HUMAN RESOURCES SELECTION

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清华大学卓越生产运营总监高级研修班

综合能力考核表详细内容

HUMAN RESOURCES SELECTION
HUMAN RESOURCES SELECTION
SELECTION
Selection involves:
assessment or measurement of job relevant individual differences,
using these measures to infer how individuals are likely to behave on the job
Making hire/no hire decisions based on these inferences
What Do We Measure?
Our predictors:
Knowledge
Skills
Abilities
Cognitive
Physical
Personality
Vocational Interests
Life history


Behavior on the Job
Typical criteria :

Job performance

Job satisfaction

Turnover

Organization Commitment
Selection Process
Measurement
Ensuring that selection devices are reliable and valid
Decision Making
Combining information about a person to make a hiring decision
Evaluation
Making sure that hiring decisions increase the efficiency and profitability of the organization

Important Statistical Methods
Correlation Analysis – is used to determine the degree of relationship between two variables

Pearson Product Moment correlation coefficient (r) is a numerical index that indicates the direction and degree of linear relationship between two variables

The Correlation Coefficient “r”
The numerical value of “r” ranges from –1.0 to +1.0

The sign of the correlation indicates the direction of the relationship

The magnitude of “r” indicates the strength of the relationship

The numerical index is appropriate only for describing linear relationships

Regression Analysis

Regression analysis is used to model a linear relationship between a dependent variable and one or more independent variables (or predictors )

Equation : Y = a+ bX
Important concepts in Selection

Reliability-- the extent to which a selection test provides consistent results


Validity – the extent to which a test measures what it purports to measure
Measuring Reliability
Test-Retest – examines the consistency of a test over time

Inter-rater – examines consistency across raters

Internal consistency- examines the extent to which all items on a test measure the same construct
Measures of Validity
Validity deals with issues of :

whether the test is an adequate measure of the characteristic it supposedly measures

Whether inferences and actions based on test scores are appropriate
Validity
Content validity – whether or not a test is representative of a constructs domain

Construct validity – whether or not a test measures the traits or abilities it is proposed to measure
Criterion Validity
Whether or not scores on a test are related to an important job related criterion
Predictive – administering a selection test and collecting criterion information later from the same applicants
Concurrent – Administering a selection test to current incumbents and obtaining criterion information at essentially the same time
Concerns in criterion validation
Range Restriction
Sample
Size
How Representative
Dynamic criterion
Validity generalization through the use of meta-analysis

Decision Making
Additive models- test scores are are converted to a common metric sometimes weighted then summed the person with the highest score is hired
Multiple cutoffs – A non- compensatory model in which applicants are required to have minimum scores on each test

Multiple Hurdle – sequential decision making in which applicants pass through several selection stages with some individuals being rejected at each stage

Profile Matching – assumes that there is an ideal level of predictor variables that an applicant should have rather than a minimum that must be met or exceeded.
Selection systems and minority groups

Differential validity
Differential prediction
Adverse Impact



Adjusting test scores of minority group members
Bonus points
Within-group norming
Separate cutoffs
Top down selection from separate lists
Banding

HUMAN RESOURCES SELECTION
 

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