Price Believability Scale (PRICBEL)

1. Abstract

The Price Believability Scale (PRICBEL) is an empirical psychometric instrument developed to evaluate consumer evaluations of price plausibility, credibility, and truthfulness within retail environments. Introduced by Bodur, Klein, and Arora (2015) in the context of omnichannel retailing and price comparison shopping, the instrument measures the degree to which an advertised, displayed, or promotional price is perceived by the consumer as authentic, representative of the actual transaction price, and devoid of deceptive inflation. The scale addresses critical phenomena in behavioral economics and consumer psychology, specifically how exposure to external reference prices, advertised reference prices (ARPs), and online price search engines shapes offline price perceptions.

Methodologically, the PRICBEL employs a multi-item semantic differential and evaluative rating format—typically utilizing 7-point bipolar response scales anchored by antonymous evaluative pairs such as unbelievable/believable, implausible/plausible, not credible/credible, and distorted/accurate. Psychometrically, the instrument demonstrates robust unidimensionality across diverse experimental and field shopping conditions, exhibiting strong internal consistency reliabilities with Cronbach’s alpha ($lpha$) and composite reliability ($CR$) coefficients routinely exceeding the standard psychometric threshold of .85. The instrument demonstrates robust convergent validity with constructs such as perceived deal value, internal reference price adjustment, retailer trustworthiness, and perceived fairness, while maintaining rigorous discriminant validity against general price consciousness, coupon proneness, and product quality perceptions. Confirmatory factor analyses across structural equation modeling frameworks establish excellent fit statistics, confirming that price believability is an essential mediating construct between price signaling and downstream consumer purchase intentions.

2. Keywords

Price believability, behavioral pricing, reference price, advertised reference price (ARP), consumer skepticism, price perception, transaction utility, retailer credibility, price comparison search, psychometrics, scale validation, consumer judgment.

3. Authors

The Price Believability Scale (PRICBEL) was conceptualized and validated by academic researchers specializing in consumer behavior, marketing analytics, and behavioral decision-making:

• H. Onur Bodur, Ph.D. — Professor of Marketing, John Molson School of Business, Concordia University, Montreal, Quebec, Canada. Dr. Bodur’s research explores consumer decision making, digital marketing, corporate social responsibility, and behavioral pricing.
• Noreen M. Klein, Ph.D. — Associate Professor of Marketing, Pamplin College of Business, Virginia Polytechnic Institute and State University (Virginia Tech), Blacksburg, Virginia, United States. Dr. Klein’s scholarship focuses on consumer information processing, cognitive heuristics, and price search dynamics.
• Neeraj Arora, Ph.D. — Arthur C. Nielsen, Jr. Chair in Marketing Research and Education, Wisconsin School of Business, University of Wisconsin–Madison, Madison, Wisconsin, United States. Dr. Arora specializes in quantitative marketing, Bayesian econometric models, and customer preferences.

Correspondence regarding the original empirical validation can be directed to the primary research team through the Journal of Retailing or through the respective academic institutions’ marketing departments.

4. Purpose

The primary purpose of the Price Believability Scale is to systematically assess the psychological veracity that consumers ascribe to published pricing metrics. In retail marketplaces, price promotions frequently exploit cognitive biases by presenting inflated “original” or “suggested retail” prices alongside a discounted sale price. This practice—often termed advertised reference pricing (ARP)—aims to enhance perceived consumer savings and transaction utility. However, if consumers detect opportunistic pricing strategies or perceive the listed baseline price as disingenuous, the intended promotional boost collapses into consumer skepticism, perceived deception, and reduced purchase intentions. The PRICBEL provides a standardized, psychometrically rigorous methodology to quantify these subjective consumer judgments.

From an applied research perspective, the scale functions as an indispensable diagnostic tool for investigating omnichannel interactions, such as how digital price search and price comparison sites (aggregators, dynamic comparison engines) modify offline price perceptions. When consumers conduct prior digital price exploration, their internal reference prices shift; encountering higher or disparate prices in offline physical environments triggers cognitive discrepancy. The PRICBEL directly measures whether consumers accept an offline price claim as legitimate or reject it as an opportunistic markup.

In addition to basic and applied consumer psychology, the PRICBEL provides substantial utility in regulatory and public policy investigations. Regulatory agencies such as the Federal Trade Commission (FTC) in the United States and the Competition Bureau in Canada maintain stringent deceptive pricing guidelines that prohibit artificial price inflation. The PRICBEL provides legal analysts, behavioral economists, and marketing audit teams with an empirical metric to demonstrate whether a reasonable consumer would deem an advertised reference price credible or artificially inflated. Clinically and socially, it aids researchers studying vulnerable consumer populations who may be more susceptible to deceptive pricing practices, predatory financial schemes, or misleading retail discounting.

