Data Environment Analysis Research Articles

Distribution Systems and Efficiency of Life Insurers in Korea

This study investigates the technical efficiencies of all life insurance companies in Korea using data environment analysis (DEA) for the sample of 2006 – 2017. During the sample period studied, new life policy sales by cyber marketing and traditional face-to-face sales have significantly increased and sales by other distribution methods have parred or decreased. The estimates of average technical efficiency measures of Korean life insurers are about 18 percent higher than those of foreign life insurers. Among competing regression models, a random effects model is found to be an appropriate model and shows that cyber marketing and tele-marketing have a statistically significant positive impact on insurers’ efficiency, while there is a statistically significant negative relationship between the capital input and the efficiency. The findings of this suggest that insurers should strive to increase their operational efficiency by reevaluating and restructuring their distribution channels.

Assessing the differences in the levels and dynamics of economic development of Kazakhstani regions

This study aims to analyze the level of differences based on effectiveness, statistical dependence, and mutual influence of economic indicators for ranking the regions of Kazakhstan. In the paper, a systematic algorithm of actions is used, ensuring the interconnectedness, the sequence of work, and the validity of the methods used. Several model specifications were formulated to identify interregional differences in economic development indicators: the operating data environment analysis model (DEA) and the random effects regression model (RE). The information database of the Bureau of National Statistics of the Republic of Kazakhstan for 2010–2020 was used. The construction of the RE model was carried out in the SPSS program. A regression model with fixed and random effects in panel data was employed to determine the impact of the selected indicators on gross regional product produced (GRP). Based on the results, the influence of the physical volume of industrial products on GRP per capita in the regions of Kazakhstan for 11 years was revealed in both models with a high significance of coefficients. The study results can be used by public administration bodies that carry out effective strategic management by smoothing interregional differences. Moreover, they can determine the prospects for studying other parameters based on efficiency, statistical dependence, and mutual influence of economic indicators for ranking regions. AcknowledgmentThis study has been funded by the Committee of Science of the Ministry of Science and Higher Education of the Republic of Kazakhstan (grant “Priorities and mechanisms of inclusive regional development of Kazakhstan in the context of overcoming the economic recession” AP09259004).

Investigation of New Prosumer Peer-to-Peer Decisions into Energy Community Integration

The search for advanced solutions for Prosumers and their integration is one of the critical directions of forming the Energy Community. Future challenges to electric grids and their solutions and other subject areas in the energy sector include such related issues as Intelligent Autonomous Vehicles, Monitoring, Protection, and Control in the Post-Cyber Attacks for the formation of integration components of progressive ecosystems. The report provides a brief overview from the perspective of the development of the Proactive Control and the study of the applicability of the Data Environment Analysis technology.

An Implementation of A Combined DEA-PROMETHEE Method for The Hull of A Ship Application

The selection of an appropriate parameter in a water absorption process experiment is an important route to reducing fabrication wastes and ensuring the optimum deployment of scarce process resources to the appropriate parameter. However, the literature is inadequate in providing an appropriate direction on selecting parameters for the hull of the ships' application due to the conflicting requirements of the interested parties. A novel method called the Data Environment Analysis (DEA) to overcome this problem. Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE) method is deployed to establish the appropriate parameter in a water absorption process on epoxy composite. The net outranking results show that criterion B (final weight) is placed in the first position. The criterion A (initial weight), D (thickness), and C (length) are placed in the second, third, and fourth positions, respectively, while E (time) is not necessary to the achievement of the system's goals. The key novelty is the unique application of the fused DEA-PROMETHEE method to a composite using the Taguchi signal-to-noise ratio response table for the hull of a ship. The method enhances the performance of multiple inputs (parameters) and multiple outputs (responses). The results of the DEA method-PROMETHEE method established the potential of epoxy composite to be used on the ship for the hull component. This could reduce the waste generated in the system, and guided allocation of resources are made to the appropriate parameters and, consequently, enhance the shipping company's profit. Furthermore, the results could improve the shipping vessel performance and develop a sustainable practice, which will lengthen the lifespan of the shipping industry.

