Sources Of Inefficiency Research Articles

Exploring environmental efficiency and total factor productivity of cultivated land use in China

During cultivated land use, nonseparable relationships exist between certain inputs and outputs. This study explored the influence of the nonseparable characteristics of input and output variables on both the cultivated land use environmental efficiency (CLUEE) and the cultivated land use environmental total factor productivity (CLUETFP). To evaluate China's CLUEE and CLUETFP from 1997 to 2017, we used the nonseparable hybrid model with undesirable outputs (NSH-U) and the nonseparable hybrid Malmquist (NSH-M) productivity index. The results showed the following: (1) The CLUEE differed significantly among regions, with the CLUEE decreasing from the eastern region to the western, northeastern, and central regions. We observed large differences in the CLUEE among provinces. (2) Nonradial input inefficiency and radial output inefficiency were the primary sources of cultivated land use environmental inefficiency. (3) Technical progress was the primary driving force behind the growth of CLUETFP across the entire country and in the eastern, central, western, and northeastern regions; however, technical efficiency limited the growth of CLUETFP to a certain extent. Finally, we proposed policy implications to improve China's CLUEE and CLUETFP.

Asymptotic theory for time series with changing mean and variance

The paper develops point estimation and asymptotic theory with respect to a semiparametric model for time series with moving mean and unconditional heteroscedasticity. These two features are modelled nonparametrically, whereas autocorrelations are described by a short memory stationary parametric time series model. We first study the usual least squares estimate of the coefficient of the first-order autoregressive model based on constant but unknown mean and variance. Allowing for both the latter to vary over time in a general way we establish its probability limit and a central limit theorem for a suitably normed and centred statistic, giving explicit bias and variance formulae. As expected mean variation is the main source of inconsistency and heteroscedasticity the main source of inefficiency, though we discuss circumstances in which the estimate is consistent for, and asymptotically normal about, the autoregressive coefficient, albeit inefficient. We then consider standard implicitly-defined Whittle estimates of a more general class of short memory parametric time series model, under otherwise more restrictive conditions. When the mean is correctly assumed to be constant, estimates that ignore the heteroscedasticity are again found to be asymptotically normal but inefficient. Allowing a slowly time-varying mean we resort to trimming out of low frequencies to achieve the same outcome. Returning to finite order autoregression, nonparametric estimates of the varying mean and variance are given asymptotic justification, and forecasting formulae developed. Finite sample properties are studied by a small Monte Carlo simulation, and an empirical example is also included.

Analysis of the dynamic electricity revenue inefficiencies of Taiwan’s municipal solid waste incineration plants using data envelopment analysis

Due to insufficient land and energy resources, municipal solid waste incineration plants are used in many countries as a means of addressing the growing volumes of generated municipal solid waste and to recover energy resources. Taiwan's government allows the private sector to offer municipal solid waste treatment services and electricity to the public. Revenue from the sale of electricity is an important source of income for municipal solid waste incineration plants. Although several studies have examined the technical efficiency of municipal solid waste incineration plants, previous studies have not measured or deconstructed the dynamic electricity revenue inefficiency of incineration plants. For our purposes, this paper presents a data envelopment analysis model that measures and deconstructs the electricity revenue inefficiency while taking into account the slacks and dynamic factors in measuring technical inefficiency levels within the context of assessing MSW incineration plants in Taiwan. This study applied the proposed model to analyze the electricity revenue inefficiency of the municipal solid waste incineration plants in Taiwan over the period of 2013–2018. In this study, we found that the main source of electricity revenue inefficiency is the technical waste from electricity production. Our empirical analysis reveals that the electricity technical, revenue and allocative efficiencies of public plants are lower than those of private plants.

Analysis of the Efficiency Level of Sharia Rural Financing Bank (SRFB ) Using Data Envelopment Analysis (DEA)

This research aims to analyze the efficiency level of Sharia Rural Financing Bank (SRFB) in Surakarta. This study used data from four Rural Sharia Banks taken from www.ojk.co.id, which published its annual report. This study conducted input-output variables with the Data Envelopment Analysis (DEA) method as a tool of analysis. The results of the research showed that the SRFB Dana Amanah is indicated as efficient during the 2017 period. The other three are indicated as inefficient in the last quarter. The inefficiency source came from its operational cost and its incapability to get higher output.

