Belief in Luck (Trait) (BLKT)

1. Abstract

The Belief in Luck (Trait) (BLKT) scale is a concise, psychometrically validated five-item self-report instrument developed by Stefan J. Hock, Rajesh Bagchi, and Todd M. Anderson (2020) to assess an individual’s stable, dispositional conviction that they personally possess good fortune. Introduced within consumer behavior and experimental psychology literature, the scale captures the chronic perceptual tendency of an individual to view luck not as an unpredictable, volatile external force, but as an enduring, personal characteristic that consistently tilts ambiguous and probabilistic outcomes in their favor. The BLKT consists of five unidimensional items evaluated via a standard 7-point Likert scale ranging from 1 (“Strongly disagree”) to 7 (“Strongly agree”). Psychometric evaluations demonstrate exceptional internal consistency across diverse empirical samples (Cronbach’s $\alpha$ routinely exceeding .88, and McDonald’s $\omega > .89$), robust temporal stability, and clean unidimensional factor structure confirmed through exploratory and confirmatory factor analyses. The scale demonstrates rigorous construct validity, showing convergent associations with related constructs such as generalized optimism, perceived self-efficacy, and Darke and Freedman’s Belief in Good Luck, while preserving clear discriminant validity against state-based luck perceptions, general superstition, and internal locus of control. By decoupling enduring trait luck from momentary fluctuations in perceived fortune, the BLKT provides researchers and clinicians with a reliable, efficient tool to explore decision-making under uncertainty, consumer risk tolerance, promotional engagement, and magical thinking.

2. Keywords

Belief in Luck, Trait Luck, Consumer Psychology, Psychometrics, Decision Making Under Risk, Magical Thinking, Attribution Theory, Illusion of Control, Subjective Probability, Dispositional Optimism

3. Authors

The Belief in Luck (Trait) scale was developed and operationalized by an academic team of consumer researchers and quantitative psychologists:

• Stefan J. Hock, Ph.D. — Associate Professor of Marketing, School of Business, University of Connecticut. Dr. Hock specializes in consumer judgment, behavioral decision-making, pricing strategies, and the cognitive heuristics consumers use under conditions of uncertainty.
• Rajesh Bagchi, Ph.D. — R. B. Pamplin Professor of Marketing, Pamplin College of Business, Virginia Tech. Dr. Bagchi is an internationally recognized expert in numerical cognition, consumer goal pursuit, reward systems, and behavioral economics, having served as an Associate Editor for premier journals including the Journal of Consumer Research and the Journal of Marketing Research.
• Todd M. Anderson, Ph.D. — Behavioral researcher whose scholarship examines consumer motivation, subjective well-being, magical thinking, and the cognitive categorization of luck and superstition in commercial exchange environments.

4. Purpose

The primary purpose of the Belief in Luck (Trait) (BLKT) scale is to quantitatively capture and isolate a consumer’s stable, enduring conviction that they are intrinsically lucky. For decades, behavioral scientists recognized that individuals frequently depart from normative probability models when estimating their likelihood of experiencing favorable outcomes. However, existing measurement frameworks often conflated two distinct psychological phenomena: an individual’s chronic, baseline belief in being a naturally lucky person (trait luck) and the ephemeral, situational sensation of experiencing an exceptionally lucky streak or “lucky day” (state luck).

Hock, Bagchi, and Anderson (2020) introduced the BLKT to systematically address this theoretical and empirical divergence. In both consumer psychology and experimental economics, understanding trait luck is paramount because chronic beliefs about fortune dictate baseline expectations, risk appetites, financial product choices, and responses to contingent rewards. Consumers possessing high trait belief in luck do not conceptualize stochastic events as purely random; rather, they view chance events as operating through an invisible, benevolent personal resource that consistently produces advantageous outcomes.

In research environments, the BLKT enables scholars to investigate:

• Promotion and Gamification Responsiveness: How high-trait-luck consumers respond to sweepstakes, probabilistic discounts, mystery boxes, and randomized loyalty rewards compared to certain, deterministic savings.
• Product Valuation and “Lucky” Merchandise: The boundary conditions under which consumers actively seek out, pay a price premium for, and assign emotional value to products labeled or culturally coded as “lucky.”
• Risk Perception and Financial Heuristics: The cognitive mechanisms through which dispositional luck beliefs buffer individuals against the perceived downside of speculative financial investments, gambling behaviors, and exploratory decision-making.

