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1 – 10 of over 31000Qian Long Kweh, Wen-Min Lu, Kaoru Tone and Mohammad Nourani
The purpose of this study is twofold. First, this research estimates banks' efficiencies from the perspectives of resource utilization and investment after incorporating risk…
Abstract
Purpose
The purpose of this study is twofold. First, this research estimates banks' efficiencies from the perspectives of resource utilization and investment after incorporating risk measures as an exogenous input in the investment-efficiency stage. Second, the current study examines the relationship between intellectual capital (IC) and banks' efficiencies.
Design/methodology/approach
First, this study uses a dynamic network data envelopment analysis approach in investigating the efficiencies of 24 Taiwanese banks in 2007–2018 from two perspectives. Second, this research utilizes various regression techniques, namely, ordinary least squares (OLS), robust least squares and truncated regression, to gauge the impact of IC on banks' efficiencies. Typically, IC is determined based on a monetary value-based measure and value-added intellectual coefficient (VAICTM).
Findings
Resource-utilization (investment) efficiencies were observed as 0.941 (0.964), thereby contributing to the mean overall efficiency of the sample banks at 0.952. However, the related efficiency changes decline over the sample period, thereby suggesting that the average banks' efficiencies hardly increase. Regression analyses show a significantly positive relationship between IC and banks' overall resource-utilization and investment efficiencies.
Research limitations/implications
Overall, this study suggests that researchers should consider risks when estimating banks' efficiencies owing to their connection to banks' investment performance. From banks' dynamic two-stage efficiencies, this study demonstrated that investments in IC will bring improved future economic benefits.
Originality/value
Different from prior studies, this study improves banks' efficiency evaluation models by incorporating risk measures and assuming weighted periods for the 2007–2008 global financial crisis. Moreover, the use of monetary value-based measure of IC provides consistent results as the commonly-used VAICTM does.
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Tessa Soetanto and Pei Fun Liem
Intellectual capital (IC) has been considered as a valuable asset in the wealth creation and sustainability of the company; however, limited and mixed results are found on its…
Abstract
Purpose
Intellectual capital (IC) has been considered as a valuable asset in the wealth creation and sustainability of the company; however, limited and mixed results are found on its impact on firm financial performance and market value (MV). This paper aims to investigate the influence of IC toward MV and financial performance of publicly listed firms in Indonesia. In addition, this research also presents the comparison of the high and low level of knowledge industries regarding IC performance.
Design/methodology/approach
A balanced panel data of 127 firms from 12 industries in Indonesia during 2010 until 2017 was evaluated using dynamic panel regression and administering a well-developed Blundell–Bond instrument (dynamic panel data estimator) to account for endogeneity problem.
Findings
The results of this study showed that IC had a significant and positive impact on firm performance. Specifically, structural capital efficiency and capital employed (CE) efficiency have been contributed to the value creation of the company, after controlling for firm size and type of industry. Different to the theoretical expectation, this research found no significant relationship between IC and MV of the firm. However, when the sample was clustered into high-level and low-level knowledge industry, CE displayed positive and significant relationship in high-level industry.
Originality/value
This research contributes to IC research by having a larger sample of Indonesian firms from all industries except banks and financial institutions and using Modified Value Added Intellectual Capital measurement model. To address the endogeneity problem, dynamic panel regression using system generalized method of moment was applied.
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Harnesh Makhija and Pankaj Trivedi
The paper aims to find out the information content of performance measures from accounting and value-based measures that best explain the total shareholder return.
Abstract
Purpose
The paper aims to find out the information content of performance measures from accounting and value-based measures that best explain the total shareholder return.
Design/ methodology/ approach
To achieve this aim, static and dynamic panel data regression analysis is applied to the sample of 56 Indian companies taken from the Nifty Midcap 100 Index, between 2012 and 2019.
