LINKING O*NET JOB ANALYSIS INFORMATION TO JOB REQUIREMENT PREDICTORS: AN O*NET APPLICATION

This is an exploratory study that examined the possible application of the job component validity (JCV) model to identify potential employee selection instruments and to determine job requirement levels from O*NET job analysis data, following a research paradigm established with the Position Analysis Questionnaire (PAQ). Job requirements were measured by mean aptitude test scores on the General Aptitude Test Battery (GATB), and the ratings on the O*NET Generalized Work Activities (GWAs) were selected as representative O*NET job analysis data. Multiple correlation coefficients ranging from .35 to .89 were found when predicting mean GATB test scores from GWAs. Similar to JCV research some 30 years ago, predictions were strongest for cognitive aptitudes and weakest for manual dexterity. The data were examined under both rational and cross-validated empirical models. The results have positive implications for the development of a database that would support JCV estimates derived from O*NET job analysis data and allow practitioners to use O*NET data to help identify useful employee selection instruments.     

USING A META-ANALYTIC PERSPECTIVE TO ENHANCE JOB COMPONENT VALIDATION

This paper develops synthetic validity estimates based on a meta-analytic-weighted least squares (WLS) approach to job component validity (JCV), using position analysis questionnaire (PAQ) estimates of job characteristics, and the Data, People, & Things ratings from the  Dictionary of Occupational Titles  as indices of job complexity. For the general aptitude test battery database of 40,487 employees, nine validity coefficients were estimated for 192 positions. The predicted validities from the WLS approach had lower estimated variability than would be obtained from either the classic JCV approach or local criterion-related validity studies. Data, People, & Things summary ratings did not consistently moderate validity coefficients, whereas the PAQ data did moderate validity coefficients. In sum, these results suggest that synthetic validity procedures should incorporate a WLS regression approach. Moreover, researchers should consider a comprehensive set of job characteristics when considering job complexity rather than a single aggregated index.     

SYNTHETIC VALIDITY AND ITS APPLICATION TO THE UNIFORM GUIDELINES VALIDATION REQUIREMENTS

The Uniform Guidelines for Employee Selection Procedures have served to create an urgent need for efficient validation methods that can be generalized to a class of occupations. The one method currently authorized for such a purpose by the Guidelines is synthetic validation. (The Guidelines erroneously describe the synthetic validity paradigm as construct validity.) Approaches to synthetic validity employed by Lawshe, Guion, McCormick, and Primoff are described. Their extent of conformance to the Guidelines validation requirements is noted. Primoff's J -Coefficient approach is recommended for two reasons; it meets the Guidelines requirements and under certain circumstances it permits the test user to estimate the traditional validity coefficient. An illustrated example of Primoff's method is presented.     

OCCUPATIONAL PRESTIGE AS A FACTOR IN THE NET RELATIONSHIP BETWEEN OCCUPATION AND JOB SATISFACTION

In contrast to earlier evidence that the relationship between level of occupation and job satisfaction is positive and monotonic, analysis of a recent national survey shows that craftsmen are more job satisfied than other males in clerical, sales, and professional-technical occupations and that this variation is independent of a number of other variables. Removal of occupational prestige modifies the occupation-job satisfaction relationship in a manner which suggests that job satisfaction may arise more from ascribed prestige than from such job characteristics as work autonomy, authority, and income.     

MATCHING INDIVIDUALS TO OCCUPATIONS USING ABILITIES AND THE O*NET: ISSUES AND AN APPLICATION IN CAREER GUIDANCE

The Occupational Information Network (O*NET) is a modern computerized occupational database with the potential to be an important resource for numerous work-related applications. However, developing any O*NET-based application requires working through conceptual, methodological, and practical issues. This article discusses a set of major issues in the context of using the O*NET for person-occupation matching purposes, providing examples of how these issues were addressed in a systematic ability-based matching application developed for career guidance. Specifically, we (a) describe the O*NET and its potential for career guidance, (b) explain person-occupation fit and its positive consequences for individuals and organizations, (c) compare person-occupation fit with person-job fit, (d) discuss matching individuals to occupations empirically using abilities, (e) highlight issues faced in using the O*NJST in this process and give examples of how these issues were addressed in our matching application, and (f) evaluate the functioning of this example matching method.     

高校教师职位O＊NET工作分析研究

本研究采用O*NET工作分析问卷调查法,探讨高校教师职位所需要的重要的工作技能、工作风格及工作价值观.结果表明:(1)高校教师职位重要的工作技能是认知技能和社会技能;重要的工作风格是创新导向、人员导向和成就导向;重要的工作价值观是独立自主和工作条件.(2)认知技能、创新导向、人员导向和成就导向与高校教师的工作绩效有密切联系,可能是高校教师重要的胜任特征.(3)独立自主、成就认可、工作条件与高校教师的教学及总体工作绩效有密切联系.     

USING WEB-BASED FRAME-OF-REFERENCE TRAINING TO DECREASE BIASES IN PERSONALITY-BASED JOB ANALYSIS: AN EXPERIMENTAL FIELD STUDY

We identify sources of biases in personality-based job analysis (PBJA) ratings and offer a Web-based frame-of-reference (FOR) training program to mitigate these biases. Given the use of job analysis data for the development of staffing, performance management, and many other human resource management systems, using biased PBJA ratings is likely to lead to a workforce that is increasingly homogenous in terms of personality but not necessarily a workforce with improved levels of performance. We conducted a field experiment (i.e., full random assignment) using 2 independent samples of employees in a city government and found evidence in support of the presence of biases as well as the effectiveness of the proposed solution. Specifically, FOR training was successful at decreasing the average correlation between job incumbents' self-reported personality and PBJA ratings from .27 to .07 (administrative support assistants) and from .30 to .09 (supervisors). Also, FOR training was successful at decreasing mean PBJA ratings by d = .44 (administrative support assistants) and by d = .68 (supervisors). We offer the entire set of Web-based FOR training materials for use in future research and applications.