Consumer Innovativeness Scale

1. Abstract

The Consumer Innovativeness Scale, commonly operationalized through the dual-construct framework of Consumer Independent Judgment Making (CIJM) and Consumer Novelty Seeking (CNS), is a foundational psychometric instrument developed by Kenneth C. Manning, William O. Bearden, and Thomas J. Madden in 1995. Grounded in the classical conceptualizations of innovation adoption formulated by Midgley and Dowling (1978) and the exploratory consumer behavior paradigms synthesized by Hirschman (1980), this instrument delineates consumer innovativeness into two distinct, near-orthogonal cognitive and motivational dimensions rather than treating it as a monolithic personality trait.

The scale comprises two primary subscales: Consumer Independent Judgment Making (CIJM), which measures an individual's predisposition to make product adoption and purchase choices autonomously without relying on the relayed experiences, evaluations, or normative influence of social peers; and Consumer Novelty Seeking (CNS), which gauges the intrinsic hedonic, sensory, and cognitive drive to actively seek out unfamiliar products, novel brand offerings, and unprecedented marketplace stimuli. Responses across both dimensions are captured via a standard seven-point Likert response format ranging from 1 (“Strongly Disagree”) to 7 (“Strongly Agree”).

Extensive psychometric evaluations across varied consumer cohorts substantiate the exceptional reliability and factorial integrity of the scale. Across initial validation samples, internal consistency reliability coefficients (Cronbach's alpha) consistently ranged from 0.84 to 0.87 for CIJM and 0.84 to 0.92 for CNS. Confirmatory factor analyses demonstrated that the two constructs share minimal variance (inter-construct correlations typically spanning $r = -0.11$ to $0.15$), confirming empirical orthogonality and warning against composite aggregation. In predictive modeling, CNS demonstrates a powerful positive direct path to actualized novelty-seeking behavior ($eta = 0.40$), while CIJM directly drives early trial adoption of breakthrough marketplace innovations ($eta = 0.19$). Consequently, the CIJM-CNS scale remains an indispensable diagnostic tool for academic marketing researchers, behavioral economists, and product managers assessing early adopter dynamics.

2. Keywords

Consumer Innovativeness, Consumer Novelty Seeking, Consumer Independent Judgment Making, Diffusion of Innovations, New Product Adoption, Exploratory Consumer Behavior, Scale Validation, Psychometrics, Cognitive Independence, Behavioral Decision Theory

3. Authors

The scale was developed and psychometrically validated by a team of prominent scholars in consumer behavior and psychometrics:

• Kenneth C. Manning, Ph.D. — Professor of Marketing at Colorado State University (formerly at the University of South Carolina during scale inception). His research focuses on consumer decision-making, behavioral responses to marketing communication, and psychometric measurement.
• William O. Bearden, Ph.D. — Bank of America Chaired Professor Emeritus of Marketing at the Darla Moore School of Business, University of South Carolina. Renowned international authority on consumer psychometrics, scale development methodology, and reference group influence.
• Thomas J. Madden, Ph.D. — Professor of Marketing at the Darla Moore School of Business, University of South Carolina. Expert in structural equation modeling, advertising effectiveness, and statistical methodology in behavioral research.

4. Purpose

The primary purpose of the Consumer Innovativeness Scale (CIJM-CNS) is to provide an empirically robust, theoretically sound operationalization of innate consumer innovativeness. Before the formulation of this dual-factor scale by Manning et al. in 1995, marketing and behavioral literature struggled with fragmented, inconsistent, and often confounding conceptualizations of what made a consumer “innovative.” Early diffusion research, such as the seminal framework proposed by Everett Rogers, operationalized innovativeness predominantly through “time of adoption” relative to others in a social system. However, methodologists pointed out that post-hoc behavioral measures fail to distinguish between true underlying cognitive innovativeness and circumstantial variables such as purchasing power, opportunistic product access, or heavy advertising exposure.

To overcome these limitations, Manning, Bearden, and Madden operationalized the latent psychological propensities that drive exploratory consumption. Specifically, the scale was designed to separate social-normative autonomy from sensory-epistemic sensation seeking. The CIJM subscale directly assesses the cognitive boundary separating an individual's autonomous decision architecture from interpersonal communication networks. In contrast, the CNS subscale measures the psychological desire for stimulation through consumption, addressing how individuals counter monotony, boredom, or informational satiation through unfamiliar marketplace alternatives.

