Local Presence in AR Scale (LP-AR)

1. Abstract

The Local Presence in AR Scale (LP-AR) is a psychometric instrument engineered to quantify the abstract perceptual consequence of high augmentation quality within augmented reality (AR) environments. Specifically, the scale assesses the subjective degree to which an individual perceives a computer-generated virtual object as genuinely real, physically situated, and authentically co-existing within their immediate, unmediated physical surroundings. Developed by Schein, Rauschnabel, Praxmarer-Carus, and Babin (2025), the LP-AR is theoretically grounded in sensory perception and spatial presence research, carving out a distinct conceptual space that departs from conventional telepresence and virtual reality (VR) spatial presence paradigms. Deriving its nomenclature from the Latin locus (meaning place or location), local presence does not capture the psychological transportation of a user away from their physical setting into an artificial world; rather, it measures the perceived arrival and integration of synthetic digital entities into the user’s localized reality.

The LP-AR is structured as a unidimensional self-report inventory comprising rigorously validated items evaluated along a multi-point Likert response format (typically a 7-point scale ranging from 1 = Strongly Disagree to 7 = Strongly Agree). Psychometric evaluations across multiple consumer and experimental samples demonstrate robust measurement properties: high internal consistency (Cronbach’s alpha coefficients routinely exceeding .88, and composite reliability metrics surpassing .90), strong convergent validity confirmed by average variance extracted (AVE) figures well above the .50 benchmark, and unambiguous discriminant validity against adjacent constructs such as immersion, spatial presence in VR, and cognitive absorption. Furthermore, confirmatory factor analyses affirm a parsimonious single-factor architecture exhibiting excellent model fit indices. Functioning as a central mediator between objective augmentation quality attributes and downstream behavioral consequences—including hedonic gratification, utilitarian informational value, brand attitudes, and transactional purchase decisions—the LP-AR provides researchers, cognitive psychologists, and human-computer interaction (HCI) engineers with an empirical tool for evaluating user experiences in spatial computing.

2. Keywords

Augmented Reality, Local Presence, LP-AR, Spatial Presence, Telepresence, Augmentation Quality, Perceptual Realism, Spatial Computing, Human-Computer Interaction, Consumer Psychology, Psychometrics, Virtual Objects

3. Authors

The Local Presence in AR Scale (LP-AR) was developed and validated by an international team of behavioral researchers and marketing scientists specializing in spatial computing, media psychology, and empirical research methodology:

• Katharina E. Schein — Institute for Digital Management and New Media, Universität der Bundeswehr München, Neubiberg, Germany. Her research specializes in emerging consumer technologies, augmented reality interface designs, and immersive digital interactions.
• Philipp A. Rauschnabel — Professor of Digital Marketing and Media Innovation at the Universität der Bundeswehr München, Neubiberg, Germany. A pioneer in AR marketing and human-computer interaction, Dr. Rauschnabel has authored foundational theoretical frameworks explaining consumer adoption of smart glasses, XR hardware, and spatial media.
• Susanne Praxmarer-Carus — Professor of Marketing, Faculty of Business Administration, Universität der Bundeswehr München, Neubiberg, Germany. Her scholarly work focuses on marketing communication, experimental design, psychometrics, and consumer behavioral decision-making.
• Barry J. Babin — Max P. Watson, Jr. Professor of Marketing and Chair of the Department of Marketing, Analysis, and Communication, Louisiana Tech University / University of Mississippi, USA. Dr. Babin is a world-renowned methodologist and marketing scholar, widely recognized for his contributions to structural equation modeling, psychometric measurement theory, and retail customer experience analysis.

Correspondence regarding the original development and empirical battery of the LP-AR is maintained primarily through the Department of Digital Marketing and Media Innovation at the Universität der Bundeswehr München.

4. Purpose

The emergence of spatial computing, mobile augmented reality engines (e.g., Apple ARKit, Google ARCore), and optical see-through smart glasses has fundamentally altered how humans interact with digital media. For decades, telepresence (the sense of being present at a remote physical location via technology) and virtual reality spatial presence (the subjective illusion of being transported into an entirely synthetic, computer-generated environment) served as the primary lenses through which immersion was conceptualized. However, augmented reality does not relocate the user’s perceptual center of gravity to an alternate realm. Instead, AR operates on an inverted spatial premise: it embeds synthetic content into the user’s immediate, unmediated physical environment.

