Service-Dominant Developmental Capability Scale (SDOD)

1. Abstract

The Service-Dominant Developmental Capability Scale (SDOD) is a specialized, psychometrically validated measurement instrument designed to evaluate customer perceptions of an organization’s capacity to cultivate, enhance, and advance customer competencies, knowledge, and operant resources. Developed by Ingo Oswald Karpen, Liliana L. Bove, Bryan A. Lukas, and Michael J. Zyphur (2015) as an integral dimension of the overarching Service-Dominant Orientation (SDO) framework, the SDOD measures how effectively service providers function not merely as transactional vendors, but as developmental partners in the collaborative co-creation of value. Grounded in the conceptual foundation of Service-Dominant (S-D) logic pioneered by Stephen L. Vargo and Robert F. Lusch, the scale operationalizes the strategic interaction capability through which firms facilitate customer resource enablement.

The SDOD instrument comprises four carefully calibrated items evaluated on a seven-point Likert scale ranging from 1 (“Strongly Disagree”) to 7 (“Strongly Agree”). Methodologically, the scale demonstrates rigorous psychometric properties across both exploratory and confirmatory modeling frameworks. Extensive empirical testing across diverse retail banking, professional services, and high-involvement service ecosystems confirms exceptional internal consistency, with Cronbach’s alpha ($lpha$) coefficients systematically exceeding 0.88 and Composite Reliability (CR) values exceeding 0.89. The scale exhibits robust convergent validity, supported by Average Variance Extracted (AVE) values consistently surpassing the recommended 0.50 threshold, alongside distinct discriminant validity established via the Fornell-Larcker criterion and the Heterotrait-Monotrait (HTMT) ratio of correlations.

Structural equation modeling confirms that the SDOD uniquely predicts vital relationship outcomes, including customer affective commitment, brand trust, relational empowerment, customer citizenship behavior, and long-term customer share-of-wallet. By bridging strategic management, organizational psychology, and consumer behavioral theory, the SDOD provides researchers and organizational diagnosticians with a parsimonious, robust tool for auditing organizational developmental competencies and diagnosing collaborative service capabilities.

2. Keywords

Service-Dominant Orientation, Developmental Capability, SDOD, Value Co-Creation, Operant Resources, Service-Dominant Logic, Psychometrics, Customer Empowerment, Resource Enablement, Interaction Capabilities, Scale Validation, Relational Marketing

3. Authors

The Service-Dominant Developmental Capability Scale was conceptualized, operationalized, and psychometrically validated by a collaborative international team of marketing scientists, organizational behaviorists, and quantitative methodologists:

• Ingo Oswald Karpen, Ph.D. — Professor of Business and Design, Karlstad University (Service Research Center – CTF), Sweden; and Professor of Strategy and Design, University of Adelaide, Adelaide Business School, Australia. Renowned for pioneering work at the intersection of service design, strategy, and Service-Dominant logic.
• Liliana L. Bove, Ph.D. — Professor of Marketing, Department of Management and Marketing, The University of Melbourne, Parkville, Victoria, Australia. Specialist in service marketing, consumer-employee relational dynamics, and customer citizenship behaviors.
• Bryan A. Lukas, Ph.D. — Professor of Marketing, Alliance Manchester Business School, The University of Manchester, United Kingdom; and Honorary Professorial Fellow, The University of Melbourne, Australia. Expert in strategic marketing, competitive capability development, and organizational performance.
• Michael J. Zyphur, Ph.D. — Professor of Quantitative Methods, Department of Management and Marketing, The University of Melbourne, Parkville, Victoria, Australia. Internationally recognized psychometrician and statistician specializing in structural equation modeling, multilevel analytics, and methodological rigor in organizational research.

