Data Mining for Airline Quality Improvement

Question 1

The rise of information and communication technologies and the advent of social media platforms allow travellers to express their opinions and share their air travel experiences. Table 1 describes a dataset that is collected from an online platform where travellers can evaluate their travel experiences with airlines.

 

Table 1. Description of the dataset

 

(a) Data mining can be used to analyse the dataset and understand the public opinions of the quality of airline services, with an objective to improve customers’ air travel experiences.

 

(i) Give one (1) example of descriptive data mining in this context and discuss how it can be used to achieve the stated objective. (15 marks)
(ii) Give one (1) example of predictive data mining in this context and discuss how it can be used to achieve the stated objective. (15 marks)

 

(b) Suggest two (2) additional variables that can be included in formulating data analytics solutions for understanding customers’ air travel experiences. Explain the rationale of their inclusion. (30 marks) 

 

(c) Assume that there are two interesting findings obtained from the analysis:
• For economy class, most travellers who recommend the airlines give a rating of 4 or above to Value for Money.
• Leisure travellers have a lower mean rating of Inflight Entertainment than other types of travellers.
Give one (1) potential explanation of each finding. Then, propose one (1) solution for improving customers’ air travel experiences based on each finding. (20 marks)

 

(d) Identify one (1) limitation of using the dataset stated in Table 1 to understand air travel experiences and propose one (1) way to address the limitation. (Note: The limitation should not be about the lack of variables you proposed in part (b).) (10 marks)