Understanding the impact of using Chatbot for shipment delivery toward environmental sustainability using the SEM-ANN approach

Abstract

This research paper examines chatbot technology acceptance in customer service and shipment delivery, adoption studies, and sustainability. However, little research concerns the effect of the use of chatbots for shipment delivery and the correlation with environmental sustainability. The study aims to evaluate the impact of chatbot use on environmental sustainability in shipment delivery and develop an integrated theoretical framework for chatbot acceptance. An online survey was conducted with 344 participants from UAE residents to test the proposed model, which considers individual, and task-technology fit factors and extends UTAUT2. The study takes a unique approach compared to prior literature by relying on structural equation modeling (SEM) and artificial neural network (ANN) to analyze hypotheses. The study findings revealed that task-technology fit had the most significant effect on sustainable chatbot use for shipment delivery, with an (87%) normalized importance score, followed by social influence (81%), hedonic motivation (78%), habit (72%), individual-technology fit (57%), and facilitating conditions (47%). Sensitivity analysis results further revealed that these factors play a crucial role in shaping consumer attitudes toward chatbot use in the shipment delivery domain and their impact on environmental sustainability. The study provides valuable recommendations for developers, designers, and decision-makers in shipment delivery based on these results. Focusing on these areas can improve the results related to effort and performance expectancy, ensuring that chatbots are used for shipment delivery as effectively and efficiently as possible. However, additional research is required to validate the results and extend the proposed theoretical framework to other domains.