The paper compares two multi-criteria methods, the analytic hierarchy process (AHP) and the best–worst method (BWM), in assessing criteria related to the quality of urban parks. The criteria assessed were accessibility, location, biodiversity preservation, park equipment, water elements, terrain configuration, cultural and historical value, and the presence of small architectural objects. Five decision-makers participated in the research, having expertise in urban greenery, urban forestry, environmental protection, landscape design, and cultural and historical heritage. The results of decision-makers’ evaluations were compared at individual and group levels after the application of three aggregation procedures: CRITIC, ENTROPY, and WGGM (weighted geometric mean method). Similarities in results, i.e., priorities of analyzed criteria after applying the two different decision support methods, indicated high consistency between experts during the cognitive evaluation processes. All applied aggregation schemes performed well and may be considered trustworthy in identifying the group solution. One of the conclusions is that either the AHP or the BWM can be efficiently used in evaluations of criteria for assessing the quality of urban parks if the members of a group are consistent, regardless of whether the consensus process is properly carried out before the decision-making process.

This paper proposes an AHP approach that utilizes the fuzzy extent model to prioritize five city parks based on their present quality and projected importance for Novi Sad City, the capital of Vojvodina Province, in Serbia. The study involved an expert evaluation of a set of eight criteria to identify the most relevant subset of criteria for a detailed park assessment. The park evaluation took into account uncertainties (fuzziness), the expert’s risk tolerance, and different levels of optimism and pessimism. The obtained results could serve when defining upcoming city plans and management agendas related to green areas in the city. The proposed fuzzy-based methodology can be extended to group decision-making scenarios by involving more experts and stakeholder representatives. The park weights obtained through the fuzzy AHP methodology described in this paper can aid city planners and politicians in the strategic allocation of financial, organizational, and human resources for parks.

This paper presents the combined use of standard DEMATEL and AHP methodologies in assessing a selected set of criteria for evaluating sustainable forestry goals. Creating a decision-making framework with two participating individuals (the authors of this research) enabled the comparison of individually obtained solutions with the aggregated solutions derived by two methodologies. The use of DEMATEL enabled strategic viewing of the causality relations among criteria and a limited indication of cardinal information (weights) about their importance. Different from DEMATEL, the use of AHP is considered a control mechanism in tactical decision-making situations such as the usage of standard multi-criteria methods for solving forestry-related allocation or selection problems. AHP’s role is to derive weights of criteria in a very structured environment based on assumption that criteria are independent and only their mutual importance is relevant for further decision-making. Individual solutions and aggregation schemes for creating group solutions are compared for both methodologies. Critical analysis is given for different aspects of their combined use when treating causalities and the importance of criteria in evaluations of long-term sustainable forestry goals.

A central focus of this study was the methodology used to evaluate both humans and AI platforms, particularly in terms of their competitiveness and the implications of six key challenges to society resulting from the development and increasing use of artificial intelligence (AI) technologies. The list of challenges was compiled by consulting various online sources and cross-referencing with academics from 15 countries across Europe and the USA. Professors, scientific researchers, and PhD students were invited to independently and remotely evaluate the challenges. Rather than contributing another discussion based solely on social arguments, this paper seeks to provide a logical evaluation framework, moving beyond qualitative discourse by incorporating numerical values. The pairwise comparison of AI challenges was conducted by two groups of participants using the multicriteria decision-making model known as the analytic hierarchy process (AHP). Thirty-eight humans performed pairwise comparisons of the six challenges after they were listed in a distributed questionnaire. The same procedure was carried out by four AI platforms—ChatGPT, Gemini (BardAI), Perplexity, and DedaAI—who responded to the same requests as the human participants. The results from both groups were grouped and compared, revealing interesting differences in the prioritization of AI challenges’ impact on society. Both groups agreed on the highest importance of data privacy and security, as well as the lowest importance of social and cultural resistance, specifically the clash of AI with existing cultural norms and societal values.

In this paper, an approach is proposed for assessing the performance of experts in the group from two perspectives: (1) individual consistencies and (2) deviations from the group decision. The quality of performance of the experts is based on combining the standard and rough analytic hierarchy process (AHP) with the technique for order of preference by similarity to the ideal solution (TOPSIS). The statistical method CRITIC is used to derive weights for the TOPSIS method before the experts are assessed based on demonstrated consistency and deviations from the group. Common performance indicators, such as consistency ratio, Euclidean distance, compatibility, and Spearman’s correlation coefficient, are proposed for re-grouping experts before making the final decisions. A genetic algorithm enables the efficient solving of this complex clustering problem. Implementing the described approach and method can be useful in comparable assessment frameworks. A critical aspect is conducting a thorough pre-assessment of the competence of potential decision makers, often referred to as experts who may not consistently exhibit apparent expertise. The competence of decision makers (which does not have to be associated with compatibility) is evidenced by selected consistency parameters, and in a way, a pre-assessment of their competence follows Plato’s ‘government of the wise’ principle. In the presented study, the compatibility of individuals in the group with the collective position (group decision) is measured by parameters related to their compatibility with the group solution and statistical deviation while ranking decision elements. The proposed multi-model-based approach stands out for its resilience in conducting thorough pre-assessment of the quality (competence) of potential decision makers, often regarded as experts who might not consistently display evident expertise. The wetland study area in Serbia is used as an example application, where seven measures for reducing the risk of drought were evaluated by twelve experts coming from different sectors and with different backgrounds and expertise.