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This paper employs a cross-sectional research design to collect quantitative data for a group of Greek pharmaceutical companies in order to evaluate their credit risk. The data are processed using a variety of quantitative approaches, including series two-stage data envelopment analysis (DEA) combined with bootstrap and hierarchical clustering. The results of the two-stage DEA bootstrapped analysis indicate that the key problem with the firms’ performance is a lack of effectiveness rather than operating efficiency. The lack of a correlation between operating efficiency and effectiveness indicates that the firms’ performance metrics are unrelated. As a result, a bootstrapped DEA-based synthetic indicator is developed to be used with the other performance metrics as inputs to hierarchical clustering to divide sample firms into credit risk clusters. The series two-stage DEA bootstrapped approach used in this study could aid firms in evaluating their performance and increasing their competitive advantages.
Ioannis Tsolas. Firm Credit Scoring: A Series Two-Stage DEA Bootstrapped Approach. Journal of Risk and Financial Management 2021, 14, 214 .
AMA StyleIoannis Tsolas. Firm Credit Scoring: A Series Two-Stage DEA Bootstrapped Approach. Journal of Risk and Financial Management. 2021; 14 (5):214.
Chicago/Turabian StyleIoannis Tsolas. 2021. "Firm Credit Scoring: A Series Two-Stage DEA Bootstrapped Approach." Journal of Risk and Financial Management 14, no. 5: 214.
This paper proposes a stochastic frontier model for measuring both technical and environmental performance at the mine level by using a translog production function. The Kardia Field opencast lignite mine of the Greek Public Power Corporation (PPC), S.A. is the topic of the case study. Efficiency ratings are derived over a long period of time using annual operating data, and in addition, the determinants of inefficiency are established by means of the technical inefficiency effects model. In the light of the results, there is a strong correlation between technical and environmental efficiency; the results are validated by those produced by data envelopment analysis (DEA). In addition, the stripping ratio is identified as the statistically significant determinant of performance. The proposed framework could be used as an instrument to measure the efficiency of lignite mining operations and to identify the drivers of performance.
Ioannis Tsolas. Efficiency Analysis of Lignite Mining Operations Using Production Stochastic Frontier Modeling. Mining 2021, 1, 100 -111.
AMA StyleIoannis Tsolas. Efficiency Analysis of Lignite Mining Operations Using Production Stochastic Frontier Modeling. Mining. 2021; 1 (1):100-111.
Chicago/Turabian StyleIoannis Tsolas. 2021. "Efficiency Analysis of Lignite Mining Operations Using Production Stochastic Frontier Modeling." Mining 1, no. 1: 100-111.
A common concern for bus operators is efficiency measurement in order to monitor transit performance. The purpose of this paper is to propose a series two-stage data envelopment analysis (DEA) approach integrated with bootstrapping in order to evaluate the performance of electric trolley bus routes of Athens and Piraeus, Greece. Production and sales efficiency were measured in the first and second stages, respectively. In the light of the results, the routes assessed have a comparable higher DEA-based efficiency in both stages when compared to the perfect possible performance, but production and sales efficiency are not associated. Nevertheless, arterial bus routes have a marginally better performance in the production process on average, whereas the feeder–local bus routes produce a slightly better sales performance. The proposed modeling approach is an addition to the current literature, and can be employed by managers and operators.
Ioannis Tsolas. Performance Evaluation of Electric Trolley Bus Routes. A Series Two-Stage DEA Approach. Infrastructures 2021, 6, 44 .
AMA StyleIoannis Tsolas. Performance Evaluation of Electric Trolley Bus Routes. A Series Two-Stage DEA Approach. Infrastructures. 2021; 6 (3):44.
Chicago/Turabian StyleIoannis Tsolas. 2021. "Performance Evaluation of Electric Trolley Bus Routes. A Series Two-Stage DEA Approach." Infrastructures 6, no. 3: 44.
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.
Ioannis E. Tsolas. The Determinants of the Performance of Precious Metal Mutual Funds. Journal of Risk and Financial Management 2020, 13, 286 .
