{"created":"2021-03-01T07:02:09.571440+00:00","id":42291,"links":{},"metadata":{"_buckets":{"deposit":"e2537aaa-50ab-41b0-8643-7948253b4162"},"_deposit":{"id":"42291","owners":[],"pid":{"revision_id":0,"type":"depid","value":"42291"},"status":"published"},"_oai":{"id":"oai:repository.dl.itc.u-tokyo.ac.jp:00042291","sets":["62:7433:7437","9:7435:7436"]},"item_8_alternative_title_1":{"attribute_name":"その他のタイトル","attribute_value_mlt":[{"subitem_alternative_title":"An Individual Level RF Analysis based on Consumer Behavior Theory: A Hierarchical Bayes Framework on the Pareto/NBD Model"}]},"item_8_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2007-11","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"CIRJE-J-188","bibliographic_titles":[{"bibliographic_title":"Discussion paper series. CIRJE-J"}]}]},"item_8_description_13":{"attribute_name":"フォーマット","attribute_value_mlt":[{"subitem_description":"application/pdf","subitem_description_type":"Other"}]},"item_8_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"This research extends a Pareto/NBD model of customer-base analysis using a hierarchical Bayesian (HB) framework to suit today's customized marketing. The proposed HB model presumes three tried and tested assumptions of Pareto/NBD models: (1) a Poisson purchase process, (2) a memoryless dropout process (i.e., constant hazard rate), and (3) heterogeneity across customers, while relaxing the independence assumption of the purchase and dropout rates and incorporating customer characteristics as covariates. The model also provides useful output for CRM, such as a customer-specific lifetime and survival rate, as by-products of the MCMC estimation. Using two different types of databases --- music CD for e-commerce and FSP data for a department store, the HB model is compared against the benchmark Pareto/NBD model. The study demonstrates that recency-frequency data, in conjunction with customer behavior and characteristics, can provide important insights into direct marketing issues, such as the demographic profile of best customers and whether long-life customers spend more.","subitem_description_type":"Abstract"},{"subitem_description":"RFM 分析で使われるリーセンシー(直近の購買からの経過時間)とフリークエンシー(購買頻度)のデータから、一般的な消費者行動の仮定に基づいて、ある時点での顧客の生存確率を推定する。既存の経験ベイズに基づいたPareto/NBD モデルを階層ベイズの枠組みに改良し、購買率と離脱率を表すパラメータに共変量を組み込むことによって、マーケティングに有益な知見が得られる。実証研究として、日米２種類の顧客購買データを使い、このモデルを評価する。","subitem_description_type":"Abstract"}]},"item_8_description_6":{"attribute_name":"内容記述","attribute_value_mlt":[{"subitem_description":"本文フィルはリンク先を参照のこと","subitem_description_type":"Other"}]},"item_8_full_name_3":{"attribute_name":"著者別名","attribute_value_mlt":[{"nameIdentifiers":[{"nameIdentifier":"97318","nameIdentifierScheme":"WEKO"}],"names":[{"name":"Abe, Makoto"}]}]},"item_8_publisher_20":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"日本経済国際共同センター"}]},"item_8_relation_25":{"attribute_name":"関係URI","attribute_value_mlt":[{"subitem_relation_type_id":{"subitem_relation_type_id_text":"http://www.cirje.e.u-tokyo.ac.jp/research/dp/2007/2007cj188ab.html","subitem_relation_type_select":"URI"}}]},"item_8_source_id_10":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11451834","subitem_source_identifier_type":"NCID"}]},"item_8_subject_15":{"attribute_name":"日本十進分類法","attribute_value_mlt":[{"subitem_subject":"330","subitem_subject_scheme":"NDC"}]},"item_8_text_21":{"attribute_name":"出版者別名","attribute_value_mlt":[{"subitem_text_value":"Center for International Research on the Japanese Economy"}]},"item_8_text_4":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東京大学大学院経済学研究科"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"metadata only access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_14cb"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"阿部, 誠"}],"nameIdentifiers":[{"nameIdentifier":"97317","nameIdentifierScheme":"WEKO"}]}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"CRM","subitem_subject_scheme":"Other"},{"subitem_subject":"One-to-One Marketing","subitem_subject_scheme":"Other"},{"subitem_subject":"Bayesian method","subitem_subject_scheme":"Other"},{"subitem_subject":"MCMC","subitem_subject_scheme":"Other"},{"subitem_subject":"data augmentation","subitem_subject_scheme":"Other"},{"subitem_subject":"マーケティング","subitem_subject_scheme":"Other"},{"subitem_subject":"階層ベイズ","subitem_subject_scheme":"Other"},{"subitem_subject":"MCMC 法","subitem_subject_scheme":"Other"},{"subitem_subject":"データ補完","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"technical report","resourceuri":"http://purl.org/coar/resource_type/c_18gh"}]},"item_title":"消費者行動理論にもとづいた個人レベルのRF分析 : 階層ベイズによるPareto/NBDモデルの改良","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"消費者行動理論にもとづいた個人レベルのRF分析 : 階層ベイズによるPareto/NBDモデルの改良"}]},"item_type_id":"8","owner":"1","path":["7436","7437"],"pubdate":{"attribute_name":"公開日","attribute_value":"2013-06-03"},"publish_date":"2013-06-03","publish_status":"0","recid":"42291","relation_version_is_last":true,"title":["消費者行動理論にもとづいた個人レベルのRF分析 : 階層ベイズによるPareto/NBDモデルの改良"],"weko_creator_id":"1","weko_shared_id":null},"updated":"2022-12-19T04:17:30.319390+00:00"}