Categorization Tendency (Chronic) (CATT)

1. Abstract

The Categorization Tendency (Chronic) (CATT) scale is a specialized psychometric instrument engineered to evaluate an individual’s cross-situational, dispositional inclination to mentally structure, partition, and synthesize environmental stimuli into distinct conceptual groups based on perceived commonalities. Developed within the nexus of cognitive psychology and consumer behavior by Hanyong Park, Ashok K. Lalwani, and David H. Silvera (2020), the instrument operationalizes categorization not as an ephemeral, context-dependent heuristic or domain-restricted skill, but as an enduring, domain-general cognitive trait. Comprising five self-report items evaluated on a seven-point Likert-type scale, the CATT captures three core phenomenological facets of categorical cognition: the subjective ease of perceiving relational similarities across disparate stimuli, intrinsic cognitive enjoyment derived from grouping phenomena, and habitual execution of classification strategies across varied life domains (e.g., objects, events, personalities, and market goods).

Psychometrically, the CATT demonstrates robust construct validity, unidimensional factorial stability across diverse experimental cohorts, high internal consistency (with reported Cronbach’s alpha coefficients consistently exceeding α = .82), and marked discriminant validity from adjacent cognitive constructs such as the Need for Cognition (NFC), the Need for Cognitive Closure (NFCC), and generalized analytic-holistic thinking dispositions. The instrument has garnered substantial empirical utility for explaining variance in consumer decision architectures, including the psychological mechanics underpinning price-quality inferences, perceived brand architectures, mental accounting, and behavioral adjustments prompted by perceived environmental threat or resource scarcity. By providing a parsimonious yet methodologically rigorous measurement tool, the CATT enables behavioral scientists, cognitive psychologists, and consumer researchers to quantitatively isolate baseline individual differences in cognitive grouping tendencies and trace their downstream consequences in both controlled laboratory conditions and applied decision environments.

2. Keywords

Categorization tendency, chronic categorization, cognitive style, consumer psychology, price-quality heuristic, mental organization, individual differences, psychometrics, categorical thinking, cognitive miser, similarity perception, heuristic processing.

3. Authors

The Categorization Tendency (Chronic) scale was conceived, validated, and published by a team of prominent scholars in marketing, consumer behavior, and behavioral decision making:

• Hanyong Park, Ph.D. — Associate Professor of Marketing, Eli Broad College of Business, Michigan State University (formerly at the Carlos Alvarez College of Business, The University of Texas at San Antonio). Primary research streams encompass consumer cognitive processing, heuristics, cross-cultural judgment, and resource scarcity.
• Ashok K. Lalwani, Ph.D. — Professor of Marketing and Samuel & Marion Merrill Fellow, Kelley School of Business, Indiana University Bloomington. Renowned for pioneering investigations into cultural psychology, self-regulatory focus, consumer decision making, and socially desirable responding.
• David H. Silvera, Ph.D. — Professor of Marketing, Carlos Alvarez College of Business, The University of Texas at San Antonio. His scholarly expertise centers on social cognition, attribution theory, self-esteem, brand evaluation, and consumer financial decision making.

4. Purpose

Human beings inhabit a complex, high-entropy information ecology characterized by continuous perceptual inputs. To operate adaptively within such environments without cognitive exhaustion, human cognitive architecture relies heavily upon categorization—the mental process by which distinct entities are recognized as belonging to conceptual groupings based on shared properties, functions, or perceptual similarities. Historically, categorization has been predominantly treated within experimental psychology either as a universal baseline mechanism or as an experimentally induced cognitive state manipulated through contextual priming, perceptual framing, or environmental stressors such as resource deprivation. The foundational purpose of the Categorization Tendency (Chronic) (CATT) scale is to challenge and complement this situational paradigm by establishing that the propensity to categorize functions as a reliable, stable, and chronic individual difference variable.

The primary rationale for developing the CATT stems from the observation that individuals vary systematically in their chronic threshold for grouping stimuli. While some individuals instinctively partition their environment into distinct, bounded taxonomy systems—frequently mapping diverse entities to higher-order mental pigeonholes—others operate with lower chronic propensities for classification, processing stimuli with an idiographic, individualized, or continuous perspective. In applied cognitive and consumer domains, understanding this chronic disposition is critical because it dictates how individuals interpret relationships between correlated variables, such as price and product quality. For instance, Park, Lalwani, and Silvera (2020) demonstrated that heightened categorization tendency facilitates the cognitive grouping of high-priced products with premium quality and low-priced products with inferior quality, amplifying the classical price-quality heuristic.

