Abstract
Energy management is a concerning subject due to the rising energy prices and environmental concerns. In this scenario, the maturity model measures an organization’s competences with benchmarking actions and performance improvement. Energy Management Maturity Models (EMMM) are already discussed in the literature. Still, few works focus on the classification of the existing models to identify gaps. This article aims to identify the main EMMM of the literature and propose a classification scheme aiming to identify gaps in the construction of future EMMM.
To achieve the goal, a literature review used an adaptation of the ProKnow-C method and snowball. Eleven maturity models were analyzed, eight directly related to energy management and three not directly related to energy management but with contributions to the research. The classification focused on the description of the type of the model, model structure, number of maturity levels, methodology of analysis, reference to international standards, mode of assessment, results of the evaluation, and guide to improvement. Results showed that most of the models are descriptive, which means they analyzed the current situation. Still, with no guide for improvement, here is also a preference for utilizing five maturity levels. ISO 50001 appears as an international reference standard, which is explicable by the area of study, which is energy. As for the presentation of the results, graphics and visual tools are common to present the results. Since the classification of the maturity models has resulted from a literature review, this research is limited by the period, keywords, and area of study. For future works, it is suggested that the expansion of the research area to identify relationships between EMMM and other maturity models is also offered the construction of a new EMMM, which fulfills the gaps identified in this research.
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Monteiro, N.J., de Oliveira, R.M.e.S., da Costa, S.E.G., Deschamps, F., de Lima, E.P. (2022). Energy Management Maturity Models: Literature Review and Classification. In: López Sánchez, V.M., Mendonça Freires, F.G., Gonçalves dos Reis, J.C., Costa Martins das Dores, J.M. (eds) Industrial Engineering and Operations Management. IJCIEOM 2022. Springer Proceedings in Mathematics & Statistics, vol 400. Springer, Cham. https://doi.org/10.1007/978-3-031-14763-0_5
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