A fuzzy Delphi-AHP-TOPSIS framework to identify barriers in big data analytics adoption: case of maritime organizations

Xiunian Zhang and Jasmine Siu Lee Lam

Maritime Policy & Management, 2019, vol. 46, issue 7, 781-801

Abstract: Big data analytics has prospered in recent years and has triggered revolutionary changes in various industries. However, its adoption in maritime organizations is relatively lagged and there is no study addressing this phenomenon so far. This paper develops a fuzzy Delphi-AHP-TOPSIS framework to identify barriers in emerging technology adoption. A case study employs this framework to investigate the hurdles for big data analytics to be adopted in the maritime industry. The case study shows that the framework is useful in identifying and ranking barriers. The results unveil the most serious managerial, cultural, and technical barriers that impede the adoption of big data analytics in maritime organizations.

Date: 2019
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DOI: 10.1080/03088839.2019.1628318

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