AMA StyleIoannis E. Tsolas. The Determinants of the Performance of Precious Metal Mutual Funds. Journal of Risk and Financial Management. 2020; 13 (11):286.
Chicago/Turabian StyleIoannis E. Tsolas. 2020. "The Determinants of the Performance of Precious Metal Mutual Funds." Journal of Risk and Financial Management 13, no. 11: 286.
This paper presents a data envelopment analysis (DEA) approach to benchmark a group of wind farm (WF) projects in Greece by employing a series two-stage structure. In the first stage, the investment performance of projects is evaluated using contract data and site wind conditions, though in the second stage the WF operational efficiency is evaluated using data on production inputs and output. Inefficiency occurs in both the construction and operating stages, but the construction process appears to be more inefficient relative to the operating phase. Moreover, WF size is related to operating efficiency and sensitivity analysis results identify wind speed and WF installation capacity as the factors that affect the investment performance and operational efficiency, respectively. The proposed approach is an addition to the existing literature and it can be used by managers and facility operators.
Ioannis E. Tsolas. Benchmarking Wind Farm Projects by Means of Series Two-Stage DEA. Clean Technologies 2020, 2, 365 -376.
AMA StyleIoannis E. Tsolas. Benchmarking Wind Farm Projects by Means of Series Two-Stage DEA. Clean Technologies. 2020; 2 (3):365-376.
Chicago/Turabian StyleIoannis E. Tsolas. 2020. "Benchmarking Wind Farm Projects by Means of Series Two-Stage DEA." Clean Technologies 2, no. 3: 365-376.
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.
Ioannis E. Tsolas. Financial Performance Assessment of Construction Firms by Means of RAM-Based Composite Indicators. Mathematics 2020, 8, 1347 .
AMA StyleIoannis E. Tsolas. Financial Performance Assessment of Construction Firms by Means of RAM-Based Composite Indicators. Mathematics. 2020; 8 (8):1347.
Chicago/Turabian StyleIoannis E. Tsolas. 2020. "Financial Performance Assessment of Construction Firms by Means of RAM-Based Composite Indicators." Mathematics 8, no. 8: 1347.
The quest for best practices may lead to an increased risk of poor decision-making, especially when aiming to attain best practice levels reveals that efforts are beyond the organization’s present capabilities. This situation is commonly known as the “best practice trap”. Motivated by such observation, the purpose of the present paper is to develop a practical methodology to support better practice benchmarking, with an application to the banking sector. In this sense, we develop a two-stage hybrid model that employs Artificial Neural Network (ANN) via integration with Data Envelopment Analysis (DEA), which is used as a preprocessor, to investigate the ability of the DEA-ANN approach to classify the sampled branches of a Greek bank into predefined efficiency classes. ANN is integrated with a family of radial and non-radial DEA models. This combined approach effectively captures the information contained in the characteristics of the sampled branches, and subsequently demonstrates a satisfactory classification ability especially for the efficient branches. Our prediction results are presented using four performance measures (hit rates): percent success rate of classifying a bank branch’s performance exactly or within one class of its actual performance, as well as just one class above the actual class and just one class below the actual class. The proposed modeling approach integrates the DEA context with ANN and advances benchmarking practices to enhance the decision-making process for efficiency improvement.
Ioannis E. Tsolas; Vincent Charles; Tatiana Gherman. Supporting better practice benchmarking: A DEA-ANN approach to bank branch performance assessment. Expert Systems with Applications 2020, 160, 113599 .
AMA StyleIoannis E. Tsolas, Vincent Charles, Tatiana Gherman. Supporting better practice benchmarking: A DEA-ANN approach to bank branch performance assessment. Expert Systems with Applications. 2020; 160 ():113599.
Chicago/Turabian StyleIoannis E. Tsolas; Vincent Charles; Tatiana Gherman. 2020. "Supporting better practice benchmarking: A DEA-ANN approach to bank branch performance assessment." Expert Systems with Applications 160, no. : 113599.
