This study focuses on the development of new, non-parametric efficiency measures based on the idea of aggregation via merging functions. We use Shephard's (1970) axiomatic approach of distance functions as the basis for theoretical methodology. In particular, this approach is a background for non-parametric efficiency measures defined on a linearly approximated technology set (Farrell, 1957 and Charnes, et al. 1987, and Fare and Grosskopf, 1985).
Two new concerns are discussed: the ambiguity in Farrell efficiency measures and the inconsistency of aggregated Industry efficiency measures with constant returns to scale assumption. As a result, two types of new measures (based on the idea of aggregation) are developed: the average efficiency measures (that take into account both input and output oriented efficiency information) and the industry structural efficiency measures via Geometric Aggregation. The existing efficiency measures as well as newly introduced measures are applied to a sample of U.S. brewing industry. The data supports the importance of new measures and the obtained results are consistent with previous studies that use similar and different (e.g., parametric) approaches. / Graduation date: 2000
| Identifer | oai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/33269 |
| Date | 25 June 1999 |
| Creators | Zelenyuk, Valentin |
| Contributors | Fare, Rolf |
| Source Sets | Oregon State University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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