Intellectual capital disclosure in private sector listed companies in India

Received: 24 January 2017

Revised: 29 November 2017

Accepted: 22 December 2017

DOI: 10.1002/kpm.1560

RESEARCH ARTICLE

Intellectual capital disclosure in private sector listed companies in India Dyna Seng

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Sriyalatha Kumarasinghe

Department of Accountancy and Finance, University of Otago, Dunedin, New Zealand Correspondence Dyna Seng, Department of Accountancy and Finance, University of Otago, PO Box 56, Dunedin, New Zealand. Email: [email protected]

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Rakesh Pandey

This study aims to investigate the extent and variety of voluntary intellectual capital disclosure (ICD) by listed private firms in India. It also compares the level of ICD of firms in the high‐IC‐intensive and low‐IC‐intensive industry sector. In addition, it evaluates the effect of firm size on ICD levels. Consistent with previous ICD research, the results show that relational capital (in particular about “brands and customers”) is the most frequently reported, followed by human capital, and lastly structural capital. In addition, the extent and variety of voluntary ICD by large firms is higher than that of small firms. Again, consistent with prior research, high‐IC‐intensive firms disclose significantly higher IC than low‐IC‐intensive firms. The findings of this study can have implications for regulators, who may want to be aware of how voluntary ICD influences and informs users. This study is one of the few that examines the extent of firms' voluntary ICD in India. It is the first to investigate the extent and variety of voluntary ICD by incorporating two different measures— count and presence—of each component of ICD.

1

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I N T RO D U CT I O N

undergoing transformation, the Indian market is still underdeveloped, and IC reporting is in the infancy stage, like other developing countries

Intellectual capital (IC) is a significant resource (Drucker, 1993) and an

(Kamath, 2008). Few studies looking at the growing importance of IC

excellent source for generating wealth (Edvinsson & Sullivan, 1996).

for the Indian economy have focused on analysing IC reporting in India

In the era of globalised competition and the recent growth in knowl-

(Kamath, 2007; Kamath, 2008; Singh & Kansal, 2011). Prior studies

edge‐based companies in the world economy, measuring and

have mainly focused on voluntary ICDs of a particular sector. For

reporting IC has garnered much attention and recognition in the busi-

example, Kamath (2007, 2008) analysed ICDs published by Indian

ness world. However, the nature of IC disclosure (ICD) is not yet

companies in the communication and technology sector, banking sec-

clear. Some researchers claim that even though the disclosure of IC

tor, and pharmaceutical industries. Unlike prior studies, this study is

is not mandatory in financial statements, more and more enterprises

not sector‐specific, instead, the study explores the IC disclosure in a

supply IC information in their annual reports (Ramanauskaite &

sample of top 100 listed firms in India. Our study complements prior

Rudzioniene, 2013). With the introduction of an integrated reporting

studies by exploring the extent (measured by count) and variety (mea-

framework, there is also a derived demand for IC information. How-

sured by presence) of IC disclosure made by large Indian firms. Specif-

ever, despite the interest and demand for this information, relatively

ically, we examine the extent and variety of ICD of the top 100 Indian

few large firms disclose IC voluntarily (Bhasin, 2014). The mismatch

firms by market capitalisation for the 2011 financial year in high‐IC‐

between the findings in the existing research encourages thorough

intensive and low‐IC‐intensive industries.1 We also examine the level

research in the same area. This study explores the extent and variety

of ICDs made by different firm sizes.

of the voluntary ICDs published by the top 100 listed private sector

The following research questions are addressed in this study.

firms in India. It also evaluates the influence of size and industry on

What is the extent and variety of voluntary ICD made by the top

ICD levels.

100 listed firms in India? What is the extent and variety of voluntary

Knowledge is one of the key sources of economic growth that cre-

ICD made by firms of different size and industry? Two different mea-

ates both opportunities and challenges for a developing economy like

sures (count and presence) of ICDs were examined, and they were cal-

India (Dahlman & Utz, 2005). Since the economic reforms in 1991,

culated for each component of IC, namely, structural capital (SC),

India has been transforming itself into a knowledge economy, and this

relational capital (RC), and human capital (HC).

transformation has played an important role in achieving higher eco-

The remainder of this study is organised as follows. Section 2 pre-

nomic growth (Raghwan, 2009). Although the Indian economy is

sents the prior literature. The research design is developed in Section 3,

Knowl Process Manag. 2018;25:41–53.

wileyonlinelibrary.com/journal/kpm

Copyright © 2018 John Wiley & Sons, Ltd.

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whereas Section 4 presents the results. Section 5 contains the

work practices, climate, information flow, performance improvement

conclusions.

processes, training and development, reward and recognition; and knowledge management dimensions of process, leadership, culture, technology, and measurement have a positive impact on learning orga-

2

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LITERATURE REVIEW

nisation dimensions. It also highlights their capacity and motivation in the private sector to apply knowledge in various ways in learning for

The field of knowledge management/IC grows at an accelerated rate

enhanced performance and efficiency.

(Booker, Bontis, & Serenko, 2008). The terms IC, knowledge‐based assets, and intangible assets are commonly used interchangeably. In the field of accounting, we come across the words “intangible assets”

2.1

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Size and industry effects on IC disclosure

more often than “intellectual capital.” The concept of IC was originally

Bozzolan, Favotto, and Ricerri's (2003) study on the ICDs of 30 nonfi-

used by Skandia, a Swedish insurance company, to illustrate different

nancial Italian companies claimed that although size and industry were

forms of organisational capital. Skandia defined IC as “the possession

not significant factors in determining the amount and the content of

of knowledge, applied experience, organizational technology, customer

ICDs, as found in social and environmental disclosure studies, Italian

relationships and professional skills” (Edvinsson, 1997, p.368) that pro-

companies disclosed RC extensively. Research in China (mainland) con-

vide Skandia with a competitive edge in the market. In the face of

firmed that larger firms report more IC relative to smaller firms and

fierce competition, businesses compel to reassess their business pro-

there was a positive relationship between corporate performance

cesses for better efficiency and accountability (Zarei, Chaghouee, &

and ICD. However, industry type did not have a significant influence

Ghapanchi, 2014). Insufficient process orientation may lead to costly

on IC reporting (Yi, Davey, & Eggleton, 2011). Revealing some con-

slow processes due to nonvalue added activities (Reijers, 2006).

trasting results, the study by Bruggen, Vergauwen, and Dao (2009)

Prior studies have shown that knowledge management and IC practices have a positive impact on the performance of organisations

on 125 Australian listed companies concluded that industry type and firm size were key determinants of ICD.

