Purchase Likelihood at Current Price (PLCP)

1. Abstract

The Purchase Likelihood at Current Price (PLCP) scale is an established psychometric instrument designed to evaluate a consumer's subjective probability and behavioral intention to acquire a designated product or service under explicitly stipulated, unadjusted market pricing conditions. Methodologically rooted in the pioneering consumer pricing paradigms developed by William B. Dodds, Kent B. Monroe, and Dhruv Grewal in 1991, and subsequently refined by Grewal, Monroe, and Krishnan in 1998, the measure was adapted by Huachao Gao, Yinlong Zhang, and Vikas Mittal (2017) to investigate how identity structures (specifically, local versus global identity) moderate consumer price sensitivity.

Structurally, the PLCP operates as a parsimonious, unidimensional measurement model typically comprising three to four completion-style item stems. Respondents evaluate their stated inclination, subjective certainty, and behavioral disposition using multi-point Likert or semantic differential response formats anchored by probabilistic extremities (e.g., "Very Unlikely" to "Very Likely" or "Definitely No" to "Definitely Yes"). The psychometric integrity of the instrument is supported across multiple empirical studies, consistently yielding robust internal consistency coefficients (Cronbach's $\alpha$ routinely exceeding .88, often surpassing .93). Confirmatory factor analytic investigations confirm strict unidimensionality, with standardized factor loadings consistently exceeding .80. The scale demonstrates rigorous construct, convergent, discriminant, and predictive validity, functioning as a reliable proxy for conative purchase behavior within experimental marketing, behavioral economics, and consumer psychology research.

2. Keywords

Purchase Likelihood at Current Price, PLCP, price sensitivity, behavioral intention, willingness to buy, consumer psychology, transaction utility, psychometrics, scale validation, local-global identity

3. Authors

The contemporary adaptation of the Purchase Likelihood at Current Price (PLCP) instrument was formulated by:

• Huachao Gao — Associate Professor of Marketing, College of Business, University of Victoria, Victoria, BC, Canada.
• Yinlong Zhang — Professor of Marketing, Department of Marketing, Terry College of Business, University of Georgia, Athens, GA, USA.
• Vikas Mittal — J. Hugh Liedtke Professor of Marketing, Jesse H. Jones Graduate School of Business, Rice University, Houston, TX, USA.

The theoretical foundations and core measurement stems trace directly to earlier structural formulations authored by:

• William B. Dodds — Emeritus Professor of Marketing, Fort Lewis College, Durango, CO, USA.
• Kent B. Monroe — J. M. Jones Professor Emeritus of Marketing, University of Illinois at Urbana-Champaign, IL, USA; Visiting Distinguished Scholar, Robins School of Business, University of Richmond, VA, USA.
• Dhruv Grewal — Toyota Chair in Commerce and Electronic Business, Professor of Marketing, Babson College, Babson Park, MA, USA.

4. Purpose

The primary purpose of the Purchase Likelihood at Current Price (PLCP) scale is to capture a standardized, quantitative assessment of a consumer's immediate intention to execute an economic transaction when exposed to a specific item at a fixed, explicitly stated price point. In the broader spectrum of behavioral decision research, measuring consumer response to price changes often suffers from measurement variance depending on whether researchers assess latent reservation prices, direct monetary willingness-to-pay (WTP), or relative value assessments. The PLCP bridges these domains by anchoring the conative behavioral response to an ecological baseline: the concrete, posted market price.

Within consumer psychology and experimental marketing, the scale serves as a critical dependent variable for isolating how internal psychological constructs—such as social identity, cultural orientation, cognitive framing, and socio-cognitive categorization—interact with economic cues to shift pricing elasticity. For example, Gao, Zhang, and Mittal (2017) deployed the instrument across laboratory and online experimental settings (notably Studies 4 and 5) to demonstrate that consumers with an activated "local identity" exhibit elevated price sensitivity relative to those with an activated "global identity." In these experiments, the PLCP isolated purchase intention at a static reference price, providing empirical clarity regarding how psychological self-construal modulates willingness to allocate financial resources.

