The blocking effect of preconceived bias
Introduction
Why are Apple Stores so successful? There are a number of reasons for their success, but clearly Ron Johnson's supposition is that the experiences that these environments offer for potential and existing customers represent an important part of the equation. In many ways, the Apple Store experience is designed to prime a customer to develop a favorable attitude about not only the software and technology in the store, but the environment and brand associated with the product. In other words, the store experience is designed to “bias” the customer in favor of the Apple brand and products. This type of bias in individual preference is also seen in non-tangible technology goods including experience goods such as Internet browsers (Internet Explorer versus Firefox) or even in credence goods (such as IPad repair shops, auto mechanics, or diet plans) [1]. This is important because whether we are discussing a choice between two different brands of cell phones, operating systems, or ERP systems, decision makers will carry into the decision-making process preexisting knowledge and biases that influence their attitudes and purchasing behaviors. As a result, products that have similar or even superior features might be ignored because the existing biases preclude the decision maker from evaluating all of the products equally. Of course, this begs the question of why some individuals will reflexively count out a particular software product and, perhaps more importantly, what the nature of biases and experiences are that influence an individual to block out the full evaluation of other alternatives. For software and technology vendors, brand-related biases are significant and, as suggested by the Apple Store experience, an important question is whether and how biases can be overcome through usage experience or persuasion.
Bias [2] and blocking [3] have each been examined to account for the phenomenon of cognitively configuring or reshaping information about products, and hence attitudes pertaining to products or services [4,5]. Specifically, research on bias has shown that if consumers are presented with a product brand along with quality information (positive or negative) regarding that brand, later introduction of attributes pertaining to the product itself are altered by the earlier brand quality information [5]. We argue that individual actions based on these biases are one type of blocking, which occurs when the subject actually blocks subsequent information based on a bias in favor of (or against) the product.1 With regard to information systems adoption decisions, this biased-blocking may affect the level of acceptance of a particular alternative by certain individuals. Biased-blocking may also help to explain why certain individuals accept a particular technology based solely on the technology brand. Information systems acceptance has classically been seen as a rational process [6,7], with later studies exploring other determinants outside of the rational domain [8,9], but no studies have explored the influence of biased-blocking in this decision-making process. As a result, a better understanding of the relationship between biases, the blocking process, and resultant behavioral intentions would provide managers and technology marketers with information to assist in designing, building, and deploying information technologies.
Previous research in technology consumption/adoption has investigated some of these non-traditional processes that affect information systems adoption. Yang and Yoo found “considerable influence” of affective attitude on usage intention and called for more attention to the construct [10]. More recently Djamasbi et al. found that positive mood is a significant predictor of technology acceptance [11], while Luo found that positive affective attitude also significantly impacted behavioral intent [12]. Clearly, this work on affect indicates that there are other factors in play beyond the traditional acceptance model, and marketing literature leads us to believe that information bias and information blocking may also have a significant impact on our understanding of technology adopters' decision mechanisms. Since bias is often linked to brand perceptions, we also further extend the IS brand literature [13,14] by investigating this information bias as it pertains to brand and its impact on technology usage intentions.
The purpose of our research is to examine the relationship between bias and blocking in the context of information technology adoption decisions. To examine these issues, we first propose a theoretical framework incorporating the concepts of bias and blocking. The review leading to this model will provide a basis for understanding not only the bias and blocking processes individually, but it will also provide a conceptual framework for linking these two constructs into a process we call biased-blocking. In doing so, we discuss situational conditions that enable biased-blocking to occur as well as define the valence direction of the effects. Additionally, we examine this phenomenon under varying informational assessment scenarios that are defined by the type of exposure that the subject is given to the technology. To evaluate these questions, we use an experimental study to examine how bias and blocking work together (i.e. biased-blocking) to influence intention decisions when subjects are presented with a novel product through either a “hands on” or vicarious-only exposure to the product. The paper concludes with a discussion of the findings, implications for theory and practice, and suggestions for future research.
Section snippets
Background
Much of what we know about the processes of bias and blocking in relation to product adoption decision-making comes from research in marketing. For example, researchers have explored how both of these processes affect satisfaction within consumer behavior (see [15] for an extensive review of this literature). This literature is relevant to the study of adoption of information systems because the consumer decision-making process for a variety of products parallels that of the processes used to
Data collection
Subjects for this research were solicited from three sections of a core undergraduate business course at a large Midwestern university. Subjects were evenly represented from all majors in the college. The course instructor offered students extra credit for participating in the research. The course instructor was the same in all course sections and had not discussed the stimulus – virtual world technologies – during lectures. A virtual world technology was selected as the focal research artifact
Results
268 subjects participated in the study; 67 were removed due to prior exposure to Second Life leaving 201 observations for analysis.10
Discussion
This research provides a number of important contributions. First, the research provides a theoretical model linking the separate constructs of bias and blocking into a combined concept of biased-blocking. Research shows that the independent concepts of bias and blocking both affect consumer attitudes toward product(s)/services(s) and buying decisions related thereto [4,5,46]. This biased-blocking effect can have a substantial impact on consumer buying and use decisions, as it has the potential
Implications and future work
This research demonstrates that bias can have a blocking impact on subsequent informational experience and the results demonstrate that the effects of experience with a technology can be fully blocked by preconceived bias held by the individual. The research provides promise for better understanding individual usage intention in the context of biases toward a particular technology.
This has important ramifications with regard to the introduction of new technologies and significant upgrades to
Conclusion
The purpose of our research is to examine whether biases can be overcome through usage experience or persuasion. Our research is premised on the notion that when a decision maker is presented with information about a product (either positive or negative) that biases his or her attitudes, subsequent information will be blocked. The result is that the evaluation made of a product will be strongly influenced by the initial bias and subsequent information will have a minimal effect. To examine
Andy Luse is an assistant professor of management science and information systems in the Spears School of Business at Oklahoma State University. He received his Ph.D.s from Iowa State University. His research interests include security, technology adoption, and research methodology. He has previously published in Journal of Management Information Systems, Computers in Human Behavior, IEEE Transactions on Visualization and Computer Graphics, among other outlets.
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Andy Luse is an assistant professor of management science and information systems in the Spears School of Business at Oklahoma State University. He received his Ph.D.s from Iowa State University. His research interests include security, technology adoption, and research methodology. He has previously published in Journal of Management Information Systems, Computers in Human Behavior, IEEE Transactions on Visualization and Computer Graphics, among other outlets.
Anthony M. Townsend is an Associate Professor of MIS at Iowa State University. He received his M.S. and Ph.D. from Virginia Polytechnic Institute and State University and conducts research in collaborative systems and virtual teams. He has published in MIS Quarterly, Information Systems Research, and the Communications of the ACM among other venues. He is currently conducting research in collaborative systems designed to enhance a variety of organizational processes, including security.
Brian E. Mennecke is an Associate Professor of Management Information Systems in the College of Business at Iowa State University. His research interests include collaboration and collaborative systems, social media and virtual worlds, embodiment and perceptions of space, security systems and privacy, and geographic information and spatial technologies. He has previously published a book on mobile commerce and articles in books as well as academic and practitioner journals such as Management Information Systems Quarterly, the Decision Sciences Journal, the International Journal of Human-Computer Studies, Computers in Human Behavior, the Journal of Management Information Systems, the Journal of Information Systems, Organizational Behavior and Human Decision Processing, the International Journal of Human Computer Studies, the Journal of Information Privacy and Security, and the Journal of Digital Forensics, Security & Law.