Skepticism of Claim (SOC)

1. Abstract

The Skepticism of Claim (SOC) scale is a specialized, unidimensional psychometric instrument developed by Abhijit Biswas, Sujay Dutta, and Chris Pullig (2006) to measure situational cognitive doubt regarding marketing claims. Originating in empirical consumer psychology and retail pricing research, the scale assesses the degree to which a consumer perceives a specific promotional assertion—such as a low price guarantee (LPG), an environmental benefit claim, or an advertising superlative—as exaggerated, untruthful, or intentionally deceptive. Unlike broad dispositional measures of consumer cynicism or generalized skepticism toward advertising, the SOC scale captures state-level, claim-specific cognitive evaluations formed during marketing communications exposure.

Comprising three carefully refined items, the instrument utilizes a standard 7-point Likert response format ranging from 1 (Strongly Disagree) to 7 (Strongly Agree). Responses are averaged to produce a composite index where higher numerical scores indicate greater perceived deceit and skepticism. Across initial validation studies and subsequent replications in consumer behavior, marketing analytics, and behavioral economics, the SOC scale demonstrates robust psychometric properties. The instrument consistently yields strong internal consistency reliability, with Cronbach’s alpha (α) values routinely exceeding .85 and composite reliability (CR) values surpassing .88. Exploratory and confirmatory factor analyses confirm a strictly unidimensional structure, explaining upwards of 75% of the total variance across diverse experimental settings. Furthermore, the scale demonstrates rigorous convergent, discriminant, and predictive validity, showing anticipated theoretical relationships with store price image, perceived deception, purchase intentions, information search behavior, and regulatory focus. This paper provides an exhaustive academic exposition of the SOC scale, detailing its theoretical foundations, psychometric architecture, administration protocol, and practical implications for marketing science and behavioral research.

2. Keywords

Skepticism of Claim, SOC scale, consumer skepticism, advertising skepticism, low price guarantees, perceived deception, persuasion knowledge model, signaling theory, psychometrics, marketing communications, consumer psychology, retail pricing

3. Authors

The Skepticism of Claim (SOC) scale was developed and psychometrically validated by a collaborative team of scholars in marketing and consumer psychology:

• Abhijit Biswas, Ph.D. — Kmart Corporation Chair in Marketing and Professor of Marketing, Department of Marketing, E. J. Ourso College of Business, Louisiana State University, Baton Rouge, Louisiana, USA. Dr. Biswas is an internationally recognized scholar in consumer information processing, pricing strategies, retail advertising effectiveness, and behavioral decision theory.
• Sujay Dutta, Ph.D. — Professor of Marketing, Department of Marketing, Mike Ilitch School of Business, Wayne State University, Detroit, Michigan, USA. Dr. Dutta specializes in behavioral pricing, reference price phenomena, price matching guarantees, and consumer perceptions of market signals.
• Chris Pullig, Ph.D. — Professor of Marketing and Chair of the Department of Marketing, Hankamer School of Business, Baylor University, Waco, Texas, USA. Dr. Pullig’s research centers on consumer attitudes, brand equity, marketing ethics, deceptive advertising, and consumer response to negative brand publicity.

4. Purpose

The primary purpose of the Skepticism of Claim (SOC) scale is to provide a parsimonious, psychometrically sound, and diagnostically sensitive instrument to capture situational consumer skepticism directed toward a specific promotional claim. In market environments characterized by aggressive promotional cues, comparative advertising, and promotional warranties, firms frequently deploy declarative assertions to signal superior value, ethical stewardship, or performance superiority. A critical challenge for researchers and practitioners is determining whether consumers accept these claims at face value or discount them as deceptive marketing tactics.

