Knowledge Value, Task Complexity, and Enterprise Technology Implementation: An Introductory Study

Knowledge Value, Task Complexity, and Enterprise Technology Implementation: An Introductory Study

Sharath Sasidharan (Bowling Green State University, USA)
Copyright: © 2019 |Pages: 20
DOI: 10.4018/IJTD.2019010102

Abstract

Employees utilize their informal social networks for acquiring system-related knowledge during enterprise technology implementation. Prior research on knowledge acquisition through social networks has not considered the domain proficiency of knowledge sources or the quality of knowledge flows. This study assigns domain-proficiency levels to knowledge sources and introduces the concept of knowledge value: the net impact of acquired knowledge on performance outcomes. Conceptualized as the differential in the domain proficiency of the knowledge source and the knowledge recipient, knowledge value is examined in the context of both factual and applied knowledge, in relation to task complexity and its influence on performance outcomes. Data collected during the implementation of an enterprise resource planning system indicate that knowledge value has a significant impact on performance outcomes, but the impact of applied knowledge is moderated by task complexity. The results stress the importance of considering domain proficiency of knowledge sources during knowledge-network modelling.
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Introduction

With a market size projected to reach $500 billion by 2022, enterprise technologies (ET) span all major industry sectors, including banking and finance, production and manufacturing, education, healthcare, retail, insurance, energy, telecom, and transportation (Gartner, 2017). As opposed to traditional “legacy” business technologies that cater to individual organizational units, ETs facilitate aggregation, integration, and analysis of organization-wide data, leading to increased competitiveness through efficient resource, capital, and inventory management. They make available timely, relevant, value-added data that can help support long-term planning and strategic decision making (Galy & Sauceda, 2014; Huang & Handfield, 2015; Marengo, Pagano, & Barbone, 2013; Ifinedo, 2017; Owusu, Ghanbari-Baghestan, & Kalantari, 2017; Tarhini, Ammar, & Tarhini, 2015). Prominent ET vendors include SAP, IBM, Microsoft, and Oracle. Together they provide an extensive range of ET software applications, including Customer Relationship Management, Enterprise Resource Planning (ERP), Business Intelligence, Data Analytics, and Supply Chain Management (Gartner, 2017).

ETs emphasize a unified cross-organizational perspective on the business. However, their full potential can be realized only when employees master their functional and operational features, and use it for the execution of work-related tasks. While employees understanding work-related tasks and their relevance to the immediate operating environment once sufficed, the new organization-focused operational paradigm introduced by ETs requires employees to understand the way the technology executes those tasks, its interdependencies with other tasks and business processes within their department, and its linkages with other business processes across the organization (Garg & Agarwal, 2014; Kini & Basaviah, 2013; Pishdad & Haider, 2014; Tarhini et al., 2015). These interdependencies between tasks and business processes across the organization may result in employees having to execute increasingly complex tasks. Hence, knowledge support commensurate with the complexities of employee-specific tasks becomes essential to meeting desired performance outcomes. Employees must acquire both technology-specific and context-relevant knowledge of the ET and understand its interaction with underlying tasks and business processes in the execution of their work-related tasks.

Acknowledging the difficulties associated with transitioning to ETs, many organizations have incorporated knowledge-support activities into their larger change management strategy. Such a strategy usually emphasizes employee learning and skill recalibration through training and education, and employee participation in the ET design and implementation processes (Abelein & Paech, 2015; Ahmad & Cuenca, 2013; Bano & Zowghi, 2015; Chou, Chang, Lin, & Chou, 2014). Apart from these organizationally mandated approaches, employees turn at a personal level to their work-related social networks to acquire knowledge regarding usage of the new technology and to understand its impact on their work practices and related business processes. Employees occupying central positions within their work-related social networks have been found to be well positioned to acquire technology-related knowledge, resulting in enhanced performance outcomes (Sasidharan, Santhanam, Brass, & Sambamurthy, 2012; Sasidharan, Santhanam, & Brass, 2017; Sykes, Venkatesh, & Gosain, 2009; Sykes, Venkatesh, & Johnson, 2014; Sykes, 2015).

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