The effect of firm specific characteristics on segment information disclosure a case of indian listed companies

International Journal of Management (IJM), ISSN 0976 – 6502(Print), ISSN 0976 - 6510(Online),
Volume 5, Issue 9, September (2014), pp. 41-48 © IAEME
INTERNATIONAL JOURNAL OF MANAGEMENT (IJM)
ISSN 0976-6502 (Print)
ISSN 0976-6510 (Online)
Volume 5, Issue 9, September (2014), pp. 41-48
© IAEME: http://www.iaeme.com/IJM.asp
Journal Impact Factor (2014): 7.2230 (Calculated by GISI)
www.jifactor.com
41

IJM
© I A E M E
THE EFFECT OF FIRM-SPECIFIC CHARACTERISTICS ON SEGMENT
INFORMATION DISCLOSURE: A CASE OF INDIAN LISTED COMPANIES
F J Peter Kumar
Assistant Professor, School of Business, Leadership and Management, Karunya University,
Coimbatore, Tamil Nadu, India
ABSTRACT
The subject of segment information disclosure practices among various companies are under
consideration by the users of the financial statements. The users of the financial statements and the
investors in general are keen to know the performance of the companies in which they are interested
for investing. In today’s business environment, the concept of globalization has entered every
business persons mind and therefore the companies go on a widespread hunt for entering the market
on a global platform. In the process of globalization, the information provided by the companies
should be useful for the investors in understanding the quantum of business they perform. Thus, The
Institute of Chartered Accountants of India has pronounced Accounting Standard 17 on Segment
Reporting. The researcher in this article tries to bring out the effect of firm-specific characteristics on
segment information disclosure with special reference to the Indian Listed Companies.
Keywords: Segment Reporting; Information Disclosure; Accounting Standard; Firm-Specific
Characteristics; Disclosure Index, Average Variance Extracted.
1. INTRODUCTION
Segment Information Disclosure by the companies are much expected by the users of the
financial statements and the investors. The users of the financial statements and the investors need to
have a better understanding on the progress of the company in which they have an interest to invest.
The investors always have a watch over the overall performance of the companies and observe the
trend in which the market price of the share moves and thereby they try in increase the investments
in the company which has an upward trend in the market. The researcher has considered several
firm-specific characteristics and studied the effect on the segment information disclosure practices of
the companies in accordance of the accounting standard 17 issued by The Institute of Chartered
Accountants of India.

42
2. THEORETICAL FRAMEWORK

The level of segment information disclosure practices adopted by the companies are
increasing over the past ten years. The companies are also having an opinion that more information
on the segments they operate are to be reported independently so that the investors will be aware on
the varied business they involve and also the areas of operations the companies have kept their foot
on. The investors in turn are benefitted to have an adequate knowledge on the performance of the
companies by analysing the varied information disclosed by the companies segment-wise and
thereby take a decision in their investment pattern. As such, the study on the effect of firm-specific
characteristics on segment information disclosure practices by the Indian Listed Companies will help
the users of the financial statements and the investors in making a proper decision for their
investments.
3. EXTANT LITERATURE
Mishari M. Alfaraih and Faisal S. Alanezi (2011) examined both the segment disclosure
practice of Companies listed on the Kuwait Stock Exchange (KSE) and the factors that influence
their level of segment disclosures. Vakhrushina M A (2011) propounded that in the modern
unstable economic environment, the competitiveness arising in the individual economy branches and
the financial crisis make the commercial organisations to approach new management technologies.
Cho, Joong-Seok (2010) empirically investigates the effect of implementation of SFAS No. 131 on
companies’ information environments by assessing the effect of interim period financial reports.
Samuel Jebaraj Benjamin et.al., (2010) revealed that in the increasing complexity of business
enterprises and the growing popularity of conglomerate type businesses, it has become clear that
consolidated financial statement reporting, while obviously necessary, may not necessarily provide
users with sufficient insights for the making of informed decisions. Mohammed Talha et.al., (2009)
investigated whether competitive disadvantage is experienced by Malaysian Companies as they
disclose segmental information under the new accounting standard known as FRS 114, Segment
Reporting. Kanogporn Narktabtee and Manatip Chankitisakul (2007) examined segment
reporting practices of the listed company during 1994-2005 by using the TAS No. 24 segment
reporting as a benchmark. Sanjiv Agarwal (2007) indicates that the most of the public sector banks
have been following the RBI directions on clarification of business segments while a few private
sector banks have been reporting as per the Accounting Standard-17.
4. RESEARCH DESIGN AND METHOD
The Accounting Standard – 17 has been implemented among enterprises in India having their
securities traded publicly and other economically significant entities, including subsidiaries by The
Institute of Chartered Accountants of India. According to the Standard, an entity should report its
segmental information classified by business and (or) geographical areas in the annual reports of the
companies. Accordingly, the research is being carried out by conducting a thorough study on the
annual reports of Select Indian Listed Companies during the year 2011-12 on the effect of firm-specific
characteristics on the segment information disclosure of the companies.
4.1 Sampling Design
The population for the study is consisting of India’s Top 500 Companies, published by the
Economics Times, “ET 500 List, 2010”, and the method of sampling used for this study is a
technique called as the “clustering sampling technique”. These Companies are the listed companies

