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Airline Passenger Satisfaction Research

Authors

  • Parv Bhargava
  • Jehan Bugli
  • Namratha Prakash
  • Venkata Madisetty

Research Topic Proposals

Our research focuses on analyzing factors affecting airline passenger satisfaction. We will utilize a survey dataset that contains various aspects of the airline flight experience to evaluate its suitability for creating a logistic regression model predicting passenger satisfaction. This research can be valuable for airlines looking to enhance their customers' experiences and compete effectively in the industry.

We will leverage a dataset that includes surveyed passenger characteristics, flight details, and satisfaction ratings for select pre-flight and in-flight components. To ensure modeling suitability, we will conduct exploratory data analysis, taking into account variable distributions and types.

SMART Questions

Our research aims to answer the following questions:

  1. To what extent do certain surveyed passenger characteristics and flight experience components impact the likelihood that a passenger will be satisfied – rather than neutral or dissatisfied – with their trip?

  2. How can we model the likelihood of passenger satisfaction using surveyed passenger characteristics and flight experience components in a manner that minimizes predictive bias?

  3. To what extent can we predict the likelihood that a flight passenger will be satisfied with their experience using multiple different variable levels?

Data Source

We will use the Airline Passenger Satisfaction dataset for our research. This dataset is sourced from Kaggle and contains information related to airline passenger satisfaction. It comprises 103,904 rows and 25 columns.

GitHub Repository

You can find our research project and related code in our team's GitHub repository. Link to GitHub Repository