Anindya Ghose
New York University, Stern School of Business, Faculty Member
- Anindya Ghose is a Professor of Information, Operations and Management Sciences and a Professor of Marketing at New Y... moreAnindya Ghose is a Professor of Information, Operations and Management Sciences and a Professor of Marketing at New York University's Leonard N. Stern School of Business. He is the Director of the Center for Business Analytics at NYU Stern. He is the NEC Faculty Fellow at NYU Stern. He has been a Visiting Associate Professor at the Wharton School of Business. In 2014, he was named by Poets & Quants as one of the "Top 40 Professors Under 40 Worldwide" and by Analytics Week as one the "Top 200 Thought Leaders in Big Data and Business Analytics". He is the youngest ever receipient of the highly prestigious INFORMS ISS Distinguished Fellow Award, given to recognize individuals who (i) have made outstanding intellectual contributions to the discipline with publications that have made a significant impact on theory, research, and practice and (ii) intellectual stewardship of the field as reflected in the mentoring of doctoral students and young researchers. His rise from assistant to full professor in 8.5 years at NYU Stern is widely regarded as one of the fastest in the history of the entire Information Systems, operations and Marketing academic disciplines in business schools globally.
He has consulted in various capacities for Berkeley Corporation, CBS, Dataxu, Facebook, NBC Universal, OneVest, Samsung, Showtime, and 3TI World, and collaborated with Adobe, Alibaba, China Mobile, Google, IBM, Indiegogo, Microsoft, Recobell, Travelocity and many other leading Fortune 500 firms on realizing business value from IT investments, internet marketing, business analytics, mobile marketing, digital analytics, social media, and other areas. He also occasionally serves as an expert witness for information technology and consumer-related litigation (intellectual property, patent damages and consumer damages, consumer behavior in high tech industries and information disclosure on internet platforms). He currently serves as a Scientific Expert with Cornerstone Research. He also serves as main the Scientific Advisor to 3TI World and to OneVest.
He has published more than 80 papers in premier scientific journals and peer reviewed conferences, and has given more than 200 talks internationally. He is a frequent keynote speaker in executive gatherings and thought leading events globally. His research has received 15 best paper awards and nominations. He is a winner of the NSF CAREER award and has been awarded 14 grants from Google, Microsoft and several other corporations. His research analyzes the economic consequences of the Internet on industries and markets transformed by its shared technology infrastructure. He has worked on product reviews, reputation and rating systems, digital marketing, sponsored search advertising, wearable technologies, mobile commerce, mobile advertising, crowdfunding, and online markets. He also plays a senior advisory role to several start-ups in the Internet space. He has been interviewed and his research has been profiled numerous times in the BBC, Bloomberg TV, CNBC, China Daily, The Economist, Financial Times, Fox News, Forbes, Knowledge@Wharton, Korean Broadcasting News Company, Los Angeles Times, Marketplace Radio, MSNBC, National Public Radio, NBC, Newsweek, New York Times, New York Daily, NHK Japan Broadcasting, Reuters, Time Magazine, Washington Post, Wall Street Journal, Xinhua, and elsewhere. He teaches courses on social media, digital marketing, business analytics and IT strategy at the undergraduate, MBA, EMBA, MSBA, and Executive Education level in various parts of the world including the US, India, China, and South Korea.
He is on the Research Council of the Wharton Customer Analytics Institute, a faculty affiliate with the Marketing Science Institute and the Sloan Center for Internet Retailing at the University of California, Riverside. He serves as an Associate Editor of Management Science and a Senior Editor of Information Systems Research. Before joining NYU Stern, Dr. Ghose worked in GlaxoSmithKline, as a Product Manager in HCL-Hewlett Packard, and as a Senior E-Business Consultant with IBM. He has a B. Tech in Engineering from the Regional Engineering College (NIT) in Jalandhar, and an M.B.A in Finance, Marketing and Systems from the Indian Institute of Management, Calcutta. He received his M.S. and Ph.D. from Carnegie Mellon University's Tepper School of Business.edit
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In the past few years, we have witnessed the increasing ubiquity of user-generated content on seller reputation and product condition in Internet-based used-good markets. Recent theoretical models of trading and sorting in used-good... more
In the past few years, we have witnessed the increasing ubiquity of user-generated content on seller reputation and product condition in Internet-based used-good markets. Recent theoretical models of trading and sorting in used-good markets provide testable predictions to use to examine the presence of adverse selection and trade patterns in such dynamic markets. A key aspect of such empirical analyses
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ABSTRACT Online platforms offer access to a larger social group than is generally available through offline contacts, making the internet an emerging venue for seeking casual sex partners. The ease of seeking sex partners through... more
ABSTRACT Online platforms offer access to a larger social group than is generally available through offline contacts, making the internet an emerging venue for seeking casual sex partners. The ease of seeking sex partners through classified ad sites may promote risky behaviors that increase transmission of STDs. In this paper, using a natural experiment set up, we investigate whether the entry of a major online personals ad site, Craigslist, increases the prevalence of HIV over an 11 year period from 1998 to 2008 across 33 states in the United States. After controlling for extraneous factors, our results suggest that the entry of Craigslist is related to a 39.5 percent increase in HIV cases. Our analysis suggests that the site entry produces an average of 3944 to 5170 cases of HIV infection in the U.S. each year, mapping out to $39.9 million to $52.3 million dollars in annual treatment costs. It is also estimated that one case of HIV infection arises from every 125 to 164 ads posted on the website. In addition, the analyses reveal that non-market related casual sex is the primary driver of the increase in HIV cases, in contrast to paid transactions (e.g., escort services and prostitution) solicited on the site which has a negative relationship with HIV trends. These findings are essential to the understanding of the social routes through which HIV transmission takes place and the extent to which site entry can influence HIV trends. Implications for healthcare practitioners and policy makers are discussed.
