Digital Borders, Location Recognition, and Experience Attribution within a Digital Geography

During an online session, a user may visit a number of websites, often following hyperlinks from one website to the next or using a search results page to find and visit pages of interest. In doing so, the user can lose track of which sites were visited and which were helpful in meeting the objective. Thus, sites that may have provided value to the user may not receive expected positive effects such as loyalty and intention to return. It is thus crucial to understand if and how an individual website is perceived by users within the context of multi-website online sessions—particularly in predicting desired outcomes, such as user loyalty, trust, brand image, and revisit intentions. To address this problem, we conceptualize the Web as a geography traversed by users who cross digital borders as they move from one website location to another. We introduce the concept of border strength, or the degree to which digital media artifacts mark a transition to a website, and propose a positive effect of border strength on users’ recognition of their locations. We then consider users’ attribution of credit for assistance in successfully completing an online task to those websites and their owners that supported the task. This attribution is a function of border strength and location recognition. We test these hypotheses using experimental data, which show that, indeed, some websites go unrecognized and that stronger borders increase users’ recognition of having visited a website and users’ credit attribution for their experience to the site. Our findings demonstrate the usefulness of the geography metaphor, suggest the need to further study dynamics regarding individual sites within the context of multi-site sessions and show the usefulness of erecting stronger borders to mark the entry into digital locations.

• 저널Journal of Management Information Systems · 36(2) · 418–449
• 토픽Digital Marketing and Social Media · Sociology and Political Science
• DOI10.1080/07421222.2019.1598690
• 저자Brian Kimball Dunn, Narayan Ramasubbu, Dennis F. Galletta, Paul Benjamin Lowry