Essec\Faculty\Model\Contribution {#2233
  #_index: "academ_contributions"
  #_id: "1309"
  #_source: array:26 [
    "id" => "1309"
    "slug" => "hedonic-prices-and-colinearity-an-empirical-comparison-of-statistical-and-neuronal-solutions"
    "yearMonth" => "2000-05"
    "year" => "2000"
    "title" => "Hedonic Prices and Colinearity: An Empirical Comparison of Statistical and Neuronal Solutions"
    "description" => "DESMET, P. (2000). Hedonic Prices and Colinearity: An Empirical Comparison of Statistical and Neuronal Solutions. <i>Fuzzy Economic Review: review of the International Association for Fuzzy-set Management and Economy</i>, pp. 61-76."
    "authors" => array:1 [
      0 => array:3 [
        "name" => "DESMET Pierre"
        "bid" => "B00000155"
        "slug" => "desmet-pierre"
      ]
    ]
    "ouvrage" => ""
    "keywords" => []
    "updatedAt" => "2021-07-13 14:30:19"
    "publicationUrl" => null
    "publicationInfo" => array:3 [
      "pages" => "61-76"
      "volume" => null
      "number" => null
    ]
    "type" => array:2 [
      "fr" => "Articles"
      "en" => "Journal articles"
    ]
    "support_type" => array:2 [
      "fr" => "Revue scientifique"
      "en" => "Scientific journal"
    ]
    "countries" => array:2 [
      "fr" => null
      "en" => null
    ]
    "abstract" => array:2 [
      "fr" => "La méthode des prix hédoniques est bien adaptée au calcul de prix relatifs et à l'évaluation du rapport qualité prix d'un produit complexe. Sa principale faiblesse réside dans l'utilisation de la régression multiple pour l'estimation des coefficients lorsque les données sont peu nombreuses et les variables corrélées. Dans cet article, différentes méthodes, statistiques et neuronales, sont comparées tant sur le plan de la capacité prédictive que sur celui de la validité faciale des résultats attendus. L'approche neuronale est globalement plus performante que la régression PLS mais aucune des deux méthodes n'apporte de solution acceptable aux problèmes d'interprétation des coefficients (signes et valeurs) issus de la colinéarité."
      "en" => "The hedonic price method is well adapted to the calculation of relative prices and the estimation of the quality price relationship for a complex product. The main weakness lies in the use of multiple regression for the evaluation of the coefficients when there is very little data and when the variables are correlated. In this article, various methods, statistical and neuronal, are compared from both the predictive capacity point of view as well as that of the facial validity of the expected results. The neuronal approach is globally more successful than PLS regression but neither of the two methods leads to an acceptable solution to the problems of interpretation of the coefficients (signs and values ) stemming from colinearity."
    ]
    "authors_fields" => array:2 [
      "fr" => "Marketing"
      "en" => "Marketing"
    ]
    "indexedAt" => "2024-11-18T17:21:41.000Z"
    "docTitle" => "Hedonic Prices and Colinearity: An Empirical Comparison of Statistical and Neuronal Solutions"
    "docSurtitle" => "Articles"
    "authorNames" => "<a href="/cv/desmet-pierre">DESMET Pierre</a>"
    "docDescription" => "<span class="document-property-authors">DESMET Pierre</span><br><span class="document-property-authors_fields">Marketing</span> | <span class="document-property-year">2000</span>"
    "keywordList" => ""
    "docPreview" => "<b>Hedonic Prices and Colinearity: An Empirical Comparison of Statistical and Neuronal Solutions</b><br><span>2000-05 | Articles </span>"
    "docType" => "research"
    "publicationLink" => "<a href="#" target="_blank">Hedonic Prices and Colinearity: An Empirical Comparison of Statistical and Neuronal Solutions</a>"
  ]
  +lang: "fr"
  +"_type": "_doc"
  +"_score": 9.310849
  +"parent": null
}