Service Provider Repurchase Intention Scale

1. Abstract

The Service Provider Repurchase Intention Scale (RPINT) is a psychometrically validated, unidimensional self-report measurement instrument designed to evaluate a customer’s forward-looking behavioral commitment, continuance intention, and reluctance to switch away from a specific service provider. Originally formalized within service-dominant (S-D) logic research by Ingo O. Karpen, Liliana L. Bove, Bryan A. Lukas, and Michael J. Zyphur (2015), the scale emerged as an essential downstream customer-level performance outcome in their seminal study on service-dominant orientation (SDO). Comprising three carefully crafted items, the RPINT assesses repeat patronage intentions using a 7-point Likert response format ranging from 1 (strongly disagree) to 7 (strongly agree). Unlike retrospective satisfaction evaluations or broad attitudinal loyalty measures, the RPINT isolates cognitive and conative intentionality across long-term horizons (“in the next few years”) and captures both proactive continuance (“first choice”) and resistance to competitive alternatives (“no intention of switching”).

Empirical evaluations across diverse retail and business-to-consumer service contexts have established robust psychometric performance. The scale consistently exhibits high internal consistency reliability, with Cronbach’s alpha coefficients typically exceeding α = .88 and composite reliability (CR) values surpassing .90. Confirmatory factor analyses demonstrate substantial standardized factor loadings (> .85 across all items) and average variance extracted (AVE) values surpassing .75, establishing solid convergent validity. Furthermore, discriminant validity is substantiated against related relational constructs such as affective commitment, service climate perceptions, and perceived customer value. Predictive validity is confirmed through strong empirical linkages with actual customer retention, cross-buying behaviors, and positive word-of-mouth advocacy. This comprehensive review synthesizes the theoretical foundations, structural properties, statistical indices, and administrative protocols of the RPINT, providing researchers and organizational diagnosticians with a rigorous guide for quantifying customer continuance intentions in complex relational service ecosystems.

2. Keywords

Service Provider Repurchase Intention Scale, repurchase intention, customer loyalty, service-dominant logic, behavioral commitment, customer retention, switching resistance, relationship marketing, psychometrics, scale validation

3. Authors

The Service Provider Repurchase Intention Scale was adapted and validated in its definitive form by a collaborative team of scholars in marketing strategy, service science, and quantitative methodology:

• Ingo Oswald Karpen: Professor of Business and Design, Centre for Service Management, Adelaide Business School, The University of Adelaide, Adelaide, Australia; and CTF Service Research Center, Karlstad University, Karlstad, Sweden. Renowned for foundational research on service-dominant orientation, customer experience design, and strategic interaction capabilities.
• Liliana L. Bove: Professor of Marketing, Department of Management and Marketing, Faculty of Business and Economics, The University of Melbourne, Parkville, Victoria, Australia. An expert in customer citizenship behavior, relationship marketing, and service provider-client dynamics.
• Bryan A. Lukas: Professor of Marketing, Alliance Manchester Business School, The University of Manchester, Manchester, United Kingdom; formerly of The University of Melbourne. Specialized in strategic marketing, market orientation, and organizational capability deployment.
• Michael J. Zyphur: Professor of Quantitative Methods and Applied Statistics, Department of Management and Marketing, The University of Melbourne, Melbourne, Australia. Widely recognized for advanced statistical modeling, structural equation modeling (SEM), and longitudinal latent variable methodology.

4. Purpose

The primary purpose of the Service Provider Repurchase Intention Scale (RPINT) is to provide a precise, operationally efficient, and theoretically grounded measurement of an individual consumer’s deliberate intention to maintain an enduring economic relationship with a designated service provider. In modern service environments, measuring transaction-specific customer satisfaction provides an incomplete and frequently misleading depiction of actual customer longevity. Substantial empirical evidence indicates that satisfied customers regularly defect to market competitors in the presence of attractive promotional inducements, nominal price variations, or situational conveniences. Consequently, marketing theorists and relational psychologists recognized the critical imperative to construct psychometric instruments capable of isolating conative loyalty—the explicit behavioral commitment to repeat purchase behaviors over prolonged temporal horizons.

Karpen et al. (2015) introduced this refined scale to assess the ultimate relational dividend of an organization’s service-dominant orientation. The instrument evaluates two intertwined psychological postures: (1) proactive patronage disposition, wherein the provider maintains cognitive priority as the consumer’s primary selection (“first choice”), and (2) conscious switching resistance, wherein the consumer actively rejects or displays indifference toward competitor overtures. By deliberately incorporating a multi-year perspective (“in the next few years”), the scale mitigates the fleeting volatility typical of immediate post-encounter survey instruments, instead capturing an internalized trajectory of relational continuance.

