Ad Divergence Scale (ADS)

1. Abstract

The Ad Divergence Scale (ADS) is a psychometric measurement instrument developed to evaluate consumer perceptions of divergence within advertising stimuli. Conceptualized comprehensively by Smith, MacKenzie, Yang, Buchholz, and Darley (2007), divergence represents one of the two foundational pillars of advertising creativity, functioning in tandem with ad relevance. Divergence captures the extent to which an advertisement departs from normative consumer expectations, category clichés, and standard marketing executions by presenting stimuli that are novel, unexpected, and distinct. Rather than treating divergence as a monolithic, undifferentiated construct, psychometric operationalizations establish it as a multidimensional construct encompassing five distinct facets: Originality, Flexibility, Elaboration, Synthesis, and Artistic Value, while also permitting global unidimensional assessments of perceived novelty and unconventionality.

The scale typically utilizes a 7-point Likert-type or semantic differential response format, ranging from 1 (“Strongly Disagree” or “Not at all”) to 7 (“Strongly Agree” or “Extremely”). Across empirical validations in structural equation modeling (SEM) and experimental consumer research, the instrument demonstrates robust psychometric properties. Internal consistency reliability estimates consistently yield Cronbach’s alpha values exceeding α = .85 for general divergence and between α = .80 and α = .92 for individual sub-dimensions. Confirmatory factor analyses confirm superior model fit for second-order hierarchical models and correlated multi-factor structures over single-factor alternatives, exhibiting rigorous convergent and discriminant validity against constructs such as brand familiarity, ad relevance, and attitude toward the ad. The ADS remains a standard metric in consumer psychology, cross-cultural marketing, and rhetorical communications research.

2. Keywords

Ad Divergence Scale, advertising creativity, divergence, originality, flexibility, elaboration, synthesis, artistic value, consumer psychology, psychometrics, marketing communications, schema incongruity.

3. Authors

The theoretical conceptualization, structural modeling, and empirical validation of the Ad Divergence Scale were established by a collaborative team of marketing and behavioral research scholars:

• Robert E. Smith — Emeritus Professor of Marketing, Kelley School of Business, Indiana University Bloomington, USA. Specialist in consumer behavioral response, marketing strategy, and advertising creativity models.
• Scott B. MacKenzie — Professor Emeritus of Marketing, Kelley School of Business, Indiana University Bloomington, USA. Renowned authority on research methodology, measurement validation, and structural equation modeling in consumer research.
• Xiaojing Yang — Professor of Marketing, Sheldon B. Lubar College of Business, University of Wisconsin-Milwaukee, USA. Scholar focusing on advertising effectiveness, consumer creativity, and cross-cultural message perception.
• Laura M. Buchholz — Executive and researcher in consumer insights and marketing strategy, formerly affiliated with Indiana University.
• William K. Darley — Professor of Marketing, College of Business, University of Toledo, USA. Specialist in consumer processing, advertising effects, and cross-national marketing behavior.

4. Purpose

The primary purpose of the Ad Divergence Scale is to provide researchers and marketing analysts with an empirically rigorous, standardized tool to quantify the degree to which an advertisement deviates from standard promotional norms and evokes perceptions of novelty, creative ingenuity, and unexpectedness. In commercial environments saturated with standard, formulaic marketing messages, consumers rapidly develop entrenched cognitive scripts regarding what a promotional execution should look like. Divergence functions as a cognitive disruptor, capturing attention, interrupting automatic message filtration, and stimulating heightened levels of central message processing as postulated in dual-process theories of persuasion.

Prior to the establishment of formalized divergence scales, creativity in advertising was frequently operationalized through idiosyncratic, subjective expert evaluations (such as industry award shows) or crude single-item measures that lacked theoretical grounding. Such approaches conflated distinct cognitive and aesthetic properties of advertisements. The ADS fulfills an essential psychometric need by disaggregating divergence into concrete, measurable components grounded in classic psychological theories of divergent thinking. Researchers deploy the scale to evaluate how divergent creative executions influence intermediate cognitive processing (e.g., focal attention, curiosity, cognitive elaboration) and downstream persuasive outcomes, including brand recall, brand attitudes, and behavioral purchase intentions.

