Discrete Choice Model in the Big Data Era

• SEKI Yoichi

  Division of Electronics and Informatics, Gunma University

書誌事項

タイトル別名

• - Creating Abundant Datasets about Choice Situations -

抄録

The discrete choice model (DCM) is a promising method used to predict the choices of decision-makers. The most basic DCM is a multinomial logit (MNL) model. One of the basic characteristics of this model is that it exhibits independence from irrelevant alternatives (IIA). This property can be seen as a restriction imposed by the model. However, we are now entering a new era where abundant data about choice situations are available. In this era of “big data,” we propose use of a simple MNL model to overcome the problem of IIA by considering interaction effects between the attributes of decision-makers and attributes of alternatives.

収録刊行物

• 日本経営工学会論文誌

  日本経営工学会論文誌 64 (2E), 343-347, 2013

  公益社団法人 日本経営工学会

キーワード

• Multinomial logit model
• Generalized nested logit model
• Independence from irrelevant alternatives
• Interaction effect

詳細情報

• CRID: 1390282680481254784
• NII論文ID: 10031197135
• NII書誌ID: AN10561806
• DOI: 10.11221/jima.64.343
• ISSN: 21879079
• ISSN: 13422618
• 本文言語コード: en
• データソース種別:
  • JaLC
  • CiNii Articles
• 抄録ライセンスフラグ: 使用不可