Examining irresponsible lending using non-radial inefficiency measures: Evidence from Australian banks

This paper aims to reveal how recent methodological advancements in efficiency analysis can be used for determining the extent of irresponsible lending in banking. It examines the legitimacy of concerns about the risk of bad debts by analysing the technical inefficiency of six Australian banks over the period 2007–2016. To this end, we use the weighted Russell directional distance model to gain an in-depth understanding of their inefficiency sources. Not only does this approach enable us to incorporate both desirable and undesirable outputs (e.g. bad loans) in modelling efficiency to examine the level of irresponsible lending but also it determines the level of inefficiency for each input and output. Our results show that the main source of inefficiency is bad and doubtful debts, followed by inefficient use of fixed assets and labour, respectively. The inefficiency level of bad and doubtful debts is at its highest in 2009, gradually decreasing to its lowest in 2014, but again increasing in 2015 and 2016. This finding justifies concerns over the irresponsible lending and the risk of bad debts despite their improvement after the global financial crisis (GFC) in 2008. The results also support the view that Australian banks perform efficiently in undertaking their core business activities of attracting deposits and lending money.

Measuring the Meta Efficiency and Its Determinants on Efficiency in the Korean Coffee Shop Franchise

Previous applications of DEA (data envelopment analysis) models in the field of franchising have been scarce. In particular, measurement and analysis of the operational efficiency of coffee shop franchisors in the explosively growing coffee market in Korea is required. In this study, we categorize 29 Korean coffee shop franchisors into three groups according to their number of franchisees and employ the metafrontier analysis to measure the efficiency of coffee shop franchisors from 2015 to 2018. Based on the results of metafrontier DEA, this study identifies sources of inefficiency within individual coffee shop franchisors to provide insights for coffee franchise operators and investigates efficiency differences between small-chain and medium-chain coffee shop franchisors. Furthermore, the results of bootstrapped truncated regression provide that the external environmental factors affecting the efficiency of each individual group are totally different patterns depending on the franchise group. Based on the analysis results, this study suggests strategic initiatives tailored to individual coffee shop groups to enhance their operating efficiency and identifies the principal operational drivers of the environmental variables to achieve sustainable growth.

EFISIENSI PEMBIAYAAN BANK PEMBIAYAAN RAKYAT SYARIAH (BPRS) DI JAWA TIMUR PERIODE 2014-2017. ANALISIS DENGAN METODE DEA (CRS,VRS, dan Skala)

<p><em>This research aimed to find out the efficiency level of financing of Islamic Rural Bak in East Java. Input variables used were the rights of third party on profit sharing and PPAP cost, while output variable used was main operational income. Method used to measure efficiency level was Data Envelopment Analysis (DEA) with the assumption of Variable Return to Scale and the input and output orientations. The measurement of efficiency value with VRS assumption resulted three efficiency values, which are Technical Efficiency (VRS), Economic Efficiency (CRS), and Scale Efficiency. Then, these three values were analyzed further to get to know the source of inefficiency of financing in inefficient Islamic Rural Bank.</em><em> </em></p><strong><em>Keywords</em></strong><em>: BPRS, Data Envelopment Analysis (DEA)Efficiency, Financing</em>

Diversity of industrial structure and economic stability: evidence from Asian gross value added

The paper provides evidence of convex growth-instability frontiers for 19 Asian countries based on the shares of different economic activities in gross value added between 1991 and 2016. Numerical simulations of gross value added shares show that Asian industry portfolios in 2014 were below the unbounded efficient frontier defined by Markowitz, and that rearranging the shares of economic activities leads to efficiency gains through higher income and lower output volatility. The data show that gross value added in Asian countries in general, and in Eastern Asia in particular, are contributed mainly by “other activity” and “transport” sectors, while optimal industry portfolios in Southern Asia and Southeast Asia are found to be more diversified. Stochastic frontier analysis confirms convex growth-instability frontiers and points to differences in labor growth rates and industrial diversification as the main sources of inefficiency. The results are robust to model specifications and data restrictions.

