Air passengers' purchasing behaviours at airport terminals

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Copyright: Tseng, Wen-Chun
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Abstract
This study analysed air passengers’ choice behaviours with regard to various airport activities (shopping, dining, and entertainment service) and air passengers’ intention to shop in different categories of retailing shops (e.g. duty-free, cosmetics, designer fashion apparel, and electronic goods) in the terminal. Two experimental designs were developed and implemented in this study. Empirical data were collected via online surveys between May 2011 and August 2012 by Pureprofile which is a survey website, and the chosen participators were paid for answering the surveys. Passengers who had visited Sydney International Airport during the previous three months were selected randomly from the Pureprofile database to participate in the study. The binary logit model was configured to model air passengers’ airport consumer behaviours and to estimate the factors influencing these behaviours. The results of the binary logit models showed that travel-related factors, shopping intentions, and socioeconomic factors had different degrees of influence on air passengers’ airport shopping behaviour, airport dining behaviour, and airport entertainment behaviour. The results showed that only the airline business model (low-cost carrier) had a negative influence on the passengers’ airport shopping behaviour, and all other travel-related factors had a positive effect on airport shopping, dining, and entertainment behaviours. It was also found that all shopping intention variables had a negative correlation with the passengers’ airport dining activity. Moreover, the inter-effect of airport consuming activities significantly affected air passengers’ airport consumer behaviours. The utility of airport shopping is influenced positively by air passengers’ airport shopping expenditure but negatively affected by air passengers’ airport dining and entertainment expenditure. In order to develop a model of passengers’ airport retail shopping intentions for different categories of airport retail shops, the binary logit model, mixed logit model, and latent class model were used in this study. The results of the binary logit models showed that passengers’ shopping intentions were influenced to different degrees by the airport retail shop attributes for different categories of airport retail shops. Passengers’ airport shopping intentions to shop for all categories of airport retail shops were also positively related to the time required walk to the shops, but negatively related to the price savings offered. In the mixed logit model, passengers’ opinions about airport shopping were considered as latent variables and, therefore, estimated jointly in the model in order to capture passengers’ perceptions regarding airport shopping behaviours. Furthermore, the variables of passengers’ most recent prior airport shopping experience were estimated as lagging effects in the model. It was found that both latent variables and lagging effects influenced passengers’ airport retail shopping intentions. In terms of latent variables, the results show that passengers did not have any intention to shop at airport duty-free liquor and tobacco shops or cosmetics shops when these were located close to the boarding gate. On the other hand, the results of the lagging effect showed that passengers who spent more time on their last airport retail shopping experience had a weaker intention to shop again at airport retail shops. On the basis of a likelihood ratio criterion, the latent class model fitted the data appropriately and improved the goodness-of-fit relative to the standard BLM and MLM models. In addition, the latent class model incorporated individual socioeconomic status, trip characteristics, attitudes towards airport retail shopping, and last airport retail shopping experience into membership segments, thereby improving the model fit relative to the corresponding latent class model without segment membership. Incorporation of individual characteristics in membership functions appeared to have changed the segment sizes as well as coefficients of airport retail shop attributes. Moreover, air passengers’ potential segments in airport retail shopping were identified by the latent class model. For example, the results of the passengers’ general airport retail shopping intention model showed that passengers in segment 1 were more likely to be females, higher-income earners, or frequent flyers travelling for business purposes.
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Author(s)
Tseng, Wen-Chun
Supervisor(s)
Wu, Cheng-Lung
Douglas, Ian
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Publication Year
2018
Resource Type
Thesis
Degree Type
PhD Doctorate
UNSW Faculty
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