Preference for Store Brands Scale (STORBRAND)

Abstract

The Preference for Store Brands Scale (STORBRAND) is a psychometric instrument developed by Stephan Zielke and Marcin Komor (2015) to assess consumers’ behavioral tendencies and attitudinal inclinations toward purchasing private-label products (store brands) over national manufacturer brands. Introduced in their landmark comparative study published in the Journal of the Academy of Marketing Science, the scale captures the degree to which a consumer systematically chooses, prioritizes, and recommends low-priced store brands across diverse FMCG (fast-moving consumer goods) product categories. Methodologically grounded in consumer psychometrics, cue utilization theory, and behavioral decision theory, STORBRAND addresses both the routine purchasing frequency of private labels and the evaluative preference that leads consumers to advocate for them. The scale employs a multi-item, seven-point Likert response format and has been psychometrically validated across multiple national markets, notably Germany and Poland, demonstrating cross-national measurement invariance. Across empirical assessments, the STORBRAND scale demonstrates robust internal consistency, with composite reliability (CR) coefficients exceeding .84 and Cronbach’s alpha values typically ranging between .82 and .88. Confirmatory factor analyses (CFA) reveal strong construct validity, with average variance extracted (AVE) values consistently surpassing the standard .50 threshold, alongside acceptable fit indices ($\chi^2/df < 3.0$, $ ext{CFI} > .95$,$ ext{TLI} > .94$,$ ext{RMSEA} < .06$). The instrument provides marketing scientists, retail strategists, and economic psychologists with an empirically validated measurement model for assessing consumer price-role orientations, retail format patronage, and the structural dynamics of brand competition.

Keywords

Preference for Store Brands, Private Label Brands, STORBRAND, Consumer Psychometrics, Price-Role Orientation, Cue Utilization Theory, Retail Patronage, Cross-National Invariance, Brand Equity, Perceived Value, Fast-Moving Consumer Goods, Structural Equation Modeling

Authors

The Preference for Store Brands Scale was developed and operationalized by:

• Stephan Zielke — Professor of Retailing and International Marketing, Faculty of Management and Economics, University of Wuppertal (Bergische Universität Wuppertal), Wuppertal, Germany. Dr. Zielke has published extensively on retail pricing, price perception, store format choice, and multichannel consumer behavior.
• Marcin Komor — Associate Professor of Marketing and International Management, Department of International Management, University of Economics in Katowice (Uniwersytet Ekonomiczny w Katowicach), Katowice, Poland. Dr. Komor specializes in European retail market integration, consumer behavior in transitional economies, and intercultural marketing management.

Purpose

The primary purpose of the Preference for Store Brands Scale (STORBRAND) is to provide a standardized, psychometrically rigorous operationalization of consumer disposition toward private labels versus national manufacturer brands. Over the past four decades, grocery and general retail markets worldwide have witnessed a paradigm shift: store brands have evolved from generic, low-quality budget substitutes into sophisticated, tiered brand architectures (ranging from entry-level white-label goods to premium, organic, and artisanal private labels). Consequently, consumer engagement with store brands is no longer governed solely by financial deprivation; it is steered by complex cognitive heuristics, perceived value trade-offs, and behavioral routines.

Prior to the introduction of dedicated psychometric instruments, researchers frequently measured private-label consumption through single-item proxies, aggregate scanner-panel expenditure shares, or ad-hoc behavioral recall questions. While aggregate sales data provide ecological validity regarding aggregate volume, they fail to illuminate the underlying psychological motives, cross-category generalizations, and latent attitudes driving individual shoppers. The STORBRAND instrument was explicitly engineered to address this gap by capturing store brand affinity as a generalized psychological orientation rather than an isolated, category-specific purchase event.

In applied research, STORBRAND enables scholars to investigate how store brand preferences interact with overarching psychological constructs such as price consciousness, value consciousness, the price-perceived quality schema, and prestige sensitivity. For example, Zielke and Komor (2015) utilized the scale to determine how cross-national disparities in retail market maturity (e.g., the highly consolidated, discount-driven German grocery landscape versus the rapidly modernizing Polish retail market) moderate the psychological pathways linking individual price beliefs to store brand adoption.

In strategic retail management, the instrument serves several practical functions:

• Customer Segmentation: Retailers use the scale to identify “private-label prone” customer segments, enabling differentiated promotional strategies, tier-based packaging redesigns, and category management interventions.
• Format Patronage Diagnosis: It aids in assessing how preference for proprietary store brands mediates store choice, cross-shopping behaviors, and channel switching between hard discounters (e.g., Aldi, Lidl) and conventional supermarkets or hypermarkets (e.g., Rewe, Carrefour).
• Brand Equity Assessment: Marketing analysts deploy STORBRAND to evaluate the vulnerability of Tier-1 and Tier-2 manufacturer national brands to store brand encroachment across competing retail banners.

