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Mots-clefs : capital de marque, avis en ligne, intention d’achat, notoriété de la marque, la valeur perçue de la marque,

Résumé : Cette étude a pour but de souligner l’importance des dimensions du capital de marque qui jouent un rôle de médiateur entre les avis en ligne et l’intention d’achat du consommateur. De nombreux consommateurs considèrent les avis en ligne comme une source d’information plus crédible que les autres sources d’information traditionnelles (Fang et al., 2016).
Les consommateurs ont le plus haut niveau de confiance dans les canaux partagés comme les évaluations des consommateurs en ligne ou les médias sociaux. Les consommateurs recherchent généralement les opinions et les recommandations d’autres consommateurs pour évaluer la performance de la marque (Jacobsen, 2018).

“Les dimensions de la valeur de la marque sont affectées lorsque les consommateurs passent en revue diverses évaluations en ligne sur les marques (qu’ils perçoivent comme crédibles) et essaient de les évaluer pour porter un jugement sur la marque (Buil et al., 2013 ; Rios et Riquelme, 2010).”

Conclusion : Cette étude conclut en affirmant que la notoriété de la marque et la valeur perçue, ont un effet de médiation partiel significatif entre les avis en ligne crédibles de la source et l’intention d’achat.
La personnalité de la marque, l’association organisationnelle et la qualité perçue, n’ont eu aucun effet de médiation entre les avis en ligne crédibles et l’intention d’achat.
Dans cette étude les consommateurs indiens utilisent les avis en ligne pour connaître la marque et son rapport coût-efficacité, ce qui influence leur intention d’achat. Les consommateurs indiens préfèrent une recommandation sur le caractère unique de la marque de la part d’une personne qu’ils connaissent personnellement plutôt qu’une recommandation en ligne émanant d’un étranger.

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Mots-clefs : acheteurs sociaux, social shopping, avis en ligne, évaluation, notes d’évaluation, contenu de l’évaluation, profils des acheteurs sociaux.

Résumé : Cet article a pour but d’évaluer les relations entre cinq caractéristiques des évaluations en ligne des acheteurs sociaux : le nombre d’évaluations faites par un évaluateur, le nombre d’amis d’un évaluateur, la note d’évaluation, le nombre de mots d’évaluation et les images/photos.
Les avis en ligne sont perçus comme plus utiles que les communications des marques et entreprises, étant plus impartiales et donc non portée par un objectif commercial.

Le social shopping est le fait de vendre ses produits via des plateformes en ligne spécialisée dans la vente avec remise élevée (ex : Groupon). Cette expérience d’achat est généralement immédiate et représente souvent une première expérience. De ce fait les avis d’autres consommateurs deviennent un critère d’évaluation essentiel.

Les sites d’évaluation en ligne aident les acheteurs sociaux à prendre des décisions éclairées sur les produits/services. Les acheteurs sociaux sont différents des acheteurs traditionnels, ils sont décisifs, ils connaissent les technologies et sont bien informés. Les clients de groupes sont beaucoup plus critiques que les clients réguliers, avec des commentaires plus sévères, et beaucoup sont des clients de passage sensibles au prix.

“Les évaluations en ligne permettent aux consommateurs de partager leur expérience directe avec d’autres consommateurs qui s’attendent à ce que l’évaluation soit crédible et utile pour leur expérience future (Casalo et al., 2010).”

Conclusion : Cette étude montre que la perception de l’utilité, de l’humour et de la sérénité des spectateurs peut dépendre de la combinaison des notes d’évaluation, du contenu de l’évaluation et des profils des acheteurs sociaux.
L’article prouve que le nombre de mot est important pour les récepteurs de l’avis.
Un évaluateur qui a plus d’amis dans son réseau social et qui écrit des commentaires plus longs a tendance à avoir plus d’influence sur la valeur perçue de l’évaluation. Il est ainsi plus crédible aux yeux des récepteurs de l’avis.

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Mots-clefs : avis en ligne, émotions, émotions négatives, crédibilité, intensité négative, utilité, prise de décision des consommateurs.

Résumé : Cet article a pour but de définir l’utilité des émotions négatives dans les avis en ligne et leur impact. L’étude se base ainsi sur des données empiriques et une méthodologie exploratoire dans le contexte de l’hôtellerie. Avec le web 2.0 les avis et commentaires en ligne sont devenus une source majeure d’évaluation aiguillant le consommateur. Nous apprenons dans cet écrit que selon une enquête eMarketer de 2014 que 79% des consommateurs lisent les avis avant un achat et que ceux-ci influencent leur décision.

