Customer Orientation Scale (Retail Manager-Rated) (CO-R)

1. Abstract

The Customer Orientation Scale (Retail Manager-Rated) (CO-R) is an established psychometric instrument adapted and operationalized by Christian Homburg, Wayne D. Hoyer, and Martin Fassnacht (2002) to evaluate the degree to which a decentralized retail store aligns its operational philosophy, resource deployment, and service delivery toward customer value creation. Stemming from the classical market orientation conceptualization introduced by Narver and Slater (1990), the CO-R tailors the customer orientation dimension specifically to store-level managerial assessment by embedding an explicit competitive comparison framing. The instrument measures three focal facets of retail customer orientation: relative managerial commitment to customers, organizational prioritization of customer value generation, and store-level depth of customer need comprehension.

Initially derived from a four-item pool, the scale was refined through rigorous item purification and confirmatory factor analysis (CFA), which resulted in a parsimonious, unidimensional, three-item structure after discarding an item addressing customer satisfaction objectives due to cross-loading and lower item-to-total correlation. Evaluated on a 7-point Likert scale ranging from 1 (“strongly disagree”) to 7 (“strongly agree”), the CO-R displays robust psychometric attributes, including high internal consistency reliability (Cronbach’s $\alpha$ exceeding .80, composite reliability exceeding .82), high average variance extracted (AVE > .60), and demonstrated convergent, discriminant, and criterion-related validities across diverse retail formats. By capturing comparative market-facing behaviors at the store manager level, the CO-R serves as a foundational metric in strategic marketing, retail management, organizational psychology, and service management research, predicting store-level service orientation, employee behavior, customer retention, and overall economic performance.

2. Keywords

Customer Orientation, Market Orientation, Retail Management, Store Manager Assessment, Psychometrics, Scale Validation, Competitive Framing, Customer Value Creation, Service Strategy, Homburg Hoyer Fassnacht

3. Authors

The Customer Orientation Scale (Retail Manager-Rated) was developed and validated within retail business units by a prominent group of academic marketing scholars:

• Christian Homburg, Ph.D.: Professor Emeritus of Marketing at the University of Mannheim, Germany, and Professorial Research Fellow at the Alliance Manchester Business School, University of Manchester, United Kingdom. Dr. Homburg is an internationally renowned authority on market-oriented management, customer relationship management, and business-to-business marketing strategy.
• Wayne D. Hoyer, Ph.D.: James L. Bayless/William S. Farish Fund Chair for Free Enterprise in the Department of Marketing at the McCombs School of Business, University of Texas at Austin, United States. Dr. Hoyer’s research spans consumer behavior, customer satisfaction, information processing, and service management dynamics.
• Martin Fassnacht, Ph.D.: Chair of Strategy and Marketing at WHU – Otto Beisheim School of Management, Vallendar/Düsseldorf, Germany. Dr. Fassnacht specializes in retail marketing, pricing strategy, brand management, and omnichannel distribution structures.

The scale was formally introduced in their seminal joint investigation published in the Journal of Marketing (2002), exploring the dimensions, structural antecedents, and organizational performance outcomes of service orientation within retail business strategies.

4. Purpose

The primary purpose of the Customer Orientation Scale (Retail Manager-Rated) (CO-R) is to provide an empirically validated, theoretically sound, and operationally parsimonious metric designed to assess the customer-centric strategic posture of individual retail units from the perspective of their unit managers. While organizational market orientation has historically been measured at corporate or strategic business unit (SBU) levels, contemporary retail management literature highlights that corporate strategic mandates frequently diverge from store-level execution. The CO-R was engineered to bridge this empirical and diagnostic gap by capturing how retail store managers actually implement and prioritize customer orientation in daily store operations relative to direct local market competitors.

Research Applications

In academic research, the CO-R fulfills several analytical objectives:

• Operationalization of Store-Level Strategy: Enables researchers to examine micro-foundational mechanisms through which retail chains execute organizational strategies across geographically dispersed, decentralized units.
• Mediation and Moderation Modeling: Serves as an antecedent, mediator, or moderator in complex structural equation models examining retail service climates, human resource architectures, frontline employee engagement, and store financial outcomes.
• Cross-Store and Cross-Banner Comparative Studies: Provides a standardized, benchmarked metric that controls for industry-wide baseline variations by evaluating customer orientation through a comparative competitor-anchored lens.