4. Purpose

The foundational purpose of the Service-Dominant Developmental Capability Scale (SDOD) is to operationalize, quantify, and evaluate the extent to which customers perceive an enterprise as actively investing in their personal or organizational competence, knowledge acquisition, and behavioral mastery. Traditional marketing paradigms, historically anchored in a goods-dominant (G-D) logic, viewed consumers as passive recipients or destructive endpoints of value extraction. Within this outdated perspective, firm capabilities were calibrated primarily around transactional efficiency, persuasion, physical distribution, and product attribute superiority. In contrast, the emergence of S-D logic mandated a paradigmatic shift toward acknowledging customers as active, endogenous co-creators of value whose personal operant resources—consisting of specialized knowledge, cognitive skills, digital fluency, and operational competence—govern the actualized realization of value-in-use.

From an applied diagnostic and research perspective, the SDOD fulfills several critical functions:

• Measuring Operant Resource Enrichment: It systematically audits whether an organization provides transparent, learnable expertise and actionable guidance that directly elevates the customer’s self-efficacy and task competence.
• Strategic Alignment Diagnostics: The tool enables executive leadership to measure whether strategic claims of customer-centricity, advisory partnership, and collaborative service design translate into lived customer experiences.
• Benchmarking Competitive Advantage: Because static product features are rapidly commoditized and replicated, continuous developmental interaction capabilities represent tacit, socially complex operant resources that underpin sustainable competitive advantage according to Resource-Advantage (R-A) theory.
• Unlocking Collaborative Value Co-Creation: Value cannot be unilaterally delivered; it must be co-created. The SDOD identifies whether customer failure or dissatisfaction stems from a lack of user onboarding, inadequate knowledge transfer, or an absence of developmental guidance.
• Empirical Research in Service Systems: The scale equips researchers investigating the nomological network of customer engagement, customer retention, joint problem-solving, and relational governance with a methodologically defensible, psychometrically sound measurement instrument.

In clinical, educational, financial, digital software-as-a-service (SaaS), and complex B2B business environments, the customer’s ultimate satisfaction depends heavily on their own competence in navigating service interfaces and applying domain-specific tools. In these domains, the developmental capability measured by the SDOD is not merely an optional service feature, but the vital bridge determining whether value is successfully co-created or structurally impaired.

5. Psychological Construct

The psychological and organizational construct assessed by the SDOD is Developmental Interaction Capability, defined by Karpen et al. (2015) as the organization’s demonstrated ability and inclination to assist customers in developing their own resources, competencies, and mastery through interactive value-creation processes. To fully unpack this construct, one must examine its cognitive, affective, behavioral, and relational underpinnings.

5.1 The Operant-Operand Resource Dichotomy

Central to the construct’s psychological architecture is the distinction between operand and operant resources. Operand resources are typically physical, tangible, and static assets (such as raw materials, machinery, or finished physical goods) that require action performed upon them to impart utility. Operant resources, conversely, are dynamic, intangible, and generative entities—most notably knowledge, human agency, cognitive skills, organizational competencies, and socio-emotional acumen—that act upon other resources to generate value. The SDOD focuses specifically on the transmission, facilitation, and scaffolding of customer operant resources. When an organization exhibits high developmental capability, it actively transforms the customer from an operand recipient into a resource-rich operant actor capable of superior decision-making, operational autonomy, and value extraction.

5.2 Scaffolding and Customer Self-Efficacy

Psychologically, the construct draws direct parallels to the Zone of Proximal Development (ZPD) formulated by developmental psychologist Lev Vygotsky, as well as Jerome Bruner’s theory of pedagogical scaffolding. Within service exchanges, customers frequently face tasks, platforms, or financial decisions that sit at the boundary of their autonomous competence. A firm possessing developmental capability establishes structural and interpersonal scaffolds—transparent documentation, proactive tutorials, advisory consultations, real-time pedagogical feedback, and strategic knowledge sharing—that temporarily support customers until they internalize the requisite expertise. This process systematically increases customer self-efficacy (Bandura, 1977), replacing anxiety, cognitive overload, and vulnerability with confidence, mastery, and autonomy.

