## 1 Introduction  
In the past decade, the dynamic transformation of the industry towards digitalization, automation, and sustainable development, known as Industry 4.0, has significantly influenced the operations of manufacturing and logistics companies. The implementation of technologies such as the Internet of Things (IoT), artificial intelligence (AI), Big Data analysis, and advanced robotization has led to increased operational efficiency, cost optimization, and increased process flexibility. At the same time, increasing social and environmental challenges, as well as the need for greater human involvement in industrial processes, have led to the emergence of a new paradigm--Industry 5.0--which emphasizes human-centricvalues, system resilience, and the pursuit of sustainable development. The literature in this field indicates the need for a comprehensive and systematic approach to assessing the readiness of enterprises to transition from Industry 4.0 to 5.0. [PERSON] et al. [1] emphasize the importance of integrating decision-support tools and knowledge generation strategies in order to overcome digital barriers, taking into account both technological and social aspects. [PERSON] et al. [2] propose a readiness assessment model that takes into account employee competencies, organizational culture, and adaptability as key factors for the effective implementation of Industry 5.0 assumptions. In turn, [PERSON] et al. [3] show that a higher level of readiness for transformation translates into sustainable growth of small- and medium-sized enterprises, especially in the context of implementing human- and environment-friendly technologies. Despite the growing number of conceptual and application studies, the literature still does not offer sufficiently integrated models enabling a comprehensive assessment of technologies supporting the transformation from Industry 4.0 to 5.0. There is a lack of analytical tools that simultaneously consider (i) the cause-and-effect relationships between technologies and transformation areas, (ii) the ranking of technologies in terms of their effectiveness across three key dimensions (economic, organizational, and technological), and (iii) their role in the full transformation cycle from digitalization to human-centric resilience. The aim of this article is to develop a framework for assessing modern technologies characteristic of Industry 4.0 and 5.0, addressing this gap through the integrated MCDM (multi-criteria decision-making) methodology, combining the DEMATEL method (for the analysis of cause-effect relationships) and PROMETHEE II (for the assessment of preferences and decision priorities). The developed model includes 22 technologies, assigned to six areas of transformation, assessed from three perspectives: economic, organizational, and technological. The following research questions were formulated in this study:  
Q1: What technologies should be prioritized for implementation by companies seeking to transform towards Industry 5.0? Q2: What are the relationships between technology assessment criteria in the context of the transformation from Industry 4.0 to 5.0? Q3: How does the adopted assessment perspective (economic, organizational, or technological) influence differences in the classification and prioritization of assessed technologies? The formulated research questions were embedded in the analytical structure of this study: Q1--the identification of technologies with the highest implementation priority; Q2--the relationships between the evaluation criteria; Q3--differences in the assessment of technologies from three perspectives, economic, organizational, and technological. The structure of this paper is as follows: Section 2 outlines a review of the literature on Industry 4.0/5.0 and the application of MCDA methods. Section 3 describes the adopted methodology in detail. Section 4 presents the implementation process of the hybrid model.