Product Recommendations in e-Commerce Retailing Applications.
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Superior document: | Forschungsergebnisse der Wirtschaftsuniversitaet Wien Series ; v.17 |
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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
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Online Access: | |
Physical Description: | 1 online resource (222 pages) |
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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 (Au-PeEL)EBL30686084 (OCoLC)1399169159 |
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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