Recognizing this fundamental epistemological and sensory divergence, Schein, Rauschnabel, Praxmarer-Carus, and Babin (2025) formulated the Local Presence in AR Scale (LP-AR) to address the lack of specialized, psychometrically sound measurement instruments dedicated exclusively to AR experiences. Prior to the LP-AR, investigators frequently adapted legacy VR or telepresence scales (such as those developed by Witmer and Singer, or Lombard and Ditton). Such adaptations introduced severe measurement error, construct contamination, and face invalidity because their items continuously referenced feelings of “being there” in an artificial world, an experience completely alien to an AR user who remains consciously anchored in their own living room, office, or retail store.

The primary purpose of the LP-AR is to measure the extent to which a user perceives a virtual, computer-generated augmentation as an authentic, physical component of their immediate surrounding environment. The scale serves critical roles across basic and applied domains:

• Psychological & Cognitive Research: Providing a validated operationalization of perceptual binding, cross-modal sensory integration, and the cognitive heuristics that govern how the human brain evaluates physical plausibility when biological sight is blended with rendered pixels.
• Consumer Behavior & Marketing Science: Elucidating the psychological bridge linking technological render parameters (e.g., environmental lighting matching, occlusion, surface tracking) to commercial outcomes, such as brand engagement, product evaluation accuracy, aesthetic appreciation, and purchase conversion.
• Human-Computer Interaction (HCI) & UI/UX Optimization: Delivering a standardized diagnostic metric for software developers and hardware manufacturers to systematically evaluate rendering algorithms, spatial audio engines, real-time shadowing pipelines, and spatial tracking fidelity across different hardware form factors.
• Clinical & Educational AR Applications: Assisting researchers in spatial medical visualization, exposure therapy, and mechanical training simulators to verify whether digital anatomical models or simulated hazards achieve sufficient physical presence to evoke genuine physiological and emotional responses.

5. Psychological Construct

The construct of Local Presence captures a specific state of perceptual and cognitive awareness: the subjective illusion that a digitally generated visual object physically exists in the user’s immediate external environment, sharing the same physical coordinates, spatial laws, and tangible reality as surrounding analog objects. The construct is rooted in sensory reality attribution, perceptual congruence, and cognitive spatial anchoring.

Distinction from Telepresence and Spatial Presence

To understand the psychological boundaries of local presence, it must be rigorously contrasted with adjacent presence constructs established over decades of media psychology:

• Telepresence: Originating from teleoperation and telecommunications research (e.g., Jonathan Steuer, 1992), telepresence reflects the mediated perception of an environment that is physically distant. The perceptual user feels connected to or operating within a remote real-world site (such as operating a robotic arm across continents or feeling connected in a live video conference). Its conceptual core is bridging geographical distance.
• Spatial Presence (in Virtual Reality): Defined as the psychological sensation of “being there” inside a synthetic world (Witmer & Singer, 1998; Lombard & Ditton, 1997). In fully immersive VR, the user’s natural physical environment is completely occluded by head-mounted displays. The cognitive system constructs a mental model of the virtual environment as the primary spatial reference frame, inducing self-location within the digital scenery.
• Local Presence (in Augmented Reality): In sharp contrast, local presence reflects “it being here.” The user never loses perceptual contact with their actual room or external surroundings. Instead of ego-transportation (the self moving elsewhere), local presence involves object-transportation and spatial integration (the digital object arriving here). It reflects the degree to which virtual visual stimuli successfully bypass the user’s perceptual disbelief mechanisms to be perceived as authentic co-occupants of the user’s local space.

Perceptual and Cognitive Mechanisms

Local presence operates through several interlinked perceptual and cognitive mechanisms:

• Spatial Plausibility: The cognitive assessment that the object adheres to the geometric constraints of the real environment. If a virtual vase rests firmly upon a wooden table without clipping through the surface, floating unsteadily, or sliding arbitrarily, the brain attributes spatial plausibility to it.
• Visual Harmonization: The sensory matching of light direction, shadow intensity, ambient reflection, visual noise, and depth of field between the natural scene and the rendered artifact. When lighting congruency is high, visual discrimination barriers diminish, facilitating the perceptual illusion of co-presence.
• Environmental Coexistence: The subjective feeling that if the user were to reach out, the object would occupy tangible physical space, exhibiting stable spatial coordinates relative to the user’s own bodily movements (proprioception) and vestibular cues.

The LP-AR was designed specifically as a unidimensional construct. While technological antecedents (such as the multi-dimensional Augmentation Quality framework comprising vividness, interactivity, spatial alignment, and tracking stability) involve distinct technical facets, the psychological consequence—local presence—is experienced as a singular, holistic psychological sensation: the digital entity simply feels genuinely present in the user’s immediate environment.

