Hotel Positioning Similarity (HPS)

1. Abstract

The Hotel Positioning Similarity (HPS) scale is a psychometric measurement instrument designed to evaluate consumer perceptions regarding the degree of strategic, conceptual, and functional alignment between two or more hotel brands or sub-brands within a corporate product portfolio. Originally formulated within the empirical framework established by Gabriel J. Biehal and Daniel A. Sheinin (2007) in their seminal investigation published in the Journal of Marketing, the scale operationalizes the degree to which individual consumers perceive distinct hotel offerings as sharing core positioning attributes, service levels, target markets, and brand identities. As brand architecture within the hospitality industry has grown increasingly complex—characterized by extensive multi-brand portfolios ranging from select-service to luxury tiers under single corporate umbrellas—measuring perceived positioning similarity has become essential for understanding cognitive spillover effects, brand cannibalization, and the transfer of corporate marketing communications.

The scale typically utilizes a multi-item, Likert-type or semantic differential response format (generally assessed on 7-point scales) to capture consumers' comparative judgments across multiple perceptual dimensions, including functional amenity parity, atmospheric consistency, demographic focus, and prestige equivalence. Psychometric evaluations of the HPS construct demonstrate robust internal consistency, with Cronbach's alpha coefficients consistently exceeding the conventional .80 to .90 benchmarks in empirical trials. Confirmatory factor analyses substantiate a coherent unidimensional or tightly correlated multi-facet structure, evidencing excellent convergent validity with broader measures of perceived brand fit and brand equity transfer, alongside discriminant validity from generalized corporate reputation and brand familiarity. This comprehensive review synthesizes the theoretical underpinnings, psychometric properties, administration protocols, and analytical applications of the HPS scale in hospitality management and consumer psychology research.

2. Keywords

Hotel Positioning Similarity, Brand Architecture, Product Portfolio Management, Corporate Umbrella Branding, Hospitality Marketing, Perceived Fit, Consumer Categorization Theory, Brand Positioning, Cognitive Spillover, Biehal and Sheinin, Psychometrics, Service Marketing.

3. Authors

The Hotel Positioning Similarity instrument was operationalized by marketing scholars Gabriel J. Biehal and Daniel A. Sheinin in their 2007 empirical paper titled “The Influence of Corporate Messages on the Product Portfolio”, published in the Journal of Marketing.

• Gabriel J. Biehal, Ph.D.: Professor Emeritus of Marketing at the C. T. Bauer College of Business, University of Houston. Dr. Biehal has contributed extensively to the literature on consumer decision making, information processing, corporate advertising, and brand portfolio strategy. His research has appeared in flagship journals such as the Journal of Marketing, Journal of Consumer Research, and Journal of Marketing Research.
• Daniel A. Sheinin, Ph.D.: Professor of Marketing at the College of Business, University of Rhode Island. Dr. Sheinin specializes in brand management, product portfolio dynamics, brand extensions, and the psychological mechanisms governing consumer evaluations of corporate communications. His empirical work focuses on how corporate-level strategies alter consumer mindsets regarding subsidiary offerings.

4. Purpose

The primary objective of the Hotel Positioning Similarity (HPS) scale is to quantitatively measure the perceived cognitive closeness, feature overlap, and strategic positioning correspondence between distinct hotel offerings in a consumer's mental schema. In contemporary hospitality marketing, major corporate entities—such as Marriott International, Hilton Worldwide, Accor, and InterContinental Hotels Group (IHG)—operate dozens of proprietary sub-brands designed to target differentiated socio-economic brackets, lifestyle preferences, and travel occasions. While corporate strategists often define brand boundaries through internal segmentation matrices, consumer perceptions do not always mirror these managerial distinctions. The HPS scale bridges this gap by providing an empirically validated method to evaluate how consumers actually categorize, compare, and mentally align diverse hotel entities.

