This document discusses different methods for identifying intellectual capital (IC)-related information from documents, including manual and computer-based content analysis. It describes the process of manual content analysis, which involves developing IC categories, coding information into categories, and analyzing the results. Limitations of the manual method include being labor-intensive and subjective. Computer-based methods like electronic keyword searches were also discussed, along with their limitations like ignoring context. More advanced computer-based tools for IC analysis are described, including dictionary-based tools, concept-based tools, and intelligent taxonomies. The Factiva intelligent taxonomy is highlighted as able to identify both positive and negative IC information from a bottom-up perspective. However, challenges remain around accurately

1. 3rd presentation of IC reporting

2. Method of Identifying IC-related information –content
analysis (Guthrie & Petty, 2000)
Manually VS Computer-based

3. Process of content analysis
“manually”
Develop the categories of IC
Coding (put IC-related information into the
classification based on the selected criterion )
Analysis (the amount of items )

4. Limitation of Manual Type
Manually
Labor-intensive/the volume of text is limited
Different coding methods applications
Coding , Identification and Categorization are
highly subjective (sensitivity, personal bias)
Difficult to replicate studies
Top-down

5. Computer-based Tool
Electronic search (Bontis, 2002)
Process:
 Electronic database (11000 Canadian Annual report)
 Terminology was compiled based on several intellectual
capital books and articles
 Each of these terms was searched individually in the
database.

6. Limitation of Electronic search (Bontis, 2002)
Computer-based
Difficult to recognize the synonyms and
words with multiple meanings
Context of the keywords is ignored
Inadequate to investigate the IC disclose
Top-down

7. The development of Computer-based
tools
• Dictionary keyword-based tools(Lee &
Guthrie, 2010)
• Concept-based tools(Lee & Guthrie, 2010)
• Classification assistant tools(Lee & Guthrie,
2010) Nvivo
• Electronic taxonomies tools(Lee & Guthrie,
2010)
• Intelligent Taxonomy “Factiva” (Lee & Guthrie,
2010)

8. Intelligent Taxonomy “Factiva”

9. Mapping
between accepted IC terms (Guthrie and Petty2000)
and the Factiva (Lee & Guthrie, 2010)
intelligent taxonomy terms

10. Contribution VS Limitation
Factiva (Lee & Guthrie, 2010)
Contribution Limitation
Identify the IC-related information that The mapping is not accurate enough
are not mentioned in the academic (e.g Recruitment )
articles
The contents that are mined are not just The content that are mined are not
limited to the Annual Report transparent enough (e.g marketing )
Neutral and negative news are also Some contents are difficult to be put into
identified practice
Bottom-up method is used

11. The development of the content
analysis
Manually Automatically Intelligent
Annual Reports Sustainability reports (Cinquini,et.al, 2012)
“Positive” “Positive” ”Neutral” ”Negative” (Lee & Guthrie, 2010)
Top- down Bottom-up (Lee & Guthrie, 2010)

12. Content analysis
advantages VS disadvantages
advantages disadvantages
Capture the IC trends in reporting Few explanation of the nature of IC
information allocated to IC categories
Compare the different level of IC disclose Insufficient for discovering potential IC
among the different organizations elements that are not already
declared/revealed in the literature
A technique for analyzing textual Insufficient for the purposes of identifying
repositories underlying relationships of IC
To clear the process of how IC is The contents that are analyzed are quite
categorized by different researchers limited
Benchmarking

13. How to overcome the limitation of content
analysis
Semantic technology
Semantic technology understands the real meaning of words based on
theories of human comprehension
Gives Structure to Unstructured Data
Integrates Data from Multiple Sources
Able to Deeply Mine Data

14. How to use Semantic Technology to
identify IC
The first thing is to develop and refine the
ontology

15. The “top-down” ontology is
developed based on the
literature review
(Lammi,2012)
Good enough?

16. The 1st barrier of developing ontology
“What is IC?”
 Information about employees =?=human capital
 Information about organization=?=structural capital
 Information about customers and suppliers =?=relational capital

17. The 2nd barrier of developing ontology
How to map the IC-related information
with the classification of IC ?
(see the excel)

18. The further research
• How to develop the IC ontology that helps to
identify IC-related information effectively?
• Which intelligent approach can be used to fill
the research gap?

19. Literature Review
• An Yi, & Davey, H. (2010). Intellectual capital disclosure in Chinese (mainland ). Journal of
intellectual capital 11(3), 326-347.
• Bontis, N. (2002). Intellectual Capital Disclosure in Canadian Corporations. Journal of Human
Resource Costing & Accounting.
• Laurence Lock Lee, & Guthrie, J. (2010). Visualising and measuring intellectual capital in capital
markets: a research method. Journal of Intellectual Capital, 11(1), 4-22.
• Lino Cinquini, Emilio Passetti, Andrea Tenucci, & Frey, M. (2012). Anlyzing inellectual capital
information in sustainability reports: some empirical evidence Journal of Intellectual Capital, 13(4).
• Lammi, A. (2012). Intellectual Capital Strategy-Integrating Strategic Management and Intellectual
Capital Ontology
• J.Guthrie, R. P., K. Yongvanich, F.Ricceri. (2004). Using content analysis as a research method to
inquire into intellectual capital reporting. Journal of Intellectual Capital, 5(2), 282-293.
• Viven Beattie , & Thomson, S. J. (2006). Lifting the Lid on the use of Content analysis to investigate
intellectual capital disclosure.
• Mouritsen, J. (2009). Classification, measurement and the ontology of intellectual capital entities
Journal of Human Resource Costing & Accounting, 13(2), 154-162.
• Mouritsen, J. (2006). Problematising intellectual capital research: ostensive versus performative IC.
Accounting, Auditing& Accountability Journal 19(6), 820-841.

20. Thank you very much!