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Advances in Multiple Criteria Decision Making for Sustainability: Modeling and Applications

A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: closed (30 September 2017) | Viewed by 101528

Special Issue Editors

Prof. Dr. Gwo-Hshiung Tzeng

E-Mail Website
Guest Editor
College of Public Affairs, National Taipei University, New Taipei City 23741, Taiwan
Interests: technological management; energy; environment; transportation systems/investment; logistics; location selection; urban planning; tourism; electronic commerce; global supply chains
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Kao-Yi Shen

E-Mail Website
Guest Editor
Department of Banking and Finance, Chinese Culture University (SCE), 55, Hwa-Kang Road, Yang-Ming-Shan, Taipei 11114, Taiwan
Interests: multiple criteria decision making (MCDM); fuzzy set theory; rough set theory; machine learning; business analytics; fundamental analysis; equity evaluation; technical analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Real-world decision problems often require the consideration and analysis of a group of factors/attributes/criteria that affect the final evaluation. As criteria are often in conflict, decision makers (DMs) need a scientific approach to conduct those analyses. The growing complexity in modern social-economics or engineering environments (or system) has impeded DMs or researchers who try to solve a complicated problem by using single-criterion models. Therefore, the use of a multiple criteria decision making (MCDM) approach to solving real-world problems has gained considerable attention in both academia and practice.

In recent years, MCDM research has been widely adopted in various fields, to exploit the preference or knowledge of DMs, for decision aids. However, traditional MCDM research mainly focuses on reaching the highest economic value or efficiency; issues related to sustainability are still underexplored. Thus, this Special Issue aims to collect high-quality papers which apply MCDM methods in all fields that address valuable topics related to sustainability. Also, owing to the uncertainty or vagueness in certain decision environments, the combination or integration of soft computing and artificial intelligence techniques with MCDM methods in modeling, are welcomed. Potential topics include, but are not limited to, the modeling or applications of MCDM (or hybrid MCDM) approaches in:

  • Business
  • Management
  • Finance
  • Marketing
  • Economics
  • Politics
  • Transportation
  • Education
  • Engineering
  • Energy
  • Ecology
  • Information Technology
  • Medical Science

Prof. Gwo-Hshiung Tzeng
Dr. Kao-Yi Shen
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

 

Keywords

  • Sustainable development
  • Multiple criteria decision making (MCDM)
  • Problem-solving
  • Optimization
  • Decision aid
  • Soft computing
  • Computational intelligence
  • Artificial intelligence (AI)
  • Fuzzy sets
  • Rough set theory

Published Papers (16 papers)

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Editorial

Jump to: Research

7 pages, 183 KiB  
Editorial
Advances in Multiple Criteria Decision Making for Sustainability: Modeling and Applications
by Kao-Yi Shen and Gwo-Hshiung Tzeng
Sustainability 2018, 10(5), 1600; https://doi.org/10.3390/su10051600 - 16 May 2018
Cited by 35 | Viewed by 9194
Abstract
With the surging complexity of real-world problems in important domains such as sustainability, there is a need to leverage advanced modern computational methods or intelligent techniques to support decisions or policy-making. In this Special Issue, 15 selected and formally peer-reviewed papers contribute their [...] Read more.
With the surging complexity of real-world problems in important domains such as sustainability, there is a need to leverage advanced modern computational methods or intelligent techniques to support decisions or policy-making. In this Special Issue, 15 selected and formally peer-reviewed papers contribute their novelty and findings, by applying various advanced decision methods or computational techniques to resolve different sustainability problems. Despite the innovations of the proposed models, most of the selected papers involve domain expert’s opinions and knowledge with in-depth discussions. These case studies enrich the practical contributions of this Special Issue. Full article
(This article belongs to the Special Issue Advances in Multiple Criteria Decision Making for Sustainability: Modeling and Applications)

