Kurt DeMaagd

The use of public computing facilities by library patrons: demography, motivations, and barriers

Abstract Public libraries play an important part in the development of a community. Today, they are seen as more than store houses of books; they are also responsible for the dissemination of online, and offline information. Public access computers are becoming increasingly popular as more and more people understand the need for internet access. Using a series of surveys conducted in 12 libraries across the state of Michigan, the current study is a step towards understanding why the computing facilities are widely used, and what are the motivations behind their use. In addition, barriers and other factors that hinder usage are also discussed. The findings from this study will help policy makers and library administrators evaluate the current allocation of scarce resources, help them promote greater use of the librarys resources, and guide their future course of action. The study is conducted as part of a federally funded public computing center grant.

Modeling the dynamic interactions of agents in the provision of network infrastructure

Although next-generation information network infrastructure is prerequisite for continued economic growth, the United States is losing ground in important areas relative to peer countries. Businesses and regulators have grown concerned that the U.S. lacks the correct regulatory and business incentives to upgrade the existing network. Due to the complex and dynamic nature of the interdependencies in the ICT value network, traditional methods of public policy and management analysis have proven inadequate to fully understand the issues and possible solutions. This paper discusses a novel Genetic Programming (GP) approach to the problem. Although only a first step towards addressing the problem, the GP discovered several interesting results stemming from the complex interactions. For example, telecommunications companies would actually be hurt by the option to charge discriminatory prices but application providers would benefit.

A quantitative explanation of governance in an online peer-production community

In this paper, we examine how user ratings of content produced for an online community are taken into account by administrators when they decide whether to delete content. Incorporating about 10 years of server data from the online peer-production community Everything2, we looked at how specific features of voting predicted deletion of posts. We found that not all types of voting are the same: negative voting of users was the strongest factor explaining deletion of a Write-up. Receiving a positive vote from a member with higher status decreases the chances of deletion, while receiving a positive vote from a user with neutral status has a very little effect on the deletion of content.

The Myth of Population Density and ICT Infrastructure

Mobile phones have become a significant platform for the delivery of information services in developing economies. Therefore, a sufficiently developed mobile telecommunications infrastructure is an important element in the economic development of these countries. This paper examines the factors that affect the quality of the mobile phone infrastructure in a country. One classic argument for limited infrastructure is a low population density. In theory, fewer people in a region means fewer customers to cover the fixed costs of the infrastructure. This paper tests the link between population density and mobile infrastructure. The results contradict the classic argument. The paper then argues that the challenge actually lies in the financial markets. If the financial markets demand a higher rate of return from the infrastructure, then the telecommunications firms will invest less in the infrastructure.

Using IT to Open Previously Unprofitable Markets

It is now widely accepted that Information Technology can make firms more efficient and has created a host of new markets. Yet IT could also open up previously unprofitable markets. In this paper, we look at this phenomenon. We begin with a traditional economic production model and identify when firms will not enter a market. Specifically, we focus on the problem of high fixed costs and limited market size. Then we introduce technology into the model to identify cases where IT could make it profitable to enter the market. Although IT doesn’t always translate into potential profitability, we find that IT may help firms enter previously unprofitable markets when compared to non-IT enabled firms.

Investigating the Value of Information and Computational Capabilities by Applying Genetic Programming to Supply Chain Management

In this paper we describe a research project centering on experiments in which game-playing evolving agents are used to investigate the value of information. Specifically, in these experiments we define populations of agents whose strategies evolve towards those that have better restocking strategies for their supply chain. The agents evolve their strategies in order to minimize costs (either for themselves or for their value chain). We describe several different experiments in which we will vary the abilities of agents both to gather and to store more information. Part of the results of this project will be related to the value of information and computational capabilities: Is it always better to have more information? If not, what are the conditions under which less information is better? The culminating experiment is one in which evolving agents compete to sell information to other evolving agents playing their roles in a supply chain.

Comparing models of IT and economic growth: An empirical investigation

Does IT help generate economic growth? Studies in developed economies say that the answer is yes. Yet, when we also consider emerging markets, the answer is less clear. Some studies find value from IT, while others fail to find any value. One possible reason for the discrepancy is the model used. We may need a new model when trying to compare the value of IT investments between both developed and developing countries. In this paper, we derive a model for analyzing IT investments at the country level. Although similar to the previous approaches, this model has one important difference: it disaggregates the historic investments in IT and current investments in IT. Furthermore, instead of relying on the perpetual inventory method to measure capital stock, we measure the current level of IT infrastructure with an index based on the ITUs Digital Access Index. This reduces a common source of measurement error. Using the new analytical model, we empirically test the model versus the traditional model. When using the traditional model, we once again fail to find a positive significant benefit from IT. When using our new model, however, we find that IT has a positive and significant effect on economic growth.

Using Genetic Programming to Search for Supply Chain Reordering Policies

The authors investigate using genetic programming as a tool for finding good heuristics for supply chain restocking strategies. In this paper they outline their method that integrates a supply chain simulation with genetic programming. The simulation is used to score the population members for the evolutionary algorithm which is, in turn, used to search for members that might perform better on the simulation. The fitness of a population member reflects its relative performance in the simulation. This paper investigates both the effectiveness of this method and the parameter settings that make it more or less effective.

Effects of Editorial Feedback in a Peer-Production Online Community

In this paper, we examine how editorial feedback for an online community is taken into consideration by users when they contribute in the future. Analyzing server data from the online peer-production game community Sploder, we looked at how editorial feedback supported future content production. We found that receiving editorial feedbacks are likely to improve the quality of the contribution and reduce the amount of spam in the post. Editorial feedback will garner more comments and visits on articles.

A Genetic Programming Approach to Network Management Regulation

Although next-generation information network infrastructure is prerequisite for continued economic growth, the United States is falling behind in this area relative to many other countries. Businesses and regulators have grown concerned that the U.S. lacks the correct regulatory and business incentives to upgrade its network. Due to the complex and dynamic nature of this problem, traditional analytic tools have proven inadequate. This paper discusses a Genetic Programming (GP) approach to the problem. Although only a first step towards addressing the problem, the GP discovered several interesting results stemming from the complex interactions. For example, telecommunications companies would actually be hurt by the option to charge discriminatory prices but application providers would benefit.