Format:
Online-Ressource (76 p)
ISBN:
9783319186443
Series Statement:
SpringerBriefs in Operations Management
Content:
This book provides a comprehensive overview of optimization issues and models in web and mobile advertising. It begins by discussing the evolution of web advertising over time. This is followed by the discussion of prominent pricing models. The reader is provided with a basic overview of different optimization issues involved in web advertising. The earlier models mainly considered the problem of scheduling ads competing to be placed on a web page. Here, the ads were specified by geometry and display frequency, and both of these factors were considered in developing a solution to the advertisement scheduling problem. These models were similar in nature to the problem of scheduling ads on newspaper or television, but the pricing structure in these models were different from those in newspaper or television ads. As the web advertising evolved, the initial models were augmented by considering how the schedule of ads is changed based on individual user click behavior. Thus, these models considered personalization in web advertising. The book also presents methods to help solve these models. More recently, there has been tremendous growth in mobile advertising. This book also provides the details of business model in mobile advertising, and presents solutions for the optimization problem involved in mobile advertising. Additionally this book looks to key future trends in web and mobile advertising (such as Fading Ads) and the associated challenges that come with it. For instance, the future trends in pricing models are more towards action-based pricing rather than impression-based pricing. Subodha Kumar (Ph.D., University of Texas at Dallas, 2001) is the Carol and G. David Van Houten, Jr. '71 Professor at the Mays Business School, Texas AM University. He has previously served at the Foster School of Business, University of Washington. He is also a regular Visiting Scholar at the Indian School of Business. Professor Kumar s research and teaching interests include Quantitative Methods, Supply Chain Management and Information Technology. He has published 21 papers in reputed journals and 50 papers in refereed conferences. In addition, he has co-authored Harvard Business School Cases and Ivey Cases. Professor Kumar also has a patent. The list of journals where his papers have appeared include Management Science, Operations Research, Information Systems Research, Production and Operations Management, IIE Transactions, Decision Sciences, Journal of Management Information Systems, IEEE Transactions on Knowledge and Data Engineering, European Journal of Operational Research, Interfaces, Journal of Scheduling and Computers and Industrial Engineering. Professor Kumar is currently the Deputy Editor and a Department Editor of Production and Operations Management, a Senior Editor of Decision Sciences, an Associate Editor of Information Systems Research and serves on the editorial boards of Journal of Database Management and International Journal of Social and Organizational Dynamics in IT. He has also organized several conferences. He has featured on the University of Washington Television and the Industrial Engineer Magazine. Prof. Kumar has taught different Ph.D., MBA, and Undergraduate level courses. He has also taught different courses for Executive MBA and Executive Programs. He has received numerous faculty-determined and student-initiated teaching awards at both Texas AM University and University of Washington.
Note:
Description based upon print version of record
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Preface; Contents; 1 Evolution of Web Advertising; 1.1 History of Web Advertising; 1.1.1 Early Phases of Web Advertising; 1.1.2 Targeting Phase of Web Advertising; 1.1.3 Growth of Web Advertising in the Twenty-First Century; 1.2 Types of Web Ads; 1.3 Differences Between Web Advertising and Offline Advertising; References; 2 Pricing Models in Web Advertising; 2.1 Traditional Exposure-Based Pricing Models; 2.2 Performance-Based Pricing Models; 2.2.1 Cost-Per-Click Pricing Model; 2.2.2 Cost-Per-Action Pricing Model; 2.2.3 Outcome-Based Pricing Model; 2.3 Hybrid Pricing Models; References
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3 Scheduling Advertisements on a Web Page3.1 Introduction; 3.2 Problem Description; 3.3 Earlier Results for Special Cases of the Problem; 3.4 MINSPACE Problem: Formulation and Complexity; 3.4.1 Approximation Results for the MINSPACE Problem; 3.4.1.1 A Linear Programming Relaxation Based 2-Approximation Algorithm; 3.4.1.2 An Improved Approximation Algorithm; 3.4.1.3 Constant Factor Approximation Algorithms; 3.4.2 Special Cases; 3.5 The MAXSPACE Problem; 3.5.1 Approximation Results for the MAXSPACE Problem; 3.5.2 Hybrid Genetic Algorithm; 3.5.3 Special Cases; 3.6 Computational Experience
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References4 Personalization of Web Advertising; 4.1 Introduction; 4.2 Problem Statement, Assumptions, and Approach; 4.2.1 Problem Statement and Assumptions; 4.2.2 Approach; 4.3 Formulating the Static Version; 4.3.1 A Successive Slot Knapsack (SSK) Heuristic; 4.4 Computational Experience: Static Version; 4.5 A Dynamic Version; 4.5.1 Generation of Hypotheses and Statistical Validation; 4.5.2 A Myopic SSK Heuristic for the Dynamic Version; 4.6 Discussions and Recommendations; References; 5 Internet Advertising Firms; 5.1 Introduction; 5.2 Overview of Solution; 5.3 Model and Solution
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5.3.1 Description of the Data Analytic Model5.3.1.1 Predicting the Probability of a Click; 5.3.1.2 The Click-Probability Distribution; 5.3.2 Description of the Decision Analytic Model; 5.4 Impact of Inaccurate Problem Parameters; 5.5 Experimental Results; 5.5.1 Choice of Update Frequency; 5.5.2 Final Recommendations; References; 6 Mobile Advertising; 6.1 Introduction; 6.2 Optimization Model; 6.2.1 Notations; 6.2.2 Formulation; 6.2.3 Special Case 1; 6.2.4 Special Case 2; 6.3 Comparison with the Existing Practice at Chitika; References
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7 Future Trends and Challenges in Web and Mobile Advertising7.1 Inclusion of Advertiser Constraints in the Problem of Ad-Firm; 7.2 Real-Time Media Buying; 7.3 Fading Ads; References; Index
Additional Edition:
9783319186450
Additional Edition:
9783319186443
Additional Edition:
Erscheint auch als Druck-Ausgabe Optimization Issues in Web and Mobile Advertising : Past and Future Trends
Language:
English
Keywords:
Electronic books
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