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A minimum of 200 words is required for each question. Please make sure you use proper academic sources and proper APA standards for each answer. A minimum of two outside sources are required for each question. (6 questions)Several standards for assessing which selection predictors should be emphasized are described in the textbook pages (543-556) in attached file. Rank these standards from least important to most important for your organization.2What are the shortcomings of using managerial judgment for assessing a candidate compared to mathematical decision tools? How can you use both judgment and mathematical tools together?3What is a multiple hurdle selection system? What advantages does it have compared to other decision making methods?4Compare lowball, competitive, and best shot approaches to negotiating a job offer. Describe situations when each approach would be most effective.5What are idiosyncratic deals, and why do both job candidates and employers tend to react positively toward them?6What are some of the techniques that an employer might employ to ensure that new hires are effectively brought onboard (i.e. socialized) to their new workplace?
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A minimum of 200 words is required for each question. Please make sure you use
proper academic sources and proper APA standards for each answer. A minimum of two
outside sources are required for each question. (6 questions)
1. Several standards for assessing which selection predictors should be emphasized are
described in the textbook pages (543-556) in attached file. Rank these standards from least
important to most important for your organization.
2. What are the shortcomings of using managerial judgment for assessing a candidate
compared to mathematical decision tools? How can you use both judgment and
mathematical tools together?
3. What is a multiple hurdle selection system? What advantages does it have compared to
other decision making methods?
4. Compare lowball, competitive, and best shot approaches to negotiating a job offer. Describe
situations when each approach would be most effective.
5. What are idiosyncratic deals, and why do both job candidates and employers tend to react
positively toward them?
6. What are some of the techniques that an employer might employ to ensure that new hires
are effectively brought onboard (i.e. socialized) to their new workplace?
The Staffing Organizations Model
Organization
Mission
Goals and Objectives
D
A
I
Organization Strategy
L
Insert unnumbered figure P501
Y
,
HR and Staffing Strategy
Staffing Policies and Programs
Support Activities
Legal compliance
Planning
Job analysis and rewards
Core Staffing Activities
R
Y
Recruitment:
external, internal
Selection:
measurement,
external, internal
A
Employment: decision making, final match
N
Staffing System and Retention Management
2
6
7
5
B
U
hen12680_ch11_538-578.indd 538
3/30/11 9:34 AM
Pa r t F i v e
Staffing Activities: Employment
Chapter Eleven
Decision Making
C h a p t e r T w e lv e
Final Match
D
A
I
L
Y
,
R
Y
A
N
2
6
7
5
B
U
hen12680_ch11_538-578.indd 539
3/30/11 9:34 AM
D
A
I
L
Y
,
R
Y
A
N
2
6
7
5
B
U
hen12680_ch11_538-578.indd 540
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Chapter Eleven
Decision Making
D
Learning Objectives and Introduction
A
Learning Objectives
Introduction
I
Choice of Assessment Method L
Validity Coefficient
Y
Face Validity
Correlation With Other Predictors
,
Adverse Impact
Utility
R
Determining Assessment Scores
Y
Single Predictor
Multiple Predictors
A
Hiring Standards and Cut Scores
N
Description of the Process
Consequences of Cut Scores
2
Methods to Determine Cut Scores
Professional Guidelines
6
Methods of Final Choice
Random Selection
Ranking
Grouping
Ongoing Hiring
7
5
B
U
Decision Makers
Human Resource Professionals
Managers
Employees
Legal Issues
Uniform Guidelines on Employee Selection Procedures
Diversity and Hiring Decisions
hen12680_ch11_538-578.indd 541
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Summary
Discussion Questions
Ethical Issues
Applications
Tanglewood Stores Case
D
A
I
L
Y
,
R
Y
A
N
2
6
7
5
B
U
hen12680_ch11_538-578.indd 542
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Chapter Eleven
Decision Making
543
Learning Objectives and Introduction
Learning Objectives







Be able to interpret validity coefficients
Estimate adverse impact and utility of selection systems
Learn about methods for combining multiple predictors
Establish hiring standards and cut scores
Evaluate various methods of
Dmaking a final selection choice
Understand the roles of various decision makers in the staffing process
Adiversity concerns in the staffing process
Recognize the importance of
I
L
Introduction
The preceding chapters describedYa variety of techniques that organizations can use
to assess candidates. However, ,collecting data on applicants does not ultimately
lead to a straightforward conclusion about who should be selected. Should interviews take precedence over standardized ability tests? Should job experience be
R
the primary focus of selection decisions,
or will organizations make better choices
if experience ratings are supplemented
with data on personality? What role should
Y
experience and education have in selection? In this chapter, we’ll discuss how this
information can be used to makeAdecisions about who will ultimately be hired. As
we will see, subjective factors often
N enter into the decision process. Having methods to resolve any disputes that arise in the process of evaluating candidates in
advance can greatly facilitate efficient decision making and reduce conflict among
2
members of the hiring committee.
