@article{ART001715394},
author={Heuiju Chun and 안철경},
title={A Study on Organizational Outcome of Life Insurance Solicitors Using Negative Binomial Regression Model},
journal={Journal of Insurance and Finance},
issn={2384-3209},
year={2012},
volume={23},
number={4},
pages={29-60}
TY - JOUR
AU - Heuiju Chun
AU - 안철경
TI - A Study on Organizational Outcome of Life Insurance Solicitors Using Negative Binomial Regression Model
JO - Journal of Insurance and Finance
PY - 2012
VL - 23
IS - 4
PB - Korea Insurance Research Institute
SP - 29
EP - 60
SN - 2384-3209
AB - In this study, on the basis of broad questionnaire about life insurance solicitors in Korea, we want not only to investigate whether or not exploratory variables such as belonging company channel, gender, age category, job career in the present company, satisfaction after job transfer, a number of interactions with insurance contractors, organization commitment, job satisfaction, channel management satisfaction affect the number of solicitor's policyholders and monthly new contract number of insurance which are insurance solicitor’s outcome variables but also to fit these outcome variables using negative binomial regression model. We use the number of solicitor's policyholders and monthly new contract number of insurance which stands for future growth to both insurance customers and insurance company as solicitor’s outcome in stead of solicitor’s income which has been used in the previous study.
As the result of study, important factors influential in the number of solicitor's policyholders turn out to be channel management satisfaction,a number of interactions with insurance contractors, job career in the present company, satisfaction after job transfer in order. the number of solicitor's policyholders increases as satisfaction after job transfer increases or a number of interactions with insurance contractors increase.
However, as channel management satisfaction decreases, the number of solicitor's policyholders increases. The factors influential in solicitor’s monthly new insurance contract numbers, followed by belonging company channel, gender, satisfaction after job transfer, organization commitment, channel management satisfaction, age category. Solicitor’s monthly new contract number of insurance increases as satisfaction after job transfer increases or job satisfaction increases. However as organization commitment decreases, Solicitor’s monthly contract number of insurance increases.
KW - insurance solicitor;job outcome;negative binomial regression model;overdispersion;poisson regression model
DO -
UR -
ER -
Heuiju Chun and 안철경. (2012). A Study on Organizational Outcome of Life Insurance Solicitors Using Negative Binomial Regression Model. Journal of Insurance and Finance, 23(4), 29-60.
Heuiju Chun and 안철경. 2012, "A Study on Organizational Outcome of Life Insurance Solicitors Using Negative Binomial Regression Model", Journal of Insurance and Finance, vol.23, no.4 pp.29-60.
Heuiju Chun, 안철경 "A Study on Organizational Outcome of Life Insurance Solicitors Using Negative Binomial Regression Model" Journal of Insurance and Finance 23.4 pp.29-60 (2012) : 29.
Heuiju Chun, 안철경. A Study on Organizational Outcome of Life Insurance Solicitors Using Negative Binomial Regression Model. 2012; 23(4), 29-60.
Heuiju Chun and 안철경. "A Study on Organizational Outcome of Life Insurance Solicitors Using Negative Binomial Regression Model" Journal of Insurance and Finance 23, no.4 (2012) : 29-60.
Heuiju Chun; 안철경. A Study on Organizational Outcome of Life Insurance Solicitors Using Negative Binomial Regression Model. Journal of Insurance and Finance, 23(4), 29-60.
Heuiju Chun; 안철경. A Study on Organizational Outcome of Life Insurance Solicitors Using Negative Binomial Regression Model. Journal of Insurance and Finance. 2012; 23(4) 29-60.
Heuiju Chun, 안철경. A Study on Organizational Outcome of Life Insurance Solicitors Using Negative Binomial Regression Model. 2012; 23(4), 29-60.
Heuiju Chun and 안철경. "A Study on Organizational Outcome of Life Insurance Solicitors Using Negative Binomial Regression Model" Journal of Insurance and Finance 23, no.4 (2012) : 29-60.