Cell Phone Demand and Consumer Learning - An Empirical Analysis

A structural model is used in this paper to analyze the demand and learning behavior in cell phone market. We assume that the cell phone consumption can be divided into a high-value part and a low-value part. The consumers are assumed to be uncertain about the exogenous shock of the need for high-value usage and also their preferences over the low-value usage. Meanwhile, we assume that the consumers' knowledge improves over time. As a result, the match between their plan choice and consumption pattern becomes better. Such a learning behavior is supported by the data set. Bayesian updating is used to represent the learning. The estimates of the parameters are obtained and compared to the benchmarks from previous research

Interest-Based Self-Organizing Peer-to-Peer Networks: A Club Economics Approach

Improving the information retrieval (IR) performance of peer-to-peer networks is an important and challenging problem. Recently, the computer science literature has attempted to address this problem by improving IR search algorithms. However, in peer-to-peer networks, IR performance is determined by both technology and user behavior, and very little attention has been paid in the literature to improving IR performance through incentives to change user behavior. We address this gap by combining the club goods economics literature and the IR literature to propose a next generation file sharing architecture. Using the popular Gnutella 0.6 architecture as context, we conceptualize a Gnutella ultrapeer and its local network of leaf nodes as a "club" (in economic terms). We specify an information retrieval-based utility model for a peer to determine which clubs to join, for a club to manage its membership, and for a club to determine to which other clubs they should connect. We simulate the performance of our model using a unique real-world dataset collected from the Gnutella 0.6 network. These simulations show that our club model accomplishes both performance goals. First, peers are self-organized into communities of interest - in our club model peers are 85% more likely to be able to obtain content from their local club than they are in the current Gnutella 0.6 architecture. Second, peers have increased incentives to share content - our model shows that peers who share can increase their recall performance by nearly five times over the performance offered to free-riders. We also show that the benefits provided by our club model outweigh the added protocol overhead imposed on the network for the most valuable peers

What’s It To You? A Survey of Online Privacy Concerns and Risks

Finding information about privacy practices can be difficult: privacy policies often do not present this information in an accessible way. People typically do not know how or for what purpose their personal information, gathered online, will be used. When asked, people frequently express concerns about their privacy, but their behavior often does not reflect their concerns. We conducted an online survey to examine participants' online privacy concerns, focusing especially on the online shopping context. We asked participants about several scenarios related to the privacy of personal information. We found that Privacy Finder, a P3Penhanced search engine, provides information that addresses the scenarios that participants believe are most likely to occur. We also asked participants about a wide range of items for purchase online to evaluate which types of items are more likely to raise privacy concerns

Network Effects and Switching Costs In the Market for Routers and Switches

This research examines the impact of switching costs on vendor choice in the market for routers and switches. We show that despite the use of open standards which attempt to enhance interoperabilities for equipments from different vendors, vendors in this market are able to maintain high switching costs. Because routers and switches are networked goods, switching costs may arise from prior investments made at the same establishment and/or at other establishments within the same firm. We study how the introduction of switches into the LAN market affected vendor choice in routers. In particular, we provide evidence of significant cross-product switching costs and sizeable shopping costs when buyers purchase routers and switches simultaneously. However, we also show that the introduction of switches may have temporarily reduced switching costs for router buyers investing in switches

Cell Phone Demand and Consumer Learning - An Empirical Analysis

A structural model is used in this paper to analyze the demand and learning behavior in cell phone market. We assume that the cell phone consumption can be divided into a high-value part and a low-value part. The consumers are assumed to be uncertain about the exogenous shock of the need for high-value usage and also their preferences over the low-value usage. Meanwhile, we assume that the consumers' knowledge improves over time. As a result, the match between their plan choice and consumption pattern becomes better. Such a learning behavior is supported by the data set. Bayesian updating is used to represent the learning. The estimates of the parameters are obtained and compared to the benchmarks from previous research