Research

Jump to: Editorial

17969 KiB  
Article
Customer Purchasing Behavior Analysis as Alternatives for Supporting In-Store Green Marketing Decision-Making
by M. Alex Syaekhoni, Ganjar Alfian and Young S. Kwon
Sustainability 2017, 9(11), 2008; https://doi.org/10.3390/su9112008 - 02 Nov 2017
Cited by 25 | Viewed by 11716
Abstract
Due to increasing concerns about environmental protection, the environmental sustainability of businesses has been widely considered in the manufacturing and supply chain context. Further, its adoption has been implemented in the retail industry for marketing field, including green product promotion. This study aimed [...] Read more.
Due to increasing concerns about environmental protection, the environmental sustainability of businesses has been widely considered in the manufacturing and supply chain context. Further, its adoption has been implemented in the retail industry for marketing field, including green product promotion. This study aimed to propose a customer purchasing behavior analysis as an alternative for supporting decision-making in order to promote green products in retail stores. Hence, right-on-target marketing strategies can be implemented appropriately. The study was carried out using shopping path data collected by radio frequency identification (RFID) from a large retail store in Seoul, South Korea. In addition, the store layout and its traffic were also analyzed. This method is expected to help experts providing appropriate decision alternatives. In addition, it can help retailers in order to increase product sales and achieve high levels of customer satisfaction. Full article
(This article belongs to the Special Issue Advances in Multiple Criteria Decision Making for Sustainability: Modeling and Applications)
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1284 KiB  
Article
Exploring R&D Influences on Financial Performance for Business Sustainability Considering Dual Profitability Objectives
by Kao-Yi Shen, Min-Ren Yan and Gwo-Hshiung Tzeng
Sustainability 2017, 9(11), 1964; https://doi.org/10.3390/su9111964 - 27 Oct 2017
Cited by 18 | Viewed by 5648
Abstract
The importance of research and development (R&D) for business sustainability have gained increasing interests, especially in the high-tech sector. However, the efforts of R&D might cause complex and mixed impacts on the financial results considering the associated expenses. Thus, this study aims to [...] Read more.
The importance of research and development (R&D) for business sustainability have gained increasing interests, especially in the high-tech sector. However, the efforts of R&D might cause complex and mixed impacts on the financial results considering the associated expenses. Thus, this study aims to examine how R&D efforts may influence business to improve its financial performance considering the dual objectives: the gross and the net profitability. This research integrates a rough-set-based soft computing technique and multiple criteria decision-making (MCDM) methods to explore this complex and yet valuable issue. A group of public listed companies from Taiwan, all in the semiconductor sector, is analyzed as a case study. More than 30 variables are considered, and the adopted soft computing technique retrieves 14 core attributes—for the dual profitability objectives—to form the evaluation model. The importance of R&D for pursuing superior financial prospects is confirmed, and the empirical case demonstrates how to guide an individual company to plan for improvements to achieve its long-term sustainability by this hybrid approach. Full article
(This article belongs to the Special Issue Advances in Multiple Criteria Decision Making for Sustainability: Modeling and Applications)
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803 KiB  
Article
Using DEMATEL and Intuitionistic Fuzzy Sets to Identify Critical Factors Influencing the Recycling Rate of End-Of-Life Vehicles in China
by Junwei Gan and Li Luo
Sustainability 2017, 9(10), 1873; https://doi.org/10.3390/su9101873 - 24 Oct 2017
Cited by 50 | Viewed by 6019
Abstract
At present, the recycling rate of End-of-life vehicles (ELVs) in China is far lower than the heavily motorized countries, resulting in severe environmental pollution, waste of resource and hidden traffic troubles, which has a negative impact on China’s economic and social sustainable development. [...] Read more.
At present, the recycling rate of End-of-life vehicles (ELVs) in China is far lower than the heavily motorized countries, resulting in severe environmental pollution, waste of resource and hidden traffic troubles, which has a negative impact on China’s economic and social sustainable development. With the arrival of the peak season of generating ELVs in China, it is urgent and important to improve the recycling rate of ELVs. The recycling rate of ELVs is influenced by multiple factors together. The existing research about the identification of influence factors of ELV recycling rate fewer considers the interaction effect among different factors. To fill the gap, firstly the influence factors are analyzed from standpoints of economy, policy, recycling network and others. Then a hybrid model based on DEMATEL (decision making trial and evaluation laboratory) and intuitionistic fuzzy sets is employed to examine the cause–effect relationships among factors. In the study, the vagueness of decision makers’ judgment and linguistic inaccuracy is dealt with effectively by intuitionistic fuzzy sets. The research results reveal “fiscal subsidy”, “government’s restrictive policies to reuse ELVs parts”, “coordination of the industry agencies”, “participation of automobile manufacturer” and “supervision of the government” are most significant criteria influencing the recycling rate of ELVs in China. A sensitivity analysis is conducted to verify the robustness of results. Lastly, according to the critical influencing factors identified, some pertinent suggestions to the government, ELV recycling enterprise, owner and vehicle manufacturer are put forward. In addition, the future research directions are proposed. Full article
