Carbon neutrality targets and optimal policy: a multicriteria analysis

Abstract

Purpose This study explores how public policy and individual behavior interact to achieve carbon neutrality targets, aiming to identify the optimal incentive structure that balances short-term mitigation costs and long-term sustainability goals. Design/methodology/approach A dynamic model integrates discrete choice and social interaction frameworks, where agents decide whether to act green and policymakers design subsidies accordingly. The multicriteria optimization problem is solved using both scalarization and e-constraint methods to compare their outcomes. Findings The optimal subsidy depends on social and individual factors such as conformism, time preference and sustainability concern. Complete carbon neutrality is not optimal; a controlled deviation minimizes overall social cost. The scalarization and e-constraint methods yield equivalent, convex efficient frontiers between short- and long-term objectives. Originality/value This paper is the first to couple optimal dynamic policymaking with a discrete choice model of green transition using the e-constraint method. It offers methodological and policy insights for designing realistic, efficiency-oriented climate strategies.