Summary of Enhancing Airline Customer Satisfaction: a Machine Learning and Causal Analysis Approach, by Tejas Mirthipati (georgia Institute Of Technology)
Enhancing Airline Customer Satisfaction: A Machine Learning and Causal Analysis Approach
by Tejas Mirthipati
First submitted to arxiv on: 15 May 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Methodology (stat.ME)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The study investigates the connection between airline industry-specific customer satisfaction enhancements and revenue growth. It combines machine learning and causal inference methods to analyze the effects of service improvements on customer satisfaction, focusing on the online boarding pass experience. The research demonstrates that digital aspect improvements significantly increase overall customer satisfaction. This paper provides insights for airlines to make data-driven decisions that enhance customer experiences and market competitiveness. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Airline customers are crucial to retaining business and building a good reputation. This study helps airlines keep their customers happy by improving online boarding pass services. The researchers used special computer tools (machine learning) and statistical methods to find out what affects customer satisfaction. They discovered that making digital improvements can make customers happier overall. This means airlines can use this information to make smart decisions and stay competitive. |
Keywords
» Artificial intelligence » Inference » Machine learning
