Venkateswaran, Aishwarya (2020) The impact of Self-Service Technology (SST) on Passenger Satisfaction - a study for Indian Metropolitan City Airports. Masters thesis, Dublin, National College of Ireland.
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Abstract
Introduction - Airports and airlines are currently integrating self-service technology (SST) into their procedures to provide quick and hassle-free services to passengers. Passenger satisfaction is explained, to some degree, by the level of service quality being offered in airports which includes their SST offering. Therefore, it is essential to empirically understand how SST service quality factors contribute to passenger satisfaction.
Objective - The primary objective of this research is to investigate the impact of service quality of SST on passenger satisfaction levels across Indian Metropolitan City Airports (Ahmedabad, Bangalore, Chennai, Delhi, Hyderabad, Kolkata, and Mumbai). The factors associated with the service quality of SST include functionality, enjoyment, design, security /privacy, assurance, convenience and customization as well as additional factors including shorter waiting time, prompt assistance and passenger traffic management (value addition). Additionally, this research focuses on the safety factor associated with SST in driving satisfaction since the outbreak of COVID-19.
Method - The study employs a cross-sectional research design and follows a quantitative approach. The questionnaire comprises socio-demographic variables, a measure of SST service quality called SSTQUAL developed by Lin and Hsieh (2011), and a measure of passenger satisfaction as a key dependent variable. It was distributed electronically via social media platforms and emails. The research took 18 days to record a total of 300 valid responses out of which 210 met the criteria of using SST in any one of the sample airports over the last 1.5 years. 210 responses were used to analyse the SST service quality while all 300 responses were used for the remaining analysis. Convenience and snowball sampling technique was used to distribute the survey. Statistical analysis included normality test, reliability test, univariate test (Mann-Whitney Test, Kruskal-Wallis Test, Spearman correlation test). The testing of the proposed hypothesis was undertaken through the use of binary logistic regression employing a hierarchical approach.
Result - The primary model included the following independent explanatory variables: the 7 dimensions of SSTQUAL in the first hierarchy and additional constructs (shorter waiting time, prompt assistance and value addition) in the second hierarchy. The dependent variable was passenger satisfaction. Factors significantly associated with higher levels of passenger satisfaction were customization [OR= 1.62, CI = 95%, 1.23 – 2.14], design [OR= 1.54, CI=95%, 1.02 – 2.32], functionality [OR= 1.35, CI = 95%, 1.13-1.61] (hierarchy 1) and the ability of SST to manage passenger traffic (value addition) [OR = 2.02, CI = 95%, 1.02 - 4] from hierarchy 2. This model explained 65% of the variation in passenger satisfaction. Thereby, service quality of SST demonstrates positive significant association with passenger satisfaction. Further, through binary logistic regression analysis, it was noted that ‘safety factor’ of SST during COVID-19 was a predictor of passenger satisfaction [OR = 1.48, CI = 95%, 1.21 – 1.82]. It accounted for over 5% of variance in satisfaction levels.
Conclusion - This research proposes an understanding of the influence of SST service quality on passenger satisfaction in the Indian Airport context. The findings of the research have helped to identify the key contributors to passenger satisfaction in the Indian Airport context. It also gives valuable contribution to the service quality literature that deals with technology and satisfaction. Finally, it gives meaningful implications to airport management to concentrate on effectively addressing SST malfunctions, safety concerns concerning COVID-19 and appropriately design the SST for sustaining the satisfaction of their passengers.
Keywords: service quality, airport, technology, self service technology, satisfaction, SSTQUAL, prompt assistance, waiting time, passenger traffic management, COVID-19
Item Type: | Thesis (Masters) |
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Subjects: | H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management H Social Sciences > HF Commerce > Customer Service |
Divisions: | School of Business > Master of Science in Management |
Depositing User: | Dan English |
Date Deposited: | 06 Feb 2021 15:17 |
Last Modified: | 06 Feb 2021 15:17 |
URI: | https://norma.ncirl.ie/id/eprint/4690 |
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