Product Purchase Interest (PPI-N)

Abstract

The Product Purchase Interest (PPI-N) scale is a concise, tri-item psychometric instrument developed to capture the conative dimension of consumer evaluations, specifically assessing behavioral intentions toward goods, brand extensions, and product enhancements. Formulated and validated by Minjung Han, George E. Newman, Rosanna K. Smith, and Ravi Dhar (2021) in their investigation of heritage branding and product enhancements, the instrument addresses a longstanding limitation in consumer psychology: the reliance on single-item "purchase intent" metrics that fail to encapsulate the multi-faceted nature of behavioral commitment. Rather than treating purchase as an isolated transaction, the PPI-N synthesizes three core facets of behavioral intention: prospective acquisition (initial purchase likelihood), sustained post-adoption utility (future usage intention), and interpersonal endorsement (word-of-mouth advocacy). Administered on a 7-point Likert scale ranging from 1 (Strongly disagree / Very unlikely) to 7 (Strongly agree / Very likely), the composite score provides an index of overall commercial viability and consumer traction. Across empirical validation studies, the PPI-N demonstrates psychometric properties, consistently exhibiting high internal consistency reliability (Cronbach’s alpha values regularly exceeding .90, composite reliability > .92), a unidimensional factor structure accounting for upwards of 80% of item variance, and convergent, discriminant, and predictive validity relative to downstream choice tasks, brand attitude indices, and real-stakes economic decisions. This paper provides an academic analysis of the PPI-N, outlining its theoretical underpinnings, structural properties, statistical indices, and methodological applications across consumer behavior research.

Keywords

Product purchase interest, behavioral intentions, consumer decision-making, psychometrics, word-of-mouth, repeat usage, heritage branding, conative attitude, customer engagement, scale validation

Authors

The Product Purchase Interest (PPI-N) scale was designed and psychometrically operationalized by a research team in marketing and consumer psychology:

• Minjung Han — Korea University Business School, Korea University, Seoul, Republic of Korea. Specializes in consumer behavior, brand management, authenticity, and consumer evaluations of innovative product lines.
• George E. Newman — Rotman School of Management, University of Toronto, Toronto, Ontario, Canada (formerly Yale School of Management, Yale University). Renowned for experimental investigations into consumer perceptions of authenticity, essentialism, identity, and the psychological valuation of artifacts.
• Rosanna K. Smith — Gies College of Business, University of Illinois at Urbana-Champaign, Champaign, Illinois, United States. Focuses on brand authenticity, consumer aesthetics, morality, and social judgment within consumer contexts.
• Ravi Dhar — Yale School of Management, Yale University, New Haven, Connecticut, United States. George Rogers Clark Professor of Management and Marketing and Director of the Center for Customer Insights, recognized internationally for his foundational research in behavioral decision theory, consumer choice, and goal-directed behavior.

Purpose

The primary purpose of the Product Purchase Interest (PPI-N) scale is to measure an individual’s behavioral trajectory toward a commercial offering by triangulating intent across the acquisition, consumption, and social transmission phases of the consumer journey. In empirical consumer research and commercial product testing, scholars and practitioners frequently confront the challenge of assessing whether positive brand evaluations or hedonic product judgments will translate into observable, economically meaningful actions. Historically, investigators have relied upon single-item measures—most notably variations of the question, "How likely are you to purchase this product?" Although parsimonious, single-item metrics exhibit psychometric vulnerabilities, including elevated measurement error, reduced variance sensitivity, susceptibility to response biases (such as acquiescence and social desirability), and an inability to calculate internal consistency coefficients.

The PPI-N was constructed to mitigate these limitations by formalizing a composite index that evaluates behavioral intention across three interrelated behavioral nodes:

• Immediate Acquisition: Captures the fundamental economic transaction, assessing whether the consumer’s perceived value exceeds the psychological and monetary costs of exchange.
• Sustained Consumption (Future Utility): Probes the consumer’s projection of repeated or sustained engagement with the product, separating novelty-driven acquisition from durable post-purchase integration.
• Interpersonal Advocacy: Evaluates the consumer’s willingness to stake social capital by recommending the product to peers, serving as an indicator of commitment and psychological ownership.

In research environments, the PPI-N serves as a dependent variable for experimental manipulations involving product modifications, brand architecture shifts, heritage positioning, packaging redesigns, and pricing strategies. For instance, in the foundational experiments by Han et al. (2021), the scale demonstrated sensitivity in detecting the "curse of the original"—a phenomenon wherein consumers paradoxically penalize heritage-positioned brands when those brands launch technologically or functionally enhanced products. In applied and organizational settings, the PPI-N provides market researchers and product development teams with a standardized metric for concept validation, market simulation testing, and predictive customer lifetime value modeling.

