Attitude Toward Private Label Products Scale (ATPLP)

1. Abstract

The Attitude Toward Private Label Products Scale (ATPLP), developed by Scot Burton, Donald R. Lichtenstein, Richard G. Netemeyer, and Judith A. Garretson in 1998, is an established psychometric instrument designed to assess consumers’ generalized affective and cognitive predispositions toward private label brands (store brands) across diverse grocery and retail product categories. Prior to its development, empirical research in consumer psychology and retailing often conflated a favorable orientation toward store brands with peripheral constructs such as generalized price consciousness, coupon proneness, or value consciousness. The ATPLP resolves this conceptual ambiguity by offering a psychometrically rigorous, unidimensional, six-item scale that isolates a consumer’s global favorability toward store brands relative to national brands.

The instrument is administered using a seven-point Likert-type response format ranging from 1 (“Strongly Disagree”) to 7 (“Strongly Agree”). Across multiple calibration and validation samples—including independent consumer surveys and actual grocery household scanner panel data—the ATPLP has demonstrated internal consistency reliability (with Cronbach’s alpha coefficients systematically exceeding .88 and composite reliabilities above .89). Confirmatory factor analyses across diverse samples consistently support a robust, invariant unidimensional factor structure characterized by strong factor loadings (ranging from .68 to .88) and fit statistics (e.g., Comparative Fit Index [CFI] > .97, Root Mean Square Error of Approximation [RMSEA] < .05). The instrument demonstrates convergent, discriminant, nomological, and criterion-related validity, exhibiting predictive efficacy for objective store brand market basket share beyond the statistical contributions of demographic variables, price consciousness, and value consciousness.

2. Keywords

Attitude Toward Private Label Products Scale, ATPLP, store brands, private label products, consumer attitudes, psychometrics, scale validation, price consciousness, value consciousness, retail marketing

3. Authors

The Attitude Toward Private Label Products Scale was developed and validated through a collaborative scholarly initiative conducted by four consumer behavior and psychometrics researchers:

• Scot Burton, Ph.D. — Distinguished Professor and Tyson Chair in Food and Consumer Products Retailing, Department of Marketing, Sam M. Walton College of Business, University of Arkansas, Fayetteville, Arkansas, United States. Dr. Burton’s research interests encompass consumer health and nutrition disclosures, pricing perceptions, retail strategy, and measurement theory in consumer psychology.
• Donald R. Lichtenstein, Ph.D. — Professor Emeritus of Marketing, Department of Marketing, Leeds School of Business, University of Colorado Boulder, Boulder, Colorado, United States. Dr. Lichtenstein has published extensively on consumer price perceptions, price-quality heuristics, sales promotion mechanics, and psychometric operationalizations of consumer price constructs.
• Richard G. Netemeyer, Ph.D. — Ralph A. Beeton Professor of Free Enterprise, Department of Marketing, McIntire School of Commerce, University of Virginia, Charlottesville, Virginia, United States. A methodological authority in structural equation modeling, measurement error, scale development, and organizational psychology, Dr. Netemeyer is a co-author of foundational psychometric textbooks, including Scaling Procedures: Issues and Applications.
• Judith A. Garretson (Folse), Ph.D. — Professor of Marketing, Sam M. Walton College of Business, University of Arkansas (formerly at Louisiana State University), United States. Her scholarship focuses on consumer promotion response, brand equity, retail branding architectures, and front-of-pack nutritional labeling.

4. Purpose

The economic landscape of modern consumer packaged goods (CPG) retailing has undergone structural transformations since the late twentieth century. Private labels—goods manufactured for and sold under the proprietary banner of a specific retail distributor—evolved from low-cost, utilitarian “generics” in plain packaging to sophisticated tiered product portfolios competing directly with major national manufacturer brands. Despite this macroeconomic transition, early academic research routinely treated private label purchasing as a mechanical artifact of budget constraints, poverty, or price-based deal seeking. Researchers lacked a standardized, methodologically vetted psychometric instrument capable of capturing the cognitive appraisal and affective affinity that modern consumers direct specifically toward store brand programs.

The primary purpose of the Attitude Toward Private Label Products Scale (ATPLP) is to measure an individual’s generalized, enduring positive cognitive appraisal of and affective affinity toward private label products across product categories. Burton, Lichtenstein, Netemeyer, and Garretson (1998) established the ATPLP to address significant theoretical and methodological deficiencies in the marketing and consumer psychology literature:

First, prior investigations frequently relied on single-item measures, ad-hoc category-specific preference indices, or proxy behavioral measures (e.g., past self-reported percentage of private label expenditures). Single-item indices are susceptible to random measurement error, lack construct breadth, and preclude formal assessments of internal consistency reliability and measurement invariance. The ATPLP provides a standardized, psychometrically grounded multi-item tool that can be applied across empirical research environments.

