This chapter is from the book
This chapter is from the book
This chapter is from the book
Introduction
The implementation of an enterprise resource planning (ERP) system is one of the more popular and radical organizational changes that can result in significant modifications to nearly 30% of key routines in contemporary firms (Davenport & Beck, 2013; Herold, Fedor, & Caldwell, 2007). Some other estimates also show high adoption rates of ERP systems, such as 75% among service-oriented companies, 60% in medium-to-large manufacturing firms, and 80% among Fortune 500 firms (Phelan, 2014). Prior studies have found that ERP systems result in multiple benefits including lowering costs and reducing inventories, enhancing firm’s productivity (Olson, 2003), improving in operational efficiency (Häkkinen & Hilmola, 2008), gaining competitive advantage (Beard & Sumner, 2004), and promoting internal resources’ restructuring (Stratman, 2007). In addition, past research highlights the critical role of ERP systems as organizational resources and indicates their importance in designing the information system (IS) of a company (Ko, Kirsch, & King, 2005; Xu & Tian, 2014).
To maximize the benefits of implemented ERP systems, it is crucial to enhance individuals’ expertise and skills in employing such systems by providing proper training (Gardiner, Hanna, & LaTour, 2002) because ineffective utilization of systems is mainly due to insufficiency of training (Henriksen & Andersen, 2008). Training has been of importance because of its significant effect on the success of IS (Chou, Chang, Lin, & Chou, 2014). In the case of ERP systems, users have to learn both a new package, and also a totally novel way of conducting business. In a recent study, Sykes, Venkatesh, and Johnson (2014) found support for this argument contending that for maximal benefit, organizations could design training interventions and support services so that the early focus is on the technical side of the systems, with later stages focusing on routines and processes.
In the last decade, researchers have encouraged the use of simulation games for the purpose of learning and instruction (Hainey, Connolly, Stansfield, & Boyle, 2011; Kebritchi, Hirumi, & Bai, 2010). Anecdotal and empirical findings suggest that computer-based simulation games are effective for enhancing employees’ skill sets. Companies such as Canon and Cold Stone Creamery developed simulation games to teach their employees various technical and managerial skills. Employees who played the game obtained 5% to 8% higher training assessment scores than those trained with older techniques, such as manuals (Sitzmann, 2011). Learning the concepts and developing competencies underlying an ERP system is a difficult task. Researchers found that adopting a learning-by-doing approach through employing simulation games to train ERP users is an effective method (Léger et al., 2011). This process focuses on guiding the learning experience in a situated context through a series of realistic and potentially complex open-ended problems. Such problem-based learning motivates the participant to gain a set of competencies by actively resolving the task (Merrill, 2007).
The ERP simulation game (ERPsim) has been designed based on the concept of situated cognition. Prior research suggests that such a realistic learning environment is associated with higher levels of learner involvement and motivation, which leads to higher understanding and better knowledge transfer (Lave & Wenger, 1991). An active learner is highly involved and plays a dynamic and self-motivated role in how and what needs to be learned (Trigwell, Ellis, & Han, 2012). Prior research has found that simulation games improve the learning process of individuals by promoting their psychological involvement (Anderson & Barnett, 2011). However, the complexity of ERP systems limits the amount of knowledge those users can absorb before they actually use an ERP system (Yi & Davis, 2003). Users have to continue to learn to obtain the knowledge and skills required for effective ERP usage.
The key objective of the study is to examine the shift of individual’s knowledge perceptions from the pre-training to the post-training stage to understand the change in user’s belief. In doing so, the study highlights that limited attention has been given to users’ perceptions of knowledge update offered by the IT artifact in prior longitudinal studies. We defined perceived knowledge update as individuals’ perceptions of their improved abilities to perform their daily work using the ERP system after taking the relevant training programs. Although perceived knowledge and training were found to promote an individual’s ability in performing challenging tasks (Torkzadeh, Pflughoeft, & Hall, 1999), there has been little research on how updated knowledge leads to continuous learning intentions and what determines individual’s perception of knowledge update in ERPsim setting. In other words, the difference between an individual’s knowledge about ERP before attending an ERPsim training session and after that, as we argue, has positive relationship with learning behaviors.
Given the research gaps mentioned previously, our study answers the following questions: What influences a user’s perception of knowledge update? What are the consequences of perceived knowledge update? To answer the research questions, our model is based on the expectation-conrmation model (ECM) (Bhattacherjee, 2001), which was used as an analytical lens to explain how an individual’s judgment of his/her improved knowledge affects his/her involvement, which in turn influences continuance intention. As ECM highlights the prominence of both pre- and post-behaviors of individuals in their subsequent usage behaviors, we recognize the variance of pre-training and post-training knowledge levels and test the levels’ central role in learner’s post-training behavior.
The chapter is organized as follows: First, we provide the theoretical background for the study. Next, we present the research hypotheses and methodology for our research followed by the analysis and the results. Finally, we conclude with a discussion of research findings and implications for theory and practice.