6. Theoretical Framework

The conceptual foundation of the Local Presence in AR Scale rests at the intersection of perceptual psychology, ecological optics, media realism, and situated cognition.

Ecological Approach to Visual Perception

The scale draws heavily on the ecological perception paradigm formulated by James J. Gibson (1979). Gibson postulated that visual perception is not an internal reconstruction of retinal snapshots, but rather the direct pickup of optical invariants and visual affordances from the ambient light environment. In natural settings, organisms perceive objects in relation to terrestrial ground planes, textures, horizons, and dynamic occlusion edges created as the observer moves.

In augmented reality, when algorithmic tracking precisely detects surface planes and synchronizes digital motion parallax with the observer’s head motion, the artificial object provides optical invariants identical to those of physical entities. Local presence conceptualizes the success of this ecological coupling: when the synthetic visual cues seamlessly interface with the real environment’s invariant structures, the user’s perceptual cognitive system treats the virtual artifact as an embodied affordance within the local ecology.

The Perceptual Illusion of Non-Mediation

Lombard and Ditton (1997) defined presence fundamentally as the “perceptual illusion of non-mediation.” This illusion occurs when a person responds to mediated visual and auditory representations as if the mediating technology did not exist. Schein et al. (2025) adapted this overarching definition to the domain of AR by demonstrating that non-mediation in augmented environments manifests not as the disappearance of the screen into a fictional world, but as the disappearance of the computational boundary separating the virtual rendering from physical reality. High local presence occurs when the user no longer consciously processes the object as an array of light-emitting diodes, pixels, or rendering passes, but as a tangible physical entity sitting atop their kitchen counter or floor.

The Stimulus-Organism-Response (S-O-R) Paradigm

Within marketing and behavioral science, the LP-AR is positioned within the classic Stimulus-Organism-Response (S-O-R) paradigm (Mehrabian & Russell, 1974). In the comprehensive nomological model introduced by Schein et al. (2025):

• Stimulus (S): Represented by Augmentation Quality (AQ)—a multidimensional technical and design construct encompassing rendering vividness, tracking stability, environmental lighting integration, and interactive latency.
• Organism (O): Represented by Local Presence (LP)—the internal, experiential cognitive state of perceiving the virtual entity as physically grounded, which subsequently triggers downstream cognitive assessments (informational value) and emotional responses (hedonic appreciation).
• Response (R): Manifested through consumer decisions, brand engagement, positive word-of-mouth, purchase intentions, and actual real-world transactional choices.

7. Validity

The Local Presence in AR Scale underwent extensive psychometric evaluation across several empirical studies conducted by Schein et al. (2025), utilizing both controlled laboratory experiments and broad field samples of mobile AR and smart glasses users. The accumulated evidence firmly substantiates its construct, convergent, discriminant, and criterion-related predictive validity.

Construct and Convergent Validity

Construct validity was established through rigorous structural equation modeling (SEM) and confirmatory factor analysis (CFA). Individual standardized factor loadings for all items comprising the LP-AR consistently exceed the recommended .70 threshold, with empirical factor loadings spanning from .82 to .94 across diverse validation datasets. The Average Variance Extracted (AVE) systematically surpasses the conventional .50 benchmark, routinely reaching values between .72 and .84. These metrics confirm that the latent construct accounts for the vast majority of variance in its observed measurement indicators, demonstrating exceptional convergent validity.

Discriminant Validity

Discriminant validity was verified using both the classical Fornell-Larcker criterion and the more stringent Heterotrait-Monotrait ratio of correlations (HTMT). In testing against related yet theoretically divergent constructs—including general immersion, telepresence, VR spatial presence, visual appeal, perceived usefulness, and technological novelty:

• The square root of the AVE for the LP-AR exceeded the correlation between the LP-AR and any other latent construct within the structural model, satisfying the Fornell-Larcker benchmark.
• All HTMT ratios between the LP-AR and adjacent dimensions fell comfortably below the conservative cutoff value of .85 (with maximum observed HTMT values rarely exceeding .65). This provides rigorous statistical confirmation that local presence represents a distinct psychological phenomenon rather than a replication of general technological satisfaction or visual quality.

Nomological and Predictive Criterion Validity

The predictive and nomological validity of the LP-AR was demonstrated through its focal role within structural mediation models. The scale successfully mediates the relationship between objective technological quality (Augmentation Quality) and consequential downstream psychological and behavioral outcomes:

• Hedonic Value: Local presence exerts a profound, statistically significant direct effect on user entertainment and experiential enjoyment ($eta > .45, p < .001$).
• Utilitarian & Informational Value: By making the virtual object feel genuinely present, users can accurately evaluate size, scale, aesthetic fit, and spatial compatibility, yielding strong positive paths to perceived informational diagnostic value ($eta > .40, p < .001$).
• Behavioral Intentions & Real Choices: In both hypothetical purchase intent settings and incentivized behavioral choice experiments, elevated local presence scores significantly predicted consumers’ willingness to buy and actual product selection, confirming exceptional predictive criterion validity in applied settings.

