Exploring the adoption and long-term effects of ChatGPT in a sustainable supply chain

Considering the environmental changes and their effects, using up-to-date technologies such as Chat Generative Pre-trained Transformer (ChatGPT) seems necessary to control environmental problems. The study aims to predict the behavior of the adoption rate of ChatGPT in a sustainable supply chain over time, focusing on Iran's pharmaceutical supply chain from 2018 to 2039. In this study, the performance of ChatGPT on a sustainable supply chain is investigated using System Dynamics (SD) simulation and introduce a new model, Dynamic Sustainable Pharmaceutical Supply Chain Simulation (DSPSCSim). SD allows for handling non-linear behavior arising from the interaction of multiple variables. Empirical data is compared with simulation one, and sensitivity analysis is conducted to validate the findings. The system studied in this research comprises five sectors: economic, socio-environmental, management, and ChatGPT. In addition, the influence of four influential variables of ChatGPT, as well as air pollution, on the sustainability of the supply chain is studied in different scenarios. The study is expected to guide policymakers and managers in using ChatGPT effectively in their organizations. By observing its long-term effects on the sustainability of the supply chain, policy-makers and managers will be better equipped to make informed decisions on its implementation. This study can also contribute to developing sustainable supply chain practices, which are essential for addressing the global challenges of environmental changes.