Customers’ Experienced Product Quality (CEPQ)

1. Abstract

The Customers' Experienced Product Quality (CEPQ) scale is a psychometrically validated, multidimensional instrument designed to evaluate post-consumption and post-purchase evaluations of tangible goods. Developed by Ramendra Roy Das Guru and Marcel Paulssen (2020), the instrument captures perceived product quality across eight fundamental first-order dimensions: aesthetics, durability, ease of use, features, materials, performance, reliability, and serviceability. Unlike traditional consumer evaluation metrics that conceptualize perceived quality either as a unidimensional global evaluation or as an aggregate of ad-hoc transactional attributes, the CEPQ operationalizes quality within a rigorous second-order structural framework. Each of the eight subscales is measured through three reflective indicator items (yielding a comprehensive 24-item battery), which are evaluated relative to reference-class products in the category using multi-point Likert or comparative rating scales. Crucially, the overall CEPQ index is specified as a formative second-order construct (type II or reflective-formative model), recognizing that the eight dimensions collectively define, construct, and determine experienced quality rather than merely reflecting an underlying global latent trait.

The scale was developed and empirically validated across multiple consumer durable goods categories in the United States, including passenger automobiles, dishwashers, consumer headphones, and tablet computers. Across calibration and cross-validation samples, the reflective first-order dimensions exhibited strong internal consistency (Cronbach's alpha ranging from .82 to .94; composite reliability values exceeding .85) and distinct convergent and discriminant validity confirmed via confirmatory factor analysis (CFA) and the heterotrait-monotrait ratio of correlations (HTMT < .85). Formative second-order weights revealed that the relative importance of individual quality dimensions adapts dynamically to specific product categories, providing product designers, brand managers, and consumer psychologists with diagnostic precision. The CEPQ resolves longstanding operationalization deficits in marketing research by providing a modular, category-agnostic instrument capable of predicting customer satisfaction, brand loyalty, and post-purchase behavioral intentions.

2. Keywords

Customers' Experienced Product Quality, CEPQ, perceived product quality, formative-reflective measurement, psychometrics, consumer behavior, post-purchase evaluation, product aesthetics, durability, scale validation

3. Authors

The Customers' Experienced Product Quality (CEPQ) scale was conceptualized, operationalized, and validated by scholars in marketing science and consumer psychology:

• Ramendra Roy Das Guru, Ph.D. — Assistant Professor of Marketing, Department of Marketing, Birla Institute of Technology and Science (BITS) Pilani, Pilani Campus, Rajasthan, India; and formerly affiliated with the Department of Marketing, University of Geneva, Geneva, Switzerland. Specialized in consumer satisfaction, product design perceptions, and structural equation modeling.
• Marcel Paulssen, Ph.D. — Chaired Professor of Marketing, Institute of Business Administration and Marketing, University of Geneva (Haute École d'Économie et de Gestion / Geneva School of Economics and Management), Geneva, Switzerland. Renowned scholar in quantitative marketing, customer loyalty, structural equation models, and psychometric measurement of customer relationship dynamics.

4. Purpose

Perceived product quality has long been recognized as a cornerstone of consumer decision-making, brand equity accumulation, and sustainable firm profitability. However, for decades, marketing literature and applied consumer research suffered from theoretical fragmentation and empirical ambiguity regarding how tangible product quality should be modeled and measured. Prior operationalizations frequently relied upon single-item measures of "overall quality," generic adjective checklists, or direct adaptations of service-oriented frameworks such as SERVQUAL, which fundamentally fail to capture the physical, structural, and operational reality of manufactured goods. Alternatively, researchers developed highly idiosyncratic, product-specific attribute lists (e.g., fuel efficiency for cars, battery run-time for electronics) that precluded comparative research across product categories and hindered generalized theoretical development.

The primary purpose of the CEPQ is to provide a standardized, category-independent, and theoretically exhaustive measurement tool that captures how consumers experience the intrinsic and extrinsic attributes of tangible products following real-world utilization. By utilizing generic product placeholders within the item phrasing (e.g., evaluating "[Product]" relative to market alternatives), the scale permits horizontal benchmarking across vastly disparate categories of durable consumer products, spanning mechanical appliances, consumer electronics, and complex transportation vehicles.

