Knowledge Management Systems Characteristics That Support Knowledge Sharing and Decision-Making Processes in Organizations

Knowledge Management Systems Characteristics That Support Knowledge Sharing and Decision-Making Processes in Organizations

Mahmoud Abdelrahman, Firas Masri, Dimitra Skoumpopoulou
DOI: 10.4018/978-1-5225-9639-4.ch004
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With the advent of the knowledge economy and the growing importance of knowledge societies, organizations are constantly seeking new ways of leveraging and sharing knowledge to support decision-making (DM) processes. This chapter presents an initial insight to the little-researched phenomenon of how knowledge management systems (KMSs) can facilitate knowledge sharing (KS) to support DM processes in organizations. In this chapter, authors aim to extend the existing literature of knowledge management, decision making, and knowledge sharing by proposing a new conceptual framework, namely “ECUA” (easiness, communication, unification, and analytics characteristics). In this study, 42 semi-structured interviews have been conducted. The proposed conceptual framework will benefit managers in both public and private sectors in finding new ways of leveraging and sharing knowledge to support DM processes via using KMSs. This framework can be used to explore KMSs characteristics that can support DM processes by facilitating knowledge sharing in organizations.
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Knowledge can be considered as one of the most important resources in any organization that can provide a sustainable competitive advantage at any competitive market and dynamic economy (Wang and Noe, 2010). Gaining a competitive advantage is challenging, especially in public sectors, as it is essential for public organizations to rely on knowledge systems that encourage employees who have specific knowledge, skills, talents, abilities, proficiencies or competencies to share their knowledge with other people in their organizations. Therefore, with the advent of the knowledge economy, organizations are continually seeking new ways of leveraging and sharing knowledge to support Decision Making (DM) processes and to achieve a lot of benefits in this competitive market place (DeTienne and Jackson, 2001). In the DM processes; decision makers combine different types of data like internal and external data, and different types of knowledge like tacit and explicit knowledge which are available in a variety of forms in organizations (Bolloju et al., 2002). In this highly competitive global environment, organizations are now recognizing an urgent need to institutionalize Knowledge Sharing (KS) as a mean of obtaining the best value from all available knowledge assets (Goh, 2007; Makela et al 2012). Accordingly, Knowledge Management (KM) and decision support processes are mutually dependent activities in many organizations. Nielsen and Michailova (2007) state that over the past two decades, many organizations have developed Knowledge Management Systems (KMSs) designed specifically to facilitate the sharing, integration and utilization of knowledge. Alavi and Leidner (2001) highlight that KMSs can support the creation and dissemination of firm expertise and knowledge. In addition, Nemati et al. (2002) emphasize that those KM initiatives can facilitate the capturing, coding and sharing of knowledge within organizations, which is expected to result in well informed decision processes. Therefore, KMSs can facilitate KM functions by ensuring knowledge flow from the person(s) who know to the person(s) who need to know throughout the organization (Abdelrahman et al., 2017; Abdelrahman and Papamichail, 2016; Bose, 2004). Moreover, Wang and Noe (2010) highlight that research has shown that knowledge management strategies are positively related to organization’s performance. For example, decisions based on KM can help organizations in reducing costs, elaborating products and services, improving team performance, encouraging firm innovation capabilities and increasing sales and revenue from new products and services. Choi et al. (2010) highlight that, little is known of how IT support for KM practices in organizations affects the development of KMSs, and the precise role of KMSs on knowledge sharing and knowledge application, which in turn influences team performance. Furthermore, Nag & Gioia, (2012) suggest a need to understand how key decision makers utilize the use of knowledge in their organizations by using what they know and seeking out what they do not know to guide the creation of unique knowledge-based competencies. Furthermore, there are many unprecedented challenges facing managers outside their organizations along with environmental “forces of change” such as: globalization, emerging technologies, emerging best business practices, government regulations, competitive global financial markets, limited knowledge workers and higher worker turnover rates (Abdelrahman et al., 2016; Cuffe, 2007). Therefore, in order to succeed in the global information society organizations need to identify, value, create, evolve and develop their knowledge assets since knowledge is one of their meaningful economic resources (Abdelrahman and Papamichail, 2016; Ergazakis, 2003; Maier and Schmidt, 2015).

Key Terms in this Chapter

Knowledge Sharing: The process by which knowledge is transferred between sender(s) and receiver(s) from one person to another, from individuals to groups, or from one group to another group in organizations.

Knowledge Management System: Is the system that facilitates supports and manages the process of creating, sharing, storing, and using of knowledge effectively and efficiently.

Procedural Knowledge: Is the knowledge about “how” to do something.

Shallow Knowledge: Is knowledge that in social domains where theories and understanding are usually less well organized and codified than in scientific domains.

Knowledge: Is a mix of contextual information, experiences, rules and values. Knowledge as the understanding, awareness, or familiarity acquired through education or experience; anything that has been learned, perceived, discovered, inferred or understood.

Information: Is data that are organized and analyzed in a meaningful way.

Esoteric Knowledge: Is the knowledge which is highly specialized, formalized, and applicable to narrow domains, that which is found in most scientific disciplines.

Knowledge Management: Is the process of reaching organization’s objectives by creating, sharing, storing and using knowledge derived from employees, organization’s practices, and other sources.

Decision-Making Processes: Is the process by which decision makers collect, combine and analyze different types of data and information, both internal and external, and different types of knowledge, tacit and explicit, which are available in a variety of forms throughout the organization networks.

Tacit Knowledge: Is that knowledge which is contained within a person’s head and is difficult or impossible to express, write down and codify.

Declarative Knowledge: Is data or information in the KM literature, consists of facts or observations about the state of the world.

Data: Are specific, objective facts or observations standing alone, such facts have no intrinsic meaning, but can be easily captured, transmitted, and stored electronically.

Deep Knowledge: Is knowledge that usually related to relatively well-structured scientific and technical domains, and consists of formal theories of behavior of phenomena in those domains.

Explicit Knowledge: Is knowledge that can be easily collected, organized and transferred through digital means. It can be readily articulated, written down, codified, and shared.

Decision Support Systems: Systems under the control of one or more decision makers that assist in the activity of decision making by providing an organized set of tools intended to impart structure to portions of the decision making situation and to improve the ultimate effectiveness of the decision outcome.

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