A Novel Integrated Strategic Portfolio Decision-Making Model

2017 ◽  
Vol 8 (3) ◽  
pp. 1-44 ◽  
Author(s):  
Darius Danesh ◽  
Michael J. Ryan ◽  
Alireza Abbasi

This study proposes a novel method for portfolio selection/decision making that combines the Portfolio Theory (PT), Analytic Hierarchy Process (AHP) and Data Envelopment Analysis (DEA) cross-efficiency technique. It takes into account the profits, risks and proficiency of a portfolio and is shown to be useful for selecting one with positive and negative data and subsequently measuring its efficiency using AHP, with a consistency test conducted to verify the objectivity of the results. To test the applicability of the proposed model, it is used to determine the efficiency levels of ten of the largest companies in Australia for the years 2014 and 2015. Two criteria, namely, the expected return and variance, are used to identify the preference status of each company. The results indicate that the proposed model is feasible and adoptable for the contemporary industrial scenario as it simultaneously analyses profits, risks and proficiency.

Vaccines ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 718
Author(s):  
Sayed F. Abdelwahab ◽  
Usama H. Issa ◽  
Hossam M. Ashour

Selecting a vaccine for fighting a pandemic is one of the serious issues in healthcare. Novel decision models for vaccine selection need to be developed. In this study, a novel vaccine selection decision-making model (VSDMM) was proposed and developed, based on the analytic hierarchy process (AHP) technique, which assesses many alternatives (vaccines) using multi-criteria to support decision making. To feed data to the VSDMM, six coronavirus disease-19 (COVID-19) vaccines were selected in a case study to highlight the applicability of the proposed model. Each vaccine was compared to the others with respect to six criteria and all criteria were compared to calculate the relative weights. The proposed criteria include (1) vaccine availability; (2) vaccine formula; (3) vaccine efficacy; (4) vaccine-related side effects; (5) cost savings, and (6) host-related factors. Using the selected criteria, experts responded to questions and currently available COVID-19 vaccines were ranked according to their weight in the model. A sensitivity analysis was introduced to assess the model robustness and the impacts of changing criteria weights on the results. The VSDMM is flexible in terms of its ability to accept more vaccine alternatives and/or more criteria. It could also be applied to other current or future pandemics/epidemics in the world. In conclusion, this is the first report to propose a VSDMM for selecting the most suitable vaccines in pandemic/epidemic situations or any other situations in which vaccine selection and usage may be deemed necessary.


Author(s):  
Ahmet Çalık ◽  
Bilge Afşar

In Turkey, since March 2020, the pandemic process caused changes in the bank selection of consumers as it affected all other activities. Prioritization of bank selection criteria is a multi-criteria decision-making (MCDM) problem with conflicting criteria. In this study, the Pythagorean fuzzy analytic hierarchy process (PFAHP) is used to prioritize the selection criteria, it is aimed to provide more freedom for decision-makers in expressing their opinions. Not only quantitative criteria such as interest rate, ATM, and number of branches, but also the environmental and social impacts of the pandemic, the nine main criteria have been determined. As a result of interviews with different sectors, it was found that the loan interest rate is the most important criterion. The results were compared with different classical and fuzzy AHP methods, and it was found that the PFAHP method produced reliable and informative results that better represented the uncertainty of the decision-making process.


2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Zaher Sepehrian ◽  
Sahar Khoshfetrat ◽  
Said Ebadi

Data envelopment analysis (DEA) has been used for obtaining weights for the analytic hierarchy process (AHP), an approach known as DEAHP. This method sometimes identifies more than one decision criterion or alternative as DEAHP-efficient. To overcome this problem, this paper proposes a new approach that not only generates appropriate weights for the decision criteria or alternatives, but also differentiates between DEAHP-efficient decision criteria or alternatives. To this end, we propose a DEA model with an assurance region and a cross-weight model that prioritizes decision criteria or alternatives by considering their most unfavorable weights. Two numerical examples are also provided to illustrate the advantages and potential applications of the proposed model.


2012 ◽  
Vol 538-541 ◽  
pp. 895-900 ◽  
Author(s):  
Han Chen Huang

A number of factors must be considered when selecting a convention site. Typically, most selections are based on the decision makers’ knowledge and experience, which may lead to biased decisions based on the decision makers’ subjective judgment. This study establishes decision-making evaluation factors and attributes for convention site selection based on a literature review. After surveying experts’ opinions using questionnaires, we employed the fuzzy analytic hierarchy process (FAHP) to analyze the weighting of the factors and attributes. The results show that of the five evaluation factors, site environment is the most important, followed by meeting and accommodation facilities, local support, extraconference opportunities, and costs. Additionally, the five most important attributes among the 20 evaluation attributes are the suitability of convention facilities, suitability and quality of local infrastructure, climate, city image, and political conflict or terrorist threats.


