If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -Many terms commonly used in the field of knowledge management (KM) have multiple uses and sometimes conflicting definitions because they are adapted from other research streams. Discussions of the various hierarchies of data, information, knowledge, and other related terms, although of value, are limited in providing support for KM. The purpose of this this paper is to define a new set of terminology and develop a five-tier knowledge management hierarchy (5TKMH) that can provide guidance to managers involved in KM efforts.Design/methodology/approach -The 5TKMH is developed by extending the knowledge hierarchy to include an individual and an innovation tier.Findings -The 5TKMH includes all of the types of KM identified in the literature, provides a tool for evaluating the KM effort in a firm, identifies the relationships between knowledge sources, and provides an evolutionary path for KM efforts within the firm.Research limitations/implications -The 5TKMH has not been formally tested.Practical implications -The 5TKMH supports a KM life-cycle that provides guidance to the chief knowledge officer and can be employed to inventory knowledge assets, evaluate KM strategy, and plan and manage the evolution of knowledge assets in the firm.Originality/value -In this paper, a new set of terminology is defined and a 5TKMH is developed that can provide guidance to managers involved in KM efforts and determining the future path of KM in the firm.
Task complexity is a construct widely used in the behavioral sciences to explore and predict the relationship between task characteristics and information processing. Because the creation and use of IT in the performance of tasks is a central area of informing science (IS) research, it follows that better understanding of task complexity should be of great potential benefit to IS researchers and practitioners. Unfortunately, applying task complexity to IS is difficult because no complete, consistent definition exists. Furthermore, the most commonly adopted definition, objective task complexity, tends to be of limited use in situations where discretion or learning is present, or where information technology (IT) is available to assist the task performer. These limitations prove to be severe in many common IS situations.The paper presents a literature review identifying thirteen distinct definitions of task complexity, then synthesizes these into a new five-class framework, referred to as the Comprehensive Task Complexity Classes (CTCC). It then shows the potential relevance of the CTCC to IS, focusing on different ways it could be applied throughout a hypothetical information systems lifecycle. In the course of doing so, the paper also illustrates how the interaction between different classes of task complexity can serve as a rich source of questions for future investigations.
Task complexity is a construct widely used in the behavioral sciences to explore and predict the relationship between task characteristics and information processing. Because the creation and use of IT in the performance of tasks is a central area of informing science (IS) research, it follows that better understanding of task complexity should be of great potential benefit to IS researchers and practitioners. Unfortunately, applying task complexity to IS is difficult because no complete, consistent definition exists. Furthermore, the most commonly adopted definition, objective task complexity, tends to be of limited use in situations where discretion or learning is present, or where information technology (IT) is available to assist the task performer. These limitations prove to be severe in many common IS situations.The paper presents a literature review identifying thirteen distinct definitions of task complexity, then synthesizes these into a new five-class framework, referred to as the Comprehensive Task Complexity Classes (CTCC). It then shows the potential relevance of the CTCC to IS, focusing on different ways it could be applied throughout a hypothetical information systems lifecycle. In the course of doing so, the paper also illustrates how the interaction between different classes of task complexity can serve as a rich source of questions for future investigations.
PurposeThis paper aims to examine the current thoughts on knowledge management (KM) and to develop a metaphor to combine these thoughts in a new way that effectively conveys the different types of knowledge and ways of managing it.Design/methodology/approachThe literature on the transition of data to knowledge is reviewed. A popular paradigm in KM states that data are integrated to create information and information is integrated to create knowledge. This paradigm is represented as a pyramid‐shaped hierarchy with knowledge at the top, information in the middle, and data on the bottom. Why this paradigm is a simplistic and limited view of knowledge and KM is discussed.FindingsThe “explicit islands in a tacit sea (EITS)” metaphor is explained and discussed in the context of knowledge and knowledge management (KM).Practical implicationsThe EITS metaphor more accurately and completely describes knowledge in the context of KM. The practical implications of this metaphor are its flexibility and transparency of the transitional actions that affect the evolution of data to knowledge.Originality/valueThe EITS metaphor is an evolution of the prevailing frameworks and removes the apparent limitations in earlier frameworks. The paper provides a paradigm shift in the discussion of KM.
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