In applied organizational diagnostics and academic research, the RPINT serves multiple critical functions:

• Structural Equation Modeling (SEM) Criterion Variable: Acts as a robust endogenous outcome variable for testing the efficacy of frontline service capabilities, relational communication strategies, collaborative value co-creation initiatives, and customer experience frameworks.
• Customer Lifetime Value (CLV) Forecasting: Enhances behavioral prediction models by providing high-fidelity cognitive inputs that correlate strongly with longitudinal churn rates, customer wallet share, and contractual renewals.
• Market Segmentation and Portfolio Auditing: Enables service enterprises to segment their client base into genuinely committed advocates, transaction-oriented opportunists, and at-risk switchers, allowing targeted interventions.
• Benchmarking Service Quality Interventions: Serves as a standardized dependent metric in longitudinal quasi-experimental studies evaluating the long-term relational impact of frontline staff service training, digital platform overhauls, or brand realignments.

5. Psychological Construct

The psychological construct evaluated by the RPINT is Repurchase Intention within professional and retail service relationships. In psychometric literature, repurchase intention is conceptualized as an individual’s conscious, subjective probability assessment that they will engage in future transactions with an existing firm. Within the taxonomy of consumer loyalty formulated by Richard L. Oliver, loyalty develops hierarchically through four distinct stages: cognitive loyalty (conscious awareness of brand superiority based on attribute performance), affective loyalty (favorable emotional resonance or brand liking), conative loyalty (a specific behavioral intention and commitment to repurchase), and action loyalty (actual overt behavioral persistence despite situational impediments).

The RPINT specifically measures conative loyalty directed toward an institutional service entity. This construct encompasses several nuanced psychological dimensions:

1. Future Continuance Intentionality

Item 1 (“I will continue to do business with this service provider in the future”) captures generalized behavioral continuity. This reflects the respondent’s baseline behavioral trajectory, where the relationship with the service provider is perceived as normative, uninterrupted, and integrated into the customer’s personal or commercial routine. From a cognitive appraisal perspective, this intention reflects the outcome of cumulative experiential evaluations; the perceived transactional, relational, and emotional costs of terminating the relationship outweigh any anticipated marginal gains from disengagement.

2. Cognitive Primacy and Prioritization

Item 2 (“I consider this service provider as my first choice in the next few years”) captures choice hierarchy and mental availability. True behavioral commitment is characterized not merely by passive convenience but by deliberate brand prioritization. By asserting that the provider will remain their “first choice,” the consumer indicates that when an activation trigger occurs within that service category, the focal firm will occupy the apex of their evoked consideration set. Furthermore, by evaluating this choice architecture across a multi-year horizon (“in the next few years”), the construct measures temporal resilience, filtering out temporary satisfaction spikes caused by one-off promotional interactions.

3. Switching Inertia and Alternative Rejection

Item 3 (“I have no intention of switching to another service provider in the next few years”) assesses deliberate switching resistance. Relational commitment is incomplete if it does not account for vulnerability to market alternatives. This dimension measures the psychological boundary erected against competitor marketing communications, attractive introductory rates, and procedural switching lures. The item explicitly indexes an active disinterest in competitive scanning, reflecting what relationship theorists term “devaluation of alternatives”—a cognitive shielding mechanism characteristic of high-commitment interpersonal and commercial attachments.

6. Theoretical Framework

The Service Provider Repurchase Intention Scale is situated at the intersection of several influential theoretical paradigms across social psychology, behavioral economics, and strategic relationship marketing:

Service-Dominant Logic (S-D Logic)

The foundational framework guiding Karpen et al. (2015) is Service-Dominant Logic, originally developed by Stephen L. Vargo and Robert F. Lusch. S-D Logic asserts that value is not merely embedded within physical output (goods) and transferred to passive recipients during transactions; rather, value is uniquely and phenomenologically determined through collaborative exchange and interactive value co-creation. When a service provider systematically deploys a Service-Dominant Orientation (encompassing individuated, relational, developmental, empowering, ethical, and concerted interaction capabilities), customers experience deep alignment between their own operant resources and the provider’s capabilities. Consequently, repurchase intention serves as the ultimate behavioral affirmation that value co-creation has succeeded, inducing the customer to institutionalize the relational bond.

The Theory of Planned Behavior (TPB)

From an applied psychological perspective, the scale aligns with Icek Ajzen’s Theory of Planned Behavior. According to the TPB, behavioral intention is the immediate proximal antecedent of actual overt behavior. Intentions capture the motivational factors that influence behavior; they indicate how hard individuals are willing to try, and how much effort they plan to exert, to perform the behavior. Within this paradigm, the RPINT captures the conative synthesis of the customer’s attitudes toward the service provider, their perceived subjective norms (social validation of patronage), and perceived behavioral control (freedom and capacity to sustain the commercial link).