Beyond academic research, the CEPQ serves critical diagnostic purposes in commercial and managerial settings. In new product development (NPD) and consumer product engineering, design teams require actionable metrics to identify which specific physical dimensions underperform relative to key industry competitors. Because the CEPQ treats overall product quality as a formative composite of its eight constituent dimensions, it allows organizations to compute exact utility weights and partial regression coefficients. This enables firms to determine whether consumer dissatisfaction stems from tactile degradation (materials), functional deficits (performance), interface friction (ease of use), or operational failure (reliability). Consequently, capital expenditures and engineering interventions can be allocated with surgical precision to those specific dimensions that exert the largest statistical weight in shaping the overall perceived quality for a targeted product category.

5. Psychological Construct

The construct of Customers' Experienced Product Quality represents a multi-faceted cognitive and perceptual appraisal of a physical product's excellence, utility, and craftsmanship, formed through sensory interaction, functional deployment, and longitudinal ownership. Rooted in both classical industrial engineering concepts and cognitive consumer psychology, the CEPQ partitions experienced quality into eight discrete, theoretically grounded dimensions:

5.1. Aesthetics

Aesthetics pertains to the sensory, visual, tactile, and artistic pleasure elicited by the product's exterior design, contours, proportions, and stylistic finish. Grounded in psychological theories of design aesthetics, this dimension measures the immediate visceral and emotional appraisal of a product's physical appearance. For instance, in evaluating a modern tablet computer or luxury automobile, aesthetics captures the visual elegance, harmonious styling, modern look, and visual appeal relative to competitive market benchmarks.

5.2. Durability

Durability reflects the consumer's perception of the product's operational lifespan, robust physical construction, and resistance to structural degradation, wear, or catastrophic mechanical breakdown over extended periods of active utilization. It represents the temporal dimension of quality, addressing the consumer's psychological expectation of enduring longevity and structural integrity without premature structural exhaustion.

5.3. Ease of Use

Ease of use measures the cognitive ergonomics, usability, intuitive control architecture, and ergonomic convenience experienced when interacting with the product. Derived from ergonomic psychology and the Technology Acceptance Model (TAM), this dimension evaluates whether operational procedures are straightforward, whether menus and physical interfaces are frictionless, and how minimal the cognitive effort required is to execute product commands.

5.4. Features

Features refer to the secondary characteristics, supplemental capabilities, modern enhancements, and technical versatility that augment the product's core functional utility. This dimension gauges whether the product incorporates up-to-date technological options, versatile settings, and value-adding functional capabilities that extend its utility beyond standard baselines.

5.5. Materials

The materials dimension captures the haptic, tactile, and qualitative appraisal of the constituent physical substances used to fabricate the product, including metals, polymers, glass, textile upholsteries, and exterior coatings. Consumers derive substantial quality inferences from the density, finish, texture, and apparent premium nature of surface materials, distinguishing cheap, brittle plastics from substantial, finely finished compositions.

5.6. Performance

Performance reflects the fundamental, primary operational efficacy of the product in executing its core functional mandate. Grounded in functionalist consumer theory, performance measures the speed, mechanical or computational prowess, power output, and primary task accuracy of the item (e.g., the acoustic fidelity of headphones, the processing speed of a tablet, or the cleaning efficacy of a dishwasher).

5.7. Reliability

Reliability represents the probability of a product operating consistently, accurately, and without malfunctioning, crashing, or displaying unexpected faults throughout its day-to-day operation. While durability focuses on physical wear and long-term lifespan, reliability centers on operational consistency and freedom from frequent errors, glitches, or unexpected operational interruptions.

5.8. Serviceability

Serviceability captures the speed, convenience, accessibility, and economic or logistical ease of maintaining, repairing, or servicing the product when an issue arises. It incorporates the psychological peace of mind associated with straightforward servicing procedures, customer support accessibility, and the simplicity of obtaining replacements, diagnostics, or technical maintenance.

