Category evaluation method for business intelligence using a hierarchical Bayes model

Author(s):  
Natsuki Sano ◽  
Katsutoshi Yada ◽  
Tomomichi Suzuki
2019 ◽  
Vol 26 (4) ◽  
pp. 640-657
Author(s):  
Mark Legg ◽  
Murat Hancer

Casinos rely extensively on free slot play (FSP) offers for incentivizing patron visitation. However, there has been a lack of understanding its influence on driving patron visitation and patrons’ valuation of FSP compared to other casino promotional offers. This study conducted a conjoint analysis on patrons’ valuations of FSP compared to other promotional offerings at a casino resort. Moreover, this study investigated the roles inter-casino competition and visitation frequency have on patrons’ perceived valuation of FSP through a hierarchical Bayes model. The results show that competition plays a significant negative role on patrons’ valuation of FSP, while competition held insignificant influence on patrons’ valuation of food and beverage (F&B) comp offers. Additionally, patrons who visited the casino more frequently valued FSP greater, while less active patrons valued F&B comp offers more. Using the study’s results, casinos can increase their margins through increased efficiencies with their promotional offering mix.


2004 ◽  
Vol 26 (4) ◽  
pp. 294-304 ◽  
Author(s):  
R.M. Huggins ◽  
D.Z. Loesch ◽  
G.Q. Qian ◽  
Q.M. Bui ◽  
R.J. Mitchell ◽  
...  

2020 ◽  
Author(s):  
Yuan Tian ◽  
Ishika Luthra ◽  
Xi Zhang

As of April 26, 2020, more than 2,994,958 cases of COVID-19 infection have been confirmed globally, raising a challenging public health issue. A predictive model of the disease would help allocate medical resources and determine social distancing measures more efficiently. In this paper, we gathered case data from Jan 22, 2020 to April 14 for 6 countries to compare different models' proficiency in COVID-19 cases prediction. We assessed the performance of 3 machine learning models including hidden Markov chain model (HMM), hierarchical Bayes model, and long-short-term-memory model (LSTM) using the root-mean-square error (RMSE). The LSTM model had the consistently smallest prediction error rates for tracking the dynamics of incidents cases in 4 countries. In contrast, hierarchical Bayes model provided the most realistic prediction with the capability of identifying a plateau point in the incidents growth curve.


2021 ◽  
Vol 36 (5) ◽  
pp. AG21-C_1-12
Author(s):  
Kohei Hatamoto ◽  
Soichiro Yokoyama ◽  
Tomohisa Yamashita ◽  
Hidenori Kawamura

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