Non-radial Approach Research Articles

Incidence and determinants of non-radial vascular approach for coronary angiography among heart transplant recipients

Abstract Background Repeated coronary angiograms may be required among heart transplant (HT) recipients to detect coronary allograft vasculopathy (CAV), exposing to higher risk of non-radial vascular approach over time. Objective To describe the incidence and determinants of non-radial vascular approach in this specific population in a large HT center. Methods Consecutive HT recipients undergoing coronary angiography between October 2020 to November 2022 at our Hospital, the largest French HT center, were included and all previous coronary angiograms performed after heart transplantation were retrospectively reviewed. A radial vascular approach has systematically been the first-line approach for coronary angiography in the last two decades. Coronary angiography is routinely performed one year after heart transplantation and every couple of years thereafter or more frequently in case of CAV progression or clinical indication. Determinants of non-radial vascular approach were assessed using multivariate logistic regression analyses, which included the individual mean number of coronary angiographies per year after heart transplantation to account for disparities in follow-up between the two groups. Results A total of 326 patients were included during the period of interest, with a median number of 4 (1-7) coronary angiographies performed over a median duration of 7.0 (1.8-13.1) years (Table 1). A non-radial approach was used in 108 (33.1%) patients, after a median delay from HT of 3.0 (1.0 - 8.4) years (Figure 1). Independent determinants of non-radial approach were female sex (Odds Ratio [OR] 2.18, 95% confidence interval [CI] 1.06 – 4.50), older age at the time of HT (OR 0.98 95%CI 0.96-0.99), post-transplantation dialysis (OR 7.34, 95%CI 2.41 – 22.30) and the development of type 3 CAV according to the International Society Heart and Lung Transplantation (ISHLT) classification (OR 2.01, 95%CI 1.20 – 3.35. Severe complications related to the vascular approach remained rare. Conclusions Non-radial vascular approach remains frequent among HT recipients. In a center of high HT volume and high radial access volume, non-radial vascular approach is used in one out of three HT recipients with multifactorial reasons.

Airline company's resource reallocation using network centralized data envelopment analysis with slack-based measure

PurposeSince airlines that employ their resources effectively will achieve operating profitability, air route resource allocation is significant for airlines. This study aims to investigate an appropriate model to reallocate resources into each air route of an airline company.Design/methodology/approachThis study proposes a network centralized data envelopment analysis (DEA) models with slack-based measure (SBM). The proposed model not only takes into account the two interconnected stages but also considers the nonradial approach with transfer-in and transfer-out slacks for resource reallocating. Furthermore, the authors modify the objective function to an input-oriented function with SBM, and divide the model into passenger and freight parts, which makes the model more realistic for the characteristic of air routes.FindingsThe empirical analysis using an airline company's internal data provides airline operators with information on how they increase or decrease input resources, which can serve as a practical guideline of resource reallocation. Specifically, the results indicate that the airline company should increase their input resources into long-haul air routes such as KOR-OCN while decreasing their input resources into short-haul air routes such as Korean-Oceania (KOR-OCN), Korean-Chinese (KOR-CHN), Korean-Southeast Asian (KOR-SEA), Korean-Japanese (KOR-JPN).Originality/valueAlthough some papers evaluate air route efficiencies based on the DEA approach, a few existing papers have addressed resource allocation for air routes. This paper is the first to study the resource reallocation for air routes based on the DEA approach, contributing to the literature in expanding the scope of research on resource reallocation.

A new intermediate network data envelopment analysis model for evaluating China's sustainability

The existing studies on network data envelopment analysis (DEA) generally adopt radial or non-radial approaches to capture internal structures of production systems. To our knowledge, however, no study has utilized the intermediate approach to construct network DEA models. To fill the research gap, this study proposes a new intermediate network DEA model, by combining the intermediate approach with network DEA. Our new model has several methodological advantages. In addition, sustainability involves a three-stage system (i.e., economic growth, environmental protection and health promotion). Towards the holistic system, quite limited studies have evaluated the performance. Following this research line, our study proposes a new methodological framework consisting of intermediate network DEA, rank sum test, Gini coefficient and decomposition analysis. By adopting this framework, this study examines multi-dimensional efficiency measures, evaluates technology inequality measures and identifies technology diffusion barriers. Empirically, the current study considers the sustainability system of Chinese provinces from 2009 to 2017. The main findings are as follows. First, China has succeeded in realizing a general improvement in overall efficiency scores. Second, significant differences have been statistically confirmed among three stages. Third, convergent trends have been confirmed across stage efficiency measures. Finally, cross-group Gini coefficient accounts for the largest part in explaining technology inequality, where the stage of environmental protection plays an important role.

