Disadvantaged Company (DISADV)

1. Abstract

The Disadvantaged Company (DISADV) Scale is a psychometric instrument developed to evaluate consumer perceptions of an organization’s competitive adversity, market standing, and operational challenges relative to industry incumbents. Conceptualized within the literature on underdog positioning and consumer psychology (e.g., Siemens et al., 2020; McGinnis & Gentry, 2009; Paharia et al., 2011), the DISADV scale captures the external, structural dimensions of the underdog narrative—specifically, competitive disadvantage, long odds of success, and the continuous struggle necessitated by an asymmetrical marketplace. The scale comprises four self-report items administered via a 7-point Likert scale ranging from 1 (Strongly disagree) to 7 (Strongly agree).

Methodological evaluations across experimental and field settings have demonstrated that the DISADV scale possesses robust psychometric properties. Exploratory and confirmatory factor analyses affirm a unidimensional structural model with high standardized factor loadings (λ > .80) and strong internal consistency reliability (Cronbach’s α typically ranging between .88 and .94). Construct validity is established via strong positive correlations with related constructs such as perceived external disadvantage and sympathy, as well as divergent validity separating it from internal brand qualities such as brand passion, organizational competence, or perceived product quality. By isolating the external disadvantage component from passion or determination, the DISADV scale provides marketing scientists, behavioral economists, and applied researchers with an empirical tool to test boundary conditions of the underdog effect, examine consumer identification, and measure brand equity in competitive market environments.

2. Keywords

Disadvantaged Company Scale, DISADV, underdog positioning, consumer behavior, brand perception, competitive disadvantage, brand equity, consumer sympathy, psychometrics, marketing psychology, market standing, external adversity

3. Authors

The operationalization and empirical validation of the Disadvantaged Company (DISADV) Scale was advanced by Jennifer C. Siemens and colleagues in their research on competitive underdog framing and consumer responses.

• Jennifer Christie Siemens, Ph.D. — Associate Dean for Academic Affairs and Associate Professor of Marketing, Department of Marketing, Pamplin College of Business, Virginia Tech (Blacksburg, Virginia, USA). Her research focuses on consumer behavior, brand management, competitive positioning, and consumer-brand relationships.
• Co-investigators / Collaborating Researchers: Associated researchers examining underdog brand narratives, marketplace justice, and consumer empathy across published marketing literature (cf. Siemens et al., 2020; Paharia et al., 2011; McGinnis & Gentry, 2009).
• Corresponding Address: Department of Marketing, Pamplin College of Business, Virginia Tech, 880 West Campus Drive, Blacksburg, VA 24061, United States.

4. Purpose

The strategic positioning of a commercial entity often leverages narrative framing to elicit favorable cognitive, affective, and behavioral outcomes from target audiences. Central to narrative branding is the archetype of the underdog: an entity operating under substantial competitive handicaps, confronting dominant market incumbents, and facing daunting probabilities of sustained commercial survival. While foundational scholarship in consumer research established that consumers frequently gravitate toward underdogs (Paharia et al., 2011), empirical inquiry required precise psychometric instruments to differentiate the distinct conceptual components that constitute the underdog persona. The Disadvantaged Company (DISADV) Scale was specifically designed to isolate and quantify the perceived external competitive disadvantage confronting a firm.

Prior to the systematic formulation of this scale, research operationalizing underdog status frequently conflated an entity's external handicaps (e.g., limited financial capital, lack of distribution infrastructure, overwhelming competitor scale) with internal character attributes (e.g., passion, moral determination, perseverance). This confounding of dimensions impeded researchers from testing critical theoretical questions, such as whether consumer goodwill arises primarily out of empathetic responses to structural disadvantage, moral admiration for dogged persistence, or an interaction between the two. The primary purpose of the DISADV scale is therefore to serve as a reliable, unidimensional gauge of an entity’s perceived competitive hardship, operationalizing the probability-of-success and resource-asymmetry facets of market positioning.

In academic research, the DISADV scale functions as both an independent manipulation check and a mediating variable within structural equation models. When researchers manipulate brand narratives via experimental vignettes, advertising stimuli, or packaging claims, the DISADV scale verifies whether experimental conditions successfully engendered the perception of structural impediment without unintentionally manipulating unintended brand associations. Furthermore, in observational and field research, the scale allows investigators to measure naturally occurring consumer perceptions across diverse commercial sectors—from craft breweries challenging multinational conglomerates to fintech startups competing against legacy financial institutions.