In applied market research and clinical/applied consumer psychology, the CIJM-CNS scale fulfills vital diagnostic and segmentation functions:

• Early Adopter Profiling: Pinpointing the exact psychological archetype of genuine early adopters enables organizations to design targeted marketing strategies. High-CNS individuals respond vigorously to positioning emphasizing radical novelty, sensory uniqueness, and avant-garde characteristics, whereas high-CIJM individuals are persuaded by objective technical specifications, comparative utility, and evidence-based performance claims rather than social proof or celebrity endorsements.
• Mitigating Marketplace Failure Rates: More than 70% of new consumer product launches fail to achieve commercial viability. Administering the CIJM-CNS scale during prototype testing and pre-market validation helps identify whether target segments possess the requisite intrinsic novelty drive or independent decision posture to overcome status-quo bias without massive promotional subsidization.
• Testing Consumer Choice Models: In academic scholarship, the scale serves as a standardized covariate, mediator, or moderator in experimental designs evaluating adoption resistance, brand switching, risk tolerance, digital technology assimilation, and response to disruptive technological paradigms.

5. Psychological Construct

The psychological architecture of the scale represents a synthesis of cognitive autonomy and exploratory motivation. Consumer innovativeness is conceptualized not as a single continuum, but as a multidimensional matrix governed by two near-orthogonal constructs: Consumer Independent Judgment Making (CIJM) and Consumer Novelty Seeking (CNS).

Consumer Independent Judgment Making (CIJM)

Consumer Independent Judgment Making represents the extent to which a consumer makes new product adoption and brand selection decisions autonomously, without relying on the experiences, social validation, word-of-mouth feedback, or observed consumption behaviors of others. Historically derived from Midgley and Dowling's (1978) conceptualization of innate innovativeness, CIJM captures cognitive resistance to interpersonal communication and normative social influence during the pre-trial evaluation stage.

An individual scoring high on CIJM exhibits pronounced internal locus of evaluation. When confronted with a novel consumer good—such as an unfamiliar functional beverage, a radically redesigned software ecosystem, or an innovative home medical diagnostic device—the high-CIJM individual evaluates product utility through personal diagnostic assessment, technical attributes, and direct interaction. They actively minimize reliance on customer reviews, peer testimonials, influencer demonstrations, or social consensus. Conversely, an individual low on CIJM experiences adoption anxiety in the absence of interpersonal confirmation, delaying adoption until trusted peers establish a social baseline of functional safety and social acceptability.

Consumer Novelty Seeking (CNS)

Consumer Novelty Seeking refers to the consumer's underlying cognitive and emotional desire to seek out novel, unfamiliar, and unusual stimulus patterns within the consumer goods ecosystem. Heavily informed by Hirschman's (1980) treatise on novelty-seeking as an inherent drive, CNS captures the epistemic and hedonic need for sensory and experiential variation. It reflects an internal homeostatic mechanism wherein the consumer experiences psychological distress, cognitive lethargy, or boredom when restricted to repetitive, familiar consumption rituals.

High-CNS consumers continuously survey the marketplace for alternative brands, unusual flavor profiles, disruptive industrial design, and nascent technological categories simply for the phenomenological sensation of experiencing the new. For example, a high-CNS consumer visiting a grocery retailer will instinctively examine newly introduced products, frequently abandoning satisfactory incumbent brands solely to fulfill a sensation-seeking impulse. A low-CNS individual, by contrast, manifests strong brand inertia and cognitive conservatism, feeling comfort in routinized, predictable consumption patterns and perceiving novelty as an unwelcome source of friction or cognitive load.

Construct Orthogonality and Interaction

A critical contribution of Manning et al. (1995) was demonstrating that CIJM and CNS are psychometrically and conceptually distinct. An individual can possess an intense thirst for sensory novelty (High CNS) while remaining completely reliant on peer group consensus and social media influencers before feeling secure enough to purchase (Low CIJM). Conversely, a highly analytical engineer may disregard all social proof and evaluate choices with clinical independence (High CIJM), yet possess minimal intrinsic interest in novelty for its own sake, adopting changes only when technical utility dictates (Low CNS). Treating these dimensions separately is essential to avoid profound aggregation bias.