(Hejazi, Ghanbari, & Alipour, 2016) and their internal learning pro-

Examining the ICDs of 25 listed companies in the Ghana Stock

cesses (Bontis, Crossan, & Hulland, 2002). There is no single definition

Exchange over a 5‐year period (2006–2010) through content analysis,

of IC. Past academic literature identifies three main components of IC:

Asare, Onumah, and Otieku (2014) concluded that the banking,

SC (or internal), RC (or external), and HC. SC corresponds to

finance, and insurance sectors tend to disclose more IC in their annual

institutionalised and codified knowledge created by a firm's informa-

reports, and there were marginal increases in average ICD levels over

tion technology systems and operating procedures such as databases,

the 5 years. Scaltrito's (2014) study on 186 listed companies in Italy

patents, copyrights, information, and networking systems and manage-

constructed and used an index based on various previous studies and

ment processes. RC encompasses brands and organisational relation-

tested against size, Big 4, leverage and ownership, and confirmed a

ships through interactions between individuals and organisations

positive association between firm size and ICD. In summary, the

identified as customers, suppliers, social agents, and various other

above‐mentioned studies share some mixed results on size and indus-

stakeholders during its basic business processes.HC refers to

try effects.

employee competence recognised through their tacit and explicit knowledge (Edvinsson & Malone, 1997; Guthrie & Petty, 2000). Company size and industry are likely to be key determinants of the

2.2

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IC disclosures in the Indian context

level of ICD. Large companies tend to be more progressive and innova-

There has been some research undertaken on ICDs in Indian firms

tive because they have the financial resources (Guthrie, Petty, &

which paint a vivid picture. The majority of those studies are on partic-

Ricceri, 2006). Similarly, knowledge‐intensive industries heavily rely

ular industries. Kamath (2007) investigated the ICD in Indian banking

on IC and therefore tend to disclose more of their IC to gain competi-

sector firms with an objective to estimate and assess their value‐added

tive advantage (Leonard‐Barton, 1992).

intellectual coefficient for a period of 5 years (2000–2004). After

However, referring to the factors that hinder the wider accep-

analysing all 98 commercial banks, his study revealed that the top per-

tance of IC reporting, Andrikopoulos (2010) reports that difficulties in

formers are big foreign banks with high technology‐intensive systems

codifying IC components due to their interdependent nature, translat-

and limited HC. Most of the public banks are average performers with

ing IC related qualitative information into monetary values, and ineffi-

a high level of HC.

ciency of capital markets for IC are major factors that hinder the wider

Joshi and Ubha (2009) analysed IC reporting in 15 Indian compa-

acceptance of IC reporting. He further argues that non‐existence

nies in the information technology sector and demonstrated that IC

reporting framework for IC reporting and absence of direct monetary

disclosures in information technology companies were almost negligi-

rewards for IC reporting are some of the major challenges for the the-

ble. They confirmed the findings in Kamath (2008). Applying Guthrie

orists and the practitioners of IC (Andrikopoulos, 2010). Therefore, it is

and Petty's (2000) approach, Singh and Kansal (2011) conducted

important to align practitioners' needs and research outcomes. Hence,

research on the top 20 pharmaceutical companies in India. They

the goal of research should be to create knowledge that managers may

focused on market‐to‐book value and found that RC was the most

utilise to advance practice (Booker et al., 2008). According to Chawla

disclosed capital. However, according to Singh and Kansal (2011), ICDs

and Joshi (2011), private sector organisations in India are far better

are relatively low and varying among firms. Singh and Kansal's findings

on all dimensions of learning organisations, namely, vision and strategy,

on low ICD in financial statements have been reconfirmed by Mondal

SENG

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and Ghosh (2014) in their study on 30 Indian knowledge‐intensive

3

R ES E A RC H D ES I GN

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firms. Bhatia and Mehrotra's (2016) study on 40 banks in India has found an influencing relationship between ICD and firm characteristics

3.1

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Sample

such as size, level of risk, HC pressure, and board composition (see The data used in this study were collected from annual reports2 of the

Table 1). However, it is interesting to note that none of the above studies

top 100 private firms by market capitalisation listed on the Bombay

on Indian companies have paid attention to the variety or presence

Stock Exchange (BSE) in India for the 2011 financial year. Data for

of ICD. In this study, we examine relationships between two different

market capitalisation were collected from the datastream database,

measures: count and presence of overall ICD and its three

and industry information was gathered from the BSE website.

components.

Established in 1875, BSE is Asia's first stock change and world's

TABLE 1

Key features of prior studies regarding IC disclosure using content analysis Method: Content analysis Descriptive (CA) (Y/N)

IC items Focus

Country

Sample

Guthrie and Petty (2000)

Australia

20 largest listed companies

CA

Y

24

Key components of IC

Key components Sveiby (1997) IC framework of IC are poorly understood and a comprehensive framework has not been developed.

Brennan (2001)

Ireland

11 listed companies

CA

Y

24

Market and book values are compared

Knowledge‐based Sveiby (1997) IC framework, Irish listed Guthrie and Petty companies have (2000) a substantial level of IC assets.

