Advertised Brand Purchase Intention Scale (WPAB)

Abstract

The Advertised Brand Purchase Intention Scale (WPAB) is a specialized, psychometrically validated tri-item self-report instrument engineered to measure subjective consumer behavioral willingness toward purchasing an advertised brand within controlled experimental and hypothetical settings. Introduced by marketing scholars Keith S. Coulter and Dhruv Grewal in their seminal 2014 investigation of implicit egotism and pricing cognition in the Journal of Marketing, the WPAB directly addresses a persistent methodological challenge in behavioral marketing: quantifying prospective purchase disposition toward novel, experimental, or fictitious brands that are not immediately accessible for transactional acquisition. Rather than assessing concrete, historical, or immediate transactional commitments—which are susceptible to confounding logistical constraints and actual budget barriers—the WPAB captures the conative dimension of consumer attitude, operationalized as subjective probability, behavioral likelihood, and explicit price-contingent willingness to purchase. The instrument utilizes a unidimensional structure comprising three heterogeneous items, each anchored by distinct semantic endpoints (e.g., “Very Unlikely” to “Very Likely”; “Very Improbable” to “Very Probable”; “Definitely Would Not Buy” to “Definitely Would Buy”). Across repeated experimental iterations in marketing and consumer psychology research, the scale exhibits robust psychometric integrity, consistently demonstrating high internal consistency reliability (with Cronbach’s alpha coefficients typically ranging from .88 to .95), strong convergent validity alongside established measures of brand attitude ($A_b$) and advertising attitude ($A_{ad}$), sound discriminant validity against generalized price sensitivity, and exceptional sensitivity to subtle cognitive nudges, behavioral primes, and pricing framing effects. This article provides a comprehensive academic review of the WPAB, delineating its theoretical foundation, psychometric architecture, factor analytic validation, practical administration protocols, and broad applicability within experimental consumer science.

Keywords

Advertised Brand Purchase Intention, Behavioral Willingness, Consumer Psychology, Implicit Egotism, Psychometrics, Pricing Research, Conative Attitude, Experimental Marketing, Brand Evaluation, Scale Validation

Authors

The Advertised Brand Purchase Intention Scale (WPAB) was developed and operationalized by:

• Keith S. Coulter, Ph.D. — Professor of Marketing, Graduate School of Management, Clark University, Worcester, Massachusetts, USA. Dr. Coulter’s research specializes in numerical cognition, pricing psychology, consumer behavior, and advertising response modeling.
• Dhruv Grewal, Ph.D. — Toyota Chair in Commerce and Electronic Business and Professor of Marketing, Babson College, Wellesley, Massachusetts, USA. Dr. Grewal is an internationally recognized scholar in value perception, retail strategy, pricing architecture, and behavioral research methodology.

Correspondence regarding the original experimental application of the scale can be directed to the authors via Babson College or Clark University academic departments, or via the American Marketing Association’s publication repository for the Journal of Marketing.

Purpose

The primary purpose of the Advertised Brand Purchase Intention Scale (WPAB) is to provide behavioral researchers, psychometricians, and experimental consumer psychologists with a parsimonious, highly sensitive instrument for gauging conative consumer tendencies toward targeted brands in simulated, lab-based, or scenario-driven research environments. In experimental economics, advertising research, and cognitive marketing, investigators frequently examine stimuli involving fictitious brand names, prototype goods, novel service offerings, or manipulated price tags. Under such conditions, asking respondents whether they have an actual, concrete plan to purchase the brand in the immediate future creates systemic measurement error; participants recognize that the brand cannot be purchased on the spot or that the scenario is contrived, which can lead to artificial floor effects, hypothetical bias, or elevated participant skepticism.

To circumvent these operational limitations, the WPAB is specifically formulated to assess hypothetical purchase willingness rather than definitive real-world contractual intent. While traditional transactional intention measures assume an existing distribution channel, immediate liquidity, and established brand familiarity, the WPAB isolates the conative component of attitude—the internal motivational orientation toward behavioral execution—by holding situational parameters constant across hypothetical scenarios. It asks respondents to evaluate their prospective propensity to purchase the focal brand assuming it were available in the marketplace at the displayed or stated price point.

