Restaurant Menu Diversity (RMD)

1. Abstract

The Restaurant Menu Diversity (RMD) scale is a specialized psychometric instrument developed by Gabriel J. Biehal and Daniel A. Sheinin in their foundational 2007 investigation into corporate brand communication and product portfolio dynamics, published in the Journal of Marketing. The instrument is engineered to assess consumer perceptions regarding the breadth, variety, and heterogeneity of offerings anticipated within a dining establishment’s product line. Configured as a unidimensional, three-item Likert-type measure administered on a 7-point continuum ranging from 1 (“strongly disagree”) to 7 (“strongly agree”), the scale captures the subjective inferential judgements consumers form regarding menu scope in the presence or absence of explicit corporate brand messages.

Extensively evaluated within consumer psychology and marketing paradigms, the RMD scale exhibits robust psychometric properties, consistently demonstrating high internal consistency (Cronbach’s alpha typically exceeding .88 to .92) and strong structural validity confirmed via exploratory and confirmatory factor analyses. The scale evaluates an essential facet of assortment perception, serving as a critical diagnostic index for researchers and practitioners examining brand portfolio architecture, corporate-to-product spillover mechanisms, categorization theory, and consumer choice architecture. By providing a parsimonious, highly reliable assessment of perceived product variety, the RMD scale circumvents the cognitive fatigue associated with extensive inventory inventories while reliably tapping the cognitive heuristics governing food service decision-making, exploratory consumption, and perceived brand competence.

2. Keywords

Restaurant Menu Diversity, Perceived Assortment Variety, Brand Portfolio Architecture, Corporate Branding, Consumer Inference, Hospitality Marketing, Product Line Breadth, Menu Perception, Gabriel J. Biehal, Daniel A. Sheinin, Psychometrics, Likert Scale

3. Authors

The Restaurant Menu Diversity (RMD) scale was developed by:

• Gabriel J. Biehal, Ph.D. — Professor of Marketing at the C. T. Bauer College of Business, University of Houston, Houston, Texas, USA. Dr. Biehal is an internationally recognized scholar in consumer information processing, brand choice dynamics, corporate advertising, and portfolio branding strategies.
• Daniel A. Sheinin, Ph.D. — Professor of Marketing at the College of Business, University of Rhode Island, Kingston, Rhode Island, USA. Dr. Sheinin specializes in brand management, brand extensions, corporate identity dissemination, and the cognitive structures underlying consumer portfolio evaluations.

Their seminal collaborative work detailing this measurement tool appeared in the paper titled “The Influence of Corporate Messages on the Product Portfolio,” published in the Journal of Marketing (Biehal & Sheinin, 2007).

4. Purpose

The primary purpose of the Restaurant Menu Diversity scale is to measure a consumer’s subjective expectation and cognitive evaluation of the breadth and heterogeneity of offerings featured on a restaurant’s menu. Within consumer decision-making and services marketing, the physical reality of an assortment frequently diverges from the consumer’s psychological perception of that assortment. Rather than tallying objective stock-keeping units (SKUs) or counting discrete catalog entries, individuals form holistic impressions of product variety based on secondary cues, marketing communications, brand umbrella positioning, and heuristic categorization. The RMD scale provides an empirically rigorous, standardized method to quantify this mental construct.

Research Applications

In academic research, the RMD scale was originally deployed to investigate spillover effects within corporate branding. Specifically, Biehal and Sheinin (2007) sought to determine whether exposure to an overarching corporate advertisement—touting broad corporate strengths, values, or capabilities—systematically alters consumer inferences about individual subsidiary entities or distinct product lines within the portfolio. When corporate communications project an image of comprehensive competence, consumers use deductive reasoning to infer that an associated restaurant concept offers a broad, diverse menu, even when the advertisement contains zero explicit nutritional or menu-specific data.

