In this paper, a new fuzzy multi-criteria decision-making model for traffic risk assessment was developed. A part of a main road network of 7.4 km with a total of 38 Sections was analyzed with the aim of determining the degree of risk on them. For that purpose, a fuzzy Measurement Alternatives and Ranking according to the COmpromise Solution (fuzzy MARCOS) method was developed. In addition, a new fuzzy linguistic scale quantified into triangular fuzzy numbers (TFNs) was developed. The fuzzy PIvot Pairwise RElative Criteria Importance Assessment—fuzzy PIPRECIA method—was used to determine the criteria weights on the basis of which the road network sections were evaluated. The results clearly show that there is a dominant section with the highest risk for all road participants, which requires corrective actions. In order to validate the results, a comprehensive validity test was created consisting of variations in the significance of model input parameters, testing the influence of dynamic factors—of reverse rank, and applying the fuzzy Simple Additive Weighing (fuzzy SAW) method and the fuzzy Technique for Order of Preference by Similarity to Ideal Solution (fuzzy TOPSIS). The validation test show the stability of the results obtained and the justification for the development of the proposed model.

Infrastructure, service delivery, governance, and digital transformation stand as indispensable cornerstones, playing pivotal roles in the establishment of intelligent and sustainable urban centers. While the extant literature has underscored the significance of each of these elements, their interconnected and symbiotic relationship demands a more profound exploration. Grounded in a systematic review of the existing literature and relevant case studies, this paper explored the intricate interplay between digital transformation, infrastructure development, service delivery, and governance in contemporary society, all in the pursuit of cultivating smart sustainable cities. It contends that by collaboratively working together, these four pillars possess the transformative potential to turn cities into smart and sustainable cities. Digital transformation emerges as the catalyst, propelling innovation and efficiency, while infrastructure forms the bedrock for the seamless delivery of services. Effective governance, in turn, ensures alignment with the evolving needs of citizens. In essence, this study underscores the transformative power of combined action, asserting that the interdependent elements within can transform cities beyond merely having smart or sustainable status to become smart sustainable cities. This paradigm shift harmonizes technological advancements with the foundational goals of sustainable development, steering towards a holistic and inclusive urban future.

Many countries across the Global South strive to align their urban development with sustainability goals. Consequently, the notion of smart sustainable cities has emerged, integrating the ideas of smart cities and sustainability. The region faces diverse challenges, including rapid population growth and financial constraints. Infrastructural deficiencies, especially in digital infrastructure and AI adoption, add to these challenges. Therefore, exploring digital technologies and AI is essential for developing smart, sustainable cities in the Global South. This paper examined both the potential and barriers to digital technologies and AI. It also explored policy implications and proposes a framework for smart sustainable cities. A qualitative methodological approach is used, including a systematic literature review and case studies. The study demonstrates how various urban challenges can be addressed with digital technologies and AI, alongside the barriers to their adoption. The study proposes a conceptual framework with three key pillars: adopting digital technologies and AI as the pivotal element, overcoming barriers, and identifying application areas to transform cities into smart sustainable cities. Moreover, the paper discusses policy implications and suggests future directions for research.

Climate change is already a reality, and it is affecting the lives and livelihoods of many people globally. Many scientists argue that adaptation is, therefore, necessary to address the impact of climate change on life-supporting systems. Climate change adaptation, however, is a complex process that involves transformations implemented through governance at multiple levels. In this paper, the barriers to climate change adaptation in South Africa are presented and analysed. Semi-structured, in-depth interviews were conducted telephonically and online via Microsoft Teams with 13 government officials working at the Department of Forestry, Fisheries, and the Environment; the KwaZulu-Natal Department of Economic Development and Environmental Affairs; and the uMkhanyakude District Municipality. The findings suggest that the barriers to climate change adaptation in South Africa include inadequate financial resources, a lack of human capacity at the provincial and local levels, limited political will at the local level, limited understanding of climate change adaptation issues by communities, inadequate coordination across government levels and sectors, no legal mandate at the local level, no climate change unit at the district and local levels, a lack of knowledge by some staff members tasked with environmental duties at the local level, not enough climate change plans in place at the local level, and outdated information on climate change used in the IDPs. This paper, therefore, recommends that climate change be a standing item in the Integrated Development Plan for local governments, which will ensure that climate change is budgeted for appropriately. In addition, this paper suggests that a mandate for climate change adaptation be developed for all three government levels. There is also a need for the government to invest in capacity development and improve horizontal and vertical coordination to strengthen the weak climate governance capacity that exists.

The quality of output or decision-making depends on high-quality input data, their adequate evaluation, the application of adequate approaches, and accurate calculation. In this paper, an objective criticism of applying the fuzzy SWARA (step-wise weight assessment ratio analysis) method based on the Chang TFN (triangular fuzzy number) scale is performed. Through research, it has been noticed that a large number of studies use this approach and, as an epilogue, there are wrong decisions based on inconsistent values in relation to the initial assessment of decision-makers (DMs). Seven representative studies (logistics, construction industry, financial performance management, and supply chain) with different parameter structures and decision matrix sizes have been singled out. The main hypothesis has been set, which implies that the application of this approach leads to wrong decisions because the weight values of the criteria are incorrect. A comparative analysis with the improved fuzzy SWARA (IMF SWARA) method has been created and a number of negative conclusions has been reached on using the fuzzy SWARA method and the Chang scale: Primarily, that using such an approach is impossible for two or more criteria to have equal value, that allocating TFN (1,1,1) leads to criteria values that are inconsistent with expert evaluation, that the last-ranked criteria in the fuzzy SWARA method have no influential value on the ranking of alternatives, that there is a great gap between the most significant and last-ranked criteria, and that the most significant criterion has a huge impact on the evaluation of alternative solutions and decision making. As a general conclusion, it is given that this approach is not adequate for application in problems of multi-criteria decision making because it produces inadequate management of processes and activities in various spheres.

The decision-making trial and evaluation laboratory (DEMATEL) method is one of the most significant multi-criteria techniques for defining the relationships among criteria and for defining the weight coefficients of criteria. Since multi-criteria models are very often used in management and decision-making under conditions of uncertainty, the fuzzy DEMATEL model has been extended in this paper by D numbers (fuzzy DEMATEL-D). The aim of this research was to develop a multi-criteria methodology that enables the objective processing of fuzzy linguistic information in the pairwise comparison of criteria. This aim was achieved through the development of the fuzzy DEMATEL-D method. Combining D numbers with trapezoidal fuzzy linguistic variables (LVs) allows for the additional processing of uncertainties and ambiguities that exist in experts’ preferences when comparing criteria with each other. In addition, the fuzzy DEMATEL-D methodology has a unique reasoning algorithm that allows for the rational processing of uncertainties when using fuzzy linguistic expressions for pairwise comparisons of criteria. The fuzzy DEMATEL-D methodology provides an original uncertainty management framework that is rational and concise. In order to illustrate the effectiveness of the proposed methodology, a case study with the application of the proposed multi-criteria methodology is presented.