めも

これはメモ。

no-show予測についてのメモ

本当にただのメモ。

no-show とは

ホテルや病院において「予約したけど実際には現れないケース」がよく存在する。 当然運営側としては「何人かはこないならば、その分を他の客に割り当てたい」し、その分のリソースを他に回せるので予測がしたい。いわゆるRevenue management 問題。

ありがちな応用分野として、以下など。論文が見つかったもののうちで上三つ。

  • 病院やヘルスケア[1]
  • ホテル
  • イベント

[1] Alaeddini, Adel, et al. "A probabilistic model for predicting the probability of no-show in hospital appointments." Health care management science 14.2 (2011): 146-157.

各手法の要約

このような問題設定は、単純に予測を行えば良い、と言った問題ではないものが多い。 病院の例だと、来ないと予測した人が全員きたら病室が足りない=予測が失敗した時に大きなペナルティを払う必要がある。 そのトレードオフのバランシングの方法、利用データ、目的関数の設定(利益maxやミス最小など)でいろいろな設定あり。

ヘルスケア関係

関連手法

  • Patient No-Show Predictive Model Development using Multiple Data Sources for an Effective Overbooking Approach

Huang, Y., and D. A. Hanauer. "Patient no-show predictive model development using multiple data sources for an effective overbooking approach." Applied clinical informatics 5.3 (2014): 836-860.

  • Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review

Goldstein, Benjamin A., et al. "Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review." Journal of the American Medical Informatics Association 24.1 (2017): 198-208.

  • Appointment template redesign in a women’s health clinic using clinical constraints to improve service quality and efficiency

Huang, Y., and S. Verduzco. "Appointment template redesign in a women’s health clinic using clinical constraints to improve service quality and efficiency." Applied clinical informatics 6.2 (2015): 271-287.

ホテルとか関係

関連手法

  • Forecasting cancellation rates for services booking revenue management using data mining

Morales, Dolores Romero, and Jingbo Wang. "Forecasting cancellation rates for services booking revenue management using data mining." European Journal of Operational Research 202.2 (2010): 554-562.

  • Special issue papers: Forecasting and control of passenger bookings

Littlewood, Ken. "Special issue papers: Forecasting and control of passenger bookings." Journal of Revenue and Pricing Management 4.2 (2005): 111-123.

  • Using Data Science to Predict Hotel Booking Cancellations

António, Nuno, Ana de Almeida, and Luis MM Nunes. "Using Data Science to Predict Hotel Booking Cancellations." Handbook of Research on Holistic Optimization Techniques in the Hospitality, Tourism, and Travel Industry (2016): 141.

交通機関関係

背景

Why is over booking of flights allowed? - Quora

関連手法

  • Airline passenger cancellations: modeling, forecasting and impacts on revenue management

Petraru, Oren. Airline passenger cancellations: modeling, forecasting and impacts on revenue management. Diss. Massachusetts Institute of Technology, 2016.

  • Bayesian estimation of hazard models of airline passengers’ cancellation behavior.

Chiew, Esther, Ricardo A. Daziano, and Laurie A. Garrow. "Bayesian estimation of hazard models of airline passengers’ cancellation behavior." Transportation Research Part A: Policy and Practice 96 (2017): 154-167.

  • Passenger-based predictive modeling of airline no-show rates

Lawrence, Richard D., Se June Hong, and Jacques Cherrier. "Passenger-based predictive modeling of airline no-show rates." Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 2003.

  • Air cargo overbooking based on the shipment information record

Becker, Bjoern, and Andreas Wald. "Air cargo overbooking based on the shipment information record." Journal of Revenue and Pricing Management 7.3 (2008): 242-255.

  • Overbooking and fare-class allocation with limited information

Lan, Yingjie, Michael O. Ball, and Itir Z. Karaesmen. "Overbooking and fare-class allocation with limited information." (2007).

  • New approaches to origin and destination and no-show forecasting: Excavating the passenger name records treasure

Neuling, Rainer, Silvia Riedel, and Kai-Uwe Kalka. "New approaches to origin and destination and no-show forecasting: Excavating the passenger name records treasure." Journal of Revenue and Pricing Management 3.1 (2004): 62-72.

  • Can You Get a Ticket? Adaptive Railway Booking Strategies by Customer Value

Wang, Jiana-Fu, and Ren-Huei Huang. "Can You Get a Ticket? Adaptive Railway Booking Strategies by Customer Value." Journal of Public Transportation 19.4 (2016): 1.

  • Forecasting cancellation rates for services booking revenue management using data mining

Morales, Dolores Romero, and Jingbo Wang. "Forecasting cancellation rates for services booking revenue management using data mining." European Journal of Operational Research 202.2 (2010): 554-562.