Comparison and Optimization of Mining Area Division Schemes for Baorixile Open-Pit Coal Mine Based on Improved AHP-EWM Method
In: HELIYON-D-24-31316
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In: HELIYON-D-24-31316
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In: Paradigms of Management, Economics and Law, Heft 1, S. 30-45
The entropy weight-TOPSIS method is used to calculate the high-quality development level of logistics industry in 31 provinces of China in 2011-2020, and to test its spatial differences and autocorrelation using Theil index and Moran's I index. The results show that: (1) the highquality development level of logistics industry in Zhejiang, Guangdong, Shanghai, Beijing and Jiangsu ranks the top; (2) the high-quality development of logistics industry is accelerated after 2014; (3) the spatial differences mainly come from the imbalance in northwest China and East China; (4) the spatial autocorrelation is remarkable and gradually increasing. Finally, in order to promote the high-quality development and coordinated development of the logistics industry, some suggestions and countermeasures are put forward.
In: Asia Pacific journal of marketing and logistics, Band 20, Heft 1, S. 44-54
ISSN: 1758-4248
PurposeThe purpose of this paper is to present a selection model that adopts several important criteria, enabling a durable goods franchiser to select franchisees that are most appropriate.Design/methodology/approachQuestionnaires based on selection criteria are identified from modified Delphi Technique and then sent to experts and decision makers. Major criteria weights are analyzed using the analytic hierarchy process and entropy. Final weights are then determined using the compromised weighting method.FindingsThis study has demonstrated that the durable goods sector in Taiwan emphasizes the condition of a franchisee personal condition more than its store location, and our results further indicate that a franchiser should emphasize finance and business ability when selecting franchisees. Additionally, consumer purchasing power, individuals passing by and parking convenience are all important factors for selecting a franchisee.Originality/valueAnalysis results indicate that the proposed selection model enables a franchiser to select franchisees more reasonably by allowing them to operate effectively.
In: Studia humana: quarterly journal ; SH, Band 11, Heft 2, S. 25-48
ISSN: 2299-0518
Abstract
Advancement in internet of things (IoT) and proliferation in the use of smart devices have raised concerns about the data privacy of online users. This study predicts the consequences of perceived data privacy risks on consumer behaviours in Lagos State, Nigeria using the integrated Entropy-Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). We employed Entropy to assign weights to each criterion. Subsequently, responses were systematically ranked to arrive at an inference using TOPSIS. 84.8% agree that any perceived cyber security threat or a breach in their data privacy would stop them from proceeding with the transaction or activity online, or the use of a digital product. Similarly, (86.7%), agree it is critical that online businesses only ask for customer information that is relevant to the use of the product or service. Thus, the findings indicate that the privacy paradox of enlightened online consumers tends to diminish when they are faced with perceived data privacy and cybersecurity risks.
In: Political analysis: PA ; the official journal of the Society for Political Methodology and the Political Methodology Section of the American Political Science Association, Band 20, Heft 1, S. 25-46
ISSN: 1476-4989
This paper proposes entropy balancing, a data preprocessing method to achieve covariate balance in observational studies with binary treatments. Entropy balancing relies on a maximum entropy reweighting scheme that calibrates unit weights so that the reweighted treatment and control group satisfy a potentially large set of prespecified balance conditions that incorporate information about known sample moments. Entropy balancing thereby exactly adjusts inequalities in representation with respect to the first, second, and possibly higher moments of the covariate distributions. These balance improvements can reduce model dependence for the subsequent estimation of treatment effects. The method assures that balance improves on all covariate moments included in the reweighting. It also obviates the need for continual balance checking and iterative searching over propensity score models that may stochastically balance the covariate moments. We demonstrate the use of entropy balancing with Monte Carlo simulations and empirical applications.