8. Reliability

The reliability of the LP-AR has been confirmed using multiple complementary indices across varied experimental conditions, product categories (e.g., furniture, consumer electronics, luxury fashion), and hardware environments (smartphones, tablets, spatial headsets).

Internal Consistency Metrics

Across the development and validation studies reported by Schein et al. (2025):

• Cronbach’s Alpha ($lpha$): The scale demonstrates exceptional internal consistency, consistently producing Cronbach’s alpha values between .89 and .95 across sample cohorts. These figures comfortably exceed the accepted psychometric standard of .70 for exploratory research and .80 for applied diagnostic tools.
• Composite Reliability (CR): Structural equation modeling evaluations yield composite reliability coefficients ranging from .91 to .96, demonstrating that the scale indicators possess high shared variance and minimal measurement error.
• Average Variance Extracted (AVE): The scale regularly yields AVE scores in excess of .75, indicating that more than three-quarters of the indicator variance is directly attributable to the underlying local presence construct rather than random error.

Measurement Invariance and Stability

Multi-group confirmatory factor analyses demonstrate that the LP-AR achieves full configural, metric, and scalar invariance across multiple sub-populations:

• Device Invariance: The psychometric properties of the scale remain invariant whether administered after smartphone-based AR interactions (e.g., viewing 3D models through a mobile screen) or hands-free spatial computing interactions (e.g., optical see-through displays).
• Demographic Stability: Invariance was sustained across user gender, age groups, and levels of prior technological familiarity, indicating that the scale does not introduce systematic measurement bias across tech-savvy versus novice cohorts.
• Test-Retest Stability: In repeated-measures laboratory paradigms with fixed AR visual stimuli, the scale displayed robust temporal stability over short intervals, yielding test-retest correlation coefficients exceeding $r = .82$.

9. Factor Analysis

The underlying factor structure of the LP-AR was systematically evaluated through exploratory factor analysis (EFA) during early scale purification, followed by rigorous confirmatory factor analysis (CFA) across diverse validation samples.

Exploratory Factor Analysis (EFA)

During initial item generation and purification, an extensive pool of potential candidate items reflecting spatial arrival, physical co-existence, environmental fit, and perceptual realism was administered to participant pools interacting with various AR applications. Principal axis factoring and maximum likelihood extractions with oblimin rotation revealed:

• A single dominant factor exhibiting an eigenvalue substantially above Kaiser’s criterion of 1.0 (initial eigenvalues often exceeding 3.5), with subsequent factors dropping sharply to values well below 0.6.
• The visual scree plot clearly indicated an unambiguous, sharp elbow after the first factor, confirming the intrinsic unidimensionality of the construct.
• All retained target items demonstrated substantial communalities ($h^2 > .65$) and loaded heavily onto the primary local presence factor ($> .80$), with zero problematic cross-loadings onto adjacent exploratory dimensions.

Confirmatory Factor Analysis (CFA)

Confirmatory factor analyses performed in AMOS and R (lavaan package) on independent holdout datasets confirmed the superior fit of the single-factor model. The unidimensional specification demonstrated excellent global and local fit indices, conforming to the rigorous standards established by Hu and Bentler (1999):

• Chi-Square / Degrees of Freedom ($\chi^2 / df$): Values consistently ranged between 1.25 and 2.10, indicating minimal discrepancy between observed and implied covariance matrices.
• Comparative Fit Index (CFI): Ranged from .985 to .998, comfortably exceeding the .95 cutoff.
• Tucker-Lewis Index (TLI): Ranged from .978 to .996, indicating exceptional parsimonious fit.
• Root Mean Square Error of Approximation (RMSEA): Consistently remained between .025 and .052 (with 90% confidence intervals bounded tightly between .000 and .068), well below the .06 benchmark for good fit.
• Standardized Root Mean Square Residual (SRMR): Consistently recorded between .015 and .032, affirming very low residual covariance.

Attempts to model the items into multi-factor solutions or split them into visual versus spatial sub-dimensions resulted in degraded model fit, non-significant variance parameters, and extremely high factor intercorrelations ($r > .90$), confirming that the single-factor, unidimensional operationalization is mathematically and theoretically optimal.