Convergence and growth – conflicting goals of economics policy – A case study of Georgia

Abstract Over the years, it has been the subject of discussions whether efficiency-oriented interventions contribute to an equity distribution of wealth across regions and whether equity orientation is a source of inefficiency. While efficiency refers to the maximization of growth in the national economy, convergence-oriented policy is focused on equalizing the level of development at interregional level. The case of Georgia was studied as a developing country facing various challenges in terms of economic growth and regional divergence. This article provides an overview of the economic development trends taking place in the regions of Georgia and reveals the high level of divergence within the country. A logarithmic model was created and used to run simulations to predict the possible results of convergence-oriented policy in Georgia. In order to make the forecast we estimated GDP per capita and average growth rates in all the Georgian regions. Use of the model allowed us to answer two main questions: (1) If the last 5 and 10 year average growth rates are maintained, how long will it take for the poorest region to converge to the wealthiest one? (2) What should be the minimum growth rate in the poorest region for the upcoming 5, 10 and 20 years in order to converge to the wealthiest capital? Results of the calculations showed that convergence between regions can only be achieved by slowing down economic growth in relatively wealthier regions and by focusing on the development of the poorest ones. The results of the study revealed that the convergence process will be faster for the regions with medium or big cities and growth centres. Therefore, creating competitive growth centres would be a reasonable regional policy objective to promote fast economic growth and future convergence without redirecting the growth process from more developed areas to lagging ones.

Descriptive Models of Sequential Decisions in Engineering Design: An Experimental Study

Abstract Engineering design involves information acquisition decisions such as selecting designs in the design space for testing, selecting information sources, and deciding when to stop design exploration. Existing literature has established normative models for these decisions, but there is lack of knowledge about how human designers make these decisions and which strategies they use. This knowledge is important for accurately modeling design decisions, identifying sources of inefficiencies, and improving the design process. Therefore, the primary objective in this study is to identify models that provide the best description of a designer’s information acquisition decisions when multiple information sources are present and the total budget is limited. We conduct a controlled human subject experiment with two independent variables: the amount of fixed budget and the monetary incentive proportional to the saved budget. By using the experimental observations, we perform Bayesian model comparison on various simple heuristic models and expected utility (EU)-based models. As expected, the subjects’ decisions are better represented by the heuristic models than the EU-based models. While the EU-based models result in better net payoff, the heuristic models used by the subjects generate better design performance. The net payoff using heuristic models is closer to the EU-based models in experimental treatments where the budget is low and there is incentive for saving the budget. This indicates the potential for nudging designers’ decisions toward maximizing the net payoff by setting the fixed budget at low values and providing monetary incentives proportional to saved budget.

Estimating financing gaps in rice production in Southwestern Nigeria

This study analysed the financing gaps relative to production frontier of rice farmers in Southwestern Nigeria. A multistage sampling technique was used to collect cross-sectional data from 360 rice farmers selected from three states in the region. A Cobb–Douglas stochastic frontier and an adapted form of Harrod–Domar (HD) growth model was employed to determine the financing gap required the farmers to be at the frontier level. The empirical results of the frontier model show that quantity of labour, quantity of rice as planting material and herbicides were statistically significant in explaining the variations in the efficiency of rice production in Nigeria. However, age, gender, farming experience, household size, access to credit, access to information, adoption of improved variety and location of rice farmers as sources of technical inefficiencies. As revealed by the result of the HD growth model, the average amount of credit per season that farmers had access to was, 38,630.56 naira (₦) while the mean financing in the form of credit required to produce at the frontier level was ₦193,626.50, showing a financing shortfall of about 80%. As unravelled by the result of the study, it can thus be concluded that technical efficiency of rice farmers can be improved by ameliorating access to timely credit and agricultural information for improving rice productivity. These findings suggest that filling the financing gap of smallholder rice farmers will improve rice productivity in Nigeria. The study, therefore, recommends that strengthening the existing technology by building farmers’ capacity on farm management practices would be the surest means of improving rice productivity growth in Nigeria. This would not only contribute to the intensification of rice production in Nigeria to meet its increasing rice demand, but also improve rice farmers’ productivity and their households’ incomes.

