###### Abstract  
This paper presents an original and comprehensive investigation into the Taxonomic Measure of Development (TMD), introduced by [PERSON] in 1968, enriching both its theoretical foundations and practical applications. It provides an overview of various variants of the [PERSON] method, including their extensions and applications, while also exploring recent trends across multiple research domains. Primarily developed as a method for multidimensional analysis, TMD has evolved into a pivotal tool in multi-criteria decision-making. It is widely used for evaluating and ranking alternatives, particularly in the analysis of complex socio-economic phenomena and decision-making scenarios involving multiple criteria. This study systematically reviews the original algorithm and its subsequent extensions and modifications, including adaptations for fuzzy sets, intuitionistic fuzzy sets, and interval-valued fuzzy sets. Furthermore, it explores an integrated multi-criteria approach based on [PERSON]'s method and its practical applications across various domains. This paper introduces an original approach by conducting a detailed, step-by-step analysis of the TMD framework. This process-oriented analysis is a novel contribution that sets this study apart from typical reviews based on statistical or bibliometric data. By examining key steps in the TMD framework--such as data collection, criterion weighting, data normalization, ideal value determination, distance calculation, and normalization factor--this paper highlights the method's versatility in addressing complex, real-world decision-making problems. Although similar to the widely used Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method in its reliance on distance to evaluate alternatives, [PERSON]'s approach is unique in focusing exclusively on proximity to an ideal solution, without considering distance from a negative ideal. This distinctive emphasis has led to numerous adaptations and extensions that address specific issues such as criterion dependencies, uncertainty, and rank reversal. The findings underscore the continued relevance of the [PERSON] method, its recent extensions, and its growing international recognition. MCDM; FMCDM; Taxonomic Measure of Development; Hellwig-based method; ideal point, pattern of development; anti-ideal point +
Footnote †: journal: Applied sciences  
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Footnote 1: email: [EMAIL_ADDRESS]  
Footnote †: journal: Applied sciences  
challenges by linearly ranking alternatives based on their distance from an ideal point, referred to as the pattern of development. [PERSON]'s concept of a pattern of development is built around the most favorable values for each criterion, along with a synthetic measure that calculates the distance of each object from this ideal pattern using the Euclidean metric. The TMD, commonly known as [PERSON]'s method, shares similarities with the widely known multi-criteria methods in theoretical analysis and practical implementations such as the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) [5] method but focuses solely on the distance to the ideal solution. However, the TOPSIS emerged over a decade after [PERSON]'s initial proposal. The TMD method has become a particularly popular linear ordering technique in the field of economic research in Poland. Due to a significant increase in publications utilizing this method in English, it is gaining greater recognition in the international academic community, both for analyzing complex socio-economic phenomena and as a multi-criteria method based on reference points. [PERSON]'s method has been adapted to tackle a range of issues involving data represented by real numbers [6; 7; 8; 9]. It has also been adapted to fuzzy sets [6; 10; 11]. Recent modifications have focused on incorporating intuitionistic fuzzy sets [12; 13; 14; 15], interval-valued fuzzy sets [16], and oriented fuzzy sets [17].