Investigating Interdependencies Between Key Features of Lessons Learned: An Integral Approach for Knowledge Sharing

Author:

Abbas Yawar1ORCID,Martinetti Alberto1,Frunt Lex2,Klinkers Jeroen3,Rajabalinejad Mohammad1,van Dongen Leo A. M.1

Affiliation:

1. Design, Production and Management Department, University of Twente, Enschede, The Netherlands

2. Netherlands Railways, Utrecht, The Netherlands

3. ProRail, Utrecht, The Netherlands

Abstract

While there is a clear consensus in the literature on the need to share lessons learned, it remains unclear how to properly do so. This paper addresses this point and offers insight into how best to incorporate tacitly held social preferences for developing knowledge-sharing strategies. A descriptive survey was conducted to analyse the knowledge sharing practices for lessons learned within the railway sector. Eight variables are investigated that are derived from the four LEAF features: learnability, embraceability, applicability, and findability. This study revealed that for learnability, storytelling and discussion with colleagues are preferred ways to share personal experiences. Trust and the creation of a learning culture emerged as key aspects of embraceability. With regard to applicability, a process-related knowledge-sharing focus for intraorganisational and a content-related focus for interorganisational knowledge domains are preferred. Better technological findability is identified as a key area of improvement. Finally, novel dependencies are established using the chi-square test between key LEAF features.

Funder

Ministerie van Economische Zaken en Klimaat

Publisher

World Scientific Pub Co Pte Ltd

Subject

Library and Information Sciences,Computer Networks and Communications,Computer Science Applications

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3