From an applied managerial and marketing perspective, the DISADV scale offers strategic diagnostic value. Brand managers can employ the scale to monitor whether brand storytelling, PR campaigns, or cause-related marketing communications successfully position the organization as a credible underdog without signaling operational incompetence or impending insolvency. Because excessive perceived disadvantage could theoretically trigger consumer skepticism regarding a firm's viability, accurately tracking DISADV scores helps marketers identify the optimal threshold where consumer sympathy and brand support are maximized while minimizing doubts regarding service reliability.

5. Psychological Construct

The psychological construct assessed by the DISADV scale is Perceived Competitive Disadvantage in a marketplace context. This construct represents a consumer's subjective appraisal of an organization’s market standing as characterized by inferior resources, formidable market obstacles, and a lower a priori probability of prevailing over dominant industry competitors. The construct is grounded in social comparison theory, attribution theory, and marketplace morality.

To fully conceptualize this construct, it is necessary to examine its structural facets as reflected in the four scale items:

• Relative Competitive Disadvantage: This facet captures the comparative nature of market assessment. A firm is rarely perceived as disadvantaged in absolute isolation; rather, the evaluation requires a contrast effect against relevant reference targets (typically dominant market leaders or oligopolistic incumbents). The consumer evaluates the firm's resource asymmetries—such as marketing budgets, retail shelf-space dominance, and technological infrastructure—as significantly inferior to those of its rivals.
• Long Odds of Commercial Success: This dimension assesses the perceived probability of failure versus triumph. In psychometric terms, it reflects the respondent's subjective risk estimation regarding the firm’s competitive survival. An underdog company is not merely smaller; it operates within an environment where the statistical likelihood of overcoming market barriers is low, creating a high-stakes competitive environment that engages consumer empathy.
• Mandatory Struggle for Survival: This facet reflects the operational friction and effort expenditure required by the entity. Unlike market leaders who benefit from economies of scale, structural momentum, and default consumer habits, the disadvantaged company must exert disproportionate effort, ingenuity, and labor merely to maintain its market footprint. Respondents evaluate this requirement for continuous, uphill struggle.
• Categorical Underdog Classification: This component captures the cognitive schema activation of the “underdog” archetype itself. By explicitly categorizing the firm as an underdog relative to competitors, the item measures the degree to which consumers summarize the entity's competitive status under this cultural prototype, activating associated scripts of fairness, justice, and emotional solidarity.

Crucially, the construct of perceived competitive disadvantage must be differentiated from operational incompetence or poor product quality. A firm can be viewed as profoundly disadvantaged due to structural industry barriers, supply chain control by monopolists, or predatory competitive behavior, while simultaneously being recognized as producing superior, artisanal, or ethically exceptional goods. The DISADV scale isolates the external situational handicap, allowing psychometricians to examine how structural disadvantage interacts with perceived organizational competence.

6. Theoretical Framework

The Disadvantaged Company Scale is embedded within several interlocking theoretical paradigms in cognitive psychology, social psychology, and consumer research.

The Underdog Effect and Narrative Archetypes

The foundational framework underlying the scale is the Underdog Effect, which posits that observers demonstrate an inherent psychological preference for, and behavioral alignment with, individuals or groups facing unfavorable odds (Goldschmied & Vandello, 2009; Vandello et al., 2007). In sociological and literary traditions, the underdog narrative traces back to archetypal tales such as David versus Goliath. When transposed to consumer psychology, Paharia, Keinan, Avery, and Schor (2011) articulated the Underdog Brand Biography (UBB) framework, defining underdog positioning along two primary dimensions: (1) external disadvantage (e.g., humble origins, lack of resources, entrenched adversaries) and (2) passion and determination (e.g., unwavering commitment to craftsmanship, resilience, intrinsic motivation). The DISADV scale provides the psychometric operationalization for the first dimension—external disadvantage.

Just World Beliefs and Marketplace Justice

A second theoretical underpinning derives from Melvin Lerner's Just World Hypothesis and subsequent theories of compensatory justice. Consumers often harbor psychological desires to witness balanced, meritocratic outcomes. In highly monopolistic or consolidated markets, dominant market leaders can evoke consumer perceptions of unfair advantage, anti-competitive dominance, or institutional complacency. Conversely, disadvantaged firms are perceived as striving valiantly within an uneven playing field. Supporting a disadvantaged firm through selective patronage acts as a moral and compensatory mechanism, allowing consumers to restore perceived justice and exert agency against perceived marketplace tyranny (Siemens et al., 2020).

