Customer satisfaction, trust and its influence on co-production and customer loyalty. A study that demonstrates the effects per online and offline channel type in a service context.

For over decades marketing literature focuses on customer satisfaction and its influence on customer loyalty and their effects on organizational profitability. Customers satisfaction still remains relevant in management strategy. A significant driver of customer satisfaction is the service that the customer receives. Nowadays, in order to compete through service, priority is given to the interaction between organizations and their customers. Organizations are trying to increasingly involve their customers in the service process, so called: co-production. Due to the rise of the Internet, organizations are facing challenges in serving their customers well, regardless of the chosen channel for using their services: online and offline (Van Bruggen et al., 2010; Shankar et al., 2011). To gain a better understanding of the relationship between organizations and their customers, including customer loyalty, co-production, trust and customer satisfaction, this research focuses on all influences. The results give a better understanding of the (unused) customer satisfaction potential and trust per online and offline channel and their influences on co-production and customer loyalty. Hereby managers are able to optimize their customer loyalty by making conscious choices in allocating their marketing efforts between customer satisfaction initiatives and loyalty programs (Shankar et al., 2010). This research is conducted in the social housing industry. The social housing industry is chosen to be representative to the services industry. In order to measure customer satisfaction, the 5C model of Hammerschmidt et al. (2015) is used. This model states that choice, charge, convenience, confidence and care are alignable satisfaction channel facets. The 5C model measures actual differences in customer satisfaction between online and offline channels which has already been validated in the retail industry. This research aims to test the generalizability of the 5C model to the services industry. To enrich the initial 5C model the influence of customer satisfaction on trust is measured. As an extension the influence of customer satisfaction and trust on both co-production and customer loyalty is measured as well. The results of the multi-group analysis gives insights in differences through online and offline users of social housing services. Data is gathered through a quantitative research approach using a questionnaire which is sent to 2.021 tenants from The results show a positive relation between customer satisfaction and trust. There is also a positive relation found between trust and co-production and between trust and customer loyalty. Co-production seems to positively influence customer loyalty as well. However, there is no positive relation found between customer satisfaction and co-production and between customer satisfaction and customer loyalty. The multi-group analysis is executed by using PLS-SEM and gives insights in significant differences for online and offline channels users. First, the multi-group analysis indicates that there is no significant relation between charge and customer satisfaction for the online group. Second, the multi-group analysis indicates that there is no relation found between choice and customer satisfaction for the online group. Third and finally, the multi-group analysis indicates that there is no relation between trust and co-production for the online group. This research makes great contributions to the literature. First, by applying the 5C model to the social housing industry we investigate its generalizability to other contexts. Second, to attempt to enrich the initial model the influence of customer satisfaction on trust will be measured as well. Third, the influence of customer satisfaction and trust on both co-production and customer loyalty is integrated. All results are shown in figure 1 below. The results of the multi-group analysis can be of practical use for managing satisfaction levels between its channels in a service context. These results give insight into the (unused) satisfaction potential across online and offline channels. This enables managers to make conscious choices about investing (more) time and money in a specific channel and facet. Therefore, the results are essential for managers to be able to create a good multichannel management strategy. of overall and attitudinal in a model. Results of this study shows that neither customer satisfaction nor attitudinal loyalty predict customer repurchase behavior. It is confirmed that overall satisfaction plays a mediating role in the relationship between transaction-specific satisfaction and attitudinal loyalty (Bodet, 2008) which is in line with and supports the study results of Jones and Suh (2000). In addition, results of the study of Auh et al. (2007) show no relationship between co-production and behavioral loyalty as well.