Non-radial two-stage network DEA model to estimate returns to scale

PurposeAs returns to scale (RTS) describes the long run connection of the changes of outputs relative to increases in the inputs, the purpose of this study is to answer the following questions: If the proportionate changes exist in the inputs, what is the rate of changes in outputs with respect to the inputs’ variations in the two-stage networks over the long term? How can the authors investigate quantitative RTS in the two-stage networks? In other words, the purpose of this research is to introduce a different approach to estimate the performance, RTS and scale economies (SE) in network structures.Design/methodology/approachThis paper proposes a novel non-radial approach based on data envelopment analysis to analyze the performance and to investigate RTS and SE in two-stage processes.FindingsThe findings show that the range adjusted measure (RAM)/RTS approach can identify reference sets for overall systems and each stage. In addition, the models presented in this paper can classify decision-making units and determine the increasing/decreasing trends of RTS.Originality/valueThe majority of previous RTS studies have been examined in black-box structures and have been discussed in a radial framework. Therefore, in this study, RTS and SE in the two-stage networks are dealt with using an extended RAM approach. Actually, the efficiency and RTS for each stage and the overall model are calculated using the proposed technique.

A non-radial approach to improve the interval cost efficiency score in DEA

A non-radial approach to improve the interval cost efficiency score in DEA

Incorporating financial ratios in DEA - an application to goat farming data. A critical examination

Goat farming in Greece, is practiced in disadvantaged regions that cannot be otherwise valorised. For these areas, goat farming is one of the main economics activities. Despite the significance of the sector, goat farming shows low efficiency and competitiveness and this is due to the high production costs. Most farms in Greece operate under increasing scale. The goal of this paper is to present how corporate performance can be measured - using data envelopment analysis (DEA) method - with financial indexes. DEA is a useful technique that measures the efficiency. However, the lack of the ability to attend to ratio measures is an ongoing challenge in DEA. In this paper there is a combination of DEA and financial ratios and that has many advantages. It is implemented by a specific procedure that is called directional distance function, and the main advantage of this method, belonging to the class of non-radial approach, is the flexibility.

Incorporating financial ratios in DEA - an application to goat farming data. A critical examination

Goat farming in Greece, is practiced in disadvantaged regions that cannot be otherwise valorised. For these areas, goat farming is one of the main economics activities. Despite the significance of the sector, goat farming shows low efficiency and competitiveness and this is due to the high production costs. Most farms in Greece operate under increasing scale. The goal of this paper is to present how corporate performance can be measured - using data envelopment analysis (DEA) method - with financial indexes. DEA is a useful technique that measures the efficiency. However, the lack of the ability to attend to ratio measures is an ongoing challenge in DEA. In this paper there is a combination of DEA and financial ratios and that has many advantages. It is implemented by a specific procedure that is called directional distance function, and the main advantage of this method, belonging to the class of non-radial approach, is the flexibility.

A non-radial approach to improve the interval cost efficiency score in DEA

This paper suggests an approach for improving the cost efficiency score of inefficient decision making units (DMUs) with interval data. Corresponding to each inefficient DMU, we consider an interval ideal input vector and then develop two non-radial models to determine a point in the production possibility set that can produce the given interval output vector with the minimum possible cost and is closest point to the corresponding ideal point. By replacing the observed interval input vector with the interval input vector of the obtained point, one can improve the lower bound of the interval cost efficiency score as much as possible while the upper bound can achieve one. A numerical example also will be designed to demonstrate the applicability of the proposed approach.

An envelopment-based approach to measuring regional social progress

Today, more than ever, it is becoming evident that Gross Domestic Product (GDP) alone is not sufficient in guiding national development strategies. In this sense, measuring the social progress of a country can provide an additional lens on national performance, which would eventually help policymakers to not only gain an advanced understanding of the ways that would unleash greater long-term economic success, but also be able to propose strategies that would create the conditions for all individuals in a society to reach their full potential, enhancing and sustaining the quality of their lives. In this paper, we propose a method to measure social progress at the sub-national level, with an application to the Peruvian regions. As such, this paper builds a unified envelopment-based model for integrating a two-stage process of the index generation. We compare and contrast the radial and non-radial envelopment approaches; it is evident from the model that the non-radial approach provides better insights when compared to the radial approach.

