知识管理
计算机科学
独创性
比例(比率)
可学性
知识价值链
构造(python库)
知识工程
工作(物理)
实证研究
数据科学
组织学习
管理科学
心理学
人工智能
创造力
经济
哲学
工程类
程序设计语言
物理
认识论
机械工程
社会心理学
量子力学
作者
Derrick A McIver,Xiaodan “Abby” Wang
标识
DOI:10.1108/jkm-11-2015-0478
摘要
Purpose This paper aims to develop a reliable and valid scale for measuring the underlying knowledge involved in work. To do so, it builds on the knowledge-in-practice (KIP) framework that suggests different types of work have different underlying knowledge characteristics. This allows us to answer two important questions: What are the underlying characteristics of KIP that are important to effectively manage a firm’s knowledge resources? How do we measure these characteristics? The answers help to build theoretical and empirical understanding of the construct of KIP. Design/methodology/approach The study uses a discovery-oriented survey design methodology to design the survey instrument, followed by a mixed-methods approach to validate the scale. Findings A new scale is developed for measuring the tacitness and learnability of the knowledge involved in work. It allows work units to be evaluated based on the underlying knowledge involved in different types of work. Research limitations/implications The KIP scale can be used for measuring the type of knowledge characteristics in organizations. Academics can use this study as a basic model to explore knowledge across different contexts and focus on the different characteristics within and across work contexts. Practical implications The study provides a clearer and more granular understanding of knowledge in organizations that can be used as a guideline to refer to when measuring and assessing knowledge requirements. Originality/value Scholars have pushed to understand work from a knowledge and collaboration perspective. A measurement scale for the KIP framework provides a critical first step towards this outcome.
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