TY - JOUR
T1 - Mix&Match
T2 - a resource-based complaint recovery framework for tangible compensation
AU - Stakhovych, Stanislav
AU - Tamaddoni, Ali
PY - 2020
Y1 - 2020
N2 - Resource exchange theory suggests service recovery compensation is optimal when it is commensurate with what was lost (e.g., refund for overcharging). However, in practice, companies cannot always follow the theory-driven prescriptions, and the complaint recovery literature remains silent on how to best recover in such suboptimal situations. This study takes a resource-based theory stance to propose Mix&Match, a complaint recovery framework for tangible compensation offers (refunds, redeliveries, or credits) to optimize customer retention and lifetime value in both optimal and suboptimal complaint recovery scenarios. We find that matching tangible compensation with the complaint cause (e.g., redelivery for expired products) is the most effective recovery response for improving customer retention and lifetime value. However, in suboptimal nonmatching scenarios, monetary compensation in the form of store credit proves to be the most effective response.
AB - Resource exchange theory suggests service recovery compensation is optimal when it is commensurate with what was lost (e.g., refund for overcharging). However, in practice, companies cannot always follow the theory-driven prescriptions, and the complaint recovery literature remains silent on how to best recover in such suboptimal situations. This study takes a resource-based theory stance to propose Mix&Match, a complaint recovery framework for tangible compensation offers (refunds, redeliveries, or credits) to optimize customer retention and lifetime value in both optimal and suboptimal complaint recovery scenarios. We find that matching tangible compensation with the complaint cause (e.g., redelivery for expired products) is the most effective recovery response for improving customer retention and lifetime value. However, in suboptimal nonmatching scenarios, monetary compensation in the form of store credit proves to be the most effective response.
KW - service failure
KW - customer complaints
KW - tangible compensation
KW - customer churn
KW - RLV
KW - customer base analysis
UR - http://www.scopus.com/inward/record.url?scp=85078124275&partnerID=8YFLogxK
U2 - 10.1177/1094670519898521
DO - 10.1177/1094670519898521
M3 - Article
AN - SCOPUS:85078124275
SN - 1094-6705
VL - 23
SP - 337
EP - 352
JO - Journal of Service Research
JF - Journal of Service Research
IS - 3
ER -