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Consumer Response To Online Recommendation Systems And The Moderating Role Of Product Knowledge And Product Involvement
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Book Synopsis Consumer Response to Online Recommendation Systems and the Moderating Role of Product Knowledge and Product Involvement by : Sungmi Lee
Download or read book Consumer Response to Online Recommendation Systems and the Moderating Role of Product Knowledge and Product Involvement written by Sungmi Lee and published by . This book was released on 2007 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Consumer Response to Online Recommendation Systems and the Moderating Role of Product Knowledge and Product Involvement: to 10; Pages:11 to 20; Pages:21 to 30; Pages:31 to 40; Pages:41 to 50; Pages:51 to 59 by : Sungmi Lee
Download or read book Consumer Response to Online Recommendation Systems and the Moderating Role of Product Knowledge and Product Involvement: to 10; Pages:11 to 20; Pages:21 to 30; Pages:31 to 40; Pages:41 to 50; Pages:51 to 59 written by Sungmi Lee and published by . This book was released on 2000 with total page 59 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Product Recommendations and Cross-Selling. Recommendation Forms, Product Categories and Product Familiarity by :
Download or read book Product Recommendations and Cross-Selling. Recommendation Forms, Product Categories and Product Familiarity written by and published by GRIN Verlag. This book was released on 2019-06-04 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt: Seminar paper from the year 2018 in the subject Business economics - Offline Marketing and Online Marketing, grade: 1,3, Nanjing University, language: English, abstract: In this study, we aim to investigate how two different types of online recommender systems affect the cross-selling of a retailer on a website using the online recommender systems. Furthermore, this will give us the chance to study the direct effect of targeting on cross-selling. Different from the previous studies, this study will mainly focus on two aspects. On the one hand, the online recommender systems will be divided into two types, the targeting recommender systems, and popular recommender systems. The first one is the personalized form through which we can give the targeted consumers the specific products recommenders based on the consumers’ purchase history. This type has been fully discussed in previous studies. The second type of a recommender system is the public form giving the recommendations based on the hot products, which is a common phenomenon in e-commerce platforms. In other words, recommended products or services come from common preferences of all consumers. Research on the relationship between cross-selling and this type of recommender system is still relatively lacking. On the other hand, we will discuss the different moderating effects between two different types of the recommended products — search-type and experience-type products — as well as the influence caused by product familiarity on the relationship between the online recommender systems and cross-selling. These two types of products have been fully discussed in the area about the helpfulness of online reviews. In addition, familiar and unfamiliar products differ in terms of the knowledge regarding the products that a consumer has stored in memory. This will affect how consumers search and process the online recommender systems and co-purchase information. Therefore, we will consider these in the process of data collecting. Through examining those previously described causal effects, we can make the following two contributions. Firstly, we can make further suggestions about how the choice for an online recommender system can influence cross-selling and thereby further contribute to the discussion about recommender systems in the e-commerce ecosystem. Secondly, we can classify the cross-influence from the product types and product familiarity in the above-stated relationship between online recommender systems and cross-selling.
Book Synopsis Driving Customer Equity by : Roland T Rust
Download or read book Driving Customer Equity written by Roland T Rust and published by Free Press. This book was released on 2000-06-27 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In their efforts to become more customer-focused, companies everywhere find themselves entangled in outmoded systems, metrics, and strategies rooted in their product-centered view of the world. Now, to ease this shift to a customer focus, marketing strategy experts Roland T. Rust, Valarie A. Zeithaml, and Katherine N. Lemon have created a dynamic new model they call "Customer Equity," a strategic framework designed to maximize every firm's most important asset, the total lifetime value of its customer base. The authors' Customer Equity Framework yields powerful insights that will help any business increase the value of its customer base. Rust, Zeithaml, and Lemon introduce the three drivers of customer equity -- Value Equity, Brand Equity, and Retention Equity -- and explain in clear, nontechnical language how managers can base their strategies on one or a combination of these drivers. The authors demonstrate in this breakthrough book how managers can build and employ competitive metrics that reveal their company's Customer Equity relative to their competitors. Based on these metrics, they show how managers can determine which drivers are most important in their industry, how they can make efficient strategic trade-offs between expenditures on these drivers, and how to project a financial return from these expenditures. The final section devotes two chapters to the Customer Pyramid, an approach that segments customers based on their long-term profitability, and an especially important chapter examines the Internet as the ultimate Customer Equity tool. Here the authors show how companies such as Intuit.com, Schwab.com, and Priceline.com have used more than one or all three drivers to increase Customer Equity. In this age of one-to-one marketing, understanding how to drive Customer Equity is central to the success of any firm. In particular, Driving Customer Equity will be essential reading for any marketing manager and, for that matter, any manager concerned with growing the value of the firm's customer base.
