Energy Inference (ENINF)

Abstract

The Energy Inference (ENINF) scale is a psychometric instrument developed by Hean Tat Keh, Di Wang, and Li Yan (2021) to capture the extent to which consumers infer that a product provides functional, energy-enhancing benefits following exposure to imaginative marketing stimuli. Grounded in visual merchandising, cognitive psychology, and cue utilization theory, the instrument evaluates spontaneous consumer inferences regarding physical vitality, specifically measuring perceived power augmentation, endurance enhancement, and sustained activity maintenance. Comprising three sentence-completion items scored on a 7-point Likert scale, the ENINF scale operates as a unidimensional construct designed to quantify subtle, non-verbal cognitive inferences triggered by creative or metaphorical retail displays. Psychometric testing across laboratory and field experiments demonstrates robust internal consistency (Cronbach’s alpha frequently exceeding .88, composite reliability > .90), excellent construct validity, and strong convergent and discriminant validity against adjacent constructs such as visual aesthetic pleasure, novelty perception, and generalized product quality. Confirmatory factor analyses across diverse product categories, including functional beverages and consumer packaged goods, affirm a distinct unidimensional structure with robust factor loadings (> .80) and superior model fit indices (e.g., CFI > .98, RMSEA < .05). By serving as an empirical bridge between imaginative visual cues and consumer downstream behavioral intentions (such as purchase intentions and willingness to pay), the ENINF scale offers researchers and commercial strategists a focused, psychometrically rigorous instrument for diagnosing consumer functional inferences in modern retail environments.

Keywords

Energy Inference, ENINF, Product Benefit Perception, Visual Merchandising, Cue Utilization Theory, Consumer Psychology, Imaginative Displays, Retail Atmospherics, Functional Inferences, Psychometrics, Sensory Marketing, Purchase Intentions

Authors

The Energy Inference (ENINF) scale was developed by an international team of researchers in marketing, consumer behavior, and retail strategy:

• Hean Tat Keh — Professor of Marketing, Department of Marketing, Monash Business School, Monash University, Melbourne, Australia. Expert in services marketing, consumer decision-making, and retail management.
• Di Wang — Senior Lecturer / Associate Professor in Marketing, School of Advertising, Marketing and Public Relations, QUT Business School, Queensland University of Technology, Brisbane, Australia. Specializes in consumer psychology, retail atmospherics, and sensory branding.
• Li Yan — Associate Professor of Marketing, School of Business Administration, Capital University of Economics and Business, Beijing, China. Research focuses on visual marketing, behavioral economics, and consumer cognitive processing.

Correspondence regarding the original experimental application of the scale is typically addressed via Monash University or Queensland University of Technology institutional marketing faculties.

Purpose

The primary purpose of the Energy Inference (ENINF) scale is to empirically quantify the degree to which an individual deduces that a target consumer good will provide functional energy benefits, based purely or predominantly on visual, structural, or context-specific product representations. Traditional consumer evaluation models often assume that consumers assess product efficacy via direct informational cues, such as explicit nutritional labels, verbal claims, or quantitative dosage specifications. However, modern merchandising frequently relies on indirect, experiential, and non-verbal communications—such as imaginative displays, spatial configurations, and metaphoric visual arrangements (e.g., stacking beverage cans to resemble a dumbbell or an athletic figure). The ENINF scale addresses a critical methodological and theoretical void: measuring the implicit, functional inferences consumers generate when observing these creative retail arrangements.

In applied retail and sensory marketing research, the ENINF scale functions as a key explanatory mechanism (mediator). When retailers deploy creative visual merchandising, consumer responses can split between viewing the design as a mere aesthetic stunt (a “gimmick”) versus extracting meaningful, task-relevant product data. The ENINF scale isolates the cognitive pathway through which physical design elements are translated into functional product assessments. By measuring inferences of power, stamina, and activity maintenance, the instrument allows researchers to determine whether imaginative displays genuinely improve product value perceptions or merely generate superficial visual intrigue.

