A Decision Support Scoring Tool for Optimal Selection of R&D Investments in Mining and Metals Industry: A Hybrid Model of FAHP and MAUT

For decades, vast studies have been conducted to show empirical evidence that Research and Development (R&D;) investments lead to increased firm and market performance, increased rate of returns and productivity. Optimizing selection of R&D; investments among different possible opportunities is crucial to maximize value but faces challenges of subjectivity and uncertainty. Companies within the mining industry have limited resources for R&D; investments and traditionally relied on personal experience and intuition for decision-making, which is prone to subjectivity and bias. Importantly, the presence of uncertainty and a plethora of different options, criteria, and factors such as risk preferences tend to create a tedious and complex process for selecting the most optimal R&D; investment option.Multi-Criteria Decision Analysis (MCDA) techniques have been introduced to address such a challenge, yet the existing methods often focus on simplicity rather than optimality. Therefore, this praxis aims to develop a hybrid model that combines Fuzzy Analytical Hierarchy Process (FAHP) with Multi-Attribute Utility Theory (MAUT) as a decision support scoring tool to help decision-makers achieve optimal results when faced with diverse R&D; investment opportunities and criteria. The praxis used practical data from a report compiled by a private consulting firm specialized in innovation in the mining and metals industry. The report consists of a large number of R&D; investment opportunities by various leading companies within the mining industry. It also provides a list of attributes associated with the opportunities and domain experts’ views. The praxis analyzed the data from the report. The statistical analysis was performed through SPSS and MiniTab that involved a t-test, one-way ANOVA, Pearson correlation, and regression analysis. FAHP and MAUT calculations were performed via python programming and a sensitivity analysis was conducted to verify the validity of the results. The results demonstrate that the developed model can be utilized as a tool to mitigate subjectivity and provide a more objective and reliable ranking over the long term. It also highlights the interdependence between selected attributes and the context of investment opportunities. Attributes alone are necessary but not sufficient to influence rankings holistically. The model can heighten awareness among decision-makers in the mining industry and beyond, instigating them to adopt this tool for their decision-making processes. Ultimately, the praxis's findings shed light on the interplay between attributes and investment contexts, emphasizing their interdependence. By adopting this model as a tool, decision-makers can make better-informed and more optimal choices and enhance their decision-making processes in the mining industry and other sectors.

Author

• Almandil, Saud

Language

• en

Date created

• 2024

Type of Work

• Dissertation

License

• All rights reserved

Rights statement

• In Copyright

GW Unit

• Engineering Management

Degree

• D.Engr.

Advisor

• Stirgwolt, Benjamin

Committee Member(s)

• Etemadi, Amir
• Stirgwolt, Benjamin
• Ali, Daniyal

Persistent URL

•  https://scholarspace.library.gwu.edu/etd/tb09j6542