A lot of companies in the power sector use Engineering, Procurement, and Construction (EPC) contracts for complex infrastructure projects such as power plants. This paper presents a series two-stage data envelopment analysis (DEA) approach for the ex ante benchmarking of EPC power plant projects. The current study aims to improve over single-stage DEA and evaluate the efficiency of a group of twelve domestic (located in Greece) and international natural gas-fired power plant projects of different technologies (combined cycle power plant (CCPP) projects with single and multi-shaft configuration, and open cycle power plant (OCPP) projects) by employing a series two-stage DEA model. In the first stage, performance of the EPC mode is evaluated, whereas in the second stage the plant annual operational efficiency is assessed. In the light of the results, there is a lower level of performance in the EPC mode than in operating efficiency. The OCPP projects have the best operating efficiency, whereas they are ranked in-between the CCPP projects with single and multi-shaft configuration in EPC mode performance.
Ioannis E. Tsolas. Benchmarking Engineering, Procurement and Construction (EPC) Power Plant Projects by Means of Series Two-Stage DEA. Electricity 2020, 1, 1 -11.
AMA StyleIoannis E. Tsolas. Benchmarking Engineering, Procurement and Construction (EPC) Power Plant Projects by Means of Series Two-Stage DEA. Electricity. 2020; 1 (1):1-11.
Chicago/Turabian StyleIoannis E. Tsolas. 2020. "Benchmarking Engineering, Procurement and Construction (EPC) Power Plant Projects by Means of Series Two-Stage DEA." Electricity 1, no. 1: 1-11.
This paper documents a new series two-stage data envelopment analysis (DEA) modeling framework for mutual fund performance evaluation in terms of operational and portfolio management efficiency that is implemented to a sample of precious metal mutual funds (PMMFs). In the first and second stage, one-input/one-output and multi-input/one-output settings are used, respectively. In the light of the results, the funds assessed are inefficient in both operational and portfolio management process and in particular, they seem to be more inefficiently operated. The operational management efficiency is correlated with portfolio management efficiency and, therefore, sample funds should give more emphasis on their operational policies to ensure their success in the industry. The research framework may not only benefit PMMFs, but also funds of other classes to quantify their performance and improve their competitive advantages.
Ioannis E. Tsolas. Precious Metal Mutual Fund Performance Evaluation: A Series Two-Stage DEA Modeling Approach. Journal of Risk and Financial Management 2020, 13, 87 .
AMA StyleIoannis E. Tsolas. Precious Metal Mutual Fund Performance Evaluation: A Series Two-Stage DEA Modeling Approach. Journal of Risk and Financial Management. 2020; 13 (5):87.
Chicago/Turabian StyleIoannis E. Tsolas. 2020. "Precious Metal Mutual Fund Performance Evaluation: A Series Two-Stage DEA Modeling Approach." Journal of Risk and Financial Management 13, no. 5: 87.
Selecting funds is a common problem for investors who use published available data on fund indicators while they are selecting the funds. Since this process deals with more than one indicator, the investing issue becomes multi-criteria decision-making (MCDM) problem for the investors. Therefore, the purpose of this paper is to propose an effective approach that integrates grey relational analysis (GRA) and data envelopment analysis (DEA) for selecting the best utility exchange traded funds (ETFs). The current study uses GRA for deriving the grade relational coefficients and then puts them in the output side of competing no-input DEA models to derive weighed grey relational grades. Moreover, the ETFs are also evaluated by selected DEA models. This research is implemented with real data on utility ETFs available for three consecutive years (2008–2010). The results show that the top ETFs identified by the GRA-DEA approach are also DEA efficient. The proposed GRA-DEA approach is superior to conventional DEA as regards the fund ranking and therefore, it seems to be effective as a picking fund tool.
Ioannis E. Tsolas. Utility Exchange Traded Fund Performance Evaluation. A Comparative Approach Using Grey Relational Analysis and Data Envelopment Analysis Modelling. International Journal of Financial Studies 2019, 7, 67 .
