Ranking Of Units Research Articles

RANKING COMPANIES IN INDIAN AVIATION SECTOR BASED ON EFFICIENCY: AN ANDERSON PETERSON SUPER-EFFICIENCY MODEL

The Indian aviation industry, an integral part of Indian transport network, plays a crucial role in connecting people, economies, and cultures. Indian aviation industry is highly competitive and its operational efficiency is of paramount importance to sustain profitability, to enhance customer satisfaction, and to maintain a competitive edge of the industry. The primary objective of the current study is to explore the concept of super efficiency on six major airline companies operating in India covering both the full service and low-cost carriers using secondary data drawn from various sources from the financial year 2004-05 to 2018-19. Super efficiency is an advanced DEA tool that extends beyond conventional efficiency measures. It provided the opportunity to conduct a more refined analysis of airline efficiency. Furthermore, the super efficiency score derived from the analysis is utilised for the ranking of decision-making units (DMUs) that are efficient in conventional terms. With a view to achieving these objectives, the current study employs a robust methodological approach, utilizing a dataset comprising various performance indicators from select airline companies. The research finds that Go Air is the most efficient airline in analysing airline efficiency through the lens of super efficiency. However, Air India is ranked first based on super efficiency scores of the aviation companies in different years

A novel ranking method in data envelopment analysis: a real case on Chinese banking industry

Purpose This study aims to address the lack of discrimination between fully efficient decision-making units in nonparametric efficiency analysis models by introducing a new ranking technique that incorporates contextual variables. Design/methodology/approach The proposed method combines Data Envelopment Analysis (DEA) and Ordinary Least Squares (OLS). First, DEA evaluates the partial efficiency of each unit, considering all inputs and only one output. Next, OLS removes the influence of contextual variables on the partial efficiencies. Finally, a ranking criterion based on modified partial efficiencies is formulated. The method is applied to data from 100 Chinese banks, including state-owned, commercial and industrial institutions, for the year 2020. Findings The ranking results show that the top six positions are assigned to highly esteemed banks in China, demonstrating strong alignment with real-world performance. The method provides a comprehensive ranking of all units, including nonextreme efficient ones, without excluding any. It resolves infeasibility issues that arise during the ranking of efficient units and ensures uniqueness in efficiency scores, leading to a more reliable and robust ranking process. Contextual variables exerted a greater influence on the first partial efficiency compared to the second. Notably, Total Capital Adequacy (TCA) significantly impact bank efficiency. Originality/value This study introduces a novel ranking method that effectively integrates contextual variables into DEA-based efficiency analysis, addressing limitations of existing methods. The practical application to Chinese banks demonstrates its utility and relevance.

СLIMATIC AND PHYTOCENOTIC EVENTS OF THE LATE PLEISTOCENE (MIS 5-MIS 3) AT THE SOUTHEASTERN COAST OF THE GULF OF FINLAND

The paper analyses a debatable issue concerning the ranking of climatic-stratigraphic units within two marine isotope stages (MIS) - MIS 5 and MIS 4. Palynological records from the Mikulino interglacial sections of the northwestern Russian Plain which are most critical for correlations are reviewed. A representative series of numerical dates obtained by the IR-OSL method, and detailed palynological records enabled a detailed climatic-chronostratigraphic division of the Late Pleistocene sequence of the Voka reference section on the southeastern coast of the Gulf of Finland. The representative palynological spectra provide strong evidence of a warm interval of interglacial rank in the latter half of MIS 5, corresponding to the standard M6, M7, and M8 Mikulino palynozones. Additionally, they highlight a period of significant cooling during MIS 4, characterized by the dominance of periglacial vegetation formations in the study area. This challenges the viewpoint of the extensive Kalinin glaciation during that time, believed to have spread many hundreds of kilometers south of the Gulf of Finland. Data for MIS 3 reveal a two-fold alternation of interstadial and stadial (periglacial) climate intervals during the period between 39 ka and 33 ka.For the first time, detailed reconstructions and datings of climate-phytocenotic successions of paleoclimatic events approximately between 100 ka and 30 ka have been provided for the territory of the East European Plain (and Northern Eurasia as a whole). These events correspond to the latter half of MIS 5, MIS 4, and an interval between 39 ka and 33 ka during MIS 3.

