Industrial R&D Project Portfolio Selection Method Using A Multi-Objective Optimization Program: A Conceptual Quantitative Framework

Abstract

Purpose: Industrial R&D Project Portfolio Selection Method using a Multi-Objective Optimization Program – a Conceptual Quantitative Framework. Design/methodology/approach: Research and development (R&D) activities are crucial if companies are to adapt to technology changes, but budget constraints and limited resources often force companies to select a subset of candidate projects through portfolio selection methods. However, existing models for R&D portfolio selection do not adequately consider interdependencies and types of projects, and this can lead to suboptimal selection and misalignment with corporate objectives. Findings: A Multi-Objective Optimisation Program (MOOP) is suggested transcending from classic manpower, time, and financial planning into addition of strategic, skills and commercial objectives. A Pareto front is used as validation mechanism. Research limitations/implications: Project selection processes are widened with select and critical quantitative positions. Potentials remain in areas of team capability, corporate capabilities, deeper skill understanding, and stakeholder engagement. Practical implications: A quantitative validation is often overlooked in PPM project selection over more qualitative or idiosyncratic selection methods. Originality/value: A quantitative validation is often overlooked in PPM project selection over more qualitative or idiosyncratic selection methods.