in the Bombay Stock Exchange or the National Stock Exchange of India during 2001 -2002 to 2011 -
2012. This study requires financial statement information, in particular the notes to financial
statements, which is found in the annual reports of the companies. The annual reports of these
companies are extracted from the company’s web site under the investor relations column and the
PROWESS data base provided by CMIE (Centre for Monitoring Indian Economy). The sample size
for the study comes to 125 companies falling under the major 6 industries which is given as follows :
43

Table 1: Sample of the selected Indian Listed Companies
Industry Automobile Cemen
t
Chemical
s
Computer
s
Constructio
n
Pharmaceutic
als
No. Of
Companies
(125)
22 13 10 24 30 26
4.2 Analytical Design
To investigate the effect of firm-specific characteristics on the segment information
disclosure among the select Indian Listed Companies, Path Co-efficient Analysis was performed by
the researcher using Path Least Square Model.
4.3 Measuring the extent of Segment Disclosure
The disclosure index is developed using the indicators selected based on the mandatory
disclosure requirements issued by The Institute of Chartered Accountants of India. The annual report
of the selected Indian Companies during the period 2011-12 was examined and an item-based
approach using a dichotomous procedure in which an item scores one if it is disclosed and zero
otherwise was followed. In the most common approach, the concept of ‘disclosure index’ was first
used by Buzby (Buzby, S. L. (1975)) and Stanga (Stanga, K.G. (1976)) and formalized by Cooke
(Cooke, T. E. (1989a); Cooke, T. E. (1989b)).
The researcher summarizes the determination of the index as follows:

Index = Actual disclosure/Total possible disclosure =
Where d = 1 if item di is disclosed and 0 if item di is not disclosed, m = number of items
disclosed and n = maximum number of disclosure items possible. The index is a ratio comparing the
actual level of disclosure and the possible level (thus not penalizing the company for non-disclosure
of irrelevant items).
5. RESULTS OF THE STUDY
To determine the effect of the company’s firm-specific characteristics on the segment
disclosure level among the Indian Listed Comapanies are performed using the inter-correlation
matrix (not shown here). In order to study the direct response and the indirect response of each of
the explanatory variables (firm-specific characteristics) through other independent variables (firm-specific
characteristics) on the dependent variable (Disclosure Index), Path Coefficient Analysis is
performed. The direct effect of each of the explanatory variables (firm-specific characteristics) on the
dependent variable (Disclosure Index) and the indirect effect of each explanatory variable (firm-specific
characteristics) on the dependent variable (Disclosure Index) through other explanatory
variables (firm-specific characteristics) are furnished in Table No. 2.

