Strategic Scenario Planning for Mining-Fleet Investment Decisions Under Energy-Cost and Carbon Uncertainty

Purpose– This study examines an operations decision faced by a mining contractor: which powertrain to choose when replacing a diesel haul fleet, given that each option's merit depends on futures the firm cannot control, namely the diesel price, the cost of electric trucks, and the carbon intensity of the charging grid. Design/methodology– The study is a single embedded case study of a 28-truck haul fleet at a coal concession in Central Kalimantan, Indonesia. It applies a four-phase intuitive-logics scenario-planning cycle: identifying driving forces, isolating two critical uncertainties, energy-cost pressure and electric-vehicle accessibility, building four scenarios from their two-by-two, and comparing five powertrain pathways within each future on cost, carbon, operational risk, and disclosure readiness. Findings– Solar-powered electrification remains a reliable pathway across all four future scenarios, while diesel is only sustainable when diesel prices are low. Grid-powered electrification is the lowest-cost option but a misstep for carbon-emissions reduction, as a coal-dominated grid increases fleet emissions by 46 to 56 percent. The same energy cost factors determine the future scenarios and drive the economics of each pathway, so the right choice changes with future assumptions. The paper contributes a replicable decision architecture that couples scenario planning with real-options reasoning, giving managers of capital-intensive fleets a way to stage an irreversible electrification commitment under deep energy-cost and carbon uncertainty rather than treating it as a one-off comparison.