scholarly journals Patients’ Preferences Regarding Osteoarthritis Medications: An Adaptive Choice-Based Conjoint Analysis Study

2020 ◽  
Vol Volume 14 ◽  
pp. 2501-2515
Author(s):  
Basem Al-Omari ◽  
Peter McMeekin
Vaccine ◽  
2011 ◽  
Vol 29 (27) ◽  
pp. 4507-4511 ◽  
Author(s):  
Melissa S. Stockwell ◽  
Susan L. Rosenthal ◽  
Lynne A. Sturm ◽  
Rose M. Mays ◽  
Rita M. Bair ◽  
...  

2019 ◽  
Vol 30 (1) ◽  
pp. 48-61
Author(s):  
Heather A. Jantzi ◽  
Matthew B. McSweeney

BMJ Open ◽  
2015 ◽  
Vol 5 (10) ◽  
pp. e009625 ◽  
Author(s):  
Domenica Coxon ◽  
Martin Frisher ◽  
Clare Jinks ◽  
Kelvin Jordan ◽  
Zoe Paskins ◽  
...  

Meat Science ◽  
2017 ◽  
Vol 131 ◽  
pp. 82-89 ◽  
Author(s):  
Liran C. Shan ◽  
Aoife De Brún ◽  
Maeve Henchion ◽  
Chenguang Li ◽  
Celine Murrin ◽  
...  

Author(s):  
Yi Ren ◽  
Panos Y. Papalambros

Conjoint analysis from marketing has been successfully integrated with engineering analysis in design for market systems. The long questionnaires needed for conjoint analysis in relatively complex design decisions can become cumbersome to the human respondents. This paper presents an adaptive questionnaire generation strategy that uses active learning and allows incorporation of engineering knowledge in order to identify efficiently designs with high probability to be optimal. The strategy is based on viewing optimal design as a group identification problem. A running example demonstrates that a good estimation of consumer preference is not always necessary for finding the optimal design and that conjoint analysis could be configured more effectively for the specific purpose of design optimization. Extending the proposed method beyond a homogeneous preference model and noiseless user responses is also discussed.


2004 ◽  
Vol 111 (8) ◽  
pp. 775-779 ◽  
Author(s):  
Amanda J. Bishop ◽  
Theresa M. Marteau ◽  
David Armstrong ◽  
Lyn S. Chitty ◽  
Louise Longworth ◽  
...  

2013 ◽  
Vol 796 ◽  
pp. 462-467 ◽  
Author(s):  
Fang Fang ◽  
Yu'e Chen ◽  
Hong Lu

Conjoint analysis is a method for estimating the relative importance of product attributes and utilities of different levels of a defined product. This research focused on finding out about the concerned attributes and preferable levels of professional badminton sportswear when purchasing and then building the preference models of seamless badminton sportswear. Two questionnaire surveys had been done in this research. Questionnaire I is the basis for getting the top ten attributes that target customers concerns when purchasing. Combined the top ten attributes with development direction, questionnaire II was designed for conjoint analysis study. Totally 20 respondents willing to buy professional badminton sportswear were asked to give his/her purchase intent score for 18 hypothetical product profiles derived from orthogonal design. As results of conjoint analysis study showed, the most preferred levels are light color, tight fitness, raglan sleeve, seamless-knit, good tactility, good moisture absorption and ¥299~400. The preference model of seamless badminton sportswear can be two kinds: relatively higher price and relatively lower price. They all have good cost performance and the relatively higher kind has good moisture absorption and good tactility, the relatively lower kind has preferable good moisture plus anti-bacteria and preferably tactility.


Sign in / Sign up

Export Citation Format

Share Document