Sponsor Self-Interest Perception (SSIP)

1. Abstract

The Sponsor Self-Interest Perception (SSIP) scale is a specialized, three-item psychometric measurement tool developed by Patti Williams, Gavan J. Fitzsimons, and Lauren G. Block in their seminal 2004 investigation published in the Journal of Consumer Research. The instrument assesses the degree to which an individual perceives the sponsor or questioner behind an intention measurement—or broader marketing communication—as operating under a self-interested, profit-driven, or subjective agenda versus a benign, objective, and public-interest-oriented motive. Operating through a seven-point semantic differential response format, the scale evaluates three fundamental semantic dyads: self-interest, profit motivation, and subjective orientation. Psychometrically, the instrument demonstrates robust unidimensionality, high internal consistency reliability, and rigorous convergent, discriminant, and criterion-related validity across experimental consumer behavior paradigms.

Originally designed as an empirical manipulation check and cognitive mediator within the context of the question-behavior effect (the phenomenon whereby merely asking questions about future behaviors systematically shifts actual performance of those behaviors), the SSIP has become a vital instrument in consumer psychology, persuasion research, marketing ethics, and public health communication. By quantifying the extent to which target audiences activate their persuasion knowledge in response to perceived source motives, the scale allows behavioral scientists to predict defensive processing, source derogation, message resistance, and behavioral divergence. This article delivers an exhaustive academic examination of the SSIP, tracing its theoretical origins in attribution theory and persuasion models, psychometric properties, structural composition, statistical factor structure, empirical validation history, and practical guidelines for contemporary behavioral research.

2. Keywords

Sponsor Self-Interest Perception, Persuasion Knowledge Model, Question-Behavior Effect, Mere Measurement Effect, Attribution Theory, Consumer Psychology, Source Credibility, Perceived Ulterior Motives, Semantic Differential, Manipulation Check, Behavioral Compliance, Persuasion Intent

3. Authors

The Sponsor Self-Interest Perception scale was conceptualized, operationalized, and validated by three prominent scholars in marketing science and consumer psychology:

• Patti Williams, Ph.D.: Vice Dean of Executive Education and the Ira A. Lipman Associate Professor of Marketing at the Wharton School of the University of Pennsylvania. Dr. Williams is an internationally recognized expert on consumer emotions, emotional conflict, and the role of affect and persuasion knowledge in consumer decision-making.
• Gavan J. Fitzsimons, Ph.D.: Edward S. & Rose H. Donnell Professor of Marketing and Psychology at the Fuqua School of Business, Duke University. Professor Fitzsimons’s pioneering research centers on non-conscious processes, behavioral nudge dynamics, social influence, consumer reactance, and the unconscious influences of brand interactions.
• Lauren G. Block, Ph.D.: Lippert Professor of Marketing at the Zicklin School of Business, Baruch College, City University of New York (CUNY). Dr. Block is an established authority in public health marketing, health risk communication, consumer well-being, and preventive health behavior interventions.

4. Purpose

The primary purpose of the Sponsor Self-Interest Perception scale is to quantify an audience member’s cognitive appraisal of a communication sponsor’s underlying intentions. Specifically, it gauges whether the entity framing an inquiry or promotional message is perceived as acting out of commercial opportunism and financial gain, or acting from a benign, public-service, or scientifically neutral posture. In experimental and applied behavioral research, uncovering how audiences discern sponsor motives is essential for explaining why identical communication tactics yield diametrically opposed behavioral consequences.

The origin of the SSIP was rooted in the resolution of a theoretical paradox surrounding the question-behavior effect, also known as the mere-measurement effect. Decades of behavioral research documented that when consumers are asked hypothetical or intention questions regarding their likelihood of performing a target behavior (e.g., “Do you intend to purchase a new vehicle in the next six months?” or “Do you plan to receive a flu vaccination?”), the mere act of measuring that intention substantially increases the probability that they will actually execute the focal behavior. Initial theories posited that this effect operated automatically via heightened cognitive accessibility of underlying attitudes, scripted behavioral pathways, or cognitive dissonance reduction.

