International Journal of Data and Network Science (Jan 2024)

Identifying variables influencing the adoption of artificial intelligence big data analytics among SMEs in Jordan

  • Belal Mathani,
  • Hamid Safyyih Ajrash,
  • Ahmad Barakat Dalaee Dalaeen,
  • Khaled Yousef Alshboul,
  • Hazem Almahameed,
  • Mohammad Haider Alibraheem,
  • Amin Khalifeh,
  • Mohammad Issa Alzoubi ,
  • Ahmad Y. A. Bani Ahmad

DOI
https://doi.org/10.5267/j.ijdns.2024.4.016
Journal volume & issue
Vol. 8, no. 4
pp. 2615 – 2626

Abstract

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The research investigates the link between technology, organization, and environment, and the uptake of artificial intelligence among SMEs in Jordan. The objective is to get a deeper understanding of the factors that promote or hinder enterprises' use of artificial intelligence during the recruitment of leaders. A total of 295 participants, who were owners or managers in several SME sectors, manufacturing, including services, construction, and agriculture, were selected via judgmental sampling. Data collection was conducted utilizing a survey instrument, and the collected data was processed employing Smart PLS. The findings demonstrated a substantial correlation between attitude toward artificial intelligence uptake and factors such as relative advantage, complexity, top management commitment, and organizational preparedness. Nevertheless, factors like competitive pressure, external assistance, a favorable regulatory environment, compatibility, and staff flexibility do not significantly influence the attitude toward the uptake of artificial intelligence. In summary, these findings provide valuable insights for decision-making and resource distribution. They underscore the significance of factors such as relative advantage, complexity, top management commitment, and organizational readiness in achieving goals in the field of artificial intelligence. Additionally, they identify areas where efforts may not result in significant effects. The practical ramifications and future study paths are emphasized according to current technological needs.