(This article belongs to the Special Issue Advances in Multiple Criteria Decision Making for Sustainability: Modeling and Applications)
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6845 KiB  
Article
Gathered Village Location Optimization for Chinese Sustainable Urbanization Using an Integrated MODM Approach under Bi-Uncertain Environment
by Lu Gan, Li Wang and Lin Hu
Sustainability 2017, 9(10), 1907; https://doi.org/10.3390/su9101907 - 23 Oct 2017
Cited by 7 | Viewed by 3929
Abstract
Urbanization has become a main challenge all over developing countries in the 21st Century. However, decision making should take into account the different national situations with their complex factors to achieve sustainable development. As standards of living have risen in urban areas, local/neighbor [...] Read more.
Urbanization has become a main challenge all over developing countries in the 21st Century. However, decision making should take into account the different national situations with their complex factors to achieve sustainable development. As standards of living have risen in urban areas, local/neighbor urbanization has become a coming trend in China. With this in mind, the paper focuses on the optimization of nearby gathered village locations in Population Migration (PM) with consideration of both qualitative and quantitative criteria. Therefore, an integrated multiple objective decision making approach (MODM) under a bi-uncertain environment is proposed to solve this problem, which is based on the comprehensive Economy-Society-Ecology-Resource-Religion (ESERR) urbanization concept. The first step is to establish a bi-uncertain multiple objective programming model orienting the problem. Secondly, the model process is composed of fuzzy random variable transformation and the expected value model based on a new fuzzy measure, which is given accordingly to obtain the equivalent model. Thirdly, in order to describe the model efficiently, the Multi-Objective Adaptive Global Local Neighbor Particle Swarm Optimization (MOAGLNPSO) with three-dimensional Pareto optimal judgment criteria is designed. Finally, a case study is tested to validate the effectiveness and to illustrate the advantages of the whole approach. This novel approach can help optimize sustainable urbanization strategies and ensure their realistic application. Full article
(This article belongs to the Special Issue Advances in Multiple Criteria Decision Making for Sustainability: Modeling and Applications)
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767 KiB  
Article
Multi Criteria Credit Rating Model for Small Enterprise Using a Nonparametric Method
by Guotai Chi and Zhipeng Zhang
Sustainability 2017, 9(10), 1834; https://doi.org/10.3390/su9101834 - 12 Oct 2017
Cited by 26 | Viewed by 5645
Abstract
A small enterprise’s credit rating is employed to measure its probability of defaulting on a debt, but, for small enterprises, financial data are insufficient or even unreliable. Thus, building a multi criteria credit rating model based on the qualitative and quantitative criteria is [...] Read more.
A small enterprise’s credit rating is employed to measure its probability of defaulting on a debt, but, for small enterprises, financial data are insufficient or even unreliable. Thus, building a multi criteria credit rating model based on the qualitative and quantitative criteria is of importance to finance small enterprises’ activities. Till now, there has not been a multicriteria credit risk model based on the rank sum test and entropy weighting method. In this paper, we try to fill this gap by offering three innovative contributions. First, the rank sum test shows significant differences in the average ranks associated with index data for the default and entire sample, ensuring that an index makes an effective differentiation between the default and non-default sample. Second, the rating equation’s capacity is tested to identify the potential defaults by verifying a clear difference between the average ranks of samples with default ratings (i.e., not index values) and the entire sample. Third, in our nonparametric test, the rank sum test is used with rank correlation analysis made to screen for indices, thereby avoiding the assumption of normality associated with more common credit rating methods. Full article
(This article belongs to the Special Issue Advances in Multiple Criteria Decision Making for Sustainability: Modeling and Applications)
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814 KiB  
Article
A Hybrid MCDM Model for Improving the Electronic Health Record to Better Serve Client Needs