Bozzolan et al. (2003)

Italy

30 nonfinancial firms (15 high profile, 15 low‐ profile)

CA

N

22

Firm size and industry

More disclosures Modified Guthrie and Petty (2000) on external capital. Industry and size are not important

Abeysekera and Guthrie (2005)

Sri Lanka

30 largest listed companies

CA

Y

45

Key components of IC

External capital was the most reported category and the second most was human capital

Guthrie et al. (2006)

Hong 100 companies (Hong Kong, Kong) and 50 largest Australia listed companies (Australia)

CA

Y

24

Firm size

Disclosure level is Sveiby (1997) IC framework positively related to company size

Oliveira, Rodrigues, and Craig (2006)

Portugal

CA

N

32

Firm size, industry, leverage, ownership concentration, auditor

IC disclosure level An index based on various previous is influenced by studies size, ownership, type of auditor and industry

Vergauwen et al. (2007)

Sweden, 20 firms of each country the UK, Denmark

CA

Y

108

Key components of IC, IC indicators, HC indicators, structural capital (SC) indicators, relational capital (RC) indicators

Strong significant Guthrie and Petty (2000), Bontis positive et al. (2002) correlation between the level of SC in firms and SC disclosures. HC and RC in firms do not have associations with HC and RC disclosures

Kamath (2008)

India

CA

Y

39

Technology industry

IC reporting in the Bontis (2003) IT sector is negligible

56 listed companies

30 “Teck” firms

Findings

Framework for IC

Study


(Continues)

44 TABLE 1

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ET AL.

(Continued)

Study

Country

Sample

Method: Content analysis Descriptive (CA) (Y/N)

IC items Focus

Findings More disclosures in external capital

Framework for IC Guthrie and Petty (2000)

Oliveras et al. Spain (2008)

12 Spanish listed companies

CA

N

25

Market and book values in different industries

Bruggen et al. Australia (2009)

125 listed companies

CA

N

36

Modified Industry, firm size, Firm size and methodology of information industry are key Bontis (2003) and asymmetry determinants of Vergauwen and IC disclosure van Alem (2005)

Whiting and Miller (2008)

New Zealand

70 listed companies

CA

N

18

Market value, book value

Joshi and Ubha (2009)

India

15 top companies in the IT CA industry

Y

39

Knowledge sector IC reporting in the Bontis (2003) IT sector is negligible

Yi and Davey (2010)

China

49 dual‐listed firms

CA

Y

26

Extent and quality Level of IC of IC disclosure disclosure and quality is not high

Yi et al. (2011)

China

49 dual‐listed firms (22 service, 27 industry), 20 large and 29 small firms

CA

Y

26

Firm size, industry Industry was not Modified Guthrie and Petty (2000), significant. Firer and Larger firms Williams (2003), report more IC. Oliveira et al. Corporate (2006) performance and IC disclosure were positively related.

Analyst reports from 67 businesses

CA

Y

34

Describe a methodology on what and how IC information is communicated in analyst reports

Suggested methodology has been applied on a sample and showed the applicability of the method by future researchers.

Abhayawansa (2011)

Positive relationship between the “hidden value” (difference between market and book values) IC disclosure


Schneider and Samkin (2008)

Rogers and Grant (1997), Unerman, Guthrie, and Striukova (2007)

Singh and Kansal (2011)

India

Top 20 listed pharmaceutical companies

CA

Y

24

Market to book value

Guthrie and Petty ICDs are low, (2000) narrative, and varying among firms. External capital has been disclosed mostly.

Asare et al. (2014)

Ghana

25 companies over a 5‐ year period (2006– 2010)

CA

Y

30

Industry

Index based on Marginal modified Guthrie increases in the et al. (2006), overall average IC disclosure Oliveira et al. levels. Banking, (2006), Wagiciengo and finance, and Belal (2012) insurance sector disclose significantly more than others.

Mondal and Ghosh (2014)

India

30 knowledge‐intensive firms

CA

N

45

Size, age, leverage, audit

Intellectually efficient companies

VAIC™ model Pulic (2000)

(Continues)

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ET AL.

TABLE 1

(Continued)

Study

Country

Method: Content analysis Descriptive (CA) (Y/N)

Sample

IC items Focus committee size, profitability

Findings

Framework for IC

disclose less information in the financial statements. Committee size, age, firm size positively related to IC disclosure.

CA

N

31

Size, Big 4, leverage, ownership

Positive association between firm size and IC disclosure

Index based on various previous literature

Abhayawansa Bangladesh 16 pharmaceutical and Azim companies (2014)

CA

N

33

Format, news‐ tenor, time‐ orientation

No consistent framework for IC reporting.

Abhayawansa (2011)

Bhatia and Mehrotra (2016)

CA

N

44

Size, risks, ICD is influenced efficiency, age, by size, risk, human capital human capital pressure, and board ownership composition. pattern, leverage, structure, board composition

Scaltrito (2014)

Italy

India

186 listed companies

40 banks

Haji and Mubaraq (2012)

Note. IT = information technology; IC = intellectual capital; ICD = intellectual capital disclosure; HC = human capital.

number‐one exchange in terms of listed companies. More than 5,500

(containing 108 terms) pertaining to each component of IC (SC, RC,

companies are listed on BSE, for a total market capitalisation of

and HC) is adopted from Vergauwen et al. (2007).4 Two different

3

USD1.64 trillion as of September 2015. The largest 100 private sector

measures were collected for the ICDs. These measures are count and

firms were chosen as they are likely to be more progressive and inno-

presence of an IC disclosure. The two measures were calculated for

vative and take the lead in the area of IC reporting due to their size and

each SC, RC, and HC. The sum of all three of these formed the total

the financial resources at their disposal (Guthrie et al., 2006; Guthrie &

IC disclosures.

