Optimizing efficiency in Tanzanian public hospitals through improved productivity and resource utilization

Exploitation of economies of scale is often argued in favour of blood-bank consolidation into large regional centres, despite a lack of adequate empirical support. This study was aimed at testing the economies of scale hypothesis in a sample of blood centres in the USA. An input-orientated data envelopment analysis (DEA) was used to calculate the technical efficiency scores of blood centres, and to determine whether they were operating under increasing returns to scale (IRS), constant returns to scale (CRS) or decreasing returns to scale (DRS). Correlation between the blood-centre efficiency score and the demographic and socioeconomic characteristics of the service area was further investigated. Seventy-one blood centres were included in the analysis. The scale of operations ranged from 7270 to 275,500 red blood cell (RBC) units per year. Six (8%) centres operated under CRS, 29 (55%) under IRS, and most of their technical inefficiency was scale-independent, and 26 (37%) operated under DRS, and most of their technical inefficiency was size-related. Efficiency scores were unrelated to any demographic or socioeconomic characteristics of the blood centre service area. Within the size range of blood centres included in this study, expanding the level of operations beyond a certain point leads to DRS.

This study has a twofold. First, it aimed to measure the efficiency of the insurance sector in the Kingdom of Saudi Arabia during the period 1995-2022. Efficiency was measured using the Data Envelopment Analysis (DEA) method, employing three inputs: general and administrative expenses, underwriting costs, and direct written premiums, and one output represented by the insurance operations surplus. The study also relied on the Malmquist Index to calculate and determine the nature of changes in the total factor productivity (TFP) of insurance companies. The results showed that only one company, Inaya Saudi Arabia Cooperative Insurance, achieved the optimal level of efficiency. Furthermore, the Malmquist Index results indicated a slight decrease in overall productivity, accompanied by a decline in pure technical efficiency and a reduction in scale efficiency. The Second objective of the research was the study of the impact of insurance sector efficiency on economic growth using the Autoregressive Distributed Lag (ARDL) model. Three models were estimated, considering three indicators of efficiency: insurance sector efficiency under constant returns to scale (CRS), under variable returns to scale (VRS), and the Malmquist Productivity Index. The findings revealed a long-run relationship between the efficiency of the insurance sector and economic growth. In the short run, the Error Correction Model (ECM) showed that efficiency has a negative and significant effect in both the CRS and VRS models, while its effect was positive and significant in the productivity index model. The causal relationships between insurance sector efficiency and economic growth were apprehended using the Toda-Yamamoto method. The results indicated a bidirectional causal relationship between insurance sector efficiency and economic growth in the constant returns to scale (CRS) model. In contrast, the variable returns to scale (VRS) model showed no causal relationship. The Malmquist Index model demonstrated the broadest connection with economic variables and the largest number of causal relationships directed toward economic growth among the models. Our results would have several prominent implications for policymakers when designing strategies to improve the performance and efficiency of the insurance sector, consistent with the economic diversification strategy outlined by the Kingdom in its Vision 2030.

Rice farming plays a critical role in ensuring food security and economic stability in Bangladesh, with environmental conditions significantly affecting its productivity and efficiency. This study assesses the impact of climatic, soil and ecological factors on the performance of three major rice varieties Aus, Aman and Boro using secondary data from 1980 to 2021. Data Envelopment Analysis (DEA) was employed to estimate technical efficiency and Total Factor Productivity (TFP) growth while Tobit regression models were used to quantify the influence of environmental variables including average temperature, rainfall, humidity, sunshine and wind speed, under both Constant Returns to Scale (CRS) and Variable Returns to Scale (VRS) assumptions. The results revealed that average temperature showed a significant positive effect on all rice types under both CRS (β = 0.3356, p < 0.001) and VRS (β = 0.0813–0.1949, p < 0.05) models. Rainfall slightly improved Aman efficiency under CRS (β = 0.0001, p < 0.05) and had mixed effects under VRS positive for Aus (β = 0.0013, p < 0.10) but negative for Aman (β = –0.0027, p < 0.05). Humidity decreased Aus and Aman efficiency under CRS (β = –0.1001 and –0.0531, p < 0.01) but enhanced Boro under VRS (β = 0.0224, p < 0.05). Sunshine reduced efficiency for Boro (β = –0.1699, p < 0.001) and Aman (β = –0.1953, p < 0.001), while wind speed had negative effects on Aus and Aman under CRS (β = –0.1563 and –0.1971, p < 0.05) and a positive impact on Aus under VRS (β = 0.3719, p < 0.05). These findings underscore the differential sensitivity of rice varieties to environmental fluctuations and provide valuable insights for climate-resilient rice production and sustainable agricultural policymaking in Bangladesh. IJSS, Vol. 26(1), March, 2026, pp 39-51