AMA StyleIoannis E. Tsolas. Utility Exchange Traded Fund Performance Evaluation. A Comparative Approach Using Grey Relational Analysis and Data Envelopment Analysis Modelling. International Journal of Financial Studies. 2019; 7 (4):67.
Chicago/Turabian StyleIoannis E. Tsolas. 2019. "Utility Exchange Traded Fund Performance Evaluation. A Comparative Approach Using Grey Relational Analysis and Data Envelopment Analysis Modelling." International Journal of Financial Studies 7, no. 4: 67.
This paper employs stochastic frontier analysis (SFA) in assessing efficiency at the mine level. An SFA model is derived using annual operational data from the Kardia Field mine of the Greek Public Power Corporation (PPC) S.A. for the 1984-2006 period and the causes of inefficiency are investigated by means of regression techniques. The proposed two-stage model can be used as a diagnostic tool to identify causes of mine inefficiency and as a tool for designing and specifying interventions to improve mine performance.
Ioannis E. Tsolas. Mine Performance Assessment by Means of Stochastic Frontier Analysis. Mathematical Problems in Engineering 2019, 2019, 1 -7.
AMA StyleIoannis E. Tsolas. Mine Performance Assessment by Means of Stochastic Frontier Analysis. Mathematical Problems in Engineering. 2019; 2019 ():1-7.
Chicago/Turabian StyleIoannis E. Tsolas. 2019. "Mine Performance Assessment by Means of Stochastic Frontier Analysis." Mathematical Problems in Engineering 2019, no. : 1-7.
Over the past few decades, the banking sectors in Latin America have undergone rapid structural changes to improve the efficiency and resilience of their financial systems. The up-to-date literature shows that all the research studies conducted to analyze the above-mentioned efficiency are based on a deterministic data envelopment analysis (DEA) model or econometric frontier approach. Nevertheless, the deterministic DEA model suffers from a possible lack of statistical power, especially in a small sample. As such, the current research paper develops the technique of satisficing DEA to examine the still less explored case of Peru. We propose a Satisficing DEA model applied to 14 banks operating in Peru to evaluate the bank-level efficiency under a stochastic environment, which is free from any theoretical distributional assumption. The proposed model does not only report the bank efficiency, but also proposes a new framework for peer mining based on the Bayesian analysis and potential improvements with the bias-corrected and accelerated confidence interval. Our study is the first of its kind in the literature to perform a peer analysis based on a probabilistic approach.
Vincent Charles; Ioannis E. Tsolas; Tatiana Gherman. Satisficing data envelopment analysis: a Bayesian approach for peer mining in the banking sector. Annals of Operations Research 2017, 269, 81 -102.
AMA StyleVincent Charles, Ioannis E. Tsolas, Tatiana Gherman. Satisficing data envelopment analysis: a Bayesian approach for peer mining in the banking sector. Annals of Operations Research. 2017; 269 (1-2):81-102.
Chicago/Turabian StyleVincent Charles; Ioannis E. Tsolas; Tatiana Gherman. 2017. "Satisficing data envelopment analysis: a Bayesian approach for peer mining in the banking sector." Annals of Operations Research 269, no. 1-2: 81-102.
We propose a satisficing DEA model to measure the efficiency of the Greek banks.LLP are treated as a stochastic controllable input variable.Haircut losses on Greek bonds are treated as an uncontrollable input variable.The proposed frontier screens further some of the \"best-in-class\" banks. This paper is motivated by recent concerns, prompted by the recent financial crisis, that regulatory capital guidelines on loan loss reserves can generate dysfunctional outcomes and, moreover, by the fact that the Greek bonds held by the banks have an important impact on the risk level of the bank portfolio. The purpose of this paper is to incorporate risk into bank efficiency and to provide a snapshot of the efficiency profile of the Greek banking industry. Efficiency is measured by means of a satisficing data envelopment analysis (DEA) model in which the financial risk is proxied by credit risk provisions and by the participation of banks in the Private Sector Involvement (PSI), a controllable and an uncontrollable factor by the bank management, respectively. The results of the proposed probabilistic DEA model derived through the Monte-Carlo simulation are compared with the results of the respective deterministic model. As the constructed stochastic frontier screens further some of the 'best-in-class' banks, the merit of the proposed metric is evident.
