TY - JOUR
T1 - Synchronizing relational benefits with customer commitment profiles
AU - FATIMA, Johra
AU - Di Mascio, Rita
PY - 2020/5/18
Y1 - 2020/5/18
N2 - The literature no longer considers commitment to be a distinct variable. Instead, commitment represents a combination of affective, calculative, and normative dimensions for individual customers, resulting in the adoption of a person-centric view for its measurement. However, customer satisfaction as a result of confidence benefit, social benefit, and special treatment benefit may vary among customers with different commitment profiles which encourages variable-centric view. Considering both variable- and person-centric views, this study uses survey data to examine the impact of relational benefits on the satisfaction of customers with different commitment profiles. It also examines the moderation role of relationship age. With cluster analysis identifying three commitment profiles, findings from structural equation modeling confirmed that highly-committed customers expected excessive special treatment benefit; low-commitment customers preferred confidence benefit to reduce cognitive dissonance; while affective dominance customers expected all three types of benefit proportionately. The study’s theoretical and practical contributions conclude the paper.
AB - The literature no longer considers commitment to be a distinct variable. Instead, commitment represents a combination of affective, calculative, and normative dimensions for individual customers, resulting in the adoption of a person-centric view for its measurement. However, customer satisfaction as a result of confidence benefit, social benefit, and special treatment benefit may vary among customers with different commitment profiles which encourages variable-centric view. Considering both variable- and person-centric views, this study uses survey data to examine the impact of relational benefits on the satisfaction of customers with different commitment profiles. It also examines the moderation role of relationship age. With cluster analysis identifying three commitment profiles, findings from structural equation modeling confirmed that highly-committed customers expected excessive special treatment benefit; low-commitment customers preferred confidence benefit to reduce cognitive dissonance; while affective dominance customers expected all three types of benefit proportionately. The study’s theoretical and practical contributions conclude the paper.
KW - cluster analysis
KW - Commitment
KW - customer satisfaction
KW - relational benefits
KW - structural equation modeling
UR - https://www.tandfonline.com/doi/full/10.1080/0965254X.2019.1619089
UR - http://www.scopus.com/inward/record.url?scp=85066875742&partnerID=8YFLogxK
UR - http://www.mendeley.com/research/synchronizing-relational-benefits-customer-commitment-profiles
U2 - 10.1080/0965254X.2019.1619089
DO - 10.1080/0965254X.2019.1619089
M3 - Article
VL - 28
SP - 366
EP - 378
JO - Journal of Strategic Marketing
JF - Journal of Strategic Marketing
SN - 0965-254X
IS - 4
ER -