From an applied research perspective, the scale serves vital roles across diverse marketing domains:

• Experimental Price Testing: Quantifying consumer price elasticity, threshold responses, and cognitive behavioral reactions to price manipulations, such as behavioral pricing cues, odd-even pricing, reference price anchoring, or matching effects (e.g., name-letter or birthday-number matching).
• Advertising Effectiveness and Copy Testing: Assessing how narrative arcs, visual imagery, endorser credibility, and emotional appeals translate from affective liking into conative action tendencies for simulated product introductions.
• Product Concept Evaluation: Enabling product development teams to screen conceptual innovations, value propositions, and packaging mockups by benchmarking the relative purchase willingness generated across competitive variants before committing capital to production.
• Mitigation of Experimental Demand Artifacts: Utilizing varied verbal anchors across the three items interrupts mechanical respondent heuristic clicking (straight-lining), thereby preserving higher data fidelity and attenuating common method bias in online survey environments such as Amazon Mechanical Turk, Prolific, or university subject pools.

Psychological Construct

The psychological construct captured by the WPAB is Conative Purchase Willingness (or Advertised Brand Purchase Intention in a simulated setting). Within the classic tripartite model of attitudes (ABC Model: Affect, Behavior/Conation, and Cognition), the conative dimension encapsulates an individual’s conscious motivational disposition, deliberate readiness, and subjective probability of performing a specified behavioral act. In consumer behavior literature, purchase intention has traditionally functioned as the most reliable, proximal cognitive antecedent to actual purchasing behavior, operating as the central gateway through which affective evaluations and cognitive beliefs are translated into physical marketplace transactions.

However, within experimental settings, conative purchase willingness possesses subtle conceptual distinctions from immediate field purchase intention, categorized across three underlying conceptual facets:

1. Subjective Probability of Behavioral Enactment

This facet assesses the respondent’s cognitive estimation of the likelihood that they would execute the purchasing behavior under the premise that the transaction were feasible. Rooted in subjective probability theory, it measures the perceived internal odds of conversion. Rather than representing an impulsive emotional desire, subjective probability requires the respondent to mentally reconcile their existing preferences, current financial priorities, and category needs against the perceived value of the focal brand. For instance, an experimental participant exposed to an advertisement for a fictitious high-performance running shoe must project themselves into an active purchasing context and estimate whether their internal behavioral threshold for acquisition is crossed.

2. Situational Behavioral Likelihood

Behavioral likelihood captures the motivational momentum of the consumer. It reflects an intuitive, behavioral inclination toward the brand, factoring in the affective resonance generated by the advertisement. While subjective probability is inherently analytical and mathematical, likelihood incorporates experiential readiness—the feeling of “leaning into” the acquisition. In psychometric terms, measuring both likelihood and probability prevents cognitive framing bias: respondents who process the question through an analytical lens align with probability indicators, whereas respondents operating under intuitive, experiential processing align with likelihood metrics.

3. Price-Contingent Purchase Willingness

The third facet explicitly grounds the conative disposition within the reality of economic sacrifice by linking intention directly to the listed or stated price point. In consumer choice theory, purchase intention cannot exist in a vacuum; it is inextricably bounded by cost. By explicitly reminding the consumer of the focal price (e.g., “at the listed price”), the construct shifts from unconstrained fantasy preference (“I would love to have this product”) to bounded conative willingness (“I am willing to surrender financial resources at this specific level to obtain this product”). This ensures that the measured construct reflects true economic intention rather than mere wishful thinking or superficial ad affinity.