Evaluating the performance of Chinese fossil fuel power plants by data environment analysis: An application of three intermediate approaches in a time horizon

To our knowledge, the previous studies did not answer the following questions: how much does window analysis differ from the original Data Envelopment Analysis (DEA) approaches and how to develop DEA window analysis? To address these questions, we propose three intermediate approaches (cross-sectional approach, window efficiency analysis and window index approach) and statistically compare their performances. The underlying concern is that we need to examine whether a metrological bias exists in our study. The concern is important in guiding policy issues such as energy policy and climate change. Empirically, the proposed approaches are applied to measure the unified efficiency of fossil fuel power plants at a provincial level in China from 2007 to 2017, since these plants are important energy consumers and CO2 emitters. We obtain two important implications. First, considerable differences were confirmed among the three approaches, thus implying an existence of the methodological bias. Second, Beijing (the capital of China) outperformed the other provinces in terms of their measures, since the government has paid serious attention to air pollution emitted from fossil fuel power plants. The governmental regulation in Beijing is a good example of pollution prevention in China. It is expected that the success on Beijing will be disseminated to the other provinces.

Performance Method for Innovative Activity on the Achieved Level of the Country’s Socioeconomic Development

The purpose of this study is to make an attempt to assess the innovation activity on the achieved result , expressed in indicators that determine the socioeconomic level of country development, as it is the purpose of innovation In the applied method of calculating the evaluation of the effectiveness of innovation (Data environment Analysis) these indicators were the results, while the indicators of innovation were considered as a “resource”. Rental indicators, Gini index and others , reflecting (directly or indirectly) the result of innovations was also taken into account. The results showed values that were less inconsistent with the estimates for other related indexes and indicators , while the evaluation with existing methods gave more inaccurate results. This suggests that the proposed method gives a more objective assessment of the innovation level in the country and more accurately determines the country ‘s place in the world ranking. The main source of the world economy development today is the innovation, an integrated assessment of which on a national scale can itself act as an indicator of the level of economic and — in a broader sense — the socio-economic level of the country development . From this point of view, an objective assessment of the innovation development level, as well as the development and proposal of methods for its evaluation are still relevant. Up-to-date assessment methods mainly assess the potential of countries to develop innovations, while their achieved level should be assessed, since, with significant differences in the development of countries , these potential opportunities can be realized to varying degrees.

The Financial Decentralization Policy for Local Development in Cameroon: An Econometric Analysis

The objective of this article is to show the effectiveness of financial decentralization policy in the process of local development. In order to do so, we analyze the financial decentralization as a determinant of the effectiveness of local development in Cameroon. To achieve the main objective, we have used the data grouped together after the exploitation of the communal development plans. Using the Data Environment Analysis (DEA) model, we have obtained interesting results: When the budget allocated to decentralized territorial collectivities (DTC) is increased by 1%, this makes possible an increase of 13 points of the achievement of non-revenue generating projects and by11 points, those of income-generating projects at the level of DTC. When the budget increases by 10 points, there is an increase of 130 points of the achievements of non-revenue generating projects and 110 points of those of income-generating projects. The increase of financial resources at the level of DTCs would create a reasonable increase of investments in socio collective projects and in basic infrastructures. This leads to a drastic reduction in the unemployment rate. We can recommend to the Government to implement strategies that can reinforce the practice of financial decentralization and ensure decentralized governance. The financial decentralization is an economic indicator that can bring growth and development

Distribution Systems and Efficiency of Life Insurers in Korea

This study investigates technical efficiencies of all life insurance companies in Korea using data environment analysis (DEA) for the sample of 2006 – 2017. During the sample period studied, new life policy sales by cyber marketing and traditional face-to-face sales have significantly increased and sales by other distribution methods have parred or decreased. The estimates of average technical efficiency measures of Korean life insurers are about 18 percentage higher than those of foreign life insurers. Among competing regression models, a random effects model is found to be an appropriate model and shows that cyber marketing and tele-marketing have statistically significantly positive impact on insurers’ efficiency, while there is a statistically significantly negative relationship between the capital input and the efficiency. The findings of this suggests insurers should strive to increase their operational efficiency by reevaluating and restructuring their distribution channels.

PERSPECTIVES OF DEVELOPMENT OF MEDICAL TOURISM IN THE RUSSIAN FEDERATION:ANALYSIS OF COMPETITIVE ENVIRONMENT BY METHOD OF DATA ENVIRONMENT ANALYSIS

Explanatory concepts of internal, exit and entrance medical tourism have been given. The data environment analysis of Russia and other countries-participants of the market of medical tourism has been carried out. The key directions of international medical tourism have been defined. Based on the analysis, the conclusions about the prospects of Russia’s participation in this market have been made, recommendations for improving the system of medical services to foreign citizens have been given. The key perspective directions of medical tourism to Russia have been determined.

