Efficiency score from data envelopment analysis can predict the future onset of hypertension and dyslipidemia: A cohort study

Abstract Primary prevention focuses on ensuring that healthy people remain healthy. As it is practically difficult to provide intervention for an entire healthy population, it is essential to identify and target the at risk of risks population. We aimed to distinguish at risk of risks population using data envelopment analysis (DEA). Efficiency score was calculated from the DEA using a cohort sample and its association with the onset of hypertension and dyslipidemia was analyzed. A stratification analysis was performed according to the number of conventional risk factors in participants. The adjusted odds ratios (aORs) of the incidence of hypertension and dyslipidemia according to a 0.1-point increase in efficiency score were 0.66 (90% confidence interval [CI] 0.55–0.78, p < 0.0001) and 0.84 (90% CI 0.75–0.94, p = 0.01), respectively. In the stratification analysis, aOR of the incidence of hypertension according to a 0.1-point increase in efficiency score was 0.57 (90% CI 0.37–0.89, p = 0.04) in participants with no conventional risk factors. Participants with lower efficiency score were suggested to be at high risk for future onset of hypertension and dyslipidemia. The DEA might enable us to identify the risk of hypertension where conventional methods might fail.

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Effects of Data Envelopment Analysis on Performance Assessment

Operations and Service Management ◽

10.4018/978-1-5225-3909-4.ch027 ◽

2018 ◽

pp. 557-581

Author(s):

Heinz Ahn ◽

Nadia Vazquez Novoa

Keyword(s):

Data Envelopment Analysis ◽

Financial Performance ◽

Performance Assessment ◽

Performance Appraisal ◽

Efficiency Score ◽

Data Envelopment ◽

Financial Assessment ◽

Dea Efficiency ◽

Controlling Processes

This paper examines the Data Envelopment Analysis (DEA) methodology from a cognitive perspective. Specifically, it analyzes (a) the role of DEA scores as an overall efficiency measure and (b) to what extent the presence of DEA scores for a non-financial performance appraisal influences a posterior financial performance assessment. The study confirms that the efficiency score acts as a strong performance marker when deciding on which decision making units (DMUs) should be awarded for their non-financial performance. Furthermore, it shows that the results of the non-financial performance evaluation may act as an anchor which significantly influences a posterior financial assessment. These insights have practical consequences for planning, reporting, and controlling processes that incorporate DEA efficiency scores.

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683Data envelopment analysis for predicting pre-diabetes for primary disease prevention

International Journal of Epidemiology ◽

10.1093/ije/dyab168.473 ◽

2021 ◽

Vol 50 (Supplement_1) ◽

Author(s):

Sho Nakamura ◽

Hiroto Narimatsu

Keyword(s):

At Risk ◽

Disease Prevention ◽

Efficiency Score ◽

Healthy Population ◽

Health Maintenance ◽

Population At Risk ◽

Diabetes Onset ◽

Primary Disease ◽

Populations At Risk ◽

Dea Efficiency

Abstract Background Identifying a population at risk of risks is imperative for primary disease prevention and allows the promotion of health maintenance in a healthy population. Previous studies on hypertension and dyslipidemia using data envelopment analysis (DEA) showed that populations at risk of risks could be identified using this method. In this study, we extended DEA to include pre-diabetes. Methods A retrospective cohort study was conducted using specific health check-up data from 2008 to 2013. DEA efficiency scores were calculated for healthy subjects with baseline glycated hemoglobin (HbA1c) <5.7%. Odds ratios (ORs) for pre-diabetes onset within 3 years were analyzed. Results Among 1,501 subjects, with 373 cases of disease onset (24.9%), the OR for the incidence of pre-diabetes (on the basis of a 0.1-point increase in the efficiency score) was 0.77 (90% confidence interval [CI] 0.68–0.86, p < 0.0002). After adjusting for age and sex, the OR was 0.66 (90% CI 0.58–0.75, p < 0.0001). Furthermore, for the subgroup with no conventional diabetes risk factors, the adjusted OR was 0.50 (90% CI 0.38–0.67, p = 0.0001). Conclusions We showed that the DEA efficiency score can help identify a pre-diabetes population at risk of risks. Further studies to validate these findings would be worthwhile for optimizing primary preventative measures. Key messages DEA was assessed for its ability to evaluate the risk of pre-diabetes. Results showed that an efficiency score could predict pre-diabetes onset and demonstrated the feasibility of applying this analysis in primary preventive healthcare.

