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on Information and Communication Technologies |
| By: | Babur De los Santos (Kelley School of Business, Indiana University); Ali Hortacsu (University of Chicago); Matthijs R. Wildenbeest (Kelley School of Business, Indiana University) |
| Abstract: | Using a large data set on consumers' web browsing and purchasing behavior we contrast various classical search models. We find that the benchmark model of sequential search with a known distributions of prices can be rejected based on the recall patterns we observe in the data. Moreover, we show that even if consumers are initially unaware of the price distribution and have to learn the price distribution, observed search behavior for given consumers over time is more consistent with non-sequential search than sequential search with learning. Our findings suggest non-sequential search provides a more accurate description of observed consumer search behavior. We then utilize the non-sequential search model to estimate the price elasticities and markups of online book retailers. |
| Keywords: | search costs, sequential search, fixed-sample search, non-sequential search, online browsing, online book industry, consumer search |
| JEL: | L80 L81 D80 D83 L10 L11 |
| Date: | 2009–08 |
| URL: | http://d.repec.org/n?u=RePEc:net:wpaper:0923&r=ict |
| By: | Anindya Ghose (Stern School of Business, NYU); Sang Pil Han (Stern School of Business, NYU) |
| Abstract: | Consumer adoption and usage of mobile communication and multimedia content services has been growing steadily over the past few years in many countries around the world. In this paper, we develop and estimate a structural model of user behavior and learning with regard to content generation and usage activities in mobile digital media environments. Users learn about two different categories of content: content from regular Internet social networking and community (SNC) sites and that from mobile portal sites. Then they can choose to engage in the creation (uploading) and consumption (downloading) of multi-media content from these two categories of websites. In our context, users have two sources of learning about content quality: (i) direct experience through their own content creation and usage behavior and (ii) indirect experience through word-of-mouth such as the content creation and usage behavior of their social network neighbors. Our model seeks to explicitly explain how direct and indirect experiences from social interactions influence the content creation and usage behavior of users over time. We estimate this model using a unique dataset of consumers mobile media content creation and usage behavior over a 3-month time period. Our estimates suggest that when it comes to user learning from direct experience, the content that is downloaded from mobile portals has the highest level of quality. In contrast, content that is downloaded by users from SNC websites has the lowest level of quality. Besides, the order of magnitude of signal accuracy for each content type from the direct experience is consistent with the order of true quality level. This finding implies that in the context of mobile media users make content choices based on their perception of differences in both content quality level and content quality variation. Further we find that signals about the quality of content from direct experience are more accurate than signals from indirect experiences. Potential implications for mobile phone operators and advertisers are discussed. |
| Keywords: | structural modeling, mobile media, mobile portals, Internet websites, uploading content, downloading content, dynamic programming, simulated maximum likelihood estimation |
| JEL: | C40 D12 D83 L96 |
| Date: | 2009–10 |
| URL: | http://d.repec.org/n?u=RePEc:net:wpaper:0924&r=ict |
| By: | Heski Bar-Isaac (Stern School of Business, NYU); Guillermo Caruana (CEMFI); Vicente Cuñat (London School of Economics) |
| Abstract: | The Internet has made consumer search much easier with consequences for competition, industry structure and product offerings. We explore these consequences in a rich but tractable model that allows for strategic design choices. We find a polarized market structure, where some firms choose designs aiming for broad-based audiences, while others target narrow niches. Such an industry structure can arise even when all firms and consumers are ex-ante identical. We perform comparative statics and show the effect of a fall in search costs on the designs, market shares, prices, and profits of different firms. In particular, a fall in search costs, through the effect on product designs, can lead to higher industry prices and profits. In characterizing sales distributions, our analysis is related to discussions of how the Internet has led to the prevalence of niche goods and the long tail and superstar phenomena. |
| Date: | 2009–09 |
| URL: | http://d.repec.org/n?u=RePEc:net:wpaper:0917&r=ict |
| By: | Jianqing Chen (Haskayne School of Business, The University of Calgary); Hong Xu (; McCombs School of Business, The University of Texas at Austin); Andrew B. Whinston (; McCombs School of Business, The University of Texas at Austin) |
| Abstract: | Online communities provide a social sphere for people to share information and knowledge. While information sharing is becoming a ubiquitous online phenomenon, how to ensure information quality or induce quality content, however, remains a challenge due to the anonymity of commentators. This paper introduces moderation into reputation systems. We show that moderation directly impacts strategic commentators incentive to generate useful information, and moderation is generally desirable to improve information quality. Interestingly, we find that when being moderated with different probabilities based on their reputations, commentators may display a pattern of reputation oscillation, in which they generate useful content to build up high reputation and then exploit their reputation. As a result, the expected performance from high-reputation commentators can be inferior to that from low-reputation ones (reversed reputation). We then investigate the optimal moderation resource allocation, and conclude that the seemingly abnormal reversed reputation could arise as an optimal result. The paper concludes with a discussion of the development of a scientific moderation system with application to academic publishing. |
| Keywords: | moderation, reputation, online community, knowledge management |
| JEL: | K21 L41 L42 L12 L86 L63 |
| Date: | 2009–08 |
| URL: | http://d.repec.org/n?u=RePEc:net:wpaper:0911&r=ict |
| By: | Hong Guo (Mendoza College of Business, University of Notre Dame); Subhajyoti Bandyopadhyay (Warrington College of Business Administration, University of Florida); Hsing K. Cheng (Warrington College of Business Administration, University of Florida) |
| Abstract: | The net neutrality debate has brought out economic rationale for and against a variety of proposals of the broadband service providers to differentiate between different classes of users. Broadband users are characterized by the differing amounts of content they request online, as well as their valuation for such content. A broadband service provider (BSP) has two potential instruments for user discrimination – price discrimination and traffic prioritization (or degradation). We model six different pricing and prioritization options that cover many of the strategies that actual BSPs have adopted in the marketplace. By comparing these options, we find that imposing net neutrality increases the BSP?s profit if the BSP price discriminates different consumer groups. If net neutrality is not imposed, however, the BSP might still prefer a net neutrality outcome depending on the various parameter values. These and other results will be useful both for the broadband service providers as they mull over the introduction of the different pricing strategies and for policymakers who are dealing with the net neutrality issue. |
| Keywords: | Net neutrality, Internet access pricing, congestion pricing, traffic prioritization, public policy, market regulation |
| JEL: | R4 D4 L5 L86 |
| Date: | 2009–08 |
| URL: | http://d.repec.org/n?u=RePEc:net:wpaper:0913&r=ict |