Application of tropical optimization for solving multicriteria problems of pairwise comparisons using log-Chebyshev approximation

We consider a decision-making problem to find absolute ratings of alternatives that are compared in pairs under multiple criteria, subject to constraints in the form of two-sided bounds on ratios between the ratings. Given matrices of pairwise comparisons made according to the criteria, the problem is formulated as the log-Chebyshev approximation of these matrices by a common consistent matrix (a symmetrically reciprocal matrix of unit rank) to minimize the approximation errors for all matrices simultaneously. We rearrange the approximation problem as a constrained multiobjective optimization problem of finding a vector that determines the approximating consistent matrix. The problem is then represented in the framework of tropical algebra, which deals with the theory and applications of idempotent semirings and provides a formal basis for fuzzy and interval arithmetic. We apply methods and results of tropical optimization to develop a new approach for handling the multiobjective optimization problem according to various principles of optimality. New complete solutions in the sense of the max-ordering, lexicographic ordering and lexicographic max-ordering optimality are obtained, which are given in a compact vector form ready for formal analysis and efficient computation. We present numerical examples of solving multicriteria problems of rating four alternatives from pairwise comparisons to illustrate the technique and compare it with others.

DEA cross-efficiency models with prospect theory and distance entropy: An empirical study on high-tech industries

Cross-efficiency evaluation with the data envelopment analysis (DEA) model is an effective way to assess performance and provide a complete ranking of decision-making units. However, it is generally assumed that decision makers are perfectly rational in the cross-efficiency model, which fails to consider the subjective preferences of decision-makers. Moreover, the arithmetic average method is usually adopted to aggregate efficiency scores in traditional cross-efficiency methods, which underestimates the importance of self-evaluation. To address these issues, we extend cross-efficiency with the DEA model by incorporating prospect theory and the distance entropy function. First, we calculate the prospect values of decision-making units to describe the non-rational subjective preferences under the risk of decision-makers. Second, based on prospect cross-efficiency, a new distance entropy function is developed to aggregate the ultimate prospect cross-efficiency values. More specifically, some traditional cross-efficiency evaluation models can be considered special cases of prospect cross-efficiency models with appropriate adjustments to the parameters. Finally, an empirical example is used to evaluate the prospect cross-efficiency results with the high-tech industries of 29 provinces in China to illustrate the applicability and effectiveness of the proposed model in ranking observations.

Alanian Military Units in Military-Administrative Structure of the Mongol Empir

The purpose of the paper is to study the question of the rank of the Alanian military units in the Mongolian imperial military-administrative order. The relevance of the study is determined by the absence in the scientific tradition of researches on this issue, while it contains studies of questions about the place of the Alans in the military-administrative system of the Yuan Empire and about their service to the Mongol ulus rulers. The result of the study was the conclusion that after the Western campaign, some representatives of the Alanian power elite became vassals of the “Golden Lineage” of Genghis Khan, that ruled the Mongol Empire, the actual unity of which remained until 1271. Some of the retinues of the Alanian rulers were left in Alanya, while the other part of them, together with some of the rulers, was taken to serve in the guards of Genghiskhanid Mongke and went with him to Central Mongolia. After the elevation of Möngke on the Mongol throne in 1251, these Alans, like the Alans that went to Mongolia by recruitment in 1254, served in the retinue of the Mongol emperor and, probably, guarded the Mongol capital Karakorum. The study used methods of comparative historical analysis, inductive and deductive methods, system-chronological and retrospective-analytical methods, as well as methods of scientific translation of texts of medieval Chinese chronicles.