Second, consumer researchers needed to determine whether private label preference represented a distinct psychological disposition or merely an alternative expression of price sensitivity or frugality. The ATPLP was conceptualized to test discriminant boundaries. Burton et al. demonstrated that consumers can be highly price conscious without holding favorable views of store brands (e.g., opting instead for discounted or coupon-promoted national brands). Conversely, consumers may exhibit a high ATPLP because they perceive private labels as smart purchases that match national brand functional quality, regardless of whether they consider themselves frugal.

In research contexts, the ATPLP allows investigators to segment populations according to cognitive-affective brand orientation, model psychological transitions during retail brand adoption, evaluate the structural antecedents of retail loyalty, and control for baseline brand dispositions when assessing packaging modifications, in-store merchandising displays, or comparative advertising campaigns. In managerial practice, category managers and market researchers utilize the ATPLP to assess target demographic receptivity toward new private label tiers (e.g., organic, premium, or bio-based store lines), calculate store equity, and calibrate brand portfolio strategies against national brand counterparts.

5. Psychological Construct

The Attitude Toward Private Label Products (ATPLP) construct is defined as a generalized, stable, unidimensional favorable disposition toward the class of private label products across diverse retail categories relative to national brands. Rather than assessing episodic, category-bound purchase intent (such as deciding between store-brand or name-brand milk), the ATPLP captures an overarching perceptual schema. This schema guides how an individual processes information, evaluates performance risks, and derives emotional or financial satisfaction when selecting store-branded products over manufacturer-branded alternatives.

The construct encompasses several interrelated cognitive and affective facets that form an integrated unidimensional structure:

Perceived Value and Economic Rationality

A core element of the ATPLP construct is the consumer’s cognitive calculation of value for money. Value consciousness reflects the ratio of quality received to price paid. Within the private label schema, high-ATPLP consumers do not view store brands merely as cheap alternatives; they view them as economically rational purchases. The consumer perceives that the margin between the price discount and any marginal performance variance favors the store brand, viewing it as the “best buy” in the category.

Equivalence of Functional Quality

Historically, consumers perceived significant functional and sensory quality gaps between store brands and national brands. The ATPLP construct captures the rejection of this perceived deficit. Consumers with a favorable attitude toward private labels evaluate store brands as functionally comparable, structurally reliable, and manufactured to standards equivalent to those of national brands. Consequently, the negative belief that store brands are intrinsically of poor quality is rejected.

Positive Affect and Smart-Shopper Identity

Beyond transactional calculations, the ATPLP incorporates an affective dimension: shopping pleasure, self-affirmation, and pride. Consumers with high ATPLP scores experience positive emotional feedback when purchasing store brands, often linking the choice to a “smart-shopper” identity. Selecting the private label confirms their consumer competence and freedom from manufacturer brand advertising claims.

Cross-Category Receptivity

A defining property of the ATPLP construct is its cross-category generalizability. While low-ATPLP consumers may occasionally purchase store brands in low-risk commodity categories (e.g., granulated sugar, table salt, paper towels), high-ATPLP consumers hold a broad perceptual orientation that extends into higher-risk categories (e.g., infant care, personal care, complex packaged foods). They welcome the availability of private labels across retail categories.

6. Theoretical Framework

The theoretical architecture of the ATPLP is informed by several foundational theories within cognitive psychology, information processing, and consumer decision-making:

Cue Utilization Theory

Originally formulated by Cox (1967) and expanded by Olson and Jacoby (1972), Cue Utilization Theory posits that products present an array of informational cues that consumers use to infer quality and performance. These cues are categorized as intrinsic (physical attributes such as taste, design, ingredients, and texture) or extrinsic (external indicators such as brand name, price, retail store reputation, and country of origin). When intrinsic cues cannot be readily evaluated prior to purchase and consumption, consumers rely on extrinsic signals.

National brand manufacturers invest heavily in advertising to establish the brand name as a primary extrinsic indicator of superior quality. Consumers with a low ATPLP rely heavily on this brand cue, viewing lower-priced store brands with skepticism. In contrast, consumers with a high ATPLP rely less on national brand names as quality heuristics; they interpret the retailer’s store banner as an adequate guarantee of quality or believe that intrinsic product formulations are largely equivalent across manufacturers.

