scholarly journals An Empirical Analysis of Search Engine Advertising: Sponsored Search in Electronic Markets

2009 ◽  
Author(s):  
Anindya Ghose ◽  
Sha Yang
Keyword(s):  
Search Engine ◽  
Empirical Analysis ◽  
Electronic Markets ◽  
Sponsored Search ◽  
Search Engine Advertising

Differences Across Device Usage in Search Engine Advertising

2018 ◽  
pp. 250-279
Author(s):  
Carsten D. Schultz ◽  
Christian Holsing
Keyword(s):  
Mobile Devices ◽  
Search Engine ◽  
Service Provider ◽  
Performance Indicators ◽  
Target Group ◽  
Search Process ◽  
Advertising Campaign ◽  
Search Engine Advertising ◽  
Multiple Devices

For advertisers, search engine advertising represents an attractive opportunity to selectively reach the target group at a point in time when the prospects are already thematically involved and activated. One question that subsequently arises is if users use various devices during different phases of the search process and if this behavior affects the search engine advertising outcome measured by corresponding performance indicators. The present chapter addresses this question. Based on a search engine advertising campaign of a German service provider, the authors examine the development of performance indicators across multiple devices. Specifically, we retrace the development across desktops, tablets, and mobile devices. Thus, the chapter provides insights into device usage in search engine advertising. The chapter concludes with overall trends in search engine advertising.

Critical Analysis of Major Search Engines

2019 ◽  
Vol 16 (9) ◽  
pp. 3712-3716
Author(s):  
Kailash Kumar ◽  
Abdulaziz Al-Besher
Keyword(s):  
Search Engine ◽  
Search Engines ◽  
Critical Analysis ◽  
Research Paper ◽  
Web Pages ◽  
Ranking Algorithm ◽  
Sponsored Search ◽  
Web Page ◽  
Rigorous Analysis ◽  
The Common

This paper examines the overlapping of the results retrieved between three major search engines namely Google, Yahoo and Bing. A rigorous analysis of overlap among these search engines was conducted on 100 random queries. The overlap of first ten web page results, i.e., hundred results from each search engine and only non-sponsored results from these above major search engines were taken into consideration. Search engines have their own frequency of updates and ranking of results based on their relevance. Moreover, sponsored search advertisers are different for different search engines. Single search engine cannot index all Web pages. In this research paper, the overlapping analysis of the results were carried out between October 1, 2018 to October 31, 2018 among these major search engines namely, Google, Yahoo and Bing. A framework is built in Java to analyze the overlap among these search engines. This framework eliminates the common results and merges them in a unified list. It also uses the ranking algorithm to re-rank the search engine results and displays it back to the user.

Empirical Generalizations in Search Engine Advertising

2014 ◽  
Vol 90 (2) ◽  
pp. 206-216 ◽  
Author(s):  
Nadia Abou Nabout ◽  
Markus Lilienthal ◽  
Bernd Skiera
Keyword(s):  
Search Engine ◽  
Search Engine Advertising ◽  
Empirical Generalizations

Analysing search engine advertising research: synthesis of two decades of research

2015 ◽  
Vol 7 (4) ◽  
pp. 308 ◽  
Author(s):  
Hamed Jafarzadeh ◽  
Aybüke Aurum ◽  
John D' ◽  
N.A. Ambra ◽  
Amir Hossein Ghapanchi
Keyword(s):  
Search Engine ◽  
Research Synthesis ◽  
Advertising Research ◽  
Search Engine Advertising

Empirical Work on Auctions of Multiple Objects

2018 ◽  
Vol 56 (1) ◽  
pp. 157-184 ◽  
Author(s):  
Ali Hortaçsu ◽  
David McAdams
Keyword(s):  
Empirical Analysis ◽  
Empirical Work ◽  
Sponsored Search ◽  
Multiple Objects ◽  
Treasury Bonds ◽  
Empirical Auctions ◽  
Recent Developments ◽  
The Empirical Analysis ◽  
Abundant Data

Abundant data has led to new opportunities for empirical auctions research in recent years, with much of the newest work on auctions of multiple objects, including: (1) auctions of ranked objects (such as sponsored search ads), (2) auctions of identical objects (such as Treasury bonds), and (3) auctions of dissimilar objects (such as FCC spectrum licenses). This paper surveys recent developments in the empirical analysis of such auctions. (JEL D44, H82)

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