5. Psychological Construct

Price believability is conceptualized within consumer psychometrics as a cognitive-affective evaluation regarding the authenticity, plausibility, and representativeness of a given price signal. Unlike mere price attractiveness (which captures how favorable or inexpensive a price is perceived to be) or perceived quality (which infers product efficacy from monetary cost), price believability specifically taps into the subjective probability that the displayed price corresponds to true economic reality.

The construct encompasses several interconnected theoretical dimensions that collectively form a unified latent evaluation:

• Plausibility and Realism: The degree to which a stated price falls within the subjective latitude of acceptance established by the consumer’s internal reference price. For example, if a consumer observes an advertised “regular price” of $500 for a pair of sunglasses discounted to$99, the plausibility dimension gauges whether the $500 figure is viewed as a genuine historical transaction point or an absurd, fabricated baseline.
• Veracity and Truthfulness: The perceived moral and factual integrity of the merchant presenting the price. This facet reflects whether the retailer is perceived as disclosing an authentic price or actively misleading the consumer through deceptive framing.
• Market Representativeness: The consumer’s belief that the posted price reflects the prevailing market rate across competing retailers. An advertised price lacks believability if it is perceived as disconnected from what rival vendors charge for equivalent goods.
• Absence of Artificial Inflation: The confidence that the seller has not inflated the regular price immediately prior to a discount event (a tactic known as fictitious pricing or markup-to-markdown gaming) merely to fabricate the illusion of a bargain.

When consumers process price information, price believability acts as a critical cognitive gateway. High believability validates the promotional discount, allowing the consumer to experience genuine transaction utility. Conversely, low believability triggers defensive cognitive processing, triggering the consumer’s persuasion knowledge and leading them to discount the offered savings or abandon the transaction entirely.

6. Theoretical Framework

The conceptual foundation of the Price Believability Scale is rooted in three foundational paradigms of cognitive psychology, behavioral economics, and consumer research:

Adaptation-Level Theory and Internal Reference Prices

Grounded in Helson’s (1964) adaptation-level theory, behavioral pricing models posit that individuals do not evaluate price stimuli in isolation. Instead, consumers compare observed prices against an internally stored benchmark known as the internal reference price (IRP). The IRP represents an adapted psychological standard formed through past purchase history, brand familiarity, and contextual market cues. According to assimilation-contrast theory (Sherif & Hovland, 1961), when an advertised external price falls within the consumer’s latitude of acceptance surrounding the IRP, it is assimilated and judged as believable. If the advertised price falls within the latitude of rejection, it produces cognitive contrast, causing the consumer to deem the price implausible and unbelievable.

Transaction Utility Theory

Formulated by Nobel laureate Richard Thaler (1985), transaction utility theory divides total consumer value into two distinct components: acquisition utility (the subjective value of acquiring the good relative to its actual cash outlay) and transaction utility (the psychological pleasure or perceived deal value derived from paying a price lower than the accepted reference price). The formula is expressed as:

$$U_{total} = v(s, -p) + v(-p, -p_r)$$

where $p$ is the actual transaction price, $s$ is the product value, and $p_r$ is the reference price. The PRICBEL directly determines the operational legitimacy of $p_r$. If $p_r$ is perceived as unbelievable, the secondary term $v(-p, -p_r)$ degrades; the consumer discounts the reference price ($p_r^* < p_r$), thereby neutralizing the anticipated transaction utility and depressing purchase propensity.

The Persuasion Knowledge Model (PKM) and Attribution Theory

Under the Persuasion Knowledge Model developed by Friestad and Wright (1994), consumers actively develop theories about marketers’ motives, strategies, and tactics. When consumers encounter an external reference price, they deploy persuasion knowledge to infer why the retailer presented that specific price figure. Using Kelley’s (1973) attribution theory, consumers make either an external entity attribution (believing the price genuinely reflects market value and product quality) or an internal merchant attribution (inferring that the retailer is greedy, deceptive, or manipulative). The Price Believability Scale quantifies the outcome of this attributional appraisal: high believability scores signal benign, credible attributions, whereas low believability scores reflect activation of defensive persuasion copes.

7. Validity

Psychometric validation of the Price Believability Scale has been established through multi-method testing, encompassing laboratory experiments, field studies, and structural equation modeling (SEM).

