Earticle

초록

영어

An extended warranty, sometimes called a service agreement, a service contract, or a maintenance agreement, is a prolonged warranty offered to consumers. Studying the extended warranty is extremely important for business investors and policymakers for effective warranty planning. However, measuring, forecasting and tracking the global diffusion of extended warranty have not been researched. This study uses model based on the knowledge of traditional diffusion theory as well as artificial neural networks. Additionally, it integrates the two into a hybrid model in order to study extended warranty growth. A count of greenery warranty can be used as a reliable measure of extended warranty growth in all the models. Our study demonstrates that a logistic Neural Network model, if properly calibrated, can create a very flexible response function to forecast the extended warranty claims. The logistic neural network successfully modeled both the usual and environmental influences in the warranty data, while the traditional formulation could only model the usual warranty claims. Logistic, artificial neural network and logistic neural network analysis are carried out on the green warranty presenting to a warranty repair department.

목차

Abstract
 1. Introduction
 2. Extended Warranty Processing
 3. Missing Treatment by Variation Relations
 4. Results and Analysis
 5. Conclusion and Future Work
 Acknowledgements
 References

키워드

저자

• Lee Sang-Hyun [ Dept. of Computer Engineering, Honam University, Korea ]
• Lim Jong-Han [ Dept. of Mechanical and Automotive Engineering, Gachon University, Korea ] Corresponding author
• Moon Kyung-Il [ Dept. of Computer Engineering, Honam University, Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Security and Its Applications

• 간기

  격월간

• pISSN

  1738-9976

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605