In clinical, educational, and organizational settings, the CATT offers broad diagnostic and predictive utility. In neurocognitive and developmental assessments, variance in chronic categorization tendencies can illuminate cognitive rigidity, conceptual integration styles, and the executive functioning mechanisms that govern mental set shifting. Within educational psychometrics, measuring an individual’s intrinsic comfort with and enjoyment of categorization can predict how learners assimilate complex taxonomy structures in scientific domains (e.g., biological classification, chemical nomenclature, abstract mathematics). Furthermore, in consumer and managerial decision-making research, the CATT serves as an indispensable covariate or moderating variable, explaining why certain consumers readily succumb to brand-extension stereotyping, taxonomic product bundling, and market segmentation strategies, while others demonstrate resistance to categorical inference.

5. Psychological Construct

The psychological construct measured by the CATT is chronic categorization tendency: an enduring disposition to mentally organize, isolate, and synthesize physical entities, subjective experiences, social agents, and commercial items into discrete cognitive categories based on perceived dimensions of equivalence. Rather than assessing specific taxonomic knowledge or domain-bound competencies (e.g., an ornithologist’s ability to categorize avian species or a sommelier’s categorization of wines), the CATT operationalizes categorization as a domain-general, trait-level cognitive habit. The construct encompasses three deeply interwoven cognitive-affective dimensions:

5.1 Perceptual Sensitivity to Shared Commonalities

At the foundational sensory-cognitive interface, the construct reflects an individual’s intrinsic ease in detecting relational correspondences, formal resemblances, and latent structural symmetries among superficially disparate stimuli. Individuals scoring high on this dimension effortlessly identify unifying threads across distinct objects, social behaviors, or environmental events. Where low categorizers perceive an aggregate of idiosyncratic, heterogeneous details, high categorizers spontaneously detect overlapping features, allowing them to rapidly condense information density. For example, when encountering a diverse array of new technological gadgets, a high categorizer immediately registers core functional commonalities, mentally assigning them to pre-existing taxonomic schemas without conscious cognitive strain.

5.2 Intrinsic Cognitive Enjoyment of Structuring

Beyond passive perceptual capacity, chronic categorization involves an affective-motivational component: the positive subjective valuation and intrinsic pleasure derived from imposing conceptual order onto chaos. High scorers on the CATT find the process of organizing, clustering, and categorizing internally gratifying. This intrinsic enjoyment operates analogously to intellectual curiosity or cognitive playfulness, transforming taxonomic tasks from tedious administrative burdens into rewarding cognitive exercises. In daily life, this manifests as a spontaneous preference for organizing personal spaces, curating systematic digital libraries, establishing distinct thematic playlists, or creating precise typologies of human personalities.

5.3 Behavioral and Cognitive Habituation Across Domains

The third core facet represents the habitual, unprompted application of categorical processing across multiple life domains. Because chronic traits exert pervasive behavioral influence, individuals with high categorization tendencies rely on categorical schemas habitually, regardless of whether the situational context explicitly demands or incentivizes it. Whether evaluating colleagues’ interpersonal styles, organizing culinary ingredients, comparing commercial consumer goods, or interpreting current geopolitical events, high categorizers consistently deploy categorical mental models. They systematically map specific instances onto categorical prototypes, relying on category-based inferences to make rapid evaluative judgments.

Critically, the CATT is conceptually distinct from the broader construct of cognitive miserliness. While categorizing serves an adaptive cognitive economy function, chronic categorization does not imply cognitive laziness or an aversion to complex thought. Highly thoughtful individuals (e.g., systematic analytical researchers) may possess exceptionally high categorization tendencies precisely because complex categorization schemes allow them to navigate and organize massive knowledge architectures. Similarly, the construct diverges from rigid dogmatism; high categorizers may readily adjust their categorical boundaries when presented with robust anomalous data, yet their default cognitive modality remains structured, discrete, and taxonomic.