Healthcare organizations must operate efficiently to provide affordable care without compromising their sustainability and competitiveness. The purpose of this is to measure the profit efficiency of select Indian Corporate Hospitals during the COVID-19 pandemic. Further, the study attempts to analyze the productivity changes in select corporate hospitals during COVID-19 and postimplementation of the national insurance policy in India. The study used the Data envelopment analysis (DEA) technique to measure the efficiency of corporate hospitals. It utilizes Constant Return to Scale (CRS), and Variable Return to Scale (VRS) to estimate profit inefficiency. DEA-based Malmquist Productivity Index (MPI) was used to examine the productivity change during the last three years since the outbreak of COVID-19. The DEA-MPI model is iterated for panel data for Financial Year 2018–2021. with year-wise employee benefits and operating expenses as the input parameters and year-wise net sales as the output parameter. The study reveals surprising results and requires critical analysis. Out of select hospitals, 80% of hospitals were found inefficient using CRS while 70% of the hospitals were found inefficient using VRS. The findings of this study are useful for healthcare administrators and managers to highlight improvement programs for efficiency maximization .

This study is aimed to examine the efficiency and productivity growth of Initial Public Offerings (IPOs) firms listed on Karachi Stock Exchange (KSE), Pakistan from 2000 to 2012 by using three stages - Data Envelopment Analysis (DEA) and Malmquist Productivity Index (MPI). The analysis and comparison of the efficiency and productivity growth of IPOs on sectoral basis in the pre and post period of IPOs is also investigated. This is ever first study to measure the pre IPO efficiency across the globe in the field of IPOs. The overall efficiency scores of IPO firms dismal as the percentage of optimum level of IPO firms remain between 5% and 20% in all the three stages in pre and post IPOs. In the analysis of broader categories of sectors; private, state-owned enterprises (SOEs), manufacturing, financial, other services sectors, the results of DEA model of three stages suggest that neither of the sector is constant return to scale (CRS) efficient nor and Variable Returns to Scale (VRS) in pre and Post IPO. Even the efficiency scores are decreased in post IPO after one year. However, in detail sector-wise analysis the only oil and gas sector showed optimal level under VRS in stage 2. Further, SOEs showed some better efficiency than private IPO firms. The overall results of declining trend in total productivity growth of IPOs after three years period in KSE are observed. The overall results suggest that, after acquiring further resources, IPO firms did not improve their efficiency level and productivity growth after the period of three years of IPOs. DOI: http://dx.doi.org/10.5755/j01.ee.27.2.10062