Petty, 2000). Prior studies of ICDs have mainly used content analysis

The “count” variable captures the extent of disclosure. It is calcu-

to capture IC disclosures (Abeysekera, 2007, 2008; Abeysekera &

lated as the sum of all the valid ICDs contained in the relevant annual

Guthrie, 2005; April, Bosma, & Deglon, 2003; Beattie & Thomson,

report.5 The “presence” variable captures the variety of disclosure. If a

2007; Brennan, 2001; Bontis, 2003; Bozzolan et al., 2003; Guthrie &

word from the search list is present in an annual report, then it is coded

Petty, 2000; Guthrie, Petty, Ferrier, & Wells, 1999; Guthrie, Petty,

a 1; if it is not present, it is coded a zero, depending on whether it

Yongvanich, & Ricceri, 2004; Joshi, Ubha, & Sidhu, 2010, 2012;

was a legitimate hit or a false positive. A false positive is a word that

Oliveras, Gowthorpe, Kasperskaya, & Perramon, 2008; Olsson, 2001;

shows up in the annual report, providing a word “hit” to the

Striukova, Unerman, & Guthrie, 2008; Sujan & Abeysekera, 2007;

Foxit Reader©, but is not a valid word. Foxit Reader© was used to

Vergauwen, Bollen, & Oirbans, 2007). This study uses the content

open all annual reports in PDF versions. Using the ctrl‐F function to

analysis method to capture the extent and variety of ICDs in annual

look up words, the program allowed us to look up a single word in all

reports disclosed by Indian firms. Measurement of ICDs is fairy

reports at once, highlighting and linking all occurrences, or “hit” of

problematic. The nature of the information makes it difficult to

the word. We would read each hit and record a tally of all hits

obtain a reliable measure of its level. The literature has primarily

per company that was related to IC disclosures while ignoring an

approached this measurement issue using content analysis. Content

occurrence that was not.

analysis is “a method of codifying the text of writing into various

Because of the nature of content analysis, there is an element of

groups or categories based on selected criteria, assuming that

subjectivity involved in gathering data. In the present study, this

the frequency indicates the importance of the subject matter”

was due to our making a decision as to whether a word hit was

(Guthrie et al., 2004, p. 285). Content analysis involves “coding

valid or not. To ensure we included and excluded the right words,

words, phrases and sentences against particular scheme of interest”

an outside person was shown how to codify the data and went

(Bowman, 1984, p. 61). When performed correctly, it should be a

through the same motions of examining each “hit” in the search and

systematic, objective, and reliable way to determine the meaning

decided whether to include IC‐related words and exclude non‐IC‐

of content in disclosures (Vergauwen et al., 2007). A list of words

related words. There was agreement on the vast majority of hits.

46

4

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RESULTS

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4.2.1

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ET AL.

RC attributes

RC is the most frequently reported in Table 4. It accounts for nearly This section provides descriptive statistics and discusses the results of

half (42%) of the total ICDs (see Figure 1).

the extent and variety of overall ICD and its three components,

This is consistent with most of the findings in prior studies which

namely, SC, RC, and HC. It is then followed by an analysis of ICD by

disclose between 37% and 61% (see Table 5). The relative popular dis-

firm size and industry sector.

closure of RC may be due to increased global competition vying for market share (Guthrie & Petty, 2000). RC can have an impact on upholding

4.1

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investor confidence, such as brand building in the case of the Sri Lankan

Descriptive statistics

sample, and it can also attract investor capital due to high disclosure of

The descriptive statistics presented in Table 2 display the number of

business partnering in the Australian sample (Abeysekera, 2007).

“hits” per category of IC. They indicate that RC is the most frequently

Another potential explanation relates to information production costs,

reported in this sample, followed by HC, and lastly SC. The average

where firms may have information on customers, suppliers, brands,

number of total IC disclosed (i.e., total ICD count) is 60.63. The average

and market share because this type of information is highly relevant

number of SC, RC, and HC disclosed is 16.02, 25.64, and 18.97, respec-

and useful to the firms. Thus, this type of information may be readily

tively. Caution is required when comparing results of prior studies due

available, less costly, and easy to report (Vergauwen et al., 2007).

to their using different coding units, frameworks, and number of search

The eight most frequently disclosed items or attributes in Table 4

terms. For example, the framework used may include a fewer number of

for RC mainly refer to brands (34% and reported by 79% of firms), cus-

SC, RC, and HC attributes in some studies than the framework used in

tomers (33% and reported by 94% of firms), market share (8% and

other studies. In addition, the source of information used in content

reported by 53% of firms), joint venture (7% and reported by 40% of

analysis may come from different types of corporate reports, such as

firms), partnership (4% and reported by 43% of firms), customer base

web pages, annual reports and accounts, annual reviews, interim

(3% and reported by 25% of firms), supply chain (3% and reported by

reports, analyst presentations, preliminary reports, and others

29% of firms), customer satisfaction (2% and reported by 36% of

(Striukova et al., 2008). However, we can compare our results with

firms), and the rest of the other RC attributes represents only 6% with

those of Vergauwen et al.' (2007) results, because we use their frame-

84% of firms reported. These results are fairly consistent with those of

work, which comprises 108 search terms or attributes of total ICDs.

Vergauwen et al. (2007), where customers, joint venture, and brands

Therefore, it is of interest to compare our results against theirs. The

are the three most often mentioned, at 57%, 15%, and 14%, respec-

average number of total IC disclosed in Vergauwen et al. (2007) was

tively. The other five most mentioned are market share (6%), partner-

260.57, whereas the average number of SC, RC, and HC disclosed was

ship (4%), and customer satisfaction, supply chain and distribution

57.88, 119.60, and 83.08, respectively. Accordingly, the extent of all

channels with 1% each. Bozzolan et al. (2003) found similar results

disclosures by Vergauwen et al. (2007) seems to be greater than that

with the “customers” attribute disclosed at 35% and “brands” at 13%.

of our study. Note that sample firms in Vergauwen et al. (2007) were

We see that the most frequently disclosed attribute of RC by Indian

from three countries (Sweden, the United Kingdom, and Denmark) with

firms is brands, which are names and symbols that differentiate firms'

a relatively high IC performance index (Bonfour, 2003). Their sample

products or services from their competitors. Thus, if their brands stand

includes the top 20 firms from each country by market capitalisation.

out and are attractive to customers, they can demand higher profit margins for their products or services that are similar to those provided

4.2 | The extent and variety of IC disclosure by attributes

by competitors. As to the variety of disclosure (i.e., presence) of the RC, the greatest number of attributes reported was 13 (see Table 2) out of a

Table 3 shows the number of “hits” per search terms and per category

possible maximum of 29. This was reported by one firm, Ranbaxy,

of IC. Table 4, which summarises the results of Table 3, displays the

followed by Hero Motocorp (12), Jubilant Lifesciences (11), Til Limited

most eight frequently disclosed items per category of IC.