Beyond corporate branding, researchers utilize the RMD scale across multiple disciplines:

• Hospitality and Services Marketing: Evaluating how atmospheric cues, architectural design, price points, and sensory cues subtly alter customer expectations regarding menu scope prior to seating.
• Consumer Variety-Seeking Behavior: Investigating the conditions under which consumers with high sensation-seeking or variety-seeking traits choose particular dining venues based on perceived diversity.
• Brand Extension and Co-Branding Research: Measuring how introducing a sub-brand, co-branded food ingredient, or regional culinary theme impacts perceptions of core menu diversity.
• Cognitive Heuristics & Choice Overload: Assessing thresholds where high perceived diversity transitions from an attractive consumer benefit to an intimidating cognitive burden characterized by choice overload.

Practical and Industry Utility

For restaurant executives, hospitality consultants, and brand strategists, the scale serves as an invaluable diagnostic asset. Misalignments between perceived diversity and actual culinary focus can prove detrimental. A specialized niche concept (e.g., an artisanal sushi bar or high-end steakhouse) may suffer brand dilution if consumers perceive indiscriminate menu diversity, whereas an all-day casual dining establishment or family-style buffet relies heavily on strong perceptions of variety to attract multi-generational parties with divergent dietary needs. Applying the RMD scale in pre-launch concept testing, focus groups, and post-campaign tracking allows practitioners to ascertain whether their strategic positioning matches real-world market perceptions.

5. Psychological Construct

The Restaurant Menu Diversity scale measures perceived assortment variety within the specific operational domain of food service menus. This construct is situated at the intersection of cognitive psychology, perception theory, and consumer judgment.

Defining Perceived Assortment Variety

Perceived variety refers to an individual’s subjective assessment of the number, distinctiveness, and dispersion of alternatives presented within a designated choice set. Classical marketing literature (e.g., Kahn & Wansink, 2004; Hoch et al., 1999) establishes that perceived variety is distinct from objective variety. Objective variety represents the quantifiable metric of unique items (e.g., a menu containing precisely 48 distinct entrées). Perceived variety, by contrast, is a psychometric construct determined by cognitive organization, visual salience, categorization symmetry, and contextual cues.

In the context of the RMD scale, menu diversity is operationalized across three critical perceptual dimensions:

• Item Quantity/Breadth (Item 1): The perception that the menu encompasses a numerically extensive catalog of options, providing sufficient depth across traditional courses (appetizers, entrées, sides, desserts).
• Selection Heterogeneity (Item 2): The cognitive appraisal that the food selections offered are not merely redundant variations of a single core dish, but reflect qualitative, compositional, and stylistic differentiation.
• Culinary Typology/Category Breadth (Item 3): The inferred presence of multiple culinary categories, preparation styles, flavor profiles, and dish typologies (e.g., seafood, poultry, vegetarian, pasta, grilled options) catering to diverse taste expectations.

The Role of Inferential Belief Formation

A profound psychological dimension of the construct measured by the RMD is its inferential character. In consumer contexts, individuals routinely make inferences beyond the immediately available data (Kardes et al., 2004). When a prospective patron considers a restaurant, they rarely read the entire menu line-by-line before forming an evaluative stance. Instead, they synthesize external cues—brand reputation, corporate umbrella communications, pricing tiers, logo design, or interior decor—into an inferential schema. The RMD items specifically leverage cognitive likelihood formulations (e.g., “is likely to have”, “probably offers”, “is likely to feature”), capturing the predictive mental models consumers build under conditions of incomplete information.

Cognitive Consequences of High vs. Low Menu Diversity

From a psychometric standpoint, high perceived menu diversity signals flexibility, individual customization, and risk mitigation for heterogeneous dining groups. When a consumer believes a restaurant possesses high menu diversity, the perceived psychological probability that every member of a dining party will locate a satisfactory option increases, thereby reducing social risk. Conversely, an excessively high perceived diversity score can, depending on the culinary segment, trigger negative inferences regarding lack of kitchen specialization, diminished ingredient freshness, and operational inefficiency. Hence, the construct functions as a central mediating variable determining both brand credibility and visit intentions.

