infonet-economy

This study aims to examine the direct and moderating effects of generative learning on customer performance.

The authors test the relationships between CRM capabilities, generative learning, customer performance, and financial performance with a cross industry survey of CEOs and senior marketing executives from 199 firms. Partial Least Squares are used to estimate the parameters of the resulting model.

The results reveal that generative learning affects customer performance directly. Moreover, the interaction of CRM capabilities and generative learning contributes to customer performance. This finding suggests that firms need a well-developed generative learning orientation to fully benefit from translating new insights resulting from CRM capabilities into establishing, maintaining, and enhancing long-term associations with customers, and vice versa.

The main limitations are those that typically apply to cross-sectional-surveys. Although several steps were taken to reduce the concern of key informant bias and common method variance, dependent and independent variables were collected from the same source at a single moment in time.

Ceteris paribus, an increase of generative learning orientation by one unit (seven-point scale) can command an increase of up to 7% of the average customer performance due to its direct and interaction effect. Because even small changes in customer performance have a strong impact on financial performance, this finding indicates a remarkable and substantial result for managers.

Though previous research provides evidence of the adaptive learning consequences of CRM, a review of the literature reveals a lack of studies that analyze the importance of generative learning orientation for successful CRM.