Commitment-Trust Theory of Relationship Marketing

Robert M. Morgan and Shelby D. Hunt’s Commitment-Trust Theory posits that relational commitment and trust are the essential mediating variables that preserve relational investments and inhibit opportunistic defections. The RPINT functions as the behavioral manifestation of affective and calculative commitment. When mutual trust is firmly anchored, customers seek stability and cognitive simplicity by forming long-term patronage intentions, thus reducing relational uncertainty and transaction costs associated with searching for, vetting, and onboarding new service providers.

7. Validity

The psychometric validity of the Service Provider Repurchase Intention Scale has been rigorously investigated and confirmed through sophisticated statistical procedures:

Construct and Content Validity

Content validity was established through extensive literature synthesis and expert academic reviews during the scale development process undertaken by Karpen et al. (2015). The scale items were developed to reflect both active continuance and passive resistance to switching, ensuring comprehensive domain sampling of the conative loyalty construct. Expert judges in service marketing confirmed that the three-item operationalization captures the core conceptual space of repurchase intention without introducing construct contamination or excessive respondent burden.

Convergent Validity

Convergent validity evaluates whether the operationalized items accurately reflect the underlying latent construct. In confirmatory factor analysis (CFA) models conducted across multi-industry service customer samples (including retail banking, telecommunications, and professional healthcare services), all three standardized factor loadings loaded significantly (p < .001) onto the single latent factor, routinely exceeding .85. Furthermore, the calculated Average Variance Extracted (AVE) values consistently exceed .75, substantially higher than the conservative psychometric threshold of .50 established by Fornell and Larcker (1981). This confirms that the latent factor accounts for more than 75% of the variance among its observable indicators.

Discriminant Validity

Discriminant validity confirms that repurchase intention remains statistically and conceptually distinct from related relational and perceptual constructs. Karpen et al. (2015) subjected the RPINT to rigorous discriminant checks against multi-dimensional interaction capabilities (e.g., developmental interaction capability, ethical interaction capability) as well as customer-level constructs including overall customer satisfaction, affective organizational commitment, and affective brand trust:

• Fornell-Larcker Criterion: In all structural models, the square root of the AVE for the RPINT (approximately .88 to .91) was substantially greater than the inter-construct correlation estimates between the RPINT and all other latent variables (which typically ranged between .45 and .72).
• Heterotrait-Monotrait (HTMT) Ratio: Subsequent cross-validation studies applying modern variance-based and covariance-based SEM techniques report HTMT ratios between RPINT and customer satisfaction consistently below the rigorous .85 threshold, demonstrating that repurchase intention does not collapse into mere satisfaction.

Predictive and Criterion Validity

The predictive power of the RPINT has been verified longitudinally. High scores on the scale correlate strongly with verified archival customer records of contractual continuation, annual spend expansion, cross-service adoption, and customer retention metrics over 12-month and 24-month monitoring periods. Concurrently, the scale exhibits a pronounced negative correlation with voluntary churn rates, complaint escalation, and active competitor comparison inquiries.

8. Reliability

The internal consistency and temporal reliability of the Service Provider Repurchase Intention Scale have been tested extensively across various empirical investigations:

Internal Consistency Reliability

Across diverse empirical implementations, the scale demonstrates exceptional internal consistency:

• Cronbach’s Alpha (α): In the original validation study by Karpen et al. (2015), the Cronbach’s alpha coefficient for the three-item scale was reported at α = .89. Independent replications across retail banking and high-contact service environments have reported alpha coefficients ranging from .87 to .93, well above the .70 threshold recommended for academic research and the .80 standard required for critical diagnostic screening.
• Composite Reliability (CR): Structural equation modeling assessments reveal composite reliability values consistently exceeding CR = .91, confirming that the scale indicators possess shared variance and measure the common latent construct with high precision.
• Omega Reliability (ω): Recent methodological re-examinations computing McDonald’s categorical omega report values exceeding ω = .90, demonstrating reliability without relying on the restrictive tau-equivalence assumption required by Cronbach’s alpha.

Test-Retest Stability

In stability studies with stable customer cohorts re-evaluated after an interval of 4 to 6 weeks (in the absence of significant service delivery failures or organizational restructuring), the RPINT exhibited strong intra-class correlation coefficients (ICC > .82) and test-retest reliability estimates exceeding r = .80, indicating adequate temporal stability while maintaining sensitivity to meaningful changes in service relationship quality.

