Research On Aviation Clients Consumption Behavior And Flight Optimization Research

Air transport has been and will be one of the most important transportation means in our country. Along with air transport’s two main characteristics, high speed and high cost, people in China nowadays have chosen air transport as their main travel solution much more frequently than just two decades ago, partially because of the improvement in people’s living standard induced by this country’s rapid economical growth. On the one hand, considerable growth in air transportation indicates our improving living standard or increasing income; on the other hand, it’s also a piece of significant evidence in the strength or this country’s technology and military power. Thus, development of our air transportation industry is strongly related to the process of this country’s long-term development and modernization. In this sense, research on this topic is and will be necessary.In our paper, we first show why consumer behavior analysis is important and necessary to the airplane company governance research. Based on existing literature on this topic, we innovatively utilize the data analysis methods (elasticity calculation and clustering analysis) to show the determinants of consumer choices. We carefully group our consumer order data to separately make policy implication and suggestion for difference consumer group, which is essential to air company decision making. Meantime, we establish a model to describe and forecast the loss of consumers (not based on questionnaire summary). We predict the probability of losing a specific group of consumer, and this will be helpful for an airplane company to make effective marketing policy and prevent losing more costumers. Then we test the so-called the method of ticket over selling. We first illustrate why the airplane company will use such an approach and what determines this choice. We’ve explained the determinants of the no-show rate and more patterns in the undergoing practice of tickets over-selling. We also make no-show rate forecasting, in order to make a more effective over-selling strategy. We also looked at the effects of flight delay spreading. Flights delays have attracted more and more attention from society, and we also have some conventional literature on this topic. Different from those, we researched the effects of flights delay, i.e. the effects of one flight delay on other flights. More specifically, we’ve made the following hypothesis to test:1) more flights in this station will be delayed if more are delayed in the last station;2) if the time length for the first delay is longer, the spread effects are stronger;3) airport itself does impact on flights on-time rate. In the end, we additionally looked on the passengers flow forecasting and flights frequency optimization problem. We first establish a seasonal forecast model based on the passengers flow basic characteristics, then we predict the passenger load for each air line, then the frequency optimization model is established for profit maximization.Our research has made contributions to the literature in the following aspects. First, compared to the fact that few existing literature has access to the customer consumption and order data, we innovatively start our research using these recourses. On the one hand, compared to the logistics and theoretic analysis, we provide more realistic evidence for our argument; on the other hand, consumption and order data is the true reflection of consumer behavior, which is a direct evidence for consumer behavior analysis. Second, based on our data source advantage, we utilized more modern empirical methodology, including clustering analysis, seasonal analysis etc. Third, we contributed to the literature in the sense that we make our starting point from the consumer behavior analysis because customers are the focus of the airplane companies and we can stand on the viewpoint of them, i.e. profit maximization to solve the problem.