Understanding expert systems applications from a knowledge transfer perspective

Abstract

Expert systems were introduced more than two decades ago but their effectiveness and success are still in debate. This paper attempts to make a contribution to the better understanding of expert system applications from a knowledge transfer perspective. The paper argues that an expert system application is knowledge transfer using Information and Communication Technologies (ICT). Underpinned by knowledge transfer theories and through a series of empirical investigations of agriculture expert system projects, the study recognises the importance of human interactions in the expert systems implementation process. Based on the evidence collected, a number of key players are examined. These are; knowledge provider/sender, knowledge engineer, knowledge extensionist and knowledge recipient. The paper represents a first attempt to introduce and acknowledge the role of a knowledge extensionist in the ICT-based knowledge transfer process. The name "extensionist" is borrowed from previous literature and describes an actor whose role is an intermediary in supporting transferring knowledge towards the knowledge user. Findings demonstrate the significant contributions made by extensionists to the success of expert systems applications. It is argued that the rigidity and limitation of ICT based knowledge transfer can be significantly reduced with the involvement of close human interactions towards the knowledge recipient.

Data-driven Applications to Foster Absorptive Capacity: A Literature-based Conceptualization

“…Some scholars even refer specifically to knowledge management systems as "IT-based systems developed to support and enhance the organizational processes of knowledge creation, storage/retrieval, transfer, and application" [3]. For instance, research on knowledge management covers DDAs such as decision support systems [40], knowledge-based systems [2], expert systems [15], or data mining [53].…”

Expert Systems and knowledge management for failure prediction to onshore pipelines: issue to Industry 4.0 implementation

“…The papers reviewed revealed opportunities for new frontier-based research to be overcome, as follows: integration of the JavaBean and Jess tools to obtain the inference engine more efficiently (Shiue et al, 2008); development of new validation methods to measure the performance of the medical recommendation proposed and also in other domains, e.g., clinical care treatment and healthy lifestyle choices to lower disease occurrence probability in public health (Chi et al, 2008); tacit knowledge transfer and the success factors affecting the ES applications from knowledge users' point of view (Chang & Chuang, 2011;Chen et al, 2009;Feng et al, 2009;Muniz et al, 2011;Nakano et al, 2013;Patil & Kant, 2014); extension of reasoning modes and automatic provision of analyses to create automatic deductions on the basis of the knowledge expressed by the expert (Ruiz-Mezcua et al, 2011); improve practices that enhance and promote KM in the problem-solving process (Vacik et al, 2013); combine knowledge expressed by fuzzy cognitive maps and sets, and neural networks with traditional knowledge (Kim, 2014); develop different methods for tacit knowledge acquisition under complex and uncertain environments (Li et al, 2018).…”

“…The review of the literature comprises expert systems (ES) and knowledge management (KM) papers focused on decision-making support tools, which indicates application in different areas represents opportunities for further research. The application fields were identified in medicine (Chi et al, 2008;Kim, 2014;Li et al, 2018;Vihinen & Samarghitean, 2008), finance (Blue & Andoh-Baidoo, 2010;Shiue et al, 2008), education (Koutsantonis & Panayiotopoulos, 2011;Lee et al, 2005), engineering (Kumar, 2014), agriculture (Feng et al, 2009), insurance (Ruiz-Mezcua et al, 2011), environmental (Vacik et al, 2013) and construction (Hajdasz, 2014). The summary of the literature review is presented in Table 1.…”

“…The results are then discussed in order to evince the ES suitability to support KM in an Industry 4.0 context. In the context of the new frontierbased research to be overcome previously presented, the contribution of this paper is mainly in tacit knowledge transfer (Feng et al, 2009) and practices that enhance and promote KM in problem-solving processes (Vacik et al, 2013).…”

A Systematic Literature Review of Agriculture Knowledge Management in KM and non-KM Journals

“…The predominant focus of the AKM articles in KM journals was similar to typical KM areas of interest, considering how to leverage knowledge for business growth, competitive advantage, and organisational improvement, although the former articles considered agricultural organisations and agri-business enterprises. 10 out of the 12 mainstream KM studies were conducted in structured organisational settings(Chisita & Fombad 2020;Gardeazabal et al, 2021;Ahmed & Newton, 2005), across inter-organisational settings(Fait et al 2019; Garcia- Villaverde et al 2008; O'Connor & Kelly 2007) or in institutional settings that bear resemblances with organisations such as a cooperative(Galindo 2007), a network (De Bernardi et al 2021) and a project(Feng et al 2009). The operational context in such structured organisational settings allowed managers/leaders to identify areas where knowledge processes can be leveraged and identify tools and techniques that coujld be used to reinforce the application of knowledge, whether consciously or unconsciously.…”