Beyond academic research, the PLCP provides commercial and managerial value. Strategic pricing decisions require dependable diagnostic indicators capable of detecting consumer hesitation prior to actual market deployment. By assessing the PLCP across multiple discrete price tiers, market analysts can construct empirical demand curves, calculate point elasticity, and locate psychological price thresholds (e.g., reservation boundaries) without the confounding noise common to open-ended contingent valuation methods.

5. Psychological Construct

The psychological construct captured by the PLCP is conative behavioral intention situated within an economic evaluation context. Under classical psychometric and attitudinal frameworks, consumer orientation consists of three interrelated components: the cognitive component (beliefs, perceived quality, and knowledge structures), the affective component (emotional valence, brand affection, and hedonic resonance), and the conative component (explicit behavioral intention, action tendency, and commitment to transactional exchange). The PLCP specifically isolates the conative component, operating as the final psychological precursor to behavioral execution.

Rather than evaluating generic purchase intention (e.g., "Do you intend to buy a laptop in the next six months?"), the PLCP measures context-contingent transactional readiness. The construct requires the cognitive processing of three interrelated informational inputs:

• Stimulus Representation ($S$): The perceived utility and physical or symbolic attributes of the target product.
• Monetary Sacrifice ($P$): The nominal cost required to obtain the target product, perceived as an immediate reduction in disposable wealth.
• Reference Price Contrast ($R$): The internal cognitive anchor or external contextual anchor against which the nominal cost is compared.

Consequently, the PLCP measures subjective probability: the consumer's self-estimated likelihood that the perceived value derived from the transaction ($S$) sufficiently offsets the perceived sacrifice ($P$), mediated by the internal reference frame ($R$). When operationalized through completion-style items, the construct functions as a continuous unidimensional continuum, ranging from total transactional aversion (zero probability) to definitive behavioral execution (near-certain probability).

6. Theoretical Framework

The theoretical architecture underpinning the PLCP integrates classical social-psychological models of action with formal economic-psychological frameworks of price perception.

Theory of Planned Behavior (TPB)

According to the Theory of Planned Behavior (Ajzen, 1991), human action is guided by behavioral intentions, which function as immediate predictors of volition. Intentions aggregate attitudes toward the behavior, subjective norms, and perceived behavioral control. Within the PLCP context, the behavior is precisely defined as "purchasing product $X$ at price $Y$." The monetary component directly challenges perceived behavioral control (affordability constraints) and attitude toward the exchange, making the stated purchase likelihood the proximal cognitive precursor to actual behavioral expenditure.

Transaction Utility Theory

Richard Thaler's (1985) Transaction Utility Theory provides the microeconomic rationale for the PLCP. Thaler posits that total transactional satisfaction is the sum of two distinct utilities:

1. Acquisition Utility ($U_A$): The subjective value of the product received minus the outlay required, mathematically conceptualized as $v(p^*, -p)$, where $p^*$ is the maximum value equivalent and $p$ is the actual price.
2. Transaction Utility ($U_T$): The psychological satisfaction or dissatisfaction associated with the deal itself, derived by comparing the posted price ($p$) to a reference price ($p_r$), conceptualized as $v(-p, -p_r)$.

The PLCP measures a consumer's conative response to the combination of acquisition and transaction utilities. When the current posted price generates negative transaction utility ($p > p_r$), stated purchase likelihood declines sharply, reflecting heightened price sensitivity.

The Price-Perceived Quality-Perceived Value Paradigm

The empirical heritage of the PLCP stems from the seminal structural model developed by Dodds, Monroe, and Grewal (1991). This framework posits that price serves a dual informational role: it signals quality (higher price increases perceived quality), but it simultaneously represents economic sacrifice (higher price increases perceived monetary sacrifice). Both pathways converge upon Perceived Value, which acts as the direct antecedent to Willingness to Buy (the core construct assessed by the PLCP). Grewal, Monroe, and Krishnan (1998) validated this pathway, demonstrating that purchase likelihood at current price points fluctuates as a direct function of the net balance between perceived acquisition value and transaction value.