Interest-Based Self-Organizing Peer-to-Peer Networks: A Club Economics Approach

Improving the information retrieval (IR) performance of peer-to-peer networks is an important and challenging problem. Recently, the computer science literature has attempted to address this problem by improving IR search algorithms. However, in peer-to-peer networks, IR performance is determined by both technology and user behavior, and very little attention has been paid in the literature to improving IR performance through incentives to change user behavior. We address this gap by combining the club goods economics literature and the IR literature to propose a next generation file sharing architecture. Using the popular Gnutella 0.6 architecture as context, we conceptualize a Gnutella ultrapeer and its local network of leaf nodes as a "club" (in economic terms). We specify an information retrieval-based utility model for a peer to determine which clubs to join, for a club to manage its membership, and for a club to determine to which other clubs they should connect. We simulate the performance of our model using a unique real-world dataset collected from the Gnutella 0.6 network. These simulations show that our club model accomplishes both performance goals. First, peers are self-organized into communities of interest - in our club model peers are 85% more likely to be able to obtain content from their local club than they are in the current Gnutella 0.6 architecture. Second, peers have increased incentives to share content - our model shows that peers who share can increase their recall performance by nearly five times over the performance offered to free-riders. We also show that the benefits provided by our club model outweigh the added protocol overhead imposed on the network for the most valuable peers

Surtrac for the People: Upgrading the Surtrac Pittsburgh Deployment to Incorporate Pedestrian Friendly Extensions and Remote Monitoring Advances

With research funding from the Traffic21 Institute\u2019s Mobility21 University Transportation Center Program, Dr. Stephen Smith, Director of the Intelligent Coordination and Logistics Laboratory at Carnegie Mellon University, developed the Scalable Urban Traffic Control (Surtrac), the world\u2019s first decentralized smart adaptive traffic signal system. This system significantly improves traffic throughput, trip delays and pollution along congested roads controlled by traffic lights. The system applies artificial intelligence to traffic signals equipped with cameras or radars adapting in realtime to dynamic traffic patterns of complex urban grids, experienced in neighborhoods like East Liberty in the City of Pittsburgh. Dr. Smith worked with the City of Pittsburgh, Southwestern Pennsylvania Commission (regional MPO), Pennsylvania Department of Transportation (PennDOT), University of Pittsburgh Medical Center, and neighborhood groups on a pilot deployment of Surtrac, which resulted in a 40% reduction in vehicle wait time and a 20% reduction in emissions. The original deployment of nine intersections in 2012 has expanded to 50 intersections and is now funded by the U.S. Department of Transportation (USDOT)\u2019s Advanced Transportation Congestion Management Technology Deployment (ATCMTD), and PennDOT grants for an additional 150 intersections in Pittsburgh. With two patents from the UTC research, Dr. Smith\u2019s Pittsburgh-based company Rapid Flow Technologies has created eight jobs and currently has commercial deployments in Atlanta, GA; Portland, ME and Needham and Quincy MA

An Empirical Analysis of Cellular Voice and Data services

Cellular telephony and associated data services has been a major social phenomena for well over a decade now. It has changed the way - in some countries more than others - in which people communicate. In many countries in Northern Europe and Asia, its penetration rates are very high and in others less so but in all cases it has engendered change at multiple levels - socially as noted and in terms of market structure and competition with the established Incumbent Local Exchange and Inter Exchange service providers. However, there has been little work published in the academic literature on user consumption of cellular voice and data services. This has been due to the unavailability of longitudinal data at the individual user level on their consumption of voice and data services. We have such data from a large cellular service provider in Asia. Demand for voice and data services is influenced by the tariffs or 'service plans' offered by firms. In our analysis we empirically estimate the drivers for cellular services how demographic and plan characteristics affect the user choices. We first provide a theoretical model and then provide insight into consumption patterns over a one year period of cellular voice and data services and relate it to service plan design

Innovative Approaches to Educate Our Future Transportation Workforce

In April 2012, the Council of University Transportation Centers sponsored a National Transportation Workforce Summit to address the dynamic needs of the future transportation workforce. One stated objective was to promote greater visibility for transportation careers in industry, government, and academia. Since then, Carnegie Mellon university\u2019s (CMU) Technologies for Safe and Efficient Transportation (T-SET), a U.S. Department of Transportation funded University Transportation Center (UTC), has developed a strategic approach. The approach includes exposing a multidisciplinary group of students to the world of transportation, demonstrating how their skills can be applied by providing real world transportation research projects, creating job opportunities by linking students with real world transportation partners, and exposing industry to innovative transportation research