人口統計變項與離職原因之關聯性研究-以某電信公司為例

企業的成功在於「人」，企業要維持競爭力，就必須留住所需的「人才」。雖然，對企業而言，企業內員工適度的流動性，不僅可藉此注入新血、減少不適任人員而保持企業的活性，且讓企業維持一定程度的彈性；但倘若企業內人員的流動性太高，除造成企業招募、訓練的成本增加外，另一方面有可能表示企業體內已暗藏某些問題點。因此，深入探討員工離職原因，並採取適當的因應對策，便是本研究之目的。本研究針對某電信公司已離職人員的離職因素進行探討，研究樣本來源為「電信公司」企業資料庫中五年內自願性離職人員，將離職因素歸納為工作相關因素、組織及工作環境因素、個人因素及外在環境因素進行分析。資料分析方法則採用描述性統計分析及卡方檢定，嘗試從人口統計變項的角度切入，分析不同性別、年齡、教育程度、婚姻狀況、工作年資、職務類型及職級與員工離職因素之間是否存在差異性。研究結果發現：不同的人口統計變項對於離職因素的差異程度不同，如下列： 1、女性傾向因個人因素離職；男性傾向因組織及工作環境因素與外在環境因素離職。 2、年幼者（21-30歲）傾向因工作相關因素離職。 3、已婚者傾向因個人因素離職；未婚者傾向因工作相關因素離職。 4、教育程度對離職因素並無顯著差異。 5、年資較淺者（未滿1年）傾向因工作相關因素離職；年資較深者（4-6年、7-9年及13-15年）傾向因個人因素離職。6、從事行政類、財務類者傾向因個人因素離職。 7、一般職員傾向因工作相關因素與組織及工作環境因素離職；中階/高階主管傾向因個人因素離職。本研究結果將可協助企業瞭解不同人口統計變項下的員工離職原因，並針對不同組群提出差異性的留任計劃，有效規劃人力分佈狀況，進而增加企業競爭力，以達到企業成長目標。

關鍵字

離職；自願性離職；可避免的離職因素；不可避免的離職因素

並列摘要

Human resource is the key success for a firm. In order to maintain the firm competitiveness, the firm should keep the valuable talent. Nevertheless, the human resource flow can recruit new people and terminate indecent people, which can make the firm elastic to a certain degree in human resource management. However, once the flow is so acute to influence the recruitment, increase the training cost, it means certain problem may occur inside the firm. Therefore, this study is to look inside and take the action on why those people leave the jobs. This study is to take a telecommunication company as an example, and to make a research on those people who leave their jobs. The samples come from the voluntary turnover within five years in this telecommunication company’s HR database. The turnover factors are related to work-related correlates, organizational and work environment correlates, personal correlates, and external correlates. The method of data analysis adopts the descriptive statistics, and the chi-square test analysis. Taking the view of the demographic variables, this study analyzes the difference of the dimission to gender, age, educational degree, marital status, seniority, job type and job title. The result is found that the relation is different when the population statistics variant is different to the turnover factors. 1. Women are prone to quit by the personal correlates and men by organizational and work environment correlates, external correlates. 2. Young people, especially aged from 21 to 30, are prone to quit by work-related correlates. 3. Married people are prone to quit by personal correlates and single people by work-related correlates. 4. The educational degree shows no significance to turnover factors. 5. The junior, less than 1 year, are prone to quit by work-related correlates and external correlates and the senior, more than 4 years, by personal correlates. 6. Those people who are devoted to administration and finance are prone to quit by personal correlates. 7. Those people who are lower in job rank are prone to quit by work-related correlates, organizational and work environment correlates, and those who are higher by personal correlates. This study will assist a firm in knowing the reason of the turnover from the population statistics variant. It will give advice on how to settle the retention program to different groups, how to manage the distribution of the human resources, in order to enhance a firm’s competitiveness, and then to reach to the target of a firm’s growth.