7. Validity

The psychometric validity of the PLCP has been rigorously examined across multiple experimental and field methodologies.

Construct and Convergent Validity

Construct validity is evidenced by high, statistically significant factor loadings on the latent conative factor ($lambda > .80$, often approaching .95). Convergent validity is supported through substantial correlations between the PLCP and complementary measures of consumer preference:

• Strong positive correlation with Perceived Value for Money ($r = .65$ to $.78, p < .001$).
• Moderate-to-strong positive correlation with Overall Brand Attitude ($r = .50$ to $.62, p < .001$).
• Moderate negative correlation with Perceived Monetary Sacrifice ($r = -.42$ to $-.58, p < .001$).
• Strong positive correlation with incentivized continuous Willingness-to-Pay (WTP) thresholds evaluated via Becker-DeGroot-Marschak (BDM) lottery procedures.

Discriminant Validity

Discriminant validity has been established through average variance extracted (AVE) versus shared variance comparisons (Fornell-Larcker criterion). Across empirical assessments (e.g., Dodds et al., 1991; Gao et al., 2017), the AVE for the purchase likelihood construct consistently exceeds .70, comfortably surpassing the squared inter-construct correlations with conceptually proximal dimensions such as perceived quality ($r^2 \approx .25 – .36$) and store image ($r^2 \approx .15 – .25$). This confirms that the PLCP isolates transactional propensity rather than general affective appraisal.

Predictive and Criterion-Related Validity

The scale demonstrates predictive validity regarding actual consumer checkout actions. In experimental designs featuring real or incentivized monetary outlays (e.g., lab-based simulated store environments), aggregate PLCP scores predict binary checkout choices with high classification accuracy (area under the ROC curve [AUC] typically exceeding .82). In the identity-focused trials conducted by Gao et al. (2017), PLCP scores successfully detected subtle shifts in price sensitivity caused by implicit cognitive primes, demonstrating the scale's sensitivity to situational framing effects.

8. Reliability

The PLCP exhibits strong reliability coefficients across diverse operational contexts, sample types, and cultural settings.

Internal Consistency

Across academic literature, the internal consistency of the multi-item scale is robust:

• Dodds, Monroe, and Grewal (1991): Initial multi-item willingness-to-buy indices reported Cronbach's alphas between $.85$ and $.93$ across varied product categories (calculators, stereo players).
• Grewal, Monroe, and Krishnan (1998): Reported composite reliabilities and Cronbach's alphas ranging from $.89$ to $.94$ in experimental pricing environments evaluating bicycle purchases.
• Gao, Zhang, and Mittal (2017): In Studies 4 and 5 examining price sensitivity via local-global identity framing, the adapted PLCP scale demonstrated Cronbach's alphas of $.91$ and $.93$, indicating high internal cohesion without redundancy.

Split-Half and Composite Reliability

Analyses evaluating McDonald's omega ($\omega$) consistently yield indices matching or exceeding Cronbach's alpha (typically $\omega > .90$), confirming that tau-equivalence assumptions do not inflate the scale's estimated consistency. Average inter-item correlations typically cluster between $.70$ and $.82$, satisfying established psychometric standards for scale parsimony and structural integrity.

9. Factor Analysis

Empirical evaluations of the PLCP's latent structure using both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) confirm a strictly unidimensional measurement model.

Exploratory Factor Analysis (EFA)

When subjected to principal axis factoring or principal component analysis with unconstrained extraction criteria:

• A single dominant factor emerges with an eigenvalue typically ranging from $2.40$ to $3.60$, accounting for $75%$ to $88%$ of the total variance across items.
• Scree plot tests display an unambiguous single-factor elbow break, with secondary eigenvalues failing to surpass conventional Kaiser-Guttman thresholds (secondary eigenvalues routinely drop below $0.40$).
• Standardized item communalities ($h^2$) routinely exceed $.70$, indicating that the shared latent factor accounts for the vast majority of individual item variance.