by James J. H. Liou, Ming-Tsang Lu, Shu-Kung Hu, Chia-Hua Cheng and Yen-Ching Chuang
Sustainability 2017, 9(10), 1819; https://doi.org/10.3390/su9101819 - 10 Oct 2017
Cited by 25 | Viewed by 5074
Abstract
Although the electronic health record (EHR) is a promising innovation in the healthcare industry, the implementation of EHR has been relatively slow. A theoretical structure for the exploration and improvement of this usage of EHR is proposed. Incorporating the theoretical structure of TOE [...] Read more.
Although the electronic health record (EHR) is a promising innovation in the healthcare industry, the implementation of EHR has been relatively slow. A theoretical structure for the exploration and improvement of this usage of EHR is proposed. Incorporating the theoretical structure of TOE (technology-organization-environment), we apply the DEMATEL (decision-making trial and evaluation laboratory) technique to illustrate the influence-matrix and to construct the INRM (influential network relationship map). Based on this DEMATEL influence matrix and the fundamental concepts of ANP (Analytic Hierarchy Process), we derive influential weights for the criteria. These influential weights are then combined with the modified VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) method to find ways to understand and enhance the usage of EHR technology. The outcome demonstrates that our model can not only be used for implementation of EHR technology, but can also be applied to analyze the gaps in performance between the aspiration level and present performance values in individual criterion/dimension. Full article
(This article belongs to the Special Issue Advances in Multiple Criteria Decision Making for Sustainability: Modeling and Applications)
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1154 KiB  
Article
Sustainable Scheduling of Cloth Production Processes by Multi-Objective Genetic Algorithm with Tabu-Enhanced Local Search
by Rui Zhang
Sustainability 2017, 9(10), 1754; https://doi.org/10.3390/su9101754 - 28 Sep 2017
Cited by 14 | Viewed by 5102
Abstract
The dyeing of textile materials is the most critical process in cloth production because of the strict technological requirements. In addition to the technical aspect, there have been increasing concerns over how to minimize the negative environmental impact of the dyeing industry. The [...] Read more.
The dyeing of textile materials is the most critical process in cloth production because of the strict technological requirements. In addition to the technical aspect, there have been increasing concerns over how to minimize the negative environmental impact of the dyeing industry. The emissions of pollutants are mainly caused by frequent cleaning operations which are necessary for initializing the dyeing equipment, as well as idled production capacity which leads to discharge of unconsumed chemicals. Motivated by these facts, we propose a methodology to reduce the pollutant emissions by means of systematic production scheduling. Firstly, we build a three-objective scheduling model that incorporates both the traditional tardiness objective and the environmentally-related objectives. A mixed-integer programming formulation is also provided to accurately define the problem. Then, we present a novel solution method for the sustainable scheduling problem, namely, a multi-objective genetic algorithm with tabu-enhanced iterated greedy local search strategy (MOGA-TIG). Finally, we conduct extensive computational experiments to investigate the actual performance of the MOGA-TIG. Based on a fair comparison with two state-of-the-art multi-objective optimizers, it is concluded that the MOGA-TIG is able to achieve satisfactory solution quality within tight computational time budget for the studied scheduling problem. Full article
(This article belongs to the Special Issue Advances in Multiple Criteria Decision Making for Sustainability: Modeling and Applications)
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6746 KiB  
Article
Manufacturing Process Innovation-Oriented Knowledge Evaluation Using MCDM and Fuzzy Linguistic Computing in an Open Innovation Environment
by Gangfeng Wang, Xitian Tian, Yongbiao Hu, Richard David Evans, Mingrui Tian and Rong Wang
Sustainability 2017, 9(9), 1630; https://doi.org/10.3390/su9091630 - 13 Sep 2017
Cited by 11 | Viewed by 5084
Abstract
In today’s complex, constantly evolving and innovation-supporting manufacturing systems, knowledge plays a vital role in sustainable manufacturing process planning and problem-solving, especially in the case of Computer-Aided Process Innovation (CAPI). To obtain formalized and promising process innovation knowledge under the open innovation paradigm, [...] Read more.