Selon l’article et des études antérieures, les avis sont influencés par de nombreuses caractéristiques : les informations descriptives de l’identité, le sexe et l’expertise (Forman et al., 2008 ; Lee et al., 2011), le style et la qualité des avis (Jensen et al., 2013 ; Li et al., 2013) et les notes des avis (Mudambi et Schuff, 2010).

Les avis négatifs sont reconnus comme plus influents que les avis positifs : 80% des consommateurs ont changé d’avis sur un produit suite à des avis négatifs (eMarketer 2011).

Cependant les auteurs définissent que l’anonymat des avis en ligne permet d’exprimer plus facilement ses émotions, notamment négatives. L’étude démontrera que les avis négatifs se sont montrés plus utiles que les avis positifs. “Ils estiment que les avis négatifs, par rapport aux avis positifs, sont plus perspicaces, plus diagnostiques et plus utiles pour prendre des décisions éclairées et meilleures”. L’article démontre également que plus l’émotion négative est importante et exprimée, moins l’avis est considéré comme utile. Il ya donc un degrés d’importance de l’émotion, le contenu et sa crédibilité sont analysés par le consommateur.

Cependant une étude de Ammon (2015) indique que les mauvais commentaires donnent plus de crédibilité aux bons commentaires avec une apparence plus honnête et offrent directement de la crédibilité, dans ce cas, aux hôtels.

Conclusion : Cette étude a prouvé que les évaluations négatives avaient leur importance tout comme le niveau et/ou degrés d’émotion exprimé dans un commentaire. Les consommateurs accordent plus d’importance et de crédibilité aux avis négatifs et trouvent même étrange si il n’y a que des effets positifs. “Selon Ammon (2015), des études réalisées par Reevoo, un site d’évaluation des clients, indiquent que 95 % des consommateurs sont méfiants à l’égard des évaluations sur les sites d’évaluation générés par les utilisateurs lorsqu’il n’y a pas de mauvais résultats”.
Cependant l’étude définie également qu’un avis trop négatif perd de la valeur, plus il y a d’expressions émotionnelles moins le commentaire est considéré crédible. L’intensité négative des expressions émotionnelles est un élément essentiel du jugement et de la crédibilité des avis en ligne et produits eux mêmes.

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Mirtalaie M, Hussain O, Chang E, Hussain F, (2018), Extracting sentiment knowledge from pros/cons product reviews: Discovering features along with the polarity strength of their associated opinions, Expert Systems with Applications, Volume 114, 30 December 2018, Pages 267-288

https://www.sciencedirect.com/science/article/abs/pii/S0957417418304718

Mots clés : Analyse des sentiments basé sur les fonctionnalités, Avantages / inconvénients des produits,Force de polarité, Arborescence des produits

Résumé : L’extraction des connaissances sur les sentiments est un domaine de recherche en croissance dans la littérature. Il aide à analyser les opinions des utilisateurs sur différentes entités ou événements, qui peuvent ensuite être utilisées par les analystes à diverses fins. En particulier, l’analyse des sentiments basée sur les fonctionnalités est l’un des domaines de recherche difficiles qui analyse les opinions des utilisateurs sur les différentes fonctionnalités d’un produit ou d’un service. Parmi les trois formats pour les évaluations de produits, notre objectif dans cet article se limite à l’analyse du type avantages / inconvénients. En raison de la nature des avis pour / contre, ils sont généralement concis et suivent une structure différente des autres types d’avis. Par conséquent, des techniques spécialisées sont nécessaires pour analyser ces avis et extraire les caractéristiques des produits discutés par les clients ainsi que leurs attitudes personnelles

Grandes lignes :

• Extraction de fonctionnalités à l’aide de règles syntaxique à partir des avis pour / contre.
• Déterminer la polarité de l’opinion en fonction de sa force émotionnelle.
• Comparer les résultats avec des approches de pointe dans différentes tâches.

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Sun X, Han M, Feng J, (2019), Helpfulness of online reviews: Examining review informativeness and classification thresholds by search products and experience products, Decision Support Systems, Volume 124, September 2019, 113099

https://www.sciencedirect.com/science/article/pii/S0167923619301289

Mots clés : Avis en ligne, Recherche de produits, Découverte de produits, Prédiction de l’utilité

Résumé : La surcharge d’informations rend souvent difficile pour les consommateurs d’identifier les avis de produits en ligne utiles grâce à la fonction traditionnelle de « votes utiles»; par conséquent, il est devenu particulièrement important d’identifier efficacement les avis utiles. En différenciant les produits de recherche des produits d’expérience, cette recherche examine l’impact de différentes mesures de l’information communiquée par les avis sur l’utilité des avis et propose différents seuils de classification pour identifier individuellement l’utilité des avis en ligne pour les produits de recherche et pour les produits d’expérience, respectivement. Toutes les expériences ont été menées à l’aide d’un ensemble de données de JD.com, l’un des plus grands marchés électroniques en ligne en Chine. Nos résultats offrent des lignes directrices pour concevoir différentes normes de classification de l’utilité pour les produits de recherche et pour les produits d’expérience.

