Marginalized Knowledge: An Agenda for Indigenous Knowledge Development and Integration with Other Forms of Knowledge

2. Purpose of the study

This study builds on the aforementioned studies and seeks to examine the literature of KM and a few related concepts as published and indexed in the Science Citation Index (SCI) and Social Sciences Citation Index (SSCI) in terms of the:

1. 
   Total number of publications
   
2. 
   Yearly Distribution of the records
   
3. 
   Growth of the literature between 1981-2007 by determining the number of
   
   1. 
      Authors
      
   2. 
      Countries
      
   3. 
      Document types
      
   4. 
      Institutions
      
   5. 
      Language
      
   6. 
      Sources
      
   7. 
      Subject categories
      

3. Methodology

Two sources (i.e. SCI and SSCI) were used to extract relevant data between April 10^th and 14^th, 2007. The two bibliographic databases, produced by the Thompson Scientific (formerly the Institute for Scientific Information), share a search platform, a situation that made it easy to conduct single searches within the two databases at the same time (see Fig 1 below).

Fig 1: ISI web of science advanced search interface

A total of 20 keywords were purposefully selected and used to extract data on KM and its related concepts. These were:

• 
  Knowledge Management
  
• 
  Intellectual Capital
  
• 
  Knowledge Production
  
• 
  Organizational Knowledge
  
• 
  Corporate Knowledge
  
• 
  Implicit Knowledge
  
• 
  Explicit Knowledge
  
• 
  Tacit Knowledge
  
• 
  Knowledge Acquisition
  
• 
  Knowledge Transfer
  
• 
  Knowledge Creation
  
• 
  Knowledge Development
  
• 
  Indigenous Knowledge
  
• 
  Repackaging knowledge
  
• 
  Knowledge re-use
  
• 
  Knowledge organization
  
• 
  Knowledge visualization
  
• 
  Knowledge representation
  
• 
  Knowledge ecosystems
  
• 
  Corporate memory
  

These keywords were selected from a list of knowledge management-related concepts provided by Wikipedia Encyclopaedia³⁷. The selection was conducted in such a way as to include processes of knowledge management and different types of knowledge. As mentioned before, it is believed that knowledge management is at its initial stages of development and therefore although the list provided above cannot be said to be exhaustive, it is representative of knowledge management concepts. Furthermore, we assumed that we cannot determine future prospects of knowledge management if we exclude what is being managed, i.e. knowledge. Hence the inclusion of terms describing different types of knowledge, such as explicit, tacit, corporate, indigenous, and implicit knowledge.

Each of these terms was fed into the search query box as shown in Fig 1. An advanced search mode was used to search for relevant records. The search was limited to the ‘TS’ field. ‘TS’ stands for Topic field, where one enters a word or phrase to search for article titles and abstracts following certain search rules, e.g. the use of truncation, wildcards, capitalization, phrase searching, hyphenated words, apostrophes, Boolean search operators, and parentheses. Notably, all the search terms that were used in this study to extract knowledge management-related records were phrases, a situation that necessitated the use of quotation marks. The idea was to download documents that contained an exact phrase within their titles, abstracts, and/or keyword fields. Phrases which did not yield any record were excluded from the final analysis.
Data was captured and stored as txt files and cleaned of duplicate and irrelevant records using the Notepad text editor. Data analysis was conducted using Sitkis software. Sitkis is citation data processing software. The software imports ISI Web of Science files into a Microsoft Access database that can be easily modified. Sitkis also exports data from the database into UCINET compatible network graphs and Excel-compatible reports. The purpose of the program is to enable researchers to easily and quickly download and analyze bibliometric records. The software is capable of performing the following tasks:

• 
  2-mode factor analysis
  
• 
  Calculation of article similarity based on common preferences
  
• 
  Calculation of co-citation networks from article-to-reference data
  
• 
  Calculation and preparation of author co-authorship networks and frequencies
  
• 
  Calculation of institutional contributions and collaboration networks
  
• 
  Cross-border research collaboration
  
• 
  Calculation of article cross-citations
  
• 
  Generation of the following types of statistics:
  
  • 
    Reference statistics
    
  • 
    Yearly citation statistics
    
  • 
    Article statistics
    
  • 
    Article / reference centrality statistics
    

Data was analyzed in order to obtain the total number of records per concept; yearly distribution of the records for each concept; a graph showing the trend of productivity; growth in the number of authors, institutions, countries, languages, document types, sources and subject categories; and the total number of citations and average citations per record.

4 Results

This section provides the results as follows:

1. 
   Productivity of records on KM and its related concepts
   
2. 
   Trend of productivity for each concept
   
3. 
   Growth of KM literature and its related concepts
   
4. 
   Subject categories utilizing and contributing to KM theory, practice and development
   
5. 
   Growth in the number of records vis-à-vis citations