6. Theoretical Framework

The theoretical scaffolding of the CEPQ is deeply anchored in David A. Garvin's foundational operations and management framework (Garvin, 1984, 1987), which originally identified eight core dimensions of product quality: performance, features, reliability, conformance, durability, serviceability, aesthetics, and perceived quality. While Garvin's conceptualization revolutionized industrial quality management, it was predominantly normative, manufacturing-driven, and formulated from an engineering standpoint rather than derived from empirical psychometrics of consumer perception.

Das Guru and Paulssen modernized and restructured Garvin's typology through the lens of cognitive psychology and modern psychometric measurement theory. Specifically, they replaced technical engineering constructs such as "conformance" (which requires internal statistical process control data invisible to ordinary users) with consumer-accessible perceptual constructs such as materials and ease of use. Furthermore, they separated subjective evaluation dimensions from overarching summary judgments, eliminating the tautological inclusion of "perceived quality" as its own subdimension.

Central to the theoretical validity of the CEPQ is its specification as a formative second-order measurement model (type II: reflective first-order, formative second-order). Psychometric theory, as articulated by Bollen, Lennox, and Jarvis et al., establishes that when indicators or sub-dimensions define, induce, and constitute a higher-order concept rather than merely being manifested by it, the measurement relationship must be modeled formatively:

Where $\eta_{\text{CEPQ}}$ is the overarching formative index of experienced quality, $\xi_j$ represents each of the eight reflective first-order dimensions, $\gamma_j$ denotes the corresponding formative weight (relative contribution parameter), and $zeta$ represents the structural disturbance or error term capturing quality facets outside the eight specified dimensions. If quality were modeled reflectively at the second order, an increase in product aesthetics would mathematically necessitate a simultaneous, parallel increase in reliability, durability, and serviceability. In the physical realm of industrial manufacturing, this assumption is fundamentally invalid: a sports car can exhibit breath-taking aesthetics and exceptional engine performance while concurrently suffering from atrocious reliability and poor serviceability. By implementing a formative second-order structure, the CEPQ accurately mirrors the compensatory and non-compensatory trade-offs consumers make in the real world.

7. Validity

The CEPQ underwent rigorous empirical validation conforming to state-of-the-art scale development paradigms (Churchill, 1979; Gerbing & Anderson, 1988; MacKenzie et al., 2011). Empirical evidence spanning multiple product categories confirms its construct, convergent, discriminant, and predictive validity.

7.1. Construct and Convergent Validity

Construct validity was established through sequential exploratory factor analyses followed by multisample confirmatory factor analyses across distinct product classes (automobiles, dishwashers, headphones, and tablets). For all first-order reflective dimensions, standardized factor loadings consistently exceeded the strict .70 threshold (all $p < .001$), with the vast majority ranging between .78 and .92. The average variance extracted (AVE) for each of the eight first-order dimensions substantially surpassed the recommended .50 benchmark, demonstrating that the shared variance between indicators and their respective latent dimension exceeds measurement error variance.

7.2. Discriminant Validity

Discriminant validity among the eight first-order constructs was demonstrated using both the Fornell-Larcker criterion and the more rigorous heterotrait-monotrait ratio of correlations (HTMT). In all comparisons across product categories, the square root of the AVE for each latent construct exceeded its bivariate correlation with any other construct. Furthermore, HTMT values remained safely below the conservative threshold of .85, confirming that despite moderate inter-correlations, each dimension represents an empirically distinguishable facet of product experience.

7.3. Predictive and Nomological Validity

Nomological validity was verified by integrating the formative CEPQ index into broader structural equation models linking product quality to key downstream behavioral and attitudinal outcomes. The overall CEPQ index demonstrated strong, statistically significant predictive pathways to:

• Overall Customer Satisfaction (standardized $\beta$ ranging from .58 to .74, $p < .001$)
• Customer Delight (standardized $\beta$ ranging from .42 to .61, $p < .001$)
• Repurchase Intentions and Brand Loyalty (standardized $\beta$ ranging from .39 to .56, $p < .001$)
• Word-of-Mouth (WOM) Recommendations (standardized $\beta$ ranging from .45 to .68, $p < .001$)

Crucially, formative indicator weights ($\gamma_j$) varied meaningfully across categories in alignment with theoretical expectations. For example, for tablet computers, ease of use and performance exhibited the largest formative weights, whereas for major household appliances such as dishwashers, durability and reliability emerged as the primary determinants of the experienced quality index.