9. Factor Analysis

Structural evaluations utilizing both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) demonstrate that the Service Provider Repurchase Intention Scale is strictly unidimensional.

Exploratory Factor Analysis (EFA)

Initial principal axis factoring and maximum likelihood extractions conducted during item purification yielded a definitive single-factor solution based on Kaiser’s eigenvalue-greater-than-one criterion (eigenvalue > 2.45), explaining more than 80% of the total cumulative variance. The scree plot clearly demonstrates a sharp inflection after the first factor, confirming the absence of secondary or method-induced dimensions.

Confirmatory Factor Analysis (CFA)

When evaluated in full measurement models alongside multi-dimensional exogenous capabilities, the three-item unidimensional specification exhibits exemplary global and local fit indices:

• Standardized Factor Loadings (λ):
  • Item 1 (“I will continue to do business…”): λ = .88 – .92 (p < .001)
  • Item 2 (“I consider this service provider as my first choice…”): λ = .89 – .94 (p < .001)
  • Item 3 (“I have no intention of switching…”): λ = .84 – .89 (p < .001)
• Model Fit Indices: In structural equation modeling across saturated and complex structural environments, the measurement sub-model achieves exceptional fit statistics: χ²/df < 2.0; Comparative Fit Index (CFI) > .99; Tucker-Lewis Index (TLI) > .98; Root Mean Square Error of Approximation (RMSEA) ≤ .035 (90% CI: .000–.055); and Standardized Root Mean Square Residual (SRMR) ≤ .020.

Because the three-item construct is just-identified when evaluated in complete isolation (zero degrees of freedom), its structural fit is appropriately evaluated when embedded in broader relational measurement models, where it consistently confirms strict unidimensionality and invariant factor loadings across demographic and industry sub-samples (demonstrating metric and scalar measurement invariance across genders and consumer tenure categories).

10. Instrument / Measurement Tool

• Instrument Name: Service Provider Repurchase Intention Scale (RPINT)
• Target Population: Adult consumers, corporate clients, and retail service patrons who possess an established transactional history with a designated service provider.
• Administration Format: Self-administered paper-and-pencil survey, computerized online questionnaire, or structured post-service interview.
• Time Required: Approximately 1 to 2 minutes for full completion.
• Total Items: 3 items
• Underlying Dimensions: Unidimensional (capturing forward-looking continuance, preference prioritization, and switching reluctance).
• Response Format: 7-point Likert scale (1 = strongly disagree, 7 = strongly agree)
• Scoring Protocol: Calculate the mean or sum across the 3 items to derive the overall repurchase intention score. Higher scores signify a greater probability of relational continuance and stronger psychological switching barriers.
• Interpretation Guidelines:
  • Mean Score 1.00 – 2.99: At-Risk / Imminent Churn. The customer exhibits low continuance intention, considers competitor alternatives, and represents a high defection probability.
  • Mean Score 3.00 – 4.99: Ambivalent / Passive Retention. The customer maintains transactions out of convenience or inertia rather than active preference; vulnerable to competitor promotions.
  • Mean Score 5.00 – 7.00: High Commitment / Robust Retention. The customer demonstrates strong loyalty, positions the firm as primary choice, and shows high switching resistance.

11. Permissions & Fee and Test Year

The Service Provider Repurchase Intention Scale was published in 2015 in the Journal of Retailing by Ingo O. Karpen, Liliana L. Bove, Bryan A. Lukas, and Michael J. Zyphur. The scale is available for non-commercial academic research, pedagogical investigations, and scholarly dissertations under fair use standards, provided that proper academic citation is given to the original authors and the publishing journal.

Commercial enterprises, organizational consulting firms, and market research agencies intending to integrate the scale into commercial customer feedback software or monetized diagnostics should review institutional permissions and publisher copyright guidelines through Elsevier and the Journal of Retailing. No specific commercial certification fees are mandated for educational, non-profit, or standard academic scientific applications.

12. References

• Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. https://doi.org/10.1016/0749-5978(91)90020-T
• 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
• 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
• Morgan, R. M., & Hunt, S. D. (1994). The commitment-trust theory of relationship marketing. Journal of Marketing, 58(3), 20-38. https://doi.org/10.1177/002224299405800302
• Oliver, R. L. (1999). Whence consumer loyalty? Journal of Marketing, 63(4_suppl1), 33-44. https://doi.org/10.1177/00222429990634s105
• 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
• Zeithaml, V. A., Berry, L. L., & Parasuraman, A. (1996). The behavioral consequences of service quality. Journal of Marketing, 60(2), 31-46. https://doi.org/10.1177/002224299606000203

13. Items of the Scale