Product Recommendations in e-Commerce Retailing Applications.

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Superior document:Forschungsergebnisse der Wirtschaftsuniversitaet Wien Series ; v.17
:
Place / Publishing House:Frankfurt a.M. : : Peter Lang GmbH, Internationaler Verlag der Wissenschaften,, 2007.
Ã2008.
Year of Publication:2007
Edition:1st ed.
Language:English
Series:Forschungsergebnisse der Wirtschaftsuniversitaet Wien Series
Online Access:
Physical Description:1 online resource (222 pages)
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id 50030686084
ctrlnum (MiAaPQ)50030686084
(Au-PeEL)EBL30686084
(OCoLC)1399169159
collection bib_alma
record_format marc
spelling Knotzer, Nicolas.
Product Recommendations in e-Commerce Retailing Applications.
1st ed.
Frankfurt a.M. : Peter Lang GmbH, Internationaler Verlag der Wissenschaften, 2007.
Ã2008.
1 online resource (222 pages)
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Forschungsergebnisse der Wirtschaftsuniversitaet Wien Series ; v.17
Cover -- 1 Introduction -- 1.1 Research Goal -- 1.2 Contents and Organization -- 2 Recommender Systems - Definition, Classification, and Marketing Perspectives -- 2.1 Working Definitions -- 2.2 Classification -- 2.3 Application Models of Recommender Systems -- 2.3.1 Broad Recommendation Lists -- 2.3.2 Customer Comments and Ratings -- 2.3.3 Notification Services -- 2.3.4 Product Associated Recommendations -- 2.3.5 Persistent Personalization -- 2.4 The Consumer Decision Process -- 2.4.1 Need Recognition -- 2.4.2 Information Search -- 2.4.3 Pre-Purchase Evaluation of Alternatives -- 2.4.4 Purchase -- 2.4.5 Post-Purchase Processes -- 2.5 Virtual Communities -- 2.5.1 Characteristics and Benefits -- 2.5.2 Virtual Communities and Network Effects -- 2.5.3 Community Building -- 3 Recommender Systems - Functional Perspectives -- 3.1 Input Data of Recommender Systems -- 3.2 Output Data of Recommender Systems -- 3.3 Measurement Scales for Preference Elicitation -- 3.4 Information Delivery -- 3.5 Recommendation Methods -- 3.5.1 Non-Personalized Recommendation Methods -- 3.5.2 Personalized Recommendation Methods -- 3.5.2.1 Synopsis of Information Filtering Methods -- 3.5.2.2 Human Approaches towards Information Filtering -- 3.5.2.3 Collaborative Filtering -- 3.5.2.4 Attribute-Based Filtering -- 3.5.2.5 Rules-Based Filtering -- 4 Research Model, Hypotheses, and Methodology -- 4.1 Problem Statement -- 4.2 Research Questions and Model -- 4.3 Methodology and Research Design -- 5 Results -- 5.1 Descriptive Results -- 5.1.1 Sample Size and Demographic Data -- 5.1.2 Internet Usage -- 5.1.3 Online Shopping -- 5.1.4 Online Product Recommendations -- 5.1.5 Ratings and Comments -- 5.2 Verification of the Research Model -- 5.2.1 Exploratory Factor Analysis -- 5.2.2 Psychographic Hypotheses - Structural Equation Model -- 5.2.3 Psychographic Hypotheses - Regression Model.
5.2.4 Sociodemographic Hypotheses -- 6 Summary and Directions for Further Research -- 6.1 Main Findings -- 6.2 Limitations and Directions for Further Research -- Bibliography -- Appendices -- A AMOS Output -- A.1 Survey AUM -- A.2 Survey AON.
Description based on publisher supplied metadata and other sources.
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
Electronic books.
Print version: Knotzer, Nicolas Product Recommendations in e-Commerce Retailing Applications Frankfurt a.M. : Peter Lang GmbH, Internationaler Verlag der Wissenschaften,c2007 9783631566220
ProQuest (Firm)
Forschungsergebnisse der Wirtschaftsuniversitaet Wien Series
https://ebookcentral.proquest.com/lib/oeawat/detail.action?docID=30686084 Click to View
language English
format eBook
author Knotzer, Nicolas.
spellingShingle Knotzer, Nicolas.
Product Recommendations in e-Commerce Retailing Applications.
Forschungsergebnisse der Wirtschaftsuniversitaet Wien Series ;
Cover -- 1 Introduction -- 1.1 Research Goal -- 1.2 Contents and Organization -- 2 Recommender Systems - Definition, Classification, and Marketing Perspectives -- 2.1 Working Definitions -- 2.2 Classification -- 2.3 Application Models of Recommender Systems -- 2.3.1 Broad Recommendation Lists -- 2.3.2 Customer Comments and Ratings -- 2.3.3 Notification Services -- 2.3.4 Product Associated Recommendations -- 2.3.5 Persistent Personalization -- 2.4 The Consumer Decision Process -- 2.4.1 Need Recognition -- 2.4.2 Information Search -- 2.4.3 Pre-Purchase Evaluation of Alternatives -- 2.4.4 Purchase -- 2.4.5 Post-Purchase Processes -- 2.5 Virtual Communities -- 2.5.1 Characteristics and Benefits -- 2.5.2 Virtual Communities and Network Effects -- 2.5.3 Community Building -- 3 Recommender Systems - Functional Perspectives -- 3.1 Input Data of Recommender Systems -- 3.2 Output Data of Recommender Systems -- 3.3 Measurement Scales for Preference Elicitation -- 3.4 Information Delivery -- 3.5 Recommendation Methods -- 3.5.1 Non-Personalized Recommendation Methods -- 3.5.2 Personalized Recommendation Methods -- 3.5.2.1 Synopsis of Information Filtering Methods -- 3.5.2.2 Human Approaches towards Information Filtering -- 3.5.2.3 Collaborative Filtering -- 3.5.2.4 Attribute-Based Filtering -- 3.5.2.5 Rules-Based Filtering -- 4 Research Model, Hypotheses, and Methodology -- 4.1 Problem Statement -- 4.2 Research Questions and Model -- 4.3 Methodology and Research Design -- 5 Results -- 5.1 Descriptive Results -- 5.1.1 Sample Size and Demographic Data -- 5.1.2 Internet Usage -- 5.1.3 Online Shopping -- 5.1.4 Online Product Recommendations -- 5.1.5 Ratings and Comments -- 5.2 Verification of the Research Model -- 5.2.1 Exploratory Factor Analysis -- 5.2.2 Psychographic Hypotheses - Structural Equation Model -- 5.2.3 Psychographic Hypotheses - Regression Model.
