Date of Award

Winter 2-28-2022

Document Type

Dissertation - Open Access

Degree Name

Doctor of Philosophy in Aviation

Department

College of Aviation

Committee Chair

Dr. Scott Winter

First Committee Member

Dr. Bruce A. Conway

Second Committee Member

Dr. Joseph R. Keebler

Third Committee Member

Dr. Valerie J. Gawron

Abstract

Aircraft noise has a long and documented history as a source of public annoyance and a driver of noise complaints. The impending large-scale use of unmanned aircraft systems (UAS)s could expose a broader cross-section of the public to a new type of aircraft noise. Recent research notes some reactions to UAS noise, but no rigorous analyses of public intention to complain about UAS noise have been found.

Due to the potential proliferation of UASs and their attendant noise, understanding public reaction could advise both government and industry. Governments at all levels could apply the results to inform policies related to providing the public information about UASs, aircraft certification standards (including noise), airspace use, routing, and restrictions to hours of operation. The industry could apply the results to optimize package delivery routes, determine regulation-compliant locations of operational hubs, and influence design of small package delivery aircraft to minimize noise.

The purpose of the study was to examine factors, as included in an extended theory of planned behavior, that influence individuals’ intentions to complain about UAS noise. The research questions were: 1) what factors influence individuals’ intentions to complain about UAS noise, and 2) how do these factors affect individuals’ intentions to complain about UAS noise? Data were collected through a cross-sectional survey of a convenience sample of adults in the general public within the United States. Confirmatory factor analysis and structural equation modeling were used to analyze the data. An investigation of moderating interaction effects among select factors was also completed. The study examined the relationships between the measured factors and the general public’s intentions to complain about UAS noise.

The results indicated that five factors influence individuals’ intentions to complain about UAS noise. These factors, in order of effect size, are 1) individuals’ attitudes toward complaining about UAS noise, 2) perceived social pressure to complain about UAS noise, 3) perceived usefulness of UASs, 4) perceptions of risks to safety, and 5) familiarity with UASs. Other factors investigated which were not statistically significant include perceived behavioral control, application type/use of UAS, and privacy concerns. The results of the structural model indicated that only one interaction was present at a statistically significant level. Attitude toward complaining about UAS noise and familiarity with UASs showed an interaction effect. As familiarity with UAS increases, the positive relationship between attitude toward complaining about UAS noise and intention to complain about UAS noise was strengthened. The subject research created and validated a theoretical framework which can be used to improve our understanding of and possibly predict individuals’ intentions to complain about UAS noise and help identify significant contributing factors.

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