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Evaluation of the efficiency of logistics activities using Data Envelopment Analysis (DEA)

Gestão & Produção ◽

10.1590/0104-530x3371-20 ◽

2020 ◽

Vol 27 (1) ◽

Author(s):

Alessandro Lepchak ◽

Simone Bernardes Voese

Keyword(s):

Data Envelopment Analysis ◽

Efficiency Score ◽

Air Transport ◽

Maximum Efficiency ◽

Data Envelopment ◽

Analysis Model ◽

Lower Efficiency ◽

Cargo Handling ◽

Multimodal Analysis ◽

Using Data

Abstract This study aimed to analyze the efficiency of activities related to logistics modes, transport and cargo handling in Brazil. The theoretical framework was composed of the logistics efficiency and of the discussion of the characteristics of modes of transport and of variables related to efficiency. The study was classified as descriptive and quantitative, using the technique of data envelopment analysis. As main results, the ancillary activities to air transport stand out as efficient, which reached scores of 100% in the analyzed periods, except in 2010, in which they obtained 91.58%. It is worth noting that the activities cabotage and long-haul and ancillary activities to land transport achieved three maximum efficiency scores. In addition to evaluating the benchmark for the activities of lower efficiency score, the study also included improvements needed for other activities to achieve maximum efficiency. Finally, the central contribution of the article lies in the proposition of a multimodal analysis model.

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PEMILIHAN SAHAM SYARIAH YANG EFISIEN UNTUK PEMBENTUKAN PORTOFOLIO OPTIMAL

JURNAL ILMIAH EKONOMI ISLAM ◽

10.29040/jiei.v5i3.643 ◽

2019 ◽

Vol 5 (3) ◽

Author(s):

Nur Rachmat Arifin ◽

Raditya Sukmana

Keyword(s):

Data Envelopment Analysis ◽

Efficiency Score ◽

Optimal Portfolio ◽

Data Envelopment ◽

Single Index ◽

Index Model ◽

Single Index Model ◽

Efficient Performance ◽

Sample Data ◽

Dea Efficiency

Abstract: Analysis of optimal portfolio allows investors to analyze appropriate to minimize the risks accepted by the objective of maximizing profit with the same risk among existing stocks. Data Envelopment Analysis (DEA) is used to determine the stocks with the efficient performance based on ratio analysis. Having selected some stocks efficient formation of optimal portfolio is then performed with a single index models and determined how much the proportion of funds invested in each stock. The sample data used are stocks in ISSI 2012-2017. Based on the analysis of efficiency as a candidate portfolio models used DEA - CCR and DEA - BCC generate 16 efficient stocks that forming the candidate portfolio. After the analysis of all 18 stocks that efficiently obtained 6 stocks forming the optimal portfolio Keywords: Optimal Portfolio,Data Envelopment Analysis (DEA), Efficiency Stocks, Relative Efficiency Score , Single Index Model.

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Effects of Data Envelopment Analysis on Performance Assessment

International Journal of Business Analytics ◽

10.4018/ijban.2015010101 ◽

2015 ◽

Vol 2 (1) ◽

pp. 1-22

Author(s):

Heinz Ahn ◽

Nadia Vazquez Novoa

Keyword(s):

Data Envelopment Analysis ◽

Financial Performance ◽

Performance Assessment ◽

Performance Appraisal ◽

Efficiency Score ◽

Data Envelopment ◽

Financial Assessment ◽

Dea Efficiency ◽

Controlling Processes

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Benchmarking—A Way of Finding Risk Factors in Business Performance

