Sato Toshikuni

サトウトシクニ | Sato Toshikuni

Affiliation and department：

Research field (3)： Commerce , Business administration , Statistical science

Research keywords (5)：消費者行動 , 消費者心理 , マーケティング・リサーチ , ベイズ統計学 , 機械学習

Research theme for competitive and other funds (2)：

2022 - 2026 Penalty estimation for the identification of latent variable models in consumer behavior analysis
2020 - 2022 Investigating the identifiability of machine learning and its application to consumer behavior analysis

Papers (8)：

Takumi Kato, Toshikuni Sato. Characteristics of Word-of-Mouth (WOM) by the Interaction Between Feedback Willingness and Incentivized WOM Willingness. Communications in Computer and Information Science (Advanced Research in Technologies, Information, Innovation and Sustainability. ARTIIS 2023.). 2023. 547-560
Toshikuni Sato. Exploring the Replication of Customer Engagement Measurements Using Text Information in the Hotel Industry. 2023 Global Marketing Conference at Seoul Proceedings. 2023. 450-455
Toshikuni Sato. A Penalized Neural Network Model for Predicting Unobserved Scores of Construct Indicators and Reproducing Latent Scores of the Theoretical Constructs by Using Text Information. Lecture Notes in Operations Research (City, Society, and Digital Transformation). 2022. 1-14
Toshikuni Sato. Penalizing Neural Network and Autoencoder for the Analysis of Marketing Measurement Scales in Service Marketing Applications. Lecture Notes in Operations Research (AI and Analytics for Smart Cities and Service Systems). 2021. 31-42
佐藤平国. レビュー・データに基づく顧客経験および属性パフォーマンスが総合評価に与える影響-ニューラルネットワークによる非線形性の推定と可視化-. マーケティング・サイエンス. 2020. 27. 1. 27-62

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MISC (1)：

Toshikuni Sato. Bayesian Estimation for Identifiable Topic Models with Latent Dirichlet Allocation. SSRN Electronic Journal. 2020. 1-24

Lectures and oral presentations (17)：

Exploring the Replication of Customer Engagement Measurements Using Text Information in the Hotel Industry
(2023 Global Marketing Conference at Seoul 2023)
テキストデータを利用したEサービス品質の測定と予測
(日本マーケティング・サイエンス学会第112回研究大会 2022)
A Penalized Neural Network Model for Predicting Unobserved Scores of Construct Indicators and Reproducing Latent Scores of the Theoretical Constructs by Using Text Information
(2022 INFORMS Conference on Service Science (Virtual) 2022)
マーケティング尺度を用いた測定モデルに対する罰則化法 -消費者心理の識別と予測への応用-
(第 63 回消費者行動研究コンファレンス 2021)
Penalizing Neural Network and Autoencoder for the Analysis of Marketing Measurement Scales in Service Marketing Applications
(2021 INFORMS Virtual Conference on Service Science (Virtual) 2021)

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Education (3)：

2017 - 2020 Tohoku University Graduate School of Economics and Management
2015 - 2017 Tohoku University Graduate School of Economics and Management
2011 - 2015 Fukushima University Faculty of Economics and Business Administration Department of Business Administration

Professional career (1)：

Work history (8)：

2022/04 - 現在 Meiji University School of Commerce
2023/09 - 2023/09 Fukushima University Faculty of Economics and Business Administration Department of Business Administration
2020/04 - 2022/03 Ishinomaki Senshu University School of Business Administration
2019/06 - 2020/03 Tohoku University Graduate School of Economics and Management
2019/10 - 2020/01 Tohoku University Graduate School of Economics and Management

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Awards (13)：

2022/07 - 2022 INFORMS Conference on Service Science Best Conference Paper Competition Finalist
2021/08 - 2021 INFORMS Virtual Conference on Service Science Best Conference Paper Competition Finalist
2020/03 - 東北大学総長賞
2020/03 - 公益財団法人経和会記念財団優秀論文賞
2019/11 - 日本マーケティング・サイエンス学会研究奨励賞

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Association Membership(s) (4)：

日本マーケティング・サイエンス学会 , 日本行動計量学会 , 日本商業学会 , 日本消費者行動研究学会

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