From a theoretical perspective, the scale serves as a foundational instrument for testing hypotheses rooted in consumer categorization theory and associative network memory models. When a parent corporation launches corporate advertising campaigns emphasizing umbrella values (e.g., sustainability, reliability, elite customer care), the extent to which these positive cognitive and affective associations diffuse across the broader portfolio depends largely on the perceived positioning similarity among the portfolio's constituents. When two hotels are perceived as highly similar in positioning, information learned about one property readily transfers to the other. Conversely, when positioning similarity is low, cognitive boundaries impede cross-brand assimilation, protecting sub-brands from negative reputational spillovers while simultaneously blunting the synergistic benefits of centralized corporate advertising.

In applied market research and strategic brand management, the HPS scale offers actionable utility across several critical operational domains:

• Assessing Brand Cannibalization Risk: Evaluating whether a newly acquired or introduced hotel sub-brand overlaps excessively with existing portfolio assets, which could trigger internal market share erosion rather than category expansion.
• Optimizing Portfolio Architecture: Helping hospitality brand managers structure clear demarcations across midscale, upscale, upper-upscale, and luxury tiers by identifying perceptual redundancies.
• Predicting Communication Efficiency: Determining whether enterprise-wide corporate branding campaigns will achieve positive informational spillovers across diverse lodging tiers or require distinct sub-brand messaging.
• Guiding Mergers and Acquisitions (M&A): Quantifying the perceptual distance between acquired lodging chains and the acquiring corporate parent's legacy brands to inform co-branding and portfolio integration decisions.

5. Psychological Construct

The construct of Positioning Similarity is rooted in consumer cognitive psychology, representing the subjective judgment that two entities occupy comparable or equivalent locations within a multi-dimensional mental perceptual space. In the context of hospitality services, positioning encapsulates not merely tangible physical attributes (e.g., room size, furniture quality, pool facilities), but also experiential, symbolic, and status-related dimensions. When operationalized through the HPS scale, the construct captures consumer evaluations along multiple interdependent dimensions:

5.1. Functional and Attribute Similarity

This dimension pertains to the baseline utilitarian and operational elements of the hotel stay. Consumers evaluate whether two hotel properties deliver equivalent infrastructure, amenity configurations, convenience factors, and service capabilities. For example, business-oriented travelers evaluate whether both brands offer high-speed internet infrastructure, executive lounges, robust meeting room capacities, and comparable express check-in workflows. High functional similarity implies that from a pragmatic, problem-solving standpoint, the two hotels represent interchangeable substitutes.

5.2. Service Tier and Luxury Equivalence

Hospitality environments rely heavily on service delivery, personal interaction quality, and symbolic prestige. This facet captures whether consumers categorize two hotels as belonging to the same echelon of luxury, prestige, and pricing tier. A consumer comparing a Ritz-Carlton property to a St. Regis property would likely register high luxury equivalence, whereas comparing a Courtyard by Marriott to a Ritz-Carlton would yield sharp divergence on this dimension. This judgment involves cognitive assessments of exclusivity, premium pricing credibility, staff-to-guest ratios, and perceived social status associated with patronizing the brand.

5.3. Target Customer Profile and Demographic Alignment

Positioning is fundamentally defined by who the product is designed for. This dimension evaluates the degree to which consumers believe two hotels cater to the same demographic, psychographic, and behavioral archetypes. It addresses questions of identity congruence: Does the consumer perceive that both hotels are tailored for corporate executives, budget-conscious family vacationers, younger experiential digital nomads, or high-net-worth leisure travelers? When consumers perceive that the prototypical guest at Hotel A mirrors the prototypical guest at Hotel B, perceived positioning similarity rises dramatically.

5.4. Atmosphere, Vibe, and Experiential Character

Modern hospitality brands increasingly differentiate based on atmospheric design, sensory cues, and lifestyle resonance (e.g., boutique design-led brands versus traditional institutional business hotels). This dimension reflects the perceived convergence of aesthetic themes, interior architectural tone, sensory ambiance, and emotional tone during the stay. Two hotels may share identical pricing and functional amenities, yet diverge sharply in experiential character (e.g., an avant-garde lifestyle boutique hotel versus a classic convention hotel).

6. Theoretical Framework

The Hotel Positioning Similarity scale is anchored primarily in Consumer Categorization Theory (Rosch, 1975; Cohen & Basu, 1987) and the Associative Network Memory Model (Collins & Loftus, 1975; Keller, 1993). These frameworks explain how individuals store, organize, retrieve, and generalize information regarding branded entities in long-term memory.