8. Reliability

The reliability of the reflective first-order subscales within the CEPQ was systematically evaluated using multiple statistical parameters across divergent product testing samples. High internal consistency was replicated across both consumer electronics and mechanical durables:

• Cronbach's Alpha ($\alpha$): Values for all eight three-item subscales routinely fell between .82 and .94, well above the conventional .70 heuristic for academic research and .80 for applied diagnostics. Specifically, across testing cohorts, alpha values were documented as: Aesthetics ($\alpha = .88 – .92$), Durability ($\alpha = .86 – .93$), Ease of Use ($\alpha = .85 – .91$), Features ($\alpha = .82 – .89$), Materials ($\alpha = .87 – .92$), Performance ($\alpha = .88 – .94$), Reliability ($\alpha = .89 – .94$), and Serviceability ($\alpha = .84 – .90$).
• Composite Reliability (CR): Raykov's composite reliability coefficients exceeded .86 across all dimensions in all product categories, indicating that error variances were minimal and item indicators accurately captured true score variance.
• Average Variance Extracted (AVE): AVE metrics for all first-order constructs consistently spanned .62 to .81, far eclipsing the .50 cutoff proposed by Fornell and Larcker.
• Multicollinearity Diagnostics for the Formative Index: Because reliability for formative constructs cannot be computed using traditional internal consistency metrics (since indicators need not correlate positively), multicollinearity was evaluated using Variance Inflation Factors (VIF). Across the empirical validation datasets, all first-order dimension VIF scores within the formative model remained below 2.5, well below the stringent ceiling of 3.3 (or the conventional threshold of 5.0), confirming that multicollinearity does not destabilize the formative regression weights.

9. Factor Analysis

The latent structure of the CEPQ was established through an exhaustive two-step factor analytic sequence, confirming an eight-factor lower-order reflective structure and a formative higher-order synthesis.

9.1. Exploratory Factor Analysis (EFA)

During initial scale purification, an exploratory factor analysis using Principal Axis Factoring with Promax oblique rotation was conducted on an expanded item pool. The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy consistently exceeded .91 across samples, and Bartlett's Test of Sphericity was highly significant ($p < .001$). The eigenvalues and scree plot unambiguously demonstrated an eight-factor solution explaining over 74% of the total variance. Items with factor cross-loadings greater than .30 or primary loadings below .60 were pruned, culminating in the optimal 24-item configuration (exactly 3 items per dimension).

9.2. Confirmatory Factor Analysis (CFA)

Subsequent validation via Confirmatory Factor Analysis using Maximum Likelihood estimation confirmed that the eight-factor reflective model provided an exceptional fit to empirical consumer data across multiple categories:

• Goodness-of-Fit Statistics: $\chi^2/\text{df} le 2.14$; Comparative Fit Index (CFI) $ge .96$; Tucker-Lewis Index (TLI) $ge .95$; Root Mean Square Error of Approximation (RMSEA) $le .048$ (with 90% confidence intervals spanning .039 to .057); Standardized Root Mean Square Residual (SRMR) $le .038$.
• Item Loadings: Standardized factor loadings across all 24 indicators were universally strong (all $lambda > .75$, $p < .0001$), confirming substantial shared variance among the three items allocated to each sub-dimension.

9.3. Formative Structural Specification

The second-order formative specification was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) and covariance-based SEM with appropriate MIMIC (Multiple Indicators and Multiple Causes) model specifications. The path coefficients from the eight first-order latent dimensions to the overall CEPQ latent variable demonstrated significant outer weights, affirming the formative conceptualization that these dimensions collectively construct the overall perception of product quality.