In today’s complex, constantly evolving and innovation-supporting manufacturing systems, knowledge plays a vital role in sustainable manufacturing process planning and problem-solving, especially in the case of Computer-Aided Process Innovation (CAPI). To obtain formalized and promising process innovation knowledge under the open innovation paradigm, it is necessary to evaluate candidate knowledge and encourage improvement suggestions based on actual innovation situations. This paper proposes a process innovation-oriented knowledge evaluation approach using Multi-Criteria Decision-Making (MCDM) and fuzzy linguistic computing. Firstly, a comprehensive hierarchy evaluation index system for process innovation knowledge is designed. Secondly, by combining an analytic hierarchy process with fuzzy linguistic computing, a comprehensive criteria weighting determination method is applied to effectively aggregate the evaluation of criteria weights for each criterion and corresponding sub-criteria. Furthermore, fuzzy linguistic evaluations of performance ratings for each criterion and corresponding sub-criteria are calculated. Thus, a process innovation knowledge comprehensive value can be determined. Finally, an illustrative example of knowledge capture, evaluation and knowledge-inspired process problem solving for micro-turbine machining is presented to demonstrate the applicability of the proposed approach. It is expected that our model would lay the foundation for knowledge-driven CAPI in sustainable manufacturing. Full article
(This article belongs to the Special Issue Advances in Multiple Criteria Decision Making for Sustainability: Modeling and Applications)
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917 KiB  
Article
A Consistent Fuzzy Preference Relations Based ANP Model for R&D Project Selection
by Chia-Hua Cheng, James J. H. Liou and Chui-Yu Chiu
Sustainability 2017, 9(8), 1352; https://doi.org/10.3390/su9081352 - 01 Aug 2017
Cited by 20 | Viewed by 5455
Abstract
In today’s rapidly changing economy, technology companies have to make decisions on research and development (R&D) projects investment on a routine bases with such decisions having a direct impact on that company’s profitability, sustainability and future growth. Companies seeking profitable opportunities for investment [...] Read more.
In today’s rapidly changing economy, technology companies have to make decisions on research and development (R&D) projects investment on a routine bases with such decisions having a direct impact on that company’s profitability, sustainability and future growth. Companies seeking profitable opportunities for investment and project selection must consider many factors such as resource limitations and differences in assessment, with consideration of both qualitative and quantitative criteria. Often, differences in perception by the various stakeholders hinder the attainment of a consensus of opinion and coordination efforts. Thus, in this study, a hybrid model is developed for the consideration of the complex criteria taking into account the different opinions of the various stakeholders who often come from different departments within the company and have different opinions about which direction to take. The decision-making trial and evaluation laboratory (DEMATEL) approach is used to convert the cause and effect relations representing the criteria into a visual network structure. A consistent fuzzy preference relations based analytic network process (CFPR-ANP) method is developed to calculate the preference-weights of the criteria based on the derived network structure. The CFPR-ANP is an improvement over the original analytic network process (ANP) method in that it reduces the problem of inconsistency as well as the number of pairwise comparisons. The combined complex proportional assessment (COPRAS-G) method is applied with fuzzy grey relations to resolve conflicts arising from differences in information and opinions provided by the different stakeholders about the selection of the most suitable R&D projects. This novel combination approach is then used to assist an international brand-name company to prioritize projects and make project decisions that will maximize returns and ensure sustainability for the company. Full article
(This article belongs to the Special Issue Advances in Multiple Criteria Decision Making for Sustainability: Modeling and Applications)
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2228 KiB  
Article
A Hybrid MCDM Approach for Strategic Project Portfolio Selection of Agro By-Products
by Animesh Debnath, Jagannath Roy, Samarjit Kar, Edmundas Kazimieras Zavadskas and Jurgita Antucheviciene
Sustainability 2017, 9(8), 1302; https://doi.org/10.3390/su9081302 - 26 Jul 2017
Cited by 69 | Viewed by 7657
Abstract
Due to the increasing size of the population, society faces several challenges for sustainable and adequate agricultural production, quality, distribution, and food safety in the strategic project portfolio selection (SPPS). The initial adaptation of strategic portfolio management of genetically modified (GM) Agro by-products [...] Read more.
Due to the increasing size of the population, society faces several challenges for sustainable and adequate agricultural production, quality, distribution, and food safety in the strategic project portfolio selection (SPPS). The initial adaptation of strategic portfolio management of genetically modified (GM) Agro by-products (Ab-Ps) is a huge challenge in terms of processing the agro food product supply-chain practices in an environmentally nonthreatening way. As a solution to the challenges, the socio-economic characteristics for SPPS of GM food purchasing scenarios are studied. Evaluation and selection of the GM agro portfolio management are the dynamic issues due to physical and immaterial criteria involving a hybrid multiple criteria decision making (MCDM) approach, combining modified grey Decision-Making Trial and Evaluation Laboratory (DEMATEL), Multi-Attributive Border Approximation area Comparison (MABAC) and sensitivity analysis. Evaluation criteria are grouped into social, differential and beneficial clusters, and the modified DEMATEL procedure is used to derive the criteria weights. The MABAC method is applied to rank the strategic project portfolios according to the aggregated preferences of decision makers (DMs). The usefulness of the proposed research framework is validated with a case study. The GM by-products are found to be the best portfolio. Moreover, this framework can unify the policies of agro technological improvement, corporate social responsibility (CSR) and agro export promotion. Full article