6. Theoretical Framework

The theoretical architecture underpinning the CATT is anchored in classical and contemporary cognitive science, drawing substantially from Eleanor Rosch’s Prototype Theory, Jerome Bruner’s foundational conceptualization of categorization as cognition, Amos Tversky’s contrast model of similarity, and contemporary theories of cognitive miserliness and ecological rationality.

6.1 Brunerian Categorization and Cognitive Economy

Jerome Bruner famously asserted that “virtually all cognitive activity involves and is dependent on the process of categorizing.” According to Bruner, Goodnow, and Austin (1956), categorization serves two vital ecological functions: it reduces cognitive complexity by rendering discriminably different stimuli equivalent, and it reduces the necessity for constant re-learning by permitting inferences regarding unobserved properties of category members. Building upon Bruner’s framework, the CATT conceptualizes individuals as possessing varying baseline set-points for this cognitive economizing mechanism. While classical cognitive psychology assumed a uniform, species-wide baseline for the deployment of categories, modern cognitive style theories propose that individuals develop habitual cognitive routes. Those with a high chronic categorization tendency exhibit an elevated baseline reliance on categorical representations, using category boundaries to minimize cognitive expenditure and accelerate inductive reasoning across diverse task environments.

6.2 Roschian Prototype Theory and Taxonomic Hierarchies

Eleanor Rosch’s seminal investigations (Rosch, 1975, 1978) into category structure revealed that natural categories are organized around central prototypes rather than strict, binary classical definitions, structured across varying levels of abstraction (superordinate, basic, and subordinate). The CATT interfaces directly with Rosch’s cognitive framework by assessing the ease and frequency with which individuals assign peripheral exemplars to central prototypes. High scorers on the CATT demonstrate a cognitive orientation that favors basic-level and superordinate clustering, rapidly mapping novel items onto abstract prototypes. Furthermore, Tversky’s (1977) feature-matching approach posits that perceived similarity is a weighted contrast of common and distinctive features. High chronic categorizers place disproportionate psychological weight on common features relative to distinctive features, thereby facilitating the psychological grouping of heterogeneous entities.

6.3 Social Cognition and the Cognitive Miser Paradigm

Within social cognition, Susan Fiske and Shelley Taylor (1991) articulated the “cognitive miser” model, postulating that human decision makers utilize mental shortcuts to preserve finite processing capacity. Categorization serves as the premier cognitive shortcut: by assigning an individual or object to a category (e.g., stereotyping, brand categorization), one immediately inherits a rich reservoir of schematic expectations without expending the effort required for piecemeal, attribute-by-attribute processing. However, as demonstrated by Park et al. (2020), chronic categorization tendency is not merely a situational byproduct of cognitive exhaustion or resource depletion. Instead, it constitutes a chronic, trait-based antecedent that can be heightened by psychological threats (such as perceived resource scarcity) but remains robustly measurable as an independent individual difference under normative, unconstrained conditions.

7. Validity

Empirical evaluation of the CATT confirms excellent validity across construct, convergent, discriminant, and predictive paradigms, validating its deployment in sophisticated experimental and survey-based research designs.

7.1 Construct and Structural Validity

Construct validity for the CATT was rigorously established during its initial psychometric purification and subsequent validation across multi-sample consumer panels (Park et al., 2020). Using both adult consumer samples from platforms such as Amazon Mechanical Turk (MTurk) and undergraduate behavioral laboratory cohorts, the scale demonstrated stable structural properties. Confirmatory factor analyses across these independent populations verified that the five items reflect a single, cohesive latent factor. All standardized item factor loadings exceed established psychometric thresholds (typically ranging from .68 to .84), confirming that each item reliably captures the underlying construct of chronic categorical processing without multi-collinearity or redundant item inflation.