The present study examined the economic efficiency of rubber smallholders in Peninsular Malaysia in a disaggregated form using Banker Charnes and Cooper (BCC) and Charnes Cooper and Rhodes (CCR) models of data envelopment analysis (DEA) as well as their respective bootstrap techniques. Multistage data collection was employed on 327 smallholders among 5 districts of Negeri Sembilan state. However, only 307 observations were used in computing inferential statistics, because the young-age category has been removed. The districts include Seremban, Tampin, Rembau, Kuala Pilah and Jempol. The results revealed that, the mean technical efficiency (TE) under variable returns to scale (VRS) and constant returns to scale (CRS) were 0.95, 0.97 0.96 and 0.45, 0.61, 0.33 for the all-age, matured-age and old-age crops respectively. The findings of the result also disclosed that naïve DEA has higher mean scores than bootstrapped-DEA, thus indicating the presence of bias in the former and absence of bias in the later. Also, the efficiency determinants under VRS and CRS as well as their respective bias-corrected (BC) efficiency scores were also analyzed using Tobit regression analysis against the 15 socio-demographic factors. It was found out that critical factors, common to all the age-categories, include educational level, tapping system and marital status under VRS and BC-VRS assumptions, while under CRS and BC-CRS assumptions include race, tapping system, marital status and farm’s distance. Therefore, education of smallholders should be given more attention to increase efficiency. The study finally recommends that the traditional concept of computing efficiency or productivity of rubber and other perennial crops in an aggregated form should be complemented with the disaggregated form as this eliminates any bias and gives meaningful results. Improved methods such as bootstrapping should also be used as this only gives what is called bias-corrected efficiency scores. Regarding the determinants, factors such as education, tapping system and farm distance should be given more emphasis.

This paper investigates the extent, dynamics, and factors influencing technical efficiency (TE) and capacity utilisation (CU) in small-scale fisheries (SSF) using a two-stage data envelopment analysis (DEA) approach covering the period 2010–2012. A considerable extent of boat-level technical inefficiency, capacity underutilisation and scale inefficiency were evident. On average, TE and CU levels under the constant returns to scale (CRS) and variable returns to scale (VRS) models declined over time. The TE and CU scores of 2010 remained unaltered with the addition of ‘fishing time’ as an input to the model. The proportion of boats with unitary scale efficiency (SE) decreased from 26 % in 2010 to 12 % in 2012. The underutilisation rates of the inputs ‘crew’ and ‘fishing time’ ranged from 15.5 % to 31.6 % and 15.8 % to 28.6 %, respectively. Among the species category, the extent of excess capacity was 70 % to 156 % and 47 % to 119 % under the CRS and VRS models, respectively. The second-stage DEA results indicated that the explanatory variables ‘fishing location’, ‘catch per unit of effort’ (CPUE), ‘fuel costs’ and ‘crew share’ significantly influenced CU under the CRS model. In contrast, the significant influence of subsidies and other operating costs were noted under the VRS model. For the TE case, ‘age’, ‘education’, ‘subsidy’ and ‘CPUE’ were found to be significant under the CRS and VRS models. Other significant variables were found in the study under CRS and VRS models. Finally, the results from the descriptive and empirical analysis under the two-stage DEA model are discussed together with policy implications.

An analysis of energy consumption and carbon dioxide emissions in countries of the Middle East and North Africa

Productivity measurement is assumed as one of the main guidelines to assess the effectiveness and efficiency of organisations. Productivity of the bank branches as main players of financial systems should be measured periodically. In this paper, the productivity and its components (i.e., technical efficiency change and technological frontier change) in 42 profit-making branches of a private bank in Tehran province, Iran, are analysed during the period 2014-2016. Inefficient bank branches are determined. The projection of inefficient bank branches toward efficient frontier is also discussed. Productivity and technical efficiency of production elements of branches of a private bank are investigated by Malmquist productivity index (MPI) and an input-oriented data envelopment analysis (DEA) in constant returns to scale (CRS) and variable returns to scale (VRS) conditions. Based on results, scale inefficiency had the greatest impact on technical efficiency in the case study.