STATUS AND DIRECTIONS OF THE DEVELOPMENT OF NATURAL PROTECTED AREAS OF THE ODESSA REGION IN THE CONTEXT OF THE "BLUE ECONOMY"

STATUS AND DIRECTIONS OF THE DEVELOPMENT OF NATURAL PROTECTED AREAS OF THE ODESSA REGION IN THE CONTEXT OF THE "BLUE ECONOMY"

Risk Assessment and Reliability Analysis of Oil Pump Unit Based on D-S Evidence Theory

Oil pumps are crucial equipment in pipeline transportation, and their safe and reliable operation is essential for the smooth and efficient operation of the oil station and associated pipelines. The failure of oil pumps can result in significant consequences, making it crucial to evaluate their safety for effective maintenance and reliable system prediction. Failure mode, effects, and criticality analysis (FMECA) is a quantitative fault analysis technique that assigns priority to fault modes using the risk priority number (RPN). However, the RPN may not accurately express uncertainty judgments of risk factors given by multiple experts. To address this limitation, this paper proposes a novel FMECA method based on the D-S evidence theory. The method involves using interval form to obtain risk factor evaluations from experts and data combination to obtain a multi-value representation of the RPN for each fault mode. The prioritization of fault modes is optimized using confidence and fidelity distribution to eliminate multiple modes of the same level. Finally, the normalization method is used to determine the risk degree ranking of oil pump units. Overall, the proposed method is an effective and practical approach for the risk evaluation and reliability analysis of oil pump units.

Data-driven derivative-free trust-region model-based method for resource allocation problems

Allocating a limited available resource between a set of units is a problem that arises in several application areas. We propose an online derivative-free trust-region model-based method to tackle a fairly general version of the resource allocation problem where units may be turned on or off. The units are considered as black boxes which may only be evaluated given that all the other units are evaluated simultaneously, and no gradient information is available. This method was inspired by an industrial problem and emphasis is put on both providing feasible points during the optimization and on not incurring additional increase in cost while searching for the optimum. The latter cannot be guaranteed, but the algorithm allows for automatic or manual ranking of the different units to attempt to reduce negative impact on the cost. The algorithm was applied to a case study from the petroleum industry where fast convergence was observed.

An inexact bi-level multi-objective modeling approach for managing agricultural water-food-carbon-land-ecology-nutrition nexus in an arid area

Multiple subsystems such as water, food, land, carbon, ecology, and nutrition are closely intertwined, and the resulting complexity and uncertainty pose challenges to water resource management. This study proposes an optimization framework from a novel water-food-carbon-land-ecology-nutrition (WONDER) nexus perspective for the integrated management of agricultural and ecological water resources. Firstly, the irrigation priority ranking of decision-making units (DMU) is obtained based on the remote sensing indices from the Google Earth Engine (GEE) platform. Secondly, the ecological satisfaction degree, which aggregates carbon sink satisfaction degree and ecological water demand satisfaction degree, is proposed to characterize the degree of achieving the pre-given ecological objectives. Then, the above two indicators (i.e., the irrigation priority ranking and the ecological satisfaction degree) are integrated with a fuzzy-interval credibility-constrained bi-level multi-objective programming model to realize: (1) reconciling conflicts in food nutrition, food security, economic development, and ecological conservation; (2) making trade-offs among the positions and preferences of different decision-makers; (3) dealing with the dual uncertainties of fuzzy-interval parameters; (4) obtaining optimal agricultural and ecological water allocation schemes. The applicability of the model is verified by taking Hongyashan Irrigation District of Minqin County as an example. The results show that: (1) the irrigation priority ranking for the DMUs is: DMU 10 > DMU 9 > DMU 4 > DMU 5 > DMU 1 > DMU 11 > DMU 6 > DMU 8 > DMU 7 > DMU 2 > DMU 3; (2) the ratio of agricultural to ecological water allocation in the irrigation district is about 3:1, which is consistent with the water use characteristics of this area; (3) the total water allocation during the whole growth period for different crops is mainly determined by planting area, and the ranking of the water allocation is: sunflower > maize > wheat > seed melon. Moreover, compared with the single-level models, the inexact bi-level multi-objective model can well coordinate the upper and lower decision-makers and the multiple decision objectives under the WONDER nexus. Therefore, the proposed framework can provide the scientific basis for balancing agricultural and ecological water management and conflicting objectives in similar irrigation districts through involving multiple subsystems and perspectives.