In: International journal of enterprise information systems: IJEIS ; an official publication of the Information Resources Management Association, Band 14, Heft 2, S. 43-55
ISSN: 1548-1123
In this article, the authors apply the big grey relational decision-making algorithm to improve performance evaluation effectiveness of the higher educational resources utilization. First, they discuss the performance evaluation indexes in higher education. Second, they propose the big data grey relational decision algorithm. Third, they establish the mathematical models of entropy weight and grey evaluation method. Finally, the authors carry out an evaluation simulation analysis on four cities as researching objects. The results show that the big data grey relational decision-making algorithm is an effective method for evaluating the higher educational resource utilization.
In: Journal of enterprise information management: an international journal, Band 35, Heft 4/5, S. 988-1010
ISSN: 1758-7409
PurposeBy calculating the information entropy of the indicator and measuring the amount of information in the data, this paper determines the weight of the indicator according to the impact of the relative change of the indicator on the whole.Design/methodology/approachIn order to study the action mechanism of circular economy development and green finance, based on the entropy method, this paper constructs a system analysis model based on event research.FindingsMoreover, this paper uses the analytic hierarchy process to obtain subjective weights based on expert opinions and then uses the entropy method to obtain objective weights and finally combines the two. In addition, an intelligent model is constructed based on the action mechanism of circular economy development and green finance to improve the system structure.Originality/valueFinally, this paper designs experiments to verify the performance of the system model. The research results show that the system model constructed in this paper meets the actual situation.
Homogeneous diethyl phthalate/phenylphthalein-dimethylether (DEP/PDE) mixtures have been investigated by means of broadband dielectric spectroscopy. Contrarily to the widespread view that homogenous binary mixtures should give rise to a single glass transition, the mixture displays two dynamics giving rise to two glass transitions. Such a finding can be rationalized invoking the self-concentration concept that relies on the localized nature of the glass transition phenomenon. In such a way, the analogy with miscible polymer blends, for which this concept has been introduced, is highlighted. A model based on the combination of the Adam-Gibbs (AG) theory of the glass transition and the self-concentration concept resulted to be fully predictive once the only unknown variable, namely, the glass-former specific parameter (α) connecting the characteristic length for the glass transition to the configurational entropy, is extracted applying the model itself to DEP/toluene and DEP/PDE solutions highly concentrated, respectively, in DEP and PDE. The α parameter obtained in such a way allows the precise determination of the most probable relaxation time even for those DEP/PDE mixtures displaying a strong overlap of the dielectric response. The model incorporating the self-concentration concept to the AG theory also provides the characteristic length scale for the glass transition for both DEP and PDE. Such a length scale was found to be on the order of 1–2 nm. This is comparable to that obtained for other glass formers. ; The authors acknowledge the University of the Basque Country and Basque Country Government (Ref. No. IT-436-07), Depto. Educación, Universidades e Investigación and Spanish Minister of Education (Grant No. MAT 2007-63681) for their support. The support of the European Community within the SOFTCOMP program is also acknowledged. ; Peer reviewed
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In this paper we propose a methodology to study circular economy processes based on mathematical modelling. In open-ended systems, waste could be converted back to recycling, transforming the economy from linear to circular. The concept of entropy and the second law of thermodynamics give the argument for a scale reduction of material circulation. As humans extract more and more energy and matter for the economy, the degree of entropy is likely to increase. Based on the findings of economic studies on the implications of industrialization in the case of growing economies, this study aims at evaluating circular economy processes at the European Union (EU) level using a Shannon-Entropy-based algorithm. An entropy-based analysis was conducted for the 28 European Union countries during the time frame 2007&ndash ; 2016. The modelling process consists of constructing a composite indicator which is composed of a weighted sum of all indicators developed by an algorithm based on Shannon Entropy. The weights assigned to each indicator in our analysis measure the significance of each indicator involved in the development of the composite indicator. The results are similar to the international rakings, consolidating and confirming the accuracy and reliability of this approach.