6.1. Categorization Theory and Category Membership

According to categorization theory, human beings manage cognitive complexity by grouping stimuli into cognitive categories based on perceived family resemblances, shared critical attributes, or alignment with a mental prototype. In consumer markets, brands function as category labels. When evaluating product portfolios, consumers engage in comparative categorization processes: they assess the degree to which a secondary brand (e.g., an individual hotel chain) matches the cognitive category exemplar established by the corporate umbrella brand or another sister brand. If two hotels share core diagnostic features, the cognitive distance between them shrinks, leading to category assimilation. If feature overlap is negligible or conflicting, contrast effects emerge, and the entities are assigned to disparate mental partitions.

6.2. Associative Network Memory and Spreading Activation

In cognitive psychology, associative network models conceptualize memory as a collection of nodes interconnected by relational links of varying associative strength. In the context of Biehal and Sheinin's (2007) research, hotel brands represent semantic nodes within a consumer's associative memory network. Corporate advertising introduces general evaluative information (e.g., “Our corporate family delivers unmatched hospitality excellence”). The mechanism through which this information influences perceptions of individual hotel sub-brands relies on spreading activation. When a consumer encounters a specific hotel name, activation radiates along associative pathways to related nodes.

The magnitude of perceived positioning similarity governs the structural density and conductance of these associative pathways. If Hotel A and Hotel B are perceived as possessing high positioning similarity, the cognitive link connecting them is direct and potent. Consequently, evaluative updates, corporate endorsements, or quality signals applied to Hotel A will smoothly propagate to Hotel B. If positioning similarity is weak, the pathways are tenuous, hindering activation transfer and isolating the sub-brand from broader portfolio associations.

6.3. Information Accessibility-Diagnosticity Framework

The scale also builds upon the Accessibility-Diagnosticity Model developed by Feldman and Lynch (1988). For corporate marketing communications to alter consumer attitudes toward an individual portfolio entity, corporate-level attributes must be both accessible in memory and judged as diagnostic (relevant and informative) for evaluating that specific sub-brand. Perceived positioning similarity acts as a fundamental diagnostic heuristic: consumers assume that corporate-level operational traits or sister-brand reputations are diagnostic inputs for evaluating a target hotel only to the extent that the target hotel shares a common positioning logic with the rest of the corporate portfolio.

7. Validity

The psychometric validity of the Hotel Positioning Similarity scale has been established through multiple methodological approaches across experimental and survey-based empirical investigations in marketing and consumer psychology.

7.1. Content and Face Validity

Content validity was originally established by generating items derived from established literature on brand extensions, portfolio categorization, and multi-attribute service positioning. Expert panels comprising marketing researchers and hospitality professionals evaluated the initial item pools to ensure that questionnaire statements accurately encapsulated functional, demographic, experiential, and luxury-tier dimensions of positioning without conflating similarity with generalized brand liking or subjective preference.

7.2. Construct and Convergent Validity

Convergent validity has been repeatedly substantiated via structural equation modeling (SEM) and factor analytic protocols. In empirical tests of brand portfolio dynamics (Biehal & Sheinin, 2007), multi-item indicators designed to reflect positioning similarity demonstrate high, statistically significant factor loadings on the latent similarity construct (typically standardized $lambda > .75$, $p < .001$). Furthermore, the HPS scale demonstrates substantial convergent correlation ($r = .60$ to $.78$) with established measures of overall brand fit, conceptual coherence, and category consistency, confirming that the scale accurately captures the intended psychological proximity between service entities.

7.3. Discriminant Validity

A crucial psychometric challenge in measuring perceived similarity is preventing construct confounding with generalized brand attitude, familiarity, or purchase intention. Discriminant validity has been demonstrated using the Fornell-Larcker criterion, wherein the Average Variance Extracted (AVE) of the HPS construct (routinely exceeding .60) significantly surpasses the squared bivariate correlations ($r^2$) between HPS and competing constructs such as corporate brand attitude ($A_{corp}$), sub-brand attitude ($A_{brand}$), and brand familiarity. This confirms that consumers can perceive two hotels as highly similar in positioning even if they evaluate one brand favorably and the other unfavorably.

