concerning the evaluation of R&D investment projects
12Th International Conference on Technology Policy and Innovation, 2009
This study introduces an ongoing research project aimed at analyzing the impact of R&D projects both from the public and private points of view. From the public perspective the social impacts and objectives of these projects, frequently supported by National or European R&D programmes, should be underlined and properly considered in the evaluation process. On the other hand, the private perspective emphasizes mainly financial and strategic returns for the companies involved in research projects. This paper addresses part of the research conducted so far, focusing in particular on the private perspective, namely on the identification of the more appropriate methods for the evaluation of research and development (R&D) investments projects by companies. Several studies indicate that the use of traditional financial methods is not the most appropriate for evaluating R&D projects (see, for example, Chan, 2001, Proctor and Canada, 1992, and Mensah and Miranti, 1989). The use of these methods consists, basically, on discounting the expected future cash flows and the adoption of several methods for measuring its financial viability (e.g. NPV, IRR). This implies that the costs and benefits associated with the investment are easily and objectively quantified. Nevertheless this is not always possible for all types of investments, particularly in the Advanced Manufacturing Technology (AMT), in Information and Communication Technologies (ICT), or in projects of R&D. For these type of investments, the estimation of financial flows and the assessment of their risks tend to be different from general tangible investments. This is particularly important in the calculation of benefits, which can be of three types: strategic, quantifiable and intangible. For example, the intangible benefits are difficult to quantify but may have a significant impact on return on investment (Adler, 2000). Moreover, has been witnessing an increasing trend for companies to include non-financial dimensions/variables (e.g. strategy, flexibility and quality) of the problem in their decision-making process on investment projects. Indeed, these non-financial aspects are particularly important in the new industrial environment in which companies today operate, where new technological developments tend to occur more rapidly than the development of methods for the evaluation of investment projects (Brownell and Merchant, 1990). One of the objectives of this paper is to present an up-to-date state-of-the-art regarding the non-financial techniques that have been proposed to evaluate investment projects in research and development (R&D). Indeed, the evaluation of such projects, although often conducted purely in the perspective of business profitability, cannot be reduced to a simple analysis of discounted cash flows, since these projects often provide strategic gains that could hardly be translated into quantifiable monetary benefits in the short term. Moreover, there are also other factors that are difficult to measure/quantify, such as: political issues, environmental impacts, knowledge, intuition, or experience. As a result, this study discusses several non-financial criteria to be considered in the evaluation of R&D projects, which have been proposed in the literature related to products manufacturing, environmental, employment, users of the results of R&D, competitiveness of technology, relevance of technology, economic benefit, social benefit, quality of technical plan, availability of resource, technical risk, development risk, commercial risk, and return of investment. A second objective is to conduct an inquiry to a sample of metallurgical companies in northern Portugal and southern Galicia in order to assess which practices have been used to evaluate R&D investments. In fact, this would allow us to gain an insight concerning both the financial and non-financial criteria used and if they use software support, as well as the importance of certain non-financial criteria in the evaluation of projects. Moreover we are trying to see if they currently use any of the multi-criteria methods. The ultimate goal of this research would be to propose an integrated methodology that can be applied to the evaluation of R&D projects, based on financial and non-financial methods using multi-criteria techniques. The purpose of multi-criteria models is to break a complex problem into simpler parts. That allows the decision-maker to structure a problem with many criteria in a visual way, through the construction of a hierarchical model that basically contains three levels: aim or objective, criteria and alternatives. Once the model is built, two by two comparisons are made between these elements (criteria-subcriteria and alternatives) and numerical values are given to the preferences assigned by individuals, therefore obtaining a summary value by aggregating this partial judgements (Rodríguez, 2008).
An R&D options selection model for investment decisions
Technovation, 2005
Technology centered organisations must be able to identify promising new products or process improvements at an early stage so that the necessary resources can be allocated to those activities. It is essential to invest in targeted R&D projects as opposed to a wide range of ideas so that resources can be focused on successful outcomes. Typically, a number of options and tradeoffs are encountered; the selection of the most appropriate projects is the aim of R&D selection models. Although capital budgeting and financial portfolio management offer a similar style approach, the techniques used for the solution of those is different to that used for R&D project selection. The reasons for this are that project selection is complicated by many factors, such as uncertainty, interrelationships between projects, changes over time and success factors that are difficult to measure. Thus, a mathematical optimisation approach in isolation is not practical. Project selection models not only have to consider these problems but also that there are different types of R&D. The spectrum of R&D ranges from low budget exploratory research to large budget product development. This paper reviews the development of a project selection and evaluation tool that can be applied to a wide range of research, technology and investment decisions. Firstly, the background on project selection models is given. This is followed by the introduction of the model and its application to a sample group of projects. Finally, some conclusions are discussed as to the applicability of such models. q
R&D and Innovation Project Selection: Can Optimization Methods be Adequate?
Procedia Computer Science, 2015
This article proposes a comprehensive framework for R&D and innovation project selection under uncertainty and subject to real-world constraints applicable to the Brazilian electricity sector, using a combination of integer programming formulation and a PROMETHEE-based method. The objective is to contribute to this domain by offering an approach suitable for the challenges of this sector, but also applicable to other situations involving R&D and innovation investments under similar conditions. The manuscript presents applications using real data from an electricity company. It also compares the proposed method with similar approaches found in the literature such as PROMETHEE II and V. The application revealed the best performance of the proposed framework in dealing with the sector's regulatory constraints, which emphasize the companies' accomplishment with R&D and innovation expenditures obligations. In this way, although R&D and innovation project selection is not a typical case of optimization, under some particular regional, sector-based or organization boundaries this can be a better solution.