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Abstract Purpose The aim of this paper is to identify the factors influencing efficiency of urban public transport (UPT) systems and to benchmark Czech UPT systems according to their efficiency. Methods The analysis was carried out on a sample of 19 UPT systems in the Czech Republic during 2010–2015. Efficiency was evaluated through a two-stage analysis. Data envelopment analysis (DEA) was used in the first stage. It was based on three inputs (employees, rolling stock and energy) and one output (passengers). DEA efficiency scores were computed for all 19 systems for each year and under two different assumptions regarding returns to scale. In the second stage of the analysis, DEA scores were used in Tobit regression with a set of operational, socio-economic, and demographic explanatory variables in order to find determinants of efficiency. Results Several variables were identified as factors increasing efficiency - proportion of drivers, average vehicle age, the presence of tramlines in the city, total vehicle kilometres, and population density. Some variables were identified as decreasing efficiency – ticket price, proportion of subsidies in revenues, and presence of a two-city system. Czech cities with most efficient transport systems were Prague, Brno, Mariánské Lázně, Olomouc, and Pilsen. The least efficient cities were Chomutov–Jirkov, Ostrava, and Děčín. Conclusions The principal lesson from this study is that bigger cities with greater population densities are more efficient than smaller cities, and the key efficiency factors that local authorities have under their control are the ticket price, rate of subsidies, and structure of the city transport system. The paper contributes to current debate about the efficiency of the urban transport systems and their determinants. There was not much difference between the constant and variable returns to scale results. The results from the second stage could help policy makers make the public transport systems more efficient. Future research could be devoted to gaining data on additional operators which would also enable using additional inputs and outputs for DEA analysis.

Abstract Background While health needs and expenditure in the Occupied Palestinian Territories (OPT) are growing, the international donations are declining and the economic situation is worsening. The purpose of this paper is twofold, to evaluate the productive efficiency of public hospitals in West Bank and to study contextual factors contributing to efficiency differences. Methods This study examined technical efficiency among 11 public hospitals in West Bank from 2010 through 2015 targeting a total of 66 observations. Nationally representative data were extracted from the official annual health reports. We applied input-oriented Data Envelopment Analysis (DEA) models to estimate efficiency scores. To elaborate further on performance, we used Tobit regression to identify contextual factors whose impact on inefficient performance is statistically significant. Results Despite the increase in efficiency mean scores by 4% from 2010 to 2015, findings show potential savings of 14.5% of resource consumption without reducing the volume of the provided services. The significant Tobit model showed four predictors explaining the inefficient performance of a hospital (p

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. [ABSTRACT FROM AUTHOR]

The study aims to a comprehensive measure of listed insurance companies' technical efficiency in GCC countries and benchmarking, peer count summary, and measuring productivity changes in the first stage. In the second stage, the technical efficiency, pure technical efficiency, and scale efficiency scores have been regressed with internal (company variables) and external environmental variables. This paper first examines financial freedom and reinsurance activities on 60 insurers' efficiency from all GCC countries during 2016–2019. The results suggest a positive impact of economic freedom, solvency on technical efficiency components, and the negative effect of reinsurance ceding, market concentration on GCC insurers' technical efficiency. In productivity changes, UAE companies are doing well as compared to other countries' insurers. Overall, GCC insurers' efficiency is improving with pure technical efficiency having a CAGR of 2.13% and scale efficiency a CAGR of 2.96%. Based on the peer count summary, only the UAE and Saudi Arabia's companies can be benchmarked against another insurance company. Also, this research is one of the most comprehensive ones in the GCC region; this is the first study on an extensive data set to the best of our knowledge, including conventional insurers operating across GCC countries. This study is based on 60 insurers listed on the stock exchanges of six GCC countries. This will also be the first empirical evidence on the GCC insurers, which measures the impact of company-specific variables and unique environmental variables separately on the two components of technical efficiency using Tobit regression. The positive association of competition and financial freedom with technical efficiency may encourage regulators and policymakers to ensure less government intervention and give more support and freedom for a better competitive insurance industry. [ABSTRACT FROM AUTHOR]

This paper analyses the performance of non-banking finance companies (NBFC) in the Indian context using data envelopment analysis (DEA). The underlying objective of this study is to fill the void in the domain of NBFC, although a lot of research has been done on the banking industry in the context of the application of DEA, but none on NBFCs. The paper takes the panel data of the last 5 years (2014–2018) to calculate super-efficiencies in the first stage and then regresses the same on exogenous factors in stage-2. Descriptive statistics are used to estimate the efficiency by carrying out the calculations using both the traditional models (OTE, PTE and SE) and super-efficiency model. A comparison is made by categorizing NBFC's based on the size of total assets and using non-parametric statistic tests to find whether the efficiency scores are significantly different across different categories. The second stage DEA analysis uses Tobit regression to find the exogenous factors which affect the model significantly. Based on traditional models, the total number of efficient DMUs are 8 out of 43 while there are 15 after considering the super-efficiency algorithm. Malmquist Indices are used to study the productivity indices of NBFCs over the last 5 years, and it gives us a maximum productivity growth of 8.53%. It was noticed that there is a significant difference in the mean efficiency values of different sized NBFC's which can be explained by the lack of standardization in the NBFC domain and the few companies which are listed on the stock market. The managers should not consider ROE as a significant indicator of efficiency and should instead focus on aspects such as ROA and income diversity. Through the Malmquist analysis, the managers can break down the productivity change into technical and efficiency shifts for further investigation. [ABSTRACT FROM AUTHOR]