DEA Non-Radial Approach for Resource Allocation and Energy Usage to Enhance Corporate Sustainability in Japanese Manufacturing Industries

This article discusses how to enhance corporate sustainability by simultaneously measuring operational and environment achievements. In past decades, most companies have made steady efforts to enhance their sustainability levels. However, they still have strategic space for improving sustainability. This research proposes a new use of environmental measurement by data envelopment analysis. We apply the approach to Japanese industrial sectors and obtain five implications. First, they maintain a high level of unified efficiency on resource allocation and energy usage under natural disposability (priority: operation). Second, the efficiency under managerial one (priority: environment) is generally lower than that of natural disposability. Third, among the industries with high operational achievement, only the pharmaceutical product industry presents high attainment on environmental protection. Fourth, the pulp and paper industry as well as the textile product industry have a potential for efficiency improvement by investing in green technology. Finally, desirable congestion indicates a potential of performance improvement by investing in green technology. Those results imply that the current business situation is different from the previous image on Japanese industries, often referred to as “Japan Inc.”, where all firms used to operate like a single entity under the governmental regulation.

Measuring unified efficiency of Chinese fossil fuel power plants: Intermediate approach combined with group heterogeneity and window analysis

As a newly-proposed method, intermediate approach has several unique features, relative to conventional radial and non-radial approaches. This study contributes to the DEA literature by combining intermediate approach with group heterogeneity in a time horizon. This extended methodology has two important advantages, since it can separate inefficiency related to different production frontiers originated from heterogeneity issue and provide steady results of time effects across periods. Empirically, this method is used to examine unified efficiency of Chinese fossil fuel power plants at provincial levels from 2005 to 2015. All provinces are classified into two regional groups. Our main findings are as follows. First, there exists significant group heterogeneity between coastal and inland provinces, where coastal provinces outperform inland provinces. Second, there are considerable differences in unified efficiency measures across provinces. For most observations, best-practice gap ratio is the most important driving factor. Furthermore, the relative importance of three decomposed indicators varies sharply across provinces. Finally, the concept of managerial disposability should attract sufficient attention, when designing environmental policies. Thus, there should be more combined contributions from eco-technology advancements along with managerial efficiency improvements by corporate leaders and policy makers. This can a new direction for China's environmental policy.

DEA environmental assessment on US petroleum industry: Non-radial approach with translation invariance in time horizon

This study empirically assesses the performance of the petroleum industry, focusing upon independent companies, in the United States (US). For the empirical study, we use the Data Envelopment Analysis (DEA) that has been widely used for environmental assessment and performance measurement. The conventional use of DEA requests that all observations in the data set should be positive, prohibiting an occurrence of zero and/or negative values. The requirement of non-negative value is inconsistent with the reality of US petroleum industry, because many oil firms recently experience negative shocks in financial performance. To overcome the obstacle, this study discusses the property of “translation invariance” under undesirable congestion (e.g., capacity limit in the transportation pipeline network) and desirable congestion (e.g., green technology innovation) based on the non-radial models. The property implies that the unified efficiency measure should be not influenced even if production factors are shifted toward the same direction by adding or subtracting a specific real number. The property makes it possible that we can evaluate the performance of firms, whose production factors contain zero and/or negative values. This study is empirically concerned with practical implications of translation invariance from energy and environmental perspectives. In addition, this study examines the proposed environmental assessment in a time horizon. For the purpose, this study uses “window analysis” to examine an efficiency change along with a time shift. Our empirical investigation finds the following three implications. First, under the natural disposability, the oil firms' efficiency growth rates have become less than unity, implying the industry-wide difficulty or inability to cut back their drilling and production operations. Second, all firms have been under regulatory and stakeholder pressures on air pollution. Therefore, the efficiency growth rates under managerial disposability have not exhibited a major change during the observed annual periods. Finally, such implications are statistically reconfirmed by regression analysis that examines how the change of energy price influences unified efficiencies under natural and managerial disposability. An exception can be found in the natural disposability where energy prices influence their efficiency growths. Thus, an increase in energy prices is important in maintaining a high level of efficiency growths in the US petroleum industry.

