Jingquan Guo

Bio: Jingquan Guo is an academic researcher from China University of Petroleum. The author has contributed to research in topics: Service (business) & Sentiment analysis. The author has an hindex of 1, co-authored 1 publications receiving 6 citations.

Airline service: low-cost-carriers (LCCs) failure and passenger emotional experience

Abstract: Purpose This study aims to analyze low-cost-carrier (LCC) passengers’ comments about their flight experience on Asian LCCs. Design/methodology/approach A netnography approach was used to review and content analyzed 230 LCC passengers’ negative feedback on the TripAdvisor website. Findings LCC service failures generated 17 different negative emotions; among them, shock, disappointment and surprise were the most frequent emotions felt by passengers. Practical implications Maintaining a high level of customer service and ensuring easy access to information reduces LCC passenger’s negative emotions and meets LCC passengers’ service expectations and satisfaction. This study provides guidelines for the LCCs management who want to implement a netnography technique as a marketing research strategy. Originality/value A better understanding of this concept will help the LCCs industry to build a robust business model than competitors, maintain their competitive advantages in the global market and develop effective marketing strategies to attract more passengers.

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.

Analyzing the Environmental Efficiency of Global Airlines by Continent for Sustainability

Abstract: The study of environmental sustainability in the aviation industry mainly focuses on research targeting specific regions such as the United States, Europe, and China. However, for the environmental sustainability of the aviation industry, global airlines on all continents around the world must implement efficient environmental management. This study divides the world into six continents and attempts to verify environmental efficiency for airlines belonging to each continent. Using data from 2014 to 2018 of 31 global airlines, this study compares environmental efficiency in the aviation industry by continent and individual airline. Data envelopment analysis (DEA), which is actively used in efficiency studies was adopted as an analysis method. We find that, first, airlines in Europe and Russia have the highest environmental efficiency, and airlines in North America and Canada are the second highest, which can be a good benchmark for other airlines. Second, in technical efficiency (TE) values, airlines in Africa and the Middle East and Latin America generally have low efficiency; but, in the airlines in Africa and the Middle East, environmental efficiency is steadily improving slightly. In comparison, airlines in Latin America showed a decrease in environmental efficiency value, requiring a lot of effort and investment to improve efficiency. Third, for airlines in North America and Canada, the scale efficiency (SE) value was the lowest, even though there was a high level of overall environmental efficiency, indicating the need for efficiency improvement through economies of scale. This study has implications, in that, it suggests how airlines can perform efficient environmental management for sustainability according to the continent to which they belong.

Significant labels in sentiment analysis of online customer reviews of airlines

Abstract: Sentiment analysis is becoming an essential tool for analyzing the contents of online customer reviews. This analysis involves identifying the necessary labels to determine whether a comment is positive, negative, or neutral, and the intensity with which the customer’s sentiment is expressed. Based on this information, service companies such as airlines can design and implement a communication strategy to improve their customers’ image of the company and the service received. This study proposes a methodology to identify the significant labels that represent the customers’ sentiments, based on a quantitative variable, that is, the overall rating. The key labels were identified in the comments’ titles, which usually include the words that best define the customer experience. This database was applied to more extensive online customer reviews in order to validate that the identified tags are meaningful for assessing the sentiments expressed in them. The results show that the labels elaborated from the titles are valid for analyzing the feelings in the comments, thus, simplifying the labels to be taken into account when carrying out a sentiment analysis of customers’ online comments.