Beyond academic laboratory experiments, the scale serves critical practical functions in commercial advertising pre-testing (copy testing) and message development. Applied consumer researchers utilize the ADS to assess whether prospective promotional campaigns successfully overcome category wear-out and cognitive banner blindness. Furthermore, cross-cultural marketing scholars employ the instrument to determine how cultural dimensions—such as individualism versus collectivism or high versus low context communication—moderate consumer tolerance and appreciation for divergent advertising executions. In educational and organizational settings, the tool enables media analysts to diagnostically break down why specific campaigns capture public imagination while others fail to elicit engagement.

5. Psychological Construct

In contemporary consumer psychology, advertising creativity is defined not merely as wild unconventionality, but as an interaction between two distinct meta-dimensions: divergence and relevance. The Ad Divergence Scale is dedicated to the systematic assessment of divergence. Divergence represents the degree to which an advertisement contains execution elements that are novel, unusual, different, and unexpected. In Smith et al.’s (2007) model, divergence is operationalized as a multidimensional construct comprising five underlying psychological dimensions adapted from early cognitive work on creative thinking:

Originality

Originality assesses the degree to which an advertising execution is perceived as unique, uncommon, rare, and surprising. An original ad avoids generic tropes, clichéd stock imagery, and predictable slogans. For example, rather than showing an automobile driving smoothly along a picturesque mountain highway, an original execution might illustrate the car navigating through a surreal landscape composed entirely of clockwork gears to emphasize mechanical precision. Originality acts as the core trigger of sensory surprise, prompting consumers to register the stimulus as distinct from competing category exemplars.

Flexibility

Flexibility captures the ad’s capacity to shift perspectives, switch across conceptual categories, or connect diverse mental domains. It reflects cognitive nimbleness, presenting ideas from multiple, non-standard vantage points. An ad demonstrating high flexibility might shift seamlessly from the micro-perspective of an ant navigating a kitchen counter to a macro-perspective of home cleaning, or use unexpected metaphors that bridge disparate industries. In cognitive testing, flexibility reflects an ad’s avoidance of rigid, linear thinking.

Elaboration

Elaboration measures the degree of unexpected intricacy, embellishment, and conceptual detail embedded in the ad. Rather than presenting a simple visual or textual claim, an elaborated divergent ad contains intricate visual cues, double-entendre wordplay, or rich contextual depth that invites the viewer to look closer and uncover deeper layers of meaning. An example includes print executions featuring high-density optical illusions or complex background narratives that reward prolonged gaze and deeper cognitive scrutiny.

Synthesis

Synthesis evaluates the creative combination, blending, or fusion of normally unrelated concepts, objects, or ideas into a cohesive whole. Grounded in associative theories of creative insight, synthesis occurs when an advertisement unites two mutually distant semantic networks. For instance, combining an alarm clock with a cup of hot coffee to communicate immediate morning wakefulness represents a conceptual synthesis. The psychological impact of synthesis stems from the cognitive resolution of incongruity, producing an “aha!” moment when the viewer understands the symbolic alignment.

Artistic Value

Artistic value reflects the aesthetic craftsmanship, verbal sophistication, and visual elegance of the execution. Divergence can manifest not only through intellectual novelty, but also through artistic excellence that transcends standard commercial production values. Ads scoring high on artistic value feature exquisite cinematography, sophisticated typographic layouts, emotive musical scores, or poetic copywriting. This facet taps into consumers’ aesthetic appreciation, inducing positive emotional resonance and elevated brand perceptions independent of utilitarian arguments.

