壽險產業雇主品牌權益 – 選擇式聯合分析法之分析應用

Abstract

本文透過求職者焦點團體訪談，設計出求職者較在意的屬性水準，其中包含品牌、組織文化、加班制度、訓練小時、福利制度、獎金制度、升遷制度、薪資，並利用層級貝氏羅吉斯模式與馬可夫鍊蒙地卡羅估計方法，獲得各水準的個人化成分效用值，並利用效用值與其他變數，如人口統計變數、求職動機、人格特質等進行回歸分析，最終瞭解其他變數如何影響成分效用值，以及透過平均成分效用值之相關係數矩陣，瞭解哪些水準可以被安排在同一職缺項目中，最終，選取其中兩間目標企業，依照雇主品牌權益找出目標求職者，並根據上述分析形成最佳的招募政策，希望藉此提升招募效率與效果。

Through the focus group interviews of job seekers, this thesis designs the attributes and levels that job seekers care about, including brand, organizational culture, overtime, training hours, the welfare system, bonus system, promotion system, and salary. Use the hierarchical Bayesian Logit model and the Markov Chain Monte Carlo estimation method to obtain the individual part-worth value of each level, and use the part-worth value and other variables, such as demographic variables, job search motivation, personality traits, etc. for regression analysis, and finally understand how other variables affect the part-worth value, and through the correlation coefficient matrix of the average part-worth value, understand which levels can be arranged in the same vacancy project. Finally, select two of the target companies and find out target job seekers according to the employer brand equity, and form the best recruitment policy based on the above analysis, hoping to improve recruitment efficiency and effectiveness.