Two-Step Estimation of the Impact of Contextual Variables on Technical Efficiency of Hospitals: The Case Study of Public Hospitals in Iran

Background: Measuring the efficiency and productivity of hospitals is a key tool to cost contamination and management that is very important for any healthcare system for having an efficient system.Objective: The purpose of this study is to examine the effects of contextual factors on hospital efficiency in Iranian public hospitals.Methods: This was a quantitative and descriptive-analytical study conducted in two steps. First, we measured the efficiency score of teaching and non-teaching hospitals by using the Data Envelopment Analysis (DEA) method. Second, the relationship between efficiency score and contextual factors was analyzed. We used median statistics (first and third quarters) to describe the concentration and distribution of each variable in teaching and non-teaching hospitals, then the Wilcoxon test was used to compare them. The Spearman test was used to evaluate the correlation between the efficiency of hospitals and contextual variables (province area, province population, population density, and the number of beds per hospital).Results: On average, the efficiency score in non-teaching hospitals in 31 provinces was 0.67 and for teaching hospitals was 0.54. Results showed that there is no significant relationship between the efficiency score and the number of hospitals in the provinces (p = 0.1 and 0.15, respectively). The relationship between the number of hospitals and the population of the province was significant and positive. Also, there was a positive relationship between the number of beds and the area of the province in both types of teaching and non-teaching hospitals.Conclusion: Multilateral factors influence the efficiency of hospitals and to address hospital inefficiency multi-intervention packages focusing on the hospital and its context should be developed. It is necessary to pay attention to contextual factors and organizational architecture to improve efficiency.

The efficiency of major industrial enterprises in Sichuan province of China: A super slacks-based measure analysis

<p style='text-indent:20px;'>The main objective of this research is to measure the efficiency of 397 major industrial enterprises in Sichuan province of China in 2013.To this end, we employed DEA super slacks-based measure (Super-SBM) model for performance evaluation of 397 major manufacturing firms.The empirical results show that 21 of the 397 enterprises operate efficiently, and the average efficiency score of the analyzed enterprises is only 0.15. The enterprise with the highest efficiency score is 96.15% higher than the average score, which is the benchmark enterprise of operational efficiency. Among the selected sample enterprises, 5.29% of the industrial enterprises are highly efficient in operation. It was also noticed that the average efficiency score of pharmaceutical firms was the highest among all industrial firms with a mean score of 0.75, which is 80% higher than the overall average score of all industries. While the average efficiency of manufacturing of chemical raw materials and chemical products was the lowest with a mean score of 0.39. Results of sensitivity analysis show that profit has a great impact on the efficiency score of special equipment manufacturing firms, but a relatively weak impact on the firms which manufacture computers, communications, and other electronic equipment. The effect of export delivery value on efficiency score is not obvious.</p>

A Novel Enhanced Russell Graph Efficiency Measure in Network DEA

Hitherto, the presented models for measuring the efficiency score of multi-stage decision-making units (DMUs) either are nonlinear or require to specify the weights for combining their divisional efficiencies. The nonlinearity leads to high computational complexity for these models, especially when used for problems with enormous dimensions, and also assigning various weights to the divisional efficiencies causes to obtain different efficiency scores for the multi-stage network system. To tackle these problems, this study contributes to network DEA by introducing a novel enhanced Russell graph (ERG) efficiency measure for evaluating the general two-stage series network structures. Then, the proposed model is extended into the general multi-stage series network structures. This study also describes the managerial and economic implications of measuring the efficiency score of the multi-stage DMUs and provides two numerical and empirical examples for illustrating the use of our proposed model.

