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Assessing Factors Affecting Intention to Adopt AI and ML: The Case of the Jordanian Retail Industry
Author(s) -
Mohammed I. Alghamdi
Publication year - 2020
Publication title -
mendel ... (brno. on-line)/mendel ...
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.221
H-Index - 13
eISSN - 1803-3822
pISSN - 1803-3814
DOI - 10.13164/mendel.2020.2.039
Subject(s) - scope (computer science) , likert scale , context (archaeology) , vendor , marketing , business , sample (material) , structural equation modeling , government (linguistics) , scale (ratio) , retail industry , data collection , survey methodology , statistics , computer science , mathematics , geography , linguistics , chemistry , philosophy , cartography , archaeology , chromatography , programming language
Aim: The aim of this research is to evaluate the factors that affect the adoption intention of AI and ML in the context of Jordan’s retail industry Method: For this research paper, primary data was collected with the help of surveying different retail companies that are operational in Jordan with a sample of 400 participants. The survey questionnaire was based on a Likert scale where five points ranging from strongly agree to strongly disagree were provided to the participants. Structural Equation Modelling (SEM) used to analyse the impact and significance of the different factors on the adoption of AI and ML in Jordanian retail sector. Results: It has been concluded from this research paper that communication, government regulations, market structure, and technological infrastructure are important factors that influence the adoption of AI and ML in the retail industry of Jordan. However, the results of this research have pointed out that managerial support and vendor relationship do not have a significant influence on the adoption of AI and ML. Limitations: The scope of the research is restricted to the context of the retail industry only. This research has been carried out in the context of Jordan thus it cannot be applied on to other geographical backgrounds. Due to the time and scope limitations, there are restricted factors considered in the framework.

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