Amazon has recently added a feature to the iOS version of the Amazon shopping app, called AR View (i.e., Augmented Reality View), which allows prospective buyers to view and to interact with virtual representations of products within their real-world environments, via the iPhone's camera. AR View engages customers just prior to confirming a purchase. If successful, such app features will sway customers who otherwise may be reluctant to make purchases. Amazon reasons that customers will value the AR View simulation, especially if they wish to visualize a product positioned in their personal environment (e.g., their home or office). Prior literature identifies comparative, characteristic-based product categories that include search vs experience, geometric vs material and functional vs expressive. However, due to the introduction of AR into product-purchasing contexts, there is a need to now classify product type in a new way: along a continuum of position-relevance. A product has high position-relevance when a customer exhibits sensitivity regarding its relative location within an environment. For example, a shopper that employs AR View to virtually place a sofa into a room in their house, would want to evaluate the suitability of its position within the area. Hence, a product has low position-relevance when a customer exhibits little or no sensitivity regarding its relative location. The aim of this research is to determine the following: 1. Is using AR more effective than not using AR in influencing purchase decisions, using the Amazon shopping app? 2. If the answer is yes, is the positionrelevance of the products the reason? This study will develop, perform, and analyze the results of an experiment that examines the influence of the AR features and the position-relevance of products on customer decisions to purchase. The research questions are, in a prominent mobile retail app: 1. do AR features influence customer experience (telepresence, flow)? 2. Do interactions between AR features and the position-relevance of products influence customer experience? 3. Does customer experience influence purchase intention? We are developing a theoretical and testable model, and experimental and survey scenarios to test the model. Expected contributions will include: 1. Development of a testable model describing AR features, interactions of product position-relevance with these features, customer AR experience, and purchase intention outcomes, 2. Increases to knowledge and understanding of AR, AR features, and the effect of these characteristics on purchase intention, 3. Increases to knowledge and understanding of AR in mobile retail applications and the relationship of these apps to revenue and profitability. Limitations include: 1. Because AR research is still in the early stages, this research is developmental, centering on developing a framework for the use of AR in a mobile retail context. 2. Consequently, the initial research methodology is developmental, subject to change with increased knowledge and understanding. [ABSTRACT FROM AUTHOR]