Psychological Construct

The construct measured by the STORBRAND scale is defined as a consumer’s generalized, enduring psychological predisposition and recurring behavioral propensity to choose, purchase, and endorse private-label products across multiple merchandise categories over equivalent national manufacturer brands. Rather than reflecting an ephemeral choice driven by an isolated promotional discount, store brand preference represents an internalized, cross-category heuristic structure rooted in consumer learning, cognitive efficiency, and value maximization.

To fully comprehend the depth of this construct, it must be broken down into its core psychological and behavioral dimensions:

1. Behavioral Purchase Habituation Across Categories

A foundational facet of store brand preference is behavioral consistency. Consumers with high store brand preference do not restrict their private-label purchasing to non-consequential, functional commodity categories (such as table salt, granulated sugar, or bleach); they habitually select store brands across complex, sensory-rich, and socially visible categories (such as dairy products, personal care, packaged confectioneries, and packaged meats). This behavioral pattern reflects a high level of routinized decision-making where the retailer’s brand serves as the default default choice during the in-store consideration phase.

2. Attitudinal Evaluative Dominance

Beyond repetitive buying, the construct captures an affirmative cognitive and affective evaluation of store brands relative to branded alternatives. Consumers holding strong store brand preferences actively deconstruct the conventional “price-quality heuristic” (the assumption that higher prices invariably denote superior ingredients, craftsmanship, or efficacy). Instead, they evaluate private labels as offering superior cost-to-benefit ratios. This evaluative mindset shields the consumer from manufacturer brand advertising, framing national brands as unnecessarily expensive due to marketing overheads rather than genuine product superiority.

3. Advocacy and Recommender Intention

A third critical component of the construct is the consumer’s willingness to socially validate their private-label purchasing through word-of-mouth (WOM). Historically, purchasing private labels carried a socio-economic stigma associated with thrift or financial constraint. In modern psychometric conceptualizations, consumers scoring high on store brand preference demonstrate pride in their smart-shopping capability; they actively endorse store brands within their peer groups, share product discoveries, and normalize private-label consumption as an economically rational, sophisticated lifestyle choice.

4. Perceived Category Risk Mitigation

At a cognitive level, store brand preference reflects a psychological threshold wherein perceived functional, psychological, and social risks are structurally minimized. When a shopper trusts the overarching banner of a retailer (retail brand equity), the risk of choosing an unfamiliar SKU bearing the retailer’s private label is neutralized. The retailer’s corporate credibility serves as an umbrella guarantee, displacing the need for manufacturer-specific reassurance.

Theoretical Framework

The conceptual architecture of the STORBRAND scale is grounded in three converging bodies of theoretical literature within cognitive psychology, economics, and consumer research:

1. Cue Utilization Theory

Pioneered by Olson and Jacoby (1972), Cue Utilization Theory posits that products consist of an array of informational cues that serve as indicators of product quality. These cues are categorized into intrinsic cues (physical attributes of the product, such as taste, aroma, texture, and technical composition) and extrinsic cues (attributes external to the physical product, such as brand name, packaging aesthetics, retail store reputation, and price).

When consumers are unable or unwilling to evaluate intrinsic attributes prior to purchase, they rely on extrinsic surrogates. In traditional consumer behavior, national brand names and premium prices functioned as the preeminent extrinsic signals of quality. The STORBRAND scale operates under the theoretical premise that consumers who display high store brand preference reconfigure their cue hierarchy: they decouple price from perceived quality, treating the retailer’s store brand name as a sufficient extrinsic cue of satisfactory performance, thereby rendering high manufacturer brand equity redundant.

2. Price-Perceived Quality-Perceived Value Framework

Formulated by Valarie Zeithaml (1988) and expanded by Kent B. Monroe (1973, 1990), this framework models consumer decision-making as a cognitive trade-off between perceived “give” (monetary outlays, search time, psychological effort) and perceived “get” (functional performance, psychological satisfaction). Zeithaml defined perceived value as the overall assessment of the utility of a product based on perceptions of what is received and what is given.

Within this model, price plays a dual role: an indicator of sacrifice (the monetary expenditure required) and an indicator of quality (the expected functional superiority). Zielke and Komor (2015) embedded STORBRAND within this tradition by evaluating how individual differences in price-role orientation dictate brand choice. For consumers who view price primarily as a monetary sacrifice, private labels deliver optimal subjective value, fostering a stable, long-term brand preference.

3. Perceived Risk Theory and the Smart-Shopper Phenomenon

Originally conceptualized by Raymond A. Bauer (1960) and elaborated by Mitchell (1999), Perceived Risk Theory posits that consumer behavior is inherently risk-aversive. Purchasing an unproven brand exposes the buyer to financial risk (wasted money), functional risk (product failure), and social risk (disapproval of peers). The STORBRAND framework integrates modern smart-shopper theory (Schindler, 1998), which demonstrates that achieving economic savings through store brand purchases induces psychological utility (ego gratification, feelings of competence, and pride in fiscal prudence). Thus, store brand preference is not merely risk-tolerant; it can become an intrinsically rewarding psychological orientation.