NATIONAL INNOVATION SYSTEMS OF BRICS COUNTRIES : GENERAL FEATURES AND PROSPECTS OF COOPERATION

Nowadays Russia is an active participant in international associations, both formal and informal (e. g. BRICS). At first glance, the BRICS is a group of countries that are not related either geographically or ideologically. However, long-term cooperation between the countries proves the opposite: new initiatives are being created, joint work is developing not only on economic, but also research and innovation projects. In this article there is the analysis about the existing features of the national innovation systems (NIS) of countries and highlights their distinguishing features, for example, the importance of national academies of Sciences in the framework of the NIS, as well as the need for their consideration as additional subjects of NIS. At the first stage of the study, the positions of the five BRICS countries in the leading international rankings of innovation activity are analyzed. At the second stage-the analysis of the operating environment (Data Environment Analysis, DEA), which allows to estimate the ratio of costs and results of innovation. According to the results of the analysis, it is suggested which of the BRICS countries can become a potential leader in further innovative cooperation between the countries.

The efficiency and impact of banking electronic services: evidence for Kosovo

Since the beginning of 2000, the banking sector has been one of the most developed sectors in the Kosovo's economy. In the session of literature review, this paper will provide a brief background on the banking electronic services, their progress during last years in Kosovo and in other Balkan countries, as well as their impact in the whole banking sector. Appropriate methods for analysing the efficiency and impact of banking electronic services are presented in the methodology session. The results in data environment analysis have shown that the highest banking efficiency has been in 2013; it is a result of increased of the volume and the value of transactions in e-banking. Then, the results found through the ordinary least squares method have shown that e-banking and point of sale service have positive impact, but automated teller machine service has negative impact in banking net profit. Our conclusions are mainly based on the further improvement and development of electronic banking services.

Measuring Economic and Environmental Performance of Energy Resources in ISIC codes: Evidence from Iran’s Industry Sector

Recently, in accordance with global environmental conservation awareness, undesirable outputs of production and social activities (e.g., air pollutants) have harmful social and environmental dimensions especially in developing countries. Therefore, this study discusses how to apply Data Environment Analysis (DEA) for environmental assessment. However, previous DEA research has documented a limited use of DEA on environmental assessment. A unique feature of DEA-based environmental assessment is that it needs to classify outputs into desirable and undesirable outputs. On the other hand, there is a lack of literatures in field of measuring on economic and environmental energy efficiency between ISIC codes. Therefore, this paper measured the energy efficiency of Iran’s main ISIC sub sectors using non linear DEA approach. Results indicated that between studied ISIC codes, the codes 15 and 24 have most economic (0.97 and 1.00) and environmental (1.00 and 0.82) efficiency, respectively. Also, in comparison with the other studied ISIC codes, the code 23 is economically and environmentally inefficient (0.28 and 0.32).

DEA environmental assessment in time horizon: Radial approach for Malmquist index measurement on petroleum companies

The climate change and various pollutions have been influencing our societies and economies. The environmental assessment, to be discussed in this study, is increasingly important because it serves as an initial step toward pollution prevention. Corporate leaders, policy makers, researchers and individuals who are interested in environmental protection have been paying attention to the assessment so that they can prepare policy suggestions on the global warming and climate change. As a methodology for the assessment, this study proposes a use of Data Environment Analysis (DEA) in a time horizon. Most of data sets on the climate change are sampled in a time series where the performance of organizations fluctuates every moment. In applying the DEA environmental assessment to such a data set, it is necessary for us to classify outputs into desirable (e.g., oil production) and undesirable (e.g., CO2 emission) categories because all organizations usually produce not only desirable but also undesirable outputs as a result of their economic activities. To unify the two different types of outputs, this study incorporates the concept of natural and managerial disposability into the computational framework of DEA and extends them into a time horizon. For the research purpose, this study incorporates Malmquist index into the proposed DEA environmental assessment to examine an occurrence of a frontier shift among multiple periods. The frontier shift indicates a technology progress and/or managerial innovation during an observed period. The index is further separated into four subcomponents in a time horizon. These subcomponents are differently expressed under the natural and managerial disposability. Thus, eight different subcomponents on the Malmquist index are proposed to measure the frontier shift. As an application, this study uses the proposed DEA approach to examine whether the frontier shift (due to technology progress) occurs or not in the petroleum industry from 2005 to 2009. Our empirical study finds that the industry has not exhibited any major frontier shift under natural disposability, but showing a considerable frontier shift under managerial disposability. In other words, the petroleum firms have improved their environmental performance by eco-technology to reduce an amount of CO2 emission during the observed annual periods.