Book Synopsis Digital and Social Media Marketing by : Nripendra P. Rana
Download or read book Digital and Social Media Marketing written by Nripendra P. Rana and published by Springer Nature. This book was released on 2019-11-11 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines issues and implications of digital and social media marketing for emerging markets. These markets necessitate substantial adaptations of developed theories and approaches employed in the Western world. The book investigates problems specific to emerging markets, while identifying new theoretical constructs and practical applications of digital marketing. It addresses topics such as electronic word of mouth (eWOM), demographic differences in digital marketing, mobile marketing, search engine advertising, among others. A radical increase in both temporal and geographical reach is empowering consumers to exert influence on brands, products, and services. Information and Communication Technologies (ICTs) and digital media are having a significant impact on the way people communicate and fulfil their socio-economic, emotional and material needs. These technologies are also being harnessed by businesses for various purposes including distribution and selling of goods, retailing of consumer services, customer relationship management, and influencing consumer behaviour by employing digital marketing practices. This book considers this, as it examines the practice and research related to digital and social media marketing.
Book Synopsis The Moderating Role of Consumer Involvement and Mood State on Product Recall by : Mary Katherine Macmillan
Download or read book The Moderating Role of Consumer Involvement and Mood State on Product Recall written by Mary Katherine Macmillan and published by . This book was released on 1993 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Recommender Systems by : Gérald Kembellec
Download or read book Recommender Systems written by Gérald Kembellec and published by John Wiley & Sons. This book was released on 2014-12-04 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: Acclaimed by various content platforms (books, music, movies) and auction sites online, recommendation systems are key elements of digital strategies. If development was originally intended for the performance of information systems, the issues are now massively moved on logical optimization of the customer relationship, with the main objective to maximize potential sales. On the transdisciplinary approach, engines and recommender systems brings together contributions linking information science and communications, marketing, sociology, mathematics and computing. It deals with the understanding of the underlying models for recommender systems and describes their historical perspective. It also analyzes their development in the content offerings and assesses their impact on user behavior.
Book Synopsis Recommender Systems Handbook by : Francesco Ricci
Download or read book Recommender Systems Handbook written by Francesco Ricci and published by Springer Science & Business Media. This book was released on 2010-10-21 with total page 848 pages. Available in PDF, EPUB and Kindle. Book excerpt: The explosive growth of e-commerce and online environments has made the issue of information search and selection increasingly serious; users are overloaded by options to consider and they may not have the time or knowledge to personally evaluate these options. Recommender systems have proven to be a valuable way for online users to cope with the information overload and have become one of the most powerful and popular tools in electronic commerce. Correspondingly, various techniques for recommendation generation have been proposed. During the last decade, many of them have also been successfully deployed in commercial environments. Recommender Systems Handbook, an edited volume, is a multi-disciplinary effort that involves world-wide experts from diverse fields, such as artificial intelligence, human computer interaction, information technology, data mining, statistics, adaptive user interfaces, decision support systems, marketing, and consumer behavior. Theoreticians and practitioners from these fields continually seek techniques for more efficient, cost-effective and accurate recommender systems. This handbook aims to impose a degree of order on this diversity, by presenting a coherent and unified repository of recommender systems’ major concepts, theories, methodologies, trends, challenges and applications. Extensive artificial applications, a variety of real-world applications, and detailed case studies are included. Recommender Systems Handbook illustrates how this technology can support the user in decision-making, planning and purchasing processes. It works for well known corporations such as Amazon, Google, Microsoft and AT&T. This handbook is suitable for researchers and advanced-level students in computer science as a reference.
