Technology adoption and performance in the sales force
Date of Completion
January 2008
Keywords
Business Administration, Marketing
Degree
Ph.D.
Abstract
Over the past several decades, products and markets have become increasingly more complex. In response to these dynamics, firms are placing new emphasis on service as a means of increasing sales, enhancing customer satisfaction, and—ultimately—improving performance. In order to achieve these, many organizations have implemented expensive software such as Customer Relationship Management (CRM) tools. ^ In parallel with this growth, and perhaps partly because of it, an extensive research stream has developed to investigate the antecedents to adoption of technology. This research has only examined the influence of technology adoption/usage on the performance at the individual level. Further research has looked at the impact of this adoption and usage on performance of the individual. Inherent in these studies of individual adoption is also an expectation that more usage/increased adoption leads to better individual performance. Also, with the increasing complexity of products, there is also an increasing move from individual sales to sales teams. ^ We first extend the current literature by bringing together the adoption and the team literature to empirically examine both individual and team characteristics and their influence on technology adoption/usage in a sales setting. Then we challenge an implicit underlying theory used in all the adoption as an antecedent to performance literature—that adoption (as measured by the amount of usage) impacts performance. We instead hypothesize that it is how the technology is used and not how much the technology is used that has the greatest impact on performance. We support that hypothesis with a comparison of methods using objective granular duration and sequencing data of every CRM screen view entered by 497 salespeople over 18 months. ^
Recommended Citation
Weinstein, Luke A, "Technology adoption and performance in the sales force" (2008). Doctoral Dissertations. AAI3308255.
https://digitalcommons.lib.uconn.edu/dissertations/AAI3308255