Perceived after sales service quality: Communication within the service chain

Andi Mwegerano, Jarno Kankaaranta, Ossi Hämeenoja, Arho Suominen

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)

Abstract

Service quality in after sales is an important factor affecting competitiveness, it is important that the technical issues raised by authorized service vendors are resolved in time and that corrective actions are of good quality. Previous work on service quality has focused on the perceived quality experienced by the customer, leaving the service chain unstudied. This study focuses on examining the views and communication within the service chain of Nokia. Using the Nokia in-house database tool, which contains information on Nokia products, issue escalation and other customer-related activities, as empirical evidence Nokia service vendors in the field were approached questionnaire elaborating on the views and communication within the service chain. The survey results were analysed using two modelling techniques, namely ordinal logistic regression and the log-linear model. Ordinal logistic regression was used to establish a statistical association between perceived quality of corrective actions (QoCA) and the perceived quality of the description and additional information (QoDesAI) needed to portray the issue completely, as well as the perceived quality of time (QoT) spent to resolve the issues. The interaction between QoDesAI and QoT was analysed using the log-linear model. The results showed that the absolute case resolution time (CRT) was found to have no practical significance when evaluating perceived QoCA. In addition, managerial implications on how to achieve high perceived QoCA were suggested.

Original languageEnglish
Pages (from-to)407-419
Number of pages13
JournalQuality Technology and Quantitative Management
Volume9
Issue number4
DOIs
Publication statusPublished - Dec 2012
MoE publication typeA1 Journal article-refereed

Keywords

  • Customer
  • Issues
  • Log-linear model
  • Logistic regression
  • Perceived quality

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