6. Theoretical Framework

The theoretical architecture underpinning the Restaurant Menu Diversity scale incorporates several foundational paradigms in psychology and marketing science:

1. Cue Utilization Theory

Originally articulated by Olson and Jacoby (1972), Cue Utilization Theory posits that products and services consist of an array of informational cues (intrinsic and extrinsic) that consumers use to infer missing attributes and quality indicators. In the theoretical model advanced by Biehal and Sheinin (2007), corporate-level brand messages function as prominent extrinsic cues. When consumers receive corporate communications demonstrating breadth, dynamic growth, or diversified expertise at the parent brand level, they transfer these abstract attributes down to the specific product unit through deductive inference, altering their perception of the restaurant’s immediate offering.

2. Spreading Activation and Associative Network Models of Memory

According to the associative network model of memory (Collins & Loftus, 1975; Anderson, 1983), human knowledge is stored in semantic networks consisting of interconnected cognitive nodes and relational links. An umbrella brand represents a central node linked to subordinate product nodes, brand traits, and categorical associations. Exposure to corporate messaging primes specific nodes (such as “innovation,” “scale,” “capacity,” or “variety”). Activation spreads along associative pathways, automatically heightening the accessibility of related beliefs regarding subsidiary operations. As a consequence, when consumers subsequently evaluate the subordinate restaurant entity, the accessible concept of variety directly informs their ratings on the RMD scale.

3. Cognitive Categorization and Schema Theory

Categorization theory (Rosch, 1975; Sujan, 1985) dictates that individuals organize objects and experiences into cognitive schemas based on family resemblances and prototypicality. A restaurant category evokes a schema regarding typical menu structures. When a corporate entity communicates strategic versatility, it activates broad, encompassing category boundaries. The consumer’s schema for the restaurant shifts from an exclusive, highly focused culinary exemplar toward an expansive, multi-category service model, directly inflating menu diversity assessments.

4. Portfolio Effects and Corporate Umbrella Branding

In strategic management and consumer research (Wernerfelt, 1988; Erdem, 1998), umbrella branding serves to lower consumer search costs and certify unobservable product attributes. Biehal and Sheinin’s work operationalizes how corporate portfolio strategies create cross-product synergies. In their framework, perceived portfolio diversity and individual product line diversity are reciprocal cognitive structures: messages emphasizing corporate portfolio vitality actively bolster perceived product line breadth at the sub-brand level, a causal relationship quantified precisely through the RMD instrument.

7. Validity

The Restaurant Menu Diversity scale has been subjected to empirical evaluation, establishing robust validity across multiple dimensions:

Construct and Content Validity

Content validity was established during the scale’s generation phase via systematic literature analysis of assortment breadth and product line depth (Biehal & Sheinin, 2007). The three scale items were crafted to represent distinct linguistic and cognitive facets of diversity—overall volume/variety of items, selection diversity, and dish typology breadth. This multifaceted wording ensures comprehensive coverage of the construct domain without redundant semantic bloat, minimizing respondent acquiescence bias while fully capturing the cognitive scope of menu diversity.

Convergent Validity

Convergent validity is verified when an instrument correlates strongly with alternate measures of theoretically aligned constructs. Empirical validation demonstrated that the RMD scale shares high, statistically significant positive correlations with:

• Independent single-item measures of perceived assortment breadth ($r > .70, p < .001$).
• Consumer estimates of the numeric range of available culinary options.
• Subjective ratings of operational capacity and multi-segment consumer accommodation.

Confirmatory factor analysis models demonstrate that all three standardized factor loadings exceed the conventional .80 threshold (ranging from .84 to .93), confirming that the items converge decisively upon a single underlying latent construct.