Grandes lignes :

• Les différences entre les produits de recherche et les produits d’expérience modèrent la perception des consommateurs quant à l’utilité des avis.
• Nous confirmons différents seuils de classification pour les produits de recherche et d’expérience.
• Amélioration des performances de classification grâce à nos variables et seuils proposés
• Le nombre d’attributs et la longueur moyenne des attributs mesurent le caractère informatif de l’examen.

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Li K, Chen Y, Zhang L, (2020), Exploring the influence of online reviews and motivating factors on sales: A meta-analytic study and the moderating role of product category, Journal of Retailing and Consumer Services, Volume 55, July 2020, 102107

https://www.sciencedirect.com/science/article/abs/pii/S0969698919304011

Mots clés : Avis en ligne, Facteurs motivants, Ventes de produits, Catégorie de produit, Méta-analyse, Effet modérateur

Résumé : Les avis en ligne, qui influencent considérablement les ventes de produits, ont été un sujet de recherche central dans le domaine du marketing. Pendant ce temps, certains facteurs de motivation liés aux détaillants en ligne ont été liés aux ventes de produits. Alors que plusieurs articles ont examiné l’impact entre les critiques en ligne et les facteurs de motivation sur les ventes de produits, de nombreuses conclusions tirées sont contradictoires. À partir de 28 études axées sur les avis et les ventes en ligne, cette étude effectue une méta-analyse pour analyser les véritables impacts de six facteurs liés aux avis (c.-à-d. Le nombre d’avis, le nombre d’étoiles, l’écart-type des notes, l’utilité, la durée de l’avis et le sentiment) et deux facteurs de motivation (c.-à-d. rabais sur les prix et expédition spéciale) sur les ventes de produits. Pendant ce temps, ce document étudie également comment un facteur lié au produit (c.-à-d. L’âge du produit) et un facteur lié aux examinateurs (i. e., la réputation de l’examinateur) influencent la relation entre les avis en ligne et les ventes de produits. De plus, pour étudier l’effet modérateur de la catégorie de produits, nous divisons la littérature sélectionnée en deux sous-groupes qui sont des produits de recherche et d’expérience. Les résultats indiquent que seules la longueur de l’examen et l’expédition spéciale n’ont pas d’impact significatif sur les ventes de produits, tandis que la catégorie de produit a un effet modérateur valide et spécifique sur la relation entre ces déterminants et les ventes. Les conclusions présentées auront des implications importantes pour la recherche universitaire et les futures pratiques de l’industrie. Nous divisons la littérature sélectionnée en deux sous-groupes qui sont des produits de recherche et d’expérience. Les résultats indiquent que seule la durée de l’examen et l’expédition spéciale n’ont pas d’impact significatif sur les ventes de produits, tandis que la catégorie de produit a un effet modérateur valide et spécifique sur la relation entre ces déterminants et les ventes. Les conclusions présentées auront des implications importantes pour la recherche universitaire et les futures pratiques de l’industrie. Nous divisons la littérature sélectionnée en deux sous-groupes qui sont des produits de recherche et d’expérience. Les résultats indiquent que seules la durée de l’examen et l’expédition spéciale n’ont pas d’impact significatif sur les ventes de produits, tandis que la catégorie de produit a un effet modérateur valide et spécifique sur la relation entre ces déterminants et les ventes. Les conclusions présentées auront des implications importantes pour la recherche universitaire et les futures pratiques de l’industrie.