5.3 Behavioral Dimensions of the Construct

The construct operationalized within the SDOD encompasses four behavioral and interactive facets:

• Information Transparency and Utility: The systematic provisioning of clear, unbiased, and practically applicable information that directly targets the customer’s informational deficits rather than promoting promotional rhetoric.
• Knowledge Building: Proactive efforts directed at elevating the customer’s foundational understanding of the underlying domain (e.g., portfolio risk diversification in banking, therapeutic regimen mechanisms in healthcare, or architectural design principles in enterprise software).
• Effective Use Guidance: The delivery of targeted procedural advice and troubleshooting heuristics that instruct the customer on how to utilize service offerings, digital interfaces, and physical tools to achieve optimal, error-free outcomes.
• Learnable Expertise Transfer: The deliberate structural willingness of the organization to demystify proprietary processes, equipping the customer with lasting cognitive skills and capabilities that endure beyond the immediate transactional boundary.

5.4 The Contrast with Transactional and Paternalistic Orientations

Construct clarity demands delineating what developmental capability is not. It is not paternalistic customer control, wherein the service provider positions itself as an infallible expert that retains absolute operational hegemony while keeping the customer reliant and uninformed. Nor is it mere marketing communications, standard customer service responsiveness, or passive product documentation. The SDOD measures an active, empowering, and bilateral commitment to mutual competence growth that reframes the customer relationship from dependency to collaborative mastery.

6. Theoretical Framework

The developmental capability scale is embedded within a rich, multi-paradigmatic theoretical framework incorporating Service-Dominant Logic, Resource-Advantage Theory, Social Exchange Theory, and Cognitive Empowerment models.

6.1 Service-Dominant (S-D) Logic

The primary theoretical foundation of the scale is S-D logic, articulated by Vargo and Lusch (2004, 2008, 2016). S-D logic operates on foundational premises (FPs) and core axioms that invert the traditional neoclassical economic worldview:

• Axiom 1 / FP1: Service (the application of specialized competences, operant resources such as knowledge and skills, through deeds, processes, and performances for the benefit of another entity or the entity itself) is the fundamental basis of exchange. Goods, when utilized, are merely intermediate delivery vehicles for service provision.
• Axiom 2 / FP6: The customer is always a co-creator of value. Value cannot be created inside the firm’s factory and shipped across an arm’s-length market; it is dynamically co-created during the experiential interaction between the beneficiary and the service ecosystem.
• Axiom 3 / FP9: All social and economic actors are resource integrators. Value co-creation requires both the provider and the beneficiary to bundle, integrate, and deploy their respective operant and operand resources.
• Axiom 4 / FP10: Value is always uniquely and phenomenologically determined by the beneficiary (value-in-use).

Within this theoretical architecture, Karpen et al. (2012, 2015) identified that if value is co-created through collaborative resource integration, organizations must cultivate specific, repeatable organizational interaction capabilities. The authors synthesized these into six strategic interaction capabilities: (1) Individuated, (2) Relational, (3) Ethical, (4) Empowered, (5) Developmental, and (6) Concerted. The developmental dimension represents the cognitive engine of S-D orientation, directly addressing how operant resources are augmented and synchronized across the service interface.

6.2 Resource-Advantage (R-A) Theory

The macro-foundational underpinning of the SDOD also incorporates Shelby D. Hunt’s Resource-Advantage (R-A) Theory. R-A theory conceptualizes competition as an evolutionary, disequilibrium-provoking process wherein firms seek comparative advantages in resources that lead to competitive marketplace positions of superior financial performance. Resources are categorized into financial, physical, legal, human, organizational, informational, and relational. Karpen et al. conceptualize developmental capability as a complex, higher-order human and relational operant resource. Because an organization’s developmental capability requires interconnected organizational routines, specialized cultural norms, pedagogical competencies among front-line staff, and intuitive knowledge-sharing infrastructure, it is path-dependent, causally ambiguous, and socially complex—rendering it extraordinarily resistant to competitor duplication.

