Documents disponibles écrits par cet auteur

An empirical analysis of user content generation and usage behavior on the mobile internet / Anindya Ghose in Management science, Vol. 57 N° 9 (Septembre 2011) 

Public ISBD [article]  in Management science > Vol. 57 N° 9 (Septembre 2011) . - pp. 1671-1691 Titre : An empirical analysis of user content generation and usage behavior on the mobile internet Type de document : texte imprimé Auteurs : Anindya Ghose, Auteur ; Sang Pil Han, Auteur Année de publication : 2011 Article en page(s) : pp. 1671-1691 Note générale : Management Langues : Anglais (eng) Mots-clés : Mobile  Internet  Social  networks  Content  generation  Content  usage  Interdependence  Geographical  mobility  Identification Index. décimale : 658 Organisation des entreprises. Techniques du commerce Résumé : We quantify how user mobile Internet usage relates to unique characteristics of the mobile Internet. In particular, we focus on examining how the mobile-phone-based content generation behavior of users relates to content usage behavior. The key objective is to analyze whether there is a positive or negative interdependence between the two activities. We use a unique panel data set that consists of individual-level mobile Internet usage data that encompass individual multimedia content generation and usage behavior. We combine this knowledge with data on user calling patterns, such as duration, frequency, and locations from where calls are placed, to construct their social network and to compute their geographical mobility. We build an individual-level simultaneous equation panel data model that controls for the different sources of endogeneity of the social network. We find that there is a negative and statistically significant temporal interdependence between content generation and usage. This finding implies that an increase in content usage in the previous period has a negative impact on content generation in the current period and vice versa. The marginal effect of this interdependence is stronger on content usage (up to 8.7%) than on content generation (up to 4.3%). The extent of geographical mobility of users has a positive effect on their mobile Internet activities. Users more frequently engage in content usage compared to content generation when they are traveling. In addition, the variance of user mobility has a stronger impact on their mobile Internet activities than does the mean. We also find that the social network has a strong positive effect on user behavior in the mobile Internet. These analyses unpack the mechanisms that stimulate user behavior on the mobile Internet. Implications for shaping user mobile Internet usage behavior are discussed. DEWEY : 658 ISSN : 0025-1909 En ligne : http://mansci.journal.informs.org/content/57/9.toc [article] An empirical analysis of user content generation and usage behavior on the mobile internet [texte imprimé] / Anindya Ghose, Auteur ; Sang Pil Han, Auteur . - 2011 . - pp. 1671-1691. Management Langues : Anglais (eng) in Management science > Vol. 57 N° 9 (Septembre 2011) . - pp. 1671-1691 Mots-clés : Mobile  Internet  Social  networks  Content  generation  Content  usage  Interdependence  Geographical  mobility  Identification Index. décimale : 658 Organisation des entreprises. Techniques du commerce Résumé : We quantify how user mobile Internet usage relates to unique characteristics of the mobile Internet. In particular, we focus on examining how the mobile-phone-based content generation behavior of users relates to content usage behavior. The key objective is to analyze whether there is a positive or negative interdependence between the two activities. We use a unique panel data set that consists of individual-level mobile Internet usage data that encompass individual multimedia content generation and usage behavior. We combine this knowledge with data on user calling patterns, such as duration, frequency, and locations from where calls are placed, to construct their social network and to compute their geographical mobility. We build an individual-level simultaneous equation panel data model that controls for the different sources of endogeneity of the social network. We find that there is a negative and statistically significant temporal interdependence between content generation and usage. This finding implies that an increase in content usage in the previous period has a negative impact on content generation in the current period and vice versa. The marginal effect of this interdependence is stronger on content usage (up to 8.7%) than on content generation (up to 4.3%). The extent of geographical mobility of users has a positive effect on their mobile Internet activities. Users more frequently engage in content usage compared to content generation when they are traveling. In addition, the variance of user mobility has a stronger impact on their mobile Internet activities than does the mean. We also find that the social network has a strong positive effect on user behavior in the mobile Internet. These analyses unpack the mechanisms that stimulate user behavior on the mobile Internet. Implications for shaping user mobile Internet usage behavior are discussed. DEWEY : 658 ISSN : 0025-1909 En ligne : http://mansci.journal.informs.org/content/57/9.toc

