Trust Change in Information Technology Products

ABSTRACT

We examine why trust change occurs when potential users first encounter news about a specific technology. We propose personal perceptions and three cognitive outcomes—attention, sensemaking, and threshold—affect trust change in educated young adults surveyed regarding a technology product. We find the outcomes of attention, sensemaking, and threshold positively affect trust change, while most hypothesized personal perceptions of the technology (e.g., reputation) do not predict trust change. For research, this implies scholars should focus more on cognitive outcomes of mental news brief processing than on technology perceptions. Our results also imply that research should examine other key dependent variables the way we studied trust change (e.g., “intention-to-use change”—to produce a more dynamic picture of how people adopt a technology). For practice, our data imply that tech companies can counter initial bad news about a technology by quickly providing strong positive news items to repair trust in that technology.

KEYWORDS:

• Trust change
• trust in technology
• initial trust
• trust repair
• cognitive attention
• sensemaking
• threshold; event; fragile; robust

Supplemental Material

Supplemental data for this article can be accessed on the publisher’s website

Notes

1. Similar trust changes were experienced regarding autonomous vehicles when news media reported traffic accidents and deaths (e.g., http://www.interaksyon.com/motoring/2018/03/23/122999/self-driving-car-industry-confronts-trust-issues-after-uber-crash/; https://www.fool.com/investing/2018/09/28/the-case-against-driverless-cars.aspx). Our study examines trust in an autonomous vehicle (Google Driverless Car).

2. We only delve briefly into how trust in a technology differs from trust in a person. This is because this has already been explained in works like [64]. Most differences pertain to trusting beliefs, which lies outside our scope.

3. This paper does not actually study the mental mechanisms per se. However, it proposes a set of three mental mechanisms that take place prior to trust change and measures indicators that represent the indicator or outcome of each mental mechanism. We use the term “mental mechanism” instead of “cognitive process” first, because the term “process” often implies something that occurs over a long time period, which we do not study in this paper. Instead we examine a very short timeframe in which people use these mental mechanisms to make rapid trust judgments. Second, we use “mental” instead of “cognitive” because “mental” is more inclusive of the overall thought process than is “cognitive.” The broad term “mental mechanisms” is also used in such domains as psychology [95] and neuroscience [3].

4. This statement basically equates attribution with sensemaking, which we use as a construct label later.

5. We thank an anonymous reviewer for these insights.

Additional information

Funding

We acknowledge the following funding sources. D.H. McKnight and B. Pentland acknowledge the Accounting and Information Systems Department and the Eli Broad College of Business for their funding support of this research.

Notes on contributors

D. Harrison McKnight

D. Harrison McKnight ([email protected]; corresponding author) is a Professor Emeritus at Michigan State University. He received a Ph.D. from the University of Minnesota’s Carlson School of Management. His research interests include trust in technology products, initial trust, the humanness of technology, the meanings of trust, and trust change. He has published in Information Systems Research, Journal of Management Information Systems, MIS Quarterly, Academy of Management Review, and others.

Peng Liu

Peng Liu ([email protected]) is an Associate Professor in the Department of Information Systems and Decision Sciences at California State University, Fullerton. His research interests include organizational routines and capabilities, board-level IT governance, and trust in technologies. He has published in MIS Quarterly, Journal of Management Studies, Information Systems Management, and others.

Brian T. Pentland

Brian T. Pentland ([email protected]) is the Main Street Capital Partners Endowed Professor in the Department of Accounting and Information Systems at Michigan State University. His research is focused on the analysis of repetitive patterns of action, such as organizational routines. His work has appeared in Academy of Management Review; Administrative Science Quarterly, Journal of Management Studies, Management Science, MIS Quarterly, Organization Science, and elsewhere.