Journal of Risk and Financial Management ◽

10.3390/jrfm14050221 ◽

2021 ◽

Vol 14 (5) ◽

pp. 221

Author(s):

Jarmila Horváthová ◽

Martina Mokrišová ◽

Mária Vrábliková

Keyword(s):

Risk Factors ◽

Data Envelopment Analysis ◽

Heat Supply ◽

Business Performance ◽

Data Envelopment ◽

Performance Factors ◽

Best Value ◽

Target Values ◽

Dea Method ◽

Comparison Of The Results

The purpose of this study was to emphasize that the Data Envelopment Analysis (DEA) method is an important benchmarking tool which provides necessary information for improving business performance. To fulfil the abovementioned goal, we used a sample of 48 Slovak companies involved in the field of heat supply. As their position in the economic and social environment of the country is essential, considerable attention should be paid to improving their performance. In addition to the DEA method, we applied the Best Value Method (BVM). We found that DEA is a highly important benchmarking tool, as it provides benchmarks for units that have problems with performance and helps us to reveal risk performance factors. The DEA method also allows us to determine target values of indicators. The originality of this paper is in its comparison of the results of the BVM and the DEA methods.

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Value-at-risk and data envelopment analysis: comments on Wu and Olson (2010)

International Journal of Production Research ◽

10.1080/00207543.2011.564666 ◽

2011 ◽

Vol 49 (23) ◽

pp. 7189-7193 ◽

Cited By ~ 2

Author(s):

Guiwu Wei ◽

Jiamin Wang

Keyword(s):

At Risk ◽

Data Envelopment Analysis ◽

Value At Risk ◽

Data Envelopment

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The Efficiency of Non-Bank Financial Intermediaries: Empirical Evidence from Malaysia

International Journal of Banking and Finance - Vol. 15, Number 2, 2020 ◽

10.32890/ijbf2008.5.2.8373 ◽

2008 ◽

Author(s):

Fadzlan Sufian

Keyword(s):

Risk Factors ◽

Data Envelopment Analysis ◽

Empirical Evidence ◽

Financial Institutions ◽

Economies Of Scale ◽

Financial Intermediaries ◽

Scale Efficiency ◽

Data Envelopment ◽

Parametric Data ◽

Dea Method

This paper investigates the performance of Malaysian non-bank financial institutions during the period of 2000-2004. Several efficiency estimates of individual NBFIs are evaluated using the non-parametric Data Envelopment Analysis (DEA) method. The findings suggest that during the period of study, scale inefficiency outweighs pure technical inefficiency in the Malaysian NBFI sector. We find that the merchant banks have exhibited a higher, technical efficiency compared to their peers. The empirical findings suggest that scale efficiency tends to be more sensitive to the exclusion of risk factors, implying that potential economies of scale may be overestimated when risk factors are excluded.

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Can the Implementation of Sharia Banks’ Roadmap Increase Their Performance? (Evidence from Indonesia 2012-2017)

Al-Iqtishad Journal of Islamic Economics ◽

10.15408/aiq.v12i2.15929 ◽

2020 ◽

Vol 12 (2) ◽

Author(s):

Riko Hendrawan

Keyword(s):