6. Theoretical Framework

The scale is anchored in two prominent theoretical pillars of modern behavioral science: Midgley and Dowling's (1978) model of innate innovativeness versus actualized innovation, and Hirschman's (1980) cognitive-experiential theory of novelty seeking, alongside broader principles from Optimal Stimulation Level (OSL) theory.

The Midgley and Dowling Model of Innovativeness (1978)

Prior to Midgley and Dowling's landmark 1978 paper in the Journal of Consumer Research, innovation adoption was overwhelmingly measured through the behaviorist framework championed by Everett Rogers, which categorized adopters ex-post (Innovators, Early Adopters, Early Majority, Late Majority, Laggards) strictly on a chronological axis. Midgley and Dowling challenged this paradigm, proposing that true innovativeness is an internal, latent personality construct that exists prior to and independent of actual product sales.

They defined innate innovativeness as “the degree to which an individual makes innovation decisions independently of the communicated experience of others.” In their mathematical and theoretical model, an innovation adoption decision can occur via two pathways: internal influence (autonomous evaluation) or external influence (interpersonal communication, social comparison, imitation). Manning et al. utilized this theoretical formulation as the direct operational foundation for the CIJM dimension, identifying cognitive independence from social influence as the decisive marker separating genuine latent innovativeness from social conformity.

Hirschman's Consumption-Based Novelty Theory (1980)

Elizabeth Hirschman expanded consumer theory by establishing that consumers do not merely seek problem-solving utility; they seek sensory, emotional, and cognitive stimulation. Hirschman integrated findings from psychological arousal theory, such as Daniel Berlyne's exploratory drive constructs, into consumer decision contexts. She posited that novelty seeking operates as an inherent drive to acquire novel information and experiences, categorized into two interrelated manifestations: epistemic novelty seeking (seeking knowledge) and experiential/sensory novelty seeking (seeking physical or affective variations).

Manning et al. (1995) operationalized Hirschman's paradigm within the CNS subscale. They established that novelty seeking represents the motivational fuel of the innovation diffusion process. While Midgley and Dowling provided the architectural framework of decision independence, Hirschman supplied the emotional and motivational imperative: the desire to encounter the unfamiliar.

Optimal Stimulation Level (OSL) and Arousal Regulation

Underpinning both dimensions is Optimal Stimulation Level (OSL) theory (Raju, 1980; Steenkamp & Baumgartner, 1992). OSL theory postulates that every biological organism maintains an internal homeostatic preference for environmental stimulation. When environmental stimulation falls below this baseline, individuals experience boredom and engage in exploratory behaviors (captured by CNS) to increase arousal. In social settings, managing cognitive arousal involves balancing informational risk with social friction—a balance negotiated by the consumer's capacity for independent cognitive judgment (captured by CIJM).

7. Validity

The psychometric validity of the CIJM-CNS scale has been thoroughly established through rigorous construct, convergent, discriminant, and predictive validity procedures across multiple independent consumer samples in Manning et al. (1995) and subsequent replication studies.

Construct and Convergent Validity

Construct validity was demonstrated by examining item-to-total correlations and factor determinacy across multiple samples. In structural equation modeling tests, all standardized indicator loadings exceeded the conventional 0.70 threshold ($p < 0.001$), signifying that the scale items capture a high proportion of true-score variance. Convergent validity was established through strong, statistically significant correlations between the CNS subscale and established generalized novelty-seeking scales, such as Raju's (1980) Exploratory Tendencies Scale and Pearson's Novelty Seeking Scale ($r > 0.60, p < 0.001$).

Discriminant Validity

Discriminant validity is a cornerstone of the Manning et al. instrument, particularly in confirming that CIJM and CNS measure distinct constructs rather than variations of a single general factor. Across three separate empirical validation cohorts (Sample 1: $N = 217$; Sample 2: $N = 184$; Sample 3: $N = 280$), the correlation between CIJM and CNS remained consistently low and statistically non-significant or weakly negative/positive, ranging between $r = -0.11$ and $r = 0.15$.

Furthermore, average variance extracted (AVE) calculations surpassed the squared correlation coefficients ($\Phi^2$) between CIJM and CNS across all test samples, satisfying the Fornell-Larcker criterion. Discriminant validity was also confirmed in relation to generalized consumer susceptibility to interpersonal influence (CSII; Bearden, Netemeyer, & Teel, 1989). CIJM correlated strongly and negatively with normative and informational CSII ($r = -0.45$ to $-0.58, p < 0.001$), whereas CNS demonstrated near-zero correlations with susceptibility to influence, demonstrating distinct psychological operations.

