Increasing amounts of data are being produced and consumed on a daily basis. Every mouse movement and click on a website can be analyzed to discover usage patterns and cognitive load (Jenkins et al., 2014), companies mine purchase histories to discover customer shopping patterns (Brin et al., 1997) and historical business transaction information can be used to improve business processes (Ghattas et al., 2014). Using sophisticated algorithms, data can be turned into information that helps guide marketers, policy makers, business managers, and other decision-makers. However, history has shown that increases in the amount and quality of information do not necessarily lead to better decision outcomes (Dawes et al., 1989). Human decision-makers may fail to understand the information, ignore it, or simply not believe it. Methods for effectively conveying information to humans must be studied so that the full value of information systems can be realized. This dissertation uses three studies to explain the factors that make technology persuasive. In the first study, attitudes toward technology measure how beliefs about technology influence the way people process information. Ordering effects are also examined to determine how people view information from decision support systems, and to find the optimal time to present information to decision-makers. In the second study, the persuasive power of text and audio modalities are compared. Additionally, the loss aversion bias is investigated to determine the utility of leveraging this cognitive bias in a technology context. In the third study, Protection Motivation Theory (Rogers, 1983) is used to extend the loss aversion model from study two. The study also investigates how message vividness and user participation through software personalization influence attitudes and behavior. Together, these experiments extend existing theoretical frameworks while giving actionable guidance to information systems practitioners. The studies demonstrate the importance of understanding cognitive biases, attitudes toward technology, and message delivery in a decision support scenario. These investigations are the first step in creating a more comprehensive model of factors that influence the persuasive power of technology.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/556848 |
| Date | January 2015 |
| Creators | Marquardson, James |
| Contributors | Nunamaker, Jay F., Jr., Valacich, Joseph S., Brown, Susan A., Nunamaker, Jay F., Jr. |
| Publisher | The University of Arizona. |
| Source Sets | University of Arizona |
| Language | en_US |
| Detected Language | English |
| Type | text, Electronic Dissertation |
| Rights | Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. |
Page generated in 0.0017 seconds