External Two Stage DEA Analysis of Bank Efficiency in West Balkan Countries

Since the beginning of the application of the Data Envelopment Analysis (DEA) model in various areas of the economy, it has found its wide application in the field of finance, more specifically banks, in the last few years. The focus of this research was to determine the sustainability of the intermediate function of banks, especially in recent years when interest rates on deposits have been at a minimum level. The research was divided into two parts, wherein the first part determined the efficiency of the intermediate function of banks in the countries of the Western Balkans in the period from 2015 to 2019. The second part approached the regression analysis in which we determined the influence of the bank size, type of bank, and mergers and acquisitions (M&A) activity on the defined efficiency. In the first stage we applied the output-oriented DEA model using deposits, labor costs, and capital as input variables; on the other side, we used loans and investments as output variables. We used data from the revised financial statements of the banks operating in Serbia, Bosnia and Herzegovina, Montenegro, North Macedonia, and Albania. The results of our study showed that there is a difference in efficiency levels between countries and within countries in the considered time period. Furthermore, Tobit regression analysis showed a significant and negative influence of the bank type and M&A on relative technical efficiency of banks, and a positive and significant relationship between bank size and relative efficiency. These findings suggest that large commercial banks can sustain on the West Balkan market. It is to be expected that less efficient small banks will be taken over by large and more efficient banks.

Ecological Efficiency of Urban Industrial Land in Metropolitan Areas: Evidence from China

Industrial land is an indispensable strategic resource in urban development that plays an indispensable role in ensuring the industrial space of urban construction and development. Measuring and analyzing the eco-efficiency of industrial land utilization (ECILU) can provide insights into how to maximize the input–output ratio of industrial land and ensure the sustainable development of land resources and economies. Based on the undesirable output slacks-based measure (SBM) model, choosing land, capital, and labor as input indicators, and the industrial added value and carbon emissions as desirable and undesirable output indicators, this study measured the ECILUs in 78 cities and 13 metropolitan areas in four Chinese major economic zones from 2007 to 2018, analyzed their spatial and temporal evolution characteristics and regional differences, and constructed a Tobit regression model to test the influence mechanism of each variable on the ECILUs in different regions. This has important theoretical and practical significance for the Chinese government in formulating relevant policies and realizing the green utilization of urban land in the future. Empirical results showed that the ECILUs in most cities were low and that the differences between regions were large. The ECILU in the Western Economic Zone was relatively high, followed by the Eastern, Central, and Northeastern Economic Zones. According to the ECILU value and urban synergy degree of each metropolitan area, this study divided the 13 metropolitan areas into four categories. The regression analysis results showed that the variables had different effects on the ECILUs of all cities and the four economic zones in China. It is suggested that all economic zones should reinforce the optimization of industrial structure, control industrial pollutant discharge, and solve the phenomenon of labor surplus. The Eastern Zone should maintain the growth of its economy while focusing on soil quality. The Central Zone should focus on the efficient use of infrastructure, and the Western, Northeastern, and Central Zones should balance the green coverage area and the industrial land area to ensure the efficient use of urban industrial land.

Eficiência das Ferrovias Especializadas em Transporte de Minério de Ferro e Pelotas

ABSTRACT Objective: the objective is to compare the relative efficiency of the railways specialized in transporting iron ore (MFe) and pellets (PLMFe), which are part of the assets of mining companies and pellet plants considering the 2016 scenario. Methods: the methods used were the data envelopment analysis (DEA) technique, with the application of the output-oriented constant returns scale (CRS) model; the initial combinatorial multicriteria method for choosing the input variables; and Tobit regression as a validation strategy for the DEA model. Results: of the twelve railways evaluated, three railways were identified as efficient: Estrada de Ferro Carajás, Fortescue, and Mount Newman. Conclusions: the applied model was considered a good method to evaluate the efficiency of railways specialized in transporting MFe and PLMFe, as it determined the efficiency of each railway, suggesting the necessary increase in the output variable or adjustments in the input variables so that the railways reach the efficiency frontier. With that, companies can use the results of this study to guide future improvements to make their railways more efficient or maintain them on the frontier of efficiency.

