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Seeking the Price Rate for Maximizing Profit by Neural Network Simulation - Comparison between the One Price and the Dynamic Pricing

Author

Listed:
  • Toshiko Takeuchi
  • Hiroko Yamanaka
  • Takaho Ueda

Abstract

本稿では,購買者の商品に対する価格感度に着目し,購買者を価格感度によりグループに分け,その価格感度グループごとに最高利益が得られる価格をニューラルネットワークモデルで推定し,ダイナミック・プライシング(ここではグループごとに価格を変えるという意味で用いる)の方が,全体で1つのプライス(ここではワンプライスと呼ぶ)より売上総利益が大きいことをシミュレーションによって示す。さらに,価格感度に代わる属性を決定木分析により探し,ダイナミック・プライシングとワンプライスの売上総利益を比較する。

Suggested Citation

  • Toshiko Takeuchi & Hiroko Yamanaka & Takaho Ueda, 2020. "Seeking the Price Rate for Maximizing Profit by Neural Network Simulation - Comparison between the One Price and the Dynamic Pricing," Gakushuin Economic Papers, Gakushuin University, Faculty of Economics, vol. 56(3-4), pages 19-40.
  • Handle: RePEc:abc:gakuep:56-3-4-2
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