Beyond academic investigations of visual rhetoric and retail atmospherics, the scale provides actionable utility in commercial consumer testing, brand management, and functional food/beverage innovation. Marketers testing packaging prototypes, experiential point-of-purchase (POP) displays, or digital advertising layouts can deploy the ENINF to assess whether their non-verbal cues effectively signal physiological vitality. Clinically oriented health communication researchers and nutritional psychologists can also adapt the ENINF to study how front-of-package imagery inadvertently cues unverified physical energy expectations, contributing to our understanding of consumer dietary choices and health claim misinterpretations.

Psychological Construct

The psychological construct captured by the ENINF scale is defined as energy-enhancement inference: an inferential belief state wherein a consumer attributes positive physical and physiological performance characteristics to a product without explicit, analytical verification. Rather than reflecting an objective evaluation of physiological nutrients (such as adenosine triphosphate synthesis, caloric value, or caffeine content), energy inference represents an associative cognitive projection. It operates as an inferential belief formed through cognitive heuristics, sensory metaphor processing, and visual-to-functional transference.

The construct encompasses three closely related, complementary facets of vitality and dynamic performance:

• Power Enhancement: The inferred capacity of the product to augment physical strength, muscular force, or immediate dynamic output. For instance, when viewing an imaginative display built in the shape of weightlifting equipment, the consumer activates internal concepts related to strength, inferring that consuming the displayed product will directly potentiate their physical strength and power.
• Endurance Elevation: The inferred capability of the product to prolong stamina, resist fatigue, and enable sustained physical or mental exertion. This facet taps into temporal durability, reflecting an assumption that the product provides steady, long-lasting fuel rather than a transient, rapidly dissipating spike in arousal.
• Activity Maintenance: The inferred potential of the product to sustain continuous bodily movement, general vigor, and alertness throughout ongoing daily or athletic tasks. This facet reflects operational resilience—the belief that the item counteracts lethargy and preserves functional engagement across demanding activities.

Importantly, the ENINF construct is distinct from general product liking, perceived brand prestige, or hedonic aesthetic appreciation. A consumer may evaluate a visual display as highly attractive or artistic without necessarily inferring that the featured beverage will improve their muscular stamina. By focusing narrowly on energy-related functional inferences, the ENINF captures the cognitive conversion of form into functional expectation.

Theoretical Framework

The theoretical architecture underpinning the ENINF scale synthesizes several foundational models from cognitive psychology, semiotics, and marketing science:

Cue Utilization Theory

Originally formulated by Olson and Jacoby (1972), cue utilization theory posits that products present a complex array of informational cues that consumers categorize into intrinsic cues (inherent physical attributes of the product, such as taste, ingredients, or viscosity) and extrinsic cues (external characteristics, such as price, brand name, packaging, and display presentation). When intrinsic cues cannot be readily sampled prior to purchase, consumers systematically rely on extrinsic cues to infer unknown product qualities. The ENINF scale operationalizes the output of this inferential chain: the imaginative display serves as a salient extrinsic cue from which consumers draw diagnostic inferences about internal physical efficacy.

Conceptual Metaphor and Embodied Cognition

The scale relies heavily on conceptual metaphor theory (Lakoff & Johnson, 1980) and the principles of embodied cognition. Conceptual metaphor theory holds that abstract cognitive domains are routinely structured and understood in terms of concrete, sensorimotor experiences. When retail merchandise is arranged in an iconic or metaphoric silhouette—such as a muscular posture, an arrow, or sports equipment—it activates conceptual schemas associated with physical vigor, motion, and dynamism. Consumers intuitively map these active visual forms onto the internal properties of the merchandise, arriving at the inference that the product embodies dynamic energy.

Visual Rhetoric and Schema Congruity

Following McQuarrie and Mick’s (1996) framework of visual rhetoric in commercial communications, imaginative displays function as three-dimensional visual figures (tropes) that challenge typical cognitive expectations. Drawing upon Mandler’s (1982) schema incongruity theory, when an imaginative display introduces moderate visual incongruity (e.g., seeing beverage cans assembled into an engine or a barbell), consumers engage in elaborative cognitive processing to resolve the visual puzzle. Successful resolution of the visual trope allows the figurative meaning—potency, endurance, power—to be seamlessly transferred to the product itself, formalizing the energy inference that the ENINF measures.