Predictive and Nomological Validity

The nomological network formulated by Manning et al. established clear differential predictive pathways for the two subscales, verifying that the dimensions generate unique behavioral consequences:

• Prediction of Actualized Novelty Seeking: Structural equation path models confirmed that CNS exerts a powerful positive direct effect on actualized novelty seeking behaviors ($eta = 0.40, p < 0.001$). Individuals high in CNS demonstrated consistently greater breadth of brand trials, varied consumption repertoires, and active information foraging.
• Prediction of Independent Product Trial: In experimental and naturalistic purchase scenarios involving new-to-market brands, CIJM emerged as the significant direct predictor of first-wave trial adoption ($eta = 0.19, p < 0.01$), whereas social-influence-dependent individuals lagged significantly.
• Demographic Nomology: Consistent with developmental lifespan theory in consumer psychology, CNS exhibited a stable, statistically significant negative correlation with respondent age ($r pprox -0.25$ to $-0.32$), reflecting age-related decline in stimulation-seeking thresholds. In contrast, CIJM showed little to no correlation with age, functioning as a stable cognitive decision style across adulthood.

8. Reliability

The reliability of the Consumer Innovativeness Scale has been established through internal consistency assessments and test-retest investigations across diverse testing conditions.

Internal Consistency Reliability

During the primary scale development protocol conducted by Manning, Bearden, and Madden (1995), psychometric evaluations were run across three large, heterogeneous samples comprising university students, general adult household heads, and non-student consumer panels. The resulting internal consistency metrics were:

• Consumer Independent Judgment Making (CIJM): Cronbach's alpha ($lpha$) coefficients consistently ranged between 0.84 and 0.87 across all three validation cohorts. Composite reliability (CR) metrics derived from structural equation models similarly exceeded 0.86, demonstrating high internal consistency.
• Consumer Novelty Seeking (CNS): Cronbach's alpha coefficients for the CNS dimension ranged from 0.84 to 0.92 across the same independent test administrations, with composite reliabilities mirroring these metrics.

Corrected item-to-total correlations across both subscales were consistently above 0.55, with the vast majority exceeding 0.65. Deletion of any single item failed to improve total internal consistency, confirming that all retained items contribute reliably to the measurement model.

Test-Retest Stability

In temporal stability assessments conducted over intervals spanning three to six weeks, test-retest correlation coefficients ($r_{tt}$) consistently exceeded 0.78 for both CIJM and CNS subscales. This temporal stability indicates that the scale captures enduring cognitive and motivational dispositions rather than transient, state-dependent affective reactions to marketing campaigns.

9. Factor Analysis

The structural integrity of the CIJM-CNS scale was developed and validated through a rigorous two-stage factor analytic sequence employing Exploratory Factor Analysis (EFA) followed by Confirmatory Factor Analysis (CFA) within structural equation modeling platforms.

Exploratory Factor Analysis (EFA)

During initial item reduction from an original candidate pool of 48 items derived from literature review and content-validation panels, maximum likelihood exploratory factor analyses with oblique (promax/oblimin) rotations were applied. Eigenvalue-greater-than-one criteria and scree-plot examinations consistently revealed a dominant two-factor solution explaining over 58% of the total variance.

Items demonstrated simple factor structure: all retained items loaded heavily (> 0.65) onto their hypothesized factor (either CIJM or CNS) while cross-loadings on the non-target dimension were systematically below 0.20. The empirical correlation between the extracted factors remained close to zero ($r pprox 0.05$), underscoring the independence of these dimensions.

Confirmatory Factor Analysis (CFA)

The two-factor orthogonal measurement model was subsequently tested using CFA on independent validation samples ($N = 184$ and $N = 280$). The hypothesized two-factor model demonstrated exceptional fit across all recognized goodness-of-fit parameters:

• Chi-Square / Degrees of Freedom Ratio ($\chi^2/df$): Values ranged between 1.34 and 1.85, well below the conservative threshold of 2.00, indicating minimal residual discrepancy.
• Comparative Fit Index (CFI): Ranged from 0.95 to 0.98 across samples, confirming that the hypothesized structure is superior to null baselines.
• Goodness of Fit Index (GFI) & Adjusted Goodness of Fit Index (AGFI): GFI values exceeded 0.93; AGFI values consistently exceeded 0.90.
• Root Mean Square Error of Approximation (RMSEA): Values ranged from 0.038 to 0.054, with 90% confidence interval upper bounds failing to exceed 0.07, demonstrating close model fit.