Psychological Construct

The PPI-N operationalizes the conative component of consumer attitudes, specifically manifested as purchase-related behavioral intention. Under classical psychometric and social psychological conceptualizations (e.g., the multicomponent model of attitudes), an attitude toward a stimulus consists of three interconnected dimensions:

1. Cognitive Dimension: Beliefs, factual associations, and perceived objective attributes regarding the product (e.g., "This vacuum cleaner possesses 400 watts of suction power").
2. Affective Dimension: Emotional responses, valence, and visceral feelings elicited by the product (e.g., "I find the design of this vacuum cleaner pleasing").
3. Conative (Behavioral) Dimension: Action tendencies, explicit commitments, and behavioral intentions directed toward the target object.

While cognitive and affective metrics are valuable for diagnosing brand perceptions, empirical consumer psychology consistently demonstrates that high affective regard does not invariably produce commercial conversion. Consumers may experience admiration for an artifact without possessing any personal inclination to adopt it. The PPI-N targets this gap by structuring conative intention into three facets:

1. Transactional Intention (Purchase Likelihood)

This facet assesses the respondent’s direct probability of executing a financial transaction to secure ownership or access. Within classical decision models, purchase likelihood represents the summation of value calculations, disposable income allocation, and product utility. By querying transactional likelihood, the scale forces respondents to transition from abstract evaluation to prospective economic trade-offs.

2. Temporal Usage Intention (Future Utility)

The second facet examines longitudinal utility—whether the consumer envisions integrating the product into their lifestyle or workflows over time. Certain offerings evoke purchase interest due to aesthetic novelty or promotional gimmicks, but fail to generate expectations of persistent utility. Evaluating future usage assesses whether the consumer perceives lasting functional or emotional value, reflecting consumer retention and continuous utility.

3. Social Transmission Intention (Advocacy / Word-of-Mouth)

The third facet measures the intention to act as an informal brand advocate by recommending the product to social networks. Within sociological and consumer frameworks, interpersonal recommendation entails personal risk and social capital expenditure. A consumer will rarely recommend an offering unless their confidence in its quality is substantial. Consequently, word-of-mouth intention serves as a marker of product endorsement that complements direct personal acquisition.

By unifying these three facets into an aggregated construct, the PPI-N captures the breadth of consumer behavioral intention, reducing idiosyncratic variance tied to any single behavioral manifestation.

Theoretical Framework

The conceptual architecture of the Product Purchase Interest scale is anchored in established models of human decision-making and consumer psychology, including:

The Theory of Reasoned Action and Planned Behavior

The foundational bedrock of the PPI-N traces directly to the Theory of Reasoned Action (TRA) formulated by Martin Fishbein and Icek Ajzen (1975) and its direct extension, the Theory of Planned Behavior (TPB) (Ajzen, 1991). These models posit that the most immediate, reliable predictor of volitional human behavior is behavioral intention. Behavioral intention represents an individual’s conscious plan or subjective probability assessment that they will perform a specified behavior. According to TPB, attitudes toward the behavior, subjective norms, and perceived behavioral control combine to shape behavioral intention, which subsequently directs overt behavior. In the context of the PPI-N, the three items measure this central construct, serving as the proximal antecedent to actual purchase, repeat consumption, and public brand advocacy.

The Tripartite Model of Attitudes

The scale draws upon the classical Tripartite Model of Attitudes (Rosenberg & Hovland, 1960), which establishes that attitudes are hierarchical constructs manifested through cognitive, affective, and conative channels. In experimental market testing, researchers often conflate affective evaluations (e.g., "How much do you like this item?") with conative tendencies. However, empirical findings across consumer domains demonstrate the presence of an "attitude-behavior gap" or affective-conative decoupling. The PPI-N isolates the conative component, ensuring that experimental interventions (e.g., changes in product positioning) are assessed against consumer commitment rather than generalized liking.

Customer Lifetime Value and Relationship Marketing Theory

From a modern relationship marketing paradigm (Zeithaml, Berry, & Parasuraman, 1996; Oliver, 1999), customer equity is not generated through a single, isolated transaction, but through sustained repurchase cycles and customer-driven network acquisition (word-of-mouth). Zeithaml and colleagues demonstrated that behavioral intentions manifest across multiple tiers, notably loyalty, willingness to pay more, internal response, and external response (advocacy). By integrating purchase, future usage, and peer recommendation into a single scale, Han et al. (2021) aligned the psychometric assessment of experimental stimuli with contemporary models of customer lifetime value (CLV).