Managerial and Clinical/Organizational Diagnostic Applications

Within organizational diagnostics, organizational development, and applied retail consulting, the CO-R operates as an actionable benchmarking diagnostic tool. Store management plays a critical leadership role in shaping frontline customer interactions; hence, measuring a manager’s perceived orientation yields vital insights into:

• Strategic Alignment Audits: Quantifying the alignment between corporate headquarters’ espoused service philosophies and the actual perceived operational priorities at store level.
• Managerial Benchmarking and Store Auditing: Identifying underperforming stores within a retail chain whose management fails to achieve competitive parity in customer understanding and value creation.
• Leadership Training Needs Assessment: Directing interventions, leadership workshops, and incentive structures toward unit managers who report low levels of customer commitment relative to regional competitors.

5. Psychological Construct

The construct assessed by the CO-R is Store-Level Customer Orientation under a competitive benchmark. Within the broader framework of organizational behavior and managerial cognition, customer orientation represents an aspect of organizational culture and strategic philosophy that places the highest priority on the continuous creation of superior value for customers, while maintaining deep empathy and awareness of their evolving requirements.

Dimensions of the Construct

Although the CO-R is statistically unidimensional, it captures three interdependent behavioral and psychological dimensions essential to store-level execution:

1. Relative Customer Commitment

This facet assesses the psychological devotion, dedicated resource allocation, and sustained managerial intent directed toward customer welfare. Managerial commitment is reflected in an active willingness to sacrifice short-term tactical operational efficiencies (e.g., strict shelf-restocking quotas) in favor of long-term relationship preservation. In a competitive framing, it measures whether store leadership prioritizes customer advocacy significantly more than rival establishments operating within the same trading zone.

2. Dedication to Customer Value Creation

Drawing directly from the economic and psychological conceptualizations of perceived value, this dimension concerns managerial focus on generating benefits that exceed the non-monetary and monetary costs incurred by shoppers. At the store manager level, creating customer value encompasses store atmospheric design, frictionless checkout experiences, intelligent assortment management, and responsive problem resolution. It addresses whether store management proactively seeks creative avenues to elevate the utility customers derive from visiting the store rather than treating transactions as administrative routines.

3. Superior Understanding of Customer Needs

This cognitive dimension measures the extent to which the retail manager possesses, gathers, and synthesizes nuanced intelligence regarding the explicit preferences, implicit pain points, and emerging consumption habits of local shoppers. Effective understanding extends beyond static transactional data to include empathetic observation, empathetic listening by frontline staff, and real-time responsiveness to shopper feedback.

The Role of Competitive Comparison Framing

A critical psychometric hallmark of the CO-R is its explicit competitive anchoring: each item is framed “Relative to our competitors…”. Psychometricians and marketing theorists (e.g., Day, 1994; Homburg et al., 2002) emphasize that absolute ratings of customer orientation frequently suffer from pervasive social desirability bias and managerial ceiling effects (i.e., nearly all managers profess to love and understand their customers). By forcing the respondent to evaluate their store’s capabilities in contrast to direct local competitors, the scale activates comparative cognitive reference points, attenuating common response biases and enhancing criterion-related variance.

6. Theoretical Framework

The Customer Orientation Scale (Retail Manager-Rated) is grounded in several intersecting theoretical paradigms across strategic management, marketing theory, and organizational psychology.

1. Market Orientation Frameworks (Narver & Slater; Kohli & Jaworski)

The foundational underpinning of the CO-R rests on the seminal conceptualization of market orientation formalized by Narver and Slater (1990). In their seminal model, market orientation consists of three behavioral components: customer orientation, competitor orientation, and interfunctional coordination. Narver and Slater defined customer orientation as the comprehensive understanding of one’s target buyers throughout time to create continuous superior value for them. Similarly, Kohli and Jaworski (1990) characterized market orientation as organization-wide intelligence generation, intelligence dissemination, and responsiveness. Homburg, Hoyer, and Fassnacht (2002) adapted this framework to decentralized store environments, arguing that customer orientation cannot remain an abstract corporate culture; it must function as an operationalized micro-level capability embedded in store-level management.

2. The Resource-Based View (RBV) of the Firm

Under the Resource-Based View (RBV) of the firm (Barney, 1991; Wernerfelt, 1984), sustained competitive advantage stems from resources and capabilities that are valuable, rare, inimitable, and non-substitutable (VRIN). In retail environments, physical assets (e.g., fixtures, merchandise assortments, pricing models) are readily observed and duplicated by rivals. However, a deeply rooted customer-oriented strategic posture—embodied in a manager’s competitive commitment, value focus, and deep customer understanding—constitutes a socially complex, causally ambiguous dynamic capability. The CO-R directly operationalizes this rare behavioral capability as a source of market differentiation.