10. Instrument / Measurement Tool

• Instrument Name: Customers' Experienced Product Quality Scale (CEPQ)
• Measurement Paradigm: Multi-dimensional, category-agnostic psychometric inventory combining reflective first-order dimensions with a formative second-order index
• Administration Modality: Self-administered paper-and-pencil questionnaire, web-based survey, or mobile customer experience monitoring interface
• Target Population: Adult consumers (ages 18+) possessing direct ownership or extensive post-purchase operational experience with a specific tangible consumer durable good
• Total Item Count: 24 items (structured as 8 distinct subscales containing exactly 3 items each)
• First-Order Subscales (8):
  • Aesthetics (3 items)
  • Durability (3 items)
  • Ease of Use (3 items)
  • Features (3 items)
  • Materials (3 items)
  • Performance (3 items)
  • Reliability (3 items)
  • Serviceability (3 items)
• Response Scale: Typically scored on a 7-point Likert scale (ranging from 1 = "Strongly Disagree" to 7 = "Strongly Agree") or a 7-point relative comparative scale (ranging from 1 = "Much Worse than Comparable Products" to 7 = "Much Better than Comparable Products"), using explicit reference-class framing.
• Scoring Procedure:
  • First-Order Dimensional Scores: Calculated by taking the unweighted arithmetic mean of the three reflective indicator items for each respective subscale (scores range from 1.0 to 7.0 per dimension).
  • Overall CEPQ Index: Derived via partial least squares or structural equation modeling regression weights ($\gamma_j$), where the overall experienced quality score represents the weighted linear composite of the eight dimension scores: $\text{CEPQ} = \sum_{j=1}^{8} \gamma_j (\text{Dimension}_j)$. In practical industry applications, an unweighted composite or category-calibrated weighted mean can also be computed.
• Completion Time: Approximately 5 to 7 minutes for a full completion.

11. Permissions & Fee and Test Year

• Year of Initial Publication: 2020
• Copyright Holder: Emerald Publishing Limited and the scale authors (Ramendra Roy Das Guru and Marcel Paulssen).
• Access and Usage Rights: Academic and scholarly research use of the CEPQ is generally permitted without payment of royalty fees under fair dealing / fair use conventions, provided full academic attribution is rendered to the original authors and the European Journal of Marketing publication.
• Commercial Applications: Commercial use, integration into proprietary corporate customer satisfaction platforms, or enterprise-wide commercial diagnostic benchmarking may require licensing or formal permission from the copyright holders and publisher. Researchers and practitioners should consult Emerald Publishing or contact the authors for permission guidelines.

12. References

• Bollen, K., & Lennox, R. (1991). Conventional wisdom on measurement: A structural equation perspective. Psychological Bulletin, 110(2), 305–314. https://doi.org/10.1037/0033-2909.110.2.305
• Churchill, G. A., Jr. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16(1), 64–73. https://doi.org/10.1177/002224377901600110
• Das Guru, R. R., & Paulssen, M. (2020). Customers' experienced product quality: Scale development and validation. European Journal of Marketing, 54(4), 645–670. https://doi.org/10.1108/EJM-03-2018-0191
• Garvin, D. A. (1984). What does "product quality" really mean? Sloan Management Review, 26(1), 25–43.
• Garvin, D. A. (1987). Competing on the eight dimensions of quality. Harvard Business Review, 65(6), 101–109.
• Gerbing, D. W., & Anderson, J. C. (1988). An updated paradigm for scale development incorporating unidimensionality and its assessment. Journal of Marketing Research, 25(2), 186–192. https://doi.org/10.1177/002224378802500207
• Jarvis, C. B., MacKenzie, S. B., & Podsakoff, P. M. (2003). A critical review of construct indicators and measurement model misspecification in marketing and consumer research. Journal of Consumer Research, 30(2), 199–218. https://doi.org/10.1086/376806
• MacKenzie, S. B., Podsakoff, P. M., & Podsakoff, N. P. (2011). Construct measurement and validation procedures in MIS and behavioral research: Integrating new and existing techniques. MIS Quarterly, 35(2), 293–334. https://doi.org/10.2307/23044045
• Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 12–40.

13. Items of the Scale