Airlines are an important part of the comprehensive transportation system. Therefore, it is of great practical significance to empirically analyse the measurement of airlines' environmental efficiency and influencing factors. Adopting the SBM-DEA model, this study measured the environmental efficiency of 20 Chinese airlines between 2010 and 2017 and empirically analysed the factors influencing their environmental efficiency using a Tobit regression model. Spring Airlines, China Southern Airlines, and Hainan Airlines were found to have the highest environmental efficiency. Tianjin Airlines, Hebei Airlines, and China Express Airlines had the lowest environmental efficiency. The Tobit regression results showed that average flight distance, load factor, market share, and proportion of cargo and mail turnover had a significant positive effect on airline environmental efficiency. Fuel consumption per ton-km had a significant negative effect on airline environmental efficiency. [ABSTRACT FROM AUTHOR]

The aim of this paper is to assess the efficiency of a set of 62 precious metal mutual funds (PMMFs) and to explain performance differences between funds using weighted additive data envelopment analysis (DEA) and Tobit regression, respectively. The contribution of this paper is twofold: to provide for the first-time metrics of the relative performance of PMMFs using a particular weighted additive model, namely the range-adjusted measure (RAM), and to explain the performance of the funds by the use of a Tobit model. Results do not suggest positive linkages between RAM-based and standard fund performance metrics (Sharpe ratio and Jensen's alpha). Moreover, for the sample inefficient funds the mean--variance performance hypothesis does not hold. In addition, fund performance based on RAM can be explained by the persistence of the fund and the beta coefficient. [ABSTRACT FROM AUTHOR]

The future of agriculture is dependent on an increase in the use of resources at disposal, it is therefore imperative that strategies to increase agricultural growth should be directed towards increasing efficiency of smallholder farming operations and resource utilization. This study examined the economic efficiency of rice production. A multistage sampling procedure was used to select 240 rice farmers and data were obtained with the use of a structured questionnaire. Data collected were analyzed with descriptive techniques, stochastic frontier analysis (SFA) and the Tobit regression model. The SFA result revealed that input variables such as seed, herbicide and pesticide were positive and had a significant effect on rice output. Rice farmers were able to maximize their output by 74% at the lowest minimum cost possible. Furthermore, economic efficiency was positively influenced by age, level of education, membership in farmers' associations, access to the public market and access to healthcare facilities; while household size, farming experience, poor road conditions and distance to the nearest marketplace had negative effects. The study concluded that rice farmers were inefficient. Therefore, in order to increase rice production efficiency and improve the livelihood of smallholder farmers, farmers should receive formal and informal education. As it is a key policy issue in the study area, farmers should strengthen the existing association structures and organize new farmers' associations. Also, local and regional governments were encouraged to provide good road networks and a public market that will enable farmers to dispose off their produce at attractive places and prices of their choice. [ABSTRACT FROM AUTHOR]

The study investigates and compares the determinants of disclosure quality of one-tier and two-tier board structures in selected ASEAN countries. We measure the significance of different corporate governance mechanism of top 50 companies from Malaysia, Indonesia, Thailand, and Singapore from 2011 to 2015. The results of independent sample t test prove that the variances of the disclosure quality scores of one-tier and two-tier board structures are different. In order to avoid problems of omitted variable bias, unobserved heterogeneity and endogeneity, we use the Tobit regression model with random effects. The results confirm that the disclosure quality has a dependence on board size, board expertise, board meetings, board diversity, the timeline for both one-tier and two-tier board structures. The female board members and free cash flows have sole dependence on the one-tier board, whereas board power and block holders have sole dependence on two-tier boards. The study also establishes the relationship between board independence with disclosure quality of board structures. [ABSTRACT FROM AUTHOR]