(11), and Panacea Biotec (10).

TABLE 2

Descriptive statistics for IC variables amount of hits (or count), presence, and score per category item of intellectual capital

Variable

Minimum

Maximum

Total

Mean

SC count

0

363

1,602

16.02

10

SC presence

0

13

5,32

5.32

5

RC count

0

881

2,564

25.64

16.5

RC presence

0

13

483

4.83

HC count

0

854

1897

18.97

HC presence

0

14

572

5.72

5

2.6708

Total ICD count

8

220

6063

60.63

42.5

49.6644

Total ICD presence

4

32

1587

15.87

Number of observation

100

100

100

100

Note. SC = structural capital; RC = relational capital; HC = human capital; ICD = intellectual capital disclosure.

Median

Standard deviation 15.8522 2.6319 26.465

4.5

2.5861

15

16.0177

14.5 100

6.722 100

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TABLE 3

Results of search terms for structural, relational and human

TABLE 3

(Continued)

capital Panel A Panel A Structural capital Leadership

Proportion of Absolute Relative firms reported 363

0.23

0.68

Proportion of Absolute Relative firms reported

Structural capital Intellectual resources

0

0.00

0.00

Intellectual material

0

0.00

0.00

Corporate learning

0

0.00

0.00

1,602

1.00

Innovation

360

0.22

0.85

Network

219

0.14

0.55

R&D/research and development

173

0.11

0.77

Philosophy

110

0.07

0.61

Value added

85

0.05

0.36

Brands

881

0.34

0.79

Intellectual property

78

0.05

0.28

Customers

843

0.33

0.94

Total Panel B

Proportion of Absolute Relative firms reported

Relational capital

Patents

69

0.04

0.20

Market share

203

0.08

0.53

Methodologies

20

0.01

0.11

Joint venture

182

0.07

0.40

Management processes

15

0.01

0.09

Partnership

113

0.04

0.43

71

0.03

0.25

Telecommunication

11

0.01

0.09

Customer base

Trademarks

9

0.01

0.04

Supply chain

68

0.03

0.29

Corporate culture

9

0.01

0.08

Customer satisfaction

56

0.02

0.36

Intellectual capital

9

0.01

0.07

Distribution networks

45

0.02

0.22

Knowledge sharing

8

0.00

0.07

Quality standards

26

0.01

0.17

Research projects

8

0.00

0.06

Licencing agreement

21

0.01

0.08

New product success rate

7

0.00

0.04

Research collaboration

13

0.01

0.07

Information systems

6

0.00

0.05

Business collaboration

10

0.00

0.07

10

0.00

0.08

Technological processes

6

0.00

0.06

Company reputation

Infrastructural assets

6

0.00

0.04

Distribution channels

7

0.00

0.06

Cultural diversity

5

0.00

0.02

Customer loyalty

7

0.00

0.03

Product development cycle

5

0.00

0.02

Brand recognition

4

0.00

0.02

Knowledge resources

4

0.00

0.02

Customer retainment

2

0.00

0.02

Management focus

3

0.00

0.03

Customer recognition

1

0.00

0.01

Networking systems

3

0.00

0.02

Competitive intelligence

1

0.00

0.01

Copyrights

3

0.00

0.03

Brand development

0

0.00

0.00

0

0.00

0.00

0

0.00

0.00

Economic value added

2

0.00

0.02

Customer knowledge

Trade secrets

1

0.00

0.01

Supplies knowledge

Corporate university

1

0.00

0.01

Customer capital

0

0.00

0.00

Business knowledge

1

0.00

0.01

Customer turnover rates

0

0.00

0.00

Operating systems

1

0.00

0.01

Favourable contracts

0

0.00

0.00

Organisational culture

1

0.00

0.01

Corporate image

0

0.00

0.00

New product revenue

1

0.00

0.01

Franchising agreement

0

0.00

0.00

Electronic data interchange

0

0.00

0.00

Financial contacts

0

0.00

0.00

2,564

1.00

Absolute

Relative

Proportion of firms reported

0.45

0.98

Total

Software systems

0

0.00

0.00

Proprietary process

0

0.00

0.00

Intellectual assets

0

0.00

0.00

Human capital

Soft assets

0

0.00

0.00

Employees

Operating software

0

0.00

0.00

Personnel

219

0.12

0.75

179

0.09

0.78

Panel C

854

Organisational learning

0

0.00

0.00

Human resources

Management quality

0

0.00

0.00

Knowledge

158

0.08

0.51

Knowledge stock

0

0.00

0.00

Expertise

152

0.08

0.57

0.00

Training programmes

84

0.04

0.41

Knowledge assets

0

0.00

(Continues)

(Continues)

48

SENG

TABLE 3

ET AL.

TABLE 4

(Continued)

Most eight frequently disclosed items per category of intellectual capital

Panel C Human capital

Absolute

Relative


Education

48

0.03

0.16

Competence

36

0.02

0.25

Human capital

33

0.02

0.24

Empowerment

24

0.01

0.17

Intelligence

17

0.01

Employee satisfaction

15

0.01

Panel A Structural capital

Absolute

Relative


Leadership

363

0.23

0.68

Innovation

360

0.22

0.85

Network

219

0.14

0.55

R&D/research and development

173

0.11

0.77

0.09 0.13

Philosophy

110

0.07

0.61

85

0.05

0.36

Know‐how

14

0.01

0.08

Value added

Motivation

13

0.01

0.12

Intellectual property

78

0.05

0.28

Specialist

12

0.01

0.10

Patents

69

0.04

0.20

Employee retention

8

0.00

0.06

Other variables (38)

