Security investment in aviation industry: a longitudinal analysis

Abstract

Purpose

Terrorist attacks have generated interests among practitioners and researchers on transportation security enhancement. This study investigates the role that rationality play in government funding on this important aspect of homeland security. In particular, it examines how environmental changes and project characteristics influence the allocation of security-related Airport Improvement Program (AIP) grants in the aviation industry. The paper aims to discuss these issues.

Design/methodology/approach

The central hypothesis is that rationality regulates transportations security investment through the dynamic balancing between type I error and type II error concerns. To empirically validate it, this study conducts various analyses on AIP history data. In particular, it uses text mining to identify the security-related AIP grants and their coverage, trend analysis to compare the trends of security funding and other transportation investment, and classification tree analysis to determine the factors that influence the allocation of security-related grants.

Findings

The longitudinal distribution of security-related grants differs from other types of transportation funding in terms of their distinct responses to terrorist and economic events. Project characteristics including project coverage and facility location have secondary yet consistent effects on the allocation of security-related grants.

Originality/value

This study empirically validates the concept of rationality in transportation security investment. In particular, the findings support that it in constant moves along both longitudinal and cross-sectional dimensions. The dynamic and multi-facet nature of rationality provides the key for researchers and practitioners to understand security funding in aviation industry.

Citation

Wang, Y., Kofi Andoh-Baidoo, F. and Sun, J. (2014), "Security investment in aviation industry: a longitudinal analysis", Industrial Management & Data Systems, Vol. 114 No. 2, pp. 276-291. https://doi.org/10.1108/IMDS-04-2013-0176