An Efficiency Model of a Medium-Sized Enterprise and the Transformation from a Conventional to a Sustainable Ecosystem Using a Hybrid DEA-MCDM Model

In conditions where information and communication technologies (ICT) dictate the rules of the market, the strong promotion and development of innovation-oriented small and medium-sized enterprises (SMEs) are essential. The transition from a traditional, linear system of waste management and fleet management in utility companies to a digital and circular-oriented system represents not only a significant challenge, but also a necessity. This paper analyses the potential transition of a medium-sized enterprise from a conventional to a sustainable business ecosystem by examining the vehicle fleet of a utility company and proposing its optimisation using the DEA-LOGSTA-MARCOS model. The hybrid DEA-MCDM model, developed and presented in this form for the first time in the literature, represents a methodological contribution of this research. The paper analyses a fleet of utility vehicles used for waste collection and transport that are 15 years old or older. The aforementioned methods are applied to highlight the importance of operationally efficient vehicles that can potentially be integrated into a digital ecosystem (DE), thereby strengthening the company s comparative advantage. In the first stage, the DEA model was applied to determine the efficiency of the vehicles, followed by the LOGSTA method in the second stage to calculate the criteria weights, and finally, the MARCOS method to rank the vehicles according to their overall efficiency. The research results indicate that the most significant barriers to the transformation toward a digital ecosystem within the observed enterprise are regulatory, financial, and technical in nature. From the perspective of the vehicle fleet and its limiting factors, the results indicate the need for an iterative transformation of the fleet structure, aligned with current efficiency levels and future electrification trends. In this context, the findings identify which types of vehicles should be retained during the initial phase of the transformation.