(This article belongs to the Special Issue Advances in Multiple Criteria Decision Making for Sustainability: Modeling and Applications)
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2774 KiB  
Article
Hybrid and Cooperative Strategies Using Harmony Search and Artificial Immune Systems for Solving the Nurse Rostering Problem
by Suk Ho Jin, Ho Yeong Yun, Suk Jae Jeong and Kyung Sup Kim
Sustainability 2017, 9(7), 1090; https://doi.org/10.3390/su9071090 - 22 Jun 2017
Cited by 9 | Viewed by 4367
Abstract
The nurse rostering problem is an important search problem that features many constraints. In a nurse rostering problem, these constraints are defined by processes such as maintaining work regulations, assigning nurse shifts, and considering nurse preferences. A number of approaches to address these [...] Read more.
The nurse rostering problem is an important search problem that features many constraints. In a nurse rostering problem, these constraints are defined by processes such as maintaining work regulations, assigning nurse shifts, and considering nurse preferences. A number of approaches to address these constraints, such as penalty function methods, have been investigated in the literature. We propose two types of hybrid metaheuristic approaches for solving the nurse rostering problem, which are based on combining harmony search techniques and artificial immune systems to balance local and global searches and prevent slow convergence speeds and prematurity. The proposed algorithms are evaluated against a benchmarking dataset of nurse rostering problems; the results show that they identify better or best known solutions compared to those identified in other studies for most instances. The results also show that the combination of harmony search and artificial immune systems is better suited than using single metaheuristic or other hybridization methods for finding upper-bound solutions for nurse rostering problems and discrete optimization problems. Full article
(This article belongs to the Special Issue Advances in Multiple Criteria Decision Making for Sustainability: Modeling and Applications)
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257 KiB  
Article
The Assessment of Real Estate Initiatives to Be Included in the Socially-Responsible Funds
by Fabrizio Battisti, Maria Rosaria Guarini and Anthea Chiovitti
Sustainability 2017, 9(6), 973; https://doi.org/10.3390/su9060973 - 07 Jun 2017
Cited by 8 | Viewed by 3671
Abstract
The acknowledgment of the ongoing economic and financial crisis involving real estate, creates the need to formulate proposals and scenarios (in real estate) with the characteristics of socially responsible investments. These kind of investments aim towards “sustainable” development both environmentally (safeguarding the shortage [...] Read more.
The acknowledgment of the ongoing economic and financial crisis involving real estate, creates the need to formulate proposals and scenarios (in real estate) with the characteristics of socially responsible investments. These kind of investments aim towards “sustainable” development both environmentally (safeguarding the shortage of resources such as land, energy, and natural elements), and socially (protecting the population and raising its level of well-being) according to so-called “ethical finance”, instead of a mere “speculative” investment. Effectively, real estate is still an investment sector only marginally explored by the socially-responsible funds. Based on these premises, this paper will: (i) briefly analyze the nature of socially-responsible investments, setting their characteristics apart from “traditional investments”; and (ii) propose a possible procedure (of the multi-criteria type) which aims to assess socially-responsible investments in real estate. This will be applied to a case study regarding a social housing initiative in the municipality of Anguillara Sabazia (Rome, Italy). Full article
(This article belongs to the Special Issue Advances in Multiple Criteria Decision Making for Sustainability: Modeling and Applications)
2523 KiB  
Article
Multiple Criteria Decision Making (MCDM) Based Economic Analysis of Solar PV System with Respect to Performance Investigation for Indian Market
by Padmanathan K., Uma Govindarajan, Vigna K. Ramachandaramurthy and Sudar Oli Selvi T.
Sustainability 2017, 9(5), 820; https://doi.org/10.3390/su9050820 - 17 May 2017
Cited by 40 | Viewed by 12084
Abstract
Energy market is subject to changing energy demands on a daily basis. The increasing demand for energy necessitates the use of renewable sources and promotes decentralized generation. Specifically, solar PV is preferred in the energy market to meet the increasing energy demand. New [...] Read more.