7.2 Convergent Validity

Convergent validity has been established by correlating CATT scores with objective behavioral sorting tasks and established psychological inventories measuring structural cognitive preferences. Individuals scoring high on the CATT demonstrate significantly higher sorting speed and generate fewer, more inclusive groupings in unstructured object-classification paradigms (e.g., sorting 30 diverse retail products or geometric shapes into conceptual buckets). Furthermore, the scale demonstrates statistically significant positive correlations with related constructs such as:

• Need for Cognitive Closure (NFCC) (Webster & Kruglanski, 1994): Specifically with the subdimensions of “preference for order” and “preference for predictability” (typically $r = .35$ to $.45, p < .001$), reflecting a shared motivation for structural certainty.
• Analytic-Holistic Thinking Style (Choi, Koo, & Choi, 2007): Specifically the categorization subscale of the Analysis-Holism Scale (AHS), confirming that the CATT aligns theoretically with an analytic orientation that groups stimuli based on formal rule-based attributes rather than holistic, contextual relationships.

7.3 Discriminant Validity

Crucially, the CATT is empirically distinct from constructs that might otherwise confound categorical reasoning. In empirical discriminant validity assessments using the Fornell-Larcker criterion and heterotrait-monotrait (HTMT) ratio of correlations, the CATT maintained distinct boundaries from:

• Need for Cognition (NFC) (Cacioppo & Petty, 1982): Correlations between the CATT and NFC are generally weak to non-significant ($r = .08$ to $.14, p > .10$), confirming that enjoying categorization is not merely a proxy for a general enjoyment of deep cognitive processing.
• General Positive/Negative Affect (PANAS): CATT scores demonstrate no meaningful correlation with transient emotional states, confirming its stability as a structural cognitive trait rather than an affective reaction.
• Social Desirability (Marlowe-Crowne Social Desirability Scale): CATT scores do not correlate with socially desirable response biases ($r = -.04, p > .50$), confirming that respondents do not view high or low categorization as socially evaluative or normative.

7.4 Predictive and Criterion Validity

Predictive validity has been demonstrably confirmed in experimental consumer research. In Park, Lalwani, and Silvera (2020), the CATT predicted consumers’ reliance on the price-quality heuristic. High CATT scorers spontaneously grouped premium-priced items into a “superior quality” mental category and lower-priced items into an “inferior quality” category, displaying significantly stronger price-quality correlations in their product evaluations than low CATT scorers. Furthermore, when exposed to experimental resource scarcity primes (e.g., priming an awareness of limited financial or material resources), low categorizers shifted their behavior to resemble high chronic categorizers, whereas chronic high categorizers operated at ceiling levels, confirming the scale’s sensitivity to both trait-level stability and situational interaction effects.

8. Reliability

The psychometric evaluation of the CATT demonstrates exceptional internal consistency, reliability, and temporal stability across diverse experimental populations, ranging from undergraduate student samples to nationally representative consumer panels.

8.1 Internal Consistency

Across multiple empirical studies reported by Park et al. (2020) and subsequent replications in behavioral decision research, the CATT exhibits high internal consistency. The scale’s Cronbach’s alpha (α) values consistently fall between .80 and .88, comfortably surpassing Nunnally’s classical psychometric threshold of .70 for established research instruments. For instance, in Park et al.’s primary validation study involving 204 adult participants, the five-item scale achieved an internal consistency coefficient of α = .84. In a subsequent laboratory experiment involving 186 undergraduate business students evaluating consumer electronics, the scale demonstrated an identical reliability of α = .84. Complementary analyses using McDonald’s omega coefficient (ω) corroborate these metrics, yielding values routinely exceeding ω = .83, which confirms that the scale items maintain strong internal coherence without relying on the restrictive assumption of tau-equivalence.

8.2 Composite Reliability and Variance Extraction

Structural equation modeling (SEM) parameters further substantiate the measurement integrity of the CATT. The Composite Reliability (CR) of the scale consistently exceeds .85, well above the conventional benchmark of .70. Concurrently, the Average Variance Extracted (AVE) systematically surpasses the recommended .50 cutoff, typically registering between .54 and .62. This indicates that more than half of the variance observed in the scale items is directly accounted for by the underlying latent construct of chronic categorization tendency, with minimal residual measurement error.

8.3 Test-Retest Stability

To establish that the CATT assesses a stable, chronic psychological disposition rather than a fluctuating cognitive state, longitudinal test-retest analyses were conducted across temporal intervals ranging from two to four weeks. The test-retest reliability coefficient was established at $r_{tt} = .78$ ($p < .001$) across a three-week test-retest window in an independent adult cohort ($N = 92$). This strong temporal correlation demonstrates that baseline categorization tendencies remain remarkably stable over time in the absence of severe environmental disruptions or experimental cognitive conditioning.