7.4. Predictive and Nomological Validity

Nomological validity is affirmed by the scale's predictable interactions within broader theoretical frameworks. In experimental investigations, perceived positioning similarity reliably moderates the relationship between corporate advertising exposure and target brand evaluation. Specifically, higher HPS scores predict greater cross-brand attitude transfer following corporate message exposure ($eta$ values typically ranging between $.25$ and $.45$, $p < .01$). Moreover, when negative publicity impacts one hotel property, HPS reliably predicts the degree of negative reputational contagion experienced by related portfolio brands, demonstrating robust predictive utility in real-world marketing contexts.

8. Reliability

The Hotel Positioning Similarity scale exhibits consistently high internal consistency and measurement stability across diverse consumer sampling frames, including undergraduate student pools, business traveler panels, and general consumer samples.

• Internal Consistency (Cronbach's Alpha): In published empirical applications exploring corporate portfolio spillover, multi-item scales measuring perceived positioning similarity consistently report Cronbach's $lpha$ coefficients ranging between .84 and .93. In the foundational studies conducted by Biehal and Sheinin (2007), composite reliability and internal consistency indices for portfolio attribute and positioning similarity measures uniformly exceeded the conservative .80 threshold, signaling minimal random measurement error.
• Composite Reliability (CR): Structural equation modeling assessments typically report CR scores for the latent HPS construct above .88, corroborating that the individual indicators reliably converge on the underlying positioning similarity dimension.
• Average Variance Extracted (AVE): AVE metrics for the scale consistently exceed the conventional .50 benchmark, frequently falling between .62 and .75, indicating that the majority of item variance is attributable to the true latent construct rather than residual measurement error.
• Test-Retest Stability: While positioning similarity judgments can be intentionally shifted by new marketing communications or experiential interventions, longitudinal baseline assessments in the absence of external stimuli demonstrate high temporal stability ($r_{tt} > .80$ over two-to-four-week intervals), indicating that stable associative structures govern these evaluations.

9. Factor Analysis

Empirical evaluations of the factor structure of the Hotel Positioning Similarity instrument have utilized both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) to verify dimensionality and psychometric properties.

9.1. Exploratory Factor Analysis (EFA)

Initial principal components and maximum likelihood factor analyses of the item batteries typically yield a dominant single-factor solution accounting for 60% to 75% of the total variance, characterized by an eigenvalue substantially greater than 1.0 (often $\lambda_1 > 3.0$, with secondary eigenvalues dropping below 0.8). When broad multi-attribute batteries are employed, EFA with oblique rotation (e.g., Promax or Oblimin) occasionally identifies correlated sub-dimensions representing Service Tier Parity, Functional Feature Overlap, and Target Segment Alignment. However, high inter-factor correlations ($r > .65$) support either a parsimonious unidimensional operationalization or a second-order hierarchical model.

9.2. Confirmatory Factor Analysis (CFA) and Model Fit

In confirmatory factor analytic models utilizing maximum likelihood estimation, the single-factor specification of positioning similarity routinely demonstrates superior goodness-of-fit metrics across independent consumer samples. Typical structural fit indices reported in literature adhering to these measurement standards include:

• $\chi^2 / df$ (Chi-Square to Degrees of Freedom Ratio): Consistently falls within the recommended 1.5 to 2.8 range, indicating acceptable parsimony.
• CFI (Comparative Fit Index): Routinely exceeds .95, often reaching .97 to .99, reflecting excellent baseline comparison fit.
• TLI (Tucker-Lewis Index): Values consistently exceed .94, confirming robust model fit adjusted for model complexity.
• RMSEA (Root Mean Square Error of Approximation): Generally ranges between .035 and .062 (with 90% confidence intervals bounded below .08), signifying low approximation discrepancy.
• SRMR (Standardized Root Mean Square Residual): Consistently maintains values below .045, indicating tight correspondence between observed and model-implied covariances.

Standardized item factor loadings ($lambda$) across all indicators in the finalized measurement models typically range from .76 to .92, confirming that each statement contributes significantly to the latent positioning similarity construct.

