Search results

The scope of this research is to investigate performing loan efficiency for fifty European banks during the period 2008–2017.

The study is structured as a two-stage analysis of performing loan efficiency and its driving factors. In the first stage of the proposed methodology “Data Envelopment Analysis” is used to estimate performing loan efficiency for each bank included in the sample. A bootstrap statistical procedure enhances the findings. In the second stage, the impact of other factors on the efficiency scores of loan performance using tobit regression is investigated.

The results are consistent with the findings of the individual banks' financial analyses. According to the findings of DEA implementation, the evaluated banks may enhance their cost efficiency by 39% on average. In addition, the results indicate that loan efficiency performance improves after 2015, coinciding with the business cycle's upward trend. The tobit regression is employed in the second stage to examine the influence of bank-related and macroeconomic factors on banks' loan management efficiency. According to the findings of the tobit regression, three factors, namely the capital adequacy ratio, GDP per capita and managerial inefficiency, have a substantial influence on performing loan efficiency.

This research investigates the effectiveness of European economic policy in protecting the European banking system from the consequences of the sovereign debt crisis in several euro area members. The results highlight the distance of the Eurozone from the level of the ‘optimal currency area’.

The purpose of this paper is to determine the most efficient hotels in the Indian hotel industry, the competitive positioning of these hotels, and the factors that affect their efficiency change.

This study conducts a two-stage analysis and uses data envelopment analysis (DEA) and Global Malmquist productivity index (MPI) approach in the first stage to calculate the managerial performance of a panel of 63 Indian hotels in 2019–2020 and their efficiency change from 2009–2010 to 2019–2020. Bootstrapped generalized least square (GLS) approach is applied in the second stage to evaluate the impact of contextual variables on efficiency change.

Using the results of the first stage analysis, the authors categorized the 63 Indian hotels into 7 distinct clusters. These clusters represent different levels of competitiveness and pace of growth. The GLS regression reveals a U-shaped relationship between hotel size and efficiency change and a negative relationship between pro social investments and efficiency.

This is the first study in the hotel industry that has used global MPI as a measure of efficiency change in the first stage and GLS in the second stage. In the Indian context, to the best of authors’ knowledge, no such study exists.

The purpose of this study is to evaluate the efficiency of a Brazilian steelmaking company’s reheating process of the hot rolling mill.

The research method is a quantitative modeling. The main research techniques are data envelopment analysis, TOBIT regression and simulation supported by artificial neural networks. The model’s input and output variables consist of the average billet weight, number of billets processed in a batch, gas consumption, thermal efficiency, backlog and production yield within a specific period. The analysis spans 20 months.

The key findings include an average current efficiency of 81%, identification of influential variables (average billet weight, billet count and gas consumption) and simulated analysis. Among the simulated scenarios, the most promising achieved an average efficiency of 95% through increased equipment availability and billet size.

Additional favorable simulated scenarios entail the utilization of higher pre-reheating temperatures for cold billets, representing a large amount of savings in gas consumption and a reduction in CO2 emissions.

This study’s primary innovation lies in providing steelmaking practitioners with a systematic approach to evaluating and enhancing the efficiency of reheating processes.

This paper aims to investigate the performance of OECD countries' long-term productivity during the period of 1975–2018.

This study employed different approaches to evaluate how efficiency scores vary with changes in inputs and outputs: Data Envelopment Analysis (CRS, VRS and FDH), TOPSIS and TOPSIS of these scores.

The findings suggest that, during the period of this study, countries with higher freedom of religion and with Presidential democracy regimes are positively associated with higher productivity.

To the best of the authors’ knowledge, this is the first study that uses efficiency models to assess the productivity levels of OECD countries based on several contextual variables that can potentially affect it.

It is imperative for policymakers, financial institutions, and individual investors to comprehend the factors that impact stock market participation, given the growing significance of the stock market in terms of personal and national wealth. This study endeavours to explore the relationship between cognitive ability and participation in the stock market. We examine the relationship between cognitive abilities and stock market participation, and further explore the mechanism of their influence.

The data from the China Family Panel Studies is utilized, and Tobit and Probit regressions are employed. Additionally, an instrumental variable approach (IV-estimate) is implemented to address the endogeneity issue linked to cognitive ability, and the study’s findings are resilient.

The results reveal a significant positive relationship between cognitive ability and stock market participation. Additionally, the findings suggest that households with higher cognitive ability tend to aggregate more information, expand social networks, and take more risks. A likely explanation is that individuals with higher cognitive ability are more likely to process more external information and evaluate the subjective uncertainty of stock markets based on a well-defined probability distribution. Our findings indicate that the impact of cognitive ability on stock market participation varies among families with differing education levels, genders, marital statuses, and geographical locations.

Therefore, the roles of cognitive abilities in accelerating stock market participation should be fully considered. More information channels and sources that contain financial markets’ information (e.g. mobile applications and financial education) should be provided. Thus, the significance of cognitive ability in increasing stock market participation should be fully considered. Providing more information channels and sources, such as mobile applications and financial education, that contain financial markets’ information would be helpful. Our study contributes to promoting financial literacy and inclusion by highlighting the significant positive impact of cognitive ability, where institutions can tailor their outreach efforts and information channels to better serve individuals with different cognitive ability.

The purpose of this study is to analyze the influence of the firms' external environment on their export intensity. More specifically, it assesses whether domestic market characteristics such as domestic demand and general export environment related to tradability across borders affect firms' export intensity.