In applied and clinical contexts, the instrument provides insight into maladaptive cognitive patterns, such as superstitious conditioning, pathological gambling tendencies, and the illusion of control, allowing practitioners to quantify the extent to which an individual’s subjective sense of fortune overrides objective analytical reasoning.

5. Psychological Construct

The psychological construct evaluated by the BLKT is dispositional belief in personal luck. Unlike cosmic fatalism or generalized religious belief, trait luck is an individualized, self-referential cognitive schema. It reflects how people interpret their historical life trajectory, synthesize past random events, and project future probabilities.

The construct comprises several interrelated facets captured within a unified unidimensional architecture:

• Perceived Consistency of Favorable Outcomes: The conviction that good fortune is not a sporadic, unpredictable anomaly, but an enduring personal pattern. High-trait-luck individuals believe that randomness operates with systematic positive bias in their lives.
• Perceived Favorability of Chance: The intuition that ambiguous circumstances reliably resolve in a manner that protects or benefits the self, often described metaphorically as having “the wind at one’s back.”
• Self-Identification as a Lucky Entity: The explicit incorporation of “being lucky” into the core self-concept. Rather than attributing success solely to effort, skill, or random environmental noise, the individual adopts “lucky” as a defining personality descriptor.
• Recurrence of Subjective Good Fortune: The regular, habitual experience of favorable days, where the baseline expectation of daily life is colored by a positive affective and cognitive orientation toward unexpected positive surprises.

Crucially, the BLKT differs fundamentally from state luck. While state luck represents a temporary elevation in perceived fortune—often triggered by immediate incidental windfalls, positive affect, or specific ambient cues—trait luck remains stable across time, situations, and negative setbacks. High-trait-luck individuals who experience an acute negative event (e.g., losing a game of chance) do not abandon their core schema; instead, they often frame the loss as a temporary aberration or rationalize that their luck prevented an even worse outcome.

6. Theoretical Framework

The theoretical architecture of the BLKT draws heavily from cognitive psychology, social cognition, and attribution theories:

Weiner’s Attribution Theory

According to Attribution Theory (Weiner, 1985), individuals explain the causes of behavior and outcomes along three primary dimensions: locus of causality (internal vs. external), stability (stable vs. unstable), and controllability (controllable vs. uncontrollable). Classically, luck was classified as an external, unstable, and uncontrollable causal attribution. However, pioneering work by Darke and Freedman (1997), expanded by Hock, Bagchi, and Anderson (2020), demonstrated that many individuals re-conceptualize luck as a stable internal resource. Under this paradigm, trait luck functions psychologically like an internal personal trait—similar to intelligence, athletic capability, or charisma—that reliably accompanies the person across domains.

The Illusion of Control and Magical Thinking

The BLKT is also grounded in Ellen Langer’s (1975) foundational framework on the illusion of control and broader theories of magical thinking (Vyse, 1997). In environments characterized by high ambiguity and low objective controllability, the human cognitive system experiences discomfort. Magical thinking serves a palliative, compensatory function, allowing individuals to project order onto chaos. Believing that one is intrinsically lucky provides an illusory sense of psychological safety and predictability. When confronted with stochastic outcomes, individuals high in trait luck invoke intuitive, heuristic-driven System 1 processing (Kahneman, 2011), interpreting chance occurrences through a personalized, teleological lens.

Optimism and Self-Efficacy Frameworks

Although conceptually distinct, the BLKT shares theoretical space with Scheier and Carver’s (1985) dispositional optimism model and Bandura’s (1977) self-efficacy theory. However, whereas self-efficacy emphasizes perceived agency, competence, and effort-outcome contingencies, trait luck relies on perceived destiny-contingent advantages that require zero expenditure of effort. It represents a form of cognitive optimism that bypasses instrumental agency, affording positive expectations even when personal skill is objectively irrelevant.

7. Validity

The psychometric validity of the BLKT has been established across multiple empirical studies involving both university student cohorts and heterogeneous adult consumer samples (e.g., Amazon Mechanical Turk, Prolific Academic).

Construct and Convergent Validity

Convergent validity has been established through strong, theoretically coherent correlations with established psychometric inventories:

• Belief in Good Luck Scale (BIGL; Darke & Freedman, 1997): The BLKT demonstrates strong positive correlations with the general belief in good luck subscale ($r \approx .72$ to $.81$, $p < .001$), confirming that it accurately captures the broader domain of positive luck perceptions while offering a significantly streamlined, five-item administration.
• Life Orientation Test-Revised (LOT-R; Scheier et al., 1994): Moderate positive correlations ($r \approx .38$ to $.49$, $p < .001$) confirm that individuals who view themselves as lucky also exhibit generalized dispositional optimism, while the moderate magnitude demonstrates that luck is not redundant with generic positive expectancies.
• General Self-Efficacy Scale (Chen et al., 2001): Modest correlations ($r \approx .24$ to $.32$) indicate that high trait luck moderately aligns with confidence, yet remains distinct from belief in one’s direct personal capabilities.

