Young-Hoon Park

Bio: Young-Hoon Park is an academic researcher from Cornell University. The author has contributed to research in topics: Common value auction & Bidding. The author has an hindex of 19, co-authored 38 publications receiving 1550 citations. Previous affiliations of Young-Hoon Park include Saint Petersburg State University.

Modeling Browsing Behavior at Multiple Websites

Abstract: While there is a growing literature on investigating the Internet clickstream data collected for a single site, such datasets are inherently incomplete because they generally do not capture shopping behavior across multiple websites. A customer's visit patterns at one or more other sites may provide relevant information about the timing and frequency of his or her future visit patterns at the site of interest. We develop a stochastic timing model of cross-site visit behavior to understand how to leverage information from one site to help explain customer behavior at another. To this end, we incorporate two sources of association in browsing patterns: one for the observable outcomes i.e., arrival times of two timing processes and the other for the latent visit propensities across a set of competing sites. This proposed multivariate timing mixture model can be viewed as a generalization of the univariate exponential-gamma model. In our empirical analysis, we show that a failure to account for both sources of association not only leads to poor fit and forecasts, but also generates systematically biased parameter estimates. We highlight the model's ability to make accurate statements about the future behavior of the "zero class" i.e., previous nonvisitors to a given site using summary information i.e., recency and frequency from past visit patterns at a competing site.

An Integrated Model for Bidding Behavior in Internet Auctions: Whether, Who, When, and how Much:

Abstract: The authors develop a general parametric modeling framework for bidding behavior in Internet auctions. Toward this end, they incorporate four key components of the bidding process under their framework: whether people bid on an auction, (if so) who bids, when they bid, and how much they bid over the entire sequence of bids in an auction. This integrated framework is based on a single, latent, time-varying construct of consumer willingness to bid, which bidders have and update for a particular auction item over the course of the auction duration. Using a database of notebook auctions from one of the largest Internet auction sites in Korea, the authors demonstrate that this general (yet parsimonious) model captures the key behavioral aspects of bidding behavior. Furthermore, the authors provide a valuable tool for managers at auction sites to conduct their customer relationship management efforts, which require them to evaluate the “goodness” of the listed auction items (whether people bid) and the...

A “Position Paradox” in Sponsored Search Auctions

Abstract: We study the bidding strategies of vertically differentiated firms that bid for sponsored search advertisement positions for a keyword at a search engine. We explicitly model how consumers navigate and click on sponsored links based on their knowledge and beliefs about firm qualities. Our model yields several interesting insights; a main counterintuitive result we focus on is the “position paradox.” The paradox is that a superior firm may bid lower than an inferior firm and obtain a position below it, yet it still obtains more clicks than the inferior firm. Under a pay-per-impression mechanism, the inferior firm wants to be at the top where more consumers click on its link, whereas the superior firm is better off by placing its link at a lower position because it pays a smaller advertising fee, but some consumers will still reach it in search of the higher-quality firm. Under a pay-per-click mechanism, the inferior firm has an even stronger incentive to be at the top because now it only has to pay for the consumers who do not know the firms' reputations and, therefore, can bid more aggressively. Interestingly, as the quality premium for the superior firm increases, and/or if more consumers know the identity of the superior firm, the incentive for the inferior firm to be at the top may increase. Contrary to conventional belief, we find that the search engine may have the incentive to overweight the inferior firm's bid and strategically create the position paradox to increase overall clicks by consumers. To validate our model, we analyze a data set from a popular Korean search engine firm and find that (i) a large proportion of auction outcomes in the data show the position paradox, and (ii) sharp predictions from our model are validated in the data.

Consumer click behavior at a search engine: : the role of keyword popularity

Abstract: The authors study consumers' click behavior on organic and sponsored links after a keyword search on an Internet search engine. Using a data set of individual-level click activity after keyword searches from a leading search engine in Korea, the authors find that consumers' click activity after a keyword search is low and heavily concentrated on the organic list. However, searches of less popular keywords (i.e., keywords with lower search volume) are associated with more clicks per search and a larger fraction of sponsored clicks. This indicates that, compared with more popular keywords, consumers who search for less popular keywords expend more effort in their search for information and are closer to a purchase, which makes them more targetable for sponsored search advertising.