DEA environmental assessment in a time horizon: Malmquist index on fuel mix, electricity and CO2 of industrial nations

Climate change and global warming become a major policy issue in the world. Economic activities produce not only desirable outputs (e.g., electricity) but also undesirable outputs (e.g., CO2 emission). The important policy issue is how each nation can balance between economic development and environmental protection to attain a sustainable society. In attaining the sustainable society, environmental assessment is increasingly important because it can serve as an initial step toward the green growth of each nation. For the purpose, this study proposes a new use of DEA (Data Environment Analysis) for environmental assessment in a time horizon. The proposed use of DEA incorporates Malmquist index to examine the degree of a frontier shift among multiple periods. The frontier shift indicates a technology progress and/or managerial innovation during an observed period. The index is conceptually separated into six subcomponents, which are further divided into twelve different subcomponents (six subcomponents×two disposability concepts) under the natural and managerial disposability. In the index measurement, it is necessary for us to consider a frontier crossover among different periods because technology innovation usually has a time lag until it really appears. As an empirical application, this study utilizes the proposed approach to identify the relationship among fuel mix, electricity and CO2 of ten industrial nations. This study finds three important empirical findings. First, there is a time lag in technology innovation on electricity generation and CO2 emission reduction. Consequently, it is necessary to consider the existence of a frontier crossover in assessing the electric power industry. Second, nuclear generation, as found in France, as well as hydro and renewable energy, as found in Netherlands, are important for the development of a sustainable society although the former is associated with a very high level of risk and the latter has a limited generation capacity. Finally, the electric power industry has been making a corporate effort to reduce the amount of CO2 emission by utilizing nuclear and renewable energy.

DEA environmental assessment of coal fired power plants: Methodological comparison between radial and non-radial models

This study discusses how to apply Data Environment Analysis (DEA) for environmental assessment. A unique feature of DEA environmental assessment is that it classifies outputs into desirable (good) and undesirable (bad) outputs because many firms often produce not only desirable outputs but also undesirable outputs as a result of their economic activities. A methodological difficulty of DEA applications is how to combine operational performance on desirable outputs and environmental performance on undesirable outputs in a unified treatment. Although previous DEA environmental studies have utilized mainly radial models and their extensions, this study uses a non-radial DEA model for the output unification because the non-radial model can unify the two types of outputs more easily than the radial models. This study incorporates three types of output unification in DEA environmental assessment. The first unification considers both an increase and a decrease in an input vector along with a decrease in the direction vector of undesirable outputs. This type of unification measures “unified efficiency”. The second unification considers a decrease in an input vector along with a decrease in the vector of undesirable outputs. This type of unification is referred to as “natural disposability” and measures “unified efficiency under natural disposability”. The third unification considers an increase in an input vector but a decrease in the vector of undesirable outputs. This type of unification is referred to as “managerial disposability” and measures “unified efficiency under managerial disposability”. All the unifications increase the vector of desirable outputs. Using the output unification under natural and managerial disposability, this study examines methodological strengths and drawbacks of the proposed non-radial approach. Moreover, using a data set on U.S. coal fired power plants, we compare methodological strengths and drawbacks of radial and non-radial models for DEA environmental assessments. The methodological comparison is important in guiding a large energy issue because policy implications depend upon a methodology(s) used for an empirical study.

Returns to scale and damages to scale under natural and managerial disposability: Strategy, efficiency and competitiveness of petroleum firms