The Efficiency of Railways Specialized in Transporting Iron Ore and Pellets

ABSTRACT Objective: the objective is to compare the relative efficiency of the railways specialized in transporting iron ore (MFe) and pellets (PLMFe), which are part of the assets of mining companies and pellet plants considering the 2016 scenario. Methods: the methods used were the data envelopment analysis (DEA) technique, with the application of the output-oriented constant returns scale (CRS) model; the initial combinatorial multicriteria method for choosing the input variables; and Tobit regression as a validation strategy for the DEA model. Results: of the twelve railways evaluated, three railways were identified as efficient: Estrada de Ferro Carajás, Fortescue, and Mount Newman. Conclusions: the applied model was considered a good method to evaluate the efficiency of railways specialized in transporting MFe and PLMFe, as it determined the efficiency of each railway, suggesting the necessary increase in the output variable or adjustments in the input variables so that the railways reach the efficiency frontier. With that, companies can use the results of this study to guide future improvements to make their railways more efficient or maintain them on the frontier of efficiency.

Charitable Behavior of Muslim in Indonesia during the COVID-19 Pandemic: A Tobit Model Analysis

The COVID-19 pandemic has caused a decline in social welfare. In such a situation, community philanthropy, including from the Muslim community, becomes critical. This study aims to explore the charitable behavior of Muslims in Indonesia during the COVID-19 pandemic. The Tobit regression was used to analyze data from online surveys to determine the pattern changes of donations during the pandemic as well as the factors affecting the amount of donation. This study uncovered that Zakat Management Organizations (BAZNAS and LAZ) were some of the main choices for distributing zakat and alms (sedekah) during the pandemic. It was found that the factors with a positive and significant effect on the probability of increasing the percentage of donations were education, length of stay, and expenses. The results of this study contribute to the policy of developing the Zakat Management Organization as institutions trusted by the community in distributing zakat funds. This study supports the fundraising of the zakat organizations in terms of offering valuable insights and clear description about the Indonesian people’s charitable behavior. More importantly, this study suggests that improving the quality of education is crucial to increase community awareness in performing Islamic philanthropy such as giving zakat, sedekah, and waqf.

Evaluating the Operational Efficiency and Quality of Tertiary Hospitals in Taiwan: The Application of the EBITDA Indicator to the DEA Method and TOBIT Regression

This study estimates the efficiency of 19 tertiary hospitals in Taiwan using a two-stage analysis of Data Envelopment Analysis (DEA) and TOBIT regression. It is a retrospective panel-data study and includes all the tertiary hospitals in Taiwan. The data were sourced from open information hospitals legally required to disclose to the National Health Insurance (NHI) Administration, Ministry of Health and Welfare. The variables, including five inputs (total hospital beds, total physicians, gross equipment, fixed assets net value, the rate of emergency transfer in-patient stay over 48 h) and six outputs (surplus or deficit of appropriation, length of stay, the total relative value units [RVUs] for outpatient services, total RVUs for inpatient services, self-pay income, modified EBITDA) were adopted into the Charnes, Cooper and Rhodes (CCR) and Banker, Charnes and Cooper (BCC) model. In the CCR model, the technical efficiency (TE) from 2015–2018 increases annually, and the average efficiency of all tertiary hospitals is 96.0%. In the BCC model, the highest pure technical efficiency (PTE) was in 2018 and the average efficiency of all medical centers is 99.1%. The average scale efficiency of all medical centers was 96.8% in the BBC model, meaning investment can be reduced by 3.2% and the current production level can be maintained with a fixed return to scale. Correlation coefficient analysis shows that all variables are correlated positively; the highest was the number of beds and the number of days in hospital (r = 0.988). The results show that TE in the CCR model was similar to PTE in the BCC model in four years. The difference analysis shows that more hospitals must improve regarding surplus or deficit of appropriation, modified EBITDA, and self-pay income. TOBIT regression reveals that the higher the bed-occupancy rate and turnover rate of fixed assets, the higher the TE; and the higher number of hospital beds per 100,000 people and turnover rate of fixed assets, the higher the PTE. DEA and TOBIT regression are used to analyze the other factors that affect medical center efficiency, and different categories of hospitals are chosen to assess whether different years or different types of medical centers affect operational performance. This study provides reference values for the improvable directions of relevant large hospitals’ inefficiency decision-making units through reference group analysis and slack variable analysis.