Validity

Psychometric evaluation across the experimental investigations conducted by Keh, Wang, and Yan (2021) establishes extensive evidence for the construct, convergent, discriminant, and predictive validity of the ENINF scale:

Construct and Convergent Validity

Convergent validity evaluates whether the scale items that theoretically reflect energy inference correlate strongly with each other and converge on a single underlying construct. Across multiple experimental studies using distinct product categories (e.g., functional energy beverages, athletic nutritional supplements) and diverse display motifs (e.g., dumbbell-shaped displays versus traditional grid displays), the three items consistently demonstrate high, standardized factor loadings ranging from .82 to .94. In all empirical tests, the Average Variance Extracted (AVE) well exceeded the established .50 benchmark (Fornell & Larcker, 1981), typically recording values between .71 and .84, confirming substantial convergent validity.

Discriminant Validity

Discriminant validity was established by comparing ENINF with conceptually related yet theoretically distinct constructs, including:

• Display Novelty / Playfulness: The degree to which the retail arrangement is perceived as unique, surprising, or entertaining.
• Visual Aesthetic Appeal: Subjective ratings of beauty and visual elegance.
• General Product Quality: Standardized expectations regarding durability, packaging caliber, and premium composition.
• Brand Familiarity / Attitude: Prior affective orientation toward the manufacturer.

Using the Fornell-Larcker criterion, the square root of the AVE for the ENINF scale consistently exceeded the inter-construct correlations between ENINF and every competing construct. Additionally, evaluations utilizing the modern Heterotrait-Monotrait (HTMT) ratio of correlations confirmed that all values fell comfortably below the conservative threshold of .85, confirming that the ENINF scale captures a unique functional cognitive assessment rather than generic consumer enthusiasm or positive affect.

Predictive and Criterion Validity

The scale exhibits robust predictive validity. In structural equation modeling and moderated mediation analyses, ENINF scores served as a vital mediating mechanism linking exposure to imaginative displays with downstream consumer intentions. Specifically, higher ENINF scores significantly predicted increased purchase intention (with path coefficients consistently statistically significant at p < .001) and elevated willingness to pay a price premium. When experimental controls eliminated the metaphoric connection (e.g., using a product display shape unrelated to physical vitality), the mediating effect of ENINF was attenuated, illustrating that the instrument is sensitive to contextual changes in visual rhetoric.

Reliability

The reliability of the ENINF scale has been demonstrated across diverse experimental samples and visual merchandising contexts. The scale demonstrates high internal consistency across both laboratory experiments involving undergraduate participants and national online panels (e.g., Prolific, Amazon Mechanical Turk):

• Cronbach’s Alpha (α): Across the empirical studies reported by Keh et al. (2021), Cronbach’s alpha values for the three-item instrument ranged from .88 to .93, demonstrating high internal consistency across all testing conditions.
• Composite Reliability (CR): Structural equation modeling yielded Composite Reliability coefficients consistently between .89 and .94, safely above the widely accepted academic threshold of .70 (Bagozzi & Yi, 1988).
• Item-Total Correlations: Corrected item-to-total correlations for each of the three items consistently exceed .75, indicating that each sentence completion item contributes significantly to the measurement of the underlying construct without redundancy.

Although test-retest reliability was not the primary design parameter in cross-sectional between-subjects experiments, split-sample cross-validation procedures confirmed parameter stability across independent experimental cohorts. The instrument’s short, three-item design also minimizes participant fatigue, thereby reducing measurement error caused by inattention or careless responding.

Factor Analysis

The underlying factor structure of the ENINF scale was rigorously examined through both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA):

Exploratory Factor Analysis (EFA)

During initial scale validation, an unconstrained principal axis factoring procedure with oblique rotation was conducted on the pool of functional inference items. The mathematical extraction converged on a clear, single-factor solution. The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy exceeded .80, and Bartlett’s test of sphericity was highly significant (p < .001). A single factor accounted for more than 75% to 82% of the total variance across experimental samples, with no secondary factor achieving an eigenvalue above 0.60. All individual items displayed primary factor loadings exceeding .85, with negligible cross-loadings on non-target evaluation dimensions.