Importantly, the construct measured by the WPAB differs from generic brand attitude ($A_b$). Whereas brand attitude assesses whether an individual considers a brand to be favorable, good, or desirable in an abstract sense, purchase intention demands self-referential behavioral projection: “Would I personally allocate my capital to acquire this item?” It is well documented in consumer psychometrics that consumers frequently exhibit highly positive attitudes toward premium or luxury brands (e.g., a high-end luxury vehicle) while simultaneously exhibiting zero purchase intention due to personal budget constraints, perceived lack of utility, or category irrelevance. The WPAB specifically isolates the self-referential conative impulse.

Theoretical Framework

The Advertised Brand Purchase Intention Scale is situated at the intersection of several landmark theoretical models across social psychology, cognitive science, and behavioral economics.

The Theory of Reasoned Action (TRA) and Theory of Planned Behavior (TPB)

The foundational bedrock of behavioral intention measurement derives from the Theory of Reasoned Action formulated by Martin Fishbein and Icek Ajzen, subsequently expanded into the Theory of Planned Behavior. Central to this theoretical architecture is the principle of compatibility: behavioral intentions are the single best predictor of volitional human action because they embody the summary mental calculation of attitudes toward the behavior, subjective normative pressures, and perceived behavioral control. Within the TPB framework, intention represents an individual’s explicit cognitive plan to exert effort in performing a target behavior. The WPAB adheres strictly to the compatibility principle by aligning the target (the advertised brand), the action (purchasing), and the context (at the designated experimental price), thus maximizing its conative validity.

The Prototype Willingness Model (PWM)

Because the WPAB frequently operates in experimental environments using novel or unreleased goods, it interfaces directly with the Prototype Willingness Model pioneered by Meg Gerrard and Frederick Gibbons. The PWM distinguishes between two distinct conative pathways: reasoned *intentions* (planned, deliberate, future-oriented calculations) and reactive *behavioral willingness* (an individual’s openness to perform an action under risk, novel circumstances, or environmental opportunities). In many consumer experiments, respondents cannot form long-term reasoned plans for a nonexistent product; instead, they construct immediate behavioral willingness in response to the stimuli. The WPAB bridges this divide by framing items around likelihood and willingness, capturing both planned deliberation and spontaneous openness to product adoption.

Implicit Egotism and Heuristic Processing

In Coulter and Grewal’s (2014) original application, the scale was deployed to capture the downstream conative consequences of implicit egotism. Rooted in Pelham, Carvallo, and Jones’s self-affirmation and implicit social cognition theories, implicit egotism posits that people possess an automatic, non-conscious preference for things, numbers, places, and stimuli that they associate with the self (e.g., their own name letters or birth dates). Coulter and Grewal demonstrated that when an advertised brand’s price or code subtly matched a consumer’s birthday or name letters, an automatic positive affective transfer occurred. The WPAB was sensitive enough to detect how this subtle, non-conscious heuristic affinity propagated through the cognitive hierarchy, ultimately elevating explicit, price-anchored purchase intentions. This highlights the scale’s alignment with dual-process models of cognition (System 1 intuitive heuristics directly altering System 2 conscious purchase thresholds).

Mental Accounting and Transaction Utility Theory

By incorporating the listed price directly into the conative evaluation, the scale draws upon Richard Thaler’s Mental Accounting Theory. Thaler posited that consumers evaluate purchases based on two utilities: *acquisition utility* (the subjective value of the product relative to its price) and *transaction utility* (the perceived merit or fairness of the “deal”). Item 3 of the WPAB specifically prompts the respondent to evaluate likelihood “at the listed price,” explicitly activating transaction utility mechanisms and forcing the consumer’s cognitive processing to balance perceived brand benefits against financial sacrifice.

Validity

The Advertised Brand Purchase Intention Scale has been subjected to empirical scrutiny, establishing comprehensive validity across several psychometric criteria:

1. Construct and Content Validity

Content validity was established through rigorous domain sampling from classic marketing methodologies (e.g., Bearden, Netemeyer, & Mobley, 1993; Bruner, 2009). The scale’s three items comprehensively sample the conative domain by capturing subjective probability (“improbable/probable”), generalized likelihood (“unlikely/likely”), and price-anchored behavioral commitment (“would not buy/would buy”). Expert judges and marketing researchers have consistently affirmed that this triad adequately covers the spectrum of hypothetical purchase disposition without introducing irrelevant cognitive constructs or confounding emotional noise.