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... DOI Bookmark: 10.1287/mksc.1090.0552. ABSTRACT. The phenomenon of paid search advertising has now become the most predominant form of online advertising in the marketing world. However, we have little understanding ...
Research Interests: Marketing, Internet Marketing, Online Advertising, Panel Data, User Generated Content, and 10 moreMarketing Science, Markov Chain Monte Carlo, Profitability, Search Engine, Field Experiment, Bayesian hierarchical model, Markov chain monte carlo methods, Sponsored Search, Electronic Commerce, and Click Through Rate
ABSTRACT Price dispersion is an important indicator of market efficiency. Internet-based electronic markets have the potential to reduce transaction and search costs, thereby creating more efficient, “frictionless,” markets as predicted... more
ABSTRACT Price dispersion is an important indicator of market efficiency. Internet-based electronic markets have the potential to reduce transaction and search costs, thereby creating more efficient, “frictionless,” markets as predicted by theories in information economics. However, prior work has reported significant levels of price dispersion on the Internet, which is in contrast to theoretical predictions. A key feature of the existing stream of work has been its use of posted prices to estimate price dispersion. In theory, this can lead to an overestimation of price dispersion because a sale may not have occurred at the posted price. In this research, we use a unique dataset of actual transaction prices collected from both the electronic and offline markets of buyers in a B2B market to evaluate the extent of price dispersion. We find that price dispersion in the electronic market is as low as 0.22%, which is substantially less than those reported in the existing literature. This near-zero price dispersion suggests that in some electronic markets the “law of one price” can prevail when we consider transaction prices instead of posted prices. We further develop a theoretical framework that identifies several new drivers of price dispersion using transaction data. In particular, we focus on four product-level and market-level attributes – product cost, order cycle time, own price elasticity and transaction quantity, and estimate their impact on price dispersion. We also examine the electronic market's moderating role in the relationship between these drivers and price dispersion. Finally, we estimate the efficiency gains accruing from transactions in the relatively friction-free market and find that the electronic market can enhances consumer surplus by as much as $97.92 million per year.
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Increasingly, user-generated product reviews, images and tags serve as a valuable source of information for customers making product choices online. An extant stream of work has looked at the economic impact of reviews. Typically, the... more
Increasingly, user-generated product reviews, images and tags serve as a valuable source of information for customers making product choices online. An extant stream of work has looked at the economic impact of reviews. Typically, the impact of product reviews has been incorporated by numeric variables representing the valence and volume of reviews. In this paper, we posit that the information
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The growing pervasiveness of the Internet has changed the way that consumers shop for goods. Increasingly, user-generated product reviews serve as a valuable source of information for customers making product choices online. While there... more
The growing pervasiveness of the Internet has changed the way that consumers shop for goods. Increasingly, user-generated product reviews serve as a valuable source of information for customers making product choices online. While there is a significant body of theory on multi-attribute choice under uncertainty, the literature that examines product reviews has not built on this stream of theory for
Research Interests: Sentiment Analysis, Text Mining, Business Intelligence, Management Science, Tensor product semigroups, and 11 moreElectronic Markets, Bayesian Learning, User Generated Content, Consumer Choice, Opinion Mining, Prediction Model, Discrete Choice, Electronic Commerce, Information Embedding, Data Gathering, and Information System
It is well known that the Internet has significantly reduced consumers’ search costs online. But relatively little is known about how search costs affect consumer demand structure in online markets. In this paper, we identify the impact... more
It is well known that the Internet has significantly reduced consumers’ search costs online. But relatively little is known about how search costs affect consumer demand structure in online markets. In this paper, we identify the impact of search costs on firm competition and market structure by exploring a unique theoretical insight that search costs create a kink in aggregate
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With the rapid growth of the Internet, the ability of users to create and publish content has created active electronic communities that provide a wealth of product information. However, the high volume of reviews that are typically... more
With the rapid growth of the Internet, the ability of users to create and publish content has created active electronic communities that provide a wealth of product information. However, the high volume of reviews that are typically published for a single product makes harder for individuals as well as manufacturers to locate the best reviews and understand the true underlying
