Cost, revenue, and profit efficiency characteristics, and intellectual capital in Indian Banks
| DOI | https://doi.org/10.1108/JIC-05-2019-0107 |
| Pages | 1-22 |
| Published date | 31 December 2019 |
| Date | 31 December 2019 |
| Author | Harishankar Vidyarthi,Ranjit Tiwari |
| Subject Matter | Organizational structure/dynamics,Accounting & Finance,Accounting/accountancy,Behavioural accounting |
Cost, revenue, and profit
efficiency characteristics, and
intellectual capital in Indian Banks
Harishankar Vidyarthi
Department of Finance and Accounting,
Institute of Public Enterprise, Hyderabad, India, and
Ranjit Tiwari
Department of Finance and Accounting,
Chandragupt Institute of Management Patna, Patna, India
Abstract
Purpose –The purpose of this paper is to estimate the economic (namely cost, revenue and profit) efficiency
and its association with intellectual capital of 37 BSE-listed Indian banks over the period 2005–2018.
Design/methodology/approach –This study employs truncated Tobit regression to compute the
relationship between intellectual capital and estimated cost, revenue and profit efficiency using Data
Envelopment Analysis (DEA) for the 37 BSE-listed Indian banks within the panel data framework.
Findings –Estimates suggest that banks’overall annual average cost, revenue and profit efficiency are
0.4466–0.7519, 0.4825–0.8773 and 0.4905–0.8803, respectively, during the sample period. Further, Tobit
regressionresults indicate thatthe aggregate intellectualcapital (value-addedintellectual coefficientor Modified
Value-addedIntellectual Capital) has a positivebut minimal impact on these efficiencyparameters at 1 percent
significance level for the overall sample as well as public sector banks. Among all the sub-components of
intellectualcapital, human capital, structural capital andrelational capital have a positiveand moderate impact
on these efficiency measures for the overall sample. Control variables, particularly bank size, are significant
drivers of the estimatedefficiency of banks.
Research limitations/implications –Findings suggest that banks should invest adequately to enhance
their overall intellectual capital to further augment these economic efficiency measures in the long run.
Originality/value –This study computes cost, revenue and profit efficiency of 37 BSE-listed banks based
on DEA followed by intellectual capital using the Pulic approach (1998 and 2000) and the Bontis (1998)
approach in the first stage. Later, it examines the dynamics between the computed efficiency parameters and
intellectual capital using Tobit regression within the panel data framework.
Keywords India, Cost efficiency, Banks, Intellectual capital, Tobit regression, Profit efficiency,
Revenue efficiency
Paper type Research paper
1. Introduction
The Indian banking sector has experienced multiple reforms, technology adoption, new
practices and increased competitiveness with the entry of new generation domestic
private banks and specialized small finance and payment banks during the last two
decades. This has revolutionized the entire banking system to perform better than before
intermsofoperationsaswellaseconomicefficiency measures. However, recent economic
slowdown and non-performing assets (NPA) crisis among Indian banks have again drawn
the attention of academia and policy makers toward the economic efficiency and
effectiveness prevailing in these banks, as many banks lost their capital base and came
under the preview of Reserve Bank of India’s prompt corrective action (PCA) due to all
time high provisioning and mounting losses because of previous reckless lending. Having
talked about the monster problem, it is still said that the Indian banking system is quite Journal of Intellectual Capital
Vol. 21 No. 1, 2020
pp. 1-22
© Emerald PublishingLimited
1469-1930
DOI 10.1108/JIC-05-2019-0107
Received 23 May 2019
Revised 25 July 2019
1 October 2019
Accepted 12 November 2019
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1469-1930.htm
The authors would like to thank the anonymous reviewers for their valuable comments and sug-
gestions to improve the quality of the paper.
1
Cost, revenue,
and profit
efficiency
robust and profitable. The credit of profitability, i.e., performance, is often attributed to
tangible resources and no recognition is given to intangible resources. But in the late
1990s, studies like Edvinsson and Malone (1997), Stewart (1997), Pulic (1998) and Bontis
(1999) highlighted the importance of intangible assets popularly known as intellectual
capital in order to gain competitive advantage, primarily for knowledge-intensive firms
like banks, insurance, pharmaceuticals and telecommunications among others in the
economy. Several studies (Riahi-Belkaoui, 2003; Mavridis, 2004; Andriessen, 2004; Youndt
et al., 2004; Bollen et al., 2005; Wang and Chang, 2005; Ng, 2006; Pew Tan et al., 2007;
Tovstiga and Tulugurova, 2007; Díez et al., 2010; Zeghal and Maaloul, 2010; Gruian, 2011;
Clarke et al.,2011;Ståhleet al., 2011; Mehralian et al., 2012; Joshi et al., 2013) have been
conducted to analyze the impact of intellectual capital on firm performance in developed
economies. We have also noticed the recent flow of studies (Firer and Williams, 2003;
Chen Goh, 2005; Kamath, 2007; Muhammad and Ismail, 2009; Mondal and Ghosh, 2012;
Vishnu and Kumar Gupta, 2014; Singh et al., 2016; Anifowose et al., 2017; Nadeem et al.,
2017; Tiwari and Vidyarthi, 2018; Tran and Vo, 2018; Smriti and Das, 2018) from
developing economies. Surprisingly, these studies measured firm performance using
accounting/market-based measures like returnonassets(ROA),returnonequity(ROE),
market value to book value ratio (MV/BV ) and Tobin’sQ, among others. These measures
failed to incorporate the scale of operation, prices of input and output and level of
efficiency during the process. Alternatively, banks’performance can be quantified in
terms of operational efficiency (technical, pure technical and scale), economic efficiency
(cost, revenue and profit) or productivity change (total factor productivity). But each has
its own pros and cons. Operational (technical, pure technical and scale) efficiency
incorporates input-output usage effectiveness but does not consider input-output price for
relative performance analysis. Thus, it is appropriate to consider economic (cost, revenue
and profit) efficiency measures for robust decision making (Chu and Lim, 1998; Rogers,
1998; Berger and Mester, 1997).
This study addresses the gap in the literature by exploring the cost, revenue and
profit efficiency of BSE-listed banks in India using non-parametric Data Envelopment
Analysis (DEA[1]), with a fairly longer data set over the period 2005–2018 to explore the
relative performance during this period. Next, we measure the intellectual capital and its
sub-components following the Pulic (1998) and Bontis (1998) approaches to know the recent
trends of bank-wise intellectual capital coefficient. Finally, we examine the impact of
the aggregate intellectual capital coefficient as well as the intellectual capital coefficient of
the sub-components on the efficiency measures for aggregate, public sector bank and
private sector bank samples.
The findings suggest that banks’overall annual average cost, revenue and profit
efficiency are 0.4466–0.7519; 0.4825–0.8773; and 0.4905–0.8803, respectively, during the
sample period. Thus, there is further scope for minimizing inefficiencies significantly
through various innovations. Second, Tobit[2] regression results suggest that intellectual
capital has a positive and significant impact on the cost, revenue and profit efficiency for the
overall sample as well as the public sector bank sample. Further, human capital, structural
capital and relational capital seem to be the major drivers for these efficiency parameters for
the overall sample as well as the public sector bank sample. However, we do not observe any
significant association between intellectual capital, and cost, revenue and profit efficiency
for the private sector banks during the study period. Thus, banks should also invest in
intellectual capitals to remain more competitive and efficient in the longer run.
The remainder of the paper is structured as follows. Section 2 discusses the related
literature in this area. Section 3 discusses the methodological approach and data employed
for the study. Empirical results are provided in Section 4, followed by conclusions in
Section 5.
2
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