Confirmatory Factor Analysis (CFA)

Structural equation modeling confirms that the single-factor specification delivers good fit to empirical data. Typical fit metrics derived from modern implementations of the Dodds et al. (1991) and Gao et al. (2017) formulations include:

• Comparative Fit Index (CFI): $.98$ to $1.00$
• Tucker-Lewis Index (TLI): $.97$ to $.99$
• Root Mean Square Error of Approximation (RMSEA): $.03$ to $.06$ (with 90% confidence intervals spanning zero to $.08$)
• Standardized Root Mean Square Residual (SRMR): $.01$ to $.03$
• Standardized Factor Loadings ($lambda$): Individual item loadings range tightly between $.84$ and $.96$ ($p < .001$), confirming that each completion stem represents the common underlying latent variable.

10. Instrument / Measurement Tool

The technical parameters and administrative specifications of the PLCP are structured as follows:

• Test Type: Self-report psychometric rating instrument; behavioral intention completion scale.
• Format: Completion-style sentence stems pairing a target product and explicit price point with probabilistic evaluation anchors.
• Item Count: Typically 3 or 4 standardized items (parsimonious adaptation).
• Administration Time: Approximately 60 to 90 seconds.
• Target Population: General consumer populations, adult experimental participants, student samples, and commercial customer panels.
• Response Formats: Evaluated using multi-point Likert or semantic differential continua, most commonly formatted as 7-point or 9-point scales:
• 1 = Very Unlikely to 7 = Very Likely
• 1 = Very Low Probability to 7 = Very High Probability
• 1 = Definitely No to 7 = Definitely Yes
• 1 = Improbable to 7 = Probable
• Scoring Protocols:
• All items are keyed in a uniform direction; no reverse-coded items are present in standard administrations.
• An overall composite score is computed by calculating the unweighted arithmetic mean of the completed items:

$$\text{PLCP Composite} = \frac{1}{k}\sum_{i=1}^{k} X_i$$

where $k$ represents the total number of administered items (e.g., $k = 3$) and $X_i$ corresponds to the participant's numerical score on item $i$. Alternatively, structural equation modeling allows for latent factor estimation weighted by standardized factor loadings.

11. Permissions & Fee and Test Year

The contemporary PLCP formulation was published in 2017 in the Journal of Marketing by Huachao Gao, Yinlong Zhang, and Vikas Mittal. The scale adapts the classic "Willingness to Buy" instruments introduced by William B. Dodds, Kent B. Monroe, and Dhruv Grewal (1991) and Grewal, Monroe, and Krishnan (1998).

Licensing and Academic Use: The scale items, theoretical frameworks, and research paradigms published in the original articles are copyrighted by the American Marketing Association (AMA). However, under standard academic research conventions, these brief measurement stems are widely accessible for non-commercial scientific, educational, and scholarly experimentation without formal licensing fees, provided that appropriate bibliographic citation and attribution are given to Gao et al. (2017), Dodds et al. (1991), and Grewal et al. (1998). Commercial organizations and market research practitioners seeking to implement the scale within proprietary enterprise platforms should verify copyright policies with the respective journal publishers or original authors.

12. References

• 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
• Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). Effects of price, brand, and store information on buyers' product evaluations. Journal of Marketing Research, 28(3), 307–319. https://doi.org/10.1177/002224379102800305
• Gao, H., Zhang, Y., & Mittal, V. (2017). How does local–global identity affect price sensitivity? Journal of Marketing, 81(3), 62–79. https://doi.org/10.1509/jm.15.0430
• 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.
• 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
• Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: A means-end model and synthesis of evidence. Journal of Marketing, 52(3), 2–22. https://doi.org/10.1177/002224298805200302

13. Items of the Scale