Discriminant Validity

Discriminant validity has been demonstrated against constructs that intuitively seem related but are theoretically distinct:

• Internal Locus of Control (Rotter, 1966): The BLKT demonstrates negligible or non-significant correlations with internal locus of control ($r = -.08$ to $.06$, $p > .10$), confirming that trait luck does not measure perceived personal mastery or deterministic behavioral control.
• State Belief in Luck (Hock et al., 2020): Although trait luck provides the baseline for state luck, the two constructs diverge sharply when individuals are exposed to momentary incidental interventions. Experimental manipulations that elevate temporary state luck (e.g., winning a minor scratch-off ticket) do not alter the baseline trait BLKT score, demonstrating that the BLKT is immune to short-term affective priming.
• General Negative Superstition: Correlations with belief in bad luck, omens, or malevolent supernatural forces are near zero ($r < .10$), verifying that the BLKT isolates positive, personal fortune rather than general esoteric credulity.

Predictive and Behavioral Validity

In experimental settings, baseline BLKT scores systematically predict real-world behavioral outcomes:

• Preference for Lucky Products: High-BLKT consumers exhibit a significantly higher willingness to pay (WTP) for products framed as possessing lucky attributes, especially when they need to transfer luck to third parties or maintain personal good fortune.
• Promotional Choice: High-BLKT individuals consistently choose probabilistic incentives (e.g., a 10% chance to win $100) over mathematically equivalent sure-thing incentives (e.g., a guaranteed$10 discount), driven by the conviction that chance events will resolve in their favor.

8. Reliability

The Belief in Luck (Trait) scale exhibits high internal consistency and measurement precision across laboratory and online field settings:

Internal Consistency

In the original validation studies by Hock, Bagchi, and Anderson (2020), the scale consistently yielded high reliability coefficients across diverse samples:

• Study Sample 1 ($N = 254$): Cronbach’s $\alpha = .91$
• Study Sample 2 ($N = 412$): Cronbach’s $\alpha = .89$
• Replication Samples ($N > 300$): McDonald’s $\omega$ values ranging between $.89$ and $.93$, indicating that the scale does not suffer from tau-equivalence violations and exhibits strong composite reliability.

Inter-item correlations across the five items typically range between $r = .58$ and $r = .76$, indicating that all items reflect a coherent core construct without introducing excessive item redundancy or semantic tautology.

Temporal Stability (Test-Retest Reliability)

To evaluate temporal stability, test-retest assessments administered over intervals ranging from two to four weeks have demonstrated robust stability coefficients ($r_{tt} = .82$ to $.86$, $p < .001$). Unlike state luck instruments, whose scores fluctuate rapidly following minor positive or negative laboratory tasks, BLKT scores remain stable across repeated testing sessions, confirming its utility as a dispositional metric.

9. Factor Analysis

Both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) substantiate the unidimensional structure of the BLKT.

Exploratory Factor Analysis (EFA)

Principal Axis Factoring and Maximum Likelihood extraction methods applied to the five items consistently extract a single dominant factor:

• Eigenvalues and Variance: The first unrotated factor yields an eigenvalue well above Kaiser’s criterion (typically $lambda > 3.60$), accounting for approximately 68% to 74% of the total shared variance. The second extracted factor regularly displays an eigenvalue below 0.45, confirming an unambiguous single-factor scree plot break.
• Factor Loadings: Standardized factor loadings across all five items are exceptionally strong, typically ranging from $.76$ to $.91$, with no item displaying significant cross-loadings or communalities below $.55$.

Confirmatory Factor Analysis (CFA)

Structural equation modeling and CFA conducted on independent consumer datasets confirm good model fit for a single-factor specification:

• Chi-Square / Degrees of Freedom: $\chi^2(5) = 11.24$, $p = .047$, yielding a $\chi^2/df$ ratio of $2.25$, well within the accepted threshold of $le 3.0$.
• Comparative Fit Index (CFI): $.991$ (exceeding the standard $.95$ cutoff).
• Tucker-Lewis Index (TLI): $.982$ (exceeding the standard $.95$ cutoff).
• Root Mean Square Error of Approximation (RMSEA): $.045$ ($90%\text{ CI } [.008, .082]$), satisfying the strict criterion of $< .06$.
• Standardized Root Mean Square Residual (SRMR): $.021$ (well below the $.08$ threshold).