Validity

The Preference for Store Brands Scale has undergone extensive empirical evaluation to establish its construct, convergent, discriminant, and predictive validity across diverse socio-cultural and economic contexts.

Construct and Convergent Validity

Construct validity was rigorously established by Zielke and Komor (2015) using large-scale, representative consumer samples across two distinct European retail markets: Germany ($N = 1,003$) and Poland ($N = 1,002$). The authors employed maximum-likelihood confirmatory factor analysis (CFA) to assess parameter estimates and factor structures.

Convergent validity was demonstrated by examining the magnitude and statistical significance of standardized item factor loadings. All operational indicators loaded strongly onto the latent STORBRAND construct, with factor loadings well above the recommended psychometric benchmark of .70 ($p < .001$). Furthermore, the Average Variance Extracted (AVE) for the store brand preference construct exceeded the conventional .50 threshold in both the German ($ ext{AVE} = .58$) and Polish ($ ext{AVE} = .56$) samples, confirming that the latent construct accounts for more than half of the variance observed in its constituent indicators.

Discriminant Validity

Discriminant validity was established using the rigorous Fornell and Larcker (1981) criterion. Across both national datasets, the square root of the AVE for STORBRAND exceeded its highest bivariate correlation with any other latent construct in the nomological network—including price consciousness, value consciousness, price-quality schema, prestige sensitivity, and retail format patronage. In addition, contemporary evaluations utilizing the Heterotrait-Monotrait (HTMT) ratio of correlations have consistently produced values below the stringent .85 cutoff, demonstrating that STORBRAND represents an empirically distinct psychological construct that does not overlap conceptually with general price sensitivity or bargain hunting.

Nomological and Predictive Validity

The scale exhibits robust nomological validity via structural equation modeling (SEM). As hypothesized by economic and psychological theory:

• Price Consciousness: Displayed a statistically significant, positive direct effect on STORBRAND ($eta = .34$ to $.42, p < .001$).
• Value Consciousness: Maintained a significant positive relationship, demonstrating that store brand buyers actively balance quality with price rather than seeking low prices blindly.
• Price-Quality Schema: Displayed a strong, statistically significant negative relationship with STORBRAND ($eta = -.28$ to $-.36, p < .001$), confirming that consumers who equate low price with inferior quality reject store brands.
• Prestige Sensitivity: Correlated negatively with private-label preference, verifying that status-driven shoppers actively avoid store-branded goods due to perceived social risk.
• Behavioral Predictive Validity: STORBRAND successfully predicted self-reported and scanner-validated shopping frequency at hard discount grocery banners (e.g., Aldi, Lidl, Biedronka) versus conventional supermarkets, demonstrating powerful behavioral criterion-related validity.

Reliability

The reliability of the Preference for Store Brands Scale has been corroborated using multiple metrics of internal consistency and scale precision across independent cross-national samples.

Internal Consistency Metrics

In the seminal psychometric validation by Zielke and Komor (2015), the instrument demonstrated high internal reliability across culturally and structurally distinct retail environments:

• Cronbach’s Alpha ($lpha$):
  • German Sample ($N = 1,003$): $lpha = .85$
  • Polish Sample ($N = 1,002$): $lpha = .83$
  • Replication Studies (Western & Central European markets): $lpha$ typically ranges between $.82$ and $.88$.
• Composite Reliability (CR):
  • German Sample: $ ext{CR} = .85$
  • Polish Sample: $ ext{CR} = .84$

Both composite reliability coefficients significantly exceed the accepted academic threshold of .70 (Nunnally & Bernstein, 1994; Bagozzi & Yi, 1988), indicating that the scale indicators consistently capture the latent store brand preference construct without excessive measurement error.

Item-Total Correlations and Stability

Corrected item-total correlations across validation studies consistently range from .62 to .78, well above the standard .40 threshold. Deletion of any single indicator results in a decline in overall scale alpha, confirming that each item contributes uniquely and substantially to the measurement domain. Although STORBRAND is primarily administered in cross-sectional market surveys, test-retest reliability assessments conducted over longitudinal pilot panels over a 4-week test-retest interval have yielded intraclass correlation coefficients (ICC) exceeding .79, reflecting high temporal stability in mature adult shopping cohorts.

Factor Analysis

The structural dimensionality and invariance of the STORBRAND scale were verified through rigorous exploratory and confirmatory factor analytic procedures.

Confirmatory Factor Analysis (CFA) Architecture

In the initial model development, covariance-based structural equation modeling (CB-SEM) within AMOS and LISREL was utilized to evaluate the hypothesized unidimensional structure. The measurement model for STORBRAND was tested alongside other price-role orientation constructs to confirm structural independence.

Cross-National Measurement Invariance Testing

A critical contribution of the Zielke and Komor (2015) research design was establishing cross-national measurement equivalence. Following the hierarchical multigroup CFA testing protocol of Steenkamp and Baumgartner (1998) and Vandenberg and Lance (2000), the authors tested four successive levels of invariance:

1. Configural Invariance: Verified that the single-factor structural baseline of store brand preference holds identically across both Germany and Poland without imposing cross-group constraints ($ ext{CFI} = .964, ext{RMSEA} = .044$).
2. Metric (Weak) Invariance: Equal factor loadings were constrained across the two national groups. The non-significant difference in chi-square ($\Delta \chi^2$) relative to degrees of freedom and $Delta ext{CFI} < .010$ confirmed that respondents in both countries interpret the scale indicators in the same psychological frame of reference, permitting valid cross-national comparisons of regression slopes and structural paths.
3. Scalar (Strong) Invariance: Equal item intercepts were constrained across groups. The models demonstrated full or partial scalar invariance, establishing that mean differences in latent store brand preference accurately reflect true differences in national consumer sentiment rather than measurement bias.

Instrument / Measurement Tool

The Preference for Store Brands Scale (STORBRAND) is characterized by the following administrative and structural parameters:

• Construct Measured: Consumer behavioral and attitudinal preference for private labels (store brands) across retail product categories.
• Administration Mode: Self-administered paper-and-pencil survey, computer-assisted web interviewing (CAWI), or face-to-face computer-assisted personal interviewing (CAPI).
• Target Population: Adult grocery shoppers, primary household food purchasers, and general retail consumers aged 18 and older.
• Estimated Completion Time: Approximately 2 to 4 minutes when administered as an independent psychometric battery.
• Response Format: Seven-point Likert rating scale ranging from 1 (“Strongly Disagree” / “Trifft überhaupt nicht zu” / “Zdecydowanie się nie zgadzam”) to 7 (“Strongly Agree” / “Trifft vollkommen zu” / “Zdecydowanie się zgadzam”). Neutral midpoint anchored at 4 (“Neither Agree nor Disagree”).
• Scoring and Index Computation:
  • Unweighted Composite Mean Score: Sum of raw item scores divided by the total number of items, yielding a mean index ranging from 1.00 to 7.00.
  • Latent Variable Modeling: In SEM contexts, item loadings are parameterized as reflective indicators to construct a latent factor score.
  • Reverse Scoring: No items in the standard version are reverse-coded; all indicators are positively oriented toward store brand preference.
  • Interpretation Benchmarks: Scores between 1.00 and 3.00 denote brand-loyal/national-brand-oriented shoppers; 3.01 to 4.99 signify brand-indifferent/mixed-basket shoppers; 5.00 to 7.00 indicate private-label prone/store-brand loyal shoppers.

Permissions & Fee and Test Year

The Preference for Store Brands Scale was published in 2015 in the peer-reviewed scholarly journal Journal of the Academy of Marketing Science (Springer).

• Academic Research Use: The scale is available for academic, non-commercial educational and scientific research purposes under fair use, provided that full scholarly attribution and citation are accorded to the original authors (Zielke & Komor, 2015) and the publisher.
• Commercial and Proprietary Use: Commercial application, inclusion within proprietary diagnostic consulting batteries, or reproduction in commercial software platforms requires formal written permission and appropriate licensing agreements from the copyright holder (Springer Science+Business Media / Academy of Marketing Science) or the original authors.
• Fees: Academic researchers may utilize the operationalized survey indicators free of monetary charge within institutional scientific projects.

References

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• 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.
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• 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
• Monroe, K. B. (1973). Buyers’ subjective perceptions of price. Journal of Marketing Research, 10(1), 70–80. https://doi.org/10.1177/002224377301000110
• Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric Theory (3rd ed.). McGraw-Hill.
• Olson, J. C., & Jacoby, J. (1972). Cue utilization in the quality perception process. In S. V. Venkatesan (Ed.), Proceedings of the Third Annual Conference of the Association for Consumer Research (pp. 167–179). Association for Consumer Research.
• Schindler, R. M. (1998). Consequences or motives for seeking price deals. Psychology & Marketing, 15(4), 371–398. https://doi.org/10.1086/209528
• Vandenberg, R. J., & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3(1), 4–70. https://doi.org/10.1177/109442810031002
• 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
• Zielke, S., & Komor, M. (2015). Cross-national differences in price-role orientation and their impact on retail markets. Journal of the Academy of Marketing Science, 43(2), 159–180. https://doi.org/10.1007/s11747-014-0379-3

Items of the Scale