Information Economics and Signaling Theory

Under Signaling Theory (Spence, 1973; Erdem & Swait, 1998), asymmetric information between buyers and sellers creates market inefficiencies. Brand names serve as credible market signals that reduce consumer search costs and perceived risk. National brands convey credibility through long-term investments in advertising and market presence. The ATPLP reflects differences in how consumers process market signals. High-ATPLP consumers view the retail distributor as a credible guarantor, whereas low-ATPLP consumers require manufacturer-level brand signals to mitigate perceived functional and psychosocial risk.

Perceived Risk Theory

Conceptualized by Bauer (1960) and elaborated by Mitchell (1999), Perceived Risk Theory posits that consumer behavior is guided by efforts to minimize potential negative outcomes across several dimensions: financial, functional, physical, psychological, and social. Private label purchases historically introduced perceived functional risk (inferior performance) and social risk (negative evaluation by peers). The ATPLP operates as an attitudinal mechanism that reflects reduced risk perception across these domains, enabling consumers to choose store brands without concern regarding product failure or social disapproval.

The Price-Perceived Quality Schema

Lichtenstein, Ridgway, and Netemeyer (1993) established that price functions dualistically in consumer cognition: as a financial constraint (allocative role) and as an indicator of product excellence (informational role). Consumers who hold a strong price-perceived quality heuristic infer that lower price points reflect inferior craftsmanship. The ATPLP captures a distinct mental model: high-ATPLP consumers reject the assumption that lower price points indicate inferior quality, viewing the price differential instead as the elimination of unnecessary manufacturer brand premiums.

7. Validity

Burton, Lichtenstein, Netemeyer, and Garretson (1998) established the psychometric validity of the ATPLP across multiple independent samples using distinct data collection methodologies, including student calibration cohorts, non-student adult consumer samples, and an empirical grocery household scanner panel from Information Resources, Inc. (IRI).

Content and Face Validity

Content validity was established through systematic item generation based on literature reviews of retail brand choice, price perceptions, and consumer decision-making. Candidate items were evaluated by a panel of expert marketing faculty and psychometricians. Items exhibiting semantic ambiguity, excessive category specificity, or conceptual overlap with general frugality were eliminated, leaving an optimized set that captures the core components of the construct.

Convergent Validity

Convergent validity was supported using confirmatory factor analysis (CFA). Across all validation samples, every standardized factor loading ($lambda$) for the six items was statistically significant ($p < .001$), with magnitude estimates ranging from .68 to .88. The Average Variance Extracted (AVE) values exceeded the standard .50 benchmark (Fornell & Larcker, 1981), indicating that the underlying latent construct accounts for the majority of variance observed across its indicators rather than measurement error.

Discriminant Validity

To demonstrate that the ATPLP represents a distinct construct rather than a reflection of existing price-related traits, Burton et al. conducted discriminant analyses against several established scales:

• Value Consciousness: Positively correlated with ATPLP ($r pprox .40$ to $.52$), yet nested two-factor CFA models demonstrated that fixing the inter-construct correlation to unity ($phi = 1.0$) resulted in a statistically significant worsening of model fit ($\Delta\chi^2 > 100, p < .001$).
• Price Consciousness: Displayed moderate positive correlations ($r pprox .30$ to $.44$). The shared variance ($r^2 < .20$) remained below the AVE of both constructs, confirming discriminant validity.
• Coupon Proneness and Sale Proneness: Exhibited weak-to-moderate correlations ($r pprox .15$ to $.30$), demonstrating that store brand preference is distinct from general promotional responsiveness.
• National Brand Loyalty: Demonstrated significant negative correlations ($r pprox -.42$ to $-.58$), confirming that store brand attitudes are inversely related to manufacturer brand attachment.

Predictive and Criterion-Related Validity

A notable strength of the validation program by Burton et al. (1998) was the inclusion of behavioral criterion data. In a sample of household primary shoppers linked to longitudinal grocery scanner records across several retail packaged goods categories, the ATPLP predicted actual private label market basket share ($r pprox .45, p < .001$). Hierarchical regression models demonstrated that the ATPLP accounted for significant incremental variance in objective store brand purchasing behavior beyond the effects of household income, education, price consciousness, and value consciousness ($\Delta R^2 = .08$ to $.14, p < .001$).