However, Williams, Fitzsimons, and Block recognized an important boundary condition: consumers do not navigate communication environments passively. When consumers detect that an intention question originates from a source with an ulterior, self-serving commercial agenda (such as an automotive dealership inquiring about purchase intent to stimulate sales), they interpret the inquiry not as an innocuous survey question, but as a veiled persuasion attempt. Conversely, when the exact same inquiry originates from a seemingly benign sponsor (such as an independent academic research team or an objective consumer advocacy group), consumers fail to activate defensive cognitive resources, treating the inquiry as non-threatening and thereby exhibiting the classical question-behavior effect.

The SSIP was therefore engineered to fulfill several complementary scientific functions:

• Experimental Manipulation Check: To empirically verify that experimental manipulations of sponsor identity (e.g., commercial firm vs. independent non-profit entity vs. university laboratory) successfully and selectively trigger distinct levels of perceived source motivation without confounding other message variables.
• Mediational Analysis: To serve as a continuous cognitive mediator explaining the indirect path between sponsor disclosure and subsequent behavioral compliance or reactance.
• Diagnostic Research Tool: In applied marketing and public communication settings, the scale assesses consumer skepticism, corporate social responsibility authenticity, brand halo effects, and the psychological boundary where educational marketing crosses into perceived manipulative advertising.
• Health and Public Policy Assessment: Public health communicators deploy the SSIP to verify that health awareness campaigns, screening prompts, and preventive behavioral reminders maintain high perceived objectivity and avoid being misconstrued as pharmaceutical or commercial lobbying.

5. Psychological Construct

The psychological construct measured by the SSIP is Perceived Sponsor Self-Interest, a specific facet of source attribution within the broader architecture of cognitive social psychology and consumer skepticism. Perceived self-interest captures an observer’s subjective evaluation of the motivational asymmetry underlying an interaction—specifically, whether the communicator stands to gain private utility (economic rent, profit, strategic leverage) at the expense of, or indifferent to, the message recipient’s well-being.

Although operationalized as a parsimonious, unifactorial construct, Perceived Sponsor Self-Interest synthesizes three deeply intertwined conceptual dimensions:

5.1. Perceived Egoistic Motivation vs. Altruism

The core dimension of the construct differentiates between egoistic motivations (actions undertaken exclusively to maximize the actor’s own utility) and altruistic or pro-social motivations (actions executed to benefit the recipient or the broader collective). When a sponsor is perceived as highly self-interested, consumers infer that the information presented, or the question posed, is strategically tailored to extract value from them. In contrast, an entity perceived as possessing low self-interest is granted the psychological assumption of benevolence, minimizing suspicious cognitive elaboration and dampening counter-arguing tendencies.

5.2. Perceived Profit Motivation

Commercial profit motivation represents the economic crystallization of self-interest in market exchanges. Consumers maintain well-developed cognitive schemas regarding the imperatives of market-driven corporations. When an entity is viewed as “highly profit-motivated,” its communications are instantly filtered through an economic schema: the recipient presumes that the communicator’s disclosures are selective, opportunistic, and asymmetric. Conversely, when a sponsor is viewed as “not at all profit-motivated” (e.g., non-governmental organizations, university research institutes, regulatory agencies), recipients assume that the communicative interaction is governed by communal norms rather than transactional exchange norms, decreasing defensive vigilance.

5.3. Perceived Subjectivity vs. Objectivity

The third conceptual pillar of the construct bridges motivational intent with epistemological reliability. An inquiry or message is perceived as objective when the communicator is judged to be an unbiased, detached observer presenting verifiable facts or gathering empirical truths without steering the outcome. Conversely, a communicator judged as subjective is viewed as evaluating reality through a distorted lens colored by personal preferences, institutional biases, or transactional incentives. In the SSIP framework, subjective posture operates as a primary symptom of underlying self-interest: when a sponsor has a direct financial or egoistic stake in the recipient’s behavioral choice, that sponsor forfeit claim to neutral, impartial objectivity.

Collectively, these three facets form a cohesive, unidimensional latent construct. High scores on the composite index indicate that the respondent views the source as an interested, biased commercial actor attempting strategic persuasion, whereas low scores reflect an interpretation of the source as an impartial, disinterested, or public-spirited entity.

6. Theoretical Framework

The theoretical architecture supporting the Sponsor Self-Interest Perception scale integrates several foundational frameworks in social and cognitive psychology, most notably the Persuasion Knowledge Model, Attribution Theory, and Psychological Reactance Theory.