145

0.09

1.02

1,602

1.00

Total

Employee productivity

7

0.00

0.07

Career development

6

0.00

0.06

Union activity

5

0.00

0.04

Employee skill

4

0.00

0.04

Brands

Panel B Relational capital

Relative


881

0.34

0.79

843

0.33

0.94

Absolute

Expert team

2

0.00

0.02

Customers

Human asset

2

0.00

0.01

Market share

203

0.08

0.53

182

0.07

0.40

113

0.04

0.43

Employee benefits

1

0.00

0.01

Joint venture

Human value

1

0.00

0.01

Partnership

Employee value

1

0.00

0.01

Customer base

71

0.03

0.25

68

0.03

0.29

Vocational qualifications

1

0.00

0.01

Supply chain

Work‐related competence

1

0.00

0.01

Customer satisfaction

56

0.02

0.36

Employee expertise

0

0.00

0.00


147

0.06

0.84

2,564

1.00

Total

Flexitime

0

0.00

0.00

Brain power

0

0.00

0.00

Expert network

0

0.00

0.00

Human capital

Value added statements

0

0.00

0.00

Employees

0.00

Personnel

Work‐related knowledge Total

4.2.2

|

0

0.00

1,897

1.00

HC attributes

HC is the second most frequently reported in Table 4. It accounts for almost one‐third (31%) of the total IC disclosure (see Figure 1). This is consistent with most of the findings in prior studies, which disclose between 10% and 36% as shown in Table 5. The eight most frequently disclosed items in Table 4 for HC are

Panel C Relative


854

0.45

0.98

219

0.12

0.75

Human resources

179

0.09

0.78

Knowledge

158

0.08

0.51

Expertise

152

0.08

0.57

Training programmes

84

0.04

0.41

Education

48

0.03

0.16

Competence

36

0.02

0.25


167

0.09

1.29

1,897

1.00

Total

Absolute

employees (45% and reported by 98% of firms), personnel (12% and reported by 75% of firms), human resources (9% and reported by 78%

third and sixth, respectively, in our study, but these two attributes were

of firms), knowledge (8% and reported by 51% of firms), expertise (8%

not disclosed at all in Vergauwen et al. (2007). The employees attribute

and reported by 57% of firms), training programmes (4% and reported

was ranked first in our study as well as in Vergauwen et al. (2007). Man-

by 41% of firms), education (3% and reported by 16% of firms), compe-

agers are aware that a company with more capable employees is likely

tence (2% and reported by 25% of firms), and the rest of the other HC

to achieve higher earnings than competitors whose employees have

attributes represent only 9% with 129% of firms reported. Again, these

lower capabilities in performing similar tasks. Thus, the value of firms

results are fairly consistent with those of Vergauwen et al. (2007),

is related to the quality of personnel, human resources, knowledge,

where the employees attribute was ranked first (77%), followed by

expertise, training programmes, education, and competence. These

knowledge (5%), and personnel (5%). The expertise attribute was

attributes are also important for organisations in the development of

ranked fourth (3%), followed by competence (3%), and lastly education

employees and the effectiveness and efficiency of staff to improve

(2%). Note that human resources and training programmes were ranked

firms' productivity (Vergauwen et al., 2007).

SENG

49

ET AL.

As to the variety of disclosure (i.e., presence) of HC, the greatest number of attributes reported was 14 (see Table 2) out of a possible maximum of 33. This was reported by Bharti Airtel, followed by Til Limited (12). Three firms (Simplex Infrastructures, Shree Cement, and Dr. Reddy) all reported the same attributes at 11 each.

4.2.3

|

SC attributes

SC is the least frequently reported in this sample in Table 4. It accounts for 27% of the total IC disclosure (see Figure 1).This is also consistent with most of the findings in prior studies, which disclose between 17% and 41% as shown in Table 5. The eight most frequently disclosed items in Table 4 for SC are leadership (23% and reported by 68% of firms), innovation (22% and reported by 85% of firms), network (14% and reported by 55% of firms), R&D/research and development (11% and reported by 77% of firms), philosophy (7% and reported by 61% of firms), value added (5% and reported by 36% of firms), intellectual property (5% and reported by 28% of firms), patents (4% and reported by 20% of firms); the rest of the other SC attributes represent only 9% with 102% of FIGURE 1

Intellectual capital disclosure by categories (frequency) [Colour figure can be viewed at wileyonlinelibrary.com]

firms reported. These results are somewhat different to those of Vergauwen et al. (2007), where the leadership attribute was ranked sixth (5% disclosed) and the innovation attribute was ranked fifth (6%) compared with our study, which ranked leadership first and innovation second. In addition, the network and research and development

TABLE 5

Comparison of proportion of ICDs per category from prior content analysis studies (Adapted from Whiting & Miller, 2008) Proportion of disclosure (%)

Study

Average number of ICDs reported per annual report

Structural capital

Relational capital

Human capital


8.9

30

40

30

Brennan (2001)

3.7

29

49

22

April et al. (2003)

10.4

30

40

30

Bozzolan et al. (2003)

51

30

49

21

14.6

37

41

22

20

44

36

Goh and Lim (2004) Abeysekera and Guthrie (2005)

N/A

Vandemaele, Vergauwen, and Smits (2005) The Netherlands

6.5

31

40

29

Sweden

8.4

28

38

34

UK

5.4

30

42

28

Australia

31.6

41

49

10

Hong Kong

13.2

28

37

35


Bozzolan et al. (2006) UK

42.5

24

60

15

Italy

46.0

29

52

19

17.4

25

48

27

Oliveira et al. (2006) Abeysekera (2007) Australia

N/A

30

40

30

Sri Lanka

N/A

20

44

36

Vergauwen et al. (2007)

260.6

22

46

32

Striukova et al. (2008)

178.4

17

61

22

Whiting and Miller (2008)

26

21

47

33

Yi and Davey (2010)

NA

30

46

24

Abhayawansa and Azim (2014)

NA

37

34

29

Note. Caution is required when comparing results as studies use different coding units, framework, and number of search terms. ICDs = intellectual capital disclosures.

