Visualisation of Knowledge Mapping for Information Systems Evaluation: A Manufacturing Context

Abstract

Information Systems (IS) are primary enablers in instigating organisational change, increasing organisational responsiveness and decreasing supply chain overheads. This paper aims to contribute through exploring and visualising Knowledge Mapping (KM) from the perspective of Information Systems Investment Evaluation (ISIE). Complexity of IS evaluation process increases with the increase in intricacy of IS. A number of interrelating factors (e.g. costs, benefits and risks) contribute towards the intricacy of IS evaluation. There seems to be a growing need to evaluate the IS investment decisionmaking processes, to better understand the often far reaching repercussions related with IS implementation and interconnected Knowledge Components (KC). In seeking to edify the often vague IS evaluation process, this paper attempts to, emphasise the increase of knowledge and learning through the application of a Fuzzy Cognitive Mapping (FCM) technique. The resulting FCM determines the intricate and developing behaviour of causal relationships within the KM area.

Information Flow Analysis of a Knowledge Mapping-Based System for University Alumni Collaboration: a Practical Approach

“…Accordingly, over the years several knowledge management techniques such as mind maps, information flow analysis, concept maps, social network analysis, knowledge mapping, etc. have been successfully applied for knowledge management in several domains as carried out by prior studies (Ferreira 2009;Mitchell and Seaman 2011;Sharif et al 2014;Song and Zhao 2015;Liu and Cui 2017). However, prior studies (see Table 1) similar to this research predominantly focus on providing explicit knowledge to alumni members.…”

The Six Pillars of Knowledge Economics

“…From 2012: Chung et al [18], Rai [19] and Trauth [20] From 2013:Bahrs et al [21], Loeser et al [22], Prpic and Shukla [23] and Thies and Stanoevska-Slabeva [24] From 2014: Brockmann and Roztocki [7], Prpic and Shukla [25] and Sharif et al [26] From 2015: Brockmann and Roztocki [27], Hilbert [28] and Kees [29] From 2016: Al Busadi [30], Kowal and Gurba [31] and Peinl et al [32] Similar to our earlier analysis [7], the 16 papers of in the HICSS mini-track Knowledge Economics were analyzed in four major steps regarding dimensions depicted in Figure 2. …”

“…[7] Broaden scope and consider emerging economies Prpic and Shukla [25] Investigate relative efficacy of episodic structures vs. constituting forms. Sharif et al [26] Extend the scope Brockmann and Roztocki [27] Creation of a knowledge society Hilbert [28] More research on short-and long-term patterns. Kees [29] Validate the developed approach in other organization Al Busadi [30] Conduct a more sophisticated econometric longitudinal analyses of World Bank data Kowal and Gurba [31] Consider socio-economic factors such personal income.…”