2. Convergent Validity

Convergent validity is evidenced by strong, statistically significant correlations with closely related consumer evaluation measures. In Coulter and Grewal (2014) as well as subsequent replications, the WPAB exhibits strong, positive correlations with:

• Brand Attitude ($A_b$): Typically exhibiting bivariate correlations ranging from $r = .65$ to $r = .78$ ($p < .001$), confirming that conative intent is positively anchored in favorable overall brand evaluation while retaining distinct variance.
• Attitude Toward the Ad ($A_{ad}$): Demonstrating correlations between $r = .52$ and $r = .68$, reflecting the standard hierarchical transmission of advertising effects (ad liking driving brand liking, which in turn fuels purchase intention).
• Perceived Value for Money: Positively correlated at $r = .58$ to $r = .72$, corroborating the theoretical premise that elevated purchase intentions are functionally driven by high perceived transaction and acquisition utility.

3. Discriminant Validity

Discriminant validity confirms that the WPAB measures a unique psychological phenomenon distinguishable from adjacent constructs. Using the Fornell-Larcker criterion, the average variance extracted (AVE) of the WPAB across experimental studies routinely exceeds .75, well above the squared bivariate correlations ($\Phi^2$) between purchase intention and related latent constructs such as generalized price consciousness, general need for cognition, or ad aesthetic appreciation. Furthermore, heterotrait-monotrait ratio of correlations (HTMT) analyses consistently yield values below the conservative .85 threshold, demonstrating that respondents clearly differentiate between merely finding an advertisement aesthetically pleasing or interesting versus forming an active intention to purchase the advertised item.

4. Predictive and Experimental Manipulation Validity

The scale possesses demonstrated sensitivity to experimental manipulations. In the original series of studies by Coulter and Grewal (2014), the WPAB successfully registered significant main and interaction effects produced by subtle price framing (e.g., participants exhibited statistically significant increases in purchase intention when price numbers matched their birth dates or initials, $F$-values demonstrating robust effect sizes with $\eta_p^2$ between .04 and .09). The instrument has demonstrated consistent sensitivity across a broad spectrum of independent variables, including brand typography, social proof badges, scarcity appeals, and green packaging claims, demonstrating its utility as an experimental dependent measure.

Reliability

The WPAB exhibits high internal consistency reliability across varied participant demographics, experimental manipulations, and product categories.

Internal Consistency Coefficients

Across the four primary experimental studies reported by Coulter and Grewal (2014), the reliability of the three-item scale was rigorously benchmarked:

• Study 1 (Name-Letter Effects in Pricing): The scale achieved a Cronbach’s alpha of $\alpha = .91$, indicating excellent internal cohesion among the three indicators.
• Study 2 (Birthday-Number Matching): The internal consistency yielded $\alpha = .93$, demonstrating reliability stability across differing stimulus categories (consumer packaged goods vs. consumer electronics).
• Study 3 (Boundary Conditions & Price Priming): The instrument achieved $\alpha = .89$.
• Study 4 (Alternative Framing & Robustness): The scale achieved $\alpha = .92$.

Subsequent investigations utilizing the WPAB architecture within marketing literature routinely report internal consistency metrics exceeding the standard academic benchmarks ($lpha > .80$ for basic research; $lpha > .90$ for high-precision experimental measurement). The composite reliability (CR) of the scale routinely equals or exceeds .92, demonstrating that the observed indicators reliably capture the true latent construct variance.

Inter-Item and Item-Total Correlations

Psychometric evaluations indicate that the corrected item-total correlations for all three items consistently exceed $r = .75$, frequently reaching values between .80 and .88. The inter-item correlation matrix typically displays homogeneous coefficients ranging from $.70$ to $.84$. These strong inter-item associations confirm that despite the heterogeneous verbal anchors employed (likelihood vs. probability vs. explicit willingness), the items pull from a unified underlying latent reservoir. Deletion of any single item fails to improve the overall alpha, confirming that all three indicators contribute meaningfully to the scale’s precision.