Findings
It is found that accounting-based measures have more relative information content in predicting total shareholder return as compared to value-based measures. Economic value added (EVA) and cash value added (CVA) do not add to the information content provided by accounting-based measures. A combination of accounting-based measures and value-added intellectual coefficient (VAIC) adds marginally to the information content provided by accounting-based measures in explaining the total shareholder return. Dynamic panel regression analysis shows that return on assets (ROA), return on capital employed (ROCE), return on equity (ROE) and EVA have a significant impact on total shareholder return.
Originality/value
In this study, along with EVA, other measures from value-based measures, i.e. CVA are empirically tested to explain the total shareholder return. Intellectual capital efficiency computed by VAIC is also empirically tested along with accounting-based measures, EVA, CVA and market value added (MVA). To bring robustness to findings, data are tested by using dynamic panel regression analysis.
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Feng Xu and Xiaohong Wang
The mechanism of leadership’s impact on dynamic capabilities has aroused widespread interest, but few studies focus on transactional leadership, especially empirical research by…
Abstract
Purpose
The mechanism of leadership’s impact on dynamic capabilities has aroused widespread interest, but few studies focus on transactional leadership, especially empirical research by micro foundations in the R&D departments from collaborative innovation alliances. The purpose of this paper is to investigate how the mechanism of transactional leadership affects dynamic capabilities based on the mediating effect of regulatory focus.
Design/methodology/approach
In order to better illustrate the role of transactional leadership on dynamic capabilities, the authors introduced regulatory focus as a mediator based on previous research. A sample of 245 dyads comprised of full-time employees and their immediate supervisors was collected from the innovation teams of industry-university alliances through questionnaires in China and analyzed via hierarchical regression method. Non-response bias and endogeneity testing were also conducted to confirm the validity of the findings.
Findings
Contingency-reward behavior promotes the development of employee sensing and seizing capability. Management-by-exception promotes the development of employee reconfiguration capability. Promotion focus positively mediates the relationship between contingency-reward and sensing-seizing capability. Prevention focus positively mediates the relationship between management-by-exception and sensing-seizing capability. In addition, management-by-exception is also positively related to sensing capability and promotion focus is positively related to reconfiguration capability.
Originality/value
This paper confirmed different dimensions of transactional leadership favor different dimensions of dynamic capabilities based on different dimensions of regulatory focus, which enriches the theory of strategic leadership and dynamic capabilities, and is conducive to the management of collaborative innovation in technological innovation alliances.
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Alper Ozun, Hasan Murat Ertugrul and Yener Coskun
The purpose of this paper is to introduce an empirical model for house price spillovers between real estate markets. The model is presented by using data from the US-UK and…
Abstract
Purpose
The purpose of this paper is to introduce an empirical model for house price spillovers between real estate markets. The model is presented by using data from the US-UK and London-New York housing markets over a period of 1975Q1-2016Q1 by employing both static and dynamic methodologies.
Design/methodology/approach
The research analyzes long-run static and dynamic spillover elasticity coefficients by employing three methods, namely, autoregressive distributed lag, the fully modified ordinary least square and dynamic ordinary least squares estimator under a Kalman filter approach. The empirical method also investigates dynamic correlation between the house prices by employing the dynamic control correlation method.
Findings
The paper shows how a dynamic spillover pricing analysis can be applied between real estate markets. On the empirical side, the results show that country-level causality in housing prices is running from the USA to UK, whereas city-level causality is running from London to New York. The model outcomes suggest that real estate portfolios involving US and UK assets require a dynamic risk management approach.
Research limitations/implications
One of the findings is that the dynamic conditional correlation between the US and the UK housing prices is broken during the crisis period. The paper does not discuss the reasons for that break, which requires further empirical tests by applying Markov switching regime shifts. The timing of the causality between the house prices is not empirically tested. It can be examined empirically by applying methods such as wavelets.
Practical implications
The authors observed a unidirectional causality from London to New York house prices, which is opposite to the aggregate country-level causality direction. This supports London’s specific power in the real estate markets. London has a leading role in the global urban economies residential housing markets and the behavior of its housing prices has a statistically significant causality impact on the house prices of New York City.