50

SENG

ET AL.

attributes were ranked first and second, respectively, in Vergauwen

the equality of the means is that of unequal variance. Table 6 shows

et al. (2007), while they were ranked third and fourth in our study.

that the difference between the means of large and small firms is sig-

Note that philosophy and value added were ranked fifth and sixth,

nificant at the 5% level only for the overall extent of disclosure,

respectively, in our study, but these two attributes were not disclosed

Count_ALL; the extent of disclosure for structural capital, Count_SC;

at all in Vergauwen et al. (2007). A possible justification for the least

and human capital, Count_HC. This result of size effect is consistent

popular disclosure of SC may be due to the cost instead of the benefits

with prior voluntary ICD and wider disclosure studies (Beattie,

of voluntary ICD, that is, the erosion of competitive advantage

McInnes, & Fearnley, 2002; Gray, Kouhy, & Lavers, 1995; Guthrie

(Vergauwen et al., 2007). Public disclosure of SC may actually be harm-

et al., 2006; Hackston & Milne, 1996; Robb, Single, & Zarzeski, 2001;

ful to firms because it could potentially reveal practices which firms

Striukova et al., 2008). As discussed earlier in the study, larger firms

use to maintain their competitive advantage. Competitors could use

are likely to be more progressive and innovative and take the lead in

this released information to the detriment of the disclosing company,

the area of IC reporting due to their size and the financial resources

therefore costing the company.

at their disposal (Guthrie et al., 2006; Guthrie & Petty, 2000). How-

As to the variety of disclosure of SC, the greatest number of attributes reported was 13 (see Table 2) out of a possible maximum

ever, it is noted that the difference between the means of RC for large and small firms is insignificant.

of 46. This was reported by one firm, Infosys, followed by Panacea Biotec (12), Jubilant Lifesciences (11), Dr. Reddy (10), and Bharti Airtel (9).

4.4

IC disclosure by industry

|

Table 7 shows that, on average, high‐IC‐intensive firms disclose total

4.3

|

IC (Count_ALL; mean = 83.36) more than low‐IC‐intensive firms

IC disclosure by firm size

(mean = 49.45). The higher disclosure by high‐IC‐intensive firms is also

Although our sample comes from the top 100 firms by market

applicable to other three categories of IC, namely, SC, RC, and HC,

capitalisation, there is still variation in size among them. We split the

under both count and presence. Note that 18 firms out of the 33

sample into two groups at the median (Guthrie et al., 2006; Mangena,

high‐IC‐intensive firms belong in the large firm category.

Pike, & Li, 2010). The group that has a market capitalisation

The independent t‐test for the means is shown in Table 7. Again,

greater than its median is classified as “large” firms, whereas the

the Levene test for equality of variances is used. Table 7 shows that

other group which has a market capitalisation below its median

the difference between the means of high‐IC‐intensive and low‐IC‐

belongs to a group of “small” firms. Table 6 shows that, on average,

intensive firms is statistically significant for all of the variables (except

large firms disclose total IC (Count_ALL; mean = 70.86) more than

for Presence_HC), with varying degrees of significance. Count_SC and

small firms (mean = 50.00). Also, the means of SC, RC, and HC for

Count_ALL are statistically significant at the 1% level, whereas the

large firms are higher than those of small firms under both count

Presence_SC and Count_RC are statistically significant at the 5% level;

and presence.

and lastly the Presence_RC, Count_HC, and Presence_ALL are statisti-

The independent t‐test for the means is shown in Table 6. To test

cally significant at the 10% level. Consequently, this result seems to

for homogeneity of variance, we use the Levene test for equality of

support the view that industry is an important determinant in the level

variances. Where applicable, when this test is significant (p < .05), then

of ICDs (Bozzolan et al., 2003; Bozzolan, O'Regan, & Riccerri, 2006;

the null hypothesis is rejected and the assumption used in testing for

Striukova et al., 2008).

TABLE 6

Descriptive disclosure of IC on firm size N

Mean

Median

Std. deviation

T‐tests statistics

Count_SC

0 1

49 51

12.41 19.49

9.00 13.00

11.97 18.30

−2.299*

Presence_SC

0 1

49 51

4.96 5.67

5.00 5.00

2.41 2.80

−1.353

Count_RC

0 1

49 51

21.98 29.16

14.00 17.00

20.81 30.74

−1.372

Presence_RC

0 1

49 51

4.69 4.96

4.00 5.00

2.72 2.47

−.514

Count_HC

0 1

49 51

15.61 22.21

13.00 16.00

9.21 20.12

−2.124*

Presence_HC

0 1

49 51

5.55 5.88

5.00 6.00

2.46 2.87

−.618

Count_ALL

0 1

49 51

50.00 70.86

36.00 47.00

37.63 57.51

−2.155*

Presence_ALL

0 1

49 51

15.20 16.51

14.00 17.00

6.68 6.76

−.971

Market capitalisation

0 1

49 51

US$193,829 m US$7,220,261 m

US$155,081 m US$1,821,712 m

US$159,157 m $US13,781,404 m

Note. 0 represents small firm and 1 represents large firm; *Significant at the 5% level.

SENG

51

ET AL.

TABLE 7

Findings of this research show the level of IC in the largest 100

Descriptive disclosure of IC on industry

Market capitalisation

N

Mean

Median

Std. deviation

T‐tests statistics

companies from India, an emerging economy that has the potential of the IC of an organisation and it creates a snapshot of knowledge

Count_SC

0 1

67 33

11.25 25.70

9.00 15.00

8.21 22.23

−3.612***

Presence_SC

0 1

67 33

4.81 6.36

5.00 6.00

2.02 3.37

−2.447**

Count_RC

0 1

67 33

21.49 34.06

13.00 26.00

23.15 30.85

−2.070**

Presence_RC

0 1

67 33

4.49 5.52

4.00 5.00

2.26 3.06

−1.702*

Count_HC

0 1

67 33

16.70 23.61

14.00 16.00

11.51 22.08

−1.687*

Presence_HC

0 1

67 33

5.64 5.88

5.00 6.00

2.30 3.33

−.368

Count_ALL

0 1

67 33

49.45 83.36

40.00 61.00

35.22 65.40

Presence_ALL

0 1

67 33

14.94 17.76

14.00 18.00

5.49 8.49

assets (Burnett, Williams, & Grinnall, 2013). Therefore, the higher level

−2.787***

assures competence and strength of the firm against the risk of competition. Results of this study have implications for business managers and in economies that are increasingly dependent on knowledge and information.