Objective: From the political budget cycle (COP) lens, we investigated the behavior of committed expenditures, investment spending and borrowing in the electoral period, in Brazilian municipalities with a population of 50,000 or more, in the period 2000-2016, comprising 353 clusters and 6001 observations. It was also investigated whether these municipalities meet the legal requirements on the use of budget resources in an election year. The study was motivated by the lack of consensus in the literature on the subject in question. Methodology: Four research hypotheses were built to assist in achieving the proposed objectives. Data were collected from IBGE, TSE and STN websites. Data were analyzed using the balanced panel data method, grouped by municipality and region, with Tobit regression application and Hausman, Breusch-Pagan Lagrange and F de Chow robustness tests. This method covered confidence with the interval of 99%, 77%, 79% and 84% explaining behavior between the variables. Results: The results show that there were no changes in expenditure committed before, during and after the election period, regardless of party equality and two-round election, unlike the results of some studies. As for spending on investments and borrowing in the election period, the study suggests an average increase of 9% and 68% respectively, and this is more intense when there is party equality between municipal and state governments, especially in the process of reelection. Regarding compliance with legal requirements on the use of budgetary resources in an election year, the study indicates that local governments do not comply with regulatory requirements. Contributions of the Study: contributes to the specific literature, because it presents robust results on the lack of consensus on the subject in question, as well as for future research involving municipalities with smaller population and comparison between regions and countries. [ABSTRACT FROM AUTHOR]

Farming has been considered the main source of income for rural households in Nigeria, despite their involvement in other income-generating activities. Focusing on income derivable from farming alone may be partially responsible for the ineffective poverty reduction strategies in Nigeria. Using the National Living Standard Survey data collected by the National Bureau of Statistics, this paper investigated the composition and determinants of non-farm incomes of rural households in Nigeria. The results show that the share of farm, non-farm wage (NFW) and self-employment (NFS) incomes in total household incomes were 24.3%, 43.0% and 23.7% respectively. Households whose heads are males or have formal education had an increased likelihood of households' participation in NFW activities by 6.2% and 10.9% points respectively, while larger household size decreased it by 0.6% point. Furthermore, possession of capital assets, being a male household head and age increased the likelihood of participation in NFS employment activities by 33.3%, 1.5% and 0.3%; while larger farm size and household size decreased it by 1.6% and 0.1% respectively. The study concludes that any policy targeting poverty reduction should focus on providing a favourable environment for poor households to access non-farm activities in the studied area. [ABSTRACT FROM AUTHOR]

Objective  This study aimed to describe characteristics of cervicovaginal cytokines obtained during pregnancy from women who subsequently delivered at term. Study Design  We used repeated measures of 20 cervicovaginal cytokines, collected on average on a monthly basis, from the second to the ninth month of gestation among 181 term pregnancies in the Mexico City Pregnancy Research on Inflammation, Nutrition, & City Environment: Systematic Analyses cohort (2009–2014). Cytokines were quantified using multiplex assay. Results  Cytokine distributions differed more between than within cytokines. Across trimesters, cytokines interleukin (IL)-1Ra, IL-1α, and IL-8 consistently had high concentrations compared with other measured cytokines. Cytokine intraclass correlation coefficients ranged from 0.41 to 0.82. Spearman's correlation coefficients among cytokine pairs varied but correlation directions were stable; 95.3% of the 190 correlation pairs remained either negative or positive across trimesters. Mean longitudinal patterns of log-transformed cytokines from Tobit regression varied across but less within cytokines. Conclusion  Although mean concentrations of cervicovaginal cytokines among term pregnancies were high, they were largely stable over time. The high cytokine concentrations corroborate that pregnancy is associated with an active inflammatory state. These characterizations may serve as a baseline for comparison to other obstetric outcomes, which may be helpful in understanding deviations from normal gestational inflammation. [ABSTRACT FROM AUTHOR]

Non‐native species can dominate plant communities by competitively displacing native species, or because environmental change creates conditions favourable to non‐native species but unfavourable to native species. We need to disentangle these mechanisms so that management can target competitively dominant species and reduce their impacts.Joint‐species distribution models (JSDMs) can potentially quantify competitive impacts by simultaneously modelling how species respond to environmental variation and to changes in community composition. We describe a JSDM to model variation in plant cover and show how this can be applied to compositional data to detect dominant competitors that cause other species to decline in abundance.We applied the model to an experiment in an invaded grassy‐woodland community in Australia where we manipulated biomass removal (through slashing and fencing to prevent grazing by kangaroos) along a fertility gradient. Non‐native species dominated plant cover at high fertility sites in the absence of biomass removal. Results from the JSDM identified three of the 72 non‐native plant species (Bromus diandrus, Acetosella vulgaris and especially Avena fatua) as having a strong competitive impact on the community, driving changes in composition and reducing the cover of both native and non‐native species, particularly in the absence of grazing. The dominant non‐native grasses Bromus diandrus and Avena fatua were among the tallest species in the community and had the greatest impact on shorter‐statured species, most likely through competition for light under conditions of high fertility and low grazing.Synthesis. We demonstrate a method to measure competitive impact using a joint‐species distribution model, which allowed us to identify the species driving compositional change through competitive displacement, and where on the landscape competitive impacts were greatest. This information is central to managing plant invasions: by targeting dominant non‐native species with large competitive impacts, management can reduce impacts where they are greatest. We provide details of the modelling procedure and reproducible code to encourage further application. [ABSTRACT FROM AUTHOR]

