Frontier Shifts Without Ranking Changes: Evaluating Service Level Agreements on the Efficiency and Productivity of Energy Tanker Fleets Using a DEA–Malmquist Approach and Mixed Methods - Muhammad Dzaky Al Tovic; Eko Budi Santoso (Sean Institute, 2026)
Maritime logistics plays a vital role in supporting the national energy supply chain, making operational cost efficiency and fleet reliability strategic concerns for energy transportation companies in Indonesia. This study evaluates the impact of implementing a Service Level Agreement (SLA) as a performance-based governance instrument on the Small Tanker I fleet of an energy maritime logistics company by comparing operational conditions before (2023) and after (2024) implementation. An explanatory sequential mixed-methods approach was employed involving ten vessels treated as Decision Making Units (DMUs). Relative technical efficiency was measured using input-oriented BCC Data Envelopment Analysis (DEA), total productivity change was assessed through the Malmquist Productivity Index (MPI), and six hypotheses were tested using the Wilcoxon signed-rank test, linear regression analysis, and the Baron and Kenny mediation procedure. Qualitative data obtained from interviews with five key informants were used to explain quantitative findings through a joint display analysis. The results indicate that SLA implementation has a positive and significant effect on fleet operational strategy (coefficient = 3.04; p < 0.001) and increases total productivity by 20.64%, with technological change emerging as the dominant component (average Malmquist index = 1.2064; p < 0.001). At the same time, relative technical efficiency among vessels did not change significantly (p = 0.2754), and operational strategy was not found to mediate the relationship between SLA implementation and efficiency. Benchmark vessels were consistently identified as references for continuous improvement. These findings suggest that SLA functions as a governance instrument that shifts the operational frontier of the fleet uniformly without altering relative efficiency rankings in the short term. The study also highlights the importance of combining static efficiency measurement and dynamic productivity assessment in evaluating operational governance performance.