A Consistent Fuzzy Preference Relations Based ANP Model for R&D Project Selection

Abstract

In today's rapidly changing economy, technology companies have to make decisions on research and development (R&D) projects investment on a routine bases with such decisions having a direct impact on that company's profitability, sustainability and future growth. Companies seeking profitable opportunities for investment and project selection must consider many factors such as resource limitations and differences in assessment, with consideration of both qualitative and quantitative criteria. Often, differences in perception by the various stakeholders hinder the attainment of a consensus of opinion and coordination efforts. Thus, in this study, a hybrid model is developed for the consideration of the complex criteria taking into account the different opinions of the various stakeholders who often come from different departments within the company and have different opinions about which direction to take. The decision-making trial and evaluation laboratory (DEMATEL) approach is used to convert the cause and effect relations representing the criteria into a visual network structure. A consistent fuzzy preference relations based analytic network process (CFPR-ANP) method is developed to calculate the preference-weights of the criteria based on the derived network structure. The CFPR-ANP is an improvement over the original analytic network process (ANP) method in that it reduces the problem of inconsistency as well as the number of pairwise comparisons. The combined complex proportional assessment (COPRAS-G) method is applied with fuzzy grey relations to resolve conflicts arising from differences in information and opinions provided by the different stakeholders about the selection of the most suitable R&D projects. This novel combination approach is then used to assist an international brand-name company to prioritize projects and make project decisions that will maximize returns and ensure sustainability for the company.

Advances in Multiple Criteria Decision Making for Sustainability: Modeling and Applications

“…The seventh paper [22] also attempts to resolve the R&D project selection problem; it presumes that the superior R&D projects are a crucial factor for technology companies to sustain in the long-term. Also, the risk-return preference should be different in each tech company; thus, how to measure and model individual risk attitude should be incorporated in an evaluation system.…”

Systemic Functions Evaluation based Technological Innovation System for the Sustainability of IoT in the Manufacturing Industry

“…Step is divided by the maximum value of every rough interval number, as illustrated in Equations (19) to (22):…”

“…The fuzzy and grey theories are representative examples. The incorporation of these two theories into the MCDM model has been used to solve a great number of issues, such as project selection [22], performance evaluation [23], evaluation of renewable energy resources [24], and selection of sustainable recycling partners [25]. Rough interval numbers, which recently have received much more attention, is another effective approach that can be utilized to deal with imprecise numeric values in decision data and subjectively collective judgments without defining membership function.…”

Methods of Development of Coordinated Managerial Decisions for Selection of Efficient Projects. Part 1

“…Покровского [9]. Постоянно предлагаются всевозможные пути модернизации МАИ для устранения проблем или расширения границ его применения зарубежными ученными [20,21,22,25,32,35,51,52]. До конца своей жизни (14.08.2017) Т. Саати не прекращал процесс модернизации МАИ в разных научных трудах [10, 11, 12, 36-42, 44, 45, 49, 50].…”