Achieving Effective Use When Digitalizing Work: The Role Of Representational Complexity

In times of accelerated digital transformation, many organizations still struggle to put enterprise systems to effective use quickly. While prior work suggests either system or task complexity as a source for these difficulties, this case study of a major system implementation at a European bank reveals the most important source to be the complexity arising from co-dependency between the system and the task. We conceptualize this codependency as inherent in system-enabled tasks by proposing system dependency (the extent to which a task is supported by a system) and semantic dependency (the degree to which semantic understanding is required for task completion). Together, these dependencies create representational complexity, which constrains users from achieving effective use in system-enabled tasks and can explain differences in achieving effective use through variations in learning effort. The concepts and insights emerging from this study provide researchers and practitioners with a deeper understanding of what complexity means and why, in some contexts, learning how to use systems effectively takes longer.

• 저널MIS Quarterly · 44(3) · 1023–1048
• 토픽Big Data and Business Intelligence · Management Information Systems
• DOI10.25300/misq/2020/14583
• 저자Jens Lauterbach, Benjamin Mueller, Felix Kahrau, Alexander Maedche