Governments used seed subsidy as an incentive to encourage crop diversification and use of high yielding varieties. In present study, an attempt has been made to study farm efficiency of groundnut seed subsidy in Ananthapuramu district of Andhra Pradesh. For this purpose, two mandals (Kanaganapalli, Gudibanda) were selected based on highest number of subsidy benefited farmers. The data pertains for the year 2021 kharif season for 64 seed subsidy beneficiary and 136 non-beneficiary farmers. The data was collected from each respondent through personal interviews with the help of structured schedules. Data Envelopment Analysis (DEA) was employed to analyze technical efficiency and scale efficiency of the farmers. For better comparison, all the farmers were divided into two categories viz. subsidized and non-subsidized and propensity score matching is also used. The empirical results observed that the overall mean Variable Returns to Scale (VRS) efficiency was 0.760, Constant Returns to Scale (CRS) efficiency was 0.70. The positive impact of seed subsidy is visible, as seed subsidy beneficiary farmers mean VRS efficiency was 0.916 which is greater than non-subsidized farmer’s i.e. 0.716. The variation is because of high input costs incurred to the non-subsidized farmers. The regression results also indicates that seed subsidy is positive influence on efficiency (VRS), efficiency (CRS) and scale efficiency to the extent of up to 20% increase in efficiency. Yet it has also been noticed that farmers still rely on non-subsidized sources for their seed requirement, because they could not meet the conditions of availing seed subsidy from the Andhra Pradesh state government.

This study analyzes the technical, allocative, and cost efficiency of Eucheuma cottonii seaweed production in Situbondo Regency, East Java, a major Indonesian producer. A census was conducted on 60 farmers in Agel Village and Pathek Beach. Primary data included inputs (seeds, plot area, labor, fuel) and output (dried seaweed production), analyzed using Data Envelopment Analysis (DEA) with DEAP 2.1, applying Constant Return to Scale (CRS) and Variable Return to Scale (VRS) approaches.The production process involves site preparation to harvesting (40-45 days), yielding 800-1,500 kg of dried seaweed per cycle. Average technical efficiency was 0.713 (CRS) and 0.873 (VRS), indicating that most inefficiencies arise from sub-optimal operational scale. Average allocative efficiency of 0.835 suggests farmers haven't fully optimized input combinations based on market prices. Average cost efficiency was only 0.799, with only 11.67% of farmers being cost-efficient, highlighting significant opportunities for improving operational cost management.Recommendations include enhancing farmers' managerial and technical capacity through training on efficient input use and business scale adjustment. Local government is encouraged to provide intensive assistance for optimizing input allocation and production cost management. Future research should consider a metafrontier DEA approach for cross-group or regional efficiency comparisons, and include variables like education level and experience for a more comprehensive analysis.

This study measured the cost efficiency and estimated the optimal cost structure in operating and maintaining the irrigation systems of eight provinces in the Red River Delta (RRD), Vietnam, from 2014 to 2016 using the input-oriented model of data envelopment analysis. The inputs included in the model were the costs of labor, materials, electric energy for irrigation, irrigation structure safety, maintenance, depreciation, administrative expenses, and overhead cost. The output was the irrigation area, which was converted to paddy areas. The findings of this study showed a large inefficiency in using the total input financial cost subsidized. The optimal technical efficiency scores under constant returns to scale (CRS) and variable returns to scale (VRS) were 0.86 and 0.98, respectively. The results implied that total input costs should be reduced by 14% under CRS and 2% under VRS to avoid cost inefficiency. The results also showed that scale efficiency occurred in the operation and maintenance (O&M) management of the irrigation systems. The O&M management in the irrigation systems in the RRD should allocate the major proportion of the costs to labor to be efficient. Application of the optimal input cost structure would improve irrigation management performance for the RRD region by 48.7% for the efficient input target (EIT) under CRS and by 5.03% for the EIT under VRS. These were the significant bases for recommending policy options for reviewing the irrigation tariff subsidy according to each input factor. And then it could create the incentives for private participation partnership in the irrigation sector.

