Academic journal article Informing Science: the International Journal of an Emerging Transdiscipline

Decision Confidence, Information Usefulness, and Information Seeking Intention in the Presence of Disconfirming Information

Academic journal article Informing Science: the International Journal of an Emerging Transdiscipline

Decision Confidence, Information Usefulness, and Information Seeking Intention in the Presence of Disconfirming Information

Article excerpt

Introduction

Computer aided data visualization that facilitate decision making by utilizing Decision Support Systems (DSS) have become part of what we can call the informing environment. This study builds upon the work of (Kahneman & Tversky, 1972) by addressing the burgeoning need to investigate the phenomenon of a priori beliefs as they relate to decision confidence, information usefulness, and information seeking within the context of different formats for information display. In this work, the applicable transdisciplinary information environment is composed of factors and influences that affect, enable, and limit the process of informing clients (Cohen, 2009). These visual decision-making systems allows informers (the information providers) and clients (the information receivers and decision makers) to become interconnected by creating rich data visualization to aid in the decision-making process.

Confirmation bias occurs when the client may focuses on a subset of the data visualization that confirms their preconceived notions and does not directly argue against these pre-established ideas, thus creating layers of complexity and barriers to seeking and using information. Because of this confirmation bias, clients tend to find newly presented information to be less useful, and by extension, are less likely to seek out more information. This is also the case for the clients who begin the decision-making process with a high level of confidence, indicating that they are very familiar with the context of the decision they are asked to make, and again are less likely to find new information useful, or to seek out additional information. Therefore, the question that motivates the present study is: What factors contribute to users seeking intention, and propensity to change their mind in the presence of newly presented disconfirming information?

In the spirit of the philosophy of informing science (Cohen, 2009), we believe the results of this study have transdisciplinary implications for future research, especially in the fields of information systems, human-computer interaction, communication, and the behavioral sciences. This work also provides needed research on information seeking in a decision-making, computer aided informing environment.

Information Systems (IS) scholars have expended significant effort in researching decision making and decision support systems. The quality of decisions depends largely on the quality, quantity and variety of information presented during the decision-making process (Kray & Galinsky, 2003). With the increase in use of Business Intelligence (BI), and by extension, data visualization techniques, the ability to make decisions based up on the visualization of data is increasingly important in today's technological and business climate. Because of data visualization, vast amounts of complex data can be visualized in ways that intuitively facilitate data-driven decision-making. The aim of these new data visualization techniques is to increase both the speed and effectiveness of computer-based decisions and to drive the data-driven decision-making process. There exists decades of research on the effectiveness of graphical data representation, i.e. graphs over textual information (Dickson, 1977; Mason & Mitroff, 1973). However, we have seen little inquiry focused on confirmation bias and its effect on information usefulness and seeking intention.

Psychologists also have contributed to bias research in information presentation. For example, studies that examine cognitive bias--thought patterns that inhibit individuals from interpreting information accurately--abound. (Baron, 2000) was instrumental in identifying types of cognitive bias, including hindsight, framing, self-selection, and confirmation bias. In this study, we focus on a specific cognitive bias, known as confirmation bias, because it closely relates to data visualization and the decision-making context. …

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