Using data envelopment analysis to measure and improve organizational performance (Record no. 524375)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02122nam a22001577a 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 231110b ||||| |||| 00| 0 eng d |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Sexton, T.R., Pitocoo, C. and Lewis, H. |
| 245 ## - TITLE STATEMENT | |
| Title | Using data envelopment analysis to measure and improve organizational performance |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication, distribution, etc | Public Administration Review |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 83(5), Sep-Oct, 2023: p.1150-1165 |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | Organizations are complex and have many goals while almost all analytical tools measure performance using only one goal. Thus, analysts often rely on multiple analytical tools to produce a bewildering array of performance measures that often lack internal consistency and a clear focus. In this article, we show how data envelopment analysis (DEA) builds a performance frontier (analogous to a production frontier) that measures organizational performance in the presence of multiple organizational measures. The DEA frontier produces target values for each organizational measure based on the observed performance of organizations in the comparison set. In addition, DEA provides factor performance levels for each performance measure for each organization and can detect circumstances in which an organization has a strong overall performance measure but still has weaknesses in one or more measures. We will illustrate this approach with applications to several examples using real data. Analyzing organizational performance data is critical in the organizational improvement process. The data must directly reflect the organization's goals and the analytical tools used must be appropriate. However, organizations are complex and have many goals while univariate analytical tools measure performance relative to only one goal. Thus, analysts often rely on multiple analytical tools to produce a collection of performance measures, sometimes resulting in a bewildering array of measures that lack focus. – Reproduced https://onlinelibrary.wiley.com/doi/10.1111/puar.13679 |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Public Administration |
| 9 (RLIN) | 45977 |
| 773 ## - HOST ITEM ENTRY | |
| Main entry heading | Public Administration Review |
| 906 ## - LOCAL DATA ELEMENT F, LDF (RLIN) | |
| Subject DIP | ORGANISATIONAL PERFORMANCE |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Item type | Articles |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Permanent location | Current location | Date acquired | Serial Enumeration / chronology | Barcode | Date last seen | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Indian Institute of Public Administration | Indian Institute of Public Administration | 2023-11-10 | 83(5), Sep-Oct, 2023: p.1150-1165 | AR130253 | 2023-11-10 | Articles |