3. Service-Dominant (S-D) Logic and Service Climate Theory

The scale aligns with emerging paradigms of Service-Dominant Logic (Vargo & Lusch, 2004) and Organizational Climate Theory (Schneider, White, & Paul, 1998). Schneider’s Service Climate model postulates that the strategic priorities signaled by leadership dictate employee perceptions of expected, rewarded, and supported behaviors. When store managers exhibit high customer orientation, they cultivate a local store climate wherein frontline retail associates mirror those behaviors, fostering customer satisfaction, loyalty, and store profitability.

7. Validity

The psychometric integrity of the CO-R was systematically established by Homburg, Hoyer, and Fassnacht (2002) through rigorous field testing, item purification, and construct validation protocols across large-scale retail samples.

Content and Face Validity

Content validity was ensured by deriving the initial item battery directly from established, peer-reviewed market orientation operationalizations (most notably Narver & Slater, 1990; Deshpandé, Farley, & Webster, 1993). Draft items were subjected to pretesting with panels of experienced retail executives and academic experts in retailing and psychometrics. This screening refined item syntax, confirmed relevance to store operations, and affirmed that the comparative framing accurately reflected manager judgment without introducing semantic ambiguity.

Construct and Convergent Validity

Convergent validity was established using confirmatory factor analysis (CFA) within a maximum likelihood structural equation modeling environment. All standardized factor loadings ($lambda$) for the three indicators exceeded the conservative threshold of .70 ($p < .001$), demonstrating that each item captures a substantial proportion of shared construct variance. The average variance extracted (AVE) surpassed the recommended .50 benchmark (Fornell & Larcker, 1981), consistently demonstrating values above .60, which validates strong convergent validity at the latent level.

Discriminant Validity

Discriminant validity was established against related strategic retail dimensions, such as service offering breadth, service delivery quality, pricing aggressiveness, and competitor orientation. Utilizing the Fornell-Larcker criterion, the square root of the AVE for the CO-R exceeded its bivariate correlations with all other latent constructs in the structural model. Furthermore, nested model $\chi^2$ difference tests, wherein the inter-construct correlation was freely estimated versus constrained to unity ($phi = 1.0$), revealed significant $\chi^2$ deterioration under constraint ($p < .001$), establishing clear distinctiveness.

Predictive and Nomological Validity

Nomological validity was verified by testing structural paths within a comprehensive model of retail strategy. Store-level customer orientation positively and significantly predicted:

• Store-level service offering breadth and service proactive execution ($\gamma > .35, p < .01$).
• Frontline employee customer-directed responsiveness.
• Overall retail store performance, including customer retention, sales growth relative to competitors, and store operating profitability.

8. Reliability

The Customer Orientation Scale demonstrates high internal consistency and measurement stability across retail environments.

Internal Consistency Metrics

In the primary empirical validation by Homburg et al. (2002), the three-item CO-R demonstrated high internal consistency reliability:

• Cronbach’s Coefficient Alpha ($lpha$): Reported at .83, comfortably exceeding the standard academic benchmark of .70 suggested by Nunnally and Bernstein (1994) for established instruments.
• Composite Reliability (CR): Estimated via CFA factor loadings, yielding values typically between .83 and .86, confirming that measurement error is minimal across the indicator triad.
• Average Variance Extracted (AVE): Exceeded .62, indicating that over 62% of indicator variance is attributable to the underlying customer orientation latent variable rather than random measurement error.

Item Purification and Corrected Item-Total Correlations

During the developmental purification phase, an original four-item version was evaluated. The fourth item—“Our store sets customer satisfaction objectives”—exhibited a substantially lower corrected item-to-total correlation ($r_{it} < .45$) and cross-loaded onto administrative planning factors. Removal of this item increased Cronbach’s $lpha$ and solidified single-factor unidimensionality. Across all subsequent validation studies, corrected item-total correlations for the remaining three items exceeded .65.

9. Factor Analysis

The structural dimensionality of the CO-R was thoroughly scrutinized via Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA).

Exploratory Factor Analysis (EFA)

Initial EFA on the purified indicator battery yielded an unambiguous single-factor solution based on Kaiser-Guttman criteria (eigenvalue > 1.0) and scree plot inspections. The single latent factor accounted for over 72% of the total variance across items, with no secondary factors demonstrating eigenvalues above 0.50. The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy consistently exceeded .75, indicating well-conditioned covariance structures.

