• Proceedings of the Korea Association of Information Systems Conference
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• 2000.11a
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• pp.36-44
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• 2000

The purpose of this study is to introduce a more efficient forecasting technique, which could help result the reduction of cost in removing the waste of airline in-flight meals. We will use a neural network approach known to many researchers as the “Outstanding Forecasting Technique”. We employed a multi-layer perceptron neural network using a backpropagation algorithm. We also suggested using other related information to improve the forecasting performances of neural networks. We divided the data into three sets, which are training data set, cross validation data set, and test data set. Time lag variables are still employed in our model according to the general view of time series forecasting. We measured the accuracy of our model by “Mean Square Error”(MSE). The suggested model proved most excellent in serving economy class in-flight meals. Forecasting the exact amount of meals needed for each airline could reduce the waste of meals and therefore, lead to the reduction of cost. Better yet, it could enhance the cost competition of each airline, keep the schedules on time, and lead to better service.

• The Journal of the Korea Contents Association
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• v.14 no.1
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• pp.466-477
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• 2014

This research aims to analyze the importance-performance among airline selection attributes using foreign tourists. For this purpose, data were collected from Japanese and Chinese tourists to Korea. Of the various airline selection attributes, four factors were deduced that includes: transport service, accompany service, cabin service and basic service using exploratory factor analysis. This study estimated how important airline selection attributes are and how much are they performed. Also, this study analyzed the ranking among each selection attributes using T-test. The importance-performance analysis showed 'Concentrate Here' in quadrant I, 'Keep up the Good Work' in quadrant II, 'Low Priority' in quadrant III and 'Possible Overkill' in quadrant IV. Quadrant I specifically showed low performance in terms of the following specific attributes: communicative convenience, flight attendant's friendliness, seating preference. As these attributes are deemed significant, airline managers should focus along these areas.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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• pp.116-130
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• 2019

This study investigates passenger-authored online reviews of airline services using social network analysis to compare the differences in customer perceptions between full service carriers (FSCs) and low cost carriers (LCCs). While deriving words with high frequency and weight matrix based on the text analysis for FSCs and LCCs respectively, we analyze the semantic network (betweenness centrality, eigenvector centrality, degree centrality) to compare the degree of connection between words in online reviews of each airline types using the social network analysis. Then we compare the words with high frequency and the connection degree to gauge their influences in the network. Moreover, we group eight clusters for FSCs and LCCs using the convergence of iterated correlations (CONCOR) analysis. Using the resultant clusters, we match the clusters to dimensions of two types of service quality models ($Gr{\ddot{o}}nroos$, Brady & Cronin (B&C)) to compare the airline service quality and determine which model fits better. From the semantic network analysis, FSCs are mainly related to inflight service words and LCCs are primarily related to the ground service words. The CONCOR analysis reveals that FSCs are mainly related to the dimension of outcome quality in $Gr{\ddot{o}}nroos$ model, but evenly distributed to the dimensions in B&C model. On the other hand, LCCs are primarily related to the dimensions of process quality in both $Gr{\ddot{o}}nroos$ and B&C models. From the CONCOR analysis, we also observe that B&C model fits better than $Gr{\ddot{o}}nroos$ model for the airline service because the former model can capture passenger perceptions more specifically than the latter model can.

• Journal of the Korea Convergence Society
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• v.13 no.2
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• pp.263-272
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• 2022

This study was to examine the effect of job insecurity on their psychological contract violation and job satisfaction among airline crew members. Also, this study intended to give meaningful hint in reducing job insecurity crew members feel, and, by examining ways to relieve psychological contract violation, give theoretical and practical suggestions on human resource management of airlines. The findings from empirical analysis are as follows. First, H 1-1 that job insecurity of airline cabin crew members will have positive effect on their transactional psychological contract violation was adopted. Second, H 1-2 that job insecurity of airline cabin crew members will have positive effect on their relational psychological contract violation was adopted. Third, H 2-1 that transactional psychological contract violation of airline cabin crew members will have negative effect on their job satisfaction was adopted. In contrast, H 2-2 that relational psychological contract violation of airline cabin crew members will have negative effect on their job satisfaction was rejected. Finally, H 3 that job insecurity of airline cabin crew members will have negative effect on their job satisfaction was adopted.

