Industrial R&D project portfolio selection method using a multi-objective optimization program: A conceptual quantitative framework

Abstract

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 techniques. 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.