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16 pages, 2836 KiB

Open AccessArticle

Hybrid Algorithm Based on an Estimation of Distribution Algorithm and Cuckoo Search for the No Idle Permutation Flow Shop Scheduling Problem with the Total Tardiness Criterion Minimization

by Zewen Sun and Xingsheng Gu

Sustainability 2017, 9(6), 953; https://doi.org/10.3390/su9060953 - 5 Jun 2017

Cited by 14 | Viewed by 4808

Abstract

The no idle permutation flow shop scheduling problem (NIPFSP) is a popular NP-hard combinatorial optimization problem, which exists in several real world production processes. This study proposes a novel hybrid estimation of the distribution algorithm and cuckoo search (CS) algorithm (HEDA_CS) to solve [...] Read more.

The no idle permutation flow shop scheduling problem (NIPFSP) is a popular NP-hard combinatorial optimization problem, which exists in several real world production processes. This study proposes a novel hybrid estimation of the distribution algorithm and cuckoo search (CS) algorithm (HEDA_CS) to solve the NIPFSP with the total tardiness criterion minimization. The problem model is built on the basis of the starting and ending time point of each job. A discrete solution representation method is applied in HEDA_CS to increase the operation efficiency. A novel probability matrix build method is also designed within the knowledge of the processing time matrix. The partially-mapped crossover operation works effectively during the CS phase. A suitable knowledge-based local search is also designed in the HEDA_CS to balance the exploitation and exploration. Finally, many simulations based on the new hard Ruiz benchmarks are conducted. Computational results demonstrate the effectiveness of the proposed HEDA_CS. Full article

(This article belongs to the Special Issue Sustainability of Economic and Management Systems: Perspectives of Uncertainty and Data Driven Optimization)

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8 pages, 420 KiB

Open AccessArticle

The Role of Technology Spillovers in the Process of Water Pollution Abatement for Large International Firms

by Luigi Aldieri and Concetto Paolo Vinci

Sustainability 2017, 9(5), 868; https://doi.org/10.3390/su9050868 - 21 May 2017

Cited by 31 | Viewed by 5676

Abstract

The objective of this paper is to analyze the effects of technology externalities stemming from different technological sectors for international firms engaged both in water pollution abatement and in dirty activities. We present a theoretical framework and an empirical analysis based upon a [...] Read more.

The objective of this paper is to analyze the effects of technology externalities stemming from different technological sectors for international firms engaged both in water pollution abatement and in dirty activities. We present a theoretical framework and an empirical analysis based upon a dataset composed of worldwide R&D-intensive firms. In order to identify the technological proximity between the firms, we construct an original Mahalanobis environmental industry weight matrix, based on the construction of technological vectors for each firm, with European ecological patents distributed across more technology classes. Opportune econometric techniques that deal with the firms’ unobserved heterogeneity and the weak exogeneity of the explanatory variables are implemented. The findings show significant spillover effects on the productivity and environmental performance of the firms. Full article

(This article belongs to the Special Issue Sustainability of Economic and Management Systems: Perspectives of Uncertainty and Data Driven Optimization)

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21 pages, 3805 KiB

Open AccessArticle

Assessing Environmental Impact Indicators in Road Construction Projects in Developing Countries

by Mohamed Marzouk, Eslam Mohammed Abdelkader, Mohamed El-zayat and Ahmed Aboushady

Sustainability 2017, 9(5), 843; https://doi.org/10.3390/su9050843 - 17 May 2017

Cited by 51 | Viewed by 16634

Abstract

Environmental pollution is considered to be one of the main concerns in the construction industry. Environmental pollution has become a major challenge to construction projects due to the huge amount of pollution caused by construction projects. There are different types of environmental impact [...] Read more.