Author :Nicolas Knotzer Publisher :Peter Lang Gmbh, Internationaler Verlag Der Wissenschaften ISBN 13 :9783631566220 Total Pages :202 pages Book Rating :4.5/5 (662 download)
Book Synopsis Product Recommendations in E-commerce Retailing Applications by : Nicolas Knotzer
Download or read book Product Recommendations in E-commerce Retailing Applications written by Nicolas Knotzer and published by Peter Lang Gmbh, Internationaler Verlag Der Wissenschaften. This book was released on 2008 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book deals with product recommendations generated by information systems referred to as recommender systems. Recommender systems assist consumers in making product choices by providing recommendations of the range of products and services offered in an online purchase environment. The quantitative research study investigates the influence of psychographic and sociodemographic determinants on the interest of consumers in personalized online book recommendations. The author presents new findings regarding the interest in recommendations, importance of product reviews for the decision process, motives for submitting ratings as well as comments, and the delivery of recommendations. The results show that opinion seeking, opinion leading, domain specific innovativeness, online shopping experience, and age are important factors in respect of the interest in personalized recommendations.
Book Synopsis Personalization Techniques And Recommender Systems by : Gulden Uchyigit
Download or read book Personalization Techniques And Recommender Systems written by Gulden Uchyigit and published by World Scientific. This book was released on 2008-04-04 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: The phenomenal growth of the Internet has resulted in huge amounts of online information, a situation that is overwhelming to the end users. To overcome this problem, personalization technologies have been extensively employed.The book is the first of its kind, representing research efforts in the diversity of personalization and recommendation techniques. These include user modeling, content, collaborative, hybrid and knowledge-based recommender systems. It presents theoretic research in the context of various applications from mobile information access, marketing and sales and web services, to library and personalized TV recommendation systems.This volume will serve as a basis to researchers who wish to learn more in the field of recommender systems, and also to those intending to deploy advanced personalization techniques in their systems.
Book Synopsis Recommender Systems: Advanced Developments by : Jie Lu
Download or read book Recommender Systems: Advanced Developments written by Jie Lu and published by World Scientific. This book was released on 2020-08-04 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recommender systems provide users (businesses or individuals) with personalized online recommendations of products or information, to address the problem of information overload and improve personalized services. Recent successful applications of recommender systems are providing solutions to transform online services for e-government, e-business, e-commerce, e-shopping, e-library, e-learning, e-tourism, and more.This unique compendium not only describes theoretical research but also reports on new application developments, prototypes, and real-world case studies of recommender systems. The comprehensive volume provides readers with a timely snapshot of how new recommendation methods and algorithms can overcome challenging issues. Furthermore, the monograph systematically presents three dimensions of recommender systems — basic recommender system concepts, advanced recommender system methods, and real-world recommender system applications.By providing state-of-the-art knowledge, this excellent reference text will immensely benefit researchers, managers, and professionals in business, government, and education to understand the concepts, methods, algorithms and application developments in recommender systems.
Book Synopsis Recommender Systems in Fashion and Retail by : Nima Dokoohaki
Download or read book Recommender Systems in Fashion and Retail written by Nima Dokoohaki and published by Springer Nature. This book was released on 2021-03-23 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes the proceedings of the second workshop on recommender systems in fashion and retail (2020), and it aims to present a state-of-the-art view of the advancements within the field of recommendation systems with focused application to e-commerce, retail, and fashion by presenting readers with chapters covering contributions from academic as well as industrial researchers active within this emerging new field. Recommender systems are often used to solve different complex problems in this scenario, such as product recommendations, or size and fit recommendations, and social media-influenced recommendations (outfits worn by influencers).
Book Synopsis Handbook of Media Branding by : Gabriele Siegert
Download or read book Handbook of Media Branding written by Gabriele Siegert and published by Springer. This book was released on 2015-08-07 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive handbook critically addresses current issues and achievements in the field of media branding. By discussing media branding from different viewpoints, disciplines and research traditions, this book offers fresh perspectives and identifies areas of interest for further research. The authors highlight the peculiarities of this field and reveal links and commonalities with other areas of study within communication science. The chapters address different research areas, such as society-, content-, management-, audience- as well as advertising aspects of media brands. This handbook thus brings together contributions from different areas making it a valuable resource for researchers and experts from industry interested in media branding.
