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Enterprise Ontology Model for Tacit Knowledge Externalization in Socio-Technical Enterprises
| Content Provider | Semantic Scholar |
|---|---|
| Author | Rao, Shreyas Suresh Nayak, Ashalatha |
| Copyright Year | 2017 |
| Abstract | INTRODUCTION Socio-technical enterprises are business organizations which regard human knowledge as the key asset in the functioning of an enterprise. Some examples are banking, education, and healthcare enterprises which are predominantly human-intensive (Booch, 2010) and use human knowledge in decision making, business innovation, and problem solving activities (Li & Lu, 2007). Since the growth of these enterprises is often marred by uncontrollable factors such as uncertain economic conditions, attrition, or retirement of highly-valued employees (Chandra, Iyer, & Raman, 2015; Whyte & Classen, 2012), knowledge creation is recognized as a vital business activity that counters these factors (Aming'a, 2015; Richards & Busch, 2003). Typically, knowledge within socio-technical enterprises is expressed using an iceberg metaphor (Serrat, 2008). As per the metaphor, enterprise knowledge is viewed as a dichotomous split between tacit and explicit, with tacit occupying 80% of the area submerged under the water and explicit as 20% visible outside the surface of the water. In retrospect, the metaphor implies that 80% of an enterprise's knowledge is contained within the minds of its employees as tacit knowledge. Hence, tacit knowledge represents the unarticulated know-how developed over time by employees through experiences derived from everyday work, dealing with clients, following company procedures (Friedrich & van der Poll, 2007), etc. Only 20% of the enterprise's knowledge is expressed externally through documents and storage repositories as explicit knowledge. As enterprise knowledge is largely tacit and perhaps underutilized, it is vital to convert this knowledge into an explicit format to facilitate knowledge utilization. The process of tacit knowledge elicitation from employees' minds and subsequent explication into explicit format is referred to as Tacit Knowledge Externalization (TKE) (Nonaka & Takeuchi, 1995). Almost always, the process of externalization is initiated by a knowledge seeker in the enterprise with the intention of utilizing the expert's tacit knowledge to solve enterprise challenges (Khan & Khader, 2014). Accordingly, the seeker engages the knowledge expert in a constructivist interaction, resulting in knowledge explication. Since the time Nonaka & Takeuchi (1995) first coined the term "externalization", researchers have explored various aspects of externalization, namely, (a) lifecycle (Dalkir, 2005; Whyte & Classen, 2012), (b) elicitation methods (Acosta et al., 2004; Al-Qdah & Salim, 2013), (c) inter-actor collaboration (Chandra et al., 2015; Khan & Khader, 2014), and (d) externalization scenarios (Leonard & Insch, 2005; Sigala & Chalkiti, 2007). Although researchers have explored diverse aspects of externalization individually, there have been no attempts for its comprehensive integration (Echajari & Thomas, 2015). This lacuna has resulted in a divergent and contradictory representation of the externalization process (Munoz, Mosey, & Binks, 2015; Venkitachalam & Busch, 2012). The paper proposes an Enterprise Ontology (EO) model for integrating diverse aspects of externalization. The EO model is based on the theory of Enterprise Ontology (Dietz, 2006), which provides formal models and patterns for representing any business operation within an enterprise. Since externalization is also perceived as a vital business operation within the enterprise (Sigala & Chalkiti, 2007), the proposed model is relevant in solving the externalization lacuna. Okafor and Osuagwu (2006) identified two types of knowledge externalization, namely, manual and automated (or machine learning). The scope of this research is of the first kind, wherein the experts' knowledge is manually elicited. The paper contributes towards existing literature by systematically investigating diverse aspects of externalization using Kipling's 5W+1H (What, Where, When, Why, Who, and How) approach (Jia, Cai, Yu, & Tse, 2016). … |
| Starting Page | 99 |
| Ending Page | 124 |
| Page Count | 26 |
| File Format | PDF HTM / HTML |
| Volume Number | 12 |
| Alternate Webpage(s) | http://www.ijikm.org/Volume12/IJIKMv12p099-124Rao3091.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