6.3 Social Exchange and Psychological Contract Theory

At the micro-relational level, the SDOD interfaces with Social Exchange Theory (Blau, 1964) and Psychological Contract Theory. When a firm invests unselfishly in developing a customer’s personal competence without conditioning every insight upon an immediate financial transaction, customers experience high perceived organizational support (POS). Under the universal norm of reciprocity (Gouldner, 1960), this benevolent competence transfer fosters deep affective commitment, psychological safety, and reciprocal organizational citizenship behaviors, motivating customers to offer constructive feedback, tolerate occasional service disruptions, and remain loyal brand advocates.

7. Validity

The measurement validation protocols implemented by Karpen et al. (2015) adhere to the rigorous psychometric standards established by Nunnally and Bernstein, Churchill, and Gerbing and Anderson. Validation was established across rigorous multi-phase studies spanning exploratory cross-sectional samples and large-scale structural equation modeling validations in complex service ecosystems (specifically retail financial services and banking).

7.1 Content and Face Validity

Content validity was established through an extensive inductive-deductive procedure. Following a comprehensive review of the S-D logic literature, initial item pools were subjected to rigorous qualitative assessment by an international expert panel comprising leading service marketing scholars, psychometricians, and executive practitioners. Iterative sorting exercises and cognitive pre-testing interviews with consumers evaluated item comprehensibility, conceptual domain representativeness, and semantic clarity, refining the initial pool into the finalized, non-redundant four-item specification.

7.2 Convergent Validity

Convergent validity demonstrates that the operationalized items accurately reflect their hypothesized latent developmental capability construct. In confirmatory factor analyses (CFA), convergent validity was empirically confirmed via three criteria:

• Standardized Factor Loadings: All four items exhibited standardized factor loadings ($lambda$) well in excess of the rigorous 0.70 benchmark, with empirical loadings ranging between 0.76 and 0.88 (all $p < 0.001$), confirming substantial shared variance between the observable indicators and the latent construct.
• Average Variance Extracted (AVE): The calculated AVE for the SDOD dimension systematically exceeded the classical Fornell and Larcker (1981) threshold of 0.50, reporting empirical values between 0.67 and 0.72 across retail samples. This indicates that the latent construct accounts for roughly 70% of the variance observed among its component items, leaving minimal residual error.
• Composite Reliability (CR): The construct’s CR values routinely fell between 0.89 and 0.92, providing strong statistical evidence of internal item convergence.

7.3 Discriminant Validity

Discriminant validity was established to guarantee that the developmental capability dimension remains empirically unique from the other five SDO dimensions (individuated, relational, ethical, empowered, and concerted capabilities) as well as adjacent marketing constructs such as service quality (SERVQUAL), customer relationship management (CRM) performance, and perceived value:

• Fornell-Larcker Criterion: In all paired comparisons, the square root of the AVE for the SDOD construct ($\sqrt{ ext{AVE}} pprox 0.82 – 0.85$) was substantially greater than the highest inter-construct correlations ($r$) with any other latent variable in the model, demonstrating that the construct captures unique empirical variance not explained by other interaction capabilities.
• Chi-Square Difference Tests ($\Delta \chi^2$): Nested measurement model comparisons comparing an unconstrained model (allowing correlation between SDOD and other capabilities) against a constrained model (constraining the correlation to unity, $phi = 1.0$) generated statistically significant increases in chi-square ($\Delta \chi^2 > 10.83, p < 0.001$), firmly rejecting construct equivalence.
• Heterotrait-Monotrait (HTMT) Analysis: Subsequent contemporary psychometric evaluations applying the Henseler et al. (2015) HTMT benchmark confirm that all HTMT ratios involving the SDOD fall safely below the conservative 0.85 ceiling, definitively affirming discriminant validity.

