Essec\Faculty\Model\Contribution {#2233
  #_index: "academ_contributions"
  #_id: "3609"
  #_source: array:26 [
    "id" => "3609"
    "slug" => "estimating-market-level-multiplicative-models-of-promotion-effect-with-linearly-aggregated-data-a-parametric-approach"
    "yearMonth" => "2002-01"
    "year" => "2002"
    "title" => "Estimating Market-level Multiplicative Models of Promotion Effect with Linearly Aggregated Data: A Parametric Approach"
    "description" => "BEMMAOR, A.C. et WAGNER, U. (2002). Estimating Market-level Multiplicative Models of Promotion Effect with Linearly Aggregated Data: A Parametric Approach. Dans: P-H. Franses, A. L. Montgomery eds. <i>Advances in Econometrics</i>. 1st ed. Bingley: Emerald Group Publishing Limited, pp. 165-189."
    "authors" => array:2 [
      0 => array:3 [
        "name" => "BEMMAOR Albert C."
        "bid" => "B00000029"
        "slug" => "bemmaor-albert-c"
      ]
      1 => array:1 [
        "name" => "WAGNER U."
      ]
    ]
    "ouvrage" => "Advances in Econometrics"
    "keywords" => array:1 [
      0 => "Market level models"
    ]
    "updatedAt" => "2021-09-06 14:06:32"
    "publicationUrl" => "https://doi.org/10.1016/S0731-9053(02)16008-7"
    "publicationInfo" => array:3 [
      "pages" => "165-189"
      "volume" => "16"
      "number" => null
    ]
    "type" => array:2 [
      "fr" => "Chapitres"
      "en" => "Book chapters"
    ]
    "support_type" => array:2 [
      "fr" => "Editeur"
      "en" => "Publisher"
    ]
    "countries" => array:2 [
      "fr" => null
      "en" => null
    ]
    "abstract" => array:2 [
      "fr" => "Les chercheurs en marketing peuvent être confrontés à des biais quand ils estiment des modèles multiplicatifs de promotions des ventes fondés sur des données agrégées de façon linéaire. Ce chapitre montre comment retrouver les paramètres obtenus avec des données qui sont agrégées d'une façon compatible avec ces modèles. Il démontre que la moyenne géométrique des ventes et des prix peut être prédite avec précision à partir de la moyenne arithmétique et de l'écart-type. L'utilisation de ces valeurs prédites dans un modèle au niveau du marché conduit à des paramètres estimés qui sont (1) compatibles  avec ceux obtenus en utilisant les véritables moyennes géométriques et (2) relativement proches des paramètres obtenus au niveau du magasin."
      "en" => "Marketing researchers may be confronted with biases when estimating response coefficients of multiplicative promotion models based on linearly aggregated data. This paper demonstrates how to recover the parameters obtained with data which are aggregated in a compatible way with such models. It provides evidence that the geometric means of sales and of prices across stores can be predicted with accuracy from their arithmetic means and standard deviations. Employing these predictions in a market-level model results in parameter estimates which are consistent with those obtained with the actual geometric means and fairly close to coefficients derived at the individual store level."
    ]
    "authors_fields" => array:2 [
      "fr" => "Marketing"
      "en" => "Marketing"
    ]
    "indexedAt" => "2024-12-03T17:21:44.000Z"
    "docTitle" => "Estimating Market-level Multiplicative Models of Promotion Effect with Linearly Aggregated Data: A Parametric Approach"
    "docSurtitle" => "Chapitres"
    "authorNames" => "<a href="/cv/bemmaor-albert-c">BEMMAOR Albert C.</a>, WAGNER U."
    "docDescription" => "<span class="document-property-authors">BEMMAOR Albert C., WAGNER U.</span><br><span class="document-property-authors_fields">Marketing</span> | <span class="document-property-year">2002</span>"
    "keywordList" => "<a href="#">Market level models</a>"
    "docPreview" => "<b>Estimating Market-level Multiplicative Models of Promotion Effect with Linearly Aggregated Data: A Parametric Approach</b><br><span>2002-01 | Chapitres </span>"
    "docType" => "research"
    "publicationLink" => "<a href="https://doi.org/10.1016/S0731-9053(02)16008-7" target="_blank">Estimating Market-level Multiplicative Models of Promotion Effect with Linearly Aggregated Data: A Parametric Approach</a>"
  ]
  +lang: "fr"
  +"_type": "_doc"
  +"_score": 9.208137
  +"parent": null
}