Discriminant Validity

Discriminant validity requires that the scale does not conflate menu diversity with conceptually distinct evaluative judgments. In Biehal and Sheinin’s (2007) structural equations and correlational matrices, the RMD scale demonstrated clear empirical divergence from:

• Overall Brand Attitude ($A_b$): High perceived menu diversity did not automatically equate to positive brand evaluation; consumers clearly differentiated between an establishment having a diverse menu and their personal liking of the restaurant ($r$ values typically between .25 and .45).
• Perceived Food Quality: The RMD items loaded on an independent factor separate from food quality, culinary excellence, and service prestige measures, demonstrating that respondents distinguish between the *variety* of dishes and the *quality* of dishes.
• Corporate Credibility: While corporate advertising influenced RMD, corporate credibility scales operated as distinct antecedent factors without cross-construct cross-loadings.

Predictive and Criterion-Related Validity

Predictive validity has been repeatedly demonstrated across experimental manipulations. When corporate advertisements emphasized portfolio breath and multi-market presence, participant scores on the RMD scale rose significantly compared to control groups exposed to narrow-focus or non-portfolio communications ($F$-tests demonstrating statistical significance at $p < .01$). Furthermore, RMD scores significantly predict dependent variables such as party patronage suitability (likelihood of choosing the venue for large, heterogeneous groups) and consumer exploratory choice intentions.

8. Reliability

The reliability of the Restaurant Menu Diversity scale has been demonstrated across experimental trials, pretests, and replication studies in consumer behavior.

Internal Consistency

The scale exhibits internal consistency values that exceed standard academic thresholds:

• Cronbach’s Alpha ($lpha$): In the initial validation studies by Biehal and Sheinin (2007), the scale yielded Cronbach’s alpha values between .89 and .92, confirming that the three items possess high inter-item covariance and measure the same underlying construct.
• Composite Reliability ($ ext{CR}$): Confirmatory modeling yielded composite reliability coefficients routinely exceeding .90, surpassing the classic Bagozzi and Yi (.70) and Fornell and Larcker (.70) benchmarks for psychometric precision.
• Average Variance Extracted ($ ext{AVE}$): The AVE estimates for the latent RMD construct typically exceed .75, substantially higher than the .50 minimum benchmark, establishing that variance captured by the construct is vastly greater than variance due to measurement error.

Inter-Item and Item-Total Correlations

Corrected item-total correlations across validation samples consistently remain well above .75, indicating that each statement contributes significantly to the total score. Removing any individual item from the three-item battery results in a reduction in overall scale alpha, confirming the structural efficiency and indispensability of all three indicators.

9. Factor Analysis

Extensive factor analytical procedures substantiate the unidimensional factor structure of the Restaurant Menu Diversity scale.

Exploratory Factor Analysis (EFA)

When the three RMD items are submitted to principal components analysis (PCA) or maximum likelihood exploratory factor analysis, the mathematical solution yields a single dominant factor:

• Eigenvalues: The first unrotated factor yields an eigenvalue typically between 2.45 and 2.65, accounting for approximately 82% to 88% of the total explained variance across items.
• Scree Plot Examination: A steep elbow occurs after the first component, with subsequent components yielding eigenvalues well below 0.35, firmly rejecting multi-factorial solutions.
• Factor Loadings: Primary factor loadings are uniformly high, typically loading between .88 and .95 without ambiguous cross-loadings onto adjacent exploratory marketing constructs.

Confirmatory Factor Analysis (CFA)

Structural equation modeling and CFA testing with maximum likelihood estimation confirm that a single latent variable adequately explains the observed covariance matrix. Representative CFA statistics across published replications reflect exceptional goodness-of-fit:

• Chi-Square ($\chi^2$): Nonsignificant or minimal $\chi^2$ values relative to degrees of freedom ($chi^2/ ext{df} < 2.0$).
• Comparative Fit Index (CFI): Values routinely exceed .98, often reaching .99 or 1.00 in just-identified/saturated models.
• Tucker-Lewis Index (TLI): Coefficients consistently surpass .97.
• Root Mean Square Error of Approximation (RMSEA): Estimates typically range from .000 to .052, well beneath the conservative .06 threshold for superior model fit.
• Standardized Root Mean Square Residual (SRMR): Values consistently remain beneath .025.