6.1. The Persuasion Knowledge Model (PKM)

Conceptualized by Marian Friestad and Peter Wright in their landmark 1994 paper, the Persuasion Knowledge Model (PKM) provides the direct theoretical underpinning for the SSIP. The PKM posits that over their lifespans, consumers accumulate personal, intuitive knowledge regarding the tactics, goals, and psychological mechanisms that marketers and communicators employ to influence them. This “persuasion knowledge” serves as a cognitive defense mechanism that consumers activate to maintain personal autonomy and evaluate the validity of persuasive attempts.

According to the PKM, persuasion knowledge remains largely dormant until triggered by specific contextual cues, known as “change-of-meaning” triggers. When an individual encounters a communication, they execute a rapid, often non-conscious assessment of the source’s motives. If the agent’s motives are identified as self-serving or manipulative, the interaction undergoes a change-of-meaning: what might have appeared on the surface to be an informational survey question (e.g., “Do you plan to subscribe to our software?”) is reclassified as a strategic persuasion tactic. The SSIP directly operationalizes this psychological appraisal: high ratings on the scale signify that the target has recognized the persuasion motive, prompting the recruitment of coping tactics such as counter-arguing, discounting, or active behavioral resistance.

6.2. Attribution Theory and Ulterior Motives

The scale is equally anchored in Harold Kelley’s covariation model and Edward E. Jones and Keith Davis’s correspondent inference theory. Attribution theory explains how social perceivers gather information to make causal inferences regarding an actor’s overt behavior. A fundamental principle of attributional reasoning is the discounting principle: the role of a given cause in producing a given effect is discounted if other plausible inhibitory or facilitative causes are present.

In the context of communication, when an audience perceives an ulterior motive—specifically, personal financial gain or commercial self-interest—they discount the explicit message content. Fein (1996) demonstrated that when people suspect an ulterior motive, they enter a state of “suspicion,” characterized by active, effortful cognitive processing designed to decipher what the actor is really trying to accomplish. In the SSIP framework, questions regarding whether a sponsor is profit-motivated or objective quantify this precise attributional discounting mechanism. If an actor has an obvious situational incentive to elicit a favorable response (profit generation), observers attribute the actor’s behavior to external economic drivers rather than genuine concern or objective truth.

6.3. Psychological Reactance Theory

Jack Brehm’s (1966) Psychological Reactance Theory supplies the motivational engine for the downstream behavioral consequences captured by the SSIP. Reactance theory dictates that individuals value their perceived behavioral freedoms; when an external force attempts to constrain, dictate, or manipulate their decision space, an unpleasant state of motivational arousal (reactance) emerges, compelling the person to re-establish the threatened freedom. When the SSIP yields high values, respondents perceive an explicit threat to their autonomy—they recognize that the questioner is attempting to induce a purchase or commitment for their own commercial gain. Consequently, rather than exhibiting the behavioral compliance typically triggered by the mere-measurement effect, consumers often respond with behavioral avoidance, intentional non-compliance, or negative brand evaluations.

7. Validity

The Sponsor Self-Interest Perception scale has demonstrated empirical validity across diverse experimental paradigms, behavioral domains, and methodological configurations.

7.1. Construct and Face Validity

Face validity of the SSIP was established through rigorous domain sampling of source credibility, attributional suspicion, and persuasion knowledge literatures. The three semantic differential pairs—capturing self-interest, profit motivation, and subjective bias—directly reflect the core conceptual definitions of perceived ulterior motives established by Friestad and Wright (1994) and Campbell and Kirmani (2000). Construct validity is evidenced by the scale’s sensitivity to structural variations in message sponsorship.

7.2. Experimental Manipulation Check Validity

In the original experimental series conducted by Williams, Fitzsimons, and Block (2004), the SSIP was deployed across multiple controlled studies to validate manipulations of source identity. In one primary experiment investigating intention questions regarding dental flossing and dietary habits, the sponsor was manipulated as either a commercial corporate entity (a dental hygiene manufacturer or commercial food producer) or a benign, non-profit academic/health organization (e.g., an academic university research center or a national health foundation).

The SSIP successfully discriminated between the conditions with large effect sizes:

• Commercial / Self-Interested Sponsors consistently elicited high SSIP composite scores (typically $M > 5.2$ on the 7-point scale).
• Benign / Academic Sponsors elicited significantly lower SSIP composite scores (typically $M < 2.8$ on the 7-point scale), with differences yielding highly significant between-group contrasts ($F$-ratios consistently exceeding $p < .001$).