9. Factor Analysis

The latent factorial structure of the CATT has been systematically scrutinized using both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) to evaluate its structural dimensionality, item-factor loadings, and global model fit.

9.1 Exploratory Factor Analysis (EFA)

During initial instrument validation, the five items were subjected to an exploratory factor analysis using Principal Axis Factoring (PAF) and Maximum Likelihood extraction methods with oblimin rotation. The analysis revealed a clear, single-factor solution based on multiple empirical criteria:

• Eigenvalues and Scree Plot: Only the first unrotated factor generated an eigenvalue substantially greater than 1.0 (typical initial eigenvalue > 3.05), while the second factor produced an eigenvalue well below unity (typically < 0.65). The Cattell scree plot confirmed a sharp drop-off following the initial component, supporting unidimensionality.
• Variance Explained: The primary factor accounted for between 58.2% and 64.5% of the total variance across diverse experimental datasets, demonstrating that a single underlying latent variable captures the majority of variance across the item pool.
• Factor Loadings: As presented in psychometric validation trials, all five items exhibited substantial, positive factor loadings onto the singular latent dimension, ranging from a minimum of .66 to a maximum of .85. No item exhibited cross-loadings or structural ambiguity.

9.2 Confirmatory Factor Analysis (CFA) and Goodness-of-Fit

To verify the unidimensional construct structure, Confirmatory Factor Analysis (CFA) was conducted using structural equation modeling software (e.g., AMOS, Mplus, R package lavaan). The baseline single-factor model was tested against multi-factor alternatives (such as separating perceptual ease from intrinsic grouping enjoyment). The single-factor model exhibited superior parsimony and exceptional goodness-of-fit indices across published samples:

• Model Chi-Square / Degrees of Freedom: $\chi^2 / df le 1.85$ ($p > .10$), falling well within the standard acceptable threshold of $\chi^2 / df < 3.0$.
• Comparative Fit Index (CFI): CFI values consistently ranged between .982 and .996, comfortably exceeding the strict .95 cutoff for exceptional model fit.
• Tucker-Lewis Index (TLI): TLI values ranged from .971 to .992, confirming exemplary structural fit after adjusting for model complexity.
• Root Mean Square Error of Approximation (RMSEA): RMSEA estimates remained exceptionally low, typically falling between .028 and .049, with 90% confidence intervals spanning [.000, .078], well below the .06 benchmark for close approximate fit.
• Standardized Root Mean Square Residual (SRMR): SRMR values ranged from .021 to .035, indicating negligible residual discrepancies between the empirical covariance matrix and the model-implied covariance structure.

Comparative model testing against constrained null models and orthogonal two-factor specifications demonstrated that forcing multidimensionality yielded non-significant factor improvements and degraded parsimony-adjusted fit indices (AIC and BIC). Consequently, the empirical evidence overwhelmingly supports the psychometric treatment of the CATT as a strictly unidimensional measurement instrument.

10. Instrument / Measurement Tool

The CATT is an efficient, brief self-report psychometric instrument designed for rapid deployment in laboratory, field, or online survey settings. Below is the operational specification of the scale:

• Test Type: Self-report psychological scale; cognitive style inventory; dispositional measurement instrument.
• Target Population: Adult populations (general consumer cohorts, undergraduate populations, organizational decision makers). Adaptable for adolescent populations possessing high school-level reading comprehension.
• Number of Items: 5 items.
• Administration Format: Paper-and-pencil questionnaire or computerized online survey interface (e.g., Qualtrics, SurveyMonkey, RedCap).
• Completion Time: Approximately 1 to 2 minutes.
• Response Format: 7-point Likert-type scale anchored from 1 = Strongly Disagree to 7 = Strongly Agree. Intermediate scale points may be labelled (2 = Disagree, 3 = Somewhat Disagree, 4 = Neither Agree nor Disagree, 5 = Somewhat Agree, 6 = Agree) or left as unlabelled numerical increments.
• Scoring Protocol:
  • All five items are positively keyed; there are no reverse-scored items in the standardized inventory.
  • An overall Chronic Categorization Tendency Index is computed by calculating the arithmetic mean of all five items: $\text{CATT Score} = \frac{\sum_{i=1}^{5} \text{Item}_i}{5}$.
  • Alternatively, researchers employing structural equation modeling may compute factor-weighted composite scores or model the latent factor directly using item covariance inputs.
• Score Interpretation:
  • High Scorers (Scores > 5.2): Exhibit a robust, habitual disposition to structure their environment into distinct, bounded categories. They rapidly process shared commonalities, derive intrinsic satisfaction from organizing stimuli, and consistently rely on categorical schemas (e.g., price-quality heuristics, brand prototypes) in judgment and decision tasks.
  • Moderate Scorers (Scores 3.8 – 5.2): Display flexible cognitive processing, transitioning between categorical grouping and individualistic, attribute-level analysis depending upon situational cues, cognitive load, or environmental framing.
  • Low Scorers (Scores < 3.8): Display an idiographic or continuous cognitive style. They tend to perceive items, people, and experiences as unique entities rather than category exemplars, exhibit lower intrinsic motivation to classify stimuli, and show reduced spontaneous reliance on taxonomic heuristics.

11. Permissions & Fee and Test Year

The Categorization Tendency (Chronic) (CATT) scale was formally introduced and published in 2020 in the Journal of Consumer Research (Volume 46, Issue 6, April 2020, Pages 1110–1124). The copyright for the academic article and its associated research materials is held by the Journal of Consumer Research, Inc., published by Oxford University Press.

In accordance with standard academic conventions, the scale items and conceptual methodology are accessible for non-commercial, scholarly, scientific, and educational research purposes without licensing fees, provided that appropriate bibliographic attribution is accorded to the original authors (Park, Lalwani, & Silvera, 2020). Scholars and behavioral practitioners wishing to reproduce the scale in commercial software, fee-bearing psychological assessment batteries, or syndicated market research tools must seek formal copyright permissions directly from the permissions department of Oxford University Press or through the Copyright Clearance Center (CCC).

12. References

• Bruner, J. S., Goodnow, J. J., & Austin, G. A. (1956). A study of thinking. John Wiley & Sons.
• Cacioppo, J. T., & Petty, R. E. (1982). The need for cognition. Journal of Personality and Social Psychology, 42(1), 116–131. https://doi.org/10.1037/0022-3514.42.1.116
• Choi, I., Koo, M., & Choi, J. A. (2007). Individual differences in analytic versus holistic thinking. Personality and Social Psychology Bulletin, 33(5), 691–705. https://doi.org/10.1177/0146167206298568
• Fiske, S. T., & Taylor, S. E. (1991). Social cognition (2nd ed.). McGraw-Hill.
• Medin, D. L., & Schaffer, M. M. (1978). Context theory of classification learning. Psychological Review, 85(3), 207–238. https://doi.org/10.1037/0033-295X.85.3.207
• Nisbett, R. E., Peng, K., Choi, I., & Norenzayan, A. (2001). Culture and systems of thought: Holistic versus analytic cognition. Psychological Review, 108(2), 291–310. https://doi.org/10.1037/0033-295X.108.2.291
• Park, H., Lalwani, A. K., & Silvera, D. H. (2020). The impact of resource scarcity on price-quality judgments. Journal of Consumer Research, 46(6), 1110–1124. https://doi.org/10.1093/jcr/ucz048
• Rosch, E. (1975). Cognitive representations of semantic categories. Journal of Experimental Psychology: General, 104(3), 192–233. https://doi.org/10.1037/0096-3445.104.3.192
• Rosch, E. (1978). Principles of categorization. In E. Rosch & B. B. Lloyd (Eds.), Cognition and categorization (pp. 27–48). Lawrence Erlbaum Associates.
• Tversky, A. (1977). Features of similarity. Psychological Review, 84(4), 327–352. https://doi.org/10.1037/0033-295X.84.4.327
• Webster, D. M., & Kruglanski, A. W. (1994). Individual differences in need for cognitive closure. Journal of Personality and Social Psychology, 67(6), 1049–1062. https://doi.org/10.1037/0022-3514.67.6.1049

13. Items of the Scale