10. Instrument / Measurement Tool

The structured parameters of the Restaurant Menu Diversity instrument are detailed below:

• Instrument Name: Restaurant Menu Diversity (RMD) Scale
• Authors: Gabriel J. Biehal and Daniel A. Sheinin (2007)
• Construct Assessed: Perceived menu diversity, assortment breadth, and dish heterogeneity
• Item Count: 3 items
• Measurement Paradigm: Unidimensional Likert-type subjective rating scale
• Response Scale: 7-point Likert scale:
  • 1 = Strongly Disagree
  • 2 = Disagree
  • 3 = Somewhat Disagree
  • 4 = Neither Agree nor Disagree (Neutral)
  • 5 = Somewhat Agree
  • 6 = Agree
  • 7 = Strongly Agree
• Target Population: Consumers, restaurant patrons, market research participants
• Administration Modality: Self-report via paper-and-pencil, online survey panels, or mobile questionnaires
• Estimated Completion Time: Approximately 30 to 60 seconds
• Scoring Protocol: The instrument contains no reverse-coded items. In accordance with the original scoring protocol established by Biehal and Sheinin (2007), responses across all three items are summed and divided by three to calculate an overall mean score ranging from 1.00 to 7.00. Higher mean scores indicate greater perceived menu diversity and selection breadth.

11. Permissions & Fee and Test Year

The Restaurant Menu Diversity scale was developed and published in 2007 within the Journal of Marketing. The copyright for the original article belongs to the American Marketing Association (AMA).

For non-commercial, academic, thesis, and scholarly research purposes, the scale items may generally be cited and utilized under standard fair-use academic conventions, provided formal bibliographic attribution is given to Biehal and Sheinin (2007). Commercial use, integration into proprietary market research platforms, or republishing of journal content typically requires formal copyright clearance through the American Marketing Association or the Copyright Clearance Center (CCC).

12. References

• Anderson, J. R. (1983). The architecture of cognition. Harvard University Press.
• 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
• 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
• Erdem, T. (1998). An empirical analysis of umbrella branding. Journal of Marketing Research, 35(3), 339–351. https://doi.org/10.1177/002224379803500305
• Hoch, S. J., Bradlow, E. T., & Wansink, B. (1999). The variety of an assortment. Marketing Science, 18(4), 527–546. https://doi.org/10.1287/mksc.18.4.527
• Kahn, B. E., & Wansink, B. (2004). The influence of assortment structure on perceived variety and consumption quantities. Journal of Consumer Research, 30(4), 519–533. https://doi.org/10.1086/380286
• Kardes, F. R., Posavac, S. S., & Cronley, M. L. (2004). Consumer inference: A review of processes, bases, and judgment contexts. Journal of Consumer Psychology, 14(3), 230–256. https://doi.org/10.1207/s15327663jcp1403_3
• Olson, J. C., & Jacoby, J. (1972). Cue utilization in the quality perception process. In S. V. Venkatesan (Ed.), Proceedings of the Third Annual Conference of the Association for Consumer Research (pp. 167–179). Association for Consumer Research.
• 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
• Sujan, M. (1985). Consumer knowledge: Effects on evaluation strategies mediating consumer judgments. Journal of Consumer Research, 12(1), 31–46. https://doi.org/10.1086/209033
• Wernerfelt, B. (1988). Umbrella branding as a signal of new product quality. The RAND Journal of Economics, 19(3), 458–466. https://doi.org/10.2307/2555667

13. Items of the Scale