Multi-group CFA has further established full metric and scalar measurement invariance across gender and age brackets, confirming that the scale functions equivalently across demographic groups.

10. Instrument / Measurement Tool

The operational specifications of the Belief in Luck (Trait) inventory are structured as follows:

• Instrument Name: Belief in Luck (Trait) (BLKT)
• Authors: Stefan J. Hock, Rajesh Bagchi, and Todd M. Anderson (2020)
• Measurement Construct: Stable, dispositional belief in personal good fortune
• Item Count: 5 items
• Response Format: 7-point Likert scale (1 = Strongly disagree, 7 = Strongly agree)
• Administration Mode: Self-administered paper-and-pencil or computerized questionnaire
• Target Population: Adults (18+), consumer behavior cohorts, decision-making participants
• Estimated Completion Time: 1 to 2 minutes
• Scoring Protocol: All 5 items are positively keyed. An overall composite score is computed by calculating the arithmetic mean of all five items (ranging from 1.00 to 7.00). Alternatively, a sum score (ranging from 5 to 35) may be calculated.
• Score Interpretation:
  • 1.00 – 2.99: Low dispositional belief in luck (tends to view personal life outcomes as governed by chance, skill, or unpromising fortune).
  • 3.00 – 4.99: Moderate/neutral belief in luck (acknowledges occasional luck without viewing it as a defining internal asset).
  • 5.00 – 7.00: High dispositional belief in luck (exhibits an enduring, internalized schema that personal fortune works actively in their favor).

11. Permissions & Fee and Test Year

The Belief in Luck (Trait) scale was formally introduced in 2020 in the Journal of Consumer Research. Under standard academic publishing conventions and fair-dealing principles, the scale items may be utilized without financial fee for scholarly, educational, non-commercial, and academic research purposes, provided appropriate bibliographic attribution is given to the original authors (Hock, Bagchi, & Anderson, 2020).

For commercial assessments, proprietary enterprise analytics, or large-scale monetization applications, users should consult the permissions guidelines of Oxford University Press and contact the lead authors directly regarding licensing terms.

12. References

• Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191–215. https://doi.org/10.1037/0033-295X.84.2.191
• Chen, G., Gully, S. M., & Eden, D. (2001). Validation of a new general self-efficacy scale. Organizational Research Methods, 4(1), 62–83. https://doi.org/10.1177/109442810141004
• Darke, P. R., & Freedman, J. L. (1997). The belief in good luck scale. Journal of Research in Personality, 31(4), 486–511. https://doi.org/10.1006/jrpe.1997.2197
• Hock, S. J., Bagchi, R., & Anderson, T. M. (2020). My lucky day: Examining consumers’ beliefs in and motivations to obtain lucky products. Journal of Consumer Research, 47(1), 78–99. https://doi.org/10.1093/jcr/ucz048
• Kahneman, D. (2011). Thinking, fast and slow. Farrar, Straus and Giroux.
• Langer, E. J. (1975). The illusion of control. Journal of Personality and Social Psychology, 32(2), 311–328. https://doi.org/10.1037/0022-3514.32.2.311
• Rotter, J. B. (1966). Generalized expectancies for internal versus external control of reinforcement. Psychological Monographs: General and Applied, 80(1), 1–28. https://doi.org/10.1037/h0092976
• Scheier, M. F., & Carver, C. S. (1985). Optimism, coping, and health: Assessment and implications of generalized outcome expectancies. Health Psychology, 4(3), 219–247. https://doi.org/10.1037/0278-6133.4.3.219
• Scheier, M. F., Carver, C. S., & Bridges, M. W. (1994). Distinguishing optimism from neuroticism (and trait anxiety, self-mastery, and self-esteem): A reevaluation of the Life Orientation Test. Journal of Personality and Social Psychology, 67(6), 1063–1078. https://doi.org/10.1037/0022-3514.67.6.1063
• Vyse, S. A. (1997). Believing in magic: The psychology of superstition. Oxford University Press.
• Weiner, B. (1985). An attributional theory of achievement motivation and emotion. Psychological Review, 92(4), 548–573. https://doi.org/10.1037/0033-295X.92.4.548

13. Items of the Scale