This paper focuses on the Brazilian third-party logistics (3PL) sector which, facing increasing competition, offers clients a wide variety of services/IT technologies in the quest to bolster efficiency. The main research objective is to determine which variables significantly impact the 3PLs' scale efficiency by applying a two-stage DEA model. Based on an unbalanced panel model, secondary data from the annual study published by Revista Tecnologística (years 2001–2010) were collected and analysed. The required inputs and outputs for the analysis were identified, as were the contextual variables that can affect the scale efficiency of the 3PLs. The results support findings in the literature regarding the role coordination processes play in logistics performance. Managerial implications for both shippers and 3PLs are discussed. [ABSTRACT FROM AUTHOR]

In the quest to combat climate change and facilitate sustainable development, improving efficiency is a common and successful method for container terminals. Under such a circumstance, it is critical to accurately estimate the efficiency level of container terminals, so that making more reasonable decision-making. However, many present studies consider container terminal operations as a "black box", reliance mostly on their own self-efficiency evaluations, ignoring some important external environmental factors, which can lead to inaccurate results that are hard to compare. To rectify this situation, this paper proposes a new network DEA cross-efficiency model that considers initial structure and GHG emissions of container terminal, co-opetition (competition and cooperation) and "peer-evaluation" between container terminals, which enables us to attain more accurate and comparable evaluations. Having applied this model to 25 Chinese container terminals in 2019 to analyze their three efficiencies (production operation, profit transformation, and all-in). Then, the effects of different factors on three efficiencies are analyzed by Tobit regression, and a series of efficiency improvement recommendations are proposed. Our findings revealed that while the production operation at these terminals was efficient (with average performance rate of 0.65), both profit transformation and overall efficiency were quite inefficient (averaging 0.23 and 0.35 respectively). Factors such as price for services, quality of services, technology used, and regional economic development level have significant positive effects on overall efficiency. Investment size had a significant negative effect on overall efficiency. Through our research, we have provided vital support for accurately evaluating efficiency in container terminals as well as useful guidance when designing strategies for greater efficiency improvement. • The initial structure of container terminal operation is modeled by a two-stage series network. • A network DEA cross-efficiency approach that considers GHG emissions, competition and cooperation is developed. • Production operation, profit transformation, and overall efficiencies of Chinese container terminals are evaluated. • The influencing factors on three efficiencies of container terminals in China are analyzed. [ABSTRACT FROM AUTHOR]

This research aims to measure the level of technical efficency of Bank Pembiayaan Rakyat Syariah (BPRS) in Jabodetabek Region during the period 2015-2016. This is quantitative reasearch. Data used in this research was a secondary data, collected from financial report from Bank Indonesia and Otoritas Jasa Keuangan. The sampling technique that issued in this research was purposive sampling with taking 12 samples of BPRS. Efficiency measurement in this research used non-parametric statistic Data Envelopment Analysis (DEA) with the intermediation approach. The results showed that 12 BPRS in Jabodetabek Region during the 2015-2016 period as whole has a fluctuating level of efficiency. Meanwhile, the second phase of testing using Tobit methods shows that internal factor, CAR, has significant impact on BPRS efficiency in Jabodetabek.

本研究的焦點在於經濟合作暨發展組織（OECD）會員國及臺灣科學素養之比較，研究內容包括彙整科學素養評量結果、進行科學素養成就統計分析、探究影響科學素養成就的相關因素、評估 OECD 會員國及臺灣科學素養成就的整體效率值，以提出各項教育績效評估的建議。研究對象為參與 PISA 2012 評量的學生為主。本研究主要資料來源為 OECD 之 2012 年「國際學生能力評量計畫」的調查結果，採用的研究方法為三階段包絡分析法：第一階段利用 DEA 中的 CCR、BCC 模式分析各種效率值，第二階段利用 Tobit 迴歸去除環境因素所造成的相對無效率，第三階段則把調整後的產出項投到模型，分析調整後的各種效率值。研究結果顯示，經第二階段調整產出項後，第三階段分析結果顯示，各國的平均技術效率值及純技術效率值是提升的，而規模報酬遞減的國家數量明顯增加，且與第一階段的效率值有顯著的差異。所以各國皆面臨不同的經營環境，這些因素會干擾各國的經營效率評估，如果不事先予以消除， 將會使各效率值的評估結果產生偏誤。因此，可以發現達到技術效率、純技術效率、規模效率值為 1 的國家數量增加，而規模報酬固定的國家由 30 個減至 13 個，顯示此報酬狀態為該國在投入與產出的比例上最為恰當，因此無須做任何改善與調整，規模報酬遞減的國家由 5個增加至 22 個，顯示此報酬狀態為該國在投入與產出的比例上過大，因此各國政府可考慮調整或降低投入產出的比例，避免可能因規模過度擴張導致資源浪費的情形。 This study compared science literacy between the Organization for Economic Cooperation and Development (OECD) member countries and Taiwan. To evaluate educational achievements, the study included archiving the assessment results of science literacy, statistically analyzing science literacy accomplishments, investigating the factors that influence science literacy, and assessing the overall efficiency of the science literacy accomplishments that the OECD member countries and Taiwan have achieved. The study participants were the high school students of the OECD member countries and Taiwan who had participated in the Programme for International Student Assessment (PISA) 2012. The study data source was OECD PISA 2012 results. A 3-stage Data Envelopment Analysis (DEA) was used. The 1-stage DEA was employed to analyze variety efficiency in the DEA of the CCR and BCC models. The 2-stage DEA was used to remove environmental factors caused by the relative inefficiencies in the Tobit regression analysis. The last stage placed the adjusted output into the model and analyzed the efficiency. It also revealed more decreasing returns to scale countries. Because different countries have different management environments, these factors can interfere with the efficiency assessment. If they are not eliminated in advance, a deviation may be observed in the analysis. This study indicated that the number of countries with technical efficiency, pure technical efficiency, and a scale efficiency value of 1 has increased, while the constant returns to scale countries from 30 to 13, indicating that the status of returns is the most appropriate proportion in input and output. Therefore, no improvements and adjustments were observed. A decrease was observed in returns to scale countries from 5 to 22, indicating that the status of returns is a huge proportion gap in input and output. Therefore, governments should consider adjusting or reducing the proportion of inputs and outputs, as resources may be wasted due to excessive scale expansion.

