Belief in Luck (State) (BLKS)

1. Abstract

The Belief in Luck (State) (BLKS) scale is a psychometric instrument developed by Stefan J. Hock, Rajesh Bagchi, and Todd M. Anderson (2020) to capture an individual’s momentary, situational perception of personal fortune. While traditional psychometric assessments of luck conceptualize it as a stable, dispositional trait—such as the widely utilized Belief in Good Luck Scale (BIGLS)—the BLKS measures transient, state-level fluctuations in the subjective sense that luck is actively operating in one’s favor at the present moment. Comprising five self-report items evaluated on a seven-point Likert scale, the instrument employs explicit temporal qualifiers (e.g., “right now,” “today”) to anchor respondents’ cognitive appraisals to immediate circumstances. Psychometric evaluations across multiple experimental and consumer behavior investigations demonstrate that the BLKS exhibits exceptional internal consistency (Cronbach’s α typically ranging from .89 to .94) and a robust unidimensional factor structure confirmed via confirmatory factor analysis (CFA). The scale possesses pronounced convergent validity with situational optimism and momentary positive affect, yet establishes strict discriminant validity from general mood states and dispositional luck beliefs. By isolating the state-based component of perceived fortune, the BLKS provides researchers in behavioral economics, experimental psychology, judgment and decision-making (JDM), and consumer research with an empirically validated tool to examine how situational cues evoke feelings of luck, modulate risk-taking propensities, and drive consumption behaviors.

2. Keywords

Belief in Luck (State), BLKS, State Luck, Psychometrics, Consumer Behavior, Subjective Fortune, Decision Making, Attribution Theory, Temporal Anchoring, Risk-Taking Propensity

3. Authors

The Belief in Luck (State) scale was developed and psychometrically validated by:

• Stefan J. Hock — Associate Professor of Marketing, Department of Marketing, School of Business, University of Connecticut, Storrs, CT, USA. Research expertise includes consumer judgment, superstitious beliefs, pricing strategies, and experimental methodology.
• Rajesh Bagchi — R. B. Pamplin Professor of Marketing, Pamplin College of Business, Virginia Polytechnic Institute and State University (Virginia Tech), Blacksburg, VA, USA. Renowned scholar in consumer decision-making, goal pursuit, numerical cognition, and behavioral economics.
• Todd M. Anderson — Professional marketing researcher and behavioral scientist, specializing in consumer insights, experiential retail, and empirical behavioral modeling.

4. Purpose

The primary purpose of the Belief in Luck (State) (BLKS) scale is to quantify an individual’s subjective, real-time assessment that external, uncontrollable chance factors are currently leaning in their favor. Historically, the behavioral literature has treated the belief in luck primarily as an enduring personal worldview or an individual difference variable. Classic measures, such as the Belief in Good Luck Scale (Darke & Freedman, 1997), operationalize luck as a stable personal resource akin to an internal locus of control or generalized optimism. However, everyday human experience suggests that individuals frequently perceive luck as dynamic, ephemeral, and episodic—manifesting as “lucky streaks,” “lucky days,” or fleeting windows of supernatural or probabilistic favor.

Hock, Bagchi, and Anderson (2020) constructed the BLKS to bridge this theoretical divide. In clinical, organizational, and experimental contexts, researchers frequently manipulate external variables (such as weather, unexpected minor windfalls, situational superstitions, or promotional framing) that may temporarily elevate feelings of being lucky without fundamentally altering one’s dispositional worldview. The BLKS provides an exact, ecologically valid mechanism to evaluate the success of such experimental manipulations and track intra-individual variations across time.

Furthermore, the scale was created to elucidate the downstream consequences of transient luck perceptions on consumer behavior and financial decision-making. High state luck feelings have been shown to elevate consumer willingness to pay for specialized or “lucky” goods, spur engagement in commercial gaming or lottery purchasing, increase risk tolerance in financial portfolios, and alter attributional evaluations of personal performance. By administering the BLKS, researchers can parse whether heightened risk-seeking stems from a general affective boost (positive mood) or a discrete cognitive appraisal that chance events are temporarily aligned with personal desires.

