Literaturnachweis - Detailanzeige
Autor/inn/en | Pecorella, Patricia A.; Bowers, David G. |
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Institution | Michigan Univ., Ann Arbor. Inst. for Social Research. |
Titel | Future Performance Trend Indicators: A Current Value Approach to Human Resources Accounting. Report I. Internal Consistencies and Relationships to Performance By Site. Final Report. |
Quelle | (1976), (302 Seiten) |
Beigaben | Tabellen |
Dokumenttyp | gedruckt; Monographie |
Schlagwörter | Accounting; Administration; Cost Effectiveness; Efficiency; Human Resources; Measurement; Organizational Development; Organizational Effectiveness; Organizational Theories; Performance; Performance Criteria; Performance Factors; Productivity; Reliability; Statistical Analysis; Surveys Abrechnung; Buchführung; Buchhaltung; Verwaltung; Kosten-Nutzen-Analyse; Kosten-Nutzen-Denken; Effectiveness; Effektivität; Wirkungsgrad; Humankapital; Messverfahren; Organisationsentwicklung; Unternehmenserfolg; Organisationstheorie; Achievement; Leistung; Leistungsindikator; Produktivität; Reliabilität; Statistische Analyse; Survey; Umfrage; Befragung |
Abstract | Analyses preparatory to construction of a suitable file for generating a system of future performance trend indicators are described. Such a system falls into the category of a current value approach to human resources accounting. It requires that there be a substantial body of data which: (1) uses the work group or unit, not the individual, as the analysis unit; (2) contains standard measures of the human organization and dollar-convertible performance measures, both with high internal consistency; and (3) displays a high frequency of statistically significant relationships of human organization to performance measures. This report presents analyses whose function is to construct a data file with these characteristics. Internal consistency reliabilities of both human organization (survey) data and performance (total variable expenses and absenteeism rate) are shown to be high, and a pattern of human organization-to-performance coefficients results which is eminently usable. It constructs a base from which to take the next steps: multiple regression, time lag and magnitude estimation, and value attribution. (Author/MV) |
Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
Update | 2004/1/01 |