Overview of second study

to reduce fuel consumption are often considered easy and effective measures to improve technical energy efficiency and comply with the EEDI regulation. However, our results overall highlight the limits of this technology lever, and we would advise ship owners to see measures like design speed reductions as complements to other levers, instead of mainly relying on them.

policy makers have at their disposal to decarbonize the industry over a time horizon and meet the targets. A key backing for this claim is based on economic reasoning; setting a cap on carbon emissions and pricing the negative social consequences raises the opportunity costs of emissions for polluters and, thus, provides them incentives to adopt clean technologies to reduce carbon emissions. In the context of an industry’s transition process, the ship owner’s investment decision is an inherently dynamic problem subject to various uncertainties, and it has implications for the decision problem. The real option theory suggests that investment decisions made in an uncertain environment might give rise to an option value of waiting to invest in costly technologies (Dixit

& Pindyck, 1994). A common concern with a maritime ETS is that the carbon price uncertainty might lead to suboptimal levels of clean technology adoption by ship owners, as their investment decision and long-term investment planning are riskier (Psaraftis & Lagouvardou, 2019). This research thoroughly examines the ship owner’s investments in clean technologies over the time horizon and the related value of actively managing the investment decision by asking:

RQ 1: “How is the ship owner’s investment policy over time shaped under an ETS regulation ?”

Further, this research examines how uncertainties affect the costs of regulation and the value of flexibility and, in turn, the investment policy over time. Previous work concerned with the adop-tion of clean technologies under an ETS paid special attenadop-tion to the impact of permit price or resource price uncertainties on the investment decision. We shift the focus to a different set of un-certainties that are of special importance in the context of an industry’s green transition process.

More precisely, we examine the impact of regulatory uncertainties, which are related to the policy design to reach industry-wide reduction targets, and pollution uncertainty, which is related to the demand of ship owners for emissions to provide transportation services. Therefore, we posit the following second research question:

RQ 2: “What impact does an environment with increased regulatory and demand uncertainties have on the ship owner’s investment policy?”

Methodology: We develop a quantitative multi-period decision model in a stochastic environment

and analyze it with mathematical optimization methods to describe the investment policy over the time horizon. Our departing point is the static case of a cost-minimizing ship owner subject to an ETS based on the efficient auction mechanism with an endogenous supply of licenses proposed by Montero (2008). To capture the dynamic and uncertain nature of the problem when facing such a mechanism, we develop a discrete and finite multi-period model for the investment decision.

The stochastic dynamic programming method is utilized to solve our problem of decision-making under uncertainty. Based on this mathematical framework, we apply deductive reasoning to derive theorems describing the optimal investment policy over time and the impact of an environment with increased uncertainties.

Findings: Our analytical results suggest there is indeed value in actively managing the investment decision instead of utilizing a passive approach to cope with the regulation. The investment policy is characterized by an investment decision rule in every decision period. The rule states that it is optimal for the ship owner to wait with the investment if their pollution demand is below a certain threshold and to invest in clean technologies if it is above the threshold. The optimal size of the investment is increasing in their current demand for pollution. Therefore, the investment levels over time are of a decreasing shape to maximize cost reductions in the auctions over the time horizon. Further, the results suggest that an environment with increased uncertainties has a substantial impact on this policy. Higher regulatory and demand uncertainty increases both the expected costs and value of managerial flexibility for a ship owner leading to a higher incentive to invest in clean technologies.

Contribution: The derived analytical results yield important implications for theory and practice.

The research enriches the theoretical understanding of a firm’s investment decision problem under uncertainty when being subject to an environmental policy. In particular, we provide insights into a firm’s investments in clean technologies over time and their associated value of managerial flex-ibility when facing an ETS designed to reach industry-wide emission reduction targets. Further, we contribute to the real option literature by showing how an environment with increased uncer-tainties pertinent to the green transition context impacts the costs of regulation and the value of managerial flexibility. The research also provides insights for policy makers into the design of a

maritime ETS and the implications of design choices. Incentives to adopt clean technologies under a maritime ETS could be increased by incorporating the emission reduction targets into the policy design. This feasible property depends on the credible commitment of policy makers to the defined reduction targets through, for example, monetary ramifications if a ship owner’s abatement efforts are insufficient. Another insight is that a maritime ETS can be a key instrument for the green transition of the industry even in an uncertain environment, as the uncertainty does not erode the value of actively managing the investment decision and incentives to invest in clean technologies.