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Craciun G, Moore K, (2019), Credibility of negative online product reviews: Reviewer gender, reputation and emotion effects, Computers in Human Behavior, Volume 97, August 2019, Pages 104-115

https://www.sciencedirect.com/science/article/pii/S0747563219301025

Mots clés : Bouche à oreille électronique, Stéréotypes de genre, Émotion, Crédibilité de l’examinateur, Avis sur les produits, Expressions émotionnelles, Théorie de l’espérance linguistique

Résumé : La documentation électronique sur le bouche-à-oreille confirme la conclusion solide selon laquelle les avis négatifs influencent généralement plus le comportement des consommateurs que les avis positifs. De plus, des études récentes suggèrent qu’une grande partie du biais de négativité est motivée par les émotions distinctes intégrées dans le contenu du bouche à oreille négatif  et les effets d’interaction entre les émotions et d’autres facteurs sources. Bien que le sexe de la source d’information soit une heuristique courante utilisée dans l’évaluation des messages, il s’agit de la première étude à examiner l’effet des stéréotypes de genre sur le bouche à oreille émotionnel. Deux expériences basées sur le Web montrent que lorsque des indices de réputation de critique sont présents, le contenu émotionnel dans le bouche à oreille négatif diminue la crédibilité des critiques masculins et l’utilité de leurs critiques, mais n’affecte pas les critiques rédigées par des femmes. En revanche, lorsque les indices de réputation sont absents, la présence d’émotions dans le bouche à oreille négatif diminue la crédibilité des examinateurs féminins, mais pas celle des examinateurs masculins. L’indice de réputation a un effet positif sur la crédibilité et l’utilité du bouche à oreille négatif.

Grandes lignes :

• Le bouche-à-oreille négatif influe généralement davantage sur le comportement des consommateurs que le bouche-à-oreille positif.
• Cette étude examine les effets de la réputation et des stéréotypes liés au sexe sur la crédibilité et l’utilité du bouche-à-oreille négatif
• Lorsque les indices de réputation des évaluateurs étaient absents, le contenu émotionnel du bouche-à-oreille négatif a nui à l’évaluation des critiques rédigées par des femmes
• Lorsque les indices de réputation des examinateurs étaient présents, le contenu émotionnel du bouche-à-oreille négatif a nui à l’évaluation des critiques rédigées par des hommes.
• L’indice de réputation a eu un effet positif sur la crédibilité et l’utilité du bouche-à-oreille négatif.

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Geng S, Li W, Qu X, Chen L, (2017), Design for the pricing strategy of return-freight insurance based on online product reviews, Electronic Commerce Research and ApplicationsVolume 25, September–October 2017, Pages 16-28

https://www.sciencedirect.com/science/article/pii/S156742231730039X

Mots clés : Assurance retour de fret, Avis de produit en ligne, Incertitude sur l’ajustement du produit, Politique de retour

Résumé : Pour résoudre les litiges liés aux achats en ligne avec le retour des produits, certaines compagnies d’assurance ont développé un nouveau type d’assurance appelé assurance retour-fret pour compenser la perte de frais de retour par les consommateurs. La détermination traditionnelle des primes d’assurance n’a pas complètement fusionné tous les facteurs de commerce électronique, tels que l’incertitude de l’ajustement des produits des achats en ligne, qui pourrait affecter à la fois la demande d’assurance et la quantité de retour. Sur la base de ces caractéristiques, nous développons un modèle de maximisation des bénéfices en termes de certains paramètres de réaction du marché, en particulier l’incertitude de l’ajustement du produit, et calculons la stratégie de tarification optimale, y compris la prime d’assurance et la compensation. En utilisant la théorie des perspectives, nous expliquons pourquoi les avis de produits en ligne pourrait influencer le comportement d’aversion au risque des demandeurs d’assurance dans la situation du commerce électronique. Ensuite, nous résolvons pour la prime et la compensation raisonnables accordées aux avis de produits en ligne du point de vue de la compagnie d’assurance et obtenons un certain nombre de directives managériales pour utiliser les variables de marketing et de stratégie opérationnelle pour influencer ces paramètres de réaction afin d’obtenir le maximum d’avantages du marché. Il est intéressant de noter que lorsque la sensibilité des consommateurs à l’incertitude sur l’ajustement du produit est modérée, une augmentation de l’incertitude sur l’ajustement du produit déplace la prime d’assurance et la compensation dans la direction opposée.

Grandes lignes :

• Assurance de retour de fret, qui compense la perte de frais de retour de produit en ligne.
• L’incertitude liée à l’ajustement du produit doit être prise en compte lors de l’analyse de la stratégie de tarification de l’assurance retour-fret.
• La relation entre la prime d’assurance retour-fret et l’incertitude sur l’ajustement du produit n’est pas une corrélation positive.
• Le bénéfice de l’assureur n’augmente pas toujours à mesure que la prime d’assurance retour-fret augmente.
• L’aléa moral doit être considéré comme une contrainte importante dans la conception d’une stratégie de tarification d’assurance.