Hubungan Kepemilikan Aset Produksi terhadap Keputusan Petani untuk Menggunakan Varietas Unggul Baru Pepaya Merah Delima (The Association of Production Assets on Farmer Selection of A New Variety, Merah Delima Papaya)

<p>Keputusan untuk mengadopsi varietas atau teknologi baru, terutama bagi petani skala kecil, sangat dipengaruhi oleh kepemilikan sumber daya. Tujuan penelitian ini adalah mengevaluasi pengaruh kepemilikan aset produksi petani terhadap keputusan petani menggunakan Varietas Unggul Baru (VUB) pepaya Merah Delima. Survei dilaksanakan di beberapa sentra produksi pepaya (Sumatra Barat, Riau, Jawa Timur, Jawa Tengah, dan Jawa Barat) melibatkan 46 responden terpilih yang terdiri atas 17 petani pengguna pepaya Merah Delima dan 29 petani penanam pepaya varietas lainnya. Faktor-faktor determinan penggunaan varietas dianalisis dengan menggunakan model regresi Logit dan Tobit. Ketersediaan sarana dan prasarana produksi berpengaruh signifikan terhadap keputusan petani menggunakan VUB pepaya Merah Delima. Pengaruh sarana dan prasarana produksi terhadap probabilitas peningkatan penggunaan varietas lebih dominan dibanding pengaruh faktor-faktor lainnya. Oleh karena itu, program pengembangan VUB pepaya Merah Delima lebih lanjut disarankan perlu didukung dengan bantuan penyediaan alat semprot (sprayer) bertenaga mesin atau ditargetkan di lokasi-lokasi yang tidak terlalu bermasalah dengan tata kelola air.</p><p><strong>Keywords</strong></p><p>Adopsi; Pepaya Merah Delima; Varietas Unggul Baru</p><p><strong>Abstract</strong></p><p>The decision to adopt a new variety or technology, especially for small-scale farmers, is heavily influenced by resource ownership. The purpose of this study was to evaluate the effect of farmer production asset ownership on farmers’ decisions to use Merah Delima papaya high yielding variety (HYV). The survey was conducted in several papaya production centers (West Sumatra, Riau, East Java, Central Java, and West Java) involving 46 selected respondents consisting of 17 farmers using Merah Delima papaya and 29 farmers growing other papaya cultivars. The determinants of farmer decision were analyzed using the Logit and Tobit regression models. The results show that the availability of production facilities and infrastructure has significant effects on farmers’ decisions to use Merah Delima papaya HYV. The influence of production facilities and infrastructure on the probability of increasing the usage of Merah Delima papaya is more dominant than the influence of other factors. Therefore, it is recommended that further Merah Delima papaya HYV development program needs to be supported by the assistance of providing farmers with machine-powered sprayers or prioritized at locations that have few water/irrigation management problems.</p>

Does Firms’ Working Capital Efficiency Matter in Dividend Payout: Empirical Evidence from India

The objective of this study is to assess the impact of working capital efficiency (WCE) (proxied by net trade cycle ( NTC)) on the dividend payout (proxied by dividend payout ratio ( DPR)) of the listed non-financial Indian firms. This study addresses the research gap in the literature about the influence of WCE on firms’ earnings distributed to equity shareholders as dividends in the Indian market. We have used secondary data of 150 firms that were listed on the Bombay Stock Exchange for the period 2012–2018 and analysed the data of the sample firms using the Tobit regression model. Our results indicate a negative and significant relationship between the NTC and the DPR of the sample firms. However, the beta coefficient of NTC was found to be very small, suggesting that the lower NTC may not inevitably generate a higher DPR of firms in the Indian context.