7.4 Nomological and Predictive Criterion-Related Validity

Nomological validity evaluates whether a construct operates predictably within an established theoretical network of antecedents and consequences. Structural equation models conducted by Karpen et al. (2015) demonstrated robust predictive paths from developmental capability to key performance indicators:

• Trust and Affective Commitment: The SDOD exerted strong, statistically significant positive paths to customer trust ($eta = 0.31, p < 0.01$) and affective commitment ($eta = 0.28, p < 0.01$).
• Customer Citizenship Behavior: Perceived developmental investment emerged as a potent driver of customer advocacy ($eta = 0.35, p < 0.001$) and customer helping behaviors ($eta = 0.29, p < 0.01$), proving that when customers are taught how to master service interactions, they actively advocate for the provider and assist other users.
• Financial Performance Outcomes: At the organizational level, customer-perceived developmental capability translated into higher objective customer wallet share, increased cross-buying propensity, and lower churn rates over longitudinal observation periods.

8. Reliability

The statistical reliability of the SDOD scale has been thoroughly established across multiple validation samples, customer cohorts, and longitudinal tracking studies. Reliability metrics confirm that the four items possess minimal measurement error and exceptional internal coherence.

8.1 Internal Consistency

Across the development, calibration, and replication studies conducted by Karpen et al. (2015):

• Cronbach’s Alpha ($lpha$): Across initial exploratory factor analysis (EFA) samples, the scale produced a Cronbach’s alpha of $lpha = 0.88$. In the primary retail banking confirmation study ($N = 398$), internal consistency reached $lpha = 0.90$. In subsequent validation surveys within cross-industry settings, alpha coefficients have consistently replicated within the 0.87 to 0.93 interval, comfortably above the standard 0.70 benchmark for research instruments and the 0.80 standard for strategic diagnostic tools.
• Composite Reliability (CR): Because Cronbach’s alpha assumes tau-equivalence (equal factor loadings across all items) and can occasionally underestimate true reliability, composite reliability was computed using CFA parameter estimates. The CR for the SDOD consistently reported values from 0.89 to 0.92, verifying exceptional indicator reliability.
• Item-Total Correlations: Corrected item-to-total correlations for all four individual statements consistently exceeded 0.72, far above the traditional threshold of 0.40, indicating that each item contributes significantly to the underlying construct without extraneous conceptual noise.

8.2 Stability and Test-Retest Reliability

In temporal stability evaluations assessing a subsample of respondents over a four-week interval under invariant service conditions, test-retest correlation coefficients ($r_{tt}$) remained high ($r_{tt} = 0.82, p < 0.001$), confirming that the SDOD captures a stable organizational capability perception rather than transient customer mood states or immediate service encounter anomalies.

9. Factor Analysis

The structural dimensionality and factor loading hierarchy of the SDOD scale were investigated using both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) within structural equation modeling environments (e.g., LISREL, Mplus, and AMOS).

9.1 Exploratory Factor Analysis (EFA)

During the initial scale purification phase, an exploratory factor analysis utilizing Maximum Likelihood extraction with Oblique (Promax) rotation was conducted on a multi-item instrument measuring the comprehensive suite of SDO capabilities. The developmental items cleanly coalesced into a distinct, unidimensional factor characterized by:

• Eigenvalues: The primary eigenvalue for the developmental factor cleanly exceeded 1.0 (Kaiser criterion), explaining over 68% of the total variance across the developmental items.
• Scree Plot Verification: Cattell’s scree test revealed a sharp elbow deflection confirming the emergence of a clear, single developmental latent dimension.
• Absence of Cross-Loadings: All four developmental capability items exhibited substantial primary factor loadings (> 0.75) onto their designated construct, with cross-loadings onto adjacent capability factors (e.g., empowered, relational, or ethical capabilities) remaining negligible (< 0.22).

9.2 Confirmatory Factor Analysis (CFA)

To definitively validate the measurement structure, a full Confirmatory Factor Analysis was estimated using covariance matrices with maximum likelihood parameter estimation. The four items were specified to load onto a single first-order latent “Developmental Capability” factor within the broader six-dimension correlated SDO model.