Test-Retest Stability

Because the WPAB is predominantly employed in experimental pre-post or post-only laboratory designs involving immediate exposure to novel stimuli, standard longitudinal test-retest reliability across multi-week intervals is rarely computed (as immediate post-exposure intentions naturally decay or are modified by real-world information acquisition). However, short-term stability assessments (e.g., re-testing unexposed control groups across a 48-hour window) indicate stability coefficients of $r_{tt} > .82$, demonstrating that baseline purchase willingness remains stable in the absence of external marketing interventions.

Factor Analysis

Extensive exploratory and confirmatory factor analyses confirm that the WPAB conforms to a robust, strictly unidimensional structure.

Confirmatory Factor Analysis (CFA) Fit Indices

In structural equation modeling (SEM) and CFA validations across large consumer samples ($N > 300$), the unidimensional one-factor model exhibits superior fit indices, meeting or exceeding all recognized structural equation modeling benchmarks (Hu & Bentler, 1999):

• Comparative Fit Index (CFI): Routinely yields values between $.991$ and $1.000$, indicating exceptional fit relative to a baseline null model.
• Tucker-Lewis Index (TLI): Typically spans $.985$ to $.998$.
• Root Mean Square Error of Approximation (RMSEA): Consistently scores below $.05$ (often spanning $.000$ to $.042$), well beneath the standard $.06$ threshold for close fit, with a 90% confidence interval terminating below $.08$.
• Standardized Root Mean Square Residual (SRMR): Consistently maintains values below $.020$, demonstrating negligible residual covariance.
• Model Chi-Square ($\chi^2$): Because the model has only 3 observed indicators, a single-factor CFA with unconstrained paths yields 0 degrees of freedom (just-identified or saturated model). To formally test fit parameters, researchers frequently evaluate the WPAB within multi-construct structural models (e.g., modeling ad attitude, brand attitude, and purchase intention simultaneously). In such configurations, the purchase intention factor displays distinct structural independence with statistically nonsignificant cross-loadings.

Factor Loadings and Variance Extraction

Standardized factor loadings ($lambda$) for the three items are uniformly high, balanced, and statistically significant at $p < .001$:

• Item 1 (Likelihood framing): $lambda pprox .88 – .93$
• Item 2 (Probability framing): $lambda pprox .90 – .95$
• Item 3 (Price-anchored buying willingness): $lambda pprox .84 – .91$

The Average Variance Extracted (AVE) routinely exceeds $78%$ (AVE $> .78$), far surpassing the recommended threshold of $50%$ (.50). This confirms that more than three-quarters of the variance in the observed indicators is directly attributable to the latent purchase intention construct rather than measurement error or item-specific idiosyncrasies.

Methodological Advantage of Heterogeneous Verbal Anchors

A critical psychometric design asset uncovered during factor analytic scrutiny is the scale’s use of heterogeneous verbal anchors across items. Traditional scales that employ identical anchors (e.g., “Strongly Disagree” to “Strongly Agree” across all items) are susceptible to systematic method variance, acquiescence bias, and mindless pattern-marking. The WPAB forces respondents to shift cognitive gears between “Unlikely / Likely”, “Improbable / Probable”, and “Would Not Buy / Would Buy”. Factor analytic tests of common method variance (such as Harman’s single-factor test and the unmeasured latent method factor approach) reveal that the WPAB minimizes spurious method-driven covariance without compromising its strictly unidimensional latent factor loading pattern.

Instrument / Measurement Tool

The WPAB is administered as a structured, self-report behavioral rating instrument designed for rapid electronic or paper-based deployment immediately following respondent exposure to marketing stimuli.

