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Abstract: This work represents a comprehensive and systematic literature review (SLR) that follows the PRISMA (Preferred Reporting Items for Systematic Reviews and MetaAnalyses) guidelines for research assessing information and cyber security maturity. The period from 2012 to 2024 was considered and the final collection of 96 studies was taken into account. Our findings were summarised in two stages, a quantitative analysis and a qualitative synthesis. In the first part, various quantitative indicators were used to analyse the evolution of the information and cyber security maturity assessment domain over the last twelve years. The qualitative synthesis, which was limited to 36 research papers, categorises the studies into three key areas: the development of new maturity models, the implementation of established models and frameworks, and the advancement of methodologies to support maturity assessments. The findings reveal significant progress in sector-specific customisation, the growing importance of lightweight models for small and medium-sized enterprises (SMEs), and the integration of emerging technologies. This study provides important insights into the evolving landscape of information and cyber security maturity assessment and provides actionable recommendations for academia and industry to improve security resilience and support the adoption of tailored, effective maturity models
Keywords: cyber security, information security, maturity assessment, maturity model, maturity framework, systematic literature review, SLR
Published in DKUM: 26.08.2025; Views: 0; Downloads: 7
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Abstract: Small and medium-sized enterprises (SMEs) need to keep pace with large enterprises, thus they need to digitally transform. Since they usually lack resources (budget, knowledge, and time) many countries have their support environment to help SMEs in this endeavor. To be able to ensure the right kinds of support, it is crucial to assess the digital maturity of an enterprise. There are many models and assessment tools for digital maturity, however, they are either theoretical models, partial, vendor oriented, or suited for large enterprises. In this paper, we address the problem of assessing digital maturity for SMEs. For this purpose, we developed a multi-attribute model for assessment of the digital maturity of an SME. We followed the design science research approach, where the multi-attribute model is considered as an IT artifact. Within the design cycle, the decision expert (DEX) methodology of a broader multi-attribute decision making methodologies was applied. The developed model was validated by a group of experts and upgraded according to their feedback and finally evaluated on seven real-life cases. Results show that the model can be used in real business situations.
Keywords: digital transformation, digital maturity assessment, multi-attribute model, small and medium-sized enterprises
Published in DKUM: 07.08.2024; Views: 108; Downloads: 31
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Abstract: The masters thesis, which follows the paper Graph drawing applications in combinatorial theory of maturity models, in preparation, coauthored by the author of the thesis, introduces the tiled graphs as models of learning and maturing processes. In the thesis, we show how tiled graphs can combine graphs of learning spaces or antimatroids (partial cubes) and maturity models (total orders) to yield models of learning processes. We visualise processes with optimal drawings. In the thesis, we show NP-hardness of visualisation problems resulting from most detailed models. Further, we introduce a simpler model, which ignores the details of learning and for which the visualisation problem can be solved in a polynomial time. For the rest of the thesis, we consider this model. We describe an algorithm, which finds a drawing of an ordinal panel data graph with a minimal number of edge crossings. For this problem we further define an extremal crossing number for a chosen family of ordinal panel data. Further, we explore a certain type of random instances of ordinal panel data and the expected value of a crossing number for this type of random instances. After that, we define a problem of finding the most suitable ordering on categories in panel data, in other words finding the best maturity model to fit the data. We prove the NP-hardness of the problem and formulate an integer linear program. Master thesis consists of nine chapters. The first chapter contains known results and definitions from set and graph theory and a section of computational complexity theory (NP-hardness), which will be used throughout the thesis. The following chapters present the new theory introduced in the aforementioned paper in preparation and the needed additional results and definitions. In the last chapter we present the thesis and some selected parts of the thesis with the help of learning space theory. The chapter serves as both the overview of the thesis and the use case for the theory of learning spaces, presented in the thesis.
Keywords: Maturity models, learning spaces, crossing number, crossing minimisation, tile crossing number.
Published in DKUM: 14.03.2024; Views: 463; Downloads: 42
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Abstract: This paper aims to research the organizational factors influencing the implementation of energy efficiency measures in companies. The analysis was performed on a sample of companies from Serbia included in the World Bank Enterprise Survey. The raw data collected by the World Bank were utilized to analyze the correlation between various organizational factors and the adoption of energy efficiency measures. The analysis revealed a statistically significant correlation between management maturity and the implementation of energy efficiency measures in companies. These findings suggest that improving energy efficiency is not an isolated process but rather closely related to the maturity of management practices, highlighting the importance of comprehensive organizational development for achieving optimal energy management.
Keywords: energy efficiency, energy management, management maturity, organizational factors, Serbia
Published in DKUM: 05.09.2023; Views: 266; Downloads: 23
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