5.2.4 Sociodemographic Hypotheses -- 6 Summary and Directions for Further Research -- 6.1 Main Findings -- 6.2 Limitations and Directions for Further Research -- Bibliography -- Appendices -- A AMOS Output -- A.1 Survey AUM -- A.2 Survey AON.
author_facet Knotzer, Nicolas.
author_variant n k nk
author_sort Knotzer, Nicolas.
title Product Recommendations in e-Commerce Retailing Applications.
title_full Product Recommendations in e-Commerce Retailing Applications.
title_fullStr Product Recommendations in e-Commerce Retailing Applications.
title_full_unstemmed Product Recommendations in e-Commerce Retailing Applications.
title_auth Product Recommendations in e-Commerce Retailing Applications.
title_new Product Recommendations in e-Commerce Retailing Applications.
title_sort product recommendations in e-commerce retailing applications.
series Forschungsergebnisse der Wirtschaftsuniversitaet Wien Series ;
series2 Forschungsergebnisse der Wirtschaftsuniversitaet Wien Series ;
publisher Peter Lang GmbH, Internationaler Verlag der Wissenschaften,
publishDate 2007
physical 1 online resource (222 pages)
edition 1st ed.
contents Cover -- 1 Introduction -- 1.1 Research Goal -- 1.2 Contents and Organization -- 2 Recommender Systems - Definition, Classification, and Marketing Perspectives -- 2.1 Working Definitions -- 2.2 Classification -- 2.3 Application Models of Recommender Systems -- 2.3.1 Broad Recommendation Lists -- 2.3.2 Customer Comments and Ratings -- 2.3.3 Notification Services -- 2.3.4 Product Associated Recommendations -- 2.3.5 Persistent Personalization -- 2.4 The Consumer Decision Process -- 2.4.1 Need Recognition -- 2.4.2 Information Search -- 2.4.3 Pre-Purchase Evaluation of Alternatives -- 2.4.4 Purchase -- 2.4.5 Post-Purchase Processes -- 2.5 Virtual Communities -- 2.5.1 Characteristics and Benefits -- 2.5.2 Virtual Communities and Network Effects -- 2.5.3 Community Building -- 3 Recommender Systems - Functional Perspectives -- 3.1 Input Data of Recommender Systems -- 3.2 Output Data of Recommender Systems -- 3.3 Measurement Scales for Preference Elicitation -- 3.4 Information Delivery -- 3.5 Recommendation Methods -- 3.5.1 Non-Personalized Recommendation Methods -- 3.5.2 Personalized Recommendation Methods -- 3.5.2.1 Synopsis of Information Filtering Methods -- 3.5.2.2 Human Approaches towards Information Filtering -- 3.5.2.3 Collaborative Filtering -- 3.5.2.4 Attribute-Based Filtering -- 3.5.2.5 Rules-Based Filtering -- 4 Research Model, Hypotheses, and Methodology -- 4.1 Problem Statement -- 4.2 Research Questions and Model -- 4.3 Methodology and Research Design -- 5 Results -- 5.1 Descriptive Results -- 5.1.1 Sample Size and Demographic Data -- 5.1.2 Internet Usage -- 5.1.3 Online Shopping -- 5.1.4 Online Product Recommendations -- 5.1.5 Ratings and Comments -- 5.2 Verification of the Research Model -- 5.2.1 Exploratory Factor Analysis -- 5.2.2 Psychographic Hypotheses - Structural Equation Model -- 5.2.3 Psychographic Hypotheses - Regression Model.
5.2.4 Sociodemographic Hypotheses -- 6 Summary and Directions for Further Research -- 6.1 Main Findings -- 6.2 Limitations and Directions for Further Research -- Bibliography -- Appendices -- A AMOS Output -- A.1 Survey AUM -- A.2 Survey AON.
isbn 9783631754528
9783631566220
genre Electronic books.
genre_facet Electronic books.
url https://ebookcentral.proquest.com/lib/oeawat/detail.action?docID=30686084
illustrated Not Illustrated
oclc_num 1399169159
work_keys_str_mv AT knotzernicolas productrecommendationsinecommerceretailingapplications
status_str n
ids_txt_mv (MiAaPQ)50030686084
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carrierType_str_mv cr
hierarchy_parent_title Forschungsergebnisse der Wirtschaftsuniversitaet Wien Series ; v.17
is_hierarchy_title Product Recommendations in e-Commerce Retailing Applications.
container_title Forschungsergebnisse der Wirtschaftsuniversitaet Wien Series ; v.17
marc_error Info : Unimarc and ISO-8859-1 translations identical, choosing ISO-8859-1. --- [ 856 : z ]
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