Asymmetric Consumer Learning and Inventory Competition

Abstract: We develop a model of consumer learning and choice behavior in response to uncertain service in the marketplace. Learning could be asymmetric, that is, consumers may associate different weights with positive and negative experiences. Under this consumer model, we characterize the steady-state distribution of demand for retailers given that each retailer holds a constant in-stock service level. We then consider a noncooperative game in steady state between two retailers competing on the basis of their service levels. The demand distributions of retailers in this game are modeled using a multiplicative aggregate market-share model in which the mean demands are obtained from the steady-state results for individual purchases, but the model is simplified in other respects for tractability. Our model yields a unique pure strategy Nash equilibrium. We show that asymmetry in consumer learning has a significant impact on the optimal service levels, market shares, and profits of the retailers. When retailers have different costs, it also determines the extent of competitive advantage enjoyed by the lower-cost retailer.

Economics of Information

Abstract: The author systematically examines one of the important issues of information — establishing the market price. He introduces the concept of «search» — where a buyer wanting to get a better price, is forced to question sellers. The article deals with various aspects of finding the necessary information.

Using Online Conversations to Study Word-of-Mouth Communication

Abstract: Managers are very interested in word-of-mouth communication because they believe that a product's success is related to the word of mouth that it generates. However, there are at least three significant challenges associated with measuring word of mouth. First, how does one gather the data? Because the information is exchanged in private conversations, direct observation traditionally has been difficult. Second, what aspect of these conversations should one measure? The third challenge comes from the fact that word of mouth is not exogenous. While the mapping from word of mouth to future sales is of great interest to the firm, we must also recognize that word of mouth is an outcome of past sales. Our primary objective is to address these challenges. As a context for our study, we have chosen new television (TV) shows during the 1999-2000 seasons. Our source of word-of-mouth conversations is Usenet, a collection of thousands of newsgroups with diverse topics. We find that online conversations may offer an easy and cost-effective opportunity to measure word of mouth. We show that a measure of the dispersion of conversations across communities has explanatory power in a dynamic model of TV ratings.

The Impact of New Media on Customer Relationships

Abstract: Recent years have witnessed the rise of new media channels such as Facebook, YouTube, Google, and Twitter, which enable customers to take a more active role as market players and reach (and be reached by) almost everyone anywhere and anytime. These new media threaten long established business models and corporate strategies, but also provide ample opportunities for growth through new adaptive strategies. This paper introduces a new ‘‘pinball’’ framework of new media’s impact on relationships with customers and identifies key new media phenomena which companies should take into account when managing their relationships with customers in the new media universe. For each phenomenon, we identify challenges for researchers and managers which relate to (a) the understanding of consumer behavior, (b) the use of new media to successfully manage customer interactions, and (c) the effective measurement of customers’ activities and outcomes.

Deriving Value from Social Commerce Networks

Abstract: Social commerce is an emerging trend in which sellers are connected in online social networks, and where sellers are individuals instead of firms. This paper examines the economic value implications of a social network between sellers in a large online social commerce marketplace. In this marketplace each seller creates his or her own shop, and network ties between sellers are directed hyperlinks between their shops. Three questions are addressed: (i) Does allowing sellers to connect to one another create value (i.e., increase sales), (ii) what are the mechanisms through which this value is created, (iii) how is this value distributed across sellers in the network and how does the position of a seller in the network (e.g., its centrality) influence how much it benefits or suffers from the network? We find that: (i) allowing sellers to connect generates considerable economic value, (ii) the network's value lies primarily in making shops more accessible to customers browsing the marketplace (the network creates a "virtual shopping mall"); and (iii) the sellers that benefit the most from the network are not necessarily those that are central to the network, but rather those whose accessibility is most enhanced by the network.

Crowdsourcing New Product Ideas Over Time: An Analysis of Dell's Ideastorm Community

Abstract: Several organizations have developed ongoing crowdsourcing communities that repeatedly collect ideas for new products and services from a large, dispersed “crowd” of non-experts (consumers) over time. Despite its promises, little is known about the nature of an individual’s ideation efforts in such an online community. Studying Dell’s IdeaStorm community, serial ideators are found to be more likely than consumers with only one idea to generate an idea the organization find valuable enough to implement, but are unlikely to repeat their early success once their ideas are implemented. As ideators with past success attempt to again come up with ideas that will excite the organization, they instead end up proposing ideas similar to their ideas that were already implemented (i.e., they generate less diverse ideas). The negative effects of past success are somewhat mitigated for ideators with diverse commenting activity on others’ ideas. These findings highlight some of the challenges in maintaining an ongoing supply of quality ideas from the crowd over time.