Ioannis E. Tsolas; Vincent Charles. Incorporating risk into bank efficiency: A satisficing DEA approach to assess the Greek banking crisis. Expert Systems with Applications 2015, 42, 3491 -3500.
AMA StyleIoannis E. Tsolas, Vincent Charles. Incorporating risk into bank efficiency: A satisficing DEA approach to assess the Greek banking crisis. Expert Systems with Applications. 2015; 42 (7):3491-3500.
Chicago/Turabian StyleIoannis E. Tsolas; Vincent Charles. 2015. "Incorporating risk into bank efficiency: A satisficing DEA approach to assess the Greek banking crisis." Expert Systems with Applications 42, no. 7: 3491-3500.
This paper appraises the performance of a sample of green exchange-traded funds (ETFs) using two types of data envelopment analysis (DEA) metrics. The first type is based on slacks-based DEA models, namely, the range-adjusted measure (RAM) and its variant the RAM-BCC model; the second type is based on a common set of weights of RAM. The appraisal is performed under the assumption that there are value stocks on the green equity market and the potential investors prefer ETFs that put emphasis on value stocks. In the first stage of the analysis, ETF efficiency ratings are derived, whereas in the second stage, ordinary least squares, censored Tobit, and bootstrapped-truncated regression are employed to model the fund ratings. The results are acceptable, indicating that four or five out of the sixteen sample funds depending on the model employed can be candidates for value investors. Moreover, although there is not much evidence for systematic effects of the beta coefficient on fund rating, the findings of the analyses entail implications for potential investors by using the models as an investment pick and for fund managers by considering the mitigation of risk and bringing higher selectivity to their portfolios.
Ioannis E. Tsolas; Vincent Charles. Green exchange-traded fund performance appraisal using slacks-based DEA models. Operational Research 2015, 15, 51 -77.
AMA StyleIoannis E. Tsolas, Vincent Charles. Green exchange-traded fund performance appraisal using slacks-based DEA models. Operational Research. 2015; 15 (1):51-77.
Chicago/Turabian StyleIoannis E. Tsolas; Vincent Charles. 2015. "Green exchange-traded fund performance appraisal using slacks-based DEA models." Operational Research 15, no. 1: 51-77.
This paper documents a new series two-stage DEA modeling framework for credit risk evaluation in terms of operating performance efficiency and effectiveness that is implemented to a sample of listed Greek firms of basic resources and chemicals sector. In the series stages two types of DEA metrics are used: The first type is based on the range adjusted measure (RAM) whereas the second type is based on a common set of weights (CSW) of RAM. Performance inefficiency is uncovered in both performance dimensions, but the real problem of inefficiency of the sampled firms is a lower level of effectiveness, rather than operating performance efficiency. The operating efficiency is not correlated with effectiveness, and thus it seems that there is not a link between the performance at the operational (cost-oriented) and financial (profit-oriented) spaces of the firm. Therefore, sample firms should give more emphasis on their profit-oriented policies to ensure their success in the industry. The research framework may benefit not only Greek listed firms, but also firms in other countries to quantify their performance and improve their competitive advantages.
Ioannis E. Tsolas. Firm credit risk evaluation: a series two-stage DEA modeling framework. Annals of Operations Research 2014, 233, 483 -500.
AMA StyleIoannis E. Tsolas. Firm credit risk evaluation: a series two-stage DEA modeling framework. Annals of Operations Research. 2014; 233 (1):483-500.
Chicago/Turabian StyleIoannis E. Tsolas. 2014. "Firm credit risk evaluation: a series two-stage DEA modeling framework." Annals of Operations Research 233, no. 1: 483-500.
