基于行为事件的履历资料评估

摘要： 行为事件的履历资料评估能有效克服传统履历数据构思效度弱、情景限制多等问题。本研究结合某通信企业招聘工作，选取250名应聘者数据，结合关键事件法，通过对履历事件的行为锚定来评估应聘者的胜任特征。研究在多重比较行为履历资料、履历表数据、认知能力等多个指标组合对录用结果预测的回归模型基础上，检验新增指标的预测效度。结果表明，行为事件的履历资料评估具有效标关联效度，与其他工具组合使用时具有增量效度。
Abstract: Biodata is an important method used in primary selection of potential job candidates. It focuses on individual historical information, including the past behaviors and experiences, as individual’s past behaviors can serve as a critical predictor for the future working behaviors. In China, the most frequently used biodata questionnaire is the resume. However, without a systematic method to assess biodata, lots of errors may occur, such as subjective misjudgment. In order to make the best use of Biodata and to promote the accuracy of personal assessment and selection decision, this study standardized the scoring process of behavioral event Biodata according to CIT (critical incident technique) and BARs (behaviorally anchored rating scales), and verified the reliability and validity of behavioral event biodata. One provincial communication company supplied 178 jobs in the Campus Recruitment last year, and more than 6000 students applied. 1500 of them took the exam. The exam included the scales of GMA (General Mental Ability) and the semi-structured resume. 750 applicants took the 2 hours’ exam and 20 minutes’ semi-structured interview. The sample in this study consisted of 250 applicants among the 750. First, we interviewed 5 human resource administrators and defined 5 main selection criterions. After analyzing the applicants’ statements to the open question, 87 critical incidents were extracted. And then all the critical incidents were differentiatexd into 5 criterions by two rounds of rating containing 13 SMEs (Subject Matter Experts, people who have some basic familiarity with appraising work) to insure consistency. Second, we verified and modified the elementary scaling tool. Behaviorial event biodata scoring scale was developed from another round of rating by 6 SMEs. The reliability of the scale was tested. There is no significant differences among the ratings of the 6 raters. Third, we established the BARS scaling tool and rated the applicants’ behavarial event biodata. The relationships among behaviorial BioData and other assessment tools were tested. After the logarithmic transform of the scaling data and the reliability analysis, interactive validity was made among behaviorial event Biodata, GMA and single scored BioData. The result revealed that the relationship is accordant with others researches. Behavioral event Biodata is a