Deriving the pricing power of product features by mining consumer reviews / Nikolay Archak in Management science, Vol. 57 N° 8 (Août 2011) 

Public ISBD [article]  in Management science > Vol. 57 N° 8 (Août 2011) . - pp. 1485-1509 Titre : Deriving the pricing power of product features by mining consumer reviews Type de document : texte imprimé Auteurs : Nikolay Archak, Auteur ; Anindya Ghose, Auteur ; Panagiotis G. Ipeirotis, Auteur Année de publication : 2011 Article en page(s) : pp. 1485-1509 Note générale : Management Langues : Anglais (eng) Mots-clés : Bayesian  learning  Consumer  reviews  Discrete  choice  Electronic  commerce  Electronic  markets  Opinion  mining  Sentiment  analysis  User-generated  content  Text  mining  Econometrics Index. décimale : 658 Organisation des entreprises. Techniques du commerce Résumé : Increasingly, user-generated product reviews serve as a valuable source of information for customers making product choices online. The existing literature typically incorporates the impact of product reviews on sales based on numeric variables representing the valence and volume of reviews. In this paper, we posit that the information embedded in product reviews cannot be captured by a single scalar value. Rather, we argue that product reviews are multifaceted, and hence the textual content of product reviews is an important determinant of consumers' choices, over and above the valence and volume of reviews. To demonstrate this, we use text mining to incorporate review text in a consumer choice model by decomposing textual reviews into segments describing different product features. We estimate our model based on a unique data set from Amazon containing sales data and consumer review data for two different groups of products (digital cameras and camcorders) over a 15-month period. We alleviate the problems of data sparsity and of omitted variables by providing two experimental techniques: clustering rare textual opinions based on pointwise mutual information and using externally imposed review semantics. This paper demonstrates how textual data can be used to learn consumers' relative preferences for different product features and also how text can be used for predictive modeling of future changes in sales. DEWEY : 658 ISSN : 0025-1909 En ligne : http://mansci.journal.informs.org/content/57/8.toc [article] Deriving the pricing power of product features by mining consumer reviews [texte imprimé] / Nikolay Archak, Auteur ; Anindya Ghose, Auteur ; Panagiotis G. Ipeirotis, Auteur . - 2011 . - pp. 1485-1509. Management Langues : Anglais (eng) in Management science > Vol. 57 N° 8 (Août 2011) . - pp. 1485-1509 Mots-clés : Bayesian  learning  Consumer  reviews  Discrete  choice  Electronic  commerce  Electronic  markets  Opinion  mining  Sentiment  analysis  User-generated  content  Text  mining  Econometrics Index. décimale : 658 Organisation des entreprises. Techniques du commerce Résumé : Increasingly, user-generated product reviews serve as a valuable source of information for customers making product choices online. The existing literature typically incorporates the impact of product reviews on sales based on numeric variables representing the valence and volume of reviews. In this paper, we posit that the information embedded in product reviews cannot be captured by a single scalar value. Rather, we argue that product reviews are multifaceted, and hence the textual content of product reviews is an important determinant of consumers' choices, over and above the valence and volume of reviews. To demonstrate this, we use text mining to incorporate review text in a consumer choice model by decomposing textual reviews into segments describing different product features. We estimate our model based on a unique data set from Amazon containing sales data and consumer review data for two different groups of products (digital cameras and camcorders) over a 15-month period. We alleviate the problems of data sparsity and of omitted variables by providing two experimental techniques: clustering rare textual opinions based on pointwise mutual information and using externally imposed review semantics. This paper demonstrates how textual data can be used to learn consumers' relative preferences for different product features and also how text can be used for predictive modeling of future changes in sales. DEWEY : 658 ISSN : 0025-1909 En ligne : http://mansci.journal.informs.org/content/57/8.toc