6. Theoretical Framework

The Ad Divergence Scale is rooted in an intersection of psychometric creativity models, cognitive schema theory, and dual-process models of persuasion. The primary foundational framework originates from early cognitive psychometrics, particularly J. P. Guilford’s (1950, 1967) structure-of-intellect model and Ellis Paul Torrance’s (1966, 1974) Torrance Tests of Creative Thinking (TTCT). Guilford and Torrance established that divergent thinking is not an unstructured burst of eccentricity, but a structured cognitive faculty measurable through distinct parameters: fluency, originality, flexibility, and elaboration. Smith et al. (2007) systematically translated these divergent cognitive operations from individual creative capacity into an evaluative receiver-response framework tailored to media stimuli.

A second major theoretical pillar is Schema Incongruity Theory (Mandler, 1982). Consumers maintain established cognitive schemas regarding product categories and promotional genres. When an advertisement conforms entirely to an existing schema, it is processed effortlessly through top-down assimilation, resulting in low focal attention, minimal cognitive elaboration, and swift forgetting. Conversely, when an advertisement exhibits divergence, it introduces moderate-to-high schema incongruity. According to Mandler’s framework, incongruent stimuli disrupt routine automatic processing, prompting cognitive arousal and activating bottom-up interpretive mechanisms to reconcile the unexpected discrepancy. If the divergence is resolved meaningfully (frequently facilitated by ad relevance), it generates cognitive pleasure, higher recall, and favorable message processing.

Furthermore, the ADS interfaces directly with the Elaboration Likelihood Model (ELM) (Petty & Cacioppo, 1986) and the Heuristic-Systematic Model (Chaiken, 1980). In low-involvement consumer scenarios where audiences typically lack the intrinsic motivation to process promotional claims, divergent advertising acts as an extrinsic engagement trigger. High divergence elevates situational motivation to process the ad, shifting consumers from superficial peripheral processing toward more substantive central processing. By bridging cognitive creativity metrics with structural models of consumer response, the ADS provides a unified conceptual framework for modeling the cognitive pathways through which advertising creativity yields market effectiveness.

7. Validity

The psychometric validity of the Ad Divergence Scale has been subjected to extensive empirical examination across diverse experimental studies, field surveys, and structural equation models:

Construct and Factorial Validity

Smith et al. (2007) demonstrated construct validity using multi-sample structural equation modeling across hundreds of broadcast television advertisements. Confirmatory factor analysis confirmed that a five-factor correlated model (or a second-order model where a higher-order divergence construct accounts for the five first-order dimensions) exhibits superior fit indices over rival single-factor models. Standardized factor loadings across items consistently range from .72 to .94, demonstrating substantial construct representation without excessive measurement error.

Convergent Validity

Convergent validity has been established by demonstrating that multiple items within each divergence dimension load strongly onto their designated latent constructs. Average Variance Extracted (AVE) values reported across the five subscales regularly exceed the standard .50 threshold established by Fornell and Larcker (1981), with values typically spanning from .58 to .78. Furthermore, overall perceived divergence correlates positively with objective, independent expert panels evaluating creative originality and creative design awards (such as Cannes Lions or Clio Awards), confirming alignment between naive consumer ratings and professional benchmarks.

Discriminant Validity

Discriminant validity is a vital consideration in advertising creativity research, particularly distinguishing divergence from ad relevance (the meaningfulness, utility, and brand-connectedness of the message). Research demonstrates that the square root of the AVE for divergence and its subscales consistently exceeds the inter-construct correlation between divergence and relevance (which typically correlates moderately between r = .25 and r = .45). Moreover, nested model chi-square difference tests confirm that constraining the correlation between divergence and relevance to unity (φ = 1.0) produces a severe, statistically significant decrement in model fit (Δχ² > 150.0, p < .001), establishing that divergence and relevance are empirically distinct constructs.

Predictive and Nomological Validity

Nomological validity is demonstrated through structural modeling showing that divergence systematically predicts hypothesized psychological and behavioral outcomes. Smith et al. (2007) and subsequent investigations (e.g., Yang & Smith, 2009; Rosengren, Dahlén, & Modig, 2013) demonstrated that divergence has statistically significant positive paths to cognitive elaboration (β = .34 to .52, p < .001), focal attention (β = .40 to .61, p < .001), and positive affective response. Crucially, studies testing the interaction between divergence and relevance demonstrate that divergence amplifies the positive effect of ad relevance on brand attitude and purchase intent, confirming its foundational role within consumer persuasion models.