Environmental pollution is considered to be one of the main concerns in the construction industry. Environmental pollution has become a major challenge to construction projects due to the huge amount of pollution caused by construction projects. There are different types of environmental impact indicators, such as the greenhouse gas (GHG) footprint, eutrophication potential (EP), acidification potential (AP), human health (HH) particulate, ozone depletion, and smog. Each of these environmental impact indicators can be linked to different phases of the construction projects. The overall environmental impact indicators can be divided into direct, indirect, and operational emissions. This paper presents a Building Information Modeling (BIM)-based methodology for the assessment of environmental impacts in road construction projects. The model takes into account the overall life cycle of the road construction project, which is divided into: manufacturing phase, transportation phase, construction phase, maintenance phase, operational phase, recycling phase, and deconstruction phase. A case study is presented to demonstrate the applicability of the proposed model. The proposed model solves a major problem for road construction project teams who want to assess the environmental impact indicators associated with their project prior to the start of the execution of their projects. Full article

(This article belongs to the Special Issue Sustainability of Economic and Management Systems: Perspectives of Uncertainty and Data Driven Optimization)

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11 pages, 579 KiB

Open AccessArticle

Optimum Returns from Greenhouse Vegetables under Water Quality and Risk Constraints in the United Arab Emirates

by Eihab Fathelrahman, Mohamed Gheblawi, Safdar Muhammad, Emily Dunn, James C. Ascough II and Timothy R. Green

Sustainability 2017, 9(5), 719; https://doi.org/10.3390/su9050719 - 29 Apr 2017

Cited by 7 | Viewed by 5720

Abstract

Greenhouses have been used in the United Arab Emirates (UAE) to produce vegetables that contribute toward UAE food security, including offering fresh vegetable produce in the off-season. However, to manage such greenhouses, farmers face both technical and environmental limitations (i.e., high water scarcity), [...] Read more.

Greenhouses have been used in the United Arab Emirates (UAE) to produce vegetables that contribute toward UAE food security, including offering fresh vegetable produce in the off-season. However, to manage such greenhouses, farmers face both technical and environmental limitations (i.e., high water scarcity), as well as vegetable market price instability. The objective of this study is to explore tradeoffs between returns (i.e., gross margin) of selected vegetables (tomato, pepper, and cucumber), risk (deviation from gross margin means), and an environmental constraint (water salinity) using a unique target MOTAD (minimization of total absolute deviations) approach to support UAE farmer decision-making processes. The optimal target MOTAD solution included all three vegetables and no corner solution. The results showed tradeoffs between returns and risks, and confirmed that product diversification reduces overall risk. The analysis was consistent with farmer perceptions based on a survey of 78 producers in the region. The search for the optimal mix of vegetable production under UAE greenhouse conditions revealed that reduction in tomato production should be offset by an increase in cucumber production while maintaining a constant level of pepper production. In other words, risk is reduced as cucumber production increases due to the high level of tomato and lettuce price volatility as the alternative to cucumber. The results also demonstrated the importance of the water salinity environmental constraint, as it was found to have a positive marginal value in the optimal vegetable mix solution (i.e., important factor). Thus the optimal solution was highly sensitive to changes in the crop water salinity constraint. The study results also demonstrate that the target MOTAD approach is a suitable optimization methodology. As a practical approach, a decision-maker in the UAE can consider gross margin (total revenue-variable costs) maximization with risk and water quality constraints to find the optimal vegetable product mix under greenhouse conditions. Full article

(This article belongs to the Special Issue Sustainability of Economic and Management Systems: Perspectives of Uncertainty and Data Driven Optimization)

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12 pages, 504 KiB

Open AccessArticle

Explore the Buffering Effects of Perceived Hidden Inflation on Survival of Mobile Phone Service Providers in Taiwan

by Sheng-Wen Liu, Ying-Chieh Yang and Ralph Norcio

Sustainability 2017, 9(4), 555; https://doi.org/10.3390/su9040555 - 6 Apr 2017

Cited by 4 | Viewed by 4644

Abstract

The purpose of this study is to examine the moderating role of perceived hidden inflation on the relationships between service quality, brand trust and brand loyalty. All data collected from the target population are analyzed through two-step structural equation modeling (SEM) and moderated [...] Read more.