PERFORMANCE OF CZECH FOOTBALL CLUBS: MALMQUIST INDEX APPROACH

Sport has become an important part of our lives in the modern times and sporting sites contribute significantly to the image and texture of modern cities. Regarding the popularity of sport, and football in particular, it has become an important modern place where specific types of economic and social interaction take place. The aim of this article is to propose a method for evaluating the performance of football clubs based on DEA and Malmquist index. Professional Czech football clubs playing in the Czech football competition Fortuna:Liga were selected for empirical analysis. To analyze the relative efficiency of football clubs, BCC and CCR models were employed. The study was conducted on a sample of 20 clubs through 2 inputs and 1 output collected during the 2015/16 – 2019/20 seasons. For some clubs the values of the Malmquist index were calculated. With help of MI it was possible to quantify the total productivity change factor and to decompose it to technological change and technical efficiency change. The results show that Czech football clubs achieved a relatively high level of efficiency in the period monitored and that traditional clubs achieved the highest efficiency score. These results could help club managers improve the performance of their teams.

Technical Efficiency of Mung Bean Producers: The Case of Myanmar

Agriculture plays a key role in Myanmar and it is the backbone of the country’s economy. Among the major export-earning crops in Myanmar, mung bean is one of the important, and it creates many opportunities for smallholders. About 90% of the total production of mung bean is exported for overseas or border trade and has extended markets, especially China, Vietnam and EU countries. This study aims to measure the level of technical efficiency of green mung bean producers and determine the factors influencing the technical efficiency of mung bean production in Tatkon Township, Myanmar. Data from 144 farms were analyzed using a DEA model and Tobit regression. The empirical results reveal that about 46% of farmers had an efficiency score of more than 0.90, which indicates that 54% of farmers were relatively inefficient in their production. The results also show that socioeconomics factors, such as age of farmers, farmers participating in associations and soil fertility, had a significantly positive impact on technical efficiency. Gender, education, access to credit and extension services had a positive impact on the technical efficiency of mung bean production in the study area. To reduce inefficiency, the government should consider providing more services to male farmers and older farmers to improve their capacities, as well as providing an extension of services, new technologies, credit and improved variety for mung bean production.

Determination of human DNA replication origin position and efficiency reveals principles of initiation zone organisation

Replication of the human genome initiates within broad zones of ~ 150 kb. The extent to which firing of individual DNA replication origins within initiation zones is spatially stochastic or localised at defined sites remains a matter of debate. A thorough characterisation of the dynamic activation of origins within initiation zones is hampered by the lack of a high-resolution map of both their position and efficiency. To address this shortcoming, we describe a modification of initiation site sequencing (ini-seq) based on density substitution. Newly-replicated DNA is rendered heavy-light (HL) by incorporation of BrdUTP, unreplicated DNA remaining light-light (LL). Replicated HL-DNA is separated from unreplicated LL-DNA by equilibrium density gradient centrifugation, then both fractions are subjected to massive parallel sequencing. This allows precise mapping of 23,905 replication origins simultaneously with an assignment of a replication initiation efficiency score to each. We show that origin firing within initiation zones is not randomly distributed. Rather, origins are arranged hierarchically with a set of very highly efficient origins marking zone boundaries. We propose that these origins explain much of the early firing activity arising within initiation zones, helping to unify the concept of replication initiation zones with the identification of discrete replication origin sites.

Train Dwell Time Efficiency Evaluation with Data Envelopment Analysis: Case Study of London Underground Victoria Line

Train dwell time is a complicated component and depends on many factors. One of the dominant factors is passenger volume. This study used actual train movement data and passenger demand data from London Underground, UK, to estimate the number of passengers and train dwell times at each station, and then evaluated train dwell times from a different perspective. Considering the various characteristics of stations, it is complicated to evaluate dwell time. Therefore, data envelopment analysis (DEA) was introduced to evaluate the dwell time at each station in relation to passenger volume at that station. The study investigated whether the dwell time spent at stations is efficient when considering the number of passengers that the stations can serve. The results showed that, in low-passenger-volume stations, the dwell time efficiency score is low and increases relative to the increase in passenger volume. For high-passenger-volume stations, interactions between passengers are more relevant and have a strong influence on dwell time. Passenger movement direction is a key factor to classify stations. This research proposes that stations should be classified according to their characteristics, and points out the challenge at any station with the same characteristics as Victoria station which has high passenger volume with bi-directional flow, and where trains arriving are crowded. This characteristic would result in high interactions between passengers, thus making a long dwell time. The station has to handle high passenger volume and also has to keep the dwell time within the threshold.

