## 5 Conclusions  
This paper offers a comprehensive state-of-the-art review of [PERSON]'s Taxonomic Measure of Development (TMD) and its various modifications, emphasizing pioneering extensions that could inspire further research in the field. The [PERSON] method is widely regarded for its flexibility, simplicity, and low computational demands, making it a powerful tool for multi-criteria analysis. It provides a structured approach to analyzing a wide range of socio-economic issues, particularly those involving multidimensional concepts that are difficult to quantify. Although [PERSON]'s approach shares similarities with the widely used TOPSIS method in its use of distance to evaluate alternatives, it is distinct in its exclusive focus on proximity to an ideal solution without considering the distance from a negative ideal. Since the original version of [PERSON]'s method was proposed, several adaptations have emerged in the literature to address specific conditions. For example, the Mahalanobis distance has been proposed to account for dependencies across criteria [132; 133], the median Weber approach to address outliers [6; 130], and the spatial weight matrix to allow for simultaneous analysis across three dimensions: section, time, and space [139; 140; 141; 7]. Fuzzy approaches have been introduced to address uncertainty [6; 10; 131], and an intuitionistic approach was developed for ordered data [12; 173]. Subsequent developments include other fuzzy methods [16; 131; 173], dynamic approaches [15; 124], and frameworks designed to prevent rank reversal issues [15; 17]. Through a series of preliminary searches, key topics extending the TMD method were identified, focusing on data collection, criterion weighting, data normalization, ideal value determination, distance calculation, and normalization factors. This process enabled a refined selection of relevant studies, ultimately leading to the review of about 100 papers, primarily in English, categorized by the type of modification and application areas. The findings reveal that Hellwig-based methods are frequently used in socio-economic analyses,particularly in areas such as sustainable development, regional development, quality of life and living standards, smart growth and smart cities, financial markets and institutions, human capital and education, agricultural development, sustainability, and negotiation support. Approximately half of these studies applied the classical Hellwig approach, while the remaining works involve extensions or modifications of the Hellwig method, utilizing real numbers, linguistic evaluations, fuzzy numbers, and intuitionistic fuzzy numbers. Some of these studies also incorporate comparative analyses, either applying different Hellwig-based methods or using other approaches, with the TOPSIS method being the most common. This underscores the flexibility and adaptability of the Hellwig approach across a wide range of analytical frameworks. The main contributions of this paper can be summarized as follows:  
* A comprehensive review of the original Taxonomic Measure of Development (TMD) method and its extensions, including applications with fuzzy and intuitionistic fuzzy sets. * The introduction of an original, step-by-step analytical framework, offering a detailed examination of the TMD process and providing new insights into its practical implementations. * Highlighting the practical versatility of the TMD method across various domains, distinguishing it from other multi-criteria methods like TOPSIS. To the best of the author's knowledge, this paper offers the first thorough exploration of [PERSON]'s Taxonomic Measure of Development and its modifications. It employs an original methodology rooted in a systematic review that adheres to the steps of algorithms while also showcasing practical applications across various domains. While this study offers an extensive overview of state-of-the-art TMD, it does have limitations that must be acknowledged.