Comparing Passenger Satisfaction, Employees’ Perspective and Performance on Quality and Safety Indicators: A Field Study

Abstract

This paper aims to analyze the impact that different attributes related to a Regional Airport service and the socio-economic factors of the passengers have on the passenger’s overall satisfaction. The study also compared passenger and employee satisfaction in relation to the service offered by the airport, to identify possible critical areas of improvement. An Ordinal Logistic Regression (OLR) approach was used to model how the attributes considered for qualifying airport services and the socio-economic variables impact the predicted variable (i.e., passenger satisfaction). Furthermore, the results were triangulated to include quality and safety performance indicators as an objective anchor point for the performance of the company. The findings indicate interesting areas of difference between the perceptions of the passengers and airport employees regarding a company’s services and its performance. The company managers in the key areas of operation were then asked to select the main areas of improvement among the ones highlighted by the survey’s results. Quality and safety indicators were also helpful in enriching the analysis and indicating good synergy with the suggestions collected from the passengers’ and the employees’ surveys, offering yet another complementary perspective.

Criteria of quality assessment of regional airport services - A very last picture before the COVID-19 pandemic

“…The respondents' features are usually presented within the research results ( Bezerra and Gomes, 2016 , 2015 ; Chonsalasin et al, 2020 ; D'Alonzo et al, 2021 ; Prentice and Kadan, 2019 ), but mostly only as sample characteristics. In general, the results are not interpreted in the context of these features.…”

“…Most of the studies were performed as statistical analysis of the data from surveys, e.g. ( Bezerra and Gomes, 2016 , 2015 ; Chonsalasin et al, 2020 ; D'Alonzo et al, 2021 ; Hong et al, 2020 ; Law et al, 2022 ; Prentice and Kadan, 2019 ). However, there has also been fuzzy logic ( Pandey, 2016 ), deep learning ( Barakat et al, 2021 ), or text of reviews analysis ( Bakır et al, 2022 ; Moro et al, 2020 ) implemented to assess the airport service quality.…”

“… Deep learning models (CNN and LSTM) The proposed approach is recommended for use as a complement to more traditional methods of measuring airport service quality. D'Alonzo et al (2021) Analysing the impact that different attributes related to a Regional Airport service and the socio-economic factors of the passengers have on the passenger's overall satisfaction. Ordinal Logistic Regression (OLR) model Indicating interesting areas of difference between the perceptions of the passengers and airport employees.…”

A Hybrid MRA-BN-NN Approach for Analyzing Airport Service Based on User-Generated Contents

“…Nonaeronautical activities, specifically retail and food services, significantly contribute to airport profitability [9,30,55]. Research indicates that an increased variety of food and beverage facilities positively influences service quality and passenger satisfaction [56]. However, high airport retail prices, often because of elevated concession fees, can negatively affect customer satisfaction [30].…”

“…Passengers expect courteous and competent operators for a positive airport experience [16,44,46,60]. Staff orientation toward passenger satisfaction influences service perceptions significantly [7,18,34,56]. The courtesy displayed by airport operators positively influences service perceptions [46,61].…”