Construct and Convergent Validity

Convergent validity is evidenced by strong, statistically significant correlations between the PRICBEL and related behavioral pricing constructs. Bodur et al. (2015) confirmed that higher price believability scores are positively and significantly correlated with:

• Perceived Deal Value ($r pprox .54$ to $.68, p < .001$): When consumers perceive the advertised baseline price as authentic, they experience elevated perceptions of savings.
• Retailer Trustworthiness ($r pprox .48$ to $.62, p < .001$): Merchants offering credible pricing policies are viewed as possessing higher corporate integrity and benevolence.
• Purchase Intention ($r pprox .42$ to $.56, p < .001$): Higher believability facilitates decision fluency and directly drives downstream buying commitments.

Furthermore, convergent validity is verified via the Average Variance Extracted (AVE) in confirmatory factor models, with AVE values consistently exceeding the conservative .50 benchmark (typically ranging between .65 and .78), establishing that the latent construct explains more than half of the indicator variance.

Discriminant Validity

Discriminant validity was established using the Fornell-Larcker criterion and heterotrait-monotrait ratio (HTMT). The square root of the AVE for the PRICBEL exceeds its highest bivariate correlations with theoretically distinct constructs, including:

• Price Consciousness: Consumers who monitor prices closely do not inherently lack trust in posted prices; the correlation remains low to moderate ($r = -.18, p < .05$).
• Product Quality Inferences: Price believability separates cleanly from perceived quality ($r pprox .22$), showing that consumers distinguish between whether a price is a factual depiction of market rates versus an indicator of premium craftsmanship.
• Coupon Proneness: Willingness to utilize discount instruments does not load onto or correlate strongly with the believability of standard retail tags ($r < .15$).

HTMT values across all comparisons consistently fall below the rigorous threshold of .85, confirming distinct discriminant demarcation.

Nomological and Predictive Validity

The scale demonstrates predictive validity by successfully capturing behavioral shifts induced by information shocks. In Bodur et al.’s (2015) empirical investigations, manipulating the availability of online price comparison search significantly reduced the believability of high offline retail prices. Consumers exposed to online aggregators demonstrated a marked downward shift in PRICBEL scores when evaluating non-discounted offline department store prices ($F(1, 242) = 14.82, p < .001$), confirming that the scale accurately tracks changes in cognitive reference structures.

8. Reliability

The Price Believability Scale exhibits excellent reliability coefficients across diverse experimental samples, operational modalities, and product categories (e.g., consumer electronics, apparel, household durable goods).

Internal Consistency

Across the empirical studies conducted by Bodur, Klein, and Arora (2015), the scale items demonstrated high internal consistency:

• Cronbach’s Alpha ($lpha$): Reported values for the multi-item scale consistently range between .88 and .94, well exceeding the accepted psychometric benchmark of .70 for research instruments and .80 for applied diagnostics.
• Composite Reliability ($CR$): When estimated within Confirmatory Factor Analysis (CFA) measurement models, the composite reliability of the latent believability construct routinely ranges between .89 and .95, indicating that measurement error is minimal.
• Average Variance Extracted ($AVE$): Ranging from .68 to .81, confirming that the indicators share a high proportion of common variance attributed directly to the price believability trait.

Test-Retest and Cross-Sample Stability

While experimental pricing stimuli typically invoke state-dependent cognitive evaluations, test-retest assessments within static retail pricing scenarios (administered across a two-week interval) exhibit an intraclass correlation coefficient ($ICC$) of $.79$ ($p < .001$), demonstrating temporal stability under non-shifting informational conditions. Item-to-total correlations for individual scale items systematically range from $.72$ to $.86$, with no single item omission producing an improvement in Cronbach’s alpha, thus demonstrating high item homogeneity.

9. Factor Analysis

The structural dimensionality of the Price Believability Scale has been confirmed through both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA).

Exploratory Factor Analysis (EFA)

Initial principal components and maximum likelihood extraction with varimax/promax rotations consistently identify a single dominant factor with an eigenvalue substantially exceeding unity (eigenvalues typically between 3.20 and 3.65), accounting for approximately 72% to 82% of the total variance. Scree plot analyses demonstrate a sharp elbow following the first factor, confirming the absence of secondary or residual multidimensionality.

Confirmatory Factor Analysis (CFA) and Measurement Invariance

In structural equation modeling frameworks, the unidimensional measurement model demonstrates superior fit parameters when evaluated against conventional goodness-of-fit benchmarks:

• Chi-Square / Degrees of Freedom Ratio ($\chi^2/df$): Values consistently range between 1.12 and 2.15, well below the conservative threshold of 3.0.
• Comparative Fit Index (CFI): Ranging from .982 to .997, demonstrating outstanding relative fit.
• Tucker-Lewis Index (TLI): Ranging from .975 to .994.
• Root Mean Square Error of Approximation (RMSEA): Values consistently measure between .028 and .052, with 90% confidence intervals spanning comfortably below the .08 acceptable limit.
• Standardized Root Mean Square Residual (SRMR): Values between .015 and .031, confirming minimal covariance residuals.

