Efficiency Frontier Research Articles

A DEA-based approach to assess manufacturing performance through operations strategy lenses

While operations strategy is critical in competitiveness, research gaps exist in applying performance frontier methodologies to identify competitive priorities in operations strategy. The concept of performance efficiency frontier can identify the competitiveness drivers specifying the maximum performance that can be achieved by a given set of inputs. This paper proposes and tests a process to measure, assess, and address improvements in manufacturing performance by operations strategy. A five-step procedure, based on the super-efficiency data envelopment analysis (DEA), supports the improvement recommendations. Secondary data of the fourth round of the High-Performance Manufacturing (HPM) survey grounds the benchmarking analysis and assessment. The proposed framework is tested using the in-depth case of a company from the Brazilian automotive industry. The results identified the main gaps of the company to become a market leader through the enhancement of its operations strategic positioning. Improvement recommendations are developed based on a gap analysis of the input variables. By integrating the operations strategy definition within the performance frontier analysis, we guided the competitiveness improvement of the case company.

Prioritizing investments in rapid response vaccine technologies for emerging infections: A portfolio decision analysis

This study reports on the application of a Portfolio Decision Analysis (PDA) to support investment decisions of a non-profit funder of vaccine technology platform development for rapid response to emerging infections. A value framework was constructed via document reviews and stakeholder consultations. Probability of Success (PoS) data was obtained for 16 platform projects through expert assessments and stakeholder portfolio preferences via a Discrete Choice Experiment (DCE). The structure of preferences and the uncertainties in project PoS suggested a non-linear, stochastic value maximization problem. A simulation-optimization algorithm was employed, identifying optimal portfolios under different budget constraints. Stochastic dominance of the optimization solution was tested via mean-variance and mean-Gini statistics, and its robustness via rank probability analysis in a Monte Carlo simulation. Project PoS estimates were low and substantially overlapping. The DCE identified decreasing rates of return to investing in single platform types. Optimal portfolio solutions reflected this non-linearity of platform preferences along an efficiency frontier and diverged from a model simply ranking projects by PoS-to-Cost, despite significant revisions to project PoS estimates during the review process in relation to the conduct of the DCE. Large confidence intervals associated with optimization solutions suggested significant uncertainty in portfolio valuations. Mean-variance and Mean-Gini tests suggested optimal portfolios with higher expected values were also accompanied by higher risks of not achieving those values despite stochastic dominance of the optimal portfolio solution under the decision maker’s budget constraint. This portfolio was also the highest ranked portfolio in the simulation; though having only a 54% probability of being preferred to the second-ranked portfolio. The analysis illustrates how optimization modelling can help health R&D decision makers identify optimal portfolios in the face of significant decision uncertainty involving portfolio trade-offs. However, in light of such extreme uncertainty, further due diligence and ongoing updating of performance is needed on highly risky projects as well as data on decision makers’ portfolio risk attitude before PDA can conclude about optimal and robust solutions.

Logistics network configuration for seasonal perishable food supply chains

Purpose: The location of actors and production, transformation, commercialization and distribution facilities generate the configuration of the perishable food supply chain (PFSC). The logistics network design (LND) lead to different supply, storage and distribution environments and result in flows, these logistics operations have an impact on the performance of the chain of fresh agricultural products. Specifically, in the PFSC with seasonality, a temporary imbalance between supply and demand is generated, which affects the balance in the flows and affects the losses, costs and response capacity. This research study that problem.Design/methodology/approach: A multi-echelon, multi-objective and multi-product model is established that determines the configuration of the logistics network of the PFSC with seasonally and allows actors to approach efficiency frontiers, which contribute to their permanence in the markets. The model was applied to the case of the perishable fruit supply chain, in a developing country, Colombia. The population information was taken from government surveys and studies, which allowed parameterizing the model.Findings: The application of model permitted to answer the next questions: How does improve the performance from PFSC through logistics network design? And, How the existence of smallholdings in food production and from retail merchants is preserved? In the perishable food supply chain.Social implications: Where the perishable food supply chain actors are located in non-efficient borders and their sustainability may be affected by competition factors, the stakeholders should focus on increasing food availability and reducing losses to improve access and therefore food security.Originality/value: A new model for the logistics network configurations of seasonal perishable fruit supply chain was development, the optimizing from five objectives with two sub-models is obtained, one for surplus and the other for the deficit moments. The model includes real conditions, such as, fruit loss due T0 and RH by different thermal floors and the means used for the transport of fruits in mountain areas at countries in route of development. The impact over the small producers, retailers and consumers in the times of scarcity or surplus was analyzed.