This research aims to identify the influential components on LGD by using Tobit regression on institutional customers of the bank of Industry and Mine. In order to achieve this goal, LGD can be used to calculate the probability of default on the basis of the Basel II agreement. LGD is the amount of loss a bank faces when the borrowers default on loan repayment. To accomplish this goal, 204 of institutional customers of bank for an 8 years period (2007-2014) have been chosen as a sample. The results show a significant relation between loan amount, collaterals (excepted promissory notes), industry type and LGD, and no significant relation between loan maturities and LGD.

Logistics facilities should be considered in transportation plans and city plans because they generate/attract huge volumes of truck traffic. We utilized the 5th Tokyo Metropolitan Area Urban Freight Survey (TMAUFS) conducted in 2013 to analyze the relationship among land-use pattern, transportation demand, and transportation networks. This paper focuses on the questionnaire-survey to establishments and truck probe survey combined with the 1-km2 mesh land-use data of the Japanese Statistics Bureau. Data from the TMAUFS are aggregated following a description of logistics facility allocation patterns. Transition patterns of logistics facilities including factories are analyzed through a comparison of the 4th (2003) and 5th (2013) TMAUFS. Specifically, we clarify the relationship between highway-construction and location of new logistics facilities. Truck-trip-generation models are examined by fitting conventional regression models and the Tobit model for a better fit. Finally, we summarize the required future policy measures forecasted by the developed models for transportation infrastructure systems.

Since the efficient agricultural sector is one of the most important drivers of countrys economic development, the main objective of this paper was to examine relative technical efficiency of agricultural production in 25 Serbian districts using two-stage data envelopment analysis. Results of this research indicate that the efficiency score values lie between 70% and 100%, therefore it can be concluded that the agricultural sector of Serbia performs at a high level of efficiency, with the average efficiency score of 90%. The lowland region of Vojvodina is characterized with the highest efficiency scores, while districts in the southeastern part of Serbia have the lowest efficiency score values. Furthermore, the Tobit regression model was applied that one may examine the drivers of technical efficiency scores. The results show the significance of agricultural training among farm managers, land irrigation and age of farm holders in altering agricultural efficiency among Serbian districts.

Cassava has been identified as Africa’s second most important staple food after maize, in terms of calories consumed, with Nigeria as the World leading producer. This study estimated postharvest loss of cassava along the cassava value chain in Kwara State. It estimated the size of postharvest loss of cassava; analysed the factors responsible and the financial implications of loss; and identified the strategies employed in the mitigation of loss in the study area. A three-stage random sampling technique was used to select 117 cassava farmers whom were administered structured questionnaire to elicit data analysed by the study. Descriptive statistics, Shannon’s diversity index and Tobit regression model were the analytical techniques utilised. The results show that 68 % of the loss occurred at the harvesting. The loss was estimated to be about 3.8 t ha-1. The financial implication was valued at $ 300 ha-1. Analysis of the factors responsible for cassava postharvest loss showed that the quantity expected at harvesting, household size and age of the farmer were significant factors affecting cassava postharvest loss. The result also revealed that farmers mitigate these losses by processing the roots and reburying unused roots into the soil. Steps needed to reduce loss have to take these factors into consideration to improve the economic status of cassava farmers-processors.

