The Augmentation Quality Scale (AQS) measures how consumers evaluate the technical goodness or badness of the integration of virtual elements into their real-world environment during an AR marketing experience. Developed through grounded qualitative work across two studies followed by two rounds of quantitative validation (total N = 670 across Studies 3 and 4), the scale conceptualises augmentation quality as a second-order factor with three first-order components. Embedding quality captures perceived realism of contextual integration — whether the virtual object fits naturally within the physical environment in terms of scale, positioning, and blending. Interaction quality reflects responsiveness — whether the virtual object reacts to user movements smoothly and in real time. Design quality captures the visual fidelity of the object itself — its level of detail, overall appearance, and realism from multiple perspectives. All three first-order factors load strongly onto the second-order augmentation quality factor, reflecting their status as complementary facets of a single quality experience. Higher augmentation quality predicts local presence, which in turn mediates effects on utilitarian and hedonic outcomes, purchase intention, and actual behavioural choices.
7-point Likert (1 = I do not agree, 7 = I fully agree); items randomised in administration
Embedding Quality (3 items). CR = .86; AVE = .67 (Study 4). Assesses perceived realism of the virtual object's contextual integration into the physical environment.
Interaction Quality (3 items). CR = .84; AVE = .63 (Study 4). Assesses perceived responsiveness and smoothness of the virtual object's reaction to user interaction.
Design Quality (3 items). CR = .87; AVE = .69 (Study 4). Assesses perceived visual fidelity and aesthetic realism of the virtual object across perspectives.
Full scale items shown. Always cite the original source when using this scale in research.
Scale wording uses generic 'virtual object' framing applicable across AR contexts; for specific product studies, items are adapted to the product (e.g., 'sunglasses' in Study 5 — full adapted wording in Appendix C of the source paper). The second-order structure was preferred over a four-factor or one-factor solution on both statistical and conceptual grounds. High design quality alone does not compensate for poor interaction or embedding quality, consistent with the second-order specification. Discriminant validity from a single first-order factor was confirmed across all studies (one-factor fit substantially worse: CFI = .76 vs .98 in Study 4). Companion scale: Local Presence in AR Scale (ID 1897, same paper). A related Shift Risk Management scale adapted from Kim (2019) in Fehl et al. (2026) is held pending independent reliability reporting.
Schein, K. E., Rauschnabel, P. A., Praxmarer-Carus, S., & Babin, B. J. (2025). Unpacking augmentation quality and local presence: Factors that drive effective augmented reality marketing. Journal of the Academy of Marketing Science, 54, 49–69. https://doi.org/10.1007/s11747-025-01108-2
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