Ranking Spatial Units with Structural Property and Traffic Distributions for Uncovering Spatial Interaction Patterns in a City

Travel activity data mining is critical to numerous urban applications such as transportation and location‐based services. This article studies the spatial units ranking algorithm for uncovering spatial interaction patterns based on the flow properties of people's travel trajectories. For example, using a taxi origin–destination flow database, a user may want to rank the origin and destination with respect to their functional importance within the urban activity space. In the literature, such an importance concept is usually specified via the frequency function of trip flows. Considering the case that the less frequently visited place in reality may still be an important origin or an important destination, we propose a different method for the ranking of spatial units by introducing the structural property of trip network. The proposed method is inspired from the mutual reinforcing relationship between the trip origins and destinations: important destinations attract travel flows from important origins and at the same time important origins have many flows toward important destinations. Our experimental results show that the proposed method is effective in uncovering spatial interaction patterns of urban activities.

A robust DEA model in the presence of uncertain integer-valued parameters

PurposeUncertainty in data, whether in real-valued or integer-valued data, may result in infeasible optimal solutions or unreliable efficiency scores and ranking of decision-making units. To handle the uncertainty in integer-valued factors in data envelopment analysis (DEA) models, this study aims to propose a robust DEA model which is applicable in the presence of such factors.Design/methodology/approachThis research focuses on the application of fuzzy interpretation of efficiency to a mixed-integer DEA (MIDEA) model. The robust optimization approach is used to address the uncertain integer-valued parameters in the proposed MIDEA model.FindingsIn this study, the authors proposed an MIDEA model without any equality constraint to avoid the arise problem by such constraints in the construction of the robust counterpart of the conventional MIDEA models. We have studied the characteristics and conditions for constructing the uncertainty set with uncertain integer-valued parameters and a robust MIDEA model is proposed under a combined box-polyhedral uncertainty set. The applicability of the developed models is shown in a case study of Malaysian public universities.Originality/valueThis study develops an MIDEA model equivalent to the conventional MIDEA model excluding any equality constraint which is crucial in robust approach to avoid restricted feasible region or infeasible solutions. This study proposes a robust DEA approach which is applicable in cases with uncertain integer-valued parameters, unlike previous studies in robust DEA field where uncertain parameters are generally assumed to be only real-valued.

An ICE aggregation method based on optimal rally points in fuzzy environment

In order to avoid the hesitation of choosing between aggressive and benevolent strategies, we propose two cross-efficiency models to get interval cross-efficiency (ICE) from the relatively neutral angle in fuzzy environment, and then propose a novel aggregation method for ICE to solve the full ranking of Decision-Making Units (DMUs). Firstly, regard the expected value of fuzzy data as the input and output of Data Envelopment Analysis (DEA) method based on fuzzy set theory. Secondly, construct the cross-efficiency models based on the fuzzy expected values from the relatively neutral angle, and generate the lower and upper bounds of ICE for all DMUs, which determines the interval cross-efficiency matrix (ICEM). Thirdly, project all ICE onto the plane as points, then seek the optimal rally point for each DMU based on ICEM as the comprehensive ICE. Fourthly, rank the comprehensive ICE to obtain the complete ranking of DMUs by using the optimal number sorting method. Finally, the proposed model is applied to the evaluation of manufacturing enterprises, and the results are compared with different models to prove its effectiveness.

Hybrid Fully Connected Tensorized Compression Network for Hyperspectral Image Classification

Deep learning models, such as convolutional neural networks (CNNs), have made significant progress in hyperspectral image (HSI) classification. However, these models require a large number of parameters, which occupy a lot of storage space and suffer from overfitting, thus resulting in performance loss. To solve the above problems, in this article, we propose a new compression network [namely, a Hybrid Fully Connected Tensorized Compression Network (HybridFCTCN)] by considering the high dimensionality of HSI data. First, using the low-rank fully connected tensor network decomposition (FCTND), three novel units, i.e., FCTN-FC, FCTNConv2D, and FCTNConv3D, are designed to compress the weight tensor of standard fully connected (FC) layer and kernel tensor of convolutional layer, reducing their parameters. In the novel units, the intrinsic correlation of the decomposed factors is adequately exploited by the FC structures, which enhances their feature extraction and classification abilities. Then, benefiting from the hybrid network backbone composed of the FCTNConv3D and FCTNConv2D units, HybridFCTCN can extract more discriminative features with fewer parameters, while it has great generalization capability and robustness, enabling better HSI classification. Finally, the rank of above-designed units is defined, and its determination is discussed to facilitate the application of the proposed model. Extensive experiments on three widely used HSI datasets reveal that the proposed model achieves state-of-the-art classification performance for different training sample sizes with a very small number of parameters.