Purpose: This study aimed to characterize the performance of Colombian Micro, Small, and Medium-sized Enterprises (MSMEs) in recent years, along with the legal framework and central public policies governing and promoting this business segment. In addition, it sought to design, validate, and implement a dynamic system of productivity indicators to help these companies improve their efficiency and competitiveness in the short, medium, and long terms. MSMEs represent approximately 99% of the business sector in Colombia, accounting for nearly 80% of national employment. Design/Methodology: In the initial descriptive–analytical phase, using secondary sources, an analysis was conducted on the performance and current situation of Colombian MSMEs, as well as the main legal provisions regulating and contributing to their development. The subsequent phase (of an applied nature) involved estimating and validating a dynamic system of productivity indicators using Data Envelopment Analysis (DEA) and Malmquist indexes for 2 samples of SMEs. Findings: After conducting the DEA, a significant decrease was observed in the productivity of the MSMEs, particularly in terms of technical efficiency in both the Constant Returns to Scale (CRS) and Variable Returns to Scale (VRS) models. This means that, evaluated both under the CRS and VRS modes, these enterprises use more inputs than necessary for the amount of goods produced. In addition, the Malmquist indexes showed that, during the period under analysis, technical efficiency related to changes in innovation exhibited a positive behavior, attributed to the incorporation of technological changes for improving their productivity. Conclusions: Despite the development of public initiatives and institutional support in recent decades, Colombian SMEs still face adverse conditions that affect their competitiveness and limit their potential in the national economy. The proposed system of indicators, which is based on DEA techniques and Malmquist indexes, holds promise in helping these businesses to improve their productivity. Originality: This study makes a significant contribution to the fields of economics and business management in the region by providing a critical and updated evaluation of the efficiency of MSMEs in Colombia. Additionally, it examines their performance and current situation and summarizes the main legal provisions regulating and contributing to their development in the country.

The purpose of this paper is to develop an output oriented methodology with constant return to scale (CRS) assumption for calculating productivity changes by using double frontier (optimistic and pessimistic) data envelopment analysis (DEA) simultaneously for two-stage processes. Measuring the productivity changes with Malmquist productivity index (MPI) via double frontiers DEA with single process has been defined by Wang and Lan (2011) as a geometrically average of optimistic and pessimistic point of views to generate an aggregate MPI. In order to develop and modify the previous studies, in this paper we have proposed a method to modify Wang and Lan (2011) aggregate MPI and also extend it to two-stage process which we refer to the double frontiers two-stage DEA (DFTDEA). It should be mentioned that the proposed model of this paper measures the MPI's distance functions for two individual stages and whole process for both DEA different points of view by the traditional DEA models and supposed relational models in output oriented CCR models, respectively. Therefore, the identified double frontiers two-stage DEA (DFTDEA-based MPI) is more realistic and comprehensive than the conventional optimistic or pessimistic DEA-based MPI individually. Subsequently, the proposed approach is examined to five Iranian commercial banks over the five-year period, 2009-2013.

This study evaluates the determinants of public spending efficiency at the provincial level in Peru by integrating Data Envelopment Analysis (DEA) with two alternative econometric models: a bootstrapped random-effects Tobit model and a spatial Durbin model. Using panel data from 196 provinces over 7 years, DEA efficiency scores under constant returns to scale (CRS) and variable returns to scale (VRS) were estimated and analyzed to assess the impact of intergovernmental transfers, local tax revenues, and spatial interdependencies. The Tobit model accounts for the bounded nature of efficiency scores and shows that FONCOMUN transfers significantly improve both technical efficiency (VRS_TE) and scale efficiency, while canon transfers primarily enhance scale efficiency due to their infrastructure-oriented allocation but have limited effects on managerial performance. Local tax revenues positively influence technical efficiency, reflecting better expenditure management in fiscally autonomous municipalities, but they have no significant effect on scale efficiency. In contrast, the spatial Durbin model captures spatial dependencies and reveals significant negative spillover effects, indicating that higher efficiency in neighboring provinces can reduce local efficiency due to competition for resources and overlapping administrative functions. These findings contribute to the literature by providing robust empirical evidence on the interplay between fiscal transfers, managerial capacity, and spatial interdependencies, offering actionable insights for policymakers seeking to optimize local government performance and improve public service delivery.