When it comes to making final
6 decisions about candidates, it is necessary to
understand the nature of the organization and the jobs being staffed. Organizations
7 needs for customer service might put a stronger
that have strong cultures and heavy
emphasis on candidate personality
5 and values. For jobs with a stronger technical
emphasis, it makes more sense to evaluate candidates on the basis of demonstrated
B
knowledge and skills. Throughout this chapter, you’ll want to consider how your
U factor into staffing decision making.
own organization’s strategic goals
The process of translating predictor scores into assessment scores is broken
down into a series of subtopics. First, techniques for using single predictors and
multiple predictors are discussed. The process used to determine minimum standards (a.k.a. “cut scores”) will be described, as well as the consequences of cut
scores and methods to determine cut scores. Methods of final choice must be considered to determine who from among the finalists will receive a job offer. For all
the preceding decisions, consideration must be given to who should be involved in
the decision process. Finally, legal issues should also guide the decision making.
hen12680_ch11_538-578.indd 543
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544
Part Five
Staffing Activities: Employment
Particular consideration will be given to the Uniform Guidelines on Employee
Selection Procedures (UGESP) and to the role of diversity considerations in hiring
decisions.
Choice of Assessment Method
In our discussions of external and internal selection methods, we listed multiple
criteria to consider when deciding which method(s) to use (e.g., validity, utility).
D
Some of these criteria require more amplification,
specifically validity, correlation
with other predictors (newly discussed
here),
adverse
impact, and utility.
A
I
L
Validity refers to the relationship between predictor and criterion scores. Often
this relationship is assessed using aYcorrelation (see Chapter 7). The correlation
between predictor and criterion scores
, is known as a validity coefficient. The use-
Validity Coefficient
fulness of a predictor is determined on the basis of the practical significance and
statistical significance of its validity coefficient. As was noted in Chapter 7, reliability is a necessary condition for validity.
Selection measures with questionable
R
reliability will have questionable validity.
Y
A
Practical Significance
Practical significance refers to the extent
N to which the predictor adds value to the
prediction of job success. It is assessed by examining the sign and the magnitude
of the validity coefficient.
2
Sign. The sign of the validity coefficient refers to the direction of the relationship
6
between the predictor and the criterion. A useful predictor is one where the sign
7 and is consistent with the logic or theory
of the relationship is positive or negative
behind the predictor.
5
Magnitude. The magnitude of theBvalidity coefficient refers to its size. It can
range from 0 to 1.00, where a coefficient
U of 0 is least desirable and a coefficient of
1.00 is most desirable. The closer the validity coefficient is to 1.00, the more useful
the predictor. Predictors with validity coefficients of 1.00 are not to be expected,
given the inherent difficulties in predicting human behavior. Instead, as shown in
Chapters 8 and 9, validity coefficients for current assessment methods range from
0 to about .60. Any validity coefficient above 0 is better than random selection and
may be somewhat useful. Validities above .15 are moderately useful, and validities
above .30 are highly useful.