44

Table 2: EFFECT OF THE FIRM-SPECIFIC CHARACTERISTICS ON THE SEGMENT
REPORTING DISCLOSURE LEVEL
Variables Log
Total
Assets
Log
Sales
Log
Market
Capitali
sation
Levera
ge
ROI ROE ROS Owners
hip
Diffusio
n
Grow
th
Rate
Market
Expectatio
n
Size
of the
Audit
Firm
Disclos
ure
Index
Log Total
Assets
0.13 0.07 0.13 -0.04 0.03 0.00 0.00 -0.04 0.00 0.03 0.00 0.33
Log Sales 0.04 0.25 0.07 0.00 -0.01 0.01 -0.02 -0.03 0.01 0.02 0.00 0.35
Log Market
Capitalisation
0.06 0.06 0.32 0.06 -0.10 0.03 0.02 -0.09 0.01 -0.02 0.01 0.34
Leverage 0.02 -0.01 -0.09 -0.19 0.13 -0.03 -0.01 0.03 0.01 0.03 0.00 -0.11
ROI -0.01 0.00 0.11 0.09 -0.28 0.06 0.02 -0.02 0.01 -0.02 0.00 -0.04
ROE 0.00 0.02 0.12 0.07 -0.22 0.08 0.01 -0.03 0.01 -0.02 0.00 0.05
ROS 0.01 -0.04 0.06 0.02 -0.05 0.01 0.10 -0.01 0.00 -0.01 0.00 0.11
Ownership
Diffusion
-0.03 -0.04 -0.17 -0.03 0.04 -0.01 -0.01 0.16 -0.01 0.02 0.00 -0.09
Growth Rate 0.00 0.02 0.02 -0.01 -0.02 0.01 0.00 -0.02 0.11 0.00 0.00 0.11
Market
Expectation
0.04 0.04 -0.06 -0.06 0.05 -0.01 -0.01 0.03 0.00 0.11 0.00 0.13
Size of the
Audit Firm
0.00 0.03 0.15 0.07 -0.06 0.01 0.01 -0.05 0.01 0.01 0.01 0.21
The results from Table 2 reveals that Log Total Assets, Log Sales and Log Market
Capitalisation have higher positive direct effect on the Disclosure Index among all other firm-specific
characteristics. This shows that all these three firm-specific characteristics, namely, Log
Total Assets, Log Sales and Log Market Capitalisation are having a higher positive direct effect on
the level of disclosure on segments among the Indian Listed Companies. It is further observed from
the results from Table 2, that the performance parameter Log Total Assets has higher positive
indirect effect on the level of disclosure on segments through other two firm-specific characteristics,
namely, Log Sales and Log Market Capitalisation. Similary, the performance parameter Log Sales
has positive indirect effect on the level of disclosure on segments through the other two firm-specific
characteristics, namely, Log Assets and Log Market Capitalisation. In the same manner, the

performance parameter Log Market Capitalisation has positive indirect effect on the level of
disclosure on segments through the other two firm-specific characteristics, namely. Log Total Assets
and Log Sales. Thus, it is observed that the three firm-specific characteristics, namely, Log Total
Assets, Log Total Sales and Log Market Capitalisation are considered to be substantially important
contributing variables in determining the effect on the level of segment information disclosure
(Disclosure Index). These three firm-specific characteristics are included in this study as a measure
of the size of the firm. This shows that Size of the Company is a significant factor in determining the
effect on the level of segment information disclosure (Disclosure Index).
45

Table 3 reveals the reliability and the average variance extracted in determining the effect of
the firm-specific characteristics on the segment reporting disclosure level. As Cronbach’s tends to
provide a severe under estimation of the internal consistency reliability of latent variables in PLS
Path Models, it is more appropriate to apply a different measure, the composite reliability. The
composite reliability takes into account that indicators have different loadings, and can be interpreted
in the same way as Cronbach’s . An internal consistency reliability value above 0.7 in early stages
of research are regarded as satisfactory whereas a value below 0.6 indicates a lack of reliability. It is
noted from the table that except the profitability variable, all other variables considered for the study
are having the composite reliability of more than 0.7 which is a satisfactory measure. For the
assessment of validity, the researcher has tested the convergent validity which signifies that a set of
indicators represents one and the same underlying construct, which can be demonstrated through
their unidimensionality. The average variance extracted is a suggested criterion of convergent
validity. An AVE value of at least 0.5 indicates sufficient convergent validity, meaning that a latent
variable is able to explain more than half of the variance of indicators on average. The results from
the table 6.43 reveal that except profitability, all other variables are above 0.5 which shows that
convergent validity of all the construct variables except profitability is satisfactory. The Path model
showing the effect of the firm-specific characteristics on the segment reporting disclosure level is
shown in Figure 1.
Table 3: RELIABILITY AND THE AVERAGE VARIANCE EXTRACTED FOR THE
PARTIAL LEAST SQUARE PATH ANALYSIS
Construct Variables Composite Reliability AVE
Size of the company 0.779336 0.541051
Leverage 1.000000 1.000000
Profitability 0.492929 0.342527
Ownership diffusion 1.000000 1.000000
Growth rate 1.000000 1.000000
Market expectation 1.000000 1.000000
Size of the audit firm 1.000000 1.000000
Disclosure index 1.000000 1.000000

