TY - GEN
T1 - Knowledge Dynamics and Expert Knowledge Translation
T2 - 24th European Conference on Knowledge Management, ECKM 2023
AU - Bratianu, Constantin
AU - Garcia-Perez, Alexeis
PY - 2023/11/1
Y1 - 2023/11/1
N2 - Knowledge dynamics means variation of knowledge in time and space. Over time, knowledge levels can increase through accumulation, or decrease through loss. Also, knowledge may change its quality through transformation from one form into another. In space, knowledge can move from one place to another one, generating a flow (i.e., knowledge flow). The present paper aims at analyzing the knowledge dynamics associated to the process of expert knowledge translation, present in almost all life domains. Knowledge translation is based on communication and transformation of knowledge. Among many models used to explain knowledge translation, we present in this paper the expert knowledge translation that is used whenever an expert is sharing his expertise with one or several individuals interested in that knowledge. We analyze the whole process of expert knowledge translation from a conceptual perspective and then we present a case study describing expert knowledge translation. Knowledge translation is necessary because the source and the receiver of the messages have different semantic domains and levels of understanding based on their education, background and their analytical skills. The main barrier in knowledge translation is the absorptive capacity of the receiver. If the absorptive capacity is rather small, the translation efficiency is very small. This situation can be improved if the translation process is broken into several smaller knowledge translation processes like in a cascade. The paper presents the model of such a cascade for expert knowledge translation showing how to construct it. As an application, the paper presents a case study focused on a company manufacturing gas turbines (GTM). The company is a global supplier of gas turbines and we show how engineering expert knowledge is translated in a cascade from design to manufacturing, automation, testing, installing and commissioning turbines to end users.
AB - Knowledge dynamics means variation of knowledge in time and space. Over time, knowledge levels can increase through accumulation, or decrease through loss. Also, knowledge may change its quality through transformation from one form into another. In space, knowledge can move from one place to another one, generating a flow (i.e., knowledge flow). The present paper aims at analyzing the knowledge dynamics associated to the process of expert knowledge translation, present in almost all life domains. Knowledge translation is based on communication and transformation of knowledge. Among many models used to explain knowledge translation, we present in this paper the expert knowledge translation that is used whenever an expert is sharing his expertise with one or several individuals interested in that knowledge. We analyze the whole process of expert knowledge translation from a conceptual perspective and then we present a case study describing expert knowledge translation. Knowledge translation is necessary because the source and the receiver of the messages have different semantic domains and levels of understanding based on their education, background and their analytical skills. The main barrier in knowledge translation is the absorptive capacity of the receiver. If the absorptive capacity is rather small, the translation efficiency is very small. This situation can be improved if the translation process is broken into several smaller knowledge translation processes like in a cascade. The paper presents the model of such a cascade for expert knowledge translation showing how to construct it. As an application, the paper presents a case study focused on a company manufacturing gas turbines (GTM). The company is a global supplier of gas turbines and we show how engineering expert knowledge is translated in a cascade from design to manufacturing, automation, testing, installing and commissioning turbines to end users.
KW - Absorptive capacity
KW - Expert knowledge
KW - Knowledge dynamics
KW - Knowledge translation
UR - https://papers.academic-conferences.org/index.php/eckm/article/view/1382
UR - http://www.scopus.com/inward/record.url?scp=85177874579&partnerID=8YFLogxK
U2 - 10.34190/eckm.24.1.1382
DO - 10.34190/eckm.24.1.1382
M3 - Conference publication
AN - SCOPUS:85177874579
SN - 9781914587733
T3 - Proceedings of the European Conference on Knowledge Management, ECKM
SP - 140
EP - 147
BT - Proceedings of the 24th European Conference on Knowledge Management, ECKM 2023
A2 - Matos, Florinda
A2 - Rosa, Alvaro
Y2 - 7 September 2023 through 8 September 2023
ER -