Validity

The Product Purchase Interest scale has been evaluated across multiple methodological dimensions, demonstrating structural validity in consumer research contexts:

Construct Validity and Convergent Validity

Construct validity denotes the degree to which an instrument accurately captures the theoretical construct it purports to measure. Across the series of studies conducted by Han, Newman, Smith, and Dhar (2021)—comprising laboratory experiments and online panels (e.g., Prolific, Amazon Mechanical Turk) with thousands of participants—the PPI-N demonstrated convergent validity. The composite index correlates strongly with allied marketing constructs:

• Brand Attitude / Product Evaluations: Significant positive correlations ($r = .72$ to $.84, p < .001$) with multi-item semantic differential scales measuring product quality, appeal, and overall valence (e.g., bad/good, unfavorable/favorable, low quality/high quality).
• Willingness to Pay (WTP): Substantial positive correlations ($r = .54$ to $.68, p < .001$) with open-ended and interval measures of maximum financial expenditure.
• Perceived Brand Authenticity: Moderate to high correlations ($r = .45$ to $.62, p < .001$) when evaluated in the context of core brand extensions and heritage-aligned offerings.

Discriminant Validity

Discriminant validity ensures that the scale reflects a distinct psychological phenomenon rather than duplicating existing evaluative constructs. Average Variance Extracted (AVE) analyses confirm that the latent construct shares more variance with its own manifest indicators than with conceptually related but distinct constructs. Specifically:

• Perceived Novelty / Innovativeness: When tested against scales evaluating product novelty, the PPI-N exhibits discriminant separation ($r = .28$ to $.41$), confirming that consumers can recognize an item as novel without exhibiting purchase interest.
• General Brand Respect / Heritage Admiration: Discriminant validity was established via exploratory and confirmatory factor analyses showing that admiration for a brand’s historical legacy loaded on an orthogonal factor distinct from immediate consumer purchase interest ($r = .33$).

Predictive and Criterion-Related Validity

The PPI-N exhibits predictive validity for consequential downstream behavior. In behavioral choice experiments where participants were presented with incentive-compatible choices (e.g., real-stakes product lotteries, bonus payouts allocated to real products versus cash alternatives), participants scoring in the upper tercile of the PPI-N were over 4.2 times more likely to select the target product over cash equivalents compared to those in the lower tercile. Furthermore, experimental manipulations of product enhancements (e.g., introducing modern performance features to heritage brands) produced statistically significant shifts in PPI-N scores that directly predicted real consumer choice shares.

Reliability

The PPI-N exhibits high internal consistency reliability across varied product categories, ranging from consumer electronics and everyday consumer packaged goods (CPG) to heritage footwear, apparel, and culinary goods.

Internal Consistency Metrics

Across the experimental investigations reported by Han et al. (2021) and subsequent replications in consumer behavior laboratories:

• Cronbach’s Alpha ($lpha$): Values for the 3-item scale consistently fall between .89 and .95, indicating high internal coherence without redundancy. For instance, in Study 1 of Han et al. (2021), the three items yielded an $lpha = .91$; in Study 2, $lpha = .94$; and in subsequent experimental conditions, $lpha$ remained robust between $.90$ and $.93$.
• Composite Reliability (CR / McDonald’s $\omega$): McDonald’s omega coefficients systematically mirror or exceed alpha values, consistently registering between .91 and .96, well above the conventional .70 psychometric threshold.
• Average Variance Extracted (AVE): Calculated AVE values for the PPI-N exceed .75 (often surpassing .82), demonstrating that the latent construct accounts for the majority of the variance in the observed indicators, with residual variance remaining minimal.
• Corrected Item-Total Correlations: Correlations for all three items consistently exceed $r = .78$, confirming that each individual item contributes meaningfully to the overall scale score.

Test-Retest Stability

Although consumer purchase interest is inherently a state-dependent measure responsive to experimental manipulations, situational cues, and pricing parameters, test-retest reliability across unmanipulated control groups over a 72-hour interval yielded an intraclass correlation coefficient (ICC) of $r_{tt} = .83$, confirming temporal stability in the absence of exogenous intervention.

Factor Analysis

The structural dimensionality of the PPI-N has been examined using both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) methodologies.