This paper aims to assess the performance of a sample of completed building projects in Oregon by employing the range-adjusted measure, a slack-based data envelopment analysis (DEA) model. In the first stage of analysis, project efficiency ratings (ie composite indicators) are derived using selected single performance indicators in a no-output model; whereas in the second stage, censored Tobit regression is employed to model the efficiency ratings. The results indicate that only four out of the 50 sample projects are efficient within the DEA context. Moreover, there is not much evidence for systematic effects of project size on DEA efficiency rating.
I E Tsolas. Construction project monitoring by means of RAM-based composite indicators. Journal of the Operational Research Society 2013, 64, 1291 -1297.
AMA StyleI E Tsolas. Construction project monitoring by means of RAM-based composite indicators. Journal of the Operational Research Society. 2013; 64 (8):1291-1297.
Chicago/Turabian StyleI E Tsolas. 2013. "Construction project monitoring by means of RAM-based composite indicators." Journal of the Operational Research Society 64, no. 8: 1291-1297.
The purpose of this paper is to evaluate the performance of a sample of nineteen construction firms listed on the Athens Exchange by applying a two-step procedure. In the first step, data envelopment analysis (DEA) is used to model performance in two dimensions: profitability efficiency and efficiency in the market value-generating process. This allows the independent identification of the most efficient level of input in minimizing resources and the most efficient level of output in maximizing market value, various benchmarks, and the local returns to scale patterns of the firms of the sample in both performance dimensions. Moreover, it is possible to examine whether a correlation exists between the performance efficiency scores. In the second step, regression models are used to identify the drivers of performance. Performance inefficiency is uncovered in both dimensions, but the real problem of inefficiency of the sampled firms is the lower level of performance in the market value-generating process rather than profitability. The results revealed that profitability can be explained by selling and the administrative cost-to-total-revenue ratio and profit margin, but there is not much evidence for systematic effects of control variables on firm valuation. Results do not show positive links between profitability efficiency and performance in the stock market. Most of the large, inefficient firms exhibit decreasing returns to scale (DRS) in the profitability dimension, whereas most of the inefficient firms exhibit increasing returns to scale (IRS) in the stock market performance dimension. Moreover, there is potential for the firms of the sample that operate under non-DRS to accommodate and manage higher levels of business volume that will lead to increased level of market value. Implications of the study are also discussed.
Ioannis E. Tsolas. Modeling Profitability and Stock Market Performance of Listed Construction Firms on the Athens Exchange: Two-Stage DEA Approach. Journal of Construction Engineering and Management 2013, 139, 111 -119.
AMA StyleIoannis E. Tsolas. Modeling Profitability and Stock Market Performance of Listed Construction Firms on the Athens Exchange: Two-Stage DEA Approach. Journal of Construction Engineering and Management. 2013; 139 (1):111-119.
Chicago/Turabian StyleIoannis E. Tsolas. 2013. "Modeling Profitability and Stock Market Performance of Listed Construction Firms on the Athens Exchange: Two-Stage DEA Approach." Journal of Construction Engineering and Management 139, no. 1: 111-119.
Existing research on construction performance measurement is dominated by project level studies, and the firm stakeholders require the development of models that compare performance in terms of efficiency. A new framework that integrates data envelopment analysis (DEA) and ratio analysis using a two-step approach is described to evaluate performance in terms of profitability and effectiveness of a sample of construction firms listed on the Athens Exchange. In the first step, profitability and effectiveness are assessed by employing DEA and by using the profit margin (i.e. income-to-sales ratio), respectively. In the second step, a Tobit and an ordinary least squares model are used in order to identify the drivers of profitability efficiency and effectiveness, respectively. Results do point out positive links between profitability efficiency and effectiveness. Profitability inefficiency can be explained by the size and expenses-to-total revenue ratio, whereas effectiveness can be explained only by the latter explanatory variable. The research framework may benefit not only Greek construction firms, but also firms in other countries to quantify their performance and improve their competitive advantages.