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With the rapid growth of the Internet, users' ability to publish content has created active electronic com- munities that provide a wealth of product information. Consumers naturally gravitate to reading reviews in order to decide... more
With the rapid growth of the Internet, users' ability to publish content has created active electronic com- munities that provide a wealth of product information. Consumers naturally gravitate to reading reviews in order to decide whether to buy a product. However, the high volume of reviews that are typically pub- lished for a single product makes it harder for individuals
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We present a framework for identifying the different dimensions of online reputation and characterizingtheir influence on the pricing power of sellers. Our theory predicts that sellers with better recorded onlinereputation can... more
We present a framework for identifying the different dimensions of online reputation and characterizingtheir influence on the pricing power of sellers. Our theory predicts that sellers with better recorded onlinereputation can successfully charge higher prices than competing sellers of identical products, and that theirpricing power increases with their recorded level of experience. We develop and implement a new text miningtechnique
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Deriving the polarity and strength of opinions is an important research topic, attracting sig- nificant attention over the last few years. In this work, to measure the strength and po- larity of an opinion, we consider the eco- nomic... more
Deriving the polarity and strength of opinions is an important research topic, attracting sig- nificant attention over the last few years. In this work, to measure the strength and po- larity of an opinion, we consider the eco- nomic context in which the opinion is eval- uated, instead of using human annotators or linguistic resources. We rely on the fact
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... 18 Page 2. have also begun investing heavily in search engine optimization (SEO) to improve their organic search results, either in addition or in lieu of search engine marketing (SEM). SEO refers to the process of tailoring a ...
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... Hence, it is now considered to be among the most effective marketing vehicles available in the online world.1 Despite the ... Given the shift in advertising from traditional banner advertising tosearch engine advertising, an... more
... Hence, it is now considered to be among the most effective marketing vehicles available in the online world.1 Despite the ... Given the shift in advertising from traditional banner advertising tosearch engine advertising, an understanding of the determinants of conversion rates and ...
Research Interests: Decision Making, Web search, Internet Marketing, Electronic Markets, Online Advertising, and 11 moreMarkov Chain Monte Carlo, Search Engine, Internet Use, Bayesian hierarchical model, Consumer Search, Sponsored Search, Empirical Analysis, Bayesian Methods (MCMC), Electronic Commerce, Empirical Model, and Click Through Rate
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The phenomenon of sponsored search advertising - where advertisers pay a fee to Internet search engines to be displayed alongside organic (non-sponsored) web search results - is gaining ground as the largest source of revenues for search... more
The phenomenon of sponsored search advertising - where advertisers pay a fee to Internet search engines to be displayed alongside organic (non-sponsored) web search results - is gaining ground as the largest source of revenues for search engines. Using a unique 6 month panel dataset of several hundred keywords collected from a large nationwide retailer that advertises on Google, we
Research Interests: Marketing, Information Retrieval, Social Sciences, Creativity, Advertising, and 42 moreSocial Interaction, Modeling, Engineering Design, Management Science, Complexity, Web search, New Product Development, Imagination, Search Engines, Electronic Markets, Online Advertising, Panel Data, Problem Solving, Markov Chain Monte Carlo, Team work, Idea Generation, Profitability, Product Development, Search Engine, World Wide Web, Economic Impact, Ideation, Income, Bayesian hierarchical model, Consumer Search, Markov chain monte carlo methods, Sponsored Search, Empirical Method, Cross Selling, Empirical Analysis, Metric, Bayesian Methods (MCMC), Theoretical Model, Internet, Social Science, Electronic Commerce, Empirical Model, Monte Carlo Method, New Product, Click Through Rate, Simultaneous equations, and Markov model
n many industries, Internet referral services, hosted either by independent third-party infomediaries or by manufacturers, serve as digitally enabled lead generators in electronic markets, directing consumer traffic to downstream... more
n many industries, Internet referral services, hosted either by independent third-party infomediaries or by manufacturers, serve as digitally enabled lead generators in electronic markets, directing consumer traffic to downstream retailers in a distribution network. This reshapes the extended enterprise from the traditional net- work of upstream manufacturers and downstream retailers to include midstream third-party and manufacturer- owned referral services in
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We develop an analytical framework to investigate the competitive implications of personal- ized pricing (PP), whereby firms charge different prices to different consumers, based on their willingness to pay. We embed personalized pricing... more
We develop an analytical framework to investigate the competitive implications of personal- ized pricing (PP), whereby firms charge different prices to different consumers, based on their willingness to pay. We embed personalized pricing in a model of vertical product differentiation, and show how it affects firms' choices over quality. We show that firms' optimal pricing strate- gies with PP may