8. Reliability

The reliability of the ATPLP has been demonstrated across multiple demographic segments, geographic markets, and retail environments:

Internal Consistency Reliability

In the original scale development study by Burton et al. (1998), internal consistency was examined across three distinct empirical samples:

• Sample 1 (Undergraduate Student Sample, $N = 188$): Cronbach’s alpha ($lpha$) was .88, with item-to-total correlations ranging from .62 to .76.
• Sample 2 (Adult Non-Student Consumer Sample, $N = 214$): Cronbach’s alpha was .89, with composite reliability (CR) reaching .90 and an Average Variance Extracted (AVE) of .61.
• Sample 3 (IRI Household Grocery Scanner Panel, $N = 143$): Cronbach’s alpha was .91, with composite reliability reaching .91 and an AVE of .64.

Subsequent independent studies in consumer behavior and international retailing (e.g., Garretson, Fisher, & Burton, 2002; Batra & Sinha, 2000) have reported Cronbach’s alpha coefficients for the ATPLP ranging between .86 and .93, confirming that the scale retains its internal consistency across diverse empirical settings.

Test-Retest Stability

A subsample of respondents was re-administered the ATPLP over a three-to-four-week interval to evaluate temporal stability. The resulting test-retest correlation coefficient was $r_{tt} = .84$ ($p < .001$), indicating that the scale captures an enduring attitudinal disposition rather than short-term situational fluctuations.

Standard Error of Measurement

Across the validation cohorts, the standard error of measurement (SEM) was low (typically between 0.35 and 0.42 on the 1-to-7 response scale), indicating high measurement precision around individual observed scores.

9. Factor Analysis

The dimensional structure of the ATPLP was established using exploratory and confirmatory factor analytic procedures:

Exploratory Factor Analysis (EFA)

During initial item calibration, an initial pool of candidate items was evaluated using principal axis factoring and maximum likelihood extraction with oblique (promax) and orthogonal (varimax) rotations. Examination of the scree plot and eigenvalues revealed a single dominant factor accounting for over 60% of the total variance across items. The first unrotated factor exhibited an eigenvalue greater than 3.70, while the second factor produced an eigenvalue well below 0.70. All six retained items demonstrated primary factor loadings exceeding .65, with no significant cross-loadings.

Confirmatory Factor Analysis (CFA)

To verify structural stability, single-factor measurement models were estimated using maximum likelihood structural equation modeling in LISREL and AMOS. Across validation cohorts, the unidimensional model demonstrated strong fit to the observed covariance matrices:

• Adult Consumer Sample ($N = 214$): $\chi^2(9) = 14.82$, $p = .096$; Goodness of Fit Index (GFI) = .98; Comparative Fit Index (CFI) = .99; Incremental Fit Index (IFI) = .99; Root Mean Square Residual (RMR) = .04; Root Mean Square Error of Approximation (RMSEA) = .048 (90% CI [.000, .091]).
• Scanner Panel Validation Sample ($N = 143$): $\chi^2(9) = 12.11$, $p = .207$; GFI = .97; CFI = .99; TLI = .98; RMSEA = .043.

Standardized factor loadings ($lambda$) across the six items in the confirmatory solutions are summarized below:

• Item 1: $lambda pprox .74$ to $.81$ ($t$-value > 11.5)
• Item 2: $lambda pprox .78$ to $.84$ ($t$-value > 12.8)
• Item 3: $lambda pprox .72$ to $.79$ ($t$-value > 10.9)
• Item 4 (Reverse-scored): $lambda pprox .68$ to $.75$ ($t$-value > 9.8)
• Item 5: $lambda pprox .80$ to $.88$ ($t$-value > 13.5)
• Item 6: $lambda pprox .75$ to $.83$ ($t$-value > 12.1)

Comparative model testing confirmed that alternative two-factor specifications (e.g., separating functional quality perceptions from transactional value/affect) did not yield statistically significant improvements in fit and produced inter-factor correlations exceeding .85, supporting the parsimonious single-factor model.