Author(s):  
Dengfeng Wang ◽  
Shenhua Li

This work proposes a material selection decision-making method for multi-material lightweight body driven by performance to achieve that the right materials are used for the correct positions of the automotive body. The internal relationship between performance and mass, cross-sectional shape, wall thickness parameters, and material properties of a thin-walled structure is studied. The lightweight material indices driven by performance are then established. The lightweight material indices and material price are taken as the decision-making criteria for the material selection of automotive body components. A hybrid weighting method integrated with the analytic hierarchy process, fuzzy analytic hierarchy process, and quality function deployment is proposed. The difficulty of quantitatively evaluating the performance requirements of different components of the body is solved using the proposed weighting method combined with the numerical analytical results of the component performance under multiple operating conditions of the automotive body. Then, the weight of the decision-making criteria for material selection is calculated. Grey relational analysis is used to make multicriteria decision-making on a variety of candidate materials to select the best material for body components. After the lightweight material selection of the front longitudinal beam of the automotive body, the frontal collision safety performance of the body is effectively improved, and the mass of the front longitudinal beam is reduced by 45%. Material selection result of the front longitudinal beam indicates that the proposed material selection decision-making method can effectively achieve the fast material selection of components in different positions of the body.


2019 ◽  
Vol 11 (8) ◽  
pp. 2330 ◽  
Author(s):  
Patricija Bajec ◽  
Danijela Tuljak-Suban

Sustainable concerns are reputed to be of the utmost priority among governments. Consequently, they have become more and more of a concern among supply chain partners. Logistics service providers (LPs), as significant contributors to supply chain success but also one of the greatest generator of emissions, play a significant role in reducing the negative environmental impact. Thus, the performance evaluations of LPs should necessarily involve such a measure which, firstly, represents a balance between all three pillars of sustainability and, secondly, consider the desirable and undesirable performance criteria. This paper proposes an integrated analytic hierarchy process (AHP) and slack-based measure (SBM) data envelopment analysis (DEA) model, based on the assumption of a variable return to scale (VRS). An AHP pairwise comparison enables selecting the most influential input/output variables. Output-oriented SBM DEA provides simultaneously evaluation of both the undesirable and desirable outputs. The proposed model was tested on a numerical example of 18 LPs. The comparison of output Charnes, Cooper and Rhodes (CCR) and SBM DEA models resulted in a higher number of inefficient LPs when the SBM DEA model was applied. Moreover, efficiency scores of inefficient LPs were lower in SBM DEA model. The proposed model is fair to those LPs that are environmentally friendly.


2019 ◽  
pp. 135481661988520
Author(s):  
Joseph Andria ◽  
Giacomo di Tollo ◽  
Raffaele Pesenti

In this article, we propose a method for ranking tourist destinations and evaluating their performances under a sustainability perspective: a fuzzy multiple criteria decision-making method is applied for determining sustainability performance values and ranking destinations accordingly. We select a set of sustainability evaluation criteria and use a fuzzy analytic hierarchy process to weight the selected criteria. We also optimize each evaluator’s membership function support by means of a fuzzy entropy maximization criteria. A case study is illustrated and results are compared with two data envelopment analysis–based models. The simplicity of the proposed approach along with the easy readability of the results allow its direct applicability for all involved stakeholders.


2019 ◽  
Vol 7 (8) ◽  
pp. 244
Author(s):  
Shaoyue Shi ◽  
Danhong Zhang ◽  
Yixin Su ◽  
Chengpeng Wan ◽  
Mingyang Zhang ◽  
...  

This paper develops a decision-making model to assist the improvement of the carrying capacity of ship locks by combing fuzzy logic, the analytic hierarchy process (AHP) method, and the technique for order preference by similarity to an ideal solution (TOPSIS). A three-level hierarchical structure is constructed to identify the key factors influencing the carrying capacity of ship locks from the aspects of ship locks, vessels, environment, and administration. On this basis, a series of targeted strategies have been put forward to improve the carrying capacity of ship locks, and the TOPSIS method is applied to rank these strategies in terms of their performance. A case study of the five-stage dual-track ship lock of the Three Gorges Dam in China has been conducted to demonstrate the feasibility and rationality of the proposed model, and correlation analysis is conducted to verify the identified influencing factors in order to eliminate potential bias which may be generated from using AHP. The results obtained from the proposed methods are consistent with the real-life situation to a certain extent, indicating that the proposed method can provide a useful reference for improving the carrying capacity of ship locks.


Author(s):  
Shouhua Yuan ◽  
Yiliu Tu ◽  
Deyi Xue

Data Envelopment Analysis (DEA) has been widely applied in evaluating multi-criteria decision making problems which have multi-inputs and multi-outputs. However, the traditional DEA method does neither take the decision maker’s subjective preferences to the individual criteria into consideration, nor rank the selected options or decision making units (DMUs). On the other hand, Satty’s Analytical Hierarchy Process (AHP) was established to rank options or DMUs under multi-inputs and multi-outputs through pairwise comparisons. But in most cases, the AHP pairwise comparison method is not perfectly consistent, which may give rise to confusions in determining the appropriate priorities of each criterion to be considered. The inconsistency implicates the fuzziness in generating the relative important weight for each criterion. In this paper, a novel method which employs both DEA and AHP methods is proposed to evaluate the overall performance of suppliers’ involvement in the production of a manufacturing company. This method has been developed through modifying the DEA method into a weighting constrained DEA method by using a piecewise triangular weighting fuzzy set which is generated from the inconsistent AHP comparisons. A bias tolerance ratio (BTR) is introduced to represent the varying but restrained weighting values of each criterion. Accordingly, the BTR provides the decision maker a controllable parameter by tightening or loosening the range of the weighting values in evaluating the overall performance of available suppliers, which in hence, overcomes the two weaknesses of the traditional DEA method.


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