Prior to the introduction of the SOC scale, empirical investigations into consumer doubt predominantly relied upon generalized measures, such as the Scale of Skepticism Toward Advertising in General (SKEP) introduced by Obermiller and Spangenberg (1998). While dispositional advertising skepticism scales effectively capture enduring consumer cynicism across broad media formats, they lack the granularity and contextual sensitivity required to measure immediate, stimulus-induced skepticism elicited by a specific promotional cue, such as a “lowest price guarantee,” an organic product label, or an energy-efficiency benchmark. The SOC scale was formulated to bridge this methodological gap, providing researchers with an agile tool capable of detecting micro-level shifts in cognitive appraisal when experimental conditions, claim framing, contextual signals, or market environments are manipulated.

In academic and applied consumer research, the SOC scale fulfills multiple crucial analytical functions:

• Evaluation of Retail Price Cues and Guarantees: The scale allows researchers to examine how consumers process low price guarantees (LPGs), refund policies, and “price match” assurances under varying conditions of perceived price dispersion, store reputation, and product category risk.
• Mediation and Moderation Modeling: The SOC scale serves as an essential mediator in psychological models tracing the pathway from marketing signals to consumer behavioral outcomes, such as information search effort, cognitive dissonance, store patronage, and ultimate willingness to pay.
• Deceptive and Exaggerated Advertising Research: Regulatory bodies, such as the Federal Trade Commission (FTC), and consumer advocacy organizations can utilize the SOC instrument to empirically evaluate whether marketing claims transgress the boundary between standard promotional puffery and actionable consumer deception.
• Public Policy and Sustainable Marketing: As green marketing and corporate social responsibility (CSR) claims proliferate, the SOC scale provides an empirical framework for measuring consumer backlash against suspected “greenwashing” or disingenuous brand declarations.

5. Psychological Construct

The psychological construct captured by the SOC scale is situational claim skepticism, defined as a consumer’s subjective state of doubt, disbelief, and cognitive discounting regarding the veracity, accuracy, and motives underlying a specific marketing assertion. This construct represents an acute, event-based cognitive reaction rather than a stable, enduring personality trait. To comprehend the operational boundaries of this construct, it is necessary to examine its structural properties, psychological mechanisms, and conceptual distinctions from adjacent cognitive phenomena.

5.1 Structural Dimensions of Claim Skepticism

Although the SOC scale is unidimensional in its mathematical representation, the construct encompasses three distinct but highly interrelated cognitive judgments:

• Perceived Exaggeration: The cognitive appraisal that the marketer’s claim overstates reality, inflates actual product or pricing benefits, or uses hyperbole beyond reasonable boundaries. Perceived exaggeration captures the subjective gap between the advertised promise and anticipated performance.
• Perceived Falsity (Objective Inaccuracy): The direct assessment that the factual content of the claim is incorrect, untrue, or unsupported by market conditions. This reflects an explicit probabilistic judgment regarding the absolute truth-value of the assertion.
• Perceived Deceptive Intent (Manipulative Motive): The attribution of deliberate intent to mislead, obfuscate, or exploit the consumer. This element introduces an intentionality attribution, wherein the consumer perceives the marketer not merely as mistaken, but as engaging in strategic opportunistic communication.

5.2 Conceptual Delineation: State vs. Trait Skepticism

It is psychometrically imperative to differentiate the construct measured by the SOC scale from related constructs across the skepticism-cynicism continuum:

• Dispositional Advertising Skepticism: A generalized, enduring disbelief in advertising across formats and industries, reflecting a broad consumer socialization trait (Obermiller & Spangenberg, 1998). In contrast, SOC represents a state variable that fluctuates dramatically based on specific claim attributes, source credibility, and contextual framing.
• Consumer Cynicism: A broad socio-cultural worldview holding that business entities are fundamentally exploitative, self-serving, and devoid of ethical standards. Cynicism is stable across contexts, whereas SOC can be low even for a cynical consumer if a claim is accompanied by a transparent, easily verifiable signal.
• Perceived Risk: A forward-looking expectation of negative utility or adverse physical, financial, or social outcomes resulting from a purchase decision. While high claim skepticism frequently inflates perceived risk, the two constructs are conceptually distinct: skepticism evaluates communicative integrity, whereas risk evaluates product outcome severity.

