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  • Thumbnail for Dynamic pricing of energy and the smartgrid in Colorado
    Dynamic pricing of energy and the smartgrid in Colorado by Osmond, Alex

    Pricing of electricity has caused a disconnect between the consumer and producers. Current methods for pricing electricity are non-inventive and do not reflect the actual costs of production. If producers were capable of monitoring electricity use by the end user, they could potentially assess greater fees associated with consumption during specified periods. To gain access to critical usage information, producers are testing out the theory of a smartgrid. This proposed smartgrid is a system of communicating, actuating and reporting devices that give system operators the capability to observe consumption on a scale unseen before. Price signals from new dynamic pricing plans motivate consumers to change their consumption habits. Producer’s main goal is to slow the growth and intensity of daily and annual “peaks” in energy consumption. By helping to lower peak, consumers have the potential to encounter lower energy bills, more accessible alternatives to carbon based energy and potentially, profit from the sale of electricity back to the grid through smartgrid technologies. This paper uses information from the SmartGridCity project by Xcel Energy in Boulder, Colorado. Raw data from multiple pilot programs in Denver, Colorado, and consumption data from Colorado Springs Utilities is also used. A smartgrid enabled society with access to dynamic electricity rates shows to be a step forward in the solution making processes surrounding the use of energy.

  • Thumbnail for The effect of various consumer characteristics on purchasing behaviors online
    The effect of various consumer characteristics on purchasing behaviors online by Schornack, Amy Nicole

    The purpose of this paper is to determine which factors will affect consumer purchasing behaviors online. While previous research has been conducted in this field, the present study aims to expand upon those papers and will include factors that have never before been analyzed. The eight determinants this paper focuses on include demographics, culture, employment information, allocation of money, risky behaviors, trust in others, place of residency, and time stress. It is hypothesized that each of these determinants will be significantly related to online purchasing behavior. Data was collected by the General Social Survey (GSS) in the year 2000 and was utilized to perform an Ordinary Least Squares regression. This paper hopes to provide insight that will not only increase the success rate of online retailers but also information that will lead to a more positive online experience for consumers.