TY  - BOOK
AU  - Wöber,Karl W.
ED  - C.A.B. International,
TI  - Benchmarking in tourism and hospitality industries: the selection of benchmarking partners 
AV  - G155.A1 W56 2002eb
U1  - 338.4/791/068 23
PY  - 2002///
CY  - Wallingford, Oxfordshire, UK
PB  - CABI
KW  - Hospitality industry
KW  - Management
KW  - Tourism
KW  - Benchmarking (Management)
KW  - Leisure, Recreation and Tourism Economics, (New March 2000)
KW  - Tourism and Travel
KW  - Mathematics and Statistics
KW  - cabt
KW  - Hotels
KW  - Measurement
KW  - Production functions
KW  - Regression analysis
KW  - Statistical analysis
KW  - Tourist industry
KW  - Electronic books
N1  - Includes bibliographical references (pages 234-256) and index; Benchmarking studies in the tourism and hospitality industries -- Measuring business performance -- Methods for estimating the production function -- The Austrian Hotel and restaurant panel -- A mixture regression model -- Data envelopment analysis -- Evolutionary data envelopment analysis -- Perspectives of benchmarking decision support systems in tourism and hospitality management; Access limited to subscribing institution; Also available in print format
N2  - This book provides a detailed description of different performance measurement methods in the context of the tourism and hospitality industry. Chapter 1 serves as an introduction to the principal concept of benchmarking and why it became so popular within the industry. Chapter 2 consists of a comprehensive description of studies on the practice of benchmarking in the tourism and hospitality industry. Chapter 3 deals with theoretical issues related to the measurement of business performance. Chapter 4 presents analytical techniques for estimating the unknown production function, basically classified as central tendency and frontier methods. Chapter 5 introduces the database (the Austrian Hotel and Restaurant Panel, 1991-97) used in the subsequent experimental studies and elaborates on existing performance studies in tourism research. Chapter 6 focuses on the application of mixture regression models as a central tendency's approach for the selection of optimal comparison partners. It includes an illustrative case example for the Austrian hotel and restaurant database. Chapter 7 discusses the data envelopment analysis (DEA) models and illustrates these using numerical examples. Chapter 8 introduces evolutionary data envelopment analysis, a completely new optimization technique for DEA problems to overcome at least some of DEA's main restrictions. Chapter 9 discusses developments and issues that are relevant for the future of benchmarking decision support systems and summarizes the most important research questions surrounding them. The book has a subject index
UR  - https://dx.doi.org/10.1079/9780851995533.0000
ER  -