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In: Journal of enterprise information management: an international journal, Band 35, Heft 2, S. 333-357
ISSN: 1758-7409
PurposeThe purpose of this study to introduce a new extended framework to evaluate and rank the sustainable suppliers based on the different sustainable criteria in the manufacturing companies using a new fuzzy decision-making approach.Design/methodology/approachThis paper introduces a new approach using decision-making and Pythagorean fuzzy sets (PFSs) to assess the best sustainable supplier. To doing so, this study integrated the entropy, stepwise weight assessment ratio analysis (SWARA) and weighted aggregates sum product assessment (WASPAS) methods under PFSs. To calculate the criteria weights, the combined entropy-SWARA method is used to compute the objective weight and subjective weight, respectively. Furthermore, the WASPAS model is utilized to rank sustainable supplier alternatives.FindingsThe results of the analysis found that occupational health and safety systems had the highest rank among other criteria, followed by green product and eco-design, green R&D and innovation and green technology. In addition, the findings of the paper demonstrated that the extended approach was efficient and useful for selecting and evaluating the best sustainable supplier in the manufacturing companies.Originality/valueRecent years have witnessed a number of studies aimed at incorporating the sustainability standards into the supplier selection problem; however, only a little research has been conducted on developing a fuzzy method for decision-making in a manner to assess and choose suppliers with high sustainability in the insurance market, encompassing the three above-mentioned sustainability criteria.
In: Lecture Notes in Networks and Systems Series v.337
Intro -- Preface -- Contents -- Analyses of Aspects of Economic, Social and Technological Development -- Ranking of Innovation and Sustainability of Tourist Destinations in Sinaloa: An Analysis with the Ordered Weighted Average Operator -- 1 Introduction -- 2 Theoretical Framework -- 2.1 A Literature Review of the Innovation and Sustainability of Tourist Destinations -- 2.2 Innovation and Sustainability in the Tourist Destinations of Mexico -- 3 The Ordered Weighted Average Operator -- 4 Measurement of the Innovation and Sustainability in the Tourist Destinations in Sinaloa with the OWA Operator -- 5 Conclusions -- References -- Dimensional Analysis Under Pythagorean Fuzzy Set with Hesitant Linguists Term Entropy Information -- 1 Introduction -- 2 Preliminaries -- 2.1 Pythagorean Fuzzy Sets -- 2.2 Dimensional Analysis -- 2.3 Entropy with Unknown Weights in Hesitant Fuzzy Linguistic Term Setting -- 3 DA-PFS with Hesitant Entropy -- 3.1 Dimensional Analysis Under Pythagorean Fuzzy Set (DA-PFS) -- 3.2 Algorithm for DA-PFS with Hesitant Entropy -- 4 Application -- 4.1 Numerical Example -- 4.2 Hesitant Entropy Weight -- 4.3 Sensitivity Analysis -- 5 Conclusion -- References -- Wages Returns in Mexico: A Comparison Between Parametric and Nonparametric Approaches -- 1 Introduction -- 2 Preliminaries -- 2.1 Mincer Equation Analysis for Mexico -- 2.2 Mincer with Decision Trees for Mexico -- 2.3 Outliers -- 2.4 Discriminant Analysis -- 3 Conclusions -- References -- Study of the Geographical Marginality in a Mexican Region Using the MR-Sort Method -- 1 Introduction -- 2 Previous Work of Marginalization in Mexico -- 3 The MR-Sort for Ordered Classification -- 4 Results -- 4.1 Data Marginalization in Mexico -- 4.2 Preference Information -- 4.3 Result Analysis -- 5 Conclusions -- References.
The lack of adequate indicators in the research of digital economy may lead to the shortage of data support on decision making for governments. To solve this problem, first we establish a digital economy indicator evaluation system by dividing the digital economy into four types: "basic type", "technology type", "integration type" and "service type" and select 5 indicators for each type. On this basis, the weight of each indicator is calculated to find the deficiencies in the development of some digital economic fields by the improved entropy method. By drawing on the empowerment idea of Analytic Hierarchy Process, the improved entropy method firstly compares the difference coefficient of indicators in pairs and maps the comparison results to the scales 1–9. Then, the judgment matrix is constructed based on the information entropy, which can solve as much as possible the problem that the difference among the weight of each indicator is too large in traditional entropy method. The results indicate that: the development of digital economy in Guangdong Province was relatively balanced from 2015 to 2018 and will be better in the future while the development of rural e-commerce in Guangdong Province is relatively backward, and there is an obvious digital gap between urban and rural areas. Next we extract two new variables respectively to replace the 20 indicators we select through principal component analysis and factor analysis methods in multivariate statistical analysis, which can retain the original information to the greatest extent and provide convenience for further research in the future. Finally, we and provide constructive comments of digital economy in Guangdong Province from 2015 to 2018.