hen12680_ch11_538-578.indd 544
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Chapter Eleven
Decision Making
545
Statistical Significance
Statistical significance, as assessed by probability or p values (see Chapter 7), is
another factor that should be used to interpret the validity coefficient. If a validity coefficient has a reasonable p value, chances are good that it would yield a
similar validity coefficient if the same predictor was used with different sets of job
applicants. That is, a reasonable p value indicates that the method of prediction,
rather than chance, produced the observed validity coefficient. Convention has it
that a reasonable level of significance is p < .05. This means there are fewer than 5 chances in 100 of concluding there is a relationship in the population of job applicants when, in fact, there is not. D Caution must be exercised in A using statistical significance as a way to gauge the usefulness of a predictor. Research has clearly shown that nonsignificant validity I coefficients may simply be due to the small samples of employees used to calcuL late the validity coefficient. Rejecting the use of a predictor solely on the basis of a small sample may lead to Y rejecting a predictor that would have been quite acceptable had a larger sample of employees been used to test for validity.1 These , have led some researchers to recommend the use concerns over significance testing of “confidence intervals,” for example, showing that one can be 90% confident that the true validity is no less than .30 and no greater than .40.2 R Y Face Validity Face validity concerns whether A the selection measure appears valid to the applicant. Face validity is potentiallyNimportant to selection decision making in gen- eral, and choice of selection methods in particular, if it affects applicant behavior (willingness to continue in the selection process, performance, and turnover once 2 are closely associated with applicant reactions.3 hired). Judgments of face validity 6 7 If a predictor is to be considered useful, 5 it must add value to the prediction of job success. To add value, it must add to the prediction of success above and beyond the foreB In general, a predictor is more useful if it has a casting powers of current predictors. smaller correlation with other predictors and a higher correlation with the criterion. U Correlation With Other Predictors To assess whether the predictor adds anything new to forecasting, a matrix showing all the correlations between the predictors and the criteria should always be generated. If the correlations between the new predictor and the existing predictors are higher than the correlations between the new predictor and the criterion, the new predictor is not adding much that is new. There are also relatively straightforward techniques, such as multiple regression, that take the correlation among predictors into account.4 hen12680_ch11_538-578.indd 545 3/30/11 9:34 AM 546 Part Five Staffing Activities: Employment Predictors are likely to be highly correlated with one another when their domain of content is similar. For example, both biodata and application blanks may focus on previous training received. Thus, using both biodata and application blanks as predictors may be redundant, and neither one may augment the other much in predicting job success. Adverse Impact A predictor discriminates between people in terms of the likelihood of their success on the job. A predictor may also discriminate by screening out a disproportionate D number of minorities and women. To the extent that this happens, the predictor has adverse impact, and it may result in A legal problems. As a result, when the validity I one predictor has less adverse impact than of alternative predictors is the same and the other predictor, the one with lessLadverse impact should be used. A very difficult judgment call arises when one predictor has high validity and high adverse impact while another Y predictor has low validity and low adverse impact. From the perspective of accurately predicting job performance, the former , predictor should be used. From an equal employment opportunity and affirmative action (EEO/AA) standpoint, the latter predictor is preferable. Balancing the R of the organization’s staffing philosophy ­trade-­offs is difficult and requires use regarding EEO/AA. Later in this chapter Y we consider some possible solutions to this important problem. A N Utility Utility refers to the expected gains to be derived from using a predictor. Expected gains are of two types: hiring success and economic. 2 6 Hiring Success Gain Hiring success refers to the proportion 7 of new hires who turn out to be successful on the job. Hiring success gain refers to the increase in the proportion of success5 as a result of adding a new predictor to the ful new hires that is expected to occur B system yields a success rate of 75% for new selection system. If the current staffing hires, how much of a gain in this success U rate will occur by adding a new predic- tor to the system? The greater the expected gain, the greater the utility of the new predictor. This gain is influenced not only by the validity of the new predictor (as already discussed) but also by the selection ratio and base rate. Selection Ratio. The selection ratio is simply the number of people hired divided by the number of applicants (sr = number hired / number of applicants). The lower the selection ratio, the more useful the predictor. When the selection ratio is low, the organization is more likely to be selecting successful employees. If the selection ratio is low, then the denominator is large or the numerator is small. Both conditions are desirable. A large denominator means that the orga- hen12680_ch11_538-578.indd 546 3/30/11 9:34 AM Chapter Eleven Decision Making 547 nization is reviewing a large number of applicants for the job. The chances of identifying a successful candidate are much better