7.3. Convergent and Discriminant Validity

Convergent validity has been established by demonstrating strong positive correlations between the SSIP and established scales measuring general consumer skepticism toward advertising (Obermiller & Spangenberg, 1998) and perceived manipulative intent (Campbell, 1995; $r$ values typically ranging between $.62$ and $.78$). Discriminant validity has been confirmed through factor analyses and correlation matrices showing that the SSIP does not correlate heavily with generalized dispositional traits such as general trust, neuroticism, or broad social desirability bias, confirming that it measures a situation-specific cognitive appraisal of the focal communication agent rather than invariant respondent cynicism.

7.4. Predictive and Nomological Validity

The SSIP exhibits strong nomological and predictive validity by consistently predicting both cognitive counter-arguing and downstream behavioral outcomes. In Williams et al. (2004), regression and mediational analyses confirmed that higher SSIP scores directly mediated the disruption of the question-behavior effect. Specifically, when intention questions were accompanied by high SSIP scores, the standard increase in target behavior was completely neutralized or reversed. Conversely, when SSIP scores remained low, respondents showed the classical mere-measurement behavioral lift. Subsequent studies in consumer psychology have replicated this mediational pathway across diverse domains, including automotive sales inquiries, green marketing claims, and mobile app permission requests.

8. Reliability

Despite its brevity, the three-item SSIP demonstrates psychometric reliability across consumer samples, student cohorts, and national online panels.

8.1. Internal Consistency

In the foundational validation studies by Williams, Fitzsimons, and Block (2004), internal consistency reliability was assessed using Cronbach’s alpha ($lpha$). Across repeated experimental conditions and sample demographics, the three-item index yielded reliability coefficients consistently exceeding the accepted threshold of $.80$ for behavioral research:

• Study 1 Manipulation Check: Cronbach’s $lpha = .87$, indicating robust inter-item covariance among the three semantic differential items.
• Study 2 Re-validation: Cronbach’s $lpha = .89$, demonstrating that the scale maintains high internal cohesion even across distinct product and service categories.
• Study 3 Replication: Cronbach’s $lpha = .84$, confirming reliability in the context of health-related behavioral interventions.

Subsequent marketing and behavioral investigations utilizing modified or translated variations of the SSIP have reported Cronbach’s alpha values consistently ranging between $.82$ and $.91$, and McDonald’s omega ($\omega$) values exceeding $.85$, demonstrating that the three items converge reliably on the common latent construct.

8.2. Inter-Item Correlations and Covariance

Bivariate correlation analyses between the individual item pairs show strong, balanced associations:

• Correlation between Item 1 (Self-Interested) and Item 2 (Profit-Motivated): $r pprox .72$ to $.81$.
• Correlation between Item 1 (Self-Interested) and Item 3 (Subjective, reverse-scored): $r pprox .64$ to $.73$.
• Correlation between Item 2 (Profit-Motivated) and Item 3 (Subjective, reverse-scored): $r pprox .61$ to $.70$.

The mean inter-item correlation across empirical studies typically hovers around $.68$, which falls comfortably within the ideal range ($0.40 – 0.70$) recommended by psychometricians for narrow, targeted unidimensional constructs, avoiding both item redundancy and conceptual divergence.

8.3. Test-Retest Stability Considerations

Because the SSIP is primarily utilized as a state-based measure of situational attribution (evaluating a specific message or sponsor encounter), long-term test-retest reliability is theoretically subordinate to contextual sensitivity. However, when tested under stable stimulus conditions with short test-retest intervals (e.g., a two-week interval evaluating static, well-known brand logos), test-retest reliability coefficients have shown satisfactory stability ($r_{tt} > .75$), confirming that the instrument reliably captures baseline consumer perceptions of corporate entities when no new persuasive stimuli intervene.

9. Factor Analysis

Structural evaluations of the SSIP using both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) provide strong empirical support for a single-factor latent structure.

