Adoption of GSCM Practices and Sensitivity/influencing Factors: An Empirical Study at the Moroccan Firm Level 1. Introduction Nowadays, the company's success is no longer measured only by its earnings but also through the extent to which it integrates environmental concerns into its strategy. Thus, the company's management level is closely linked to its environmental responsi- bility. GSCM (Green Supply Chain Management) is an approach much appreciated by researchers and professionals as it responds to the growing trend in favor of ecological management and to face the chal- lenges of climate change. It has become a priority for many companies due to increasing environmental awareness and increasingly stringent government reg- ulations [1]–[3]. According to [4], GSCM can be de- fined as the environmental considerations integrated throughout the supply chain management process. It encompasses various stages such as product design, material sourcing, selection of manufacturing meth- ods, delivery to consumers, and post-consumer prod- uct management. For better implementation of the GSCM approach, it is crucial to study the factors that influence the adoption of GSCM practices can help GSCM (Green Supply Chain Management) is a concept that aims at the environmental di- mension of sustainable development. Many factors influence the decision to adopt a green strategy, which is also an important indicator in determining the adoption level of its prac- tices. In this article, based on a literature review, we propose a theoretical model that shows a hypothesis on the relationship between ten sensitivity factors and the level of adoption (LA) of GSCM practices (GSCMPs). Using the linear multiple regression method on collected data from a survey of Moroccan companies, we confirmed or invalidated the relationships in our model. Finally, we retained the operational model that shows the impact of the two main factors on the approval of GSCM practices: the importance of early adoption of environmen- tal practices (EAEP) and top management commitment (TMC). Organizations can use this model to improve their GSCM practices and enhance their LA. The analysis results can also provide insights for future research on GSCM and LA. Article history: Received November 23, 2022 Revised June 22, 2023 Accepted July 5, 2023 Published online July 20, 2023 Keywords: Age of companies; Size of companies; Regression linear multiple; GSCM practices; Sensitivities factors; Early adoption *Corresponding author: Khaoula Amrani Souhli khaoula.amranisouhli@usmba.ac.ma ISSN 2683-345X hp://doi.org/10.24867/IJIEM-2023-3-334 Published by the University of Novi Sad, Faculty of Technical Sciences, Novi Sad, Serbia. This is an open access article distributed under the CC BY 4.0 terms and conditions. ABSTRACT ARTICLE INFO International Journal of Industrial Engineering and Management Volume 14 / No 3 / September 2023 / 214 - 231 Original research article journal homepage: hp://ijiemjournal.uns.ac.rs/ K. Amrani Souhli a, *, A. En-nadi a a Faculty of Sciences and Techniques, Sidi Mohamed Ben Abdellah University, Department of Industrial Engineering, Industrial Technical Laboratory (LTI) B.P. 2202 - Imouzzer Road, Fez, Morocco