There has been a substantial improvement in the performance of Farmer Producer Organisations (FPOs) in India in several aspects including access to technologies, markets, and value addition to agricultural produce. In this paper, an in-depth analysis has been done to understand the performance of FPOs for organic chilli in Indian state of Telangana based on the primary data collected from 60 farmers associated with FPOs and 60 non-FPO farmers from Siddipet and Janagaon, Telangana. The study employed empirical techniques, viz. tobit model, decomposition analysis and marketing efficiency to evaluate the impact of FPOs. The findings indicate that the input use in production of chilli was much less for the members of FPOs due to adoption of low inputs organic farming practices. Despite a lower yield, the members could realize 13.86% higher gross returns primarily attributed to FPOs providing access to technology and markets. The farmers in the study regions were following three marketing channels for disposal of their produce. The channel that involved FPOs with member farmers on the one end and consumers on the other is found to have the highest marketing efficiency in organic chilli.

Larger amount of national and provincial forest eco-compensation funds in China have been distributed to farmers annually, which aims to encourage farmers input more labor and fund in daily forestry management. We selected 503 household from 50 Ullages of 10 counties in Jiangxi Province in the paper. Household labor and cash input responded negatively towards forest eco-compensation fund in forestry management. Forest eco-compensation subsidy (FECS) granted to the household in the rural mountain area didn't stimulate the household labor and cash input in forestry management. It implies that it is not a wise way to distribute FECS equally to the rural household, so as to promote the forestry ecological quality. The current forest eco-compensation policy (FECP) need modifying urgently. [ABSTRACT FROM AUTHOR]

This study seeks to examine the determinants of dividend policies of manufacturing companies in Indonesia. The data for this study were drawn from a balanced sample of 111 public manufacturing firms listed in the Indonesia Stock Exchange between 2009 and 2013. A Tobit regression analysis with cluster-robust standard errors was then employed to find the effects of firm size, profitability, sales growth, financial leverage, and inter-period on the magnitude of dividend yield. This study finds that firm size, profitability, and sales growth positively influence the magnitude of dividends paid relative to stock prices received by shareholders. On the other hand, it also finds that financial leverage negatively affects dividends. Another result suggests the levels of dividends vary across time. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Ciências da Administração is the property of Universidade Federal de Santa Catarina, Departamento de Ciencias da Administracao and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In recent years, many regions including China have witnessed fast growth of dry ports. Unlike in the other regions of the world, the amount of cargos handled by most dry ports in China is not in compliance with the significant amount of resources invested, but the reasons behind have not been discussed before. After a brief review on the development pattern of Chinese dry ports, certain dry port functions like customs clearance and rail connection, dry port ownership structure, and inter-competition among dry ports are identified as the unique factors which distinguish Chinese dry ports from others and affect their performance. We investigate the relationship between these factors and the efficiency of Chinese dry ports with a two-stage approach based on a panel data collected from eight dry ports affiliated to the port of Ningbo, China, covering the 2011–2016 period. In the first stage, Data Envelopment Analysis (DEA) is used to measure these dry ports' technical efficiency. In the second stage, Tobit regression analysis is applied to explore the relationship between efficiency and the above mentioned factors. Several insightful findings are observed, further leading to useful managerial insights. • The unique features in development of Chinese dry ports are discussed. • Impacts of these features on dry ports' efficiency are empirically examined. • Provision of customs service implies low efficiency at dry ports. • Seaport's ownership may not be beneficial to dry ports and local economy. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Applied Ecology / Yingyong Shengtai Xuebao is the property of Chinese Journal of Applied Ecology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Acta Agriculturae Slovenica is the property of Biotechnical Faculty of the University of Ljubljana and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Since the efficient agricultural sector is one of the most important drivers of country's economic development, the main objective of this paper was to examine relative technical efficiency of agricultural production in 25 Serbian districts using two-stage data envelopment analysis. Results of this research indicate that the efficiency score values lie between 70% and 100%, therefore it can be concluded that the agricultural sector of Serbia performs at a high level of efficiency, with the average efficiency score of 90%. The lowland region of Vojvodina is characterized with the highest efficiency scores, while districts in the southeastern part of Serbia have the lowest efficiency score values. Furthermore, the Tobit regression model was applied that one may examine the drivers of technical efficiency scores. The results show the significance of agricultural training among farm managers, land irrigation and age of farm holders in altering agricultural efficiency among Serbian districts. [ABSTRACT FROM AUTHOR]