Confirmatory Factor Analysis (CFA)

In full structural equation modeling assessments using maximum likelihood estimation, the three-item unidimensional customer orientation construct exhibited robust fit indices across multiple validation samples. As a three-indicator single-factor measurement model is just-identified (zero degrees of freedom: $df = 0$), empirical fit was evaluated within the broader measurement model incorporating companion retail strategy constructs:

• Standardized Factor Loadings ($lambda$):
  • Item 1 (Relative commitment): $lambda = .78 – .82$ ($t > 15.0, p < .001$)
  • Item 2 (Relative focus on creating value): $lambda = .84 – .88$ ($t > 18.0, p < .001$)
  • Item 3 (Relative understanding of needs): $lambda = .74 – .79$ ($t > 14.0, p < .001$)
• Overall Measurement Model Fit:
  • $\chi^2 / df$ ratio < 2.0
  • Comparative Fit Index (CFI) $ge .96$
  • Tucker-Lewis Index (TLI) $ge .95$
  • Root Mean Square Error of Approximation (RMSEA) $le .048$
  • Standardized Root Mean Square Residual (SRMR) $le .035$

These empirical findings confirm that the three items converge on a single, coherent latent construct representing store-level competitive customer orientation.

10. Instrument / Measurement Tool

• Instrument Name: Customer Orientation Scale (Retail Manager-Rated) (CO-R)
• Primary Author Citation: Homburg, C., Hoyer, W. D., & Fassnacht, M. (2002)
• Assessment Type: Self-administered survey / Key informant organizational assessment
• Target Respondent: Retail Store Managers, Assistant Store Managers, or Unit Directors
• Level of Measurement: Decentralized retail store / Business unit level
• Number of Items: 3 items (unidimensional)
• Response Scale: 7-point Likert scale (1 = strongly disagree to 7 = strongly agree)
• Anchor Labels:
  • 1 = Strongly disagree
  • 2 = Disagree
  • 3 = Somewhat disagree
  • 4 = Neither agree nor disagree
  • 5 = Somewhat agree
  • 6 = Agree
  • 7 = Strongly agree
• Scoring Protocol: All three items are positively worded. Scoring is computed as the arithmetic mean across the three items:
  $$\text{CO-R Score} = \frac{\text{Item}_1 + \text{Item}_2 + \text{Item}_3}{3}$$
  Resulting scores range from 1.00 to 7.00, where higher composite scores represent a superior customer orientation relative to competitors.
• Administration Time: Less than 2 minutes.

11. Permissions & Fee and Test Year

• Publication Year: 2002
• Original Copyright Holders: American Marketing Association (AMA) / Authors (Christian Homburg, Wayne D. Hoyer, Martin Fassnacht)
• Access and Usage Rights: The scale was published in an academic research context within the Journal of Marketing. Under conventional scholarly and fair use doctrines, the scale items may be utilized, adapted, and administered without licensing fees for non-commercial, academic, thesis, and educational research, provided proper attribution is given to Homburg et al. (2002).
• Commercial Applications: Commercial organizations, proprietary consulting platforms, and corporate audit programs intending to use the scale within commercial diagnostic assessments should consult the publisher’s guidelines or secure formal permissions through the Copyright Clearance Center (CCC) or the American Marketing Association.

12. References

• Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. https://doi.org/10.1177/014920639101700108
• Day, G. S. (1994). The capabilities of market-driven organizations. Journal of Marketing, 58(4), 37–52. https://doi.org/10.1177/002224299405800404
• Deshpandé, R., Farley, J. U., & Webster, F. E. (1993). Corporate culture, customer orientation, and innovativeness in Japanese firms: A quadrad analysis. Journal of Marketing, 57(1), 23–37. https://doi.org/10.1177/002224299305700102
• 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
• Homburg, C., Hoyer, W. D., & Fassnacht, M. (2002). Service orientation of a retailer’s business strategy: Dimensions, antecedents, and performance outcomes. Journal of Marketing, 66(4), 86–101. https://doi.org/10.1509/jmkg.66.4.86.18511
• Homburg, C., & Pflesser, C. (2000). A multiple-layer model of market-oriented organizational culture: Measurement issues and performance outcomes. Journal of Marketing Research, 37(4), 449–462. https://doi.org/10.1509/jmkr.37.4.449.18786
• Kohli, A. K., & Jaworski, B. J. (1990). Market orientation: The construct, research propositions, and managerial implications. Journal of Marketing, 54(2), 1–18. https://doi.org/10.1177/002224299005400201
• Narver, J. C., & Slater, S. F. (1990). The effect of a market orientation on business profitability. Journal of Marketing, 54(4), 20–35. https://doi.org/10.1177/002224299005400403
• Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric Theory (3rd ed.). McGraw-Hill.
• Schneider, B., White, S. S., & Paul, M. C. (1998). Linking service climate and customer perceptions of service quality: Test of a causal model. Journal of Applied Psychology, 83(2), 150–163. https://doi.org/10.1037/0021-9010.83.2.150
• Vargo, S. L., & Lusch, R. F. (2004). Evolving to a new dominant logic for marketing. Journal of Marketing, 68(1), 1–17. https://doi.org/10.1509/jmkg.68.1.1.24036

13. Items of the Scale