Inland waterway transport (IWT) is an integral part of today's society. Similar to other transport sectors, however, it has to transition away from fossil fuels. Regulations are tightening, but barges have a largely varying operational profile, making it difficult to find one suitable alternative to contemporary diesel. There are many alternatives available, yet none of them can fully replace diesel in the short term without impeding the sector too much. It seems that a mix of alternative energy carriers (AECs) is needed throughout the transition. Hardly any of the alternative energy carriers are being applied in IWT and when they are, it is typically still on a very small scale. This leaves the question why this is the case. This research is aimed at finding the determinants for the large-scale introduction of AECs to IWT.

Energy carriers in IWT can be seen as a system around a technology. To analyze their shortcomings for large-scale introduction to the sector, it is important to understand the necessities for the large-scale introduction of such a system in the first place. The framework from Ortt and Kamp (2022) for technological innovation systems (TIS) characterizes exactly this. Therefore, to analyze the determinants for the large-scale introduction of AECs to IWT, this framework is used. This framework consists of seven building blocks. These are product performance & quality, product price, production system, complementary products and services, network formation, customers, and innovation-specific institutions. These seven building blocks split up the aspects of large-scale introduction into smaller parts which are analyzed individually.

To gather data on why AECs are not being applied in IWT currently, seven different AECs are analyzed. These energy carriers all have a potential to be implemented on a larger scale in the sector. They are diesel, LNG, hydrogen, methanol, ammonia, batteries, and flow batteries. The data is gathered by interviewing experts in IWT who have experience with AECs. A total of eight interviews were conducted with ten interviewees in total. These experts vary in their position in the sector. Types of actors and stakeholders who have been interviewed were representatives for a barge owner, shipyard, energy carrier supplier, component supplier, classification society, terminal, and a researcher. The results from the interviewees have been coded using ATLAS.ti. The first step was to code all observations in interviews to a corresponding building block from the TIS framework. Once all the observations had been split up into building blocks, the building blocks could be analyzed individually. At this point, the determinants could be extracted from the observations per building block. This has resulted in a total of 23 determinants. Any determinant can be used to analyze an AEC. Analyzing a determinant can show whether a factor is aiding or blocking, or whether there is a barrier or opportunity for a particular AEC.

The 23 determinants can be viewed through three different scopes. The first scope, the intra-barge scope, contains the determinants of the first three building blocks; production system, product performance & quality, and product price. The second scope, the intra-fleet scope, contains the determinants of the next two building blocks; complementary products & services, and customers. The third and last scope, the actor-based scope, contains determinants of the last two building blocks; network formation & coordination, and innovation-specific institutions. The three scopes can be used to analyze whether the three scopes align for an AEC. This occurs when the mix of determinants in every scope is equally ready for implementation. When the three scopes align for an AEC, it is ready for implementation in IWT.

This framework with three scopes and their 23 determinants can be applied to any AEC, so not only the ones which were used in this research. It can be used by any actor or stakeholder in the sector to analyze which AECs are ready for implementation by them. Similarly, it can also be used to analyze where specific AECs are misaligned between scopes.