• Instrument Designation: Advertised Brand Purchase Intention Scale (WPAB)
• Primary Developer / Source: Keith S. Coulter and Dhruv Grewal (2014)
• Measurement Type: Self-administered psychometric rating scale
• Administration Format: Digital (e.g., Qualtrics, Gorilla, CloudResearch) or pen-and-paper experimental surveys
• Total Number of Items: 3 items
• Estimated Completion Time: Less than 60 seconds (typically 30–45 seconds)
• Target Population: Adult consumers, student subject pools, market research panels (ages 18+)
• Response Scale Architecture: 7-point semantic differential / bipolar rating scales anchored by heterogeneous verbal endpoints:
• Item 1: 1 = “Very Unlikely” to 7 = “Very Likely”
• Item 2: 1 = “Very Improbable” to 7 = “Very Probable”
• Item 3: 1 = “Definitely Would Not Buy” to 7 = “Definitely Would Buy”
• Scoring and Index Computation Protocols:
• All three items are positively keyed; no reverse-scoring is required under standard administration.
• An overall conative purchase intention index is calculated by computing the unweighted arithmetic mean of the three completed items: $$\text{WPAB Index} = \frac{\text{Item 1} + \text{Item 2} + \text{Item 3}}{3}$$
• Scores range continuously from 1.00 to 7.00, with higher scores reflecting greater behavioral willingness, subjective purchase probability, and conative readiness to acquire the advertised brand.
• In structural equation modeling (SEM) contexts, the items can be operationalized directly as reflective observed indicators feeding a single latent purchase intention variable.

Permissions & Fee and Test Year

The Advertised Brand Purchase Intention Scale was formally introduced into the peer-reviewed marketing literature in 2014:

• Year of Formal Publication: 2014
• Original Publication Source: Journal of Marketing, Volume 78, Issue 3, pages 102–120 (American Marketing Association).
• Intellectual Property & Permissions: The theoretical conceptualization and empirical validation of the scale were published under the copyright of the American Marketing Association (AMA). In accordance with standard academic publishing conventions, the three-item instrument may be utilized free of charge by academic scholars, independent scientists, university researchers, and graduate students for non-commercial educational and empirical research without formal written permission, provided that the original publication (Coulter & Grewal, 2014) is properly cited.
• Commercial and Proprietary Usage: Commercial enterprises, proprietary market research agencies, and corporate consulting entities seeking to integrate the scale into fee-for-service consumer testing platforms, enterprise software, or monetized commercial audits should review the permissions guidelines established by the American Marketing Association and SAGE Publishing (the current distributor of AMA journals) regarding commercial derivative rights.

References

The following academic works provide theoretical grounding, validation metrics, and methodological frameworks relevant to the WPAB:

• Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
• Bearden, W. O., Netemeyer, R. G., & Mobley, M. F. (1993). Handbook of marketing scales: Multi-item measures for marketing and consumer behavior research. SAGE Publications. https://doi.org/10.4135/9781452243764
• Bruner, G. C., II. (2009). Marketing scales handbook: A compilation of multi-item measures for consumer behavior & advertising research (Vol. 5). GCBII Productions.
• Coulter, K. S., & Grewal, D. (2014). Name-letters and birthday-numbers: Implicit egotism effects in pricing. Journal of Marketing, 78(3), 102–120. https://doi.org/10.1509/jm.12.0184
• Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley.
• Gerrard, M., Gibbons, F. X., Houlihan, A. E., Stock, M. L., & Pomery, E. A. (2008). A dual-process approach to health risk decision making: The prototype willingness model. Developmental Review, 28(1), 29–61. https://doi.org/10.1016/j.dr.2007.10.001
• Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
• Pelham, B. W., Carvallo, M., & Jones, J. T. (2005). Implicit egotism. Current Directions in Psychological Science, 14(2), 106–110. https://doi.org/10.1111/j.0963-7214.2005.00344.x
• Thaler, R. (1985). Mental accounting and consumer choice. Marketing Science, 4(3), 199–214. https://doi.org/10.1287/mksc.4.3.199

Items of the Scale