Revenue Optimization Models โดย รศ.ดร.กาญจ์นภา อมรัชกุล
รองศาสตราจารย์ ดร.กาญจ์นภา อมรัชกุล
This text has been developed over several years of teaching courses in revenue management (R.M) at the Graduate School of Applied Statistics, National Institute of Development Administration (NIDA). At the first time the course was offered in 2008 (the year I started teaching at NIDA), there were few other comparable course and only a limited application of quantitative RM models among industries in Thailand. The aieline industry was the first to fully embrace the quantitative RM techniques. Since then, the success of RM in the airline industry has beenwidely publicized, prompting growing interest in revenue optimization across many other industries. including the hotel. car rental. tourism and retail sectors. Inaddition to teaching the RM course at NIDA, I have been a guest lecturer on this topic for related courses at different institutions, including Mahidol University. Sirindhorn International Institute of Technology (SIIT) Thammasat University and Kasetsart University. Since its firt draft in 2008. the book has been used inthese classes and undergone regular updates. Furthermore. the book has greatly benefited from my extensive interactions with the revenue management department at Bangkok Airwaysduring my sabbatical leave. This experience resulted in the manuscript being revised substantially to include a number of managerial insights and bring it more in line with business practices.
Intended to serve as an introductory course in RM, this textbook sets out thefollowing objectives: (1) identify opportunities for price optimization and revenue management in different business contexts, and (2) enable the application of quantitative models for price optimization and RM. The primary audience of this text is students taking an RM course at either undergraduate or postgrasuate level. While the writing styles may not be as theoretically elegant as in journal articles, the main objective of elucidating concepts of price optimization and RM in practical business cases in served.