Book Synopsis Consumer Participation in Using Online Product Recommendation Agents by : Xiaojing Sheng
Download or read book Consumer Participation in Using Online Product Recommendation Agents written by Xiaojing Sheng and published by . This book was released on 2009 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: Online product recommendation agents are gaining greater strategic importance as an innovative technology to deliver value-added services to consumers. Yet the active role of consumers as the participants in using this technology is not well understood. This dissertation builds on the technology-based self-service (TBSS) literature, consumer participation literature, the service-dominant logic, and the trust literature on recommendation agents to develop a research framework that explains the role of consumer participation in using online product recommendation agents. The objective of this dissertation is three-fold: (1) to examine the effects of consumer participation and privacy/security disclosures in using online product recommendation agents, (2) to explore the mediating effects of trust, perceived control, and perceived risk in providing personal information, and (3) to test the trust transference process within the current research context. A field experiment using existing recommendation agents was conducted with multiple sessions in computer labs to collect data from university students, a representative sample of the online population. 67 undergraduate students participated in the pretest, and 117 participated in the main study. Structural equation modeling with AMOS 7.0 was used to test the research hypotheses. The results showed that consumer participation was a contributing factor in building consumers' trust in recommendation agents and that privacy/security disclosures decreased consumers' perceived risk in providing personal information. Moreover, the trust transference process was validated among the three different types of consumer trust within the agent-mediated environment, that is, trust in the recommendation agent, trust in the Web site, and trust in recommendations. Finally, perceived control was shown to be a salient factor in increasing consumers' trust and motivating consumers to reuse the recommendation technology.
Book Synopsis Fashion Recommender Systems by : Nima Dokoohaki
Download or read book Fashion Recommender Systems written by Nima Dokoohaki and published by Springer. This book was released on 2020-11-05 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes the proceedings of the first workshop on Recommender Systems in Fashion 2019. It presents a state of the art view of the advancements within the field of recommendation systems with focused application to e-commerce, retail and fashion. The volume covers contributions from academic as well as industrial researchers active within this emerging new field. Recommender Systems are often used to solve different complex problems in this scenario, such as social fashion-based recommendations (outfits inspired by influencers), product recommendations, or size and fit recommendations. The impact of social networks and the influence that fashion influencers have on the choices people make for shopping is undeniable. For instance, many people use Instagram to learn about fashion trends from top influencers, which helps them to buy similar or even exact outfits from the tagged brands in the post. When traced, customers’ social behavior can be a very useful guide for online shopping websites, providing insights on the styles the customers are really interested in, and hence aiding the online shops in offering better recommendations and facilitating customers quest for outfits. Another well known difficulty with recommendation of similar items is the large quantities of clothing items which can be considered similar, but belong to different brands. Relying only on implicit customer behavioral data will not be sufficient in the coming future to distinguish between for recommendation that will lead to an item being purchased and kept, vs. a recommendation that might result in either the customer not following it, or eventually return the item. Finding the right size and fit for clothes is one of the major factors not only impacting customers purchase decision, but also their satisfaction from e-commerce fashion platforms. Moreover, fashion articles have important sizing variations. Finally, customer preferences towards perceived article size and fit for their body remain highly personal and subjective which influences the definition of the right size for each customer. The combination of the above factors leaves the customers alone to face a highly challenging problem of determining the right size and fit during their purchase journey, which in turn has resulted in having more than one third of apparel returns to be caused by not ordering the right article size. This challenge presents a huge opportunity for research in intelligent size and fit recommendation systems and machine learning solutions with direct impact on both customer satisfaction and business profitability.
Book Synopsis Recommender Systems in Fashion and Retail by : Humberto Jesús Corona Pampín
Download or read book Recommender Systems in Fashion and Retail written by Humberto Jesús Corona Pampín and published by Springer Nature. This book was released on 2023-03-01 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes the proceedings of the fourth workshop on recommender systems in fashion and retail (2022), and it aims to present a state-of-the-art view of the advancements within the field of recommendation systems with focused application to e-commerce, retail, and fashion by presenting readers with chapters covering contributions from academic as well as industrial researchers active within this emerging new field. Recommender systems are often used to solve different complex problems in this scenario, such as product recommendations, size and fit recommendations, and social media-influenced recommendations (outfits worn by influencers).
Book Synopsis Recommender Systems in Fashion and Retail by : Nima Dokoohaki
Download or read book Recommender Systems in Fashion and Retail written by Nima Dokoohaki and published by Springer Nature. This book was released on 2022-03-07 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes the proceedings of the third workshop on recommender systems in fashion and retail (2021), and it aims to present a state-of-the-art view of the advancements within the field of recommendation systems with focused application to e-commerce, retail, and fashion by presenting readers with chapters covering contributions from academic as well as industrial researchers active within this emerging new field. Recommender systems are often used to solve different complex problems in this scenario, such as product recommendations, size and fit recommendations, and social media-influenced recommendations (outfits worn by influencers).