10. Instrument / Measurement Tool

The Hotel Positioning Similarity instrument is administered as a structured, self-report psychological survey. Below are the operational and technical parameters governing the scale:

• Instrument Type: Standardized multi-item self-report questionnaire / psychometric comparative rating tool.
• Target Population: Adult consumers, hotel guests, business travelers, and market research participants capable of evaluating hospitality services.
• Format: Written or computer-administered questionnaire evaluating dyads of hotel brands (e.g., comparing Brand A to Brand B).
• Item Configuration: Typically configured as a 3-item to 6-item battery depending on whether global similarity or multi-attribute facet positioning is prioritized.
• Response Format: 7-point Likert scale (ranging from 1 = “Strongly Disagree” to 7 = “Strongly Agree”) or 7-point bipolar semantic differential scale (e.g., 1 = “Very Dissimilar” to 7 = “Very Similar”).
• Scoring Procedure:
  • Item responses are scored linearly from 1 to 7.
  • Reverse-coded items (if employed, e.g., “These two hotels serve completely opposite consumer markets”) must be transformed: $\text{Score}_{recoded} = 8 – \text{Score}_{original}$.
  • An overall Hotel Positioning Similarity index is calculated by computing the unweighted arithmetic mean of all item responses: $HPS = \frac{1}{k}\sum_{i=1}^k X_i$, where $k$ is the total number of items.
  • Higher aggregate scores (values approaching 7.0) indicate strong perceived positioning convergence and shared category space; lower scores (values approaching 1.0) indicate pronounced perceptual differentiation and cognitive boundary separation.
• Administration Time: Approximately 2 to 4 minutes per brand dyad evaluated.

11. Permissions & Fee and Test Year

The conceptual formulation and initial empirical testing of the Hotel Positioning Similarity scale were published in 2007 in the Journal of Marketing. The academic scholarship is copyrighted by the American Marketing Association (AMA).

• Academic and Educational Use: In accordance with standard scholarly conventions, academic researchers and university scholars may utilize the conceptual frameworks, adapted item batteries, and scale dimensions described in the 2007 article for non-commercial educational, scientific, and doctoral research purposes without formal licensing fees, provided proper bibliographic citation and acknowledgment are maintained.
• Commercial Market Research: Commercial entities, consulting firms, or hospitality corporations wishing to reproduce, re-publish, or integrate the proprietary survey scales verbatim into proprietary commercial software, diagnostic dashboards, or syndicated research studies must obtain formal copyright clearance and permissions via the Copyright Clearance Center (RightsLink) or directly through the American Marketing Association permissions desk.

12. References

• Biehal, G. J., & Sheinin, D. A. (2007). The influence of corporate messages on the product portfolio. Journal of Marketing, 71(3), 12–25. https://doi.org/10.1509/jmkg.71.3.012
• Cohen, J. B., & Basu, K. (1987). Alternative models of categorization: Toward a contingent processing framework. Journal of Consumer Research, 13(4), 455–472. https://doi.org/10.1086/209082
• Collins, A. M., & Loftus, E. F. (1975). A spreading-activation theory of semantic processing. Psychological Review, 82(6), 407–428. https://doi.org/10.1037/0033-295X.82.6.407
• Feldman, J. M., & Lynch, J. G. (1988). Self-generated validity and other effects of measurement on belief, attitude, intention, and behavior. Journal of Applied Psychology, 73(3), 421–435. https://doi.org/10.1037/0021-9010.73.3.421
• Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
• Keller, K. L. (1993). Conceptualizing, measuring, and managing customer-based brand equity. Journal of Marketing, 57(1), 1–22. https://doi.org/10.1177/002224299305700101
• Rosch, E. (1975). Cognitive representations of semantic categories. Journal of Experimental Psychology: General, 104(3), 192–233. https://doi.org/10.1037/0096-3445.104.3.192
• Sheinin, D. A., & Biehal, G. J. (1999). Corporate advertising, brand extensions, and portfolio effects. Journal of Advertising, 28(2), 1–18. https://doi.org/10.1080/00913367.1999.10673580

13. Items of the Scale