5. Psychological Construct

The construct measured by the BLKS is State Belief in Luck. In contemporary cognitive and consumer psychology, luck is conceptualized as an explanation for uncontrollable, random events that yield positive outcomes. The state formulation of this belief centers on three core dimensions of situational cognitive appraisal:

Current Lucky-Day Perception

This facet captures the holistic heuristic appraisal that an entire current cycle (typically the current calendar day) is marked by heightened positive chance. Rather than evaluating a solitary isolated event, respondents engage in a broad categorical appraisal that “today is my lucky day.” This cognitive framing primes the individual to expect subsequent events throughout the day to resolve favorably, creating an expectation of positive probabilistic skewness.

Momentary Sense of Favorable Fortune

Contrasting with broader day-level perceptions, this dimension captures the acute, real-time feeling that luck is actively operating “right now” or “at this exact moment.” It reflects the phenomenological sense that unseen external forces or serendipitous probabilistic distributions are actively protecting or boosting the individual in the immediate present. In experimental paradigms, this feeling can be induced by micro-events, such as finding a coin, rolling a critical number in a game, or receiving an unexpected positive notification.

Perceived Lucky Streak or Period

This component reflects the perception of temporal clustering in random processes, conceptually adjacent to the “hot hand phenomenon.” It taps the belief that the individual is currently situated within a discrete, transient window or temporal epoch where chance events do not conform to independent and identically distributed (i.i.d.) statistical expectations, but rather exhibit positive auto-correlation. Individuals scoring high on this dimension perceive that recent successes are predictive of immediate future successes due to an active, benevolent force of luck.

Crucially, State Belief in Luck must be conceptually delineated from generalized optimism and positive affect. While positive affect involves generalized valence and physiological arousal (e.g., feeling enthusiastic, excited, or proud), state luck involves a specific cognitive attribution regarding the behavior of external probability. Similarly, dispositional luck involves an enduring self-concept (“I am a lucky person”), whereas state luck is intrinsically transient, volatile, and highly susceptible to immediate contextual framing.

6. Theoretical Framework

The theoretical foundations of the BLKS rest at the intersection of causal attribution theory, heuristic cognitive processing, and magical thinking:

Weiner’s Attribution Theory

According to Bernard Weiner’s Attribution Theory (1985), individuals attribute performance outcomes along three primary dimensions: locus of causality (internal vs. external), stability (stable vs. unstable), and controllability (controllable vs. uncontrollable). Classical models of luck classify it as an external, unstable, and uncontrollable factor. When luck is experienced as a stable trait, individuals violate standard normative attributions by treating it as an internal or permanent property of the person. However, the BLKS aligns directly with Weiner’s canonical definition of luck as an unstable situational attribution. Respondents use state luck to account for immediate, transient variations in their environmental outcomes without necessarily redefining their personal self-concept.

Magical Thinking and Illusory Control

The scale integrates theories of magical thinking and illusion of control (Langer, 1975). When individuals confront irreducible uncertainty, heuristic cognitive processing often leads them to impose agency, intention, or patterning onto purely stochastic systems. Hock et al. (2020) demonstrated that when consumers experience elevated state luck, they perceive a momentary alignment between their intentions and probabilistic outcomes. This theoretical framework posits that feelings of state luck satisfy fundamental epistemic and psychological needs for certainty and perceived predictability in inherently hazardous or uncertain environments.

The Hot Hand Fallacy and Cognitive Clustering

The psychometric structure of the BLKS also draws from cognitive biases identified in behavioral economics, specifically the hot hand fallacy (Gilovich et al., 1985). Human cognitive architecture exhibits poor intuitive comprehension of random dispersion, frequently misinterpreting random clusters of favorable outcomes as indicative of an underlying state of enhanced capability or metaphysical favor. The BLKS measures the psychological manifestation of this perceived cluster—the subjective feeling that one is currently riding an upward probabilistic wave.