6. Theoretical Framework

The conceptual architecture of the Skepticism of Claim scale is grounded in three dominant theoretical paradigms within cognitive psychology, information processing, and microeconomics: the Persuasion Knowledge Model, Signaling Theory, and Attribution Theory.

6.1 The Persuasion Knowledge Model (PKM)

Introduced by Friestad and Wright (1994), the Persuasion Knowledge Model posits that over time, consumers accumulate an extensive repertoire of beliefs and theories regarding the persuasion tactics utilized by marketers. This persuasion knowledge enables consumers to recognize when an attempt at behavioral influence is taking place, decipher the underlying goals of the communicator, and deploy coping strategies to preserve cognitive autonomy.

Within this framework, the SOC scale measures the immediate output of the consumer’s activated persuasion knowledge. When confronted with an aggressive marketing assertion—such as a guarantee that a store possesses the lowest market price—the consumer’s cognitive processing shifts from heuristic acceptance to critical scrutiny. If the claim triggers persuasion knowledge coping mechanisms, the individual interprets the assertion not as an objective informational service, but as an engineered psychological lever designed to arrest competitive search. The items in the SOC scale operationalize this activated defense mechanism by measuring whether the consumer views the claim as an exaggerated or misleading tactic.

6.2 Signaling Theory

Originating in information economics (Spence, 1973), Signaling Theory addresses markets characterized by information asymmetry, wherein sellers possess superior knowledge regarding product quality or pricing relative to buyers. To bridge this information gap, sellers emit signals—observable market actions that convey underlying unobservable characteristics. For a signal to be credible and effective, it must possess sufficient signal cost, meaning it must be economically irrational for a low-quality seller to mimic a high-quality seller’s signal.

In Biswas, Dutta, and Pullig’s (2006) foundational study, low price guarantees (LPGs) were examined as signals of a firm’s lowest price status. When market price dispersion is high, consumers intuitively understand that a low price guarantee carries substantial exposure risk for the retailer, rendering the signal costly and therefore credible. Under such conditions, claim skepticism remains low. Conversely, when perceived price dispersion is low or the penalty for false signaling is negligible, consumers perceive the signal as costless cheap talk, leading to elevated scores on the SOC scale. The scale thus captures the psychological failure of an unconvincing market signal.

6.3 Attribution Theory

Grounded in the foundational work of Fritz Heider and expanded by Harold Kelley, Attribution Theory explains how individuals attribute causal factors to observable behaviors and environmental stimuli. In marketing interactions, consumers engage in spontaneous attributional processing to discern why a retailer is making a specific claim.

Consumers choose between two primary attributional pathways:

• Internal / Communicator Attribution: The consumer attributes the claim to genuine firm characteristics (e.g., operational efficiency, competitive supply chains, superior quality, customer orientation). This yields minimal claim skepticism.
• Manipulative / Situational Attribution: The consumer attributes the claim to a deceptive attempt to exploit consumer inertia, minimize comparison shopping, or manipulate price perceptions. The SOC scale directly indexes this manipulative attribution by assessing whether the retailer is “trying to mislead” the consumer.

7. Validity

The psychometric validity of the SOC scale has been rigorously evaluated through construct, convergent, discriminant, and predictive (nomological) validation procedures across experimental and correlational investigations.

7.1 Construct and Convergent Validity

Construct validity evaluates how well an instrument reflects its underlying conceptual foundation. In Biswas et al. (2006), convergent validity was demonstrated through standardized factor loadings obtained in confirmatory factor models. All three items loaded significantly onto the focal construct, with standardized parameter estimates exceeding .80 (ranging from .82 to .91, p < .001). The Average Variance Extracted (AVE) systematically exceeded the recommended .50 threshold established by Fornell and Larcker (1981), demonstrating that the scale captures more construct-specific variance than measurement error.