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In: Journal of multi-criteria decision analysis, Band 18, Heft 1-2, S. 23-38
ISSN: 1099-1360
ABSTRACTWith the rapid development of urbanization, urban environmental problems become a big challenge for urban socio‐economic development planning. In this paper, a new Dynamic Assessment method, which integrates technique for order preference by similarity to ideal solution, Entropy weight for time series data analysis, Grey relational analysis and Clustering, is proposed for urban eco‐environmental quality assessment of the Yangtze River Delta and Pearl River Delta in China. A sensitivity analysis is also conducted to identify the influence of weight or value changes of factors. The urban eco‐environmental quality ranking by the proposed method is consistent with the Chinese city competitiveness rankings in 2009 by the Chinese Academy of Social Sciences. It is much easier and more efficient to obtain the urban eco‐environmental quality ranking by the proposed method than by field studies and surveys. Copyright © 2011 John Wiley & Sons, Ltd.
The research analyzes the progress of Member States in the implementation of Europe 2020 strategy targets and goals in 2016–2018. Multiple criteria decision-making approaches applied for this task. The set of headline indicators was divided into two logically explained groups. Interval entropy is proposed as an effective tool to make prioritization of headline indicators in separate groups. The sensitivity of the interval entropy is its advantage over classical entropy. Indicator weights were calculated by applying the WEBIRA (weight-balancing indicator ranks accordance) method. The WEBIRA method allows the best harmonization of ranking results according to different criteria groups—this is its advantage over other multiple-criteria methods. Final assessing and ranking of the 28 European Union countries (EU-28) was implemented through the α-cut approach. A k-means clustering procedure was applied to the EU-28 countries by summarizing the ranking results in 2016–2018. Investigation revealed the countries–leaders and countries–outsiders of the Europe 2020 strategy implementation process. It turned out that Sweden, Finland, Denmark, and Austria during the three-year period were the countries that exhibited the greatest progress according to two headline indicator groups' interrelation. Cluster analysis results are mainly consistent with the EU-28 countries' categorizations set by other authors.
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The q-rung orthopair fuzzy set ((ROPFS)-R-q), proposed by Yager, is a more effective and proficient tool to represent uncertain or vague information in real-life situations. Divergence and entropy are two important measures, which have been extensively studied in different information environments, including fuzzy, intuitionistic fuzzy, interval-valued fuzzy, and Pythagorean fuzzy. In the present communication, we study the divergence and entropy measures under the q-rung orthopair fuzzy environment. First, the work defines two new order-alpha divergence measures for (q)ROPFSs to quantify the information of discrimination between two (q)ROPFSs. We also examine several mathematical properties associated with order-alpha (ROPF)-R-q divergence measures in detail. Second, the paper introduces two new parametric entropy functions called "order-alpha (ROPF)-R-q entropy measures" to measure the degree of fuzziness associated with a (ROPFS)-R-q. We show that the proposed order-alpha divergence and entropy measures include several existing divergence and entropy measures as their particular cases. Further, the paper develops a new decision-making approach to solve multiple attribute group decision-making problems under the (ROPF)-R-q environment where the information about the attribute weights is completely unknown or partially known. Finally, an example of selecting the best enterprise resource planning system is provided to illustrate the decision-making steps and effectiveness of the proposed approach ; Chilean Government (Conicyt) through the Fondecyt Postdoctoral Program 3170556
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