OPERATIONS STRATEGY IN ENERGY INVESTMENT PRIORITIZATION: AN ADAPTED AHP-BASED DECISION FRAMEWORK

Abdi Nafi; Gogor Arif Handiwibowo

doi:10.26533/eksis.v21i1.1748

Abdi Nafi Institut Teknologi Sepuluh Nopember
Gogor Arif Handiwibowo Institut Teknologi Sepuluh Nopember

DOI: https://doi.org/10.26533/eksis.v21i1.1748

Keywords: Analytical Hierarchy Process, energy investment, project portfolio management, project prioritization, sustainability

Abstract

Introduction: Prioritizing investment projects in power-generation companies is a strategic operations decision because capital allocation shapes asset reliability, service continuity, organizational resilience, and energy-transition capability. This study develops a transparent managerial framework that integrates financial, technical, strategic, risk, and sustainability considerations in project selection at PT PLN Nusantara Power.

Methods: An exploratory sequential mixed-methods case study combined internal document analysis, executive contextualization, criterion assessments by Board members, and evaluations of 50 project proposals by Vice Presidents. Criterion weights were derived through an adapted Analytical Hierarchy Process, while project priorities were synthesized using a weighted additive approach.

Results: The resulting structure placed financial considerations slightly ahead of strategic, risk, sustainability, and technical considerations, indicating a balanced decision logic rather than financial dominance. Major inspections, system restoration, and maintenance projects ranked prominently, highlighting the strategic role of sustaining capital in protecting operating capability. Project priority was also not simply determined by project size. Discussion: The framework connects operations strategy with project portfolio governance by making trade-offs more visible, documenting managerial reasoning, and distinguishing technical feasibility from strategic prioritization. It offers a practical basis for more consistent capital-allocation decisions, while its context-specific design and limited expert sample require cautious application and further validation.

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