scholarly journals COMBINING REVEALED AND STATED PREFERENCE DATA TO ESTIMATE THE NONMARKET VALUE OF ECOLOGICAL SERVICES: AN ASSESSMENT OF THE STATE OF THE SCIENCE

2008 ◽  
Vol 22 (5) ◽  
pp. 872-908 ◽  
Author(s):  
John C. Whitehead ◽  
Subhrendu K. Pattanayak ◽  
George L. Van Houtven ◽  
Brett R. Gelso
1999 ◽  
Vol 16 ◽  
pp. 955-961
Author(s):  
Hongzhi Guan ◽  
Kazuo Nishii ◽  
Atsushi Tanaka ◽  
Takeshi Morikawa

2013 ◽  
Vol 55 (2) ◽  
pp. 289-314 ◽  
Author(s):  
Jae Young Choi ◽  
Jungwoo Shin ◽  
Jongsu Lee

Among various methodologies for demand forecasting of new products, the random-coefficient discrete-choice model using stated preference data is considered to be effective because it reflects heterogeneity in consumer preference and enables the design of experiments in the absence of revealedpreference data. Based on estimates drawn from consumer preference data by structural hierarchical Bayesian logit models, this study develops the overall, strategic, demand-side management for new products by combining market share simulation and a rigorous clustering methodology, the Gaussian mixture model. It then applies the process to the empirical case of electronic payment instruments.


2013 ◽  
Vol 28 (3) ◽  
pp. 221-241 ◽  
Author(s):  
George R. Parsons ◽  
Zhe Chen ◽  
Michael K. Hidrue ◽  
Naomi Standing ◽  
Jonathan Lilley

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