Energy market is subject to changing energy demands on a daily basis. The increasing demand for energy necessitates the use of renewable sources and promotes decentralized generation. Specifically, solar PV is preferred in the energy market to meet the increasing energy demand. New approaches are preferred in the economic analysis to simulate multiple actor interplays and intermittent behavior in order to predict the increasing complexity in solar PV. In the Indian society, there are various myths and perceptions regarding economics of electricity generated through solar PV system. Therefore, this paper will address the various Life Cycle Cost Analysis (LCCA) and economic analysis for all types of consumers in the Indian electricity market. A detailed economic and performance study is made by considering ten categories and seven sub categories of investment plan for 1 MW solar projects using Multi Criteria Decision Making (MCDM). Analytic Hierarchy Process (AHP) is applied to support the decision. Full article
(This article belongs to the Special Issue Advances in Multiple Criteria Decision Making for Sustainability: Modeling and Applications)
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978 KiB  
Article
Eco-Efficiency Evaluation Considering Environmental Stringency
by Pyoungsoo Lee and You-Jin Park
Sustainability 2017, 9(4), 661; https://doi.org/10.3390/su9040661 - 21 Apr 2017
Cited by 17 | Viewed by 5444
Abstract
This paper proposes an extended data envelopment analysis (DEA) model for deriving eco-efficiency. In order to derive eco-efficiency, the proposed model utilizes the concepts of operational efficiency and environmental efficiency. Since DEA can separately measure operational efficiency and environmental efficiency, the treatment for [...] Read more.
This paper proposes an extended data envelopment analysis (DEA) model for deriving eco-efficiency. In order to derive eco-efficiency, the proposed model utilizes the concepts of operational efficiency and environmental efficiency. Since DEA can separately measure operational efficiency and environmental efficiency, the treatment for constructing the unified indicator is required to ultimately evaluate eco-efficiency through balancing operational and environmental concerns. To achieve this goal, we define the environmental stringency as the business condition reflecting the degree of enforcing environmental regulations across the firms or particular industries in different countries. The proposed model provides flexibility, as required by the pollution-intensity of industry, in that it allows the decision maker to evaluate DMU’s (decision-making unit) eco-efficiency appropriately depending on the business environment. We present a case of agricultural production systems to help readers understand what eco-efficiency becomes when we vary the stringency conditions. Through the illustrative example, this paper presents the potential application by which different environmental stringencies can successively be incorporated in DEA. Full article
(This article belongs to the Special Issue Advances in Multiple Criteria Decision Making for Sustainability: Modeling and Applications)
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1134 KiB  
Article
Risk Assessment for Distribution Systems Using an Improved PEM-Based Method Considering Wind and Photovoltaic Power Distribution
by Qingwu Gong, Jiazhi Lei, Hui Qiao and Jingjing Qiu
Sustainability 2017, 9(4), 491; https://doi.org/10.3390/su9040491 - 24 Mar 2017
Cited by 8 | Viewed by 4168
Abstract
The intermittency and variability of permeated distributed generators (DGs) could cause many critical security and economy risks to distribution systems. This paper applied a certain mathematical distribution to imitate the output variability and uncertainty of DGs. Then, four risk indices—EENS (expected energy not [...] Read more.
The intermittency and variability of permeated distributed generators (DGs) could cause many critical security and economy risks to distribution systems. This paper applied a certain mathematical distribution to imitate the output variability and uncertainty of DGs. Then, four risk indices—EENS (expected energy not supplied), PLC (probability of load curtailment), EFLC (expected frequency of load curtailment), and SI (severity index)—were established to reflect the system risk level of the distribution system. For the certain mathematical distribution of the DGs’ output power, an improved PEM (point estimate method)-based method was proposed to calculate these four system risk indices. In this improved PEM-based method, an enumeration method was used to list the states of distribution systems, and an improved PEM was developed to deal with the uncertainties of DGs, and the value of load curtailment in distribution systems was calculated by an optimal power flow algorithm. Finally, the effectiveness and advantages of this proposed PEM-based method for distribution system assessment were verified by testing a modified IEEE 30-bus system. Simulation results have shown that this proposed PEM-based method has a high computational accuracy and highly reduced computational costs compared with other risk assessment methods and is very effective for risk assessments. Full article
(This article belongs to the Special Issue Advances in Multiple Criteria Decision Making for Sustainability: Modeling and Applications)
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