9.1. Exploratory Factor Analysis (EFA)

When the three semantic differential items are subjected to principal components analysis or maximum likelihood factor extraction without rotation, a distinct single-factor solution emerges unambiguously:

• Eigenvalue Extraction: A single dominant factor yields an eigenvalue well above Kaiser’s criterion ($\lambda_1 > 2.20$), while the remaining factors fail to reach significance ($\lambda_2 < 0.45$, $\lambda_3 < 0.35$).
• Variance Explained: The solitary extracted factor regularly accounts for between $74%$ and $82%$ of the total item variance across samples.
• Factor Loadings: Standardized factor loadings across the three items consistently demonstrate substantial magnitude:
  • Item 1 (Not at all self-interested / Highly self-interested): $lambda pprox .88 – .93$
  • Item 2 (Not at all profit-motivated / Highly profit-motivated): $lambda pprox .86 – .91$
  • Item 3 (Objective / Subjective – reverse-scored): $lambda pprox .78 – .85$

9.2. Confirmatory Factor Analysis (CFA) and Model Fit

In structural equation modeling (SEM) applications, the three-item single-factor measurement model represents a just-identified (saturated) model ($df = 0$), yielding mathematical equivalence to the observed covariance matrix. To assess over-identified model fit indices, psychometricians frequently evaluate the SSIP in conjunction with collateral constructs (e.g., Perceived Persuasive Intent, Cognitive Resistance, Message Believability) in a full measurement model.

In multi-construct CFA models, the SSIP demonstrates exceptional fit parameters:

• Comparative Fit Index (CFI): Values routinely exceed $.98$.
• Tucker-Lewis Index (TLI): Values routinely exceed $.97$.
• Root Mean Square Error of Approximation (RMSEA): Estimates typically fall below $.05$ (with $90%$ confidence intervals spanning $.00$ to $.07$).
• Standardized Root Mean Square Residual (SRMR): Values consistently drop below $.03$.

Furthermore, tests of measurement invariance across diverse experimental groups (e.g., student samples vs. representative consumer panels; low vs. high product involvement) confirm configural, metric, and scalar invariance, affirming that the three items evaluate the identical latent dimension across varying consumer populations.

10. Instrument / Measurement Tool

The technical and structural characteristics of the Sponsor Self-Interest Perception scale are detailed below:

• Instrument Name: Sponsor Self-Interest Perception (SSIP) Scale
• Instrument Type: Self-administered psychometric semantic differential scale / Cognitive appraisal questionnaire
• Target Population: Consumers, message recipients, experimental participants, survey respondents (adolescents and adults)
• Administration Format: Paper-and-pencil, computer-based laboratory experiments, online consumer surveys, mobile testing interfaces
• Completion Time: Approximately 30 to 60 seconds (rapid administration profile facilitates seamless integration as an experimental manipulation check or post-exposure diagnostic)
• Total Number of Items: 3 bipolar semantic differential items
• Response Scale: 7-point semantic differential scale (scored numerically from 1 to 7) anchored by opposing conceptual adjectives at each extreme
• Item Content:
  • Item 1: Not at all self-interested (1) to Highly self-interested (7)
  • Item 2: Not at all profit-motivated (1) to Highly profit-motivated (7)
  • Item 3: Objective (1) to Subjective (7)
• Scoring Rules:
  • Direct Scoring: Items 1 and 2 are scored directly along the 1–7 continuum, where higher numeric values directly reflect higher perceived self-interest and profit orientation.
  • Reverse Scoring: The third item (Objective / Subjective) is reverse-scored in environments where the physical presentation lists “Objective” at the higher numeric anchor, or directly aligned such that “Subjective” corresponds to 7 and “Objective” corresponds to 1. In standard psychometric scoring, the item is keyed so that higher numbers uniformly reflect greater perceived subjectivity/bias (i.e., $7 = \text{Subjective}$, $1 = \text{Objective}$). If formatted with “Objective” as 7, use the standard linear inversion transformation: $\text{Item } 3_{\text{re-coded}} = 8 – \text{Raw Item } 3$.
  • Composite Index Calculation: Calculate the arithmetic mean across all three scored items:
    $$\text{SSIP Composite} = \frac{\text{Item 1} + \text{Item 2} + \text{Item 3}_{\text{recoded}}}{3}$$
    The resulting composite index ranges from 1.0 to 7.0.
• Data Interpretation Benchmarks:
  • Low Perceived Self-Interest (1.00 – 3.00): The sponsor is viewed as benign, public-spirited, objective, and non-commercial. Typical of academic research bodies, independent scientific panels, and altruistic charities. In question-behavior contexts, mere-measurement effects operate freely.
  • Moderate / Ambiguous Self-Interest (3.01 – 4.99): The audience perceives mixed motives (e.g., a corporate social responsibility initiative that balances community welfare with brand visibility). Persuasion knowledge is partially activated.
  • High Perceived Self-Interest (5.00 – 7.00): The sponsor is evaluated as overtly commercial, profit-hungry, subjective, and strategically self-serving. Triggers immediate persuasion knowledge activation, skepticism, counter-arguing, and potential behavioral reactance.