The Impact of Liberalization on Determinants of Bank Efficiency: Evidence from Malaysian Commercial Banks

This paper aims to examine the impact of liberalization in 2009 on the determinants of bank efficiency in Malaysia by employing a two-stage approach within the context of the growing number of foreign commercial banks. Commercial banks can play a vital role in the internationalization and diversification of Malaysia's financial sector. In the initial stage, measuring the efficiency score of 19 commercial banks throughout 2008 to 2019 by using the Data Envelopment Analysis (DEA). Multivariate panel regressions were then used to determine the impact of liberalization on the determinants of bank efficiency in 2009. As a result, domestic commercial banks seem to be more competitive than their foreign counterparts. The findings signify that bank size, market power, capitalization, and liquidity all have a positive impact on technical efficiency. However, credit risk, bank diversification, and inflation all have a negative impact. The control of the effects of liberalization, bank size, capitalization, bank’s market power, and liquidity remain positive. However, bank diversification and inflation flip negative to positive, whereas credit risk becomes less explanatory. The findings will provide bank stakeholders, regulators, investors, and regulators with important insights into the impact of liberalization measures on bank efficiency and its determinants.

Financial performance of the textile industry in India: the case of Haryana

Purpose This study aims to evaluate the financial performance of the textile industry in Haryana located in the northern part of India. Design/methodology/approach Input-oriented Cooper, Charnes and Rhodes (CCR) and Banker, Charnes and Cooper (BCC) techniques of data envelopment analysis, as well as the return to scale (RTS) technique, were used to conduct the analysis. Findings The findings show that textile units in Haryana have hugely underperformed financially with a consolidated technical efficiency score of only 0.35. Both private and public limited textile companies with respective scores of 0.46 and 0.24 are technically efficient. Public limited textile companies are more efficient than private limited companies. Private limited textile companies need to increase their input scale because they are operating at an increasing return to scale while public limited textile companies have to lower their input scale because most companies are operating at a decreasing return to scale to enhance their efficiency. Originality/value The study can assist in decision-making to all key stakeholders (Shareholders, management, government, tax authorities, debtors and creditors, among others) by identifying efficient and inefficient companies. Appropriate policies can be framed based on that knowledge.

Exploring PM2.5 Environmental Efficiency and Its Influencing Factors in China

In China, air pollution, especially fine particulate matter (PM2.5) pollution, has become increasingly serious with the rapid economic growth that has occurred over the past 40 years. This paper aims to introduce PM2.5 pollution as a constraint in the environmental efficiency research framework through the use of panel data covering the Chinese provinces from 2001–2018. PM2.5 environmental efficiency is measured with the slack-based measure (SBM)-Undesirable-variable returns-to-scale (VRS) model, and the results show that the average PM2.5 environmental efficiency score is 0.702, which indicates inefficiency, and is U-shaped over time. The PM2.5 environmental efficiency scores are unbalanced across the eight regions and 30 provinces of China. Additionally, the relationship between PM2.5 environmental efficiency and its influencing factors is examined with a tobit model, and the empirical findings indicate that the relationship between economic development and PM2.5 environmental efficiency is an inverted U, which is the opposite of the traditional environmental Kuznets curve (EKC). In addition, technological innovation, trade dependency, and regional development each have a significantly positive effect on PM2.5 environmental efficiency. However, environmental regulations, the industrial structure, and population density have significantly negative effects on PM2.5 environmental efficiency. Finally, this paper fails to prove that foreign direct investment (FDI) has created a PM2.5 “pollution haven” in China.