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Moon S, Kamakura W, (2017), A picture is worth a thousand words: Translating product reviews into a product positioning map, International Journal of Research in Marketing, Volume 34, Issue 1, March 2017, Pages 265-285

https://www.sciencedirect.com/science/article/abs/pii/S016781161630074X

Mots clés : Avis de produits en ligne, Carte de positionnement du produit, Exploration de texte, Psychométrie, Découvrir les produits, Segmentation des consommateurs

Résumé : Les avis sur les produits deviennent omniprésents sur le Web, ce qui représente une riche source d’informations pour les consommateurs sur un large éventail de catégories de produits. Surtout, un avis de produit reflète non seulement la perception et la préférence pour un produit, mais aussi l’acuité, le parti pris et le style d’écriture de la critique. Cet aspect a été négligé dans des études antérieures qui ont tiré des conclusions sur les marques à partir des critiques de produits en ligne. Notre cadre combine des techniques d’exploration de texte basées sur l’apprentissage d’ontologie et des techniques psychométriques pour traduire les critiques de produits en ligne en une carte de positionnement de produit, tout en tenant compte des réponses idiosyncrasiques et des styles d’écriture des critiques individuels ou d’un nombre gérable de groupes de critiques (c.-à-d., Les méta-critiques). Nos illustrations empiriques utilisant des critiques de vins et d’hôtels montrent qu’une revue de produit révèle des informations sur le critique (pour l’exemple de vin avec un petit nombre de critiques d’experts) ou le méta-critique (pour l’exemple d’hôtel avec un nombre énorme de critiques réduit à un nombre gérable de méta-évaluateurs), ainsi que sur le produit examiné.

Grandes lignes :

• Les avis sur les produits deviennent omniprésents sur le Web.
• Un avis de produit reflète non seulement la perception et la préférence pour un produit, mais aussi l’acuité, le parti pris et le style d’écriture de la critique.

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Singh A, Tucker C (2017) A machine learning approach to product review disambiguation based on function, form and behavior classification, Decision Support Systems, Volume 97, May 2017, Pages 81-91

https://www.sciencedirect.com/science/article/pii/S0167923617300477

Mots clés : Apprentissage automatique, Extraction d’attribut de produit, Exploration de texte, Avis sur les produits, La conception des produits

Résumé : Les évaluations de produits en ligne se sont révélées être une source d’informations viable pour aider les clients à prendre des décisions d’achat éclairées. Dans de nombreux cas, les utilisateurs de plateformes d’achat en ligne ont la possibilité d’évaluer les produits sur une échelle numérique et de fournir également des commentaires textuels concernant un produit acheté. Au-delà de l’utilisation de plateformes de revue de produits en ligne comme systèmes d’aide à la décision client, cette source de données riche en informations pourrait également aider les concepteurs qui cherchent à augmenter les chances de succès de leurs produits sur le marché grâce à une meilleure compréhension des besoins du marché. Cependant, la taille et la complexité croissantes des produits sur le marché rendent difficile l’analyse manuelle de ces données. Les informations obtenues à partir de ces sources, si elles ne sont pas exploitées correctement, risquent de déformer le véritable succès / échec d’un. L’objectif de cet article est triple: i) proposer une approche d’apprentissage automatique qui dissipe les commentaires des clients en ligne en les classant en l’une des trois caractéristiques directes du produit (c.-à-d. La forme ,fonction ou comportement ) et deux caractéristiques indirectes du produit (c.-à-d. service et autre ), ii) pour découvrir l’ algorithme d’apprentissage automatique qui donne les résultats les plus élevés et les plus généralisables pour atteindre l’objectif i) et iii) pour quantifier la corrélation entre les évaluations de produits et les évaluations directes et les caractéristiques indirectes du produit. Une étude de cas impliquant des données d’examen pour des produits extraits de sites Web de commerce électronique est présentée pour démontrer la validité de la méthode proposée. Une approche de validation multicouche est présentée pour explorer la généralisation de la méthode proposée. Les contributions scientifiques de ce travail ont le potentiel de transformer la manière dont les concepteurs de produits et les clients intègrent les avis sur les produits dans leurs processus décisionnels en quantifiant la relation entre les avis sur les produits et les caractéristiques des produits.

Grandes lignes :

• Les évaluations de produits en ligne sont une source d’informations viable pour aider les clients à prendre des décisions d’achat.
• Elles peuvent aider les concepteurs qui cherchent à augmenter les chances de succès de leurs produits.
• Classification par apprentissage automatique de la forme, de la fonction et du comportement du produit
• Précisions de classification d’apprentissage automatique de plus de 82% pour le modèle de base
• Corrélation entre les évaluations de produits et la forme, la fonction et le comportement des produits
• La corrélation entre la forme des produits et les notes des produits a donné une valeur de 0,934

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