46

The variables included in the model are as follows:
Size – Size of the Company; Leverage – Leverage; Profit – Profitability; Owner – Ownership
Diffusion; Grow – Growth Rate; Mark – Market Expectation; Auditor – Size of the Audit Firm;
DISIND – Disclosure Index
Figure. 1: EFFECT OF THE FIRM-SPECIFIC CHARACTERISTICS ON THE SEGMENT
REPORTING DISCLOSURE LEVEL USING VISUAL PARTIAL LEAST SQUARE PATH
ANALYSIS
The nonparametric bootstrap procedure can be used in PLS path modeling to provide
confidence intervals for all parameter estimates, building the basis for statistical inference. In
general, the bootstrap technique provides an estimate of the shape, spread, and bias of the sampling
distribution of a specific statistic. Bootstrapping treats the observed sample as if it represents the
population. The procedure creates a large, pre-specified number of bootstrap samples. Each bootstrap
sample should have the same number of cases as the original sample. Bootstrap samples are created
by randomly drawing cases with replacement from the original sample.

47

Table 4: THE RELATIONSHIP BETWEEN THE FIRM-SPECIFIC CHARACTERISTICS
AND THE DISCLOSURE INDEX USING THE STRUCTURAL MODEL – BOOTSTRAP
Entire
Sample
estimate
Mean
of
Subsamples
Standard
error
T-Statistic
Size-Disclosure Index 0.4850 0.5099 0.0870 5.5761
Leverage-Disclosure Index -0.1130 -0.1663 0.0861 -1.3122
Profitability-Disclosure Index 0.0990 0.1428 0.1120 0.8842
Ownership Diffusion-Disclosure
Index
0.1540 0.1667 0.0645 2.3886
Growth Rate-Disclosure Index 0.0930 0.1317 0.0831 1.1190
Market Expectation-Disclosure
Index
0.0880 0.0810 0.0520 1.6907
Size of the Audit Firm-
Disclosure Index
0.0470 0.0794 0.0543 0.8659
PLS estimates the path model for each bootstrap sample. The obtained path model
coefficients form a bootstrap distribution, which can be viewed as an approximation of the sampling
distribution. The PLS results for all bootstrap samples provide the mean value and standard error for
each path model coefficient. This information permits a student’s t-test to be performed for the
significance of path model relationships. The researcher has used the bootstrap structural model to
test the significance of path model relationships based on the t-statistic from the results showed in
table 6.44. The results from the table reveal that the t-statistic for Size with the Disclosure Index is
the highest having 5.571 which shows that there is a significant association between the size of the
company and the disclosure level more than any of the firm-specific characteristics considered for
the study.
6. CONCLUSION AND DISCUSSION
The factors Log Total Assetss, Log Sales and Log Market Capitalisation have a direct effect
on the segment information disclosure index. In this observation, these three firm-specific
characteristics contribute more towards the improvement in the performance level of the companies
by having disclosed more segment-wise information in their annual reports. The results also reveal
that the firm-specific character, the size of the company has a significant association with the

disclosure level more than any of the other firm-specific characteristics considered for the study as
per the bootstrap stuctural model.
48
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The effect of firm specific characteristics on segment information disclosure a case of indian listed companies

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