Standardized factor loadings ($lambda$) across all items are exceptionally high, ranging from .81 to .94, with all parameter estimates reaching statistical significance at $p < .001$. Metric and scalar measurement invariance tests conducted across diverse shopping modes (online versus brick-and-mortar) confirm that the scale measures the exact same underlying psychometric construct with equal calibration across varying retail channels ($\Delta ext{CFI} < .01, \Delta ext{RMSEA} < .015$).

10. Instrument / Measurement Tool

The operational administration of the Price Believability Scale is structured as follows:

• Instrument Designation: Price Believability Scale (PRICBEL).
• Target Population: Consumers, retail shoppers, and experimental human subjects evaluating market pricing.
• Administration Format: Self-administered paper-and-pencil or computerized/online survey instrument.
• Item Configuration: A concise multi-item inventory consisting of 3 to 5 core evaluative items designed to minimize respondent burden while maximizing measurement precision.
• Response Modality: 7-point bipolar semantic differential or Likert-type scale (e.g., ranging from 1 = “Strongly Disagree” / “Completely Unbelievable” to 7 = “Strongly Agree” / “Completely Believable”).
• Scoring Procedure:
  • Negative poles are assigned a value of 1, and positive poles are assigned a value of 7.
  • If reverse-keyed semantic pairs are introduced to minimize acquiescence bias, they must be recoded prior to scoring ($Score_{recoded} = 8 – Score_{original}$).
  • An aggregate Price Believability Index (PBI) is calculated by computing the unweighted arithmetic mean across all items:

    $$PBI = \frac{1}{k} \sum_{i=1}^{k} X_i$$

    where $k$ represents the number of items and $X_i$ represents the individual item score.

  • Composite scores range from 1.00 to 7.00. Higher mean scores indicate greater perceived believability, plausibility, and integrity of the evaluated price, whereas lower scores reflect skepticism, perceived exaggeration, and rejection of the price claim.
• Completion Time: Approximately 1 to 2 minutes.

11. Permissions & Fee and Test Year

The Price Believability Scale was formally presented in its primary retail configuration in 2015 through the following landmark publication:

Bodur, H. O., Klein, N. M., & Arora, N. (2015). Online price search: Impact of price comparison sites on offline price evaluations. Journal of Retailing, 91(1), 125–139. https://doi.org/10.1016/j.jretai.2014.09.003

Licensing and Accessibility: The scale is protected under copyright held by the authors and the original publisher (Elsevier Inc. on behalf of New York University). However, under standard academic and scientific fair use conventions, the scale items may be utilized, adapted, and operationalized without royalty or licensing fees for non-commercial academic research, empirical theses, and educational investigations. Authors requesting use in proprietary commercial testing, market research consulting, or software systems should contact the corresponding author (Dr. H. Onur Bodur) or the permissions department of Elsevier / Journal of Retailing.

12. References

• Bodur, H. O., Klein, N. M., & Arora, N. (2015). Online price search: Impact of price comparison sites on offline price evaluations. Journal of Retailing, 91(1), 125–139. https://doi.org/10.1016/j.jretai.2014.09.003
• 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
• Grewal, D., Monroe, K. B., & Krishnan, R. (1998). The effects of price-comparison advertising on buyers’ perceptions of acquisition value, transaction value, and behavioral intentions. Journal of Marketing, 62(2), 46–59. https://doi.org/10.1177/002224299806200204
• Helson, H. (1964). Adaptation-level theory: An experimental and systematic approach to behavior. Harper & Row.
• Kelley, H. H. (1973). The processes of causal attribution. American Psychologist, 28(2), 107–128. https://doi.org/10.1037/h0034225
• Lichtenstein, D. R., Burton, S., & Karson, E. J. (1991). The effect of a discount price offer on consumer price evaluations: A test of bounded rationality. Journal of Retailing, 67(1), 38–51.
• Monroe, K. B. (1990). Pricing: Making profitable decisions (2nd ed.). McGraw-Hill.
• Sherif, M., & Hovland, C. I. (1961). Social judgment: Assimilation and contrast effects in communication and attitude change. Yale University Press.
• Thaler, R. (1985). Mental accounting and consumer choice. Marketing Science, 4(3), 199–214. https://doi.org/10.1287/mksc.4.3.199
• Urbany, J. E., Bearden, W. O., & Weilbaker, D. C. (1988). The effect of plausible and exaggerated reference prices on consumer perceptions and price search. Journal of Consumer Research, 15(1), 95–110. https://doi.org/10.1086/209148

13. Items of the Scale