Extracting Key Drivers of Air Passenger’s Experience and Satisfaction through Online Review Analysis

Abstract

This study compared the competitiveness of the Commonwealth Independent State Airlines (Azerbaijan Airlines, Air Astana, Aeroflot) with Korean airlines (Asiana Airlines, Korean Air) using customer online reviews through big data analytics. The purpose of this study was to get the understanding of airline issues, especially the relationship between airline traveler experience and satisfaction. This study also shows which group has a better service and is more developed and provides significant and social network-oriented suggestions for another group of airlines. Data were collected from Skytrax and the collected reviews were written from January 2011 to March 2019. The size of the dataset was 1693 reviews, and a total of 199,469 words were extracted. As part of the qualitative analysis method, semantic network analysis through text mining was performed, and linear regression analysis was conducted using SPSS as part of the quantitative analysis method. This study shows which group of airlines has a better service and provides significant and social network-oriented suggestions for another group of airlines. The common concerns, as well as special features for different airlines, can also be extracted from online review data.

How to Achieve Passenger Satisfaction in the Airport? Findings from Regression Analysis and Necessary Condition Analysis Approaches through Online Airport Reviews

“…We live in a digital age, and online reviews, also known as electronic word of mouth, are critical components of service systems [36]. Online reviews reflecting customers' experiences provide information about products, services and brands and allow customers to voice their experiences [37].…”

“…From the managers' point of view, customer reviews provide a wealth of data that enables real-time customer feedback analysis. Thus, online customer reviews provide a cost-effective and timely method of gathering consumer feedback in the air transport industry [36].…”

“…Punel et al [67] concluded that Skytrax is a well-established and reliable indicator of passenger satisfaction in aviation services. In recent years, air transport research has relied on Skytrax as a data source for its inclusive and reliable nature [7,35,36,38,40,[67][68][69]. Due to the richness of the data, the existing literature frequently uses the Skytrax source to reflect online word of mouth [68].…”

Use of Electronic Word of Mouth as Quality Metrics: A Comparison of Airline Reviews on Twitter and Skytrax

“…[25], [26], and [27] utilized tweets to identify polarity directions based on classified service attributes. [28], [29], and [23] collected Skytrax reviews to seek for relationships between service aspects performance and customer satisfaction. Other studies ( [30], [31], and [4]) used data from the review website such as TripAdvisor to measure service quality using unstructured data and converting them into managerial insights.…”

Online Customer Reviews and Satisfaction with an Upscale Hotel: A Case Study of Atlantis, The Palm in Dubai

“…For example, there were two separate files included: file.##h, the named header information dataset, and file.##d containing data lines [52]. UCINET software is used for sentimental analysis by many researchers in the field of hospitality [53][54][55][56]. Based on the previous literature, the following hypotheses were formulated: Hypothesis 1 (H1).…”