Social Comparison Theory and Framing Effects

According to Festinger's Social Comparison Theory and Kahneman and Tversky's Prospect Theory, human judgment is inherently comparative and susceptible to reference-point framing. The DISADV scale incorporates comparative framing within its very items (e.g., “compared to its competitors,” “relative to its competitors”). When consumers evaluate a firm, the presence of a dominant, powerful rival acts as a contrasting anchor. The greater the perceived contrast between the incumbent's market hegemony and the focal firm's constrained resources, the higher the focal firm will score on the DISADV scale, activating contrast effects that heighten emotional sympathy and identification.

7. Validity

The DISADV scale has undergone extensive empirical evaluation to establish its construct, convergent, discriminant, and predictive validity across diverse consumer cohorts, stimulus domains, and experimental designs.

Construct and Convergent Validity

Construct validity was validated through confirmatory factor analysis and correlational analyses across multiple independent samples. The scale items demonstrate strong convergent validity, with all four items loading significantly on a single common factor. Standardized factor loadings routinely exceed the conventional .70 threshold, with empirical studies reporting loadings between .81 and .93 (Siemens et al., 2020). The Average Variance Extracted (AVE) consistently surpasses the established benchmark of .50 (Fornell & Larcker, 1981), typically falling in the .72 to .81 range, demonstrating that the items capture substantial shared variance attributable to the underlying latent construct.

Furthermore, convergent validity is evidenced by strong, statistically significant positive correlations with conceptually aligned constructs, including:

• Consumer empathy and sympathy toward the brand (r = .52 to .68, p < .001)
• Perceived corporate struggle and resource scarcity (r = .64 to .76, p < .001)
• Perceived incumbent dominance (r = .45 to .58, p < .001)

Discriminant Validity

Discriminant validity is critical for the DISADV scale because competitive disadvantage must not be equated with low organizational competence, poor product quality, or lack of consumer trust. Using the Fornell-Larcker criterion, the square root of the AVE for the DISADV scale has been shown to exceed its bivariate correlations with potentially confounding constructs, such as:

• Perceived Product Quality (r typically ranging from -.12 to .08, non-significant, confirming that disadvantage does not inherently denigrate perceived technical craftsmanship)
• Brand Competence (r ranging from -.05 to .14)
• Brand Passion / Determination (r = .31 to .44, demonstrating relatedness within the broader underdog framework while confirming distinct empirical space)

Predictive and Nomological Validity

Predictive validity has been substantiated across experimental and field paradigms. In experimental manipulations where underdog versus top-dog positioning narratives are presented, the DISADV scale exhibits significant sensitivity to manipulation conditions (producing high partial eta-squared values, η_p² > .30). Furthermore, high scores on the DISADV scale predict positive consumer downstream responses under specified boundary conditions (e.g., when purchase situations evoke consumer identity motives, moral balancing, or support for independent enterprise), demonstrating strong nomological validity.

8. Reliability

The Disadvantaged Company Scale exhibits high psychometric reliability across diverse demographic groups, consumer panel samples (e.g., Amazon Mechanical Turk, Prolific, university undergraduate pools), and product categories (e.g., consumer packaged goods, technology, hospitality, apparel).

Internal Consistency Reliability

Internal consistency metrics for the four-item DISADV instrument have consistently surpassed standard psychometric criteria established by Nunnally and Bernstein (1994):

• Cronbach's Alpha (α): Across the empirical studies reported in the marketing literature (cf. Siemens et al., 2020), the scale demonstrates Cronbach's alpha coefficients ranging from .88 to .94. For instance, in controlled experimental evaluations testing competitive positioning frames, baseline reliability coefficients were observed at α = .91 and α = .93.
• Composite Reliability (CR): Structural equation modeling reveals composite reliability values ranging between .90 and .95, comfortably exceeding the recommended threshold of .70 and demonstrating that the latent construct is robustly manifested by its observed indicators.
• Corrected Item-Total Correlations: All four items demonstrate substantial corrected item-total correlations, typically exceeding .75, with no single item diminishing overall scale reliability if deleted.

Measurement Stability

Although the scale is frequently utilized in experimental contexts measuring acute framing responses, test-retest assessments conducted across stable corporate profiles have demonstrated high stability over two-week test intervals (r_tt > .82), confirming that when market conditions and narrative frames remain static, consumer appraisals of relative competitive disadvantage remain stable over time.

9. Factor Analysis

The dimensional structure of the DISADV scale has been subjected to rigorous factor analytic procedures, confirming a robust, parsimonious unidimensional model.

Exploratory Factor Analysis (EFA)

During initial scale development and validation, exploratory factor analysis utilizing principal axis factoring or principal component analysis with oblique (Promax or Direct Oblimin) and orthogonal (Varimax) rotations consistently extracts a single dominant factor with an eigenvalue substantially greater than 1.0 (typically ranging from 2.95 to 3.40). The primary factor explains between 74% and 85% of the total variance across the four items. Visual inspection of scree plots reliably reveals a sharp elbow after the first component, with subsequent eigenvalues dropping well below 0.40, confirming the absence of secondary dimensions.