Social implications
The house price co-integration observed in this research at both country and city levels should be interpreted as a continuity of real estate and financial integration in practice.
Originality/value
The paper is the first research which applies a dynamic spillover analysis to examine the causality between housing prices in real estate markets. It also provides a long-term empirical evidence for a dynamic causal relationship for the global housing markets.
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Mohammad Alipour, Mehrdad Ghanbari, Babak Jamshidinavid and Aliasghar Taherabadi
This study aims to link environmental disclosure quality (EDQ) to firm performance and examine the moderating role of board independence in this relationship.
Abstract
Purpose
This study aims to link environmental disclosure quality (EDQ) to firm performance and examine the moderating role of board independence in this relationship.
Design/methodology/approach
Drawing on agency theory and stakeholder theory, the authors developed and tested hypotheses using original survey data from 720 firm-year observations collected from 120 Iranian companies over six years between 2011 and 2016. In this paper, they conducted static and dynamic panel data analysis.
Findings
After correcting for endogeneity bias, the results showed that there is a significant positive relationship between EDQ and firm performance. The results also showed that board independence significantly reinforces the positive effect of EDQ on performance, and firms with more independent board members are involved environmental disclosure for improved performance. This is consistent with agency theory, which posits that a more independent board of directors can better monitor the CEO and reduce incentives for pursuing personal interests, which in turn improves performance. The results are robust after performing sensitivity tests.
Research limitations/implications
This paper takes the perspective of corporate governance to empirically examine the effect of EDQ on firm performance. This study makes a contribution to the literature by showing that board independence moderates the effects of EDQ on firm performance.
Practical implications
The evidence supports the emphasis that recent policy statements have put on increasing the number of independent directors on corporate boards. This study offers insights to policymakers interested in enhancing the monitoring role of corporate boards.
Originality/value
The study adds value to the understanding of the effect of the EDQ on performance and how board independence influences this relationship, particularly in an emerging economy like Iran.
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Dinesh Jaisinghani and Amritjot Kaur Sekhon
The purpose of the present study is to analyze the impact of corporate social responsibility (CSR) disclosures on firms' profitability and its persistence.
Abstract
Purpose
The purpose of the present study is to analyze the impact of corporate social responsibility (CSR) disclosures on firms' profitability and its persistence.
Design/methodology/approach
The study has been conducted for listed firms operating in India from 2008 to 2017. Content analysis has been utilized to estimate the CSR disclosures score. Further, dynamic panel regression has been utilized to estimate the relationship between CSR disclosures and profit persistence.
Findings
The results confirm positive profit persistence for Indian companies. The results further show that different dimensions of CSR disclosure have differential impact on firms' profitability. CSR dimensions concerning total community development and product-related disclosures have a positive relationship, whereas dimensions related to environmental and customer-related disclosures have a negative relationship with financial performance. The results also indicate that CSR disclosures are significantly related to profit persistence.
Originality/value
The study is first of its kind that analyzes the impact of CSR disclosure on profit persistence for Indian companies. The results can provide useful implications for managers and regulators in terms of formulation of overall CSR policies.
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Aivars Spilbergs, Diego Norena-Chavez, Eleftherios Thalassinos, Graţiela Georgiana Noja and Mirela Cristea
The COVID-19 pandemic deteriorated the economic situation and raised the issue of the quality of banks’ assets and, in particular, the growth of non-performing loans (NPLs). The…
Abstract
The COVID-19 pandemic deteriorated the economic situation and raised the issue of the quality of banks’ assets and, in particular, the growth of non-performing loans (NPLs). The study approaches a topical subject that is of interest to banks and society at large, as credit availability is likely to be reduced. Over the last 10 years, the Baltic countries’ banking sector has significantly improved its risk management policies and practices, increased capital ratios on its balance sheets, and created risk reserves. The current chapter examines the factors affecting NPLs in the Baltic States based on advanced econometric modelling applied to data extracted from the International Monetary Fund (IMF) and Eurostat. The study results show that credit risk management in the Baltic States has significantly improved compared to the period before the global financial crisis (GFC), the capitalisation of credit institutions is one of the highest in the European Union (EU), and banks are liquid and profitable. Lending recovered from the downturn in the first phase of the pandemic, and credit institutions have taken advantage of the European Central Bank’s (ECB) long-term funding programme ITRMO III to improve the liquidity outlook. Although the credit quality of commercial banks has not deteriorated, as the exposures of credit institutions in the most affected sectors are insignificant and governments have provided fiscal support to businesses and households, some challenges remain. The increase in credit risk is expected due to rising production prices as well as the rebuilding of disrupted supply chains. The findings allow conclusions to be drawn on the necessary actions to mitigate the credit risk of the banking sector.