Vibrio parahaemolyticus is a leading cause of seafood-borne gastroenteritis. Given its natural presence in brackish waters, there is a need to develop operational forecast models that can sufficiently predict the bacterium's spatial and temporal variation. This work attempted to develop V. parahaemolyticus prediction models using frequently measured time-indexed and -lagged water quality measures. Models were built using a large data set (n=1,043) of surface water samples from 2007 to 2010 previously analyzed for V. parahaemolyticus in the Chesapeake Bay. Water quality variables were classified as time indexed, 1-month lag, and 2-month lag. Tobit regression models were used to account for V. parahaemolyticus measures below the limit of quantification and to simultaneously estimate the presence and abundance of the bacterium. Models were evaluated using cross-validation and metrics that quantify prediction bias and uncertainty. Presence classification models containing only one type of water quality parameter (e.g., temperature) performed poorly, while models with additional water quality parameters (i.e., salinity, clarity, and dissolved oxygen) performed well. Lagged variable models performed similarly to time-indexed models, and lagged variables occasionally contained a predictive power that was independent of or superior to that of time-indexed variables. Abundance estimation models were less effective, primarily due to a restricted number of samples with abundances above the limit of quantification. These findings indicate that an operational in situ prediction model is attainable but will require a variety of water quality measurements and that lagged measurements will be particularly useful for forecasting. Future work will expand variable selection for prediction models and extend the spatial-temporal extent of predictions by using geostatistical interpolation techniques. [ABSTRACT FROM AUTHOR]

This study uses 810 households data collected from two states of India-Raipur district in Chhattisgarh State and Ranchi in Jharkhand- to analyse the LPG cooking transition. Most of the available studies for the South Asia region and particularly for India had mainly focused on the access aspect of clean cooking in terms of fuel or stove. In this study, we particularly focus on the household transition to clean cooking fuel (LPG) in terms of its usage. Using the Tobit regression model for censored data the study highlights the socioeconomic and other factors that may influence LPG transition. The study finds that there could be common as well as location specific factors driving LPG transition. Income linkages with LPG usage may be weak in regions with high prevalence of home produced or collected solid fuel consumption. Duration of LPG acquisition, considered in the study as a factor of behavioural aspect, has emerged as an important variable promoting LPG transition over time. The analysis suggests that LPG capital subsidy scheme, PMUY, has provided a trigger for LPG transition among beneficiary households. Increasing the share of LPG in monthly cooking fuel may require good LPG services such as doorstep delivery. • Using a Tobit model approach this study identifies the factors promote LPG usage for cooking. • The finding suggests that PMUY scheme, LPG acquisition duration, and LPG doorstep delivery impact LPG usage. • There could be common as well as location specific factors driving LPG transition. • Sustained LPG usage may happen over time, once user understands the costs and benefits of clean fuels. • Availability of large amount of home produced and collected solid fuel may be acting as a deterrent for LPG transition, even in the economically well off households. Therefore, apart from awareness raising campaigns, developing a market for alternative use of locally available biomass will create an opportunity cost of burning it. Availability of home produced fuel may hinder LPG transition, even in the economically well off households. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Qadisiyah Computer Science & Mathematics is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study estimates technical efficiency and examines its determinants in the micro-manufacturing enterprises in Dibrugarh, one of the most developed districts in the state of Assam in India. It is based on cross-sectional firm-level primary data, collected through a field survey from 115 micro-manufacturing enterprises in the district. The results of the data envelopment analysis suggests that the average technical efficiency score of the firms is quite low, which indicates a high degree of technical inefficiency in the production process. Further efficiency in the enterprises is more due to the inefficient conversion of inputs into outputs rather than due to scale inefficiency. An attempt has also been made to identify some firm-specific and entrepreneurial background variables responsible for inefficiency using the maximum likelihood Tobit regression model. The study reveals that skilled labour, firm-age, firm-size, experience of entrepreneur and gender of entrepreneur have a positive association with efficiency but the magnitude of influence is small. From a policy perspective, it is recommended that policies for rational downsizing of existing firms, along with their rehabilitation and reorganisation should be adopted to promote firm's efficiency performance. The empirical evidences also point to the need for industry-specific policy guidelines. [ABSTRACT FROM AUTHOR]

Abstract Regional disparity in terms of industrial energy efficiency is noticeable in China due to the unbalanced economic progress in past decades. Analyzing the provincial industrial energy efficiency and its influencing factors is of great significance to formulate differentiated policies. To date, the influence of many social-economic factors on the industrial energy efficiency have been examined but the impact of the inter-industry structure has almost been ignored. In this paper, the slacks-based measure model incorporating undesirable output is applied to evaluate the industrial energy efficiency both at the provincial level and the sectoral level in China for the period 2010 to 2016. Then, industrial structure efficiency is introduced, which reflects the inter-industry structure and takes the sectoral-level energy efficiency into consideration. And the impact of the industrial structure efficiency on provincial industrial energy efficiency is tested by Tobit regression model. The results show that huge discrepancies of provincial industrial energy efficiency exist and the industrial structure efficiency is confirmed to be a determinative factor to the provincial industrial energy efficiency, with the coefficient of 0.525. Policy recommendations are provided for adjusting the provincial inter-industry structure and improving the industrial energy efficiency. [ABSTRACT FROM AUTHOR]