• Knowledge Management Research
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• v.18 no.2
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• pp.103-127
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• 2017

This study examines the effects of failed airline services on the consumers' psychological process and their behavioral responses. Having different classifications from the previous studies, this study focuses on dividing important factors of airline services into search attributes(e.g. sale and procedure services, services concerning flight attendant, in-flight services) and experience attributes(e.g. flight services, collateral services). Using structural equation modeling, this study shows that the failure of service factors of the experience attributes provokes the feeling of disappointment with mediation effect of external attribution while the failure of service factors of search attributes provokes the feeling of regret with mediation effect of internal attribution. Finally, disappointment leads to consumers' complaint behavior while regret leads to consumers' switching behavior. Unlike previous studies, we show that when a service failure occurs, depending on each attribute, consumers feel negative emotions of disappointment or regret through different attribution processes and finally show different behavioral responses with an empirical analysis.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.2
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• pp.137-145
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• 2014

The paper is to investigates how influence service quality satisfaction, trust and repurchase intention using SERVPERF instrument in airline industry. This study will contributes to provide development strategies how to expense market and strength relation between customer to FSC and LCC by an empirical study. This study uses computer software of SPSS 20.0 and AMOS 20.0 for study analysis. The LCC should strengthen the price competitiveness, as well as it needs to establish a strategic management distinguishing service quality from other airline. The airline will has improved service quality of reliability and tangibles since improve service of reliability and tangibles. This study will provide strategic insights and information on service quality in airline industry.

• Journal of the Korea Convergence Society
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• v.11 no.3
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• pp.219-226
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• 2020

This study set the research model to analyze the effect of customer value on brand identification and loyalty using customers of K Airline. Based on previous researches, this study extracted variables, and built a structural equation model to examine the relationship among variables. The findings of empirical research are as follows. First, it was found that functional value and emotional value of customer value have significant effect on brand identification. Thus, hypothesis 1 was accepted. Second, customers seek emotional aspect in choosing a product or a service. That is, by using an airline brand which they think is identical with their image, value, or lifestyle, they pursue brand identification with the airline. Third, given that functional value and emotional value of customer value do not affect brand loyalty, we can know that customer value strengthens brand loyalty through brand identification. To boost brand loyalty, K Airline needs to pay attention to raise brand identification of customers with consideration of other mediating variables.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.15 no.25
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• pp.91-95
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• 1992

The aircraft schedule is the central of an airline's planning process, aimed at optimizing the deployment of airline's resources in order to maximize profits In this paper, the aircraft schedule is formulated as an integer programming model and the exact algorithm hared on enumeration method is proposed.

• Journal of the Korean Institute of Rural Architecture
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• v.16 no.3
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• pp.9-18
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• 2014

Small and medium-sized local airports have suffered from chronic operating deficits due to many factors except for large airports in Incheon, Gimpo, Jeju and Gimhae. These small and medium-sized local airports have currently been degraded to inefficient airports handling the significantly lower airline demand than their carrying capacities. In this context, this study conducted a survey on the actual conditions of the airline demand in small and medium-sized local airports for the last 10 years after the opening of the Korea Train eXpress and investigated the causes and actual conditions of an increase and a decrease in the airline demand. In addition, it analyzed the functionality, convenience and economic feasibility, competition elements in comparison with other means of transportation, and the actual competitive conditions of local airports. It investigated facility improvements through a field visit for local airports and analyzed the performance rate of passenger demands and the use rate of terminal facilities according to a change in the airline demand. This study aimed to provide basic data in the architectural planning field, needed to establish a plan for the airport revitalization of local airports with the results of an analysis on the actual conditions of small and medium-sized local airports.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.26-32
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• 2020

There are many airline customer evaluation data, but they are insufficient in terms of predicting customer satisfaction in practice. In particular, they are generally insufficient in case of verification of data value and development of a customer satisfaction prediction model based on customer evaluation data. In this paper, airline customer satisfaction analysis is conducted through an experiment of correlation analysis between customer evaluation data provided by Google's Kaggle. The difference in accuracy varied according to the three types, which are the overall variables, the top 4 and top 8 variables with the highest correlation. To build an airline customer satisfaction prediction model, they are applied to three classification algorithms of Random Forest, SVM, DNN and conduct a classification experiment. They are divided into training data and verification data by 7:3. As a result, the DNN model showed the lowest accuracy at 86.4%, while the SVM model at 89% and the Random Forest model at 95.7% showed the highest accuracy and performance.