Ranking of Production Units Using SWOT, AHP and RAPS Techniques

Strategic management is the process by which an organization formulates its objectives and manages to achieve them. By application of AHP (Analytical Hierarchy Process), RAPS (Ranking Alternatives by Perimeter Similarity) and SWOT (Strengths, Weaknesses, Opportunities and Threats) analysis, the growth of the organization can be achieved smoothly. By implementing correct methodologies for the analysis, it is possible to ensure that an organization will sustain forever.

Measuring technological innovation efficiency using interval type-2 fuzzy super-efficiency slack-based measure approach

As an important leading industry in China’s economy, the high-tech industry needs to systematically analyze technological innovation activities, thereby measuring the technological innovation efficiency and further improving sustainable development. The high-tech industry in different provinces benefits from individual policies due to their geographical locations. However, since the intensity of policy implementation in the technological innovation activities of the provincial high-tech industry is qualitative information, which is difficult to be expressed by quantitative data and rarely considered in the efficiency assessment. Therefore, this study adopts interval type-2 fuzzy sets to characterize the uncertain qualitative information and constructs an interval type-2 fuzzy evaluation method to measure the technological innovation efficiency of China’s high-tech industry. More specifically, considering the handling of undesirable outputs and the ranking of multiple efficient decision-making units, the super-efficiency slack-based measure (SBM)-Data envelopment analysis (DEA) method has been selected as the basic evaluation model. Then, the super-efficiency SBM-DEA model has been extended into an interval type-2 evaluation approach by considering the uncertain variables. Moreover, the α-cuts and best-and-worst methods are introduced to conduct the decomposition of the proposed evaluation model and aggregate the ultimate efficiency. Finally, a comparative analysis of technological innovation efficiency in the regional high-tech industry has been performed to validate the applicability of the proposed model.

A Method for Evaluating the Green Economic Efficiency of Resource-Based Cities Based on Neural Network Improved DEA Model.

In this study, we use BP neural network to improve the DEA model to conduct in-depth research and analysis on the method of green economic efficiency evaluation of resource-based cities. The traditional DEA cannot make ranking and analysis of effective units, which affects the accuracy of empirical analysis. Accordingly, the BP-DEA model is introduced to further conduct a comparative eco-efficiency analysis of relatively effective provinces. In this study, the optimal inputs and outputs are calculated by DEA, and further, the BP neural network is used to fit the functional relationship between the optimal inputs and outputs, and by adding variables, the trained neural network can be used for the prediction of the optimal outputs. In this study, the BP-DEA model is used to empirically investigate the temporal evolution trend, spatial differences, and efficiency differences in eco-efficiency. Meanwhile, breaking through the limitation that DEA can only calculate regional efficiency values, this study combines the Malmquist index to compare and decompose the eco-efficiency of different provinces to analyze the sources of total factor productivity changes. The results show that the method can clarify the gap between the actual operation of each indicator and the reference point; it can identify how much room for improvement still needs to be made for each indicator, and it can also determine whether each city should be rewarded or penalized and its specific amount. Finally, based on the evaluation of eco-efficiency and the main constraints, corresponding policy recommendations are proposed. Finally, based on the evaluation results of the BP-DEA method, this study analyzes the overall efficiency improvement of cities in the two study areas in three dimensions: urbanization construction, ecology, and economic development put forward seven types of urban efficiency improvement and propose targeted urban development suggestions according to regional characteristics.