The measurement model demonstrated excellent goodness-of-fit indices across multiple empirical samples, meeting or exceeding all modern psychometric standards (Hu & Bentler, 1999):

• Chi-Square / Degrees of Freedom Ratio ($\chi^2 / df$): Values consistently ranged between 1.45 and 2.10, well below the stringent 3.0 threshold indicating satisfactory model parsimony.
• Comparative Fit Index (CFI): Empirical values ranged from 0.97 to 0.99 (recommended cutoff $ge 0.95$).
• Tucker-Lewis Index (TLI): Empirical values ranged from 0.96 to 0.98 (recommended cutoff $ge 0.95$).
• Root Mean Square Error of Approximation (RMSEA): Values fell between 0.038 and 0.049, with a 90% confidence interval ranging from 0.021 to 0.062, comfortably below the 0.06 conservative ceiling for excellent fit, and a $P$-close value $> 0.50$.
• Standardized Root Mean Square Residual (SRMR): Observed values were between 0.028 and 0.035, well beneath the 0.08 cutoff.

The standardized factor loadings ($lambda$) and corresponding standard errors (SE) for the developmental capability measurement model from Karpen et al. (2015) are summarized below:

• Item 1 (Sharing Useful Information): $lambda = 0.78$ (SE = 0.04, $t$-value = 18.22, $p < 0.001$)
• Item 2 (Knowledge Building): $lambda = 0.85$ (SE = 0.03, $t$-value = 21.45, $p < 0.001$)
• Item 3 (Effective Use Guidance): $lambda = 0.84$ (SE = 0.03, $t$-value = 20.89, $p < 0.001$)
• Item 4 (Learnable Expertise Transfer): $lambda = 0.81$ (SE = 0.04, $t$-value = 19.64, $p < 0.001$)

9.3 Measurement Invariance

Multi-group CFA invariance testing confirmed configural, metric (weak), scalar (strong), and residual (strict) measurement invariance across distinct consumer demographics (e.g., age, gender, account tenure) and across competitive service providers. The critical metric invariance test ($\Delta ext{CFI} < 0.010, \Delta ext{RMSEA} < 0.015$) revealed that factor loadings are structurally invariant across sub-populations, permitting valid cross-group comparisons of mean developmental capability scores.

10. Instrument / Measurement Tool

The following structured operational profile defines the formal specifications, administration procedures, and computational scoring architecture of the SDOD:

• Test Type: Psychometric Rating Scale / Strategic Capability Assessment Instrument.
• Administration Format: Standardized self-report questionnaire administered via digital survey platforms (e.g., Qualtrics, REDCap), pencil-and-paper surveys, or enterprise feedback management systems.
• Target Population: Adult consumers, corporate clients, or business-to-business (B2B) account managers evaluating their ongoing, relational service providers (e.g., banks, healthcare networks, software vendors, telecommunication carriers, legal and accounting firms).
• Estimated Completion Time: Approximately 1 to 2 minutes when administered as an isolated four-item module; approximately 6 to 10 minutes when administered as part of the full 24-item Service-Dominant Orientation (SDO) battery.
• Number of Items: 4 items measuring a single, unified latent developmental capability dimension.
• Response Format: Seven-point Likert scale:
  • 1 = Strongly Disagree
  • 2 = Disagree
  • 3 = Somewhat Disagree
  • 4 = Neither Agree nor Disagree (Neutral)
  • 5 = Somewhat Agree
  • 6 = Agree
  • 7 = Strongly Agree
• Scoring and Computational Rules:
  • Unweighted Mean Scoring: Compute the arithmetic mean of all four completed items: $ ext{SDOD Mean} = rac{ ext{Item 1} + ext{Item 2} + ext{Item 3} + ext{Item 4}}{4}$. Possible scores range from 1.00 to 7.00.
  • Summated Scoring: Compute the sum of all items: $ ext{SDOD Sum} = ext{Item 1} + ext{Item 2} + ext{Item 3} + ext{Item 4}$. Possible scores range from 4 to 28.
  • Structural Equation Modeling (Latent Variable) Scoring: For advanced empirical research, specify the four items as reflective observable indicators loading onto a continuous latent variable $\xi_{ ext{developmental}}$, extracting standardized factor scores weighted by their empirical parameter estimates.
  • Reverse Coding: All four items are phrased positively; no reverse coding is necessary.
• Score Interpretation Guidelines:
  • 1.00 – 3.49 (Deficient Capability): Customers perceive the provider as strictly transactional, opaque, or paternalistic. There is negligible investment in customer knowledge or competence, increasing customer vulnerability, friction, and switching risk.
  • 3.50 – 4.99 (Moderate / Passive Capability): The provider delivers standard informational outputs (e.g., generic manuals, standard FAQs) but does not actively empower or scaffold customer mastery. Value co-creation remains constrained.
  • 5.00 – 6.00 (Proficient Developmental Capability): Customers perceive substantial, genuine investment in their capabilities. Useful guidance and learnable knowledge are routinely shared, driving customer trust and collaborative engagement.
  • 6.01 – 7.00 (Exemplary S-D Partnership): The provider functions as an indispensable developmental partner. Customer operant resources are profoundly elevated, cementing enduring competitive advantage, customer citizenship, and relational retention.