8. Reliability

The reliability of the Ad Divergence Scale has been corroborated across numerous empirical investigations employing diverse consumer cohorts, cultural settings, and media channels (e.g., television commercials, print layouts, digital social video ads). Both internal consistency and composite reliability indices consistently surpass recommended psychometric criteria (≥ .70 to .80):

• Overall Divergence (Global Scale): Cronbach’s alpha values typically fall within the α = .88 to .94 range, indicating exceptional item homogeneity when measuring global perceptions of novelty and uniqueness.
• Originality Subscale: Internal consistency estimates consistently report α = .86 to .92, with composite reliability (CR) values exceeding .88.
• Flexibility Subscale: Cronbach’s alpha values generally span α = .81 to .87, reflecting stable measurement of perspective shifting.
• Elaboration Subscale: Reported internal consistency statistics range from α = .80 to .89 across varied media formats.
• Synthesis Subscale: Cronbach’s alpha coefficients demonstrate robust values between α = .83 and .90.
• Artistic Value Subscale: Psychometric evaluations report reliability coefficients between α = .84 and .91, indicating strong consistency across aesthetic judgment indicators.

Test-retest reliability assessments conducted across two-to-four-week intervals in laboratory settings demonstrate stability coefficients ranging from r = .78 to r = .86, indicating that consumer evaluations of divergence remain stable across time in the absence of exogenous campaign wear-out or repetitive overexposure.

9. Factor Analysis

Extensive exploratory (EFA) and confirmatory factor analyses (CFA) have confirmed the dimensionality of the Ad Divergence construct:

Exploratory Factor Analysis (EFA)

Initial exploratory factor analyses utilizing principal axis factoring with promax and oblimin oblique rotations consistently reveal a clear five-factor structure corresponding to the theoretical dimensions postulated by Smith et al. (2007). In initial calibration samples, the five eigenvalues exceed the Kaiser criterion (λ > 1.0), collectively accounting for over 65% to 74% of the total shared variance. Scree plot analyses demonstrate a definitive break after the fifth factor. Cross-loadings across alternative factors are low, rarely exceeding .25, indicating clear factorial separation among the creative facets.

Confirmatory Factor Analysis (CFA)

In structural confirmatory factor models evaluated across thousands of consumer respondents, the hypothesized multidimensional model exhibits good-to-excellent goodness-of-fit indices:

• Comparative Fit Index (CFI): .94 to .98, well above the conventional .90/.95 thresholds.
• Tucker-Lewis Index (TLI): .93 to .97.
• Root Mean Square Error of Approximation (RMSEA): .042 to .062 (with 90% confidence intervals spanning .035 to .069), indicating close model fit.
• Standardized Root Mean Residual (SRMR): .038 to .051.

When evaluated as a hierarchical second-order factor model—wherein the higher-order latent construct of “Ad Divergence” directly predicts the five first-order factors of Originality, Flexibility, Elaboration, Synthesis, and Artistic Value—the target coefficient (ratio of first-order model chi-square to second-order chi-square) frequently exceeds .90. This indicates that the five distinct dimensions are structurally organized under the overarching macro-construct of creative divergence.