Confirmatory Factor Analysis (CFA)

To verify the unidimensional structure, structural equation modeling (SEM) with maximum likelihood estimation was conducted. The one-factor measurement model exhibited good fit across distinct experimental studies:

• Chi-Square / Degrees of Freedom (χ²/df): Ratios were consistently below 2.0 (often non-significant due to saturation with three indicators, or demonstrating excellent fit when evaluated within broader multi-construct measurement models).
• Comparative Fit Index (CFI): Values ranged from .985 to 1.000.
• Tucker-Lewis Index (TLI): Values consistently exceeded .975.
• Root Mean Square Error of Approximation (RMSEA): Coefficients remained below .05 (with 90% confidence intervals spanning .000 to .078).
• Standardized Root Mean Square Residual (SRMR): Observed values were consistently below .025.

Standardized parameter estimates for the three indicators were uniform, substantial, and statistically significant (p < .001), corroborating the theoretical assumption that power improvement, endurance enhancement, and sustained activity reflect a coherent latent psychological construct.

Instrument / Measurement Tool

The Energy Inference (ENINF) scale is administered as an explicit, self-report, sentence-completion instrument. The formal parameters of the tool are structured as follows:

• Instrument Type: Self-administered psychometric questionnaire (paper-and-pencil or computer-assisted personal interviewing / online survey platforms).
• Measurement Format: Sentence-completion technique consisting of an anchored common stem followed by three operational benefit completions.
• Item Count: 3 items.
• Target Domain: Consumer product inference, functional attribution, visual merchandising evaluation.
• Response Scale: 7-point Likert-type scale typically anchored from 1 (“Strongly Disagree”) to 7 (“Strongly Agree”). Neutral midpoint is anchored at 4 (“Neither Agree nor Disagree”).
• Scoring Protocol: All three items are positively keyed. The composite ENINF score is calculated by computing the unweighted arithmetic mean of the three completed items:
  ENINF Score = (Item 1 + Item 2 + Item 3) / 3
  Alternatively, latent factor scores generated through structural equation modeling can be used in complex path models. Higher average scores indicate stronger consumer inferences that the product enhances physical vitality, power, and sustained performance.
• Administration Time: Less than 60 seconds, making it ideal for experimental designs, field intercepts, or extensive multi-scale survey batteries.

Permissions & Fee and Test Year

The Energy Inference (ENINF) scale was formally introduced in 2021 in the following foundational publication:

Keh, H. T., Wang, D., & Yan, L. (2021). Gimmicky or effective? The effects of imaginative displays on customers’ purchase intentions. Journal of the Academy of Marketing Science, 49(1), 117–137.

Licensing and Usage: The scale items, theoretical framework, and psychometric documentation are published within the Journal of the Academy of Marketing Science (Springer Nature). The instrument is widely accessible for academic, educational, and non-commercial scientific research under standard academic fair-use guidelines, provided that full scholarly attribution is extended to the original authors. Researchers intending to incorporate the scale into proprietary commercial testing platforms, syndicated marketing audits, or profit-generating retail diagnostic software should ensure compliance with the publisher’s copyright policies and contact the lead authors regarding commercial deployment.

References

• Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94. https://doi.org/10.1007/BF02723327
• Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
• Keh, H. T., Wang, D., & Yan, L. (2021). Gimmicky or effective? The effects of imaginative displays on customers’ purchase intentions. Journal of the Academy of Marketing Science, 49(1), 117–137. https://doi.org/10.1007/s11747-020-00742-7
• Lakoff, G., & Johnson, M. (1980). Metaphors we live by. University of Chicago Press.
• Mandler, G. (1982). The structure of value: Accounting for taste. In M. S. Clark & S. T. Fiske (Eds.), Affect and cognition: The 17th annual Carnegie symposium on cognition (pp. 3–36). Lawrence Erlbaum Associates.
• McQuarrie, E. F., & Mick, D. G. (1996). Figures of rhetoric in advertising language: A elements of an aesthetic response. Journal of Consumer Research, 22(4), 424–438. https://doi.org/10.1086/209459
• Olson, J. C., & Jacoby, J. (1972). Cue utilization in the quality perception process. In S. V. Venkatesan (Ed.), Proceedings of the Third Annual Conference of the Association for Consumer Research (pp. 167–179). Association for Consumer Research.
• Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879

Items of the Scale