Русские эмигранты в Китае в 1920–1930-е гг.: две гражданские войны на одном жизненном пути

Introduction. The purpose of this study is to present a picture of the life path of Russians (military, cossacks) who witnessed and participated in two civil wars: in Russia and in China. This topic is relevant, since its research allows us to analyze the ways of adaptation of people who have experienced severe forms of transformation in various spheres of life of the two states. Methods and materials. The source base of the study is represented by narrative sources (personal diaries of Russian emigrants A.P. Budberg, G.P. Larin, E.N. Pastukhin, A.A. Tikhobrazova, I.I. Shtina) and periodicals published in Russian by Russian emigrants in China in the 1920 (newspapers “Molva”, “Zarya”, “Russian Voice”, “Gun-Bao”). To present a multifaceted picture of the life of Russian emigrants in China, the following methods were used: dialectical, systemic, analytical-synthetic, historical-comparative, historicalanthropological. Analysis. This study examines the unique history of various categories of emigrants who survived the collapse of spiritual values, ideology, political and economic systems, and the breakdown of the social structure during the civil wars. Against the background of political games, battles, the formation and destruction of military alliances, the story of former Russian military and civilians unfolds, who, in search of earnings and / or for ideological reasons, fought in the ranks of the military units of the Chinese militarists in the 1920–1930. The presented study reflects the struggle between Soviet and anti-Soviet ideology in the Far East, in China: the participation of Russians in the civil war in China, condemnation of Soviet policy on the pages of personal diaries and Russian-language newspapers published in China, support by some public organizations of fascist ideology and the occupation policy of Japan. Results. Historical events were identified that linked the fate of a large number of representatives of the two states. Shown are the various life paths that Russians chose in a foreign land, the difficulties they faced. Their attitude to the spiritual (moral) values of Russian culture is noted. The problem of disunity between military units and their leaders, which killed the “white” army in the civil war in Russia, was not overcome in China. The modern world never ceases to accept the challenges of supporters of radical transformations. This increases public interest in the experience of adaptation of Russian emigrants in China.

Euclidean ideal classes in Galois number fields of odd prime degree

Weinberger in 1972, proved that the ring of integers of a number field with unit rank at least $1$ is a principal ideal domain if and only if it is a Euclidean domain, provided the generalised Riemann hypothesis holds. Lenstra extended the notion of Euclidean domains in order to capture Dedekind domains with finite cyclic class group and proved an analogous theorem in this setup. More precisely, he showed that the class group of the ring of integers of a number field with unit rank at least $1$ is cyclic if and only if it has a Euclidean ideal class, provided the generalised Riemann hypothesis holds. The aim of this paper is to show the following. Suppose that $\mathbf{K}_1$ and $\mathbf{K}_2$ are two Galois number fields of odd prime degree with cyclic class groups and Hilbert class fields that are abelian over $\mathbb{Q}$. If $\mathbf{K}_1\mathbf{K}_2$ is ramified over $\mathbf{K}_i$, then at least one $\mathbf{K}_i$ ($i \in \{1,2\}$) must have a Euclidean ideal class.

Sustainability measurement with a non-compensatory approach in Cuban nature-based tourism

ABSTRACT This paper aims to assess the sustainability of tourism destinations. To this end, various methodologies have been considered, among which composite indicators constitutes a valuable tool. A non-compensatory methodology has been applied in order to address the problem caused by the compensation of low values in certain indicators of a particular destination with high scores in other aspects. The proposed methodology provides a clear ranking of units and permits a post-optimization analysis for the design of strategies with a view to the improvement of the relative position regarding the sustainability of a destination. It is applied in an island context, for which tourism represents its main economic activity and, therefore, its dependence on natural, social, economic, and cultural resources, among others, for its development. The analysis demonstrates the possibility associated with each destination to improve its position, acting in just a single indicator while maintaining major values in the remaining indicators, this being a more restrictive methodology in sustainability assessment. The originality is the methodology being supported by the combination of the non-compensatory approach with participative methods to include the considerations of the stakeholders throughout the weights in a regional initiative in the Caribbean Zone of Sustainable Tourism. The findings reveal that the economic aspects receive more importance than those in the Cuban context that are social and patrimonial. The method can be applied to other destinations and regions, allowing the inclusion of external and reducing the absence of incomparability issues in ranking destinations supporting managerial decisions.