Earticle

초록

영어

The government-driven open data policies are on the rise to protect consumers from misunderstandings and monitor the companies. However, in contract-based industries such as insurance, the contract-inherent characteristics make information asymmetry between consumers and companies. Our paper focuses on insurance contracts where the contingency has high uncertainty of occurrence, and the clauses may incur high costs of reading. Given those contracts, we hypothesized that the contract’s clear statement decreases customer dissatisfaction and lowers the number of complaints. To empirically support the claim, we collected customers’ complaint documents of insurance companies and insurance contracts from 2005 until 2017. Our econometric models showed that clearer statements and words significantly reduce the complaints after controlling for firm-specific heterogeneity and time-specific heterogeneity. We identify that insurance companies’ complaint ratio significantly differ depending on the insurance contract, including specific clauses and words.

목차

ABSTRACT
Ⅰ. Introduction
Ⅱ. Conceptual Background
2.1. Incomplete Contract Theory
2.2. Complaints in Insurance Industry
2.3. Insurance Contract and Ambiguity
2.4. Ambiguity Type
2.5. POS tagging & Text mining
Ⅲ. Research Methodology
3.1. Data Source and Data Sampling
3.2. Empirical Methodology
Ⅳ. Data Analysis and result
4.1. Baseline Result
4.2. Ambiguity Index
4.3. Word Class
4.4. Individual Words
4.5. Meanings Analysis
Ⅴ. Conclusion

저자

• Jeongkwon Seo [ Master Student, College of Business, Korea Advanced Institute of Science and Technology, Korea ]
• Woojin Yang [ Ph.D. Student, College of Business, Korea Advanced Institute of Science and Technology, Korea ] Corresponding Author
• Hyejin Mun [ Ph.D. Student, College of Business, Korea Advanced Institute of Science and Technology, Korea ]
• Chul Ho Lee [ Assistant Professor, College of Business, Korea Advanced Institute of Science and Technology, Korea ]

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