Analyzing the Retail Sector in Jordan to Determine the Elements Influencing the Intention to Implement AI and ML

Abstract

In the context of Jordan’s retail business, this study aims to examine the variables that determine the desire to use AI and ML.
Approach: A total of 400 people were surveyed by several Jordanian retail firms to provide the main data used in this research
report. A Likert scale, with five options ranging from “strongly agree” to “strongly disagree,” was used to construct the survey
questionnaire. The usage of artificial intelligence and machine learning in Jordan’s retail industry was examined using structural
equation modeling (SEM). Findings: This study found that the adoption of artificial intelligence and machine learning
in Jordan’s retail sector is impacted by communication, government legislation, market structure, and technical infrastructure.
This study’s findings, however, suggest that vendor relationships and management buy-in do not significantly impact AI and
ML adoption. Restrictions: This study solely covers the retail business as a whole. The studies conducted in Jordan cannot be
generalized to other locations because of this. The framework takes into account limited elements because of time and scope
constraints.