Cost-effectiveness Analysis of Breast Cancer Screening Using Mammography in Singapore: A Modeling Study.

Limited research is available on the cost-effectiveness of breast cancer screening programs in Asian countries. We evaluated the cost-effectiveness of Singapore's national mammography screening program, implemented in 2002, recommending annual screening between ages 40 and 49 and biennial screening between ages 50 and 69, and alternative screening scenarios taking into account important country-specific factors. We used national data from Singapore in the MIcrosimulation SCreening ANalysis-Fatal diameter (MISCAN-Fadia) model to simulate 302 screening scenarios for 10 million women born between 1910 and 1969. Screening scenarios varied by starting and ending age, screening interval, and attendance. Outcome measures included life-years gained (LYG), breast cancer deaths averted, false positives, overdiagnosis, quality-adjusted life years (QALY), costs (in 2002 Singapore dollars; S$), and incremental cost-effectiveness ratios (ICER). Costs and effects were calculated and discounted with 3% using a health care provider's perspective. Singapore's current screening program at observed attendance levels required 54,158 mammograms per 100,000 women, yielded 1,054 LYG, and averted 57 breast cancer deaths. At attendance rates ≥50%, the current program was near the efficiency frontier. Most scenarios on the efficiency frontier started screening at age 40. The ICERs of the scenarios on the efficiency frontiers ranged between S$10,186 and S$56,306/QALY, which is considered cost-effective at a willingness-to-pay threshold of S$70,000/QALY gained. Singapore's current screening program lies near the efficiency frontier, and starting screening at age 40 or 45 is cost-effective. Furthermore, enhancing screening attendance rates would increase benefits while maintaining cost-effectiveness. Screening all women at age 40 or 45 is cost-efficient in Singapore, and a policy change may be considered.

Interval BCC model based on variable production possibility sets

The conventional BCC model is based on a fixed production possibility set. As the input–output data gathered from real production systems may be expressed by interval numbers, the production possibility sets are variable within a certain range. To enrich the interval BCC models, two parameter vectors were introduced to represent the variabilities of the production possibility sets. The necessary and sufficient conditions for the DMUs to reach Pareto efficiency under the variable production possibility sets were shown and expanded production efficiency frontiers were formulated. Then, the inclusion relationship between different frontiers were expressed, and their convexities were discussed. Furthermore, RTS classifications of the arbitrary inner points of DMUs were decided according to the optimal production efficiency frontier and were proposed for technical efficient DMUs. An example of an interval number was introduced to show the rationality and validity of the method.

Regional Diversification of Potential, Production and Efficiency of Use of Biogas and Biomass in Poland

Energy obtained from renewable sources is an important element of the sustainable development strategy of the European Union and its member states. The aim of this research is, therefore, to assess the potential and use of renewable energy sources and their effectiveness from the regional perspective in Poland. The research covered the years 2012 and 2018. The diversification of production and potential of renewable energy sources was defined on the basis of biogas and biomass. Calculations made using the data envelopment analysis (DEA) method showed that, in 2012, only three voivodeships achieved the highest efficiency in terms of the use of biogas and biomass resources; in 2018, this number increased to four. Comparing the effective units in 2012 and 2018, it can be seen that their efficiency frontier moved upwards by 56% in terms of biogas and 21% in terms of to biomass. Despite a large relative increase in the production of heat from biogas by 99% compared to the production of heat from biomass by 38%, the efficiency frontier for biogas did not change considerably. It was found that the resources of solid biomass are used far more intensively than the resources of biogas. However, in the case of biogas, a significant increase in the utilization of the production potential was observed: from 3.3% in 2012 to 6.4% in 2018, whereas in the same years, the utilization of solid biomass production potential remained at the same level (15.3% in 2012, 15.4% in 2018). It was also observed that, at the level of voivodeships, the utilization of biogas and biomass production potential is negatively correlated with the size of this potential. The combined potential of solid biomass and biogas can cover the demand of each of the studied regions in Poland in terms of thermal energy. The coverage ranges from 104% to 1402%. The results show that when comparing biomass and biogas, the production of both electricity and heat was dominated by solid biomass. Its high share occurred especially in voivodeships characterized by a high share of forest area and a low potential for biogas production (Lubuskie Voivodeship, Zachodniopomorskie Voivodeship).