10. Instrument / Measurement Tool

The operational administration of the Ad Divergence Scale follows established psychometric protocols:

• Instrument Designation: Ad Divergence Scale (ADS); occasionally categorized under the comprehensive Divergence and Relevance Advertising Creativity Scale (DRACS).
• Measurement Format: Standardized self-report survey administered immediately post-exposure to the target advertisement stimulus.
• Item Structure:
  • Full Multidimensional Inventory: 15 to 20 items (typically 3 to 4 items per sub-dimension).
  • Global / Short-Form Divergence Scale: 3 to 5 items evaluating general novelty, distinctiveness, and departure from routine advertising norms.
• Response Scale: 7-point Likert-type agreement scales (1 = “Strongly Disagree” to 7 = “Strongly Agree”) or 7-point semantic differential scales (e.g., 1 = “Not at all novel” to 7 = “Extremely novel”).
• Target Stimuli: Suitable for television/video commercials, print advertisements, audio/radio spots, outdoor billboards, and interactive digital/social media campaigns.
• Scoring Protocols:
  • Subscale Scores: Computed by averaging the item scores corresponding to each specific dimension (Originality, Flexibility, Elaboration, Synthesis, Artistic Value).
  • Composite Divergence Score: Computed either as an unweighted grand mean of all subscale scores or via latent variable factor weights derived through structural equation modeling.
  • Polarity: Positively keyed; higher scores indicate greater perceived creative divergence. Negatively worded reverse-coded items (if deployed) are inverted prior to score computation.

11. Permissions & Fee and Test Year

The foundational empirical architecture of the Ad Divergence Scale was published in 2007 in the journal Marketing Science by Robert E. Smith, Scott B. MacKenzie, Xiaojing Yang, Laura M. Buchholz, and William K. Darley.

The scale was developed within an academic research context and is widely accessible for non-commercial scholarly research, educational purposes, and scientific replication under academic fair-use guidelines, provided proper formal bibliographic citation is given to the original authors and the publishing journal. However, the published article and specific verbatim text formulations remain copyrighted by the Institute for Operations Research and the Management Sciences (INFORMS). Commercial market research organizations, syndicated copy-testing agencies, and corporate practitioners seeking to embed the scale within proprietary commercial software platforms or commercial testing suites should obtain appropriate permissions from the copyright holder and journal publishers.

12. References

• Chaiken, S. (1980). Heuristic versus systematic information processing and the use of source versus message cues in persuasion. Journal of Personality and Social Psychology, 39(5), 752–766. https://doi.org/10.1037/0022-3514.39.5.752
• 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
• Guilford, J. P. (1950). Creativity. American Psychologist, 5(9), 444–454. https://doi.org/10.1037/h0063487
• Guilford, J. P. (1967). The Nature of Human Intelligence. McGraw-Hill.
• Mandler, G. (1982). The structure of value: Accounting for taste. In M. S. Clark & S. T. Fiske (Eds.), Affect and Cognition: The 17th Annual Carnegie Symposium on Cognition (pp. 3–36). Lawrence Erlbaum Associates.
• Petty, R. E., & Cacioppo, J. T. (1986). The Elaboration Likelihood Model of persuasion. Advances in Experimental Social Psychology, 19, 123–205. https://doi.org/10.1016/S0065-2601(08)60214-2
• Rosengren, S., Dahlén, M., & Modig, E. (2013). Think wild! The effects of divergent advertising on brand evaluation. Journal of Advertising, 42(4), 312–324. https://doi.org/10.1080/00913367.2013.795141
• Smith, R. E., & Yang, X. (2004). Toward a general theory of creativity in advertising: Examining the role of divergence. Marketing Theory, 4(1–2), 31–58. https://doi.org/10.1177/1470593104044086
• Smith, R. E., MacKenzie, S. B., Yang, X., Buchholz, L. M., & Darley, W. K. (2007). Modeling the determinants and effects of creativity in advertising. Marketing Science, 26(6), 819–833. https://doi.org/10.1287/mksc.1070.0272
• Torrance, E. P. (1966). Torrance Tests of Creative Thinking: Norms-technical manual. Personnel Press.
• Torrance, E. P. (1974). Torrance Tests of Creative Thinking: Streamlined scoring guide for figural form A and B. Scholastic Testing Service.
• Yang, X., & Smith, R. E. (2009). Beyond attention: Effects of divergence on consumer cognitive processing and responses to advertising. Journal of Marketing Research, 46(6), 708–721. https://doi.org/10.1509/jmkr.46.6.708

13. Items of the Scale