The purpose of this chapter is to contribute to the improvement of the acceptance of information systems (IS) devoted to the codification and sharing of knowledge (a type of knowledge management systems [KMS]). A research model was developed through a multi-staged, multi-method research process and its test supports the hypotheses that the acceptance of KMS is determined, in addition to the classical constructs of the technology acceptance model (TAM), by a few organizational factors, and by the influence exerted on the user by individuals close to her/him.
Improving KMS Acceptance: The Role of Organizational and Individuals’ InfluenceTop
The topics of knowledge management (KM) and KMS are among the most popular topics in the IS field with recent years yielding a number of reviews of the literature and taxonomies of KMS (Alavi & Leidner, 2001; Argote, McEvily, & Reagans, 2003; Jennex, 2006; Jennex & Olfman, 2004; Liao, 2003; Maier, 2002; Malhotra, 2004; Muscatello, 2003; Sambamurthy & Subramani, 2005; Wickramasinghe, 2003). Far from sharing a common viewpoint regarding to what extent and under which hypotheses KMS represent an actual support to organizational processes, researchers and practitioners in the KMS field recognize a number of issues that need to be studied. From the academic standpoint, Argote et al. (2003) and Sambamurthy Subramani (2005) have identified a set of emergent issues for the future of research on KM and KMS. They emphasize social relations in understanding knowledge creation, retention and transfer (Argote et al., 2003) and the role of IT to facilitate the efficient and effective development of communities of practice (CoP) (Sambamurthy & Subramani, 2005). They also point out the need to shift the interests of academia from single to multiple relations dealing with the KM process. The complementary practitioner view has been effectively synthesized by Smith and McKeen (2003) who have collected opinions and expectations of chief knowledge officers (CKO). CKOs are confident that the development of KMS has come to a turning point, where investments in implementation of new KM tools and methodologies should be replaced by initiatives aiming at measuring and maximizing the return on the investments (both in the organizational structure and in information and communication technologies [ICT]) that companies made in the past (Folkens & Spiliopoulou, 2004; Smith & McKeen, 2003).
Such indications suggest concentrating the efforts of research towards the achievement of a better and eventually a more complete understanding of the factors that influence the effectiveness and efficiency of a KMS. To this end, adopting a widely accepted definition of KM is a prerequisite. In this work we use the Alavi and Leidner (2001) KM definition which envisions KM as a process and the KMS as the specific IS which supports the organizational KM processes of creation, storage, diffusion, and application of knowledge. This definition fits our study for two reasons. First, it is compatible with those provided in relevant publications about KMS (Grover & Davenport, 2001; Hansen, 2002; Lai, Ong, Yang, & Tang, 2005; Money & Turner, 2005; Ong, Lai, Wang, & Wang, 2005; Schultze & Leidner, 2002; Xu & Quaddus, 2004, 2005). Second, it can be used to classify KMS applications according to their main purpose: (1) to code and share knowledge, (2) to create corporate knowledge directories, and (3) to create knowledge networks (Alavi & Leidner, 2001).
This chapter refers to the first category of KMS, therefore its general aim is to contribute to the improvement of the effectiveness of those KMS devoted to the codification and sharing of knowledge. In order to do so, a multi-staged, multi-method research has been carried out, combining a theoretical analysis with an empirical investigation, structured in a preliminary qualitative and a subsequent quantitative research that allowed to design and test a research model.