Tobit model-based analysis on the influencing factors of wheat loss during harvesting by the combine harvester

Based on the investigation data of wheat mechanized harvest in eight major wheat producing areas from the south to the north of Henan Province, the main factors affecting wheat mechanized harvest loss were identified and the influence of each factor was decomposed. In this article, the loss rate of wheat mechanical harvest was calculated by using the method of artificial measurement of wheat yield in the field, and the influencing factors of wheat mechanical harvest operation in 8 regions of Henan province were treated and analyzed by using Tobit regression model. In this paper, the loss rate of wheat mechanical harvest was calculated by using the method of wheat field artificial yield measurement and the influencing factors of wheat mechanical harvest operation in eight regions of Henan province were treated and analyzed by using Tobit regression model. The results show that the average harvest loss rate in the field amounts to 2.96%, the average harvest loss rate at the edge of field amounts to 3.06%, whereas the loss rate in the normal operation area amounts 2.86%. The main factors that caused the harvest loss of wheat field machinery were the maturity of wheat, the area of operation field, the diseases and pests, weather conditions and the accumulated working hours of harvester drivers in a single day. Therefore, the main technical measures to reduce the operation loss of wheat combine harvester were put forward to provide a theoretical basis for promoting the deep integration of agricultural machinery and agronomy.

Determinants of adherence to public health and social measures (PHSM) against COVID-19 among the general population in South Korea: A national survey (Preprint)

BACKGROUND Public health efforts to reduce the spread of COVID-19 are the priority of national policy to respond to it globally. The public health and social measures (PHSM) are shown to be effective when used alone or in combination with other measures, reducing the risk of spreading COVID-19. However, there is insufficient evidence on the status of compliance of PHSM in the general population for the prevention of COVID-19 in public areas, including Korea. OBJECTIVE The aim of this study is to assess the level of compliance with the recommended PHSM against COVID-19 infection and its predictors among the general population using national data. METHODS This study is a secondary data analysis using an Infectious Disease Prevention Behaviors in Community Survey conducted by the Korea Disease Control and Prevention Agency (KDCA) between October 12 and October 30, 2020. The primary study was cross-sectional, using stratified sampling with an adjusted proportional allocation method to select representative samples and secure the stability of samples. The data were collected through a phone interview conducted by trained enumerators using a structured questionnaire. The PHSM was measured using a 10-item Comprehensive Infectious Disease Preventive Behavior(CIDPB) scale and each of the socio-cognitive factors, such as perceived susceptibility to COVID-19 infection, perceived severity of COVID-19 infection, perceived confidence in performing preventive behaviors related to COVID-19, information comprehensive ability, and trust in information from the KDCA, were measured by a single question. A total of 4,003 cases were included in the final analysis. A Tobit regression and decision tree were performed to identify the predictors of preventive measures and the targeted group for intervention. RESULTS We discovered that females had a 1.34 point higher CIDPB score than males (P<.001). The participants who were aged between 50 and 59 years performed 1.89 points higher on the CIDPB (P<.001) and the participants who were older than 60 years performed 2.48 points higher on the CIDPB (P<.001) than those who were aged between 19 and 29 years. The perceived severity of infection, confidence in preventive behaviors, information comprehensive ability, and trust in information from the KDCA were statistically significant and positive (P<.001). The perceived susceptibility to infection was statistically significant and negative (P<.001). CONCLUSIONS Being female, older in age, having a lower income, and socio-cognitive factors were significant predictors for performing PHSM. These findings suggest a need for targeted intervention for these specific groups. Adequate government action and policy development are needed to increase the level of health literacy and trust in the healthcare system.