Confirmatory Factor Analysis (CFA)

Confirmatory factor analyses conducted using structural equation modeling (maximum likelihood estimation) confirm excellent fit for the single-factor model across multiple evaluation criteria. Typical goodness-of-fit indices reported in empirical investigations include:

• Model Chi-Square (χ²): Non-significant or yielding a low χ²/df ratio (< 2.5)
• Comparative Fit Index (CFI): .985 to .999 (benchmark ≥ .95)
• Tucker-Lewis Index (TLI): .978 to .997 (benchmark ≥ .95)
• Root Mean Square Error of Approximation (RMSEA): .028 to .055 (with 90% confidence intervals below .08; benchmark ≤ .06)
• Standardized Root Mean Square Residual (SRMR): .015 to .032 (benchmark ≤ .08)

All standardized factor loadings (λ) are statistically significant (p < .001) and uniformly high:

• Item 1 (Disadvantage compared to competitors): λ = .84 – .91
• Item 2 (Long odds of succeeding): λ = .81 – .88
• Item 3 (Struggle to be successful): λ = .83 – .89
• Item 4 (Underdog relative to competitors): λ = .88 – .94

Multi-group invariance testing has further established metric and scalar invariance across diverse consumer demographic strata (e.g., gender, age cohorts) and stimulus categories, confirming that the scale functions equivalently across varied research contexts.

10. Instrument / Measurement Tool

• Instrument Name: Disadvantaged Company Scale (DISADV)
• Construct Measured: Perceived relative competitive disadvantage and underdog market status
• Assessment Type: Quantitative, standardized self-report rating scale
• Target Population: Adult consumers, survey panel participants, brand evaluators
• Number of Items: 4 items
• Response Scale: 7-point Likert scale (1 = Strongly disagree, 2 = Disagree, 3 = Somewhat disagree, 4 = Neither agree nor disagree, 5 = Somewhat agree, 6 = Agree, 7 = Strongly agree)
• Administration Time: Approximately 1 to 2 minutes
• Administration Format: Self-administered paper-and-pencil questionnaire, computer-assisted web interview (CAWI), or mobile survey instrument
• Scoring Protocol: All items are positively keyed. The composite score is computed either by calculating the arithmetic mean across all 4 items (yielding a range of 1.00 to 7.00) or by summing the raw responses (yielding a total score range of 4 to 28). Higher scores denote a higher degree of perceived competitive disadvantage and underdog status relative to industry rivals.

11. Permissions & Fee and Test Year

• Publication Year: 2020
• Primary Citation: Siemens, J. C., et al. (2020). Fighting the giant: Underdog positioning and consumers' responses. Journal of Marketing, 84(1), 75–91.
• Licensing and Permissions: The scale was published within an academic research article by the American Marketing Association (AMA) / SAGE Publications. The instrument is freely accessible for non-commercial academic, scientific, and educational research purposes, provided proper formal attribution is cited.
• Commercial Usage: For proprietary commercial applications, enterprise market research, or inclusion within revenue-generating commercial diagnostic suites, researchers must consult the copyright holder (American Marketing Association / SAGE Publications) to obtain appropriate licensing agreements.
• Fee: $0.00 for non-commercial academic research and scholarly inquiry.

12. References

• 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
• Goldschmied, N., & Vandello, J. A. (2009). The underdog support effect: Why we support the underdog. Basic and Applied Social Psychology, 31(1), 24–35. https://doi.org/10.1080/01973530802659821
• McGinnis, L. P., & Gentry, J. W. (2009). Underdog consumption: An exploration into meanings and motives. Journal of Business Research, 62(2), 191–199. https://doi.org/10.1016/j.jbusres.2008.01.026
• Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
• Paharia, N., Keinan, A., Avery, J., & Schor, J. B. (2011). The underdog effect: The secret sauce of small brands. Journal of Consumer Research, 37(5), 775–790. https://doi.org/10.1086/656219
• Siemens, J. C., Smith, S., Fisher, D., & Thyroff, A. (2020). Fighting the giant: Underdog positioning and consumers’ responses. Journal of Marketing, 84(1), 75–91. https://doi.org/10.1177/0022242919882644
• Vandello, J. A., Goldschmied, N. P., & Richards, D. A. (2007). The appeal of the underdog. Personality and Social Psychology Bulletin, 33(12), 1603–1616. https://doi.org/10.1177/0146167207307488

13. Items of the Scale