7. Validity

The psychometric validity of the BLKS has been extensively documented through multiple empirical studies involving experimental manipulations, field interventions, and survey paradigms (Hock, Bagchi, & Anderson, 2020):

Construct and Convergent Validity

Construct validity is substantiated by significant positive correlations with established constructs of dispositional luck, situational optimism, and positive affect. In initial validation studies, the BLKS demonstrated moderate-to-high positive correlations with the Belief in Good Luck Scale (BIGLS; r ≈ .45 to .58, p < .001). The moderate magnitude confirms convergent validity while confirming that the two scales measure distinct phenomena; if the correlation approached unity, it would suggest redundancy between state and trait operationalizations. Furthermore, state luck correlates positively with the positive affect subscale of the Positive and Negative Affect Schedule (PANAS) (r ≈ .35 to .48, p < .001), reflecting the pleasant phenomenological tone associated with feeling lucky.

Discriminant Validity

Discriminant validity was established using Fornell-Larcker criterion tests and nested confirmatory factor analytic comparisons. Hock et al. (2020) modeled state luck simultaneously with state mood, general optimism (Life Orientation Test-Revised; LOT-R), and trait luck. In all instances, the average variance extracted (AVE) for the BLKS exceeded the squared correlation between BLKS and the comparator constructs (AVE > .65 vs. r² < .35). Crucially, while positive mood manipulations elevate generalized valence, targeted luck manipulations (such as subtle framing of random selection) selectively elevated BLKS scores without producing corresponding elevations across unrelated positive emotional markers (such as feeling alert or attentive).

Predictive and Criterion-Related Validity

The predictive utility of the scale is exceptionally strong in behavioral and economic settings. Studies conducted by Hock et al. (2020) revealed that elevated BLKS scores directly predict:

• A significantly increased willingness to pay (WTP) for products framed as possessing lucky attributes (e.g., limited-edition “lucky” promotional packaging).
• Greater willingness to engage in probabilistic gambles and higher purchase incidence of state lottery tickets.
• Statistical mediation of the relationship between lucky environmental cues (such as serendipitous finding of an item) and downstream consumer risk tolerance.

8. Reliability

The BLKS demonstrates robust internal consistency and psychometric reliability across diverse demographic samples, including undergraduate cohorts and adult online panels (such as Amazon Mechanical Turk and Prolific):

Internal Consistency

Across the experimental studies reported in Hock, Bagchi, and Anderson (2020), the five-item scale consistently yielded high internal consistency coefficients:

• Study 1: Cronbach’s α = .92
• Study 2: Cronbach’s α = .90
• Study 3: Cronbach’s α = .94
• Study 4: Cronbach’s α = .89

McDonald’s omega (ω) coefficients evaluated in structural equation modeling replications routinely exceed .91, indicating that the scale possesses minimal measurement error. Corrected item-total correlations across all five items consistently exceed .70, demonstrating high mutual coherence without problematic collinearity.

Test-Retest Stability Considerations

Because the BLKS is designed explicitly as a state measure, high test-retest reliability across long intervals (e.g., multiple weeks) is neither theoretically expected nor desirable. However, short-interval test-retest assessments administered within an identical experimental session (prior to experimental intervention) exhibit high stability (r > .85), while longitudinal re-testing across distinct days demonstrates moderate-to-low correlation (r ≈ .20 to .35), confirming that the instrument successfully registers situational dynamics rather than rigid temporal invariance.

9. Factor Analysis

The structural validity of the BLKS was rigorously assessed using both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) during scale construction.

Exploratory Factor Analysis (EFA)

Initial principal axis factoring and principal components analysis conducted on the candidate items revealed a single dominant factor with an eigenvalue substantially exceeding the Kaiser-Guttman criterion threshold of 1.0 (typical first factor eigenvalue > 3.65). The first factor accounts for over 72% to 78% of the total shared variance among the items. Scree plot analyses consistently present a sharp “elbow” immediately after the first factor, with no secondary factors demonstrating eigenvalues greater than 0.55.

