Influence of Knowledge Management Enablers in Manufacturing Organizations: A Multi- Criteria Decision Making in Indian Context

2020 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Ravi Kant ◽  
HITESHKUMAR SHAH
Keyword(s):  
Decision Making ◽  
Knowledge Management ◽  
Multi Criteria Decision Making ◽  
Indian Context ◽  
Manufacturing Organizations

Modeling enablers of knowledge management process using multi criteria decision making approach

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nishant Agrawal
Keyword(s):  
Decision Making ◽  
Knowledge Management ◽  
Research Work ◽  
Research Area ◽  
Multi Criteria Decision Making ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Effect Relationship ◽  
Integrated Method ◽  
Knowledge Based

Purpose Drawing from boundary-spamming knowledge processes and knowledge-based theory, the purpose of this paper is to study enablers of the knowledge management (KM) process using robust multi-criteria decision-making (MCDM) tools like interpretive structural modeling (ISM) and decision-making trial and evaluation laboratory (DEMATEL) method. Design/methodology/approach Drawing on the knowledge-based view and through the detailed literature review among different KM success, eight enablers were identified. By using the ISM-DEMATEL approach, a systematic framework was designed, and further cause–effect relationship diagram visualized a causal relationship among the enablers. Findings The combined approach of ISM-DEMATEL showcase that “knowledge creation” and “knowledge capture” are essential enablers. These two identified enablers have considered being pillars for KM implementation. On the other side, knowledge organization, knowledge application are dependent enablers. Practical implications From a practical viewpoint, the findings of this research work enable the industry consultants to identify the most prominent driving enablers for KM implementation. Additionally, it provides a clue for the effective implementation of KM in a systematic approach. Originality/value The integrated method depending on the hierarchical model and cause–effect relationship between enablers of the KM process is a novel approach that opens a new research area in this domain. Moreover, this is the first-ever attempt to combine ISM along with DEMATEL to identify enablers of the KM process.

Artificial Intelligence

2021 ◽  
pp. 210-221
Author(s):  
Ankit Dhamija ◽  
Niti Chatterji
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Knowledge Management ◽  
Stage Of Development ◽  
Indian Context ◽  
The Relationship ◽  
Current Stage

Machines have emerged as intelligent players and are set to replace skilled practitioners in various fields. So, what would be a leader's contribution be if machines do the decision making? The chapter addresses this question by proposing that artificial intelligence will act as a catalyst enabling managers and leaders in the process of knowledge management. Further, the chapter aims to bring together the three constructs of leadership, artificial intelligence, and knowledge management and try to theoretically establish a relationship among them. The work is immensely relevant to the Indian context given the fact that at its current stage of development, artificial intelligence has the potential to add $957 billion to the country's economy by 2035. Thus, the chapter will emphasize the relationship between leadership and artificial intelligence and how it supports knowledge management in organizations and influences its everyday decision making.

Competitive priorities and knowledge management

2015 ◽  
Vol 26 (6) ◽  
pp. 791-806 ◽  
Author(s):  
Matloub Hussain ◽  
Mian M. Ajmal ◽  
Mehmood Khan ◽  
Hussein Saber
Keyword(s):  
Decision Making ◽  
Knowledge Management ◽  
United Arab Emirates ◽  
Future Research ◽  
Customer Focus ◽  
Multi Criteria Decision Making ◽  
Manufacturing Companies ◽  
Global Knowledge ◽  
Competitive Priorities ◽  
Content Type

Purpose – The purpose of this paper is to identify attributes of knowledge management (KM) for large and small manufacturing companies in United Arab Emirates (UAE) and to propose a process to evaluate the competitive priorities of these companies. Design/methodology/approach – This research is designed by composing multi criteria decision making of KM attributes in order to identify competitive priorities of large and small manufacturing companies to achieve better customer focus. To deal with this complexity of multi criteria decision-making process, Analytical Hierarchical Process (AHP) method has been used in this research. Findings – Results show that large manufacturing companies are putting more emphasis on “Know-Why” knowledge attribute in all four competitive priorities for achieving customer focus. While, small size manufacturing companies put higher weight on “Know-What” knowledge attribute by focussing on two competitive priorities (flexibility and quality). Research limitations/implications – Results are derived from a limited number of empirical data only in one country, therefore these cannot be generalized. Future research with larger samples of small and large manufacturing firms from other countries is needed. Practical implications – To be competitive, manufacturing companies must reshuffle their production strategies to allow them to play a role in global knowledge-intensive market. Therefore, they must incorporate knowledge attributes as a way to achieve higher levels of performance. Originality/value – This study is among the first and most exhaustive ones carried out in the small and large size firms operating in the manufacturing sector of UAE. It provides a systematic approach to identify the operational competencies and knowledge attributes being followed by large and small manufacturing companies.

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