in this situation than when an organization hires the first available person or reviews only a few applicants. A small numerator indicates that the organization is being very stringent with its hiring standards. The organization is hiring people likely to be successful rather than hiring anyone who meets the most basic requirements for the job; it is using high standards to ensure that the very best people are selected. Base Rate. The base rate is defined as the proportion of current employees who are successful on some criterionDor human resource (HR) outcome (br = number of successful employees / number A of employees). A high base rate is desired for obvious reasons. A high base rate may come about from the organization’s staffI with other HR programs, such as training and ing system alone or in combination compensation. L When considering possible use of a new predictor, one issue is whether the Y proportion of successful employees (i.e., the base rate) will increase as a result of , using the new predictor in the staffing system. This is the matter of hiring success gain. Dealing with it requires simultaneous consideration of the organization’s current base rate and selection ratio, as well as the validity of the new predictor. R address this issue. An excerpt is shown in The ­Taylor-­Russell tables help Exhibit 11.1. Y A N Exhibit 11.1 Excerpt From the ­Taylor-­Russell Tables A. Validity .20 .60 B. 2 6 7 5 B U Base Rate .30 Selection Ratio .10 .70 43% 77 33 40 Base Rate .80 Selection Ratio Validity .10 .70 .20 .60 89% 99 83 90 Source: H. C. Taylor and J. T. Russell, “The Relationship of Validity Coefficients to the Practical Effectiveness of Tests in Selection,” Journal of Applied Psychology, 1939, 23, pp. 565–578. hen12680_ch11_538-578.indd 547 3/30/11 9:34 AM 548 Part Five Staffing Activities: Employment The cells in the tables show the percentage of new hires who will turn out to be successful. This is determined by a combination of the validity coefficient for the new predictor, the selection ratio, and the base rate. The top matrix (A) shows the percentage of successful new hires when the base rate is low (.30), the validity coefficient is low (.20) or high (.60), and the selection ratio is low (.10) or high (.70). The bottom matrix (B) shows the percentage of successful new hires when the base rate is high (.80), the validity coefficient is low (.20) or high (.60), and the selection ratio is low (.10) or high (.70). Two illustrations show how these tables may be used. D the decision whether to use a new test to The first illustration has to do with select computer programmers. Assume A that the current test has a validity coefficient of .20. Also assume that a consulting firm has approached the organization I with a new test that has a validity coefficient of .60. Should the organization purL chase and use the new test? At first blush, the answer might seem Y to be yes, because the new test has a substantially higher level of validity. This initial reaction, however, must be gauged in the context of the selection ratio ,and the current base rate. If the current base rate is .80 and the current selection ratio is .70, then, as can be seen in matrix B of Exhibit 11.1, the new selection procedure will only result in a hiring success gain from 83% to 90%. The organization R may already have a very high base rate due to Y quite well (e.g., training, rewards). Hence, other facets of HR management it does even though it has validity of .20, the A base rate of its current predictor is already .80. On the other hand, if the existing base rate of the organization is .30 and the N existing selection ratio is .10, the organization should strongly consider the new test. As shown in matrix A of Exhibit 11.1, the hiring success gain will go from 43% to 77% with the addition of the new test. 2 Russell tables has to do with recruitment A second illustration using the ­Taylor-­ in conjunction with selection. Assume 6that the validity of the organization’s current predictor, a cognitive ability test, is 7.60. Also assume that a new college recruitment program has been very aggressive. As a result, there is a large swell in the 5 ratio has decreased from .70 to .10. The number of applicants, and the selection organization must decide whether toB continue the college recruitment program. An initial reaction may be that the program should be continued because of the U As shown in matrix A of Exhibit 11.1, this large increase in applicants generated. answer would be correct if the current base rate is .30. By decreasing the selection ratio from .70 to .10, the hiring success gain increases from 40% to 77%. On the other hand, if the current base rate is .80, the organization may decide not to continue the program. The hiring success increases from 90% to 99%, which may not justify the very large expense associated with aggressive college recruitment campaigns. The point of these illustrations is that when confronted with the decision of whether to use a new predictor, the decision depends on the validity coefficient, hen12680_ch11_538-578.indd 548 3/30/11 9:34 AM Chapter Eleven Decision Making 549 base rate, and selection ratio. They should not be considered independent of one another. HR professionals should carefully record and monitor base rates and selection ratios. Then, when management asks whether they should use a new predictor, the HR professionals can respond appropriately. The ­Taylor-­Russell tables may be used for any combination of validity coefficient, base rate, and selection ratio values. The values shown in Exhibit 11.1 are excerpts for illustration only; when other values need to be considered, the original tables should be consulted to provide the appropriate answers. D Economic Gain Economic gain refers to the ­bottom-­ A line or monetary impact of a predictor on the org ... Purchase answer to see full attachment

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