What are the drivers of inefficiency in the Gulf Cooperation Council banking industry? A comparison between conventional and Islamic banks

This paper analyses the efficiency and productivity of the Gulf Cooperation Council (GCC) banks using an innovative nonparametric methodology that not only considers undesirable outputs but also determines the contribution of individual input and output variables in total inefficiency. We investigate the impact of incorporating non-performing loans (NPLs) on the performance of banks in our sample. We also adopt the innovative Malmquist-Luenburger productivity index to analyse the changes in productivity based on the weighted Russell directional distance model (WRDDM). The results show that the main source of inefficiency is securities followed by NPLs and fixed assets, respectively. In addition, this paper investigates the differences and sources of inefficiency between Islamic and non-Islamic banks. Our results show that during the global financial crisis in 2008–2009 GCC banks experienced productivity decline. We also show that the difference in inefficiency between Islamic and commercial banks has significantly narrowed and that Islamic banks have been able to catch up and lessen the gap with commercial banks over the study period.

Decomposition of technical efficiency in agricultural production in Africa into transient and persistent technical efficiency under heterogeneous technologies

Abstract The agricultural sector remains a cornerstone to Africa’s economic transformation and the achievement of the Sustainable Development Goals (SDGs). However, the sector’s performance, in terms of productivity growth, has been sub-optimal when compared with performances in Asia, America, and Europe. Technical efficiency is a major contributor to the growth in agricultural productivity. However, there is limited research about the sources of technical inefficiency in agricultural production in Africa. This is critical given that Africa has problems with food security and high poverty. This study applied a parametric technique to estimate technical efficiency in Africa’s agricultural sector under heterogeneous technologies, while separating unobserved country-specific heterogeneities from transient and persistent technical efficiency. Data consisted of 49 African countries spanning from 1990 to 2016. Assuming a homogeneous technology, the estimated mean technical efficiency of 38.2%, suggests that, in Africa, about 62% of the potential agricultural output is untapped. However, considering heterogeneity in production technologies, the mean estimated technical efficiency value differed between the two classes. The numbers suggest that about 59% and 69% of untapped potential agricultural output in class one and class two groups, respectively. In all cases, persistent technical inefficiency hinders technical efficiency, an indication that government or regional agricultural policies should be long-term oriented. With the evidence of conditional convergence in technical efficiency, efforts to improve persistent technical efficiency can drive regional targets in food security and poverty alleviation and induce inclusive growth and sustainable development.

BROILER POULTRY FARMING OPEN HOUSE SYSTEM PATTERNS STOCHASTIC FRONTIER OF ECONOMIC, TECHNICAL AND ALLOCATIVE EFFICIENCY OF IN LAMONGAN REGENCY EAST JAVA

19Jan 2020 BROILER POULTRY FARMING OPEN HOUSE SYSTEM PATTERNS STOCHASTIC FRONTIER OF ECONOMIC, TECHNICAL AND ALLOCATIVE EFFICIENCY OF IN LAMONGAN REGENCY EAST JAVA Niswatin Hasanah , Zaenal Fanani , Suyadi and Bambang Ali Nugroho Animal Husbandry Departmentof Polythecnic State Jember. Postgraduate Animal Husbandry of Brawijaya University.

Entrepreneurial Intentions among University Students: The Moderating Role of Creativity

Many institutions have carried out different policies to promote entrepreneurship as a way to stimulate economic development. However, educational policies and stimulus for entrepreneurship do not produce the same effects on different people. This is a source of inefficiencies. The aim of this paper is to deepen into the analysis of the effects of one key personal characteristic on entrepreneurial behavior: creativity. We analyze the effects of creativity on the generation of entrepreneurial intentions. A moderation analysis was conducted on data obtained from a final sample of 502 undergraduate students. The results indicated that the creativity not only has direct influence on attitudes and perceived control but that it also has a positive moderating effect on the influence of attitudes on entrepreneurial intentions. These results highlight the relevance of the interactive effects of personal characteristics on entrepreneurial behaviors. Several implications for entrepreneurship education have been drawn from this study.

IDENTIFYING SOURCES OF INEFFICIENCY IN HEALTHCARE.

In medicine, the reasons for variation in treatment rates across hospitals serving similar patients are not well understood. Some interpret this variation as unwarranted, and push standardization of care as a way of reducing allocative inefficiency. An alternative interpretation is that hospitals with greater expertise in a treatment use it more because of their comparative advantage, suggesting that standardization is misguided. A simple economic model provides an empirical framework to separate these explanations. Estimating this model with data for heart attack patients, we find evidence of substantial variation across hospitals in both allocative inefficiency and comparative advantage, with most hospitals overusing treatment in part because of incorrect beliefs about their comparative advantage. A stylized welfare-calculation suggests that eliminating allocative inefficiency would increase the total benefits from the treatment that we study by 44%.