Disability-Adjusted Life Years Averted Versus Quality-Adjusted Life Years Gained: A Model Analysis for Breast Cancer Screening

ObjectivesTo quantify the impact of mammography-based screening on the quality of life, disability-adjusted life years (DALYs) averted or quality-adjusted life years (QALYs) gained can be used. We aimed to assess whether the use of DALYs averted or QALYs gained will lead to different cost-effective screening strategies. MethodsUsing the microsimulation model MISCAN, we simulated different breast cancer screening strategies varying in starting age (starting at 45, 47, and 50 years), stopping age (stopping at 69, 72, and 74 years), and frequency (annual [A], biennial [B], combination of both [A + B], and triennial [T]). In total, we defined 24 different breast cancer screening strategies, including no screening as a reference strategy. We calculated incremental cost-effectiveness ratios (ICERs) and compared which strategies were on the efficiency frontiers for DALYs and QALYs. ResultsBreast cancer screening averted between 46.00 and 105.58 DALYs and gained between 28.69 and 64.50 QALYs per 1000 women. For DALYs there were 5 strategies on the efficiency frontier (T50-69, T50-74, T45-74, B45-74, and A45-74). The same strategies plus one (B45-72) were on the efficiency frontier for QALYs. ConclusionsUsing DALYs averted instead of QALYs gained to assess the effects on quality of life from breast cancer screening in the Dutch population yields differences in ICERs, but almost the same strategies were on the efficiency frontiers. Whether the choice in outcome measure leads to a difference in optimal policy depends on the cost-effectiveness threshold.

Environmental efficiency of disaggregated energy R&D expenditures in OECD: a bootstrap DEA approach.

Two essential topics of Sustainable Development Goals (SDGs) are accessible which are clean energy (SDG-7) and climate change action (SDG-13). Developments and innovations in energy technologies play an essential role in achieving these goals. Therefore, any country should use energy R&D expenditures, which are the primary source of energy innovation, most optimally. This paper aims to investigate the environmental efficiency of R&D expenditures for energy efficiency, renewable energy, hydro and fuel cells, fossil energy, nuclear energy, and other power and storage technologies in OECD countries using data envelopment analysis (DEA) and bootstrap DEA. Estimation findings indicate that only the USA ensures the environmental efficiency in energy R&D expenditures among OECD countries. Although Japan, Canada, France, Germany, and Italy cannot provide environmental efficiency in energy R&D, their scores are very close to the efficiency frontier. Portugal, Hungary, and Slovak Republic are the countries with the lowest environmental efficiency in energy R&D expenditures. At the end of the investigation, this paper also provides an empirical estimation of the extent to which inefficient countries should change their R&D spending to achieve efficiency.

Evaluating Health System Efficiency using Data Envelopment Analysis: A case of Indian Healthcare System

Purpose-With increased demand and restricted healthcare resources, it becomes important to take a step back and evaluate the efficiency of healthcare delivery. The present study aims to evaluate the health system efficiency of India by benchmarking it against its peers in BRICS countries and against OECD countries. Design/Methodology/Approach: The input and output variables required for measuring the efficiency of healthcare system were identified. A Data Envelopment Analysis (DEA) approach was used and efficiency frontier identified with the rankings of the BRICS and OECD countries. India is thus benchmarked against its peers (BRICS) and against OECD countries. Finding: India was found to operate at the efficiency frontier along with China, Russia, Brazil, and South Africa, however it ranked fourth. When benchmarked against OECD countries, India operates on the efficiency frontier along with Canada, Greece, Japan, Korea, Mexico, Spain, Sweden, Switzerland, Turkey, Great Britain, Chile and Israel. Countries like Germany, United States of America, Czech Republic, Slovakia and Lithuania operate at a lower healthcare efficiency and need to use their resources wisely. Practical/Research Implications: Developing countries like India can look to improve its healthcare system delivery by replicating best practices of healthcare systems from its peers and the top 10 OECD countries. Majority of the OECD countries in the top 10 have implemented universal health coverage, have higher physician and nurse density and higher hospital bed ratios. They are inclined towards branded drugs vis-à-vis generics and have follow evidence based medicine. From a theoretical perspective, it adds to the body of literature of DEA and health system efficiency. Originality/Value: This is a pioneer study that benchmarks India against its peers and against OECD countries drawing unique insights about healthcare efficiency

