Author List: Zablah, Alex R.; Bellenger, Danny N.; Straub, Detmar W.; Johnston, Wesley J.;
Information Systems Research, 2012, Volume 23, Issue 2, Page 418-435.
Extant research is equivocal about the organizational performance effects of customer relationship management (CRM) technology use, with some studies reporting positive effects and other studies reporting no effects at all. The present research effort posits that these mixed findings may potentially be explained by two factors: (1) CRM technology use may have different effects on different customers, and (2) different CRM tools may have different performance consequences. This study investigates this possibility by building on relationship marketing and management theory to propose and test a model of the customer- and firm-level consequences of the organizational use of CRM interaction support and customer prioritization tools. The results of data analysis of 295 customer firms nested within 10 provider firms reveal that firm use of CRM interaction support tools is positively related to customers' relationship perceptions, regardless of customer account size. In contrast, the data indicate that use of CRM prioritization tools appears to have positive effects on a firm's larger customers and negative effects on smaller customers. The results also suggest that when considered at an aggregate level, customer perceptions of the exchange relationship are predictive of organizational performance and that the association between these two variables is significant for larger customer accounts but insignificant for smaller accounts. Overall, the study's results help explain some of the inconsistent findings reported in the literature regarding the performance implications of CRM technology use and suggest that use of the technology may serve to enhance organizational performance, at least over the short term.
Keywords: CRM; CRM technology; customer relationship management; multilevel modeling; relationship investment; relationship marketing and management
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#285 0.132 effects effect research data studies empirical information literature different interaction analysis implications findings results important set large provide using paper
#93 0.108 performance results study impact research influence effects data higher efficiency effect significantly findings impacts empirical significant suggest outcomes better positive
#55 0.094 attributes credibility wikis tools wiki potential consequences gis potentially expectancy shaping exploring related anonymous attribute employing life comment comments 2.0
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#166 0.068 negative positive effect findings results effects blog suggest role blogs posts examined period relationship employees research employee bloggers reveal companies
#271 0.065 technology investments investment information firm firms profitability value performance impact data higher evidence diversification industry payoff return findings decisions greater