Chapter 6 Findings and interpretation – Content analysis

• Published date: 31 December 2010
• DOI: https://doi.org/10.1108/S1479-3512(2011)0000021014
• Pages: 59-62
• Date: 31 December 2010
• Author: Indra Abeysekera

CHAPTER 6

FINDINGS AND INTERPRETATION –

CONTENT ANALYSIS

6.1. INTRODUCTION

This chapter outlines f‌indings for the f‌irst objective of the study from the

model in order to determine the effectiveness of disclosure as predictors

of revenue growth reputation. Section 6.2 outlines the results analysed

by frequency count and sentence count. Section 6.3 outlines the results of

categories of intellectual capital, namely internal, external and human

capital and provides a summary of the chapter.

6.2. REGRESSION ANALYSIS OF INTELLECTUAL

CAPITAL DATA FROM THE CONTENT ANALYSIS

The model included six variables: the number of voting shareholders

(SHD

t

), if the f‌irm is listed or unlisted (OWN

t

), the f‌irm size measured by

total revenue (SIZ

t

), whether or not the f‌irm belongs to a service-based

industry group (IND

t

), whether or not the website has an e-commerce site

(ECO

t

) and the proportion of director and indirect director ownership in the

f‌irm (DIR

t

).

A detailed table of the results is shown in the appendix. The frequency

count showed that narratives were negatively associated with revenue

growth reputation, and the sentence count showed that in 2007 it was

negatively associated with revenue growth reputation (see Appendices 6.A

and 6.B). The visual disclosure count was also negatively associated with

revenue growth reputation as measured by three-year average growth in

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