Output volatility and efficiency gains: evidence from Latin American gross value added

ABSTRACT Based on gross value added (GVA) shares of economic activities from 1990 to 2014, the paper shows that convex growth-instability frontiers exist for 19 Latin American countries. Numerical simulations show that in 2011, Latin America's industry portfolios were below Markowitz's efficiency frontier, and that rearranging the shares of economic activities contributes to efficiency gains that are negatively linked to industrial diversification. Reducing output volatility, MERCOSUR countries with a low degree of industrial diversification would average relatively high efficiency gains, while the reverse is true for CACAM and CAN countries. Analyzing more recent industry portfolios, Latin American countries closed the efficiency frontier gap and captured efficiency gains in terms of lower output volatility and higher GVA growth rates. Convex growth-instability frontiers are confirmed by stochastic frontier analysis, which identifies variations in employment ratios and industrial diversification as the key sources of inefficiency.

ПОРІВНЯННЯ ЕКОНОМЕТРИЧНИХ МЕТОДІВ ОЦІНКИ ЕФЕКТИВНОСТІ В ЕНЕРГЕТИЦІ

Evaluation of the efficiency of enterprises in energy sector is a rather difficult problem, since the production of useful energy services (electricity and heat energy) is often accompanied by the emission of harmful substances (carbon dioxide, sulfur dioxide, nitrogen oxides, etc.), which should be taken into account when assessing efficiency of the enterprises’ activity. The purpose of this article is to determine the main features of the application of main econometric methods, which are used in order to assess the efficiency of enterprises in energy sector, as well as to identify the advantages and disadvantages of these methods. Using general scientific research methods, namely analysis, synthesis, theoretical generalization, abstraction and analogy, the author characterizes the following parametric methods: Stochastic Frontier Approach (SFA), Distribution Free Approach (DFA) and Thick Frontier Approach (TFA). Moreover, the following nonparametric methods are considered: Data Envelopment Analysis (DEA) and Free Disposal Hull (FDH). All these methods are based on the calculation of approximation of indicators of the enterprise to the potential or actual efficiency frontier. The concept of “frontier efficiency” is characterized. The main features of the above-mentioned methodological approaches are considered by the author. The advantages and disadvantages of given methodological approaches due to the existence of mistakes, quantity of input and output factors, subjectivity of estimation, accuracy of the results obtained, etc. are indicated in the article. The author shows that the analyzed methodical approaches can be applied for the estimation of the efficiency of enterprises in energy sector, taking into account the multiple inputs and outputs of such enterprises. It is emphasized that further research will be focused on determination of the efficiency of enterprises in energy sector. The conducted analysis could be used as a basis for further managerial decision-making, both at the micro level (enterprise) and at the macro level (regions and the state as a whole).

Optimal capital adequacy ratio: An investigation of Vietnamese commercial banks using two-stage DEA

Over the last years the Vietnamese banking system has been struggling to restructure, reform governance, consolidate financial statements and build up merge and acquisition, in line with international standards. The Bank for International Settlements (BIS) proposed BASEL III in 2010, whereby banks must increase their minimum Capital Adequacy Ratios (CAR) year by year with a goal of 10.5% by 2019. The objective of this paper is to address the questions: (1) what are the optimal CAR levels for Vietnamese Commercial Banks (2) whether the minimum required CARs stipulated in the Basel II and III are reasonable for Vietnam banking system? The data set consists of a sample of Vietnamese commercial banks over the six-year period from 2010 to 2015. The optimal CARs of banks are calculated using the nonparametric two-stage Data Envelopment Analysis (DEA) model, with two inputs: fixed assets, employee expense and two outputs: interest income, non-interest income. The findings indicate that 92.4% of the banks have the optimal CAR higher than the minimum ratio 10.5% defined in BASEL III. Moreover, 57.98% of the banks should raise their current level of CAR to reach their optimal ones. To conclude, this paper will provide a guideline for Vietnamese banks to decide their optimal CAR to reach the efficiency frontier.