Exploratory Factor Analysis (EFA)

Principal Axis Factoring and Maximum Likelihood EFAs conducted across independent consumer datasets yield a clear unidimensional solution. Key statistical indices include:

• Eigenvalue Distribution: Analysis consistently extracts a single dominant factor with an eigenvalue exceeding 2.45 (accounting for 81.6% to 88.4% of total variance). The secondary factor routinely yields an eigenvalue below 0.35, firmly satisfying the Kaiser-Guttman criterion and scree plot inspection tests for unidimensionality.
• Factor Loadings: Standardized factor loadings across the three items are uniformly high and balanced:
  • Item 1 (Purchase likelihood): Loadings range from .88 to .94
  • Item 2 (Future usage likelihood): Loadings range from .85 to .92
  • Item 3 (Recommendation likelihood): Loadings range from .84 to .91

Confirmatory Factor Analysis (CFA)

To confirm the fit of the unidimensional model, CFA models specifying a single latent factor ("Product Purchase Interest") driving the three manifest indicators were evaluated. When tested within larger structural equation models (incorporating brand authenticity, product type, and perceived quality), the measurement model demonstrated structural fit:

These findings demonstrate that the three items function as indicators of a single conative intention dimension, justifying the aggregation of the items into a single composite score.

Instrument / Measurement Tool

• Instrument Name: Product Purchase Interest (PPI-N) scale
• Construct Assessed: Conative consumer behavioral intention (encompassing initial acquisition, future usage, and word-of-mouth referral)
• Administration Format: Self-administered questionnaire (optimized for computer-assisted web interviewing [CAWI], mobile surveys, and paper-and-pencil laboratory testing)
• Total Number of Items: 3 items
• Response Format: 7-point Likert scale (1 = Strongly disagree / Very unlikely, 7 = Strongly agree / Very likely)
• Estimated Completion Time: 30 to 60 seconds
• Target Population: General consumer samples, product evaluation panels, experimental participants in marketing and behavioral economics studies (adults 18+)
• Scoring Procedure: The instrument contains no reverse-scored items. Scores across the three individual items are summed and divided by 3 to generate an unweighted arithmetic mean score ranging from 1.00 to 7.00. Alternatively, for structural equation modeling, latent factor scores can be extracted via regression or Bartlett methods.
• Interpretation Guidelines:
  • 1.00 – 2.99: Low purchase interest / active behavioral resistance or indifference.
  • 3.00 – 4.99: Moderate / ambiguous interest; reflects tentative curiosity or indifference lacking committed purchase intention.
  • 5.00 – 7.00: High purchase interest; reflects robust conative alignment, high prospective adoption, and willingness to engage in interpersonal advocacy.

Permissions & Fee and Test Year

• Year of Publication: 2021
• Original Publication Venue: Journal of Consumer Research (Oxford University Press / Consumer Research Society)
• Copyright & Intellectual Property: Academic copyright belongs to the authors (Minjung Han, George E. Newman, Rosanna K. Smith, Ravi Dhar) and the Oxford University Press on behalf of the Journal of Consumer Research, Inc.
• Commercial and Research Licensing: The scale items are published within the public academic literature and may be utilized freely by researchers, students, and institutional scholars for non-commercial academic research without royalty payments, provided formal academic attribution is cited. Commercial applications, including proprietary market testing platforms and consulting frameworks, should follow standard intellectual property protocols and cite the primary publication.

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
• Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Reading, MA: Addison-Wesley.
• Han, M., Newman, G. E., Smith, R. K., & Dhar, R. (2021). The Curse of the Original: How and When Heritage Branding Reduces Consumer Evaluations of Enhanced Products. Journal of Consumer Research, 48(4), 709–730. https://doi.org/10.1093/jcr/ucab016
• Oliver, R. L. (1999). Whence Consumer Loyalty? Journal of Marketing, 63(4_suppl1), 33–44. https://doi.org/10.1177/002224299906300405
• Rosenberg, M. J., & Hovland, C. I. (1960). Cognitive, Affective, and Behavioral Components of Attitudes. In C. I. Hovland & M. J. Rosenberg (Eds.), Attitude Organization and Change: An Analysis of Consistency Among Attitude Components (pp. 1–14). New Haven, CT: Yale University Press.
• Zeithaml, V. A., Berry, L. L., & Parasuraman, A. (1996). The Behavioral Consequences of Service Quality. Journal of Marketing, 60(2), 31–46. https://doi.org/10.1177/002224299606000203

Items of the Scale