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- Research (4)
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- All HBS Web
(4)
- Research (4)
- Faculty Publications (3)
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Results
- May–June 2018
- Article
Data Uncertainty in Markov Chains: Application to Cost-Effectiveness Analyses of Medical Innovations
By: Joel Goh, Mohsen Bayati, Stefanos A. Zenios, Sundeep Singh and David Moore
Cost-effectiveness studies of medical innovations often suffer from data inadequacy. When Markov chains are used as a modeling framework for such studies, this data inadequacy can manifest itself as imprecision in the elements of the transition matrix. In this paper,... View Details
Keywords: Markov Chains; Cost Effectiveness; Medical Innovations; Colorectal Cancer; Health Care and Treatment; Cost vs Benefits; Innovation and Invention; Mathematical Methods; Health Industry
Goh, Joel, Mohsen Bayati, Stefanos A. Zenios, Sundeep Singh, and David Moore. "Data Uncertainty in Markov Chains: Application to Cost-Effectiveness Analyses of Medical Innovations." Operations Research 66, no. 3 (May–June 2018): 697–715. (Winner, 2014 INFORMS Health Applications Society Pierskalla Award & Finalist, 2014 INFORMS George E. Nicholson student paper competition.)
- July–August 2013
- Article
A Joint Model of Usage and Churn in Contractual Settings
By: Eva Ascarza and Bruce G.S. Hardie
As firms become more customer-centric, concepts such as customer equity come to the fore. Any serious attempt to quantify customer equity requires modeling techniques that can provide accurate multiperiod forecasts of customer behavior. Although a number of researchers... View Details
Keywords: Churn; Retention; Contractual Settings; Access Services; Hidden Markov Models; RFM; Latent Variable Models; Customer Value and Value Chain; Consumer Behavior
Ascarza, Eva, and Bruce G.S. Hardie. "A Joint Model of Usage and Churn in Contractual Settings." Marketing Science 32, no. 4 (July–August 2013): 570–590.
- March 2019
- Article
A Structural Analysis of the Role of Superstars in Crowdsourcing Contests
By: Shunyuan Zhang, Param Singh and Anindya Ghose
We investigate the long-term impact of competing against superstars in crowdsourcing contests. Using a unique 50-month longitudinal panel data set on 1677 software design crowdsourcing contests, we illustrate a learning effect where participants are able to improve... View Details
Keywords: Crowdsourcing Contests; Superstar Effect; Bayesian Learning; Utility; Economics Of Information System; Dynamic Structural Model; Dynamic Programming; Markov Chain; Monte Carlo; Learning; Competition; Performance Improvement
Zhang, Shunyuan, Param Singh, and Anindya Ghose. "A Structural Analysis of the Role of Superstars in Crowdsourcing Contests." Information Systems Research 30, no. 1 (March 2019): 15–33.
- 17 Oct 2017
- First Look
First Look at New Research and Ideas, October 17, 2017
Research Data Uncertainty in Markov Chains: Application to Cost-Effectiveness Analyses of Medical Innovations By: Goh, Joel, Mohsen Bayati, Stefanos A. Zenios, Sundeep Singh, and David Moore Abstract—Cost-effectiveness studies of medical... View Details
Keywords: Sean Silverthorne