Social sustainability measured by intermediate approach for DEA environmental assessment: Chinese regional planning for economic development and pollution prevention

This study examines the level of simultaneous achievement on economic prosperity and environmental protection, so measuring the level of sustainability by a newly proposed intermediate approach. Conventionally, DEA (Data Envelopment Analysis) for performance evaluation was used to assess various economic activities of organizations that utilized inputs (e.g., the number of employees) to yield desirable outputs (e.g., the number of products). The methodology was usually classified into radial or non-radial category. In an effort of extending it to environmental assessment, DEA needs to incorporate undesirable outputs (e.g., the amount of CO2) into the computational framework. This type of assessment is referred to as “DEA environmental assessment”. The proposed intermediate approach develops a new type of DEA environmental assessment by combining the analytical features of radial approach with those of non-radial approach. The new approach measures the level of unified inefficiency on each production factor and determines the level of total unified inefficiency from the average of the sum of these inefficiency scores. A rank sum test and a mean test are additionally incorporated into the proposed intermediate approach. Such a combination enhances the statistical capability. As an application, this study examines the level of sustainability related to 30 provinces in China from 2003 to 2014. The application finds four policy implications. First, it is important for China to allocate its resources to western provinces at a level that it has used for coastal developments. Second, the government continues to reinforce the policy making effort on environmental protection by paying attention to central and southern regions. The Chinese industries need to transfer toward “green” energy. The transfer should be efficiently executed for their future developments. Third, the government has focused on the sustainability development in urban provinces and then has gradually shifted the policy influence toward rural areas. Finally, the policy implementation needs a time lag until it becomes effective. The time lag on economic policy is longer than that of environmental policy. The economic policy has historically produced a regional imbalance, often leading to educational and income imbalances, among Chinese provinces.

An integrated model for slack-based measure of super-efficiency in additive DEA

As a non-radial approach, a super-efficiency model, Super SBM, was proposed by Tone [15] to rank efficient DMUs. Du et al. [7] extends the Super SBM model to the additive (slacks-based) DEA model. To obtain the super-efficiencies of the DMUs, one needs to identify the efficient DMUs first and then apply the additive super-efficiency model to those efficient DMUs. In this paper, we propose an integrated model so that the efficiencies of the inefficient DMUs and the super-efficiencies of the efficient DMUs can be obtained by a single model. The efficiency scores obtained by our integrated model are the same as those obtained by Du et al. [7] and the additive DEA model.

Environmental assessment on coal-fired power plants in U.S. north-east region by DEA non-radial measurement

This study discusses a new use of DEA (Data Envelopment Analysis) environmental assessment to measure unified (operational and environmental) and scale efficiencies among inputs, desirable and undesirable outputs. In particular, the measurement of scale efficiency is discussed by two non-radial models. That is a new methodological contribution. To discuss these efficiency measures, this study first examines a concept of disposability from the perspective of corporate strategies to adapt a regulation change on undesirable outputs. The concept is separated into natural and managerial disposability. After discussing how to measure the degree of scale efficiency within the non-radial approach, this study applies the proposed DEA environmental assessment to measure the performance of coal-fired power plants in the U.S. north-east region. The region has been long producing a large amount of coal from the Appalachian Mountains. The coal mining industry has supported U.S. energy utility and other industries. Because of the long history, the quality of coal became worse and the coal-fired power plants have been producing a large amount of undesirable gases. This study has statistically confirmed that there is a significant difference between the two types (BIT: bituminous coal and SUB: subbituminous coal) of coal-fired power plants in terms of their unified efficiency measures, including their scale efficiencies, under the concept of managerial disposability (the first priority: environment performance and the second priority: operational performance). In contrast, under the natural disposability (the first priority: operational performance and the second priority: environmental performance), this study cannot find such a statistical significance between them. The fact, in which BIT outperforms SUB in terms of their unified and scale efficiencies, suggests the policy implication that these power plants need to shift their coal combustions from SUB to BIT in the United States. Besides the empirical finding, this study cannot confirm the other hypothesis on whether coal-fired power plants with small operation (less than 50% in plant capacity factor) outperform ones with large operation (more than 50% in plant capacity factor), and vice versa, in terms of their unified and scale efficiency measures under natural and managerial disposability. An exception is found in environmental performance under variable returns to scale. The rationale is because their plant operations are frequently monitored by regulatory agencies. As a consequence, this study cannot find such a statistical difference between them on operational performance. This result implies that the regulation on coal-fired power plants has been effective on their unified performance but large power plants may have a potential to improve their environmental performance.

