Examining the Impact of Ranking on Consumer Behavior and Search Engine Revenue

被引:167
作者
Ghose, Anindya [1 ]
Ipeirotis, Panagiotis G. [2 ]
Li, Beibei [3 ]
机构
[1] NYU, Stern Sch Business, Dept Mkt, Dept Informat Operat & Management Sci, New York, NY 10012 USA
[2] NYU, Stern Sch Business, Dept Informat Operat & Management Sci, New York, NY 10012 USA
[3] Carnegie Mellon Univ, Heinz Coll, Pittsburgh, PA 15213 USA
关键词
travel search engine; randomized experiments; hierarchical Bayesian methods; information systems; IT policy and management; electronic commerce; RANDOMIZED-TRIAL; ONLINE; MODEL; INFORMATION; POSITION; REVIEWS; MARKETS; SYSTEMS; PRICE;
D O I
10.1287/mnsc.2013.1828
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
In this paper, we study the effects of three different kinds of search engine rankings on consumer behavior and search engine revenues: direct ranking effect, interaction effect between ranking and product ratings, and personalized ranking effect. We combine a hierarchical Bayesian model estimated on approximately one million online sessions from Travelocity, together with randomized experiments using a real-world hotel search engine application. Our archival data analysis and randomized experiments are consistent in demonstrating the following: (1) A consumer-utility-based ranking mechanism can lead to a significant increase in overall search engine revenue. (2) Significant interplay occurs between search engine ranking and product ratings. An inferior position on the search engine affects "higher-class" hotels more adversely. On the other hand, hotels with a lower customer rating are more likely to benefit from being placed on the top of the screen. These findings illustrate that product search engines could benefit from directly incorporating signals from social media into their ranking algorithms. (3) Our randomized experiments also reveal that an "active" personalized ranking system (wherein users can interact with and customize the ranking algorithm) leads to higher clicks but lower purchase propensities and lower search engine revenue compared with a "passive" personalized ranking system (wherein users cannot interact with the ranking algorithm). This result suggests that providing more information during the decision-making process may lead to fewer consumer purchases because of information overload. Therefore, product search engines should not adopt personalized ranking systems by default. Overall, our study unravels the economic impact of ranking and its interaction with social media on product search engines.
引用
收藏
页码:1632 / 1654
页数:23
相关论文
共 40 条
[11]   UNDERSTANDING THE METROPOLIS-HASTINGS ALGORITHM [J].
CHIB, S ;
GREENBERG, E .
AMERICAN STATISTICIAN, 1995, 49 (04) :327-335
[12]  
Chittor V., 2010, Online Retail: Getting the Right Product in Front of Your Customers
[13]  
De los Santos B., 2013, WORKING PAPER
[14]   Double Marginalization in Performance-Based Advertising: Implications and Solutions [J].
Dellarocas, Chrysanthos .
MANAGEMENT SCIENCE, 2012, 58 (06) :1178-1195
[15]   EFFECTS OF PRICE, BRAND, AND STORE INFORMATION ON BUYERS PRODUCT EVALUATIONS [J].
DODDS, WB ;
MONROE, KB ;
GREWAL, D .
JOURNAL OF MARKETING RESEARCH, 1991, 28 (03) :307-319
[16]  
Dzyabura D, 2014, WORKING PAPER
[17]  
Ghose A, 2013, WORKING PAPER
[18]   How Is the Mobile Internet Different? Search Costs and Local Activities [J].
Ghose, Anindya ;
Goldfarb, Avi ;
Han, Sang Pil .
INFORMATION SYSTEMS RESEARCH, 2013, 24 (03) :613-631
[19]   Designing Ranking Systems for Hotels on Travel Search Engines by Mining User-Generated and Crowdsourced Content [J].
Ghose, Anindya ;
Ipeirotis, Panagiotis G. ;
Li, Beibei .
MARKETING SCIENCE, 2012, 31 (03) :493-520
[20]   An Empirical Analysis of Search Engine Advertising: Sponsored Search in Electronic Markets [J].
Ghose, Anindya ;
Yang, Sha .
MANAGEMENT SCIENCE, 2009, 55 (10) :1605-1622