A process‐tracing approach toward understanding supervisors' SDy estimates
Results from five job classes
Bibliographic Data
| ID | 14683771 |
|---|---|
| Authors | John E Mathieu (0000-0002-6881-4022, Pennsylvania State University, corresponding author), Scott I Tannenbaum, Scott Tannenbaum (0000-0002-6578-8746, University at Albany, State University of New York) |
| Year | 1989 |
| Volume | 62 |
| Issue | 3 |
| Pages | 249-256 |
| Publication date | 1989-09-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Occupational Psychology (JOURNAL) |
| Journal identifiers | ISSN: 0305-8107 • E-ISSN: 2056-8142 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/j.2044-8325.1989.tb00496.x |
| OpenAlex | W2087222557 |
| Language | EN |
| Citations received | 2 |
Schmidt, Hunter, McKenzie & Muldrow (1979) have proposed a method for using supervisors' estimates of the value of various levels of job performance to calculate the standard deviation of performance in money values—SDy. The use of this procedure has become popular in recent years. However, little is known about how supervisors make such estimates. This study employed a process‐tracing approach to identify the types of information supervisors used to make their estimates. Several different types of information (e.g. salary, overall job responsibilities, work attitudes) were cited consistently across five job classes. Other sources of information were tied more uniquely to certain jobs. Supervisors' percentile estimates were found to conform rather closely to minimum, mean and maximum job class salary levels. Furthermore, more experienced supervisors tended to use salary information and existing organizational documentation for making such estimates. Implications of these findings were discussed in terms of the use of SDy estimates in practice and directions for future research
Documentation · Economics · Job description · Management · Percentile · Political science · Salary · Standard deviation · Statistics · Tracing · Accounting and Organizational Management · Computer Science · Engineering · Law · Mathematics · Psychology
| Citations per year | 0.06 |
|---|---|
| Citation span | 1991 - 2015 (25) |
| Highly cited | No |