Environmental assessment recently becomes a major policy issue all over the world. This study discusses how to use Data Environment Analysis (DEA) for environmental assessment for planning corporate strategy and international competitiveness. An important feature of DEA environmental assessment is that it classifies outputs into desirable (good) and undesirable (bad) outputs because all private and public entities produce not only desirable outputs but also undesirable outputs as a result of their production activities. This study proposes the two types of output unification for DEA environmental assessment by using a non-radial model. One of the two output unifications is that it considers a decrease in an input vector along with a decrease in the vector of undesirable outputs. This type of unification is referred to as “natural disposability”. The other unification considers an increase in an input vector but a decrease in the vector of undesirable outputs. This type of strategy is referred to as “managerial disposability”. Both unifications increase the vector of desirable outputs. After developing the two concepts on disposability, this study theoretically explores how to measure Returns to Scale (RTS) under natural disposability and Damages to Scale (DTS) under managerial disposability. To document the practicality of the proposed approach, this study applies it to compare the performance of national oil firms with that of international oil companies. This study identifies four important findings on the petroleum industry. First, national oil companies outperform international oil companies in the unified efficiency under natural disposability. Second, international oil companies outperform national oil companies in the unified efficiency under managerial disposability. Third, national oil firms exhibit a mixed result on RTS, while international oil firms exhibit decreasing RTS. Finally, both national and international oil companies exhibit increasing DTS, implying that all oil firms need to decrease their operational sizes for improving their environmental performance on CO2 emission. As an alternative strategy, the result suggests that they need to introduce technology innovation (e.g. clean air technology) into their business operations. The technology based strategy has more practicality than the size reduction in their operations.

Efficiency-based rank assessment for electric power industry: A combined use of Data Envelopment Analysis (DEA) and DEA-Discriminant Analysis (DA)

This study discusses a combined use of DEA (Data Environment Analysis) and DEA–DA (Discriminant Analysis) to determine the efficiency-based rank of energy firms. This type of performance evaluation is important because we often have a difficulty in accessing a large sample on energy firms to derive reliable empirical results. The proposed approach is useful in dealing with such a limited number of energy firms, often found in previous DEA studies on energy industries in the world. The proposed approach uses DEA to classify energy firms into efficient and inefficient groups based upon their efficiency scores. Then, it utilizes DEA–DA to assess their efficiency scores and ranks. In this stage, we can find an adjusted efficiency score for each energy firm. The proposed approach provides us with the following analytical capabilities, all of which cannot be found in a conventional use of DEA in assessing energy firms. First, the proposed DEA approach can avoid zero in all multipliers on efficient energy firms by incorporating SCSC (Strong Complementary Slackness Condition) so that it can handle an occurrence of multiple reference sets and multiple projections. The DEA result classifies all energy firms into efficient and inefficient groups. Second, DEA–DA, applied to the two groups, evaluates all energy firms by an industry-wide evaluation, not depending upon a limited number of efficient energy firms in a reference set, as found in a conventional use of DEA. The analytical capability can reduce the number of efficient energy firms. Third, the proposed approach can provide their efficiency-based ranking scores. Finally, we can conduct a rank sum test based upon their ranking scores to obtain a statistical inference. As an application, this study uses the proposed approach to examine the performance of Japanese electric power industry. We find two economic implications. One of the two implications is that no major change has occurred in the operational performance of Japanese electric power industry because of Japanese sluggish economy from 2005 to 2009. The other implication indicates that there are strategic differences in the operation of Japanese electric power firms after the liberalization.

A combined use of DEA (Data Envelopment Analysis) with Strong Complementary Slackness Condition and DEA–DA (Discriminant Analysis)

This study discusses a combined use of DEA (Data Environment Analysis) with SCSC (Strong Complementary Slackness Condition) and DEA–DA (Discriminant Analysis). Many studies use DEA to evaluate the performance of various organizations in private and public sectors. A conventional use of DEA is not perfect because it still contains zero in many multipliers. This implies that DEA does not fully utilize information on all inputs and outputs. As a result, DEA produces many efficient organizations. To overcome the methodological difficulty, this study proposes a new use of DEA/SCSC and DEA–DA to reduce the number of efficient organizations.

Methodological comparison between two unified (operational and environmental) efficiency measurements for environmental assessment

Environmental assessment recently becomes a very large-scale policy issue among corporate leaders, environmental researchers and individuals who are interested in environmental protection in the world. This study discusses how to apply Data Environment Analysis (DEA) for environmental assessment. DEA has been long utilized to measure operational performance in private and public sectors. However, previous DEA research has documented a limited use of DEA on environmental assessment. A unique feature of DEA-based environmental assessment is that it needs to classify outputs into desirable (good) and undesirable (bad) outputs because private and public entities often produce not only desirable outputs but also undesirable outputs as a result of their production activities. A methodological difficulty associated with the previous DEA-based environmental assessment is how to combine operational performance on desirable outputs and environmental performance on undesirable outputs in a unified treatment. This study proposes two types of unification for DEA-based environmental assessment within a non-radial DEA framework. Then, this study compares the two types of unification from economic and mathematical perspectives of environmental assessment.