The authors use a sample of 29,266 firms from nine European countries, for the period of 2010–2016, and test several estimation methods (random effects models, Tobit models, and Heckman's selection models).

Results show that external factors such as domestic demand and ease of trade across borders are important determinants of firms' export intensity. Moreover, results reveal that firm's internal characteristics such as age, size and productivity also play an import role.

Studies about the influence of the firms' external environment on firms' export intensity are scarce because most of them are confined to a single country context. In this way, the present study contributes to the body of knowledge on the influence that external factors can have on firms' export performance by analyzing firms from nine European countries, which has important policy implications.

Utilizing the expectation states theory in sociology, this study probes into the influence of the board's informal hierarchy on the quality of enterprise innovation, originating from the perspective of internal directorial interactions, while analyzing the boundary effects exhibited by the nature of property rights and the intensity of geo-culture.

The study selects China's A-share listed companies from 2008 to 2021 as the research sample, employing the Tobit regression analysis method to scrutinize the hypotheses presented in the text.

The regression results demonstrate a positive correlation between the board's informal hierarchy and the enterprise innovation quality (EIQ). Upon introducing variables specific to property rights and geographical culture, the authors found that in comparison to non-state-owned enterprises (non-SOEs), the influence of the board's informal hierarchy on the quality of corporate innovation is diminished in SOEs. Conversely, the intensity of geo-culture across Chinese provinces enhances their mutual positive influence. In the additional analysis, the authors also found that the elevation of corporate risk tolerance is a significant pathway for the positive effect of the board's informal hierarchy on EIQ. Moreover, this positive influence is more profound in high-tech enterprises, businesses implementing equity incentive plans and companies that have subscribed to director and officer liability insurance.

The findings not only deepen the understanding of how the board's internal status characteristics influence corporate decision-making but also enrich the application scope of expectation states theory. Furthermore, this study offers valuable guidance for optimizing innovation decision-making by adjusting the personnel structures of corporate boards.

Building on resource dependence theory and the dynamic institution-based view, this paper examines the influence of government affiliations on firm product innovation in a dynamic institutional environment.

Using unique panel data of Chinese manufacturing firms covering a period of 12 years (1998–2009) with 2,564,547 firm-year observations, this study chooses the panel Tobit model with random effects to explore the influence of government affiliations on firm product innovation, followed by an analysis to test the moderation effects of dynamic institutional environments.

The study findings suggest that Chinese firms with higher-level government affiliations have a relatively high product innovation performance. It finds that this innovation stimulating effect is contingent on the dynamic nature of the institutional environment. To be specific, a high speed of institutional transition may depress the positive innovation effects of government affiliations, while a more synchronized transition speed of institutional components may enhance the positive innovation effects of firms' government affiliations.

This study adds to a better understanding of the drivers of product innovation in Chinese firms that are situated in environments that are characterized by institutional change, using and contributing to resource dependence theory and the dynamic institution-based view.

The purpose of this study is to explore how digital construction policy (DCP) drives enterprise green innovation (EGI) from an information processing theory (IPT) perspective, including the mediating mechanisms of market information accessibility and operational risk, the moderating role of intellectual property protection (IPP) and product market competition (PMC) and the heterogeneous effects of ownership, Internet development and managerial ability.

Based on the matched panel data of A-share listed enterprises from 2011 to 2019 and the Broadband China policy as a quasinatural experiment, this study investigates the impact of DCP on EGI by constructing a multi-time point difference-indifferences (DID) model.

Digital construction policies can significantly promote EGI. DCP works in two fundamental ways, namely by increasing market information accessibility and reducing operational risk. IPP and PMC significantly increased the contribution of digital construction policies to EGI. Heterogeneity analysis found that digital technology has a stronger promotion effect for SOEs, high-managerial-ability enterprises and enterprises in regions with low Internet development levels.

The study provides new insights about the antecedents of EGI from a DCP perspective. It also enlightens emerging economies to actualize green innovation under the digital wave.

From the perspective of IPT, this study explains the mechanism of DCP-driven EGI. It enhances understanding of the relationship between DCP and EGI.

This paper aims to analyze relative contribution of intensive margin (IM) and extensive margin (EM) to growth in India's agricultural exports for the period 2001 to 2020. It also analyses the determinants of IM and EMs through a standard gravity model.

The study uses export data from United Nations Comtrade, which is accessed through World Integrated Trade Solution (WITS) software. Data for the period 2001 to 2020 were compiled for analysis using the Harmonized System (HS) of commodity classification system at the six-digit level. This study decomposed the contribution of IM and EM in the growth of Indian agricultural trade by using Hummels and Klenow's approach. After performing the export decomposition analysis, the authors analyze the factors influencing IM and EM by using the Tobit regression model and Poisson pseudo-maximum-likelihood (PPML) method of estimation.

The EM grew at 1.24% per annum, while the intensive margin (IM) increased by 0.23%. The contribution of growth at the EM increased from 58.8% in 2001 to 70.2% in 2020. Export growth along the IM was relatively high for animal products and agricultural raw materials, while growth at the EM was an important contributor to the export growth of horticultural and processed agricultural products. There was a positive and significant effect of the free trade agreement (FTA) on export margins.

More disaggregated commodity-specific studies on value chain analysis would provide valuable insights into the issues hindering exports and realizing the untapped export potential.

There is a scarcity of holistic and recent studies illustrating the role of IM and EMs in agricultural trade growth, covering a large number of commodities and geographies associated with Indian agricultural trade. The study would be helpful to the stakeholders in facilitating informed policy decisions.