7.2 Discriminant Validity

Discriminant validity requires that the measure does not correlate excessively with theoretically distinct constructs. In retail pricing environments, claim skepticism must be empirically distinguishable from generalized ad skepticism, store price image, and consumer value consciousness. Applying the Fornell-Larcker criterion, the square root of the AVE for the SOC scale substantially exceeded the inter-construct correlation between SOC and related latent variables across all experimental conditions (correlations rarely exceeded r = .45, whereas the square root of the AVE exceeded .85). This confirms that situational claim skepticism is distinct from general consumer cynicism or brand-level negative sentiment.

7.3 Predictive and Nomological Validity

The SOC scale exhibits superior nomological and predictive validity across diverse retail and promotional experiments:

• Interaction Effects: Biswas, Dutta, and Pullig (2006) demonstrated that claim skepticism operates as a critical moderating or mediating variable in the relationship between price guarantees and store price perceptions. When perceived price dispersion was low, the presence of a low price guarantee paradoxically heightened claim skepticism (F-values demonstrating statistical significance at p < .01), which subsequently suppressed favorable store price perceptions.
• Consumer Search Behavior: Higher SOC scores directly predict increased post-exposure information search effort, as skeptical consumers feel compelled to verify assertions independently across competitor websites or consumer review portals.
• Purchase and Behavioral Intentions: In mediation analyses, elevated claim skepticism consistently exerts a robust negative direct effect on patronage intentions and purchase likelihood (standardized β coefficients typically ranging from -.35 to -.52).

8. Reliability

The SOC scale demonstrates consistently high internal consistency reliability across multiple consumer cohorts, experimental manipulations, and product categories.

8.1 Internal Consistency Metrics

In the seminal validation by Biswas, Dutta, and Pullig (2006), the three-item instrument achieved high internal consistency:

• Cronbach’s Alpha (α): Reported coefficients for the scale across experimental studies routinely ranged between .85 and .92, well above the conventional academic benchmark of .70 recommended by Nunnally and Bernstein (1994).
• Composite Reliability (CR): Structural equation modeling evaluations report composite reliability figures exceeding .88, indicating minimal measurement error in the composite score.
• Item-Total Correlations: Corrected item-to-total correlations for each of the three manifest items consistently surpass .70, demonstrating that each statement contributes significantly to the overall construct measurement without redundancy.

8.2 Temporal and Contextual Stability

Because the SOC scale is explicitly designed to capture a state response to an external stimulus, classical test-retest reliability over long intervals is conceptually inapplicable (as state skepticism shifts immediately upon the provision of new contextual information). However, split-sample cross-validation and multi-group invariance tests across different product categories (e.g., consumer electronics, apparel, and durable goods) confirm that the measurement model remains metric and scalar invariant, showing consistent statistical behavior across varied experimental stimuli.

9. Factor Analysis

The factorial validity of the SOC scale has been evaluated using both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), confirming a strictly parsimonious, unidimensional structural model.

9.1 Exploratory Factor Analysis (EFA)

In initial exploratory factor extraction (using Principal Axis Factoring with orthogonal or oblique rotations), all three manifest variables load unequivocally onto a single primary factor with an eigenvalue significantly greater than 1.0 (typically ranging between 2.15 and 2.45). This dominant factor accounts for approximately 72% to 81% of the total explained variance across datasets. Scree plot visual analysis reveals an unmistakable single-factor “elbow,” with no secondary factors approaching an eigenvalue of 0.60. Communalities for all three items consistently exceed .65, affirming that each item shares substantial common variance with the underlying latent factor.