10. Instrument / Measurement Tool

The ATPLP is structured as a brief self-report instrument:

• Test Type: Self-administered psychometric rating scale; non-cognitive, attitudinal consumer disposition measure.
• Format: Paper-and-pencil or digital/computer-assisted survey questionnaire.
• Number of Items: 6 items.
• Response Scale: 7-point Likert-type scale anchored by 1 = “Strongly Disagree” to 7 = “Strongly Agree”. Intermediate points may be labeled (2 = Disagree, 3 = Somewhat Disagree, 4 = Neither Agree nor Disagree, 5 = Somewhat Agree, 6 = Agree) or presented as numerical continuum anchors.
• Administration Time: Approximately 2 to 3 minutes.
• Target Population: Adult consumers, primary household shoppers, retail patrons, and adolescent/young adult purchasing agents.
• Scoring Procedure:
  • Step 1 (Reverse Scoring): Item 4 is negatively phrased and must be reversed prior to computing scale scores: $\text{Item } 4_{\text{rev}} = 8 – \text{Raw Score}$.
  • Step 2 (Composite Aggregation): Calculate the composite score by averaging the six items: $\text{ATPLP Mean} = \frac{\sum_{i=1}^6 \text{Item}_i}{6}$, or summing the items to produce a total score ranging from 6 to 42.
• Score Interpretation:
  • Mean Scores 1.00 – 3.25 (Total: 6 – 19): Unfavorable attitude toward private label products. High reliance on national brand cues, high perceived risk regarding store brands, and low propensity to purchase store brands.
  • Mean Scores 3.26 – 4.75 (Total: 20 – 28): Ambivalent or category-dependent attitude. Purchase decisions depend on promotional conditions, explicit price differentials, or product category complexity.
  • Mean Scores 4.76 – 7.00 (Total: 29 – 42): Highly favorable attitude toward private label products. High perceived equivalence with national brands, strong perceived value, and regular cross-category store brand purchasing.

11. Permissions & Fee and Test Year

The Attitude Toward Private Label Products Scale was developed and published in 1998:

• Publication Year: 1998.
• Original Publication: Journal of Advertising, Volume 27, Issue 4, pages 25–41.
• Copyright Holder: The original article is copyrighted by the American Academy of Advertising, with publishing services provided by Taylor & Francis Group.
• Licensing and Academic Use: The scale items were published in the original 1998 peer-reviewed article for scholarly and research applications. Non-commercial academic researchers may use the instrument for educational, non-profit empirical studies without licensing fees, provided the source publication is cited in resulting work. Commercial applications, inclusion within proprietary software platforms, or commercial syndicated consumer panels require permissions or licensing from the publisher and copyright holders.

12. References

• Batra, R., & Sinha, I. (2000). Consumer-level factors moderating the success of private label brands. Journal of Retailing, 76(2), 175–191. https://doi.org/10.1016/S0022-4359(00)00027-0
• Bauer, R. A. (1960). Consumer behavior as risk taking. In R. S. Hancock (Ed.), Dynamic Marketing for a Changing World (pp. 389–398). American Marketing Association.
• Burton, S., Lichtenstein, D. R., Netemeyer, R. G., & Garretson, J. A. (1998). A scale for measuring attitude toward private label products and an examination of its psychological and behavioral correlates. Journal of Advertising, 27(4), 25–41. https://doi.org/10.1080/00913367.1998.10673567
• Cox, D. F. (1967). Risk Taking and Information Handling in Consumer Behavior. Division of Research, Graduate School of Business Administration, Harvard University.
• Erdem, T., & Swait, J. (1998). Brand equity as a signaling phenomenon. Journal of Consumer Psychology, 7(2), 131–157. https://doi.org/10.1207/s15327663jcp0702_02
• 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
• Garretson, J. A., Fisher, D., & Burton, S. (2002). Antecedents of private label attitude and national brand promotion attitude: Similarities and differences. Journal of Retailing, 78(2), 91–99. https://doi.org/10.1016/S0022-4359(02)00071-4
• Lichtenstein, D. R., Ridgway, N. M., & Netemeyer, R. G. (1993). Price perceptions and consumer shopping behavior: A field study. Journal of Marketing Research, 30(2), 234–245. https://doi.org/10.1177/002224379303000208
• Mitchell, V. W. (1999). Consumer perceived risk: Conceptualisations and models. European Journal of Marketing, 33(1/2), 163–195. https://doi.org/10.1108/03090569910249229
• Netemeyer, R. G., Bearden, W. O., & Sharma, S. (2003). Scaling Procedures: Issues and Applications. SAGE Publications. https://doi.org/10.4135/9781412985772
• Olson, J. C., & Jacoby, J. (1972). Cue utilization in the quality perception process. In M. Venkatesan (Ed.), Proceedings of the Third Annual Conference of the Association for Consumer Research (pp. 167–179). Association for Consumer Research.
• Richardson, P. S., Dick, A. S., & Jain, A. K. (1994). Extrinsic and intrinsic cue effects on perceptions of store brand quality. Journal of Marketing, 58(4), 28–36. https://doi.org/10.1177/002224299405800403
• 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