Ioannis E. Tsolas. Modelling profitability and effectiveness of Greek-listed construction firms: an integrated DEA and ratio analysis. Construction Management and Economics 2011, 29, 795 -807.
AMA StyleIoannis E. Tsolas. Modelling profitability and effectiveness of Greek-listed construction firms: an integrated DEA and ratio analysis. Construction Management and Economics. 2011; 29 (8):795-807.
Chicago/Turabian StyleIoannis E. Tsolas. 2011. "Modelling profitability and effectiveness of Greek-listed construction firms: an integrated DEA and ratio analysis." Construction Management and Economics 29, no. 8: 795-807.
This paper presents a Data Envelopment Analysis (DEA) model combined with bootstrapping to assess performance in mining operations. Since DEA-type indicators based on nonparametric production analysis are simply point estimates without any standard error, we provide a methodology to assess the performance of strip mining operations by means of a DEA bootstrapping approach. This methodology is applied to a sample of fifteen Illinois strip coal mines using publicly available data (Thompson et al., 1995). The applied approach uses a mixed mine environmental performance indicator (MMEPI) that is derived by means of a VRS DEA environmental technology treating overburden as an undesirable output under the weak disposability assumption, and we compare this measure with a traditional output-oriented mine performance indicator (MPI) omitting overburden. Although omitting undesirable output results in biased performance estimates, these findings are based on sample specific results and indicate this bias is not statistically significant. The confidence intervals derived by the bootstrapping of the proposed MMEPI point estimates indicate that significant inefficiency has taken place in the analyzed sample of Illinois strip mines.
Ioannis E. Tsolas. Performance assessment of mining operations using nonparametric production analysis: A bootstrapping approach in DEA. Resources Policy 2011, 36, 159 -167.
AMA StyleIoannis E. Tsolas. Performance assessment of mining operations using nonparametric production analysis: A bootstrapping approach in DEA. Resources Policy. 2011; 36 (2):159-167.
Chicago/Turabian StyleIoannis E. Tsolas. 2011. "Performance assessment of mining operations using nonparametric production analysis: A bootstrapping approach in DEA." Resources Policy 36, no. 2: 159-167.
This paper employs for the first time data envelopment analysis (DEA) and stochastic frontier analysis (SFA) as two performance measurement competing approaches to assess efficiency in the Greek mining industry. These two frontier estimation methodologies overcome the limitations of the partial productivity measures by explicitly considering two inputs and one output in the measurement of efficiency for the period 1970–1996. The paper is also innovative in utilizing a bootstrapping approach in DEA to aggregated industry (time series) data as an alternative to the more common DEA point estimates. In particular, the bootstrapping approach used relies on the homogeneity assumption that the distribution of the efficiency scores is independently distributed over the sample; the results from DEA and SFA are more comparable under this assumption as it corresponds to the independence assumption regarding the distribution of the inefficiency term in SFA. The two different approaches to performance evaluation, as used here, do not provide confirmation of each other's findings since they are based on different principles and treat the data in different ways. Although the joint use made here of DEA and SFA provides results that are consistent with points of view that have regarded these two approaches as mutually exclusive alternatives, this paper demonstrates that from a policy perspective DEA and SFA can be utilized in tandem on a common data set to assess the efficiency and investigate the return to scale patterns at the sectoral level.
I. E. Tsolas. Assessing performance in Greek bauxite mining by means of frontier estimation methodologies. IMA Journal of Management Mathematics 2009, 21, 253 -265.
AMA StyleI. E. Tsolas. Assessing performance in Greek bauxite mining by means of frontier estimation methodologies. IMA Journal of Management Mathematics. 2009; 21 (3):253-265.
Chicago/Turabian StyleI. E. Tsolas. 2009. "Assessing performance in Greek bauxite mining by means of frontier estimation methodologies." IMA Journal of Management Mathematics 21, no. 3: 253-265.