9.2 Confirmatory Factor Analysis (CFA)

Structural equation modeling and CFA procedures verify the single-factor specification. Because a three-item measurement model with zero correlated errors is mathematically just-identified (zero degrees of freedom), goodness-of-fit indices are conventionally evaluated when the SOC scale is modeled alongside other latent constructs within a multi-factor structural model. In these nomological network CFA evaluations, the SOC scale consistently generates excellent global fit metrics:

• Comparative Fit Index (CFI): ≥ .98
• Tucker-Lewis Index (TLI): ≥ .97
• Root Mean Square Error of Approximation (RMSEA): ≤ .05 (90% CI: [.000, .078])
• Standardized Root Mean Square Residual (SRMR): ≤ .03

10. Instrument / Measurement Tool

The SOC scale is designed for efficient, self-administered integration into laboratory experiments, online surveys, and field research protocols. Below are the administrative specifications:

• Instrument Name: Skepticism of Claim (SOC) Scale
• Target Construct: Situational cognitive skepticism and perceived deception regarding a specific marketing claim
• Item Count: 3 items
• Scale Structure: Strictly unidimensional
• Administration Format: Self-administered online questionnaire, paper-and-pencil instrument, or mobile consumer survey
• Target Population: Consumers, experimental research participants, retail shoppers, and digital platform users (ages 18 and older)
• Completion Duration: Under 1 minute (approximately 30 to 45 seconds)
• Response Scale: 7-point Likert scale (1 = Strongly Disagree to 7 = Strongly Agree)
• Scoring and Index Calculation:
  • All three items are positively worded in the direction of skepticism; there are no reverse-coded items.
  • An overall continuous claim skepticism score is calculated by taking the arithmetic mean of the three responses:
    SOC Score = (Item 1 + Item 2 + Item 3) / 3
  • Composite scores range from 1.00 to 7.00, with higher scores reflecting greater skepticism, perceived deceit, and cognitive discounting of the marketing assertion.

11. Permissions & Fee and Test Year

The Skepticism of Claim scale was originally published in 2006 in the peer-reviewed scholarly journal Journal of Retailing:

• Year of Publication: 2006
• Copyright Holder: © 2006 New York University. Published by Elsevier Inc. on behalf of the Journal of Retailing.
• Academic Research Usage & Fee: The scale items were published within an academic article for open scholarly evaluation. In standard academic practice, researchers and university scholars may freely adapt, reproduce, and administer the SOC scale for non-commercial educational, scientific, and empirical research purposes without paying royalty fees, provided full academic attribution is cited to Biswas, Dutta, and Pullig (2006).
• Commercial Applications: Commercial entities, proprietary research platforms, or corporate consulting firms intending to embed the instrument into proprietary measurement batteries should verify copyright permissions through Elsevier’s RightsLink permissions service or contact the authors directly.

12. References

The following academic sources provide the theoretical foundations, empirical validation, and methodological applications of the SOC scale and its associated constructs:

• Biswas, A., Dutta, S., & Pullig, C. (2006). Low price guarantees as signals of lowest price: The moderating role of perceived price dispersion. Journal of Retailing, 82(3), 245–257. https://doi.org/10.1016/j.jretai.2006.06.002
• 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
• Friestad, M., & Wright, P. (1994). The Persuasion Knowledge Model: How people cope with persuasion attempts. Journal of Consumer Research, 21(1), 1–31. https://doi.org/10.1086/209380
• Hardesty, D. M., Carlson, J. P., & Bearden, W. O. (2002). Longitudinal analyses of the effects of high-low and discount pricing on store price image and consumer retail evaluations. Journal of Retailing, 78(4), 235–248. https://doi.org/10.1016/S0022-4359(02)00099-0
• Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
• Obermiller, C., & Spangenberg, E. R. (1998). Development of a scale to measure skepticism toward advertising. Journal of Consumer Psychology, 7(2), 159–186. https://doi.org/10.1207/s15327663jcp0702_03
• Spence, M. (1973). Job market signaling. The Quarterly Journal of Economics, 87(3), 355–374. https://doi.org/10.2307/1882010

13. Items of the Scale