Detecting congestion in DEA by solving one model

Presence of input congestion is one of the key issues that results in lower efficiency and performance in Decision Making Units (DMUs). So, determination of congestion is of prime importance, and removing it improves performance of DMUs. One of the most appropriate methods for detecting congestion is Data Envelopment Analysis (DEA). Since the output of inefficient units can be increased by keeping the input constant through projecting on the weak efficiency frontier, it is unnecessary to determine the congested inefficient DMUs. Therefore, in this case we solely determine congested vertex units. Towards this aim, only one LP model in DEA is proposed and the status of congestion (strong congestion and weak congestion) obtained. In our method, a vertex unit under evaluation is eliminated from the production technology, and then, if there exists an activity that belongs to the production technology with lower inputs and higher outputs compared with omitted unit, we say vertex unit evidences congestion. One of the features of our model is that by solving only one LP model and with easier and fewer calculations compared to other methods, congested units can be identified. Data set obtained from Japanese chain stores for a period of 27 years is used to demonstrate the applicability of the proposed model and the results are compared with some previous methods.

Resource use efficiency of rice farming in Jammu and Kashmir, India

Farming is the most dominant land-use in the Kashmir valley, India. However, the region is characterised by low productivity of agricultural crops that includes rice. To this end, the present study aims to measure economic efficiency of farm land inputs using Cobb-Douglas production model and MVP/MFC ratio. The results reveal that rice production operates at diminishing returns to scale as summation of estimated coefficients of signifcant variables was found to be less than unity (0.76). Coming to the MVP/MFC ratio, the labour was found to be operating beyond price efficiency frontier, indicating allocative inefficiency of the said resource. The study calls for immediate reallocation of resources so that optimum use of inputs is ensured not only to sustain rice production but also enhance proft maximization of indigent rice farmers in the study area.

Behavioral Portfolio Management with Layered ESG Goals and Ai Estimation of Asset Returns

Portfolio managers and individual investors alike are in quest of efficient asset allocation models that simultaneously express environmental, social, and governance (ESG) considerations along with investor behavioral biases. The current study presents a novel approach to optimize the behavioral portfolio management model in the presence of investor biases for ESG sustainability, loss aversion, and cognitive dissonance. We extend the factor pricing literature by implementing a factor extraction protocol to identify three unique and pervasive ESG factors. Upon examining the interconnectedness of the factors, machine learning methods are applied to a production-theoretic six-factor Fama and French model to predict individual asset returns. Enumeration of efficient asset allocations is obtained by solving a hierarchical multiobjective portfolio optimization model. simulation results from solving alternate specifications of the layered goal ESG-driven model corroborate and extend emergent research on portfolio sustainability, network theory, and the interconnectedness of financial returns. Additionally, we provide results to amplify the existence of a hump-shaped ESG efficiency frontier. The results provide new information about the trade-offs available for resolving cognitive dissonance when investors are conflicted between holding ‘green’ versus ‘brown’ asset diversification plans.

Technical efficiency of local dairy milk processing in Kwara State, North Central, Nigeria.


 
 
 
 This study examined the profitability and technical efficiency of local dairy milk processing in Kwara State using budgetary analysis and stochastic frontier model. Data set for the study was obtained through a randomly selected one hundred nomadic households in the state. The results of the budgetary analysis showed that local dairy milk processing was profitable in the study area with a net farm income of N683.25 per day. Results of the stochastic frontier efficiency model revealed the percentage efficiency to be 50-95 per cent with a mean of 76 per cent. The level of education of the nomadic household heads, the household size, as well as the years of experience in milk processing significantly reduced the inefficiency of local dairy milk processing in the study area. Improvement in the level of education of the milk processors will have positive implication on their technical efficiency.
 