Profitability and technical efficiency of leafy vegetable production: a stochastic frontier production function analysis

ABSTRACT Smallholder leafy vegetable farmers are often faced with resource-use inefficiency in production. This work examined the profitability and technical efficiency of leafy vegetable production to determine sources of inefficiencies in smallholder production. The Maximum Likelihood Estimates of the Stochastic frontier production function indicated factors positively influencing production gross margin were education level, experience, seed, labor costs, fertilizer and farm-size; farmer age negatively influenced results, especially those who have less contact with extension agents. The mean efficiency score was 0.804 with R2 of 0.912. With more education, the application of required inputs could improve the yield of leafy vegetables.

Estimation and determinants of efficiency among rice farmers in Benin

Rice plays an important role in achieving food security in Benin but its production remains low and needs to be optimized. This study estimates technical and allocative efficiencies as well as the sources of inefficiency among rice producers in Benin. The data used cover 210 rice producers, proportionally distributed in the Departments of Mono and Couffo. This farm-level data were collected under the project “Facilité d’Appui aux Filières Agricole du Mono et du Couffo (FAFA-MC).” We employed a stochastic frontier approach to analyze technical efficiency and the marginal value product approach for allocative efficiency analysis. Furthermore, a Chow test was performed to test for difference in determinants of efficiency between the two departments. We found that the average technical efficiency score of rice producers is 78%. The sources of technical inefficiency were age, gender, education level and access to credit. The results also revealed allocative inefficiency in rice production. Labour was overused while other inputs such as seeds, herbicide, and fertilizer were underutilized. Allocation efficiency was influenced by age, gender, area planted, type of culture, and access to credit. Finally, we found difference in determinants of efficiency between the departments of Mono and Couffo. Our results imply that there are opportunities to increase rice production in the Departments of Mono and Couffo. Rice producers in these departments therefore would benefit by adopting better farming practices such as the use of fertilizers, agrochemicals, and irrigation facilities.

Financial performance–efficiency nexus in public health services: A nonparametric evidence-based approach

Public health services, as a preventive aspect of health care, are essential for the sustainability of the entire health care system. However, the context of public health services, which focus is primarily on prevention, is not a common setting when measuring the efficiency within nonparametric evidence-based approach. The aim of this study is to measure the efficiency of the financial performance of organizational units of the public health institute in Croatia, the Health Ecology Department in particular, during the period 2016–2018 using data envelopment analysis. Among the many reasons behind choosing this nonparametric method is the fact that it identifies the sources of inefficiency and specifies the directions and magnitudes of improvements required. Two input-oriented models – CCR under constant and BCC under variable returns-to-scale assumption – are employed for evaluating three types of efficiency – technical, pure technical and scale efficiency. Two hypotheses are examined and empirically confirmed: first, that there is significant between-unit variability in financial performance, and second, that investments are the major source of inefficiency among the observed indicators. The results have additionally revealed that the mentioned differences are less pronounced in the case of pure technical efficiency, implying that the overall inefficiency of the Health Ecology Department units can be generally attributed to scale efficiency. Besides, only three out of twelve department units are considered efficient. The implications of the research results are aimed at further research and testing the efficiency of the entire network of public health institutes, as well as to provide policy makers with new insights when considering different modes of organizing and delivering public health services.

Blockchain-based human resource management practices for mitigating skills and competencies gap in workforce

Skills gap between company needs and competencies occupied by the workforce can be the source of inefficiencies. The purpose of this research is to develop a blockchain-based human resource (HR) framework to match the needs from the company and workforce competencies This framework will help Corporate Training Centre to standardized the competencies which then used by HR Department to develop the training material. In order to get valid information regarding skills that are needed from the company, we develop a prototype based on Blockchain. Hence, blockchain-based HRM is built to improve the quality of workforce competency in an organization. The current organizations are struggling to fulfil the needs of the workforce in accordance with industry quality standards. Therefore, this will help all parties to create a consensus between the needs of the industry with the labour market. Corporate Training Centre through the competent institution will be the mediator or intermediary to unite the information from companies, training institutions, and Professional Certification Institutions. As a result, in the long term, the needs of the workforce with the qualification required by the company in such industries will always fit the current situation. Blockchain helps to process the information and data needed by each party so that the connection between parties will be assisted efficiently and effectively.