Managerial Discretion and E-CRM Performance

Managerial Discretion and E-CRM Performance

Tim Coltman (University of Wollongong, Australia)
DOI: 10.4018/978-1-60566-154-4.ch003
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Most sectors of industry, commerce, and government have reported variation in the performance payoff from electronic customer relationship management (e-CRM). In this paper we build on a surprisingly sparse literature regarding the importance of managerial discretion, to show that the heterogeneity of beliefs held by managers about e-CRM execution matter when explaining e-CRM success. Drawing on a data sample comprising 50 interviews and 293 survey responses we utilise segmentation techniques to identify significant differences in managerial beliefs and then associate these belief segments with e- CRM performance. Results indicate that three distinct types of managers can be identified based on the heterogeneity of their e-CRM beliefs: (1) mindfully optimistic, (2) mindfully realistic, and (3) mindfully pessimistic. Further, our results imply that there are far less homogeneity at the individual firm level than is normally assumed in the literature, and that heterogeneity in managerial beliefs is systematically associated with organisational performance. Finally, these results serve to remind practitioners that e-CRM performance is dependent upon the right balance between managerial optimism and realism.
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Variation in the degree of business success has been attributed to the importance of the customer and the competitive advantages associated with a market orientation (Rust et al. 2000). One view of market orientation defines it as the ability to systematically gather and analyse customer and competitor information, to share this market knowledge, and then to use this knowledge to guide strategy recognition, understanding, creation, selection, implementation and modification (Hunt & Morgan 1995). It should also come as no surprise that many marketers have turned to information technology─in particular customer relationship management (CRM)─as a way to support customer-oriented thinking, customer analysis and understanding (Javalgi et al. 2006; Ray et al. 2005).

According to research analyst, the Gardner Group, corporate investment in CRM technology will continue to grow at a compound annual rate of 11.7 percent during the 2006-2011 period (Lauchlan 2007). Reports of a positive link between CRM uptake and improved firm performance have been less encouraging. For example the Gartner Group, a research and advisory firm, claim that close to 50 percent of all CRM projects fail to meet expectations (The Australian, 8th July, 2003). Additionally, an InfoWorld survey of chief technology officers (InfoWorld 2001) found that close to 30 percent of chief technology officers said that CRM was one of the most “over hyped” technologies they had seen. A follow up survey of IT executives found that 43 percent of large companies that have deployed CRM still believe that it deserves the bad press (InfoWorld 2003).

In contrast to the above industry survey reports, the recent academic literature appears to confirm that CRM programs enhance firm performance. For instance, in a special section in the Journal of Marketing eight of the ten papers published─conducted in a wide variety of industry settings─came to this conclusion (Boulding et al. 2005). As a whole however, CRM is a neglected area of research where “further efforts to address its mobilization and alignment are not only warranted but desperately needed” (Zablah et al. 2003, p. 116).

One of the problems with the way CRM and performance has been measured is that the term often means different things to different people, creating confusion and uncertainty. For example, in a series of interviews with executives, Payne and Frow (2005) found that to some, CRM meant direct mail, a loyalty scheme, help desk and call centre. Whereas, others envisioned a data warehouse, data mining, e-commerce solution or databases for sales force automation. To alleviate this problem we focus specifically on electronic customer relationship management (eCRM) programs as defined in a SAS Institute white paper (2000): “the creation of knowledge from process automation and the collection, synthesis and delivery of data derived from the Internet and information technology (IT) based interactions between the company and its customers/channel partners.” This definition captures two important aspects of eCRM: (1) IT infrastructure, and (2) e-intelligence capability. Modern IT such as relational databases, data warehousing, data mining and Internet delivery are a feature of eCRM programs that customise and enhance personal relationships with customer and suppliers. However, alone IT is an insufficient source of competitive advantage (Carr 2003). Rather, competitive advantages arise from the interpretation of data or what we refer to as “e-intelligence” in this study.1

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