• Title/Summary/Keyword: DB(defined benefit) Type

Search Result 2, Processing Time 0.016 seconds

The Impact of Employee's Attributes on Corporate Pension Insurance Products Preference (기업연금보험상품 선호도에 대한 종업원 속성의 영향)

  • Joo, Heon
    • The Korean Journal of Franchise Management
    • /
    • v.7 no.2
    • /
    • pp.27-35
    • /
    • 2016
  • Purpose - The primary objective of this study is to investigate the impact of employee characteristics on employees' preference towards corporate pension products. This study can provide a guidance for maximization of benefits for employees and their affiliated corporation. Employee characteristics include average length of labour, wage system of annual salary, age, types of interest rates and size of corporation. Existing research generally concentrate on vitalizations of corporate pension product raising an imperfection, improvements, tax benefit analysis and legal consideration. Thus, this study intensively analyses the effect of employee attributes on firms' decision for corporate pension products, such as DB(defined benefit) and DC(defined contribution) type. Research design, data, and methodology - The data were collected using self-administrated questionnaire survey on corporate pension products from CEOs or HR directors 250 foreign-invested companies', purchasing pension plans in practice with domestic financial trustees (insurance companies, banks and security companies). Hypotheses testing was conducted using Logistic Regression analysis with SPSS/PC+ 21.0. Results - The findings of the study are as follows. Employees with the long length of labour are more likely to have DB plan; more likely to prefer DC plan with the dividend distribution product regarding the types of interest rate. SMEs(less than 100 employees) are more likely to select DC plan whereas high fluctuation in wage with annual salary has no impacts. In addition, the ages has no significant effect on the preference. Conclusions - This study has examined with the empirical testing that employees' variable attributes and qualities are one of the vital factors for corporation pension plan selection. Currently, majority employees are highly likely to join DB plan and Defined interest types. Corporation with less than 10 employees prefer IRP scheme while most of corporation are intended to join DC plan. In a very near future, corporation more than 300 employees will be required to purchase mandatory plan under national regulation. For maximization of employees' contentment to corporation pension insurance and for complementing the flaws of existing plans, the future studies shall also research in a perspective of employee benefit.

Smart Synthetic Path Search System for Prevention of Hazardous Chemical Accidents and Analysis of Reaction Risk (반응 위험성분석 및 사고방지를 위한 스마트 합성경로 탐색시스템)

  • Jeong, Joonsoo;Kim, Chang Won;Kwak, Dongho;Shin, Dongil
    • Korean Chemical Engineering Research
    • /
    • v.57 no.6
    • /
    • pp.781-789
    • /
    • 2019
  • There are frequent accidents by chemicals during laboratory experiments and pilot plant and reactor operations. It is necessary to find and comprehend relevant information to prevent accidents before starting synthesis experiments. In the process design stage, reaction information is also necessary to prevent runaway reactions. Although there are various sources available for synthesis information, including the Internet, it takes long time to search and is difficult to choose the right path because the substances used in each synthesis method are different. In order to solve these problems, we propose an intelligent synthetic path search system to help researchers shorten the search time for synthetic paths and identify hazardous intermediates that may exist on paths. The system proposed in this study automatically updates the database by collecting information existing on the Internet through Web scraping and crawling using Selenium, a Python package. Based on the depth-first search, the path search performs searches based on the target substance, distinguishes hazardous chemical grades and yields, etc., and suggests all synthetic paths within a defined limit of path steps. For the benefit of each research institution, researchers can register their private data and expand the database according to the format type. The system is being released as open source for free use. The system is expected to find a safer way and help prevent accidents by supporting researchers referring to the suggested paths.