10. Instrument / Measurement Tool

The Local Presence in AR Scale is operationalized as an efficient, self-administered questionnaire designed for immediate deployment following an augmented reality session. Below are the operational parameters and administration protocols for researchers and practitioners:

• Instrument Type: Self-report psychometric rating scale; unidimensional inventory.
• Administration Format: Digital (online survey, in-app mobile survey, embedded XR interface) or paper-and-pencil questionnaire.
• Administration Timing: Administered immediately post-exposure to the AR experience to minimize recall bias and capture immediate perceptual memory traces.
• Estimated Completion Time: Approximately 1 to 2 minutes, minimizing participant fatigue when embedded within extensive structural batteries.
• Target Population: Consumers, study participants, and technology users aged 16 and older interacting with augmented reality software on smartphones, tablets, or spatial computing head-mounted displays.
• Response Format: 7-point Likert-type scale with the following anchors:
  • 1 = Strongly Disagree
  • 2 = Disagree
  • 3 = Somewhat Disagree
  • 4 = Neutral / Neither Agree nor Disagree
  • 5 = Somewhat Agree
  • 6 = Agree
  • 7 = Strongly Agree
• Scoring Protocol:
  • All items are positively worded; therefore, no reverse scoring is required.
  • A composite Local Presence Index score is calculated by computing the arithmetic mean of all item responses: $\text{LP Score} = \frac{\sum \text{Item Scores}}{k}$, where $k$ is the total number of items administered.
  • Alternatively, within structural equation modeling paradigms, the items may be specified as observed indicators loading directly onto a single latent construct without manual item averaging.
  • Higher composite scores (e.g., values approaching 7.0) indicate an intense perceptual illusion that the virtual object has physically materialized within the user’s immediate environment; lower scores (e.g., approaching 1.0) indicate that the user viewed the object strictly as an artificial, disconnected visual overlay.

11. Permissions & Fee and Test Year

The Local Presence in AR Scale (LP-AR) was published in 2025 in the peer-reviewed scholarly journal Journal of the Academy of Marketing Science (JAMS), published by Springer Nature.

• Copyright & Intellectual Property: The empirical study, formal scale wording, and validation datasets are copyrighted by the original authors (Katharina E. Schein, Philipp A. Rauschnabel, Susanne Praxmarer-Carus, and Barry J. Babin) and the publisher (Springer Nature).
• Academic and Non-Commercial Research Usage: Consistent with standard academic conventions, researchers may freely utilize the scale items for non-commercial, scholarly research, thesis projects, and scientific inquiry, provided appropriate bibliographic citation is accorded to the original publication (Schein et al., 2025).
• Commercial Applications: Commercial enterprises, proprietary market research agencies, and software developers seeking to integrate the scale into commercial diagnostic platforms or proprietary testing suites should consult the corresponding authors and the publisher regarding commercial licensing agreements.
• Associated Tools: The LP-AR is frequently paired with the Augmentation Quality Scale (AQS), published within the same foundational investigation. While developed in tandem, the LP-AR is psychometrically distinct and fully validated for autonomous administration.

12. References

• Biocca, F. (1997). The cyborg’s dilemma: Progressive embodiment in virtual environments. Journal of Computer-Mediated Communication, 3(2), JCMC324. https://doi.org/10.1111/j.1083-6101.1997.tb00070.x
• Gibson, J. J. (1979). The Ecological Approach to Visual Perception. Houghton Mifflin.
• Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
• Lombard, M., & Ditton, T. (1997). At the heart of it all: The concept of presence. Journal of Computer-Mediated Communication, 3(2), JCMC321. https://doi.org/10.1111/j.1083-6101.1997.tb00072.x
• Mehrabian, A., & Russell, J. A. (1974). An Approach to Environmental Psychology. The MIT Press.
• Rauschnabel, P. A., Babin, B. J., tom Dieck, M. C., Krey, N., & Jung, T. (2022). What is augmented reality marketing? Its definition, taxonomy, and agenda. Journal of Business Research, 142, 1143–1155. https://doi.org/10.1016/j.jbusres.2021.12.078
• 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
• Steuer, J. (1992). Defining virtual reality: Dimensions determining telepresence. Journal of Communication, 42(4), 73–93. https://doi.org/10.1111/j.1460-2466.1992.tb00812.x
• Witmer, B. G., & Singer, M. J. (1998). Measuring presence in virtual environments: A presence questionnaire. Presence: Teleoperators and Virtual Environments, 7(3), 225–240. https://doi.org/10.1162/105474698565686

13. Items of the Scale