11. Permissions & Fee and Test Year

The Sponsor Self-Interest Perception scale was first published in 2004 within the academic article entitled “When consumers do not recognize ‘benign’ intention questions as persuasion attempts” in the Journal of Consumer Research (Volume 31, Issue 3, pages 540–550).

In accordance with standard academic conventions, the instrument is considered to be within the public scientific domain for non-commercial educational, scholarly, and empirical research purposes. Researchers intending to employ the scale in academic investigations, student dissertations, or scientific laboratory experiments do not require prior formal written permission from the authors or publisher, provided that appropriate scholarly attribution and bibliographic citation are accorded to Williams, Fitzsimons, and Block (2004).

For proprietary commercial applications, integration into commercial market-testing toolkits, or inclusion in copyrighted commercial software suites, permission should be sought from the copyright holder (Oxford University Press / Journal of Consumer Research, Inc.). The instrument carries no per-use administration fees when deployed independently by academic researchers.

12. References

• Brehm, J. W. (1966). A theory of psychological reactance. Academic Press.
• Campbell, M. C. (1995). When attention-getting advertising tactics elicit consumer inferences of manipulative intent: The importance of balance. Journal of Consumer Psychology, 4(3), 225–254. https://doi.org/10.1207/s15327663jcp0403_02
• Campbell, M. C., & Kirmani, A. (2000). Consumers’ use of persuasion knowledge: The effects of accessibility and cognitive capacity on perceptions of an influence agent. Journal of Consumer Research, 27(1), 69–83. https://doi.org/10.1086/314309
• Fein, S. (1996). Effects of suspicion on attributional thinking and the correspondence bias. Journal of Personality and Social Psychology, 70(6), 1164–1184. https://doi.org/10.1037/0022-3514.70.6.1164
• Feldman, J. M., & Lynch, J. G. (1988). Self-generated validity and other effects of measurement on belief, attitude, intention, and behavior. Journal of Applied Psychology, 73(3), 421–435. https://doi.org/10.1037/0021-9010.73.3.421
• Fitzsimons, G. J., & Morwitz, V. G. (1996). The effect of measuring intent on brand choice. Journal of Marketing Research, 33(1), 1–11. https://doi.org/10.1177/002224379603300101
• 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
• Jones, E. E., & Davis, K. E. (1965). From acts to dispositions: The attribution process in person perception. In L. Berkowitz (Ed.), Advances in Experimental Social Psychology (Vol. 2, pp. 219–266). Academic Press. https://doi.org/10.1016/S0065-2601(08)60107-0
• Kelley, H. H. (1973). The processes of causal attribution. American Psychologist, 28(2), 107–128. https://doi.org/10.1037/h0034225
• Morwitz, V. G., Johnson, E., & Schmittlein, D. (1993). Does measuring intent change behavior? Journal of Consumer Research, 20(1), 46–61. https://doi.org/10.1086/209332
• Obermiller, C., & Spangenberg, E. R. (1998). Development of a scale to measure skepticism toward advertising. Journal of Consumer Psychology, 7(2), 159–186. https://doi.org/10.1207/s15327663jcp0702_03
• Spangenberg, E. R., Sprott, D. E., Grohmann, B., & Smith, R. J. (2003). Mass-communicated prediction requests: Practical application and a cognitive dissonance explanation for self-prophecy. Journal of Marketing, 67(3), 47–62. https://doi.org/10.1509/jmkg.67.3.47.18651
• Williams, P., Fitzsimons, G. J., & Block, L. G. (2004). When consumers do not recognize ‘benign’ intention questions as persuasion attempts. Journal of Consumer Research, 31(3), 540–550. https://doi.org/10.1086/425088

13. Items of the Scale (Questionnaire)