To verify the superiority of the two-factor specification, Manning et al. compared the two-factor model against a competing unidimensional (one-factor) model where all items loaded on a single general innovativeness factor. The one-factor model suffered catastrophic deterioration in fit ($\Delta \chi^2(1) > 350.0, p < 0.0001$; CFI < 0.72; RMSEA > 0.14), disconfirming the hypothesis that consumer innovativeness is an undifferentiated trait.

10. Instrument / Measurement Tool

• Construct Measured: Innate Consumer Innovativeness, divided into two distinct dimensions: Consumer Independent Judgment Making (decision autonomy from interpersonal influence) and Consumer Novelty Seeking (motivational drive for new experiences and products).
• Subscales:
  • Consumer Independent Judgment Making (CIJM): Evaluates independence from the communicated experiences and normative validation of peers.
  • Consumer Novelty Seeking (CNS): Evaluates the intrinsic cognitive, sensory, and hedonic drive to explore novel marketplace offerings.
• Test Type: Self-report psychological scale / survey instrument.
• Response Scale: 7-point Likert-type scale ranging from 1 (“Strongly Disagree”) to 7 (“Strongly Agree”).
• Scoring and Directionality Rules:
  • Scores for the CIJM and CNS subscales must always be calculated and reported separately. Under no circumstances should items from both subscales be summed or averaged into a single aggregate innovativeness score, as doing so obscures their orthogonal relationship.
  • Reverse Scoring: Within the original item inventory, Item 1 of the CIJM subscale is negatively worded and requires reverse scoring ($X_{reversed} = 8 – X_{raw}$). Similarly, Item 5 of the CNS subscale requires reverse scoring prior to index computation.
  • Subscale Index: Calculate the mean or sum of the items for each subscale after reverse-coding specified items. Higher scores indicate greater cognitive independence in purchasing (CIJM) or a stronger behavioral drive to explore new product categories (CNS).
• Administration Time: Approximately 3 to 5 minutes to complete.

11. Permissions & Fee and Test Year

The Consumer Innovativeness Scale was published in 1995 by Kenneth C. Manning, William O. Bearden, and Thomas J. Madden in the Journal of Consumer Psychology.

Licensing and Academic Use: As an academic measurement tool published in peer-reviewed scholarship, the instrument is widely accessible to academic researchers, graduate students, and non-commercial educators without payment of licensing royalties, provided appropriate bibliographic citation is extended to the original authors and the journal publication. Commercial research organizations, marketing agencies, and corporate practitioners intending to integrate the scale into commercial diagnostic platforms, software architectures, or proprietary consulting frameworks should seek formal clearance or review permissions via the rights-management representatives of the Society for Consumer Psychology (SCP) and the original publisher (Elsevier / Wiley / Lawrence Erlbaum Associates depending on journal publishing archives).

12. References

The conceptualization, validation, and theoretical framework of the CIJM-CNS scale are supported by the following foundational literature:

• Bearden, W. O., Netemeyer, R. G., & Teel, J. E. (1989). Measurement of consumer susceptibility to interpersonal influence. Journal of Consumer Research, 15(4), 473–481. https://doi.org/10.1086/209186
• Hirschman, E. C. (1980). Innovativeness, novelty seeking, and consumer creativity. Journal of Consumer Research, 7(3), 283–295. https://doi.org/10.1086/208816
• Manning, K. C., Bearden, W. O., & Madden, T. J. (1995). Consumer innovativeness and the adoption process. Journal of Consumer Psychology, 4(4), 329–345. https://doi.org/10.1207/s15327663jcp0404_02
• Midgley, D. F., & Dowling, G. R. (1978). Innovativeness: The concept and its measurement. Journal of Consumer Research, 4(4), 229–242. https://doi.org/10.1086/208701
• Raju, P. S. (1980). Optimum stimulation level: Its relationship to personality, demographics, and exploratory behavior. Journal of Consumer Research, 7(3), 272–282. https://doi.org/10.1086/208815
• Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.
• Steenkamp, J. B. E., & Baumgartner, H. (1992). The role of optimum stimulation level in exploratory consumer behavior. Journal of Consumer Research, 19(3), 434–448. https://doi.org/10.1086/209313

13. Items of the Scale