Data Envelopment Analysis ◽

T Test ◽

P Value ◽

Islamic Banking ◽

Data Envelopment ◽

Average Efficiency ◽

Road Map ◽

Significant Difference ◽

Dea Efficiency ◽

Increase Efficiency

Abstract. The purpose of this research is to compare the efficiency of 11 Sharia Banks in Indonesia and its impact on their performance. This study relies on the quarterly data from 2012-2017 and applied Data Envelopment Analysis to measure their performance. The result of the T-test shows that the P-value for two tail = 0.706. So based on this trend the P-value is greater than α = 0.05 (P-value> α). In the condition of P-value> α, H1 is rejected, meaning that there is no change in the value of efficiency between the period 2012-2014 and the period 2015-2017. This research shows that the efficiency of Islamic banking has not occurred during the implementation of the 2012-2017 Indonesian Sharia Banking Roadmap. Furthermore, the highest efficiency value during the period before implementation was 0.92 with an average efficiency value of 0.57. This means that during this period there was room to increase efficiency by 0.35. Meanwhile the period after implementing the highest efficiency value was 0.87 with an average efficiency value of 0.59. This means that during this period there was room to increase efficiency by 0.28. This means that during the 2012-2017 period, there was no significant difference in efficiency levels during the 2012-2014 period (before the implementation) and the 2015-2017 period (after the implementation of the Islamic banking road map). Keywords: DEA, Efficiency, Sharia Bank Abstrak. Tujuan dari penelitian ini adalah untuk membandingkan efisiensi dari 11 Bank Syariah di Indonesia dan dampaknya terhadap kinerja bank tersebut. Penelitian ini menggunakan data setiap kuartal selama tahun 2012 hingga tahun 2017 dan menggunakan Data Envelopment Analysis untuk mengukur kinerja. Hasil penelitian ini menunjukan bahwa selama implementasi Roadmap, perbankan syariah belum menunjukan kenaikan efisiensi. Sementara itu, sebelum implementasi tersebut, nilai efisiensi tertinggi perbankan syariah sebesar 0,92, sedangkan rata-rata nilai efisiensinya sebesar 0,57. Ini berarti bahwa ada ruang untuk meningkatkan level efisiensi sebesar 0,35. Sedangkan pada periode implementasi, nilai efisiensi tertingi perbankan syariah sebesar 0,87, dan ratarata nilai efisiensinya sebesar 0,59. Ini berarti ada ruang untuk meningkatkan level efisiensi sebesar 0,28. Hasil penelitian juga menunjukan bahwa, secara keseluruhan periode tahun 2012 hingga tahun 2017, hasil t-test menunjukan nilai P-value for two tail = 0.706. Ini berarti P-value> α, dan menolak H1, sehingga tidak terdapat perbedaan level efisiensi selama periode 2012-2014 (sebelum implementasi) dan periode 2015 – 2017 (setelah implementasi) Kata kunci: DEA, Efisiensi, Bank Syariah

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Supporting Better Decision-Making: A Combined Grey Model and Data Envelopment Analysis for Efficiency Evaluation in E-Commerce Marketplaces

Sustainability ◽

10.3390/su122410385 ◽

2020 ◽

Vol 12 (24) ◽

pp. 10385

Author(s):

Chia-Nan Wang ◽

Thanh-Tuan Dang ◽

Ngoc-Ai-Thy Nguyen ◽

Thi-Thu-Hong Le

Keyword(s):

Data Envelopment Analysis ◽

Business Performance ◽

Technology Development ◽

Technological Development ◽

Hybrid Approach ◽

Efficiency Score ◽

Grey Model ◽

Modern World ◽

Data Envelopment ◽

Input Variables

E-commerce has become an integral part of businesses for decades in the modern world, and this has been exceptionally speeded up during the coronavirus era. To help businesses understand their current and future performance, which can help them survive and thrive in the world of e-commerce, this paper proposes a hybrid approach that conducts performance prediction and evaluation of the e-commerce industry by combining the Grey model, i.e., GM (1, 1) and data envelopment analysis, i.e., the Malmquist-I-C model. For each e-commerce company, GM (1, 1) is applied to predict future values for the period 2020–2022 and Malmquist-I-C is applied to calculate the efficiency score based on output variables such as revenue and gross profit and input variables such as assets, liabilities, and equity. The top 10 e-commerce companies in the US market are used to demonstrate model effectiveness. For the entire research period of 2016–2022, the most productive e-commerce marketplace on average was eBay, followed by Best Buy and Lowe’s; meanwhile, Groupon was the worst-performing e-commerce business during the studied period. Moreover, as most e-commerce companies have progressed in technological development, the results show that the determinants for productivity growth are the technical efficiency change indexes. That means, although focusing on technology development is the key to e-commerce success, companies should make better efforts to maximize their resources such as labor, material and equipment supplies, and capital. This paper offers decision-makers significant material for evaluating and improving their business performance.

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