Table 1

Taxonomy of the literature review and research gaps

LiteratureCiteDescription: key topicResearch gapContribution of this study
1) Return policy, product replacement and customer outcomesBonifield et al. (2010) Customers' perceived quality of e-tailers moderates the impact of return leniency on perceived purchase riskUnderstanding how stockouts during service recovery impact customers' perceived fairness, and retail SCs address the challenges of a lenient return policy with high service recovery standards in the context of product replacementWe introduce SCR as the capability to support a returns management program in the case of a stockout during product replacement
Bower and Maxham (2012) Return shipping costs negatively impact customers' perceived fairness of product return process
Confente et al. (2021) Return policy leniency mitigates customers' perceived risk for remanufactured products for both online and brick-and-mortar retail channels
Hjort and Lantz (2016) Return policy leniency improve repeat customers' spending but reduces firm's profit in the long run
Janakiraman et al. (2016) Return policy leniency improves customers' outcomes, stimulating purchases and decreasing the return hassle
Mollenkopf et al. (2007) Customers' return service experience influences perceived fairness and customers' outcomes
Shang et al. (2019) Retailers benefit from customizing the return policy leniency based on product maturity and variety to impact return and exchange likelihood
2) Service recovery and justice theoryAndreassen (2000) The perceived performance of service recovery impacts customer satisfactionDistinguishing service recovery dimensions that represent, in fact, a distinct theoretical construct and understand the impact on customers' perceived fairness of the process and interactions with the retailerWe theorize service recovery at a more granular level to assess the key role of an inherent SC capability – resilience – on addressing the challenges of the service recovery process. We empirically test the impact of service recovery resilience on customers' outcomes
Collier and Bienstock (2006) Interactive, procedural and outcome fairness constitute the e-service recovery three second-order dimensions
Craighead et al. (2004) Service recovery techniques vary in their effectiveness to address different types of service failures
Gu and Ye (2014) The impact of online management responses is greater among low satisfaction customers when experiencing service recovery
Holloway and Beatty (2003) Managing customer expectations of online service recovery affects how they perceive the service failures
Kau and Loh (2006) Customer satisfaction and purchasing behaviors are affected by perceived justice in service recovery
Lin et al. (2011) Perceived justice differently impacts customer outcomes and the service recovery paradox
Maxham III (2001) The level of provided service recovery affects customer outcomes
Roggeveen et al. (2012) Customers' co-creation in service recovery positively affects outcomes with higher service failure severity
Zhu et al. (2004) Resource allocation on service recovery depends on customers' risk profiles and firms' cost structure
3) Measurements of service recoveryAkinci et al. (2010) Assessed and refined E-S-Qual and E-RecS-Qual in bank service settingsExisting service recovery scales do not adhere to service recovery in SCM processesProvide a measurement scale to capture perceived service recovery resilience efforts in SCM
Parasuraman et al. (2005) Developed E-S-Qual and E-RecS-Qual scales
Peinkofer et al. (2022) Adapted service recovery dimensions to SCM context
Sajjanit and Rompho (2019) Conceptualized and developed a measure for customer-oriented product returns service

or Create an Account

Close Modal
Close Modal