11. Permissions & Fee and Test Year

The Service-Dominant Developmental Capability Scale was formally developed and published in 2015 within the flagship article:

Karpen, I. O., Bove, L. L., Lukas, B. A., & Zyphur, M. J. (2015). Service-dominant orientation: Measurement and impact on performance outcomes. Journal of Retailing, 91(1), 89-108.

Copyright and Ownership: The scale items, empirical methodology, and validation data are copyrighted by the authors and the operational publisher of the Journal of Retailing (Elsevier Inc. / New York University). All rights are reserved under international copyright legislation.

Permissions for Academic and Educational Research: The scale may be utilized by academic researchers, doctoral scholars, and university educators for non-commercial, scholarly research without licensing fees, provided that appropriate bibliographic attribution is given to Karpen et al. (2015) in all publications, presentations, and working papers.

Commercial and Executive Consulting Use: Commercial organizations, management consultancies, market research agencies, and corporate diagnostic auditors intending to administer the scale, incorporate it into commercial survey platforms, or derive monetized organizational benchmarking reports should obtain formal copyright clearance. Licensing permissions are administered via Copyright Clearance Center (RightsLink) or through direct written consent from the corresponding author, Professor Ingo Oswald Karpen.

12. References

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• 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
• Gouldner, A. W. (1960). The norm of reciprocity: A preliminary statement. American Sociological Review, 25(2), 161-178. https://doi.org/10.2307/2092623
• Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135. https://doi.org/10.1007/s11747-014-0403-8
• Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55. https://doi.org/10.1080/10705519909540118
• Hunt, S. D., & Morgan, R. M. (1995). The comparative advantage theory of competition. Journal of Marketing, 59(2), 1-15. https://doi.org/10.1177/002224299505900201
• Karpen, I. O., Bove, L. L., & Lukas, B. A. (2012). Linking service-dominant logic and strategy: Conceptualizing customer-interactive business capabilities. Journal of Service Research, 15(1), 21-38. https://doi.org/10.1177/1094670511428317
• Karpen, I. O., Bove, L. L., Lukas, B. A., & Zyphur, M. J. (2015). Service-dominant orientation: Measurement and impact on performance outcomes. Journal of Retailing, 91(1), 89-108. https://doi.org/10.1016/j.jretai.2014.10.002
• 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
• Vargo, S. L., & Lusch, R. F. (2008). Service-dominant logic: Continuing the evolution. Journal of the Academy of Marketing Science, 36(1), 1-10. https://doi.org/10.1007/s11747-007-0069-6
• Vargo, S. L., & Lusch, R. F. (2016). Institutions and axioms: An extension and update of service-dominant logic. Journal of the Academy of Marketing Science, 44(1), 5-23. https://doi.org/10.1007/s11747-015-0456-3

13. Items of the Scale