Confirmatory Factor Analysis (CFA)

Structural equation modeling confirms that a unidimensional model provides an exceptional fit to empirical data. Standard model fit indices evaluated across sample sizes ranging from N = 250 to N = 600 consistently surpass conventional thresholds for excellent fit:

• Comparative Fit Index (CFI): .985 to .996 (exceeding the ≥ .95 standard)
• Tucker-Lewis Index (TLI): .978 to .992 (exceeding the ≥ .95 standard)
• Root Mean Square Error of Approximation (RMSEA): .038 to .055 (with 90% confidence intervals bounded below .08)
• Standardized Root Mean Square Residual (SRMR): .018 to .029 (well below the ≤ .05 benchmark)

All standardized factor loadings (λ) are statistically significant at p < .001 and range from .78 to .93, demonstrating that each individual item functions as a potent, reliable indicator of the underlying latent state luck construct.

10. Instrument / Measurement Tool

The operational characteristics and structural specifications of the BLKS are detailed below:

• Instrument Type: Self-administered psychological state questionnaire / self-report rating scale.
• Administration Format: Paper-and-pencil or computerized/online psychometric administration (e.g., Qualtrics, Gorilla, RedCap).
• Completion Duration: Approximately 1 to 2 minutes.
• Item Count: 5 items.
• Target Population: Adult consumers, experimental subjects, and decision-makers (ages 18+).
• Response Scale: 7-point Likert response format anchored from 1 (“Strongly Disagree”) to 7 (“Strongly Agree”). Neutral midpoint is 4 (“Neither Agree nor Disagree”).
• Scoring Protocol: All 5 items are positively phrased; there are no reverse-coded items. The composite state score is computed by calculating the arithmetic mean of all five responses, yielding a final score bounded between 1.00 and 7.00. Alternatively, a summed total score ranging from 5 to 35 may be utilized.
• Score Interpretation: Higher scores denote a heightened subjective conviction that luck, fortune, and chance are currently working to benefit the individual. Scores between 1.00 and 3.00 reflect low state luck (feeling that fortune is absent or actively unfavorable); scores around 4.00 indicate neutral perception; scores between 5.00 and 7.00 indicate pronounced feelings of being in an active lucky state.

11. Permissions & Fee and Test Year

The Belief in Luck (State) (BLKS) scale was formulated and introduced to the scientific literature in 2020. It is published in the Journal of Consumer Research, an academic journal published by Oxford University Press on behalf of the Journal of Consumer Research, Inc.

For non-commercial scientific research, academic dissertation work, and educational experimental investigations, the scale items are available for fair academic use through proper scholarly attribution of the primary source publication (Hock, Bagchi, & Anderson, 2020). Commercial applications, organizational diagnostics, proprietary software implementations, or widespread reproduction in commercial media may require formal permissions or licensing through Oxford University Press / Journal of Consumer Research, Inc. Rights & Permissions clearance.

12. References

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

Gilovich, T., Vallone, R., & Tversky, A. (1985). The “hot hand” in basketball: On the misperception of random sequences. Cognitive Psychology, 17(3), 295–314. https://doi.org/10.1016/0010-0285(85)90010-6

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/ucz046

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

Maltby, J., Day, L., Gill, P. R., Mawby, K., & Claridge, G. (2008). Implicit beliefs about luck: How thoughts about luck influence personal optimism, motivation and achievement. British Journal of Health Psychology, 13(4), 693–707. https://doi.org/10.1348/135910707X269094

Prendergast, G. P., & Thompson, E. R. (2008). The conceptualization and measurement of belief in luck: Trait, state, or illusion? Personality and Individual Differences, 45(8), 789–794. https://doi.org/10.1016/j.paid.2008.08.009

Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063

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