The purpose of this study is to examine the moderating role of perceived hidden inflation on the relationships between service quality, brand trust and brand loyalty. All data collected from the target population are analyzed through two-step structural equation modeling (SEM) and moderated multiple regression (MMR) to examine the hypotheses. 1,050 questionnaires are randomly distributed at 21 telecommunication service stores in Taiwan. Findings indicated that service quality has no direct impact on behavioral loyalty but it has a significant indirect impact on behavioral loyalty through brand trust or attitudinal loyalty. Moreover, findings identify perceived hidden inflation as the moderating role in the service quality–brand trust–brand loyalty chain. Besides the need for empirical confirmation of the hypotheses given, finally, there are several practical implications for service marketers and future research directions for scholars. Full article

(This article belongs to the Special Issue Sustainability of Economic and Management Systems: Perspectives of Uncertainty and Data Driven Optimization)

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17 pages, 708 KiB

Open AccessArticle

Optimal Remanufacturing Certification Contracts in the Electrical and Electronic Industry

by Huihui Liu, Xiaohang Yue, Hui Ding and G. Keong Leong

Sustainability 2017, 9(4), 516; https://doi.org/10.3390/su9040516 - 30 Mar 2017

Cited by 13 | Viewed by 4628

Abstract

While remanufacturing is highly encouraged worldwide, some original equipment manufacturers (OEMs) in the electrical and electronics industry are still not willing to embrace remanufacturing, for fear of expensive investment or the cannibalization of existing products. Meanwhile, third-party remanufacturers’ (TPRs) remanufactured products are developing [...] Read more.

While remanufacturing is highly encouraged worldwide, some original equipment manufacturers (OEMs) in the electrical and electronics industry are still not willing to embrace remanufacturing, for fear of expensive investment or the cannibalization of existing products. Meanwhile, third-party remanufacturers’ (TPRs) remanufactured products are developing quickly. Due to quality reasons, consumers usually have a higher preference for OEM-certified remanufactured products than uncertified ones. As such, remanufacturing certification has become a strategy that OEMs can use to benefit from product remanufacturing. Our paper focuses on the remanufacturing certification contract between an OEM and a TPR. Once certified, the TPR makes payments to the OEM. These payment terms will affect their enthusiasm for participating in remanufacturing certification. By establishing game models among an OEM, a certified TPR, and an uncertified TPR, our paper explores three certification contracts, namely, the lump-sum payment, profit-sharing payment, and piece-rate payment. We identify the conditions for the OEM and certified TPR to reach a win-win outcome. Our results show that when TPRs have a high profit margin and there is no significant difference in consumers’ preferences between certified and non-certified remanufacturing channels, the profit-sharing payment contract yields the highest profit; otherwise, the piece-rate payment contract is best for the OEM. Full article

(This article belongs to the Special Issue Sustainability of Economic and Management Systems: Perspectives of Uncertainty and Data Driven Optimization)

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19 pages, 2467 KiB

Open AccessArticle

Industry Interdependence Dynamics and Structure Change Causal Analysis: An Empirical Study on China’s Shipbuilding Industry

by Xiaofeng Xu, Jun Hao and Yirui Deng

Sustainability 2017, 9(4), 517; https://doi.org/10.3390/su9040517 - 29 Mar 2017

Cited by 2 | Viewed by 5522

Abstract

Based on empirical evidence from Yangtze River Delta, Pearl River Delta and Circum-Bohai-Sea region, this study applies the Input-Output (I-O) model and ArcGIS to analyze the interdependence and its dynamic evolution of the shipbuilding industry. In order to study the change cause of [...] Read more.

Based on empirical evidence from Yangtze River Delta, Pearl River Delta and Circum-Bohai-Sea region, this study applies the Input-Output (I-O) model and ArcGIS to analyze the interdependence and its dynamic evolution of the shipbuