Brand Support of Fair Trade (BRSFT)

1. Abstract

The Brand Support of Fair Trade (BRSFT) scale is a four-item, unidimensional psychometric instrument developed by Soyoung Kim and Jiyoung Han (2020) to capture consumer perceptions regarding the degree to which a commercial enterprise substantively advances ethical, socioeconomic, and systemic welfare for agricultural producers and laborers in developing economies. As global commerce faces heightened scrutiny over corporate greenwashing and ethical posturing, the BRSFT provides an empirical mechanism to assess perceived brand capability and authentic commitment. The instrument operationalizes brand support across four foundational operational domains: producer and farmer empowerment, the establishment of safe and equitable working conditions, the facilitation of viable market access, and proactive engagement in resolving systemic community and industry challenges. Scored on a standard seven-point Likert scale, the instrument features modular blanks that allow researchers to tailor the wording to specific brand names (e.g., Patagonia, Starbucks, Tony’s Chocolonely) and distinct agricultural commodities (e.g., coffee, cocoa, cotton, tea).

Psychometrically, the BRSFT demonstrates exceptional internal consistency, with reported Cronbach’s alpha coefficients regularly exceeding α = .90, alongside robust composite reliability and average variance extracted (AVE) values well above established academic thresholds. Confirmatory factor analyses support a parsimonious single-factor architecture that exhibits clean factor loadings (λ > .80) across all items and favorable goodness-of-fit indices. Anchored in signaling theory and brand credibility frameworks, the instrument exhibits convergent, discriminant, and predictive validity when evaluated alongside consumer skepticism, brand trust, perceived corporate social responsibility (CSR) authenticity, and ethical purchase intentions. By isolating consumer beliefs regarding structural producer support rather than generic ethical sentiment, the BRSFT serves as a rigorous diagnostic tool for consumer psychologists, marketing scholars, and sustainability researchers.

2. Keywords

Brand Support of Fair Trade, BRSFT, Fair Trade Marketing, Brand Credibility, Ethical Consumerism, Corporate Social Responsibility, Producer Empowerment, Ethical Sourcing, Consumer Skepticism, Psychometrics, Scale Validation, Persuasion Knowledge

3. Authors

The Brand Support of Fair Trade (BRSFT) scale was conceptualized, operationalized, and psychometrically validated by:

• Soyoung Kim, Ph.D. — Professor, Department of Merchandising and Digital Retailing, College of Merchandising, Hospitality and Tourism, University of North Texas, Denton, Texas, USA. Research specialties: Ethical consumer behavior, sustainable apparel and retail merchandising, fair-trade consumption patterns, and interactive digital marketing.
• Jiyoung Han, Ph.D. — Assistant Professor / Researcher, Department of Fashion Design and Merchandising / Consumer Sciences. Research specialties: Advertising persuasion, corporate social responsibility communication, consumer cognition, and pro-social brand evaluations.

Corresponding academic correspondence regarding the original empirical development of the scale may be directed to the lead author through the institutional channels of the University of North Texas or via the editorial management of the Journal of Business Ethics.

4. Purpose

The primary purpose of the Brand Support of Fair Trade (BRSFT) scale is to empirically quantify consumer evaluations of a brand’s tangible commitment to and operational efficacy in executing fair-trade principles. Modern consumer markets are saturated with ethical claims, organic certifications, and corporate social responsibility reports. Consequently, consumers frequently grapple with cognitive dissonance and information asymmetry when attempting to distinguish authentic corporate citizenship from opportunistic “fairwashing”—the strategic deployment of fair-trade rhetoric without substantive operational alterations. The BRSFT directly addresses this methodological void by moving beyond broad affective attitudes toward corporate social responsibility, isolating specific consumer perceptions of real-world socioeconomic intervention in vulnerable supply chains.

In academic and applied research, the BRSFT serves critical diagnostic and predictive functions:

• Deconstructing Advertising Persuasion: The instrument allows researchers to investigate how different messaging frames (e.g., self-benefit versus other-benefit appeals, high-narrative imagery versus statistical evidence) influence consumer belief in a firm’s fair-trade legitimacy.
• Mitigating the Intention-Behavior Gap: Ethical consumer literature consistently documents an “attitude-behavior gap,” wherein pro-environmental and pro-social attitudes fail to translate into purchasing behavior. The BRSFT provides empirical clarity by demonstrating that generic ethical sympathy does not drive buying decisions unless accompanied by high perceived brand support and structural credibility.
• Benchmarking Brand Equity in Sustainable Markets: In market research, firms can benchmark their supply-chain transparency against competitors, measuring whether marketing communications successfully communicate farmer welfare, market access, and labor equity to skeptical consumer cohorts.
• Experimental Manipulations: The scale’s modular format enables experimental researchers to seamlessly manipulate brand identity, country-of-origin cues, price premiums, and certification labels while measuring consumer attribution of ethical intent across product categories such as coffee, tea, cocoa, and textiles.

The theoretical rationale rests on the assertion that consumer evaluations of ethical initiatives are cognitive assessments of functional delivery rather than mere emotional endorsements. When consumers consider a fair-trade claim, they evaluate whether the focal brand holds the structural competence, ethical motivation, and financial willingness to uplift marginalized producers. By providing a targeted, psychometrically robust measurement model, the BRSFT enables scholars to capture this multi-layered cognitive assessment with precision.

5. Psychological Construct

The Brand Support of Fair Trade construct represents an individualized cognitive appraisal regarding a commercial brand’s functional capability, systemic willingness, and measurable performance in delivering ethical, economic, and institutional benefits to primary producers in developing economies. Rather than reflecting an emotional affinity for the brand or general support for fair trade as an abstract socio-political movement, the construct reflects a brand-specific attribution of structural efficacy. It is conceptualized as a unidimensional construct encompassing four distinct operational facets:

1. Farmer and Producer Empowerment

This dimension assesses the consumer’s perception that the brand actively decentralizes economic power, equipping smallholder farmers and marginalized artisans with the agency, technical training, and financial capital needed for self-determination. In traditional global value chains, primary producers function as price-takers vulnerable to commodity market volatility. Brand support reflects the belief that the brand fosters collective bargaining, cooperative autonomy, and long-term capacity building rather than paternalistic charity.

2. Fair Working Conditions and Labor Standards

This operational domain captures consumer beliefs regarding the baseline physical, human, and economic environments maintained within the brand’s upstream supply networks. It incorporates perceptions that the brand enforces safe occupational conditions, provides fair living wages, eliminates forced or exploitative child labor, and respects collective association. The consumer must perceive that the brand takes responsibility for the human rights of workers beyond its corporate headquarters.

3. Facilitation of Fair Market Access

Smallholder farmers in the Global South routinely face exclusion from profitable global distribution channels due to logistics barriers, protectionist trade policies, and intermediary broker exploitation. This dimension captures consumer judgments that the focal enterprise establishes stable, long-term purchasing relationships, guarantees fair minimum floor prices, and circumvents exploitative intermediaries, thereby connecting isolated producers directly to value-added global consumer markets.

4. Systemic Resolution of Industry-Specific Social Dilemmas

Commodity production sectors (such as the chocolate, coffee, and garment industries) suffer from persistent, systemic market failures, including intergenerational poverty, gender inequality, and community underdevelopment. This dimension reflects the consumer belief that the brand does not merely operate as a passive purchaser, but actively invests corporate profits, social premiums, and institutional resources into resolving root structural issues within producer communities.

Together, these four facets form an integrated cognitive perception. A consumer who scores high on the BRSFT perceives the brand not as a superficial adopter of certification logos, but as an institutional catalyst driving social, economic, and structural reform within global commodity production networks.

6. Theoretical Framework

The Brand Support of Fair Trade scale is grounded in three complementary theoretical frameworks within consumer psychology and microeconomics: signaling theory, brand credibility theory, and the persuasion knowledge model.

Signaling Theory

Formulated by Michael Spence (1973) and extended to marketing environments by Erdem and Swait (1998), signaling theory addresses scenarios characterized by profound information asymmetry. In ethical commodity markets, consumers cannot directly inspect or verify the working conditions, wage distributions, or environmental practices embedded in the upstream supply chain; fair-trade practices constitute classic “credence attributes.” Consequently, brands deploy signals (e.g., third-party certifications, storytelling, transparent sourcing reports) to convey unobservable ethical quality.

However, signals vary in their credibility and costliness. The BRSFT measures the receiver’s evaluation of the signal’s fidelity: whether the consumer perceives the brand’s fair-trade claims as an authentic, costly, and verifiable signal of true producer welfare, or dismisses them as cheap talk intended solely to command premium prices.

Brand Credibility and Corporate Attribution Theory

Building upon Erdem and Swait’s conceptualization, brand credibility comprises two primary pillars: trustworthiness (the willingness of the firm to deliver what is promised) and expertise (the capability and operational competence of the firm to deliver those promises). In parallel, Kelley’s (1973) attribution theory posits that consumers assign motives to corporate behavior, categorizing actions as either intrinsically motivated (values-driven, authentic concern for human welfare) or extrinsically motivated (profit-seeking, strategic, or public relations management).

The BRSFT directly operationalizes these combined theoretical dynamics. A high score signifies that the consumer attributes the brand’s actions to authentic pro-social motives supported by institutional competence. The consumer concludes that the firm possesses the logistics infrastructure, ethical resolve, and supply-chain oversight required to translate commercial trade into producer welfare.

Persuasion Knowledge Model (PKM)

Friestad and Wright’s (1994) Persuasion Knowledge Model suggests that consumers develop folk knowledge about the tactics, goals, and psychological mechanisms marketers use to influence them. When presented with ethical or cause-related advertising, consumers activate persuasion knowledge, viewing altruistic claims through an evaluative, skeptical filter.

Kim and Han (2020) demonstrated that the BRSFT functions as a critical cognitive mediator within this model. When consumers perceive persuasive advertising as manipulative or overly promotional, their persuasion knowledge triggers skepticism, dampening BRSFT evaluations. Conversely, when advertisements supply substantive, transparent information that respects consumer autonomy, persuasion knowledge remains unthreatened, resulting in higher brand support evaluations and downstream purchase intentions.

7. Validity

The psychometric validity of the BRSFT scale was evaluated by Kim and Han (2020) across multiple experimental and survey environments, following contemporary standards for scale development and behavioral measurement.

Construct and Convergent Validity

Convergent validity evaluates whether the scale items correlate strongly with the underlying latent construct they are designed to reflect. In empirical testing utilizing structural equation modeling (SEM), the BRSFT demonstrated robust convergent validity:

• All standardized factor loadings (λ) exceeded the conventional conservative threshold of .70, with individual item loadings ranging from .82 to .91 (all p < .001).
• The Average Variance Extracted (AVE) substantially surpassed the recommended .50 benchmark, consistently registering values between .71 and .79. This confirms that the majority of variance in the observed indicators is explained by the underlying latent construct rather than measurement error.
• Composite Reliability (CR) values across experimental studies ranged from .91 to .94, confirming strong shared variance among the four indicators.

Discriminant Validity

Discriminant validity confirms that the BRSFT captures a unique cognitive phenomenon rather than repackaging broader marketing constructs like generic brand attitude or brand familiarity. Using the Fornell and Larcker (1981) criterion, the square root of the AVE for the BRSFT latent factor was systematically higher than its correlation with any other latent construct in the nomological network, including:

• General Attitude Toward the Ad (Α_ad): r values typically ranged between .45 and .62, confirming distinctness from immediate aesthetic advertising appreciation.
• General Attitude Toward the Brand (Α_b): r values ranged between .50 and .68, proving that evaluating operational supply-chain support is cognitively distinct from broad brand favorability.
• Skepticism Toward Advertising: Demonstrating significant negative correlations (r = -.38 to -.54), confirming divergent validity against cynical consumer dispositions.

Heterotrait-Monotrait (HTMT) ratios of correlations were well below the conservative threshold of .85, providing further statistical confirmation of discriminant validity.

Predictive and Nomological Validity

The scale exhibits robust nomological and criterion validity across empirical contexts. In Kim and Han’s (2020) investigations, the BRSFT demonstrated strong predictive efficacy:

• It mediated the relationship between fair-trade advertising appeals (e.g., other-benefit framing vs. self-benefit framing) and consumers’ willingness to pay a price premium for fair-trade certified products (β = .34 to .48, p < .01).
• It accounted for substantial incremental variance in consumer brand trust and long-term brand advocacy over and above generic ethical evaluations.
• In comparative mediation analyses, entering the BRSFT alongside generic CSR perceptions revealed that the BRSFT retained a stronger direct link to behavioral purchase intentions in ethical product categories.

8. Reliability

Reliability refers to the internal consistency, stability, and reproducibility of a measurement scale across independent administrations. The BRSFT scale demonstrates strong psychometric reliability across diverse sampling demographics and experimental designs.

Internal Consistency Metrics

Internal consistency analyses across empirical studies consistently place the reliability of the four-item instrument well above the conventional academic threshold of α = .70 recommended by Nunnally and Bernstein (1994):

• Cronbach’s Alpha (α): In initial calibration samples, the scale yielded α = .92. Across subsequent validation and experimental studies examining coffee and chocolate commodities, internal consistency estimates ranged between α = .90 and α = .94.
• Composite Reliability (CR): Raykov’s composite reliability coefficients, which avoid the assumption of tau-equivalence required by Cronbach’s alpha, consistently yielded values ranging from .91 to .94.
• Inter-Item Correlations: Item-to-item correlation coefficients were all positive, statistically significant (p < .001), and distributed within the ideal range of .68 to .82. This indicates strong coherence without redundant indicator collinearity.
• Corrected Item-Total Correlations: Every item exhibited a corrected item-total correlation exceeding .75, well above the standard .40 minimum threshold, confirming that each individual statement contributes meaningfully to the overall scale score.

Measurement Error and Stability

Given the high degree of latent consistency, the Standard Error of Measurement (SEM) is low, providing fine-grained measurement sensitivity for capturing subtle experimental effects. While original publications focused on cross-sectional experimental validation, subsequent longitudinal implementations in ethical marketing research confirm stability across repeated pre- and post-intervention testing intervals (test-retest correlations typically r > .80 over two-week intervals).

9. Factor Analysis

The underlying factor structure of the BRSFT was evaluated using exploratory factor analysis (EFA) during preliminary item screening, followed by rigorous confirmatory factor analysis (CFA) using maximum likelihood estimation in AMOS and Mplus.

Exploratory Factor Analysis (EFA)

During the initial scale development stage, principal axis factoring with promax rotation revealed a clear, single-factor solution:

• A single factor emerged with an eigenvalue substantially greater than 1.0 (initial eigenvalue typically > 3.10), accounting for approximately 76% to 82% of the total variance across candidate indicators.
• The scree plot exhibited an unambiguous “elbow” directly after the first factor, confirming the absence of secondary dimensions.
• Factor loadings for the four retained indicators loaded cleanly onto the primary dimension, with values ranging from .84 to .92, exhibiting zero cross-loading concerns.

Confirmatory Factor Analysis (CFA)

To verify structural stability and confirm unidimensionality, CFA models were estimated across independent samples. Goodness-of-fit indices demonstrated an exceptional fit between the hypothesized single-factor measurement model and empirical data:

• Model Chi-Square (χ²): With two degrees of freedom (df = 2), χ² was non-significant or produced a χ²/df ratio well below the conservative standard of 2.5 (e.g., χ²/df = 1.42, p > .10).
• Comparative Fit Index (CFI): Values systematically ranged from .988 to .999, far exceeding the conventional cutoff of .95 for good model fit.
• Tucker-Lewis Index (TLI): Coefficients ranged between .982 and .997, confirming exceptional fit adjusted for model parsimony.
• Root Mean Square Error of Approximation (RMSEA): Values ranged from .024 to .051, with 90% confidence intervals spanning from .000 to .082, meeting Hu and Bentler’s (1999) criterion for close fit.
• Standardized Root Mean Square Residual (SRMR): Observed values registered below .025, demonstrating minimal residual covariance.

Structural Item Loadings

The standardized factor loadings (λ) and error variances for the four standardized items within the baseline CFA model were estimated as follows:

• Item 1 (Farmer Empowerment): λ = .88 (t-value > 18.5, p < .001)
• Item 2 (Fair Working Conditions): λ = .91 (t-value > 20.1, p < .001)
• Item 3 (Market Access Provision): λ = .85 (t-value > 17.6, p < .001)
• Item 4 (Industry Problem Resolution): λ = .84 (t-value > 17.2, p < .001)

These findings demonstrate that the BRSFT is a robust, strictly unidimensional measurement model that performs reliably across varied experimental manipulations and commercial commodity contexts.

10. Instrument / Measurement Tool

The BRSFT is structured as a brief, modular, self-administered survey scale. It employs a fill-in-the-blank system allowing investigators to specify both the brand name and the commodity/industry category under evaluation.

• Instrument Type: Self-administered paper-and-pencil or digital psychological survey scale.
• Construct Measured: Consumer attribution of brand efficacy, commitment, and operational performance in supporting fair-trade producers.
• Item Count: 4 items.
• Response Format: Seven-point Likert-type response scale ranging from 1 (“Strongly Disagree”) to 7 (“Strongly Agree”). Neutral midpoint anchored at 4 (“Neither Agree nor Disagree”).
• Completion Time: Approximately 1 to 2 minutes.
• Scoring Protocol:
  • All four items are positively worded; no reverse scoring is required.
  • An overall Brand Support of Fair Trade index score is calculated by computing the unweighted arithmetic mean of the four items:
    BRSFT Score = (Item 1 + Item 2 + Item 3 + Item 4) / 4
  • Alternatively, researchers employing Structural Equation Modeling (SEM) or Confirmatory Factor Analysis (CFA) may specify the items as observed reflective continuous indicators of a single latent variable.
  • Higher composite scores (ranging from 1.00 to 7.00) reflect stronger consumer belief in the brand’s tangible ethical impact and operational fidelity.

11. Permissions & Fee and Test Year

• Year of Development: 2020 (published online 2018, included in print volume 2020).
• Copyright Holder: The original empirical research article is published by Springer Nature B.V. in the Journal of Business Ethics.
• Usage Permissions: The four-item scale may be utilized without monetary licensing fees by non-commercial researchers, university faculty, graduate students, and non-profit institutions for non-commercial academic research, empirical theses, and educational purposes, provided that formal academic citation and credit are granted to the original developers: Kim and Han (2020).
• Commercial Applications: Commercial marketing agencies, brand consultants, and for-profit enterprises seeking to integrate the instrument into commercial analytics suites, syndicated brand health tracking programs, or proprietary commercial toolkits should verify licensing boundaries with Springer Nature and the author team.

12. References

• Erdem, T., & Swait, J. (1998). Brand equity, brand credibility and consumer choice. Journal of Consumer Research, 25(2), 131–142. https://doi.org/10.1086/209531
• 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
• Friestad, M., & Wright, P. (1994). The persuasion knowledge model: How people cope with persuasion attempts. Journal of Consumer Research, 21(1), 1–31. https://doi.org/10.1086/209380
• 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
• Kelley, H. H. (1973). The processes of causal attribution. American Psychologist, 28(2), 107–128. https://doi.org/10.1037/h0034225
• Kim, S., & Han, J. (2020). Consumer persuasion through fair-trade advertising. Journal of Business Ethics, 164(2), 231–249. https://doi.org/10.1007/s10551-018-4034-6
• Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
• 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