Man vs machine: Relational and performance outcomes of technology utilization in small business CRM support capabilities. (9th April 2018) - Powell, Adam; Noble, Charles H.; Noble, Stephanie M.; Han, Sumin
Abstract : Purpose: The purpose of this paper is to examine the use of technology in customer relationship management (CRM) support capabilities by using an environmental contingency perspective. By examining the moderating effects of micro- and macro-environmental characteristics in which CRM support capabilities are used, the authors seek to extend the literature on CRM technology effectiveness in both customer commitment and overall firm performance. The authors also seek to advance managerial knowledge about CRM support capability technology utilization strategies in various market offering and dynamic market settings. Design/methodology/approach: The authors utilized a questionnaire to collect data from a sample of 276 small business CRM managers across a wide range of industries. Measures were adapted from the existing literature, and these were largely multiple-item measures of latent variables. The hypotheses were tested using a combination of Ridge regression and a bootstrapping test of mediation. In addition, residual centering was used to reduce multi-collinearity in the interaction analysis. Findings: The contingency/fit analysis performed in this research highlights the complex nature of the use of technology in CRM support capabilities. The benefits of a man vs a machine CRM support capability depend on the support function (whether marketing, sales, service, data access or data analysis), as well as upon the characteristics of the operating environment. Machine-based marketing support is positively related with customer commitment in turbulent markets, and machine-based service support is preferred in technologically turbulent markets. Sales support, on the other hand, is positively related to customer commitment in technologically turbulent markets when performed by man rather than machine. Practical implications: CRM support capabilities differ across firms and markets, thus a "one size fits all" approach is not appropriate. This research shows under what conditions a machine-based approach to CRM can be effective for small businesses. Originality/value: This research is the first to consider market offering and turbulence variables as moderators of the relationship between technology use in CRM support capabilities and customer commitment. Taking this contingency approach, the authors find that resource-based competitive advantage is obtainable based on the fit of the resources (e.g. CRM capabilities) to the environmental characteristics of the firm. Through this perspective that is unique to CRM research, the authors are able to provide both general and specific recommendations to managers and researchers.