Stakeholders'

demand

for

greater

transparency

in

organisational disclosures on IC has forced managers to present IC information in organisational reports. Stakeholders demand for greater accountability and transparency is increasing globally, therefore, find-

−1.735*

*Significant at the 10% level. **Significant at the 5% level. ***Significant at the 1% level.

|

of ICD can be used as a measure of internal tacit knowledge that

stakeholders because of the crucial role of IC in organisational success

Note. 0 represents low‐IC intensive and 1 represents high‐IC intensive. IC = intellectual capital; SC = structural capital; RC = relational capital; HC = human capital.

5

to become a leading knowledge‐based economy ICD is a stocktake

C O N CL U S I O N S

ings of this study may have implications for global companies. Furthermore, the majority of companies in our sample are multinational companies, therefore, these findings will have implications for multinational companies around the globe. Findings of this research will educate and create awareness among business managers for designing efficient strategies and processes to manage and report IC. India is one of the top most attractive destinations for foreign direct investment (Ministry of Commerce and Industry, Government of India6), therefore, these findings may help investors who are willing to invest in India. Findings may also have implications for regulators who may

This study adds to the body of IC knowledge and is the first to study

wish to design an IC framework to measure and report IC.

the extent (count) and variety (presence) of voluntary ICD by listed pri-

There are a number of limitations in this study. First, we use a sam-

vate firms in India. It also compares the level of ICD of firms in the

ple from privately listed firms, although there might be publicly listed

high‐IC‐intensive and low‐IC‐intensive industry sectors. In addition, it

firms that are actively engaged in producing ICDs. This leaves an

evaluates the effect of firm size on ICD levels. This study begins to fill

opportunity for future research to replicate this study by examining

a research gap with respect to ICD in India because previous research

publicly listed firms in India to enable a more comprehensive under-

has examined mainly the extent of voluntary ICD in a specific industry

standing of the similarities or differences between the two sectors.

(Kamath, 2007, 2008).

Second, this study assumes that all ICD is good/positive disclosure

The extent and variety of voluntary ICD by large firms is higher

and so it was not further classified into neutral or negative tone of dis-

than that of small firms. However, although the difference between

closure. Third, as in common with other ICD and corporate reporting

the means of large and small firms is significant at the 5% level for

analysis, this study focuses on the analysis of ICD in written corporate

the overall extent of disclosure Count_ALL, Count_SC, and Count_HC,

annual reports only. It does not consider different types of disclosure

no significant differences are observed between the large and small

in terms of, for example, analyst presentation, interim report, prelimi-

firms for RC. This suggests that RC is perceived as important in both

nary report, web page, and annual review (Striukova et al., 2008) as

small and large firms. In this respect, it would seem that all firms con-

they can capture a more representative picture of ICD practices.

sider RC as important. It is expected that high‐IC‐intensive firms would have a higher level of ICD than low‐IC‐intensive firms. Our results support this

EN DNOTES 1

The sample was divided into high‐IC‐intensive (knowledge‐intensive) and low‐IC‐intensive (traditional) industries. There are 33 firms in the high‐ IC‐intensive industry sector and 67 in the low‐IC‐intensive sector. High‐IC‐intensive sectors consist of biotech and pharmaceuticals, IT, service providers, telecommunications, banks and insurance, media and publishing, aerospace and defence, chemicals, and electronic and electrical equipment. Low‐IC‐intensive sectors consist of real estate, mining, retailing, engineering, food and beverages, and utilities (Mangena et al., 2010).

2

The use of annual reports is consistent with prior studies of this nature (Abeysekera & Guthrie, 2005; Bontis, 2003; Bozzolan et al., 2003; Brennan, 2001; Guthrie & Petty, 2000; Joshi et al., 2010, 2012; Oliveras et al., 2008; Olsson, 2001; Striukova et al., 2008; Vergauwen et al., 2007). The annual reports were considered to be important to external users regarding company information (Lang & Lundholm, 1993).

expectation and are consistent with prior research. Firms with low IC intensity mainly rely on their physical capital (e.g., property, plant, equipment, and inventory) and financial capital (e.g., cash, marketable securities, and receivable) to derive their value (Brennan, 2001), and those items are recognised and reported on the balance sheet. On the other hand, it is expected that high‐IC‐intensive firms derive a major part of their value because of their IC, which includes intangible assets such as copyrights, patents, franchises, and intellectual property rights. Therefore, these high‐IC‐intensive firms will disclose more qualitative IC in annual reports, because current accounting standards on recognition criteria hinder quantitative amounts of IC to be disclosed on the balance sheet.

52

SENG

3

http://www.bseindia.com/static/about/introduction.aspx?expandable=0 accessed 7 October 2016.

4

Vergauwen et al. (2007) incorporates the list of IC items (containing 108 terms) from Guthrie and Petty (2000); Brennan (2001); Bontis (2003); Bozzolan et al. (2003); Abeysekera and Guthrie (2005); Goh and Lim (2004); Vergauwen and van Alem (2005) and Vandemaele et al. (2005).

5

6

All sections of the annual reports were examined except for details of board and executive board members, the corporate directory, the auditor's independence declaration, all financial report information (such as income statement, balance sheet, statement of cash flows, and notes to financial statements), auditor's report, shareholders' information, and glossary to ensure that only voluntary ICDs were recorded. Also, pictures or diagrams, graphs, and tables were excluded due to complications in attempting to quantify the impact they have (Guthrie et al., 2004). http://www.hindustantimes.com/business‐news/india‐s‐fdi‐inflows‐at‐ a‐record‐60‐1‐billion‐in‐2016‐17/story‐7a8pt2u7e8IJttptDQcwhO.html ‐ Accessed on November 24, 2017.

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How to cite this article: Seng D, Kumarasinghe S, Pandey R.

Robb, S. W. G., Single, L. E., & Zarzeski, M. T. (2001). Non‐financial disclosure across Anglo‐American countries. Journal of International Accounting, Auditing and Taxation, 10, 71–83.

in India. Knowl Process Manag. 2018;25:41–53. https://doi.org/

Intellectual capital disclosure in private sector listed companies 10.1002/kpm.1560