Radial and non-radial approaches for environmental assessment by Data Envelopment Analysis: Corporate sustainability and effective investment for technology innovation

Environmental assessment and protection are important concerns in modern business. Consumers are interested in corporate effort and investment for environmental protection. It can be easily imagined that they avoid purchasing products from dirty-imaged companies even if their prices are much less than the ones produced by green-imaged companies. A green image is recently a very important concern for corporate survivability in a competitive global market. By extending previous works on environment assessment and corporate sustainability, where companies need to consider both economic prosperity and pollution prevention in their operations, this study discusses a new use of Data Envelopment Analysis (DEA) for environmental assessment by utilizing its radial and non-radial measurements. The proposed radial and non-radial approaches may guide corporate leaders, managers and policy makers by providing not only quantitative assessment on their efforts for environmental protection but also information regarding how to invest for technology innovation on abatement of undesirable outputs. The empirical investigation identifies that the green investment in U.S. energy industry is useful for improving its unified (operational and environmental) performance if operational performance is measured by ROA (Return on Assets) and an amount of CO2 emission reduction because the industry is the largest emitter among seven industry sectors examined in this study. The green investment makes it possible that firms can increase their net incomes by a good corporate image. However, if the financial measure is replaced by a corporate value (i.e., Tobin's q ratio, mainly measured by stock price), the energy industry does not exhibit the best investment opportunity because the effect of green investment is limited on enhancing its corporate value. The energy industry is a very large process industry so that the green investment does not immediately increase its corporate value as found in the other industrial sectors such as information technology industry.

Returns to scale and damages to scale on U.S. fossil fuel power plants: Radial and non-radial approaches for DEA environmental assessment

This study proposes a new use of Data Envelopment Analysis (DEA) for environmental assessment, paying attention to a methodological bias (i.e., different methods produce different results). DEA is analytically classified into radial and non-radial approaches. The radial approach determines the level of unified (operational and environmental) efficiency by measuring an inefficiency score. The score indicates the distance of a projection from an observed performance to an efficiency frontier. In contrast, the non-radial approach determines the level of unified efficiency by measuring a total amount of slacks because each slack indicates inefficiency. To avoid the methodological bias, this study considers the use of radial and non-radial approaches. In this study, we consider a production process where all organizations produce not only desirable (good) but also undesirable (bad) outputs as a result of their business operations. To unify the two types of outputs, this study discusses the concept of disposability, which is separated into natural and managerial disposability. The natural disposability indicates negative adaptation to a regulation change on undesirable outputs. In contrast, the managerial disposability indicates corporate strategy by which a firm considers the regulation change as a new business opportunity. A firm attempts to improve its unified efficiency by utilizing new environmental technology and/or new management. This type of strategy indicates positive adaptation to the regulation change. Under the two disposability concepts, this study discusses how to measure RTS (Returns to Scale) under natural disposability and DTS (Damages to Scale: corresponding to RTS on undesirable outputs) under managerial disposability. The two scale measures are analytically discussed by the proposed radial and non-radial approaches with SCSCs or without SCSCs, where SCSCs indicate strong complementary slackness conditions. An illustrative example on U.S. fossil fuel power plants indicates a policy implication that they need to introduce new technology for environmental protection. This study also discusses a necessity of examining a methodological bias in energy studies. Empirical findings identified in this study document the practicality of the proposed approaches to measure RTS/DTS.

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.

Social efficiency benchmarking of transport infrastructure with non-radial approach: focusing on airports

The aim of this paper is to show current position of domestic airports and provide an improvement scheme through the comparative analysis of efficiency and social efficiency. We used SBM (Slack Based Measure) for efficiency and undesirable output model that is extended from SBM for social efficiency. In addition, window analysis is used for analyzing the trend of the values. For the scope of this study, we analyzed fourteen airports in Korea from 2004 to 2009. In the models, we considered the length of runway, the number of employees and terminal area as input factors, and the number of passengers, the amount of cargo and the number of flights as desirable outputs and directly controllable CO2 emissions from airports as undesirable output. The results show that all of the efficiencies are higher than the social efficiencies and both of them are decreasing by years. To improve social efficiency in 2009, the average amounts of reduced CO2 emissions which account for 48.3% of the total emissions are required.

Social efficiency benchmarking of transport infrastructure with non-radial approach: focusing on airports

The aim of this paper is to show current position of domestic airports and provide an improvement scheme through the comparative analysis of efficiency and social efficiency. We used SBM (Slack Based Measure) for efficiency and undesirable output model that is extended from SBM for social efficiency. In addition, window analysis is used for analyzing the trend of the values. For the scope of this study, we analyzed fourteen airports in Korea from 2004 to 2009. In the models, we considered the length of runway, the number of employees and terminal area as input factors, and the number of passengers, the amount of cargo and the number of flights as desirable outputs and directly controllable CO2 emissions from airports as undesirable output. The results show that all of the efficiencies are higher than the social efficiencies and both of them are decreasing by years. To improve social efficiency in 2009, the average amounts of reduced CO2 emissions which account for 48.3% of the total emissions are required.