Published In

IEEE Transactions on Engineering Management

Document Type

Pre-Print

Publication Date

3-2024

Subjects

Cybersecurity, Computer networks -- Security measures

Abstract

Payment processing systems have advanced significantly in the airline business. Because e-payments are easy, they have captured the attention of many companies in the aviation industry and are quickly becoming the dominant means of payment. However, as technology advances, fraud grows at a comparable rate. Over the years, there has been a surge in payment fraud incidents in the airline sector, reducing the platform's trustworthiness. Despite attempts to eliminate epayment fraud, decision-makers lack the technical expertise required to use the finest fraud detection and prevention assessments. This research recognizes the lack of an established decision model as a hurdle and seeks to fix the problem. In response, this research aims to develop a decision model for the airline industry to evaluate the e-payment fraud detection and prevention capabilities of airlines. The literature examines the scope of airline payment fraud to formulate the optimal framework to handle the problem. Guided by the results, the study proceeds to develop an HDM model from experts’ validation, quantification, and desirability inputs. The results of the factors’ validation and quantification show that the Economic and Financial, and the Security perspectives have the most impact on decision-making. Airline companies can use the developed framework to examine whether they are ready to adopt online fraud prevention technologies to increase their success rate. To measure payment organizations' readiness for digital payment fraud protection technologies, a scoring methodology was developed in this research and applied to two case studies.

Rights

© Copyright the author(s) 2024

Description

Pre-Print:

This article has been accepted for publication in IEEE Transactions on Engineering Management. This is the author's version which has not been fully edited and content may change prior to final publication.

Locate the Document

10.1109/TEM.2024.3376314

DOI

10.1109/TEM.2024.3376314

Persistent Identifier

https://archives.pdx.edu/ds/psu/41446

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