 
 

A non-parametric approach in assessment of operational efficiency of irrigation systems in Southern Mindanao, Philippines

This study sought to estimate the technical efficiency of irrigation systems in Southern Mindanao Region, Philippines. In order to do so, the study assessed the relative efficiency of 108 communal irrigation systems of the five provinces in Southern Mindanao based on the combination inputs and outputs. The input-oriented data envelopment analysis via DEAP 2.1 revealed 28 irrigation systems that are fully-technically efficient as they exhibited 1.00 technical efficiency scores in both constant- and variable returns-to-scale assumptions. Among the fully efficient irrigation systems, Cebuza SIS, Cateel Integrated IS, Badagoy CIS, and Pantang CIS lead the irrigation systems that lie in the efficiency frontier. Implications were discussed.

Definition of input and output variables to assess operations strategy efficiency frontier

PurposeTo investigate the relationship between performance frontier and operations strategy. A two-level conceptual framework is proposed based on performance elements that act as output/input variables and delimit the scope of the frontier analysis.Design/methodology/approachThe framework proposition is based on the fourth round of high-performance manufacturing survey data. A representative set of variables for assessing performance based on operations strategy constructs is defined through multivariate data analysis techniques. The main method used is the principal component analysis.FindingsThe proposed first-level conceptual framework formalizes the relationships between performance frontier analysis techniques and operations strategy, delimiting the scope and the structural definitions. The second-level conceptual framework defines the constructs of the input and output dimensions for frontier analysis studies.Originality/valueThe paper contribution is developed in the gap of market-led orientation to study operations strategy performance frontier since most related literature focuses on capabilities development with a main focus on the resource-based view (RBV) approach. A conceptual framework based on the competitive priorities is therefore proposed to represent the operations strategy in the view of the frontier techniques. The value lies in defining performance measures which are not a straightforward task as the growth of organization competitiveness and complexity require multiple performance measures. A deeper understanding of frontier estimation on the operations strategy context is also provided, contributing to positively influence firms to succeed in the current dynamic competitive environments.

Uma análise da eficiência de portos europeus por meio da ferramenta análise envoltória de dados

Os portos possuem cada vez mais uma posição consolidada em virtude da vital importância na cadeia logística e comercial das nações. Após a expressiva concorrência apresentada com o decorrer da globalização trouxe como necessidade a melhora das ferramentas de gestão portuária. Dessa forma, a presente pesquisa pretende mostrar através da ferramenta Análise Envoltória de Dados, indicadores de eficiência de fatores como input/output. Dados os aspectos capacidade média de transporte por navio, número de contêineres transportados, idade média dos navios, número de chegadas ao porto e o tempo médio de atracação, a fim de estabelecer relações entre os 23 portos analisados com relação à fronteira de eficiência. Os resultados mostram uma disparidade significante entre as eficiências portuárias dos portos internacionais entre os modelos Constant Return Scale-CRS e Variable Return Scale-VRS. O top quatro dos portos eficientes em todas as análises foram Alemanha, Espanha, Bélgica e França. No entanto, pode-se perceber que o modelo VSR se mostrou menos eficiente frente ao CRS.

Performance evaluation of R&D organisations: an Asian perspective

Asian countries have enhanced their innovation capabilities through the advancements in science, technology and innovation with skilled workers and R&D institutions. Regardless of the investments made in R&D, a country’s objective of nurturing economic growth might not be fulfilled if R&D resources are used inefficiently. The aim of this paper is to evaluate and compare the R&D performance of Asian countries divided into two groups based on a threshold expenditure of 1% of GDP on R&D. Using an output-oriented DEA model, the study finds that five countries (Bahrain, Armenia, Oman, Georgia and Vietnam) in the first group and two countries (Singapore and Israel) in the second group are operating in the efficiency frontier. The study also reveals the relevance of parameters such as ‘ease of doing business’ strategies, regulatory policies, trade policies, industry academia collaboration, strategic collaboration between nations and public and private partnership on R&D efficiency.