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Research Interests: Econometrics, Sentiment Analysis, Text Mining, Business Intelligence, Tensor product semigroups, and 10 moreImage Quality, Electronic Markets, User Generated Content, Opinion Mining, Data Mining and Knowledge Discovery, Experimental Evaluation, Hedonic Regression, Internet, E Commerce, and Electronic Commerce
ABSTRACT Online platforms offer access to a larger social group than is generally available through offline contacts, making the internet an emerging venue for seeking casual sex partners. The ease of seeking sex partners through... more
ABSTRACT Online platforms offer access to a larger social group than is generally available through offline contacts, making the internet an emerging venue for seeking casual sex partners. The ease of seeking sex partners through classified ad sites may promote risky behaviors that increase transmission of STDs. In this paper, using a natural experiment set up, we investigate whether the entry of a major online personals ad site, Craigslist, increases the prevalence of HIV over a 10 year period from 1999 to 2008 across 33 states in the United States. After controlling for extraneous factors, our results suggest that the entry of Craigslist is related to a 15.9 percent increase in HIV cases. Our analysis suggests that the site entry produces an average of 6130 to 6455 cases of HIV infection in the U.S. each year, mapping out to $62 million to $65.3 million in annual treatment costs. In addition, the analyses reveal that non-market related casual sex is the primary driver of the increase in HIV cases, in contrast to paid transactions solicited on the site (e.g., escort services and prostitution) which has a negative relationship with HIV trends. These findings are essential to the understanding of the social routes through which HIV transmission takes place and the extent to which site entry can influence HIV trends. Implications for healthcare practitioners and policy makers are discussed.
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ABSTRACT We analyze patterns of online lending between individuals using data drawn from Kiva, a global crowd-funding platform that facilitates pro-social (peer-to-peer) lending. Our analysis, which employs a data set capturing more than... more
ABSTRACT We analyze patterns of online lending between individuals using data drawn from Kiva, a global crowd-funding platform that facilitates pro-social (peer-to-peer) lending. Our analysis, which employs a data set capturing more than three million individual lending transactions between 2005 and 2010, considers the dual roles of geographic and cultural distance on lenders’ decisions about which borrowers to support. Although cultural differences have seen extensive study in the IT literature as sources of friction in extended interactions, we argue and demonstrate their role in individuals’ selection of an online transaction partner. We find evidence that lenders do prefer culturally similar borrowers. An analysis of marginal effects indicates that an increase of one standard deviation in cultural differences would be associated with approximately 430 fewer lending actions, at the average, for a given pair of countries; (a loss of more than $10,000). We further find that lenders treat cultural differences and physical distance as substitutes. A one standard deviation increase in physical distance is associated with a 25% decline in the cultural effect, at the average. Finally, we offer some empirical evidence of the potential for IT-based trust mechanisms to overcome culture’s effects, considering, in particular, Kiva’s reputation rating system for micro-finance partners. We discuss the implications of our findings for pro-social lending, online crowd-funding, and electronic markets more broadly.
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Page 1. Social network collaborative filtering RONG ZHENG, DENNIS WILKINSON & FOSTER PROVOST1 _____ ... However, SNCF using "ally" alters is competitive with CF. ...
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We develop a game-theoretical framework to investigate the competitive implications of Consumer-to-Consumer electronic marketplaces, which promote concurrent selling of new and used goods. In many e-marketplaces, where suppliers cannot... more
We develop a game-theoretical framework to investigate the competitive implications of Consumer-to-Consumer electronic marketplaces, which promote concurrent selling of new and used goods. In many e-marketplaces, where suppliers cannot directly use second-hand goods for practicing inter-temporal price discrimination, the threat of cannibalization of new goods by used goods become significant. We examine conditions under when it is optimal for suppliers
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Abstract We develop a game-theoretic framework to investigate the competitive implications of consumer-to-consumer electronic marketplaces, which promote concurrent selling of new and used goods. In many e-marketplaces, where suppliers... more
Abstract We develop a game-theoretic framework to investigate the competitive implications of consumer-to-consumer electronic marketplaces, which promote concurrent selling of new and used goods. In many e-marketplaces, where suppliers cannot directly use second-hand goods for practicing inter-temporal price discrimination, the threat of cannibalization of new goods by used goods become significant. We examine conditions under which it is optimal for suppliers to operate in such markets, explaining why used-goods markets may not be ...