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Enterprise systems enable efficiency across an organization through streamlining of business processes, faster access to real-time data, and the use of advanced management and reporting tools (Aremu et al., 2020; Galy & Sauceda, 2014; Huang & Handfield, 2015; Ranjan et al., 2016). However, its implementation transforms the operating paradigm within the organization and changes many aspects of day-to-day work roles, including operational workflows, technical procedures, and data requirements. As a result, implementation success depends on the ability of end-users to acquire, internalize, and utilize knowledge specific to the newly implemented enterprise system (Freeze et al., 2012; Sasidharan et al., 2012; Sasidharan et al., 2017; Sykes et al., 2009). However, end-user resistance to change arising from a lack of understanding of the technology and associated business processes can result in incompetent and, at times, improper use of the new system, leading to implementation failure and long-term financial losses (Aremu et al., 2020; Chadhar & Daneshgar, 2018; Ilie & Turel, 2020; Rai & Selnes, 2019; Ranjan et al., 2016).
Formal knowledge dissemination strategies adopted by organizations include the use of technology champions and support structures such as a helpdesk, a service desk, and a shared inbox (Andrews et al., 2016; Babinchak, 2017; Koch & Mitteregger, 2016; Konrad, 2020; Rahman, 2016). While end-users can source system-related knowledge from any of these entities, extant research has focused primarily on knowledge acquired from other end-users through social networking (Freeze et al., 2012; Sasidharan et al., 2017; Sasidharan et al., 2012; Sykes et al., 2009; Sykes, Venkatesh, & Johnson, 2014). Drawing upon the actor-network theory (Callon, 1996; Latour, 2005), this study argues that all actors contribute to the knowledge dynamics within the implementation environment, and the knowledge contributions of each can impact end-user system use and subsequent implementation outcomes (Kane & Alavi, 2008). It proposes an expanded and more inclusive multimodal social network, one extending beyond end-users, through the inclusion of knowledge actors such as technology champions, the helpdesk, the service desk, and the shared inbox. Current research treats knowledge ties as unidimensional, the proposed multimodal social network views them as bidimensional, through incorporating technical and business process knowledge.
This paper addresses two substantial research questions: (1) Do knowledge actors in the expanded multimodal social network influence end-user performance with the system? (2) Does their influence differ across the technical and business process knowledge networks? Data collected from an enterprise system implementation substantiated the proposed model: end-user performance levels were related to the knowledge actor from whom the knowledge was sourced, and the knowledge network involved. Top-level performers drew upon technology champions and, to a lesser extent, the helpdesk for technical knowledge, and other end-users for business process knowledge. In contrast, low-level performers preferred the shared inbox for both technical and business process knowledge.