Determinants of an Organization's Readiness for Drone Technologies Adoption

• Published in: IEEE transactions on engineering management Vol. 71; pp. 43 - 57
• Main Authors: Ali, Sadia Samar, Kaur, Rajbir, Gupta, Himanshu, Ahmad, Zulfiqar, Elnaggar, Ghada
• Format: Journal Article
• Language: English
• Published: New York IEEE 2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: best-worst method (BWM); Competitive advantage; Complexity theory; Costs; Customers; Decision analysis; determinants; diffusions-of-innovation (DOI); drone; Drones; Multiple criteria decision making; Multiple criterion; Organizations; Regulation; Technological innovation; Technology; Technology adoption; technology-organisation-environment (TOE); Testing; Unmanned aerial vehicles
• ISSN: 0018-9391; 1558-0040
• DOI: 10.1109/TEM.2021.3083138

Increased use of unmanned arial vechieles has generated interest in the scope of its applications in alternate fields motivating organizations to integrate these smart flying robots in their systems. Looking at the significant rise in drone usage in diversified fields of industrial operations, organization must capture on its value for competetive advantage and outreach to vast customer community. Theoretical foundations of technology-organisation-environment and diffusions-of-innovation are taken along with expert opinion to identify the determinants of an organizations readiness for the adoption of drone in their systems. A multicriteria decision analysis method, the best worst method is applied here to evaluate and priortize the determinants of drone adoption. The results depict cost parameters of technology, competiton, trading partners' advantage and top management as strong supporters of the adoption. The complexity and compatibility along with customer perception and regulations need more considerations for effective results. This article offers valuable insights to practitioners as well as future researchers regarding soft dimensions of drone adoption and navigates them to work on their operational and industrial environemnt to derive maximum benefits.