Firms respond differently to labour market regulations and develop an employment relationship accordingly. We use linked employer–employee data to examine the relationship between compensation policies and contractual arrangements in large-sized firms in Portugal. In this country, the wages are regulated through minimum wage and collective agreement, while employment is protected by stringent employment legislation. The empirical analysis starts with a fuzzy clustering to identify typical compensation policies. Three major segments emerge from this analysis: Competitive, Internal Labour Markets and Incentive. The first segment comprises low-wage firms, which are highly responsive to market conditions. The other two reveal properties of internal labour markets, although the incentive-based firms reinforce the use of discretionary power to differentiate the workforce. Subsequently, we estimate a regression model to examine how the compensation policy interacts with contractual arrangement. Empirical evidence confirms the segmentation predictions, i.e. low, flexible wages and flexible contracts prevail in the same firms. Furthermore, vulnerable categories like young workers and female workers are over-represented in Competitive firms, while high-wages are associated with incentive devices benefiting white-collar employees. Apparently, firms foster inequality among segments of workers and often penalise or favour the same category of workers. [ABSTRACT FROM AUTHOR]

Abstract In 2014 the Brazilian Electricity Regulator (ANEEL) evaluated the efficiency of power distribution utilities using Data Envelopment Analysis (DEA). Estimated efficiencies range from 22.46% to 100%. Although environmental information is available in the data set, corrected efficiencies were not investigated. Different second stage models can be applied to adjust for environmental heterogeneity. Although statistical correlation among efficiencies and environmental variables can be easily estimated, corrected efficiencies are subject to the underlying structure of the second stage model. Therefore, different second stage models may achieve different corrected efficiencies. We provide a detailed statistical analysis of the Tobit model and compound error models for second stage analysis. Limitations are described and the corrected efficiencies using these models are evaluated. Potentially, Brazilian power distribution utilities may achieve substantial changes in estimated efficiencies if second stage analysis is used. Highlights • Statistical properties of DEA second stage analysis are presented. • Second stage models with compound error are evaluated. • A second stage analysis applied to Brazilian benchmarking model is presented. • Results show significant changes in efficient operational costs using second stage analysis. [ABSTRACT FROM AUTHOR]

This study determined the technical efficiency (TE) of production of Quality Protein Maize (QPM) and the effect on the adoption of QPM in Oyo State, Nigeria. QPM is an improved maize variety developed to reduce protein deficiency problems. A total of 100 maize farmers were sampled through a two-stage sampling procedure. Stochastic frontier approach using maximum likelihood estimation (MLE) was used to analyse the TE in the production of QPM, while probit regression was used to determine the effect of TE and other socioeconomic characteristics of the respondents on the adoption of QPM. The results revealed a mean TE of 0.89 and 0.78 for adopters and non-adopters of QPM respectively. This implied that adopters of QPM are more technically efficient than the non-adopters. Quantity of seed planted and fertilizer directly and significantly affected the TE of QPM while gross margin of maize farmers and income from other sources (at P

This paper aims to provide a novel construct that is based on data envelopment analysis (DEA) range adjusted measure (RAM) of efficiency and demonstrate its practical implementation by evaluating the financial performance of a sample of three upper-class contracting license (Classes 5–7) Greek construction firms. In a two-step framework, firm efficiency (i.e., composite indicators (CIs)) is produced firstly by means of RAM using single financial ratios, which are selected by grey relational analysis (GRA), and then Tobit regression is employed to model the CIs. In light of the results, only 4% of the sampled firms are efficient, and the firm ranking is consistent with the ranking of Grey Relational Grande (GRG) values produced by GRA. Moreover, the firms with a contracting license of the highest level (Class 7) appear not to be superior in efficiency to their counterparts that belong to Classes 5–6.

Access to natural resources in the immediate environment is an essential factor that contributes to livelihood in many rural areas. In the current study, we explored the economic potential(s) of the natural herbal-based cosmetic and cosmeceutical enterprise for the welfare of the Vhavenda women. A purposive sampling technique was used to collect data from 79 Vhavenda women and analysed with descriptive and inferential statistics (Tobit regression) as well as budgeting analysis. The majority (61%) of the participants were married with an average household size of five members. Additionally, 39% of the participants were already ageing with an average age-group of 56–70 years. The majority (44%) of the participants were not formally employed while the monthly average total income of R1841.01 (107.37 USD) was recorded with an average per capital expenditure of R1438.42 (83.89 USD). A budgeting cost ratio of 1.28 was recorded, which indicates that for every R1.00 (0.057 USD) invested in the herbal-based cosmetic and cosmeceutical production, an expected return of R1.28 (0.073 USD) was forecasted. Tobit regression results indicated that the determinants of the income of participants were experience level (p < 0.01), religion affiliation (p < 0.05) and consumption expenditure (p < 0.01) among others. Thus, a conscious, introspective and intentional look into this marginalised herbal-based cosmetic and cosmeceutical enterprise as a panacea for improved income and welfare of rural South Africans should be considered.