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Dolly Gaur and Dipti Ranjan Mohapatra
In recent years, the Indian banking sector is facing a major cause of concern in the form of Nonperforming Assets (NPA), and the priority sector lending (PSL) is generally…
Abstract
Purpose
In recent years, the Indian banking sector is facing a major cause of concern in the form of Nonperforming Assets (NPA), and the priority sector lending (PSL) is generally recognized as the major factor contributing to it. Thus, the present study has been carried out with the objective of examining the relationship between priority sector lending and GDP growth. Thereafter, the role of PSL and certain other bank-specific, industry-specific and macroeconomic variables in determining NPA has been studied.
Design/methodology/approach
Taking a sample of 45 scheduled commercial banks, the study has been carried out for 14 years (2004–2018). Granger causality between PSL and GDP has been examined by applying the Dumitrescu-Hurlin test. For the purpose of investigating the impact of PSL and other determinants on NPA, both static and dynamic panel regression have been performed. Under the dynamic panel, system generalized methods of moments (S-GMM) approach has been followed.
Findings
The findings show that there exists a positive correlation and bidirectional causal relationship between PSL and GDP, which implies that PSL brings additional growth for the whole economy. In addition to it, PSL is found to be insignificant for the NPA ratio, and thus, it can be inferred that credit extended to government-specified sectors does not bring any major increase in the bad loan portfolio of banks.
Practical implications
The policymakers and bank management can take a cue from the findings of this study to decrease the exposure to loan nonrepayment issue. The priority sectors are in need of formal credit for their growth, and since the rising population of the country can find employment in these sectors, banks should meet their credit needs while securing their position with regard to the NPA problem.
Originality/value
The issue of NPA determinants, and in particular, the contribution of priority sector lending in it has not been much explored for Indian banking sector. Also, the present study adds to the literature by using the causality approach for examining the importance of directed credit schemes for economic growth.
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Land transactions are a key indicator of urban sustainable development and urban space expansion. Therefore, this paper aims to study the spatial correlation of different types of…
Abstract
Purpose
Land transactions are a key indicator of urban sustainable development and urban space expansion. Therefore, this paper aims to study the spatial correlation of different types of land transactions.
Design/methodology/approach
Based on the big data of land micro transactions in Yangtze River Delta urban agglomeration, this paper uses the generalized forecast error variance decomposition (GFEVD) method to measure the correlation level of urban land markets. Also, social network analysis (SNA) is used to describe spatial correlation network characteristics of an urban agglomeration land market. In the meantime, the factors that influence the spatial correlation of urban land markets are investigated through a quadratic assignment procedure (QAP).
Findings
The price growth rate of urban residential land was higher than that of industrial land and commercial land. The spatial relevance of urban residential land is the highest, while the spatial relevance of the urban commercial land market is the lowest. The urban industrial land market, commercial land market and residential land market all present a typical network structure. Population distance (POD) and Engel coefficient distance (EGD) are negatively correlated with the correlation degree of the urban residential land network; traffic distance (TRD) and economic distance (ECD) are negatively correlated with the correlation degree of the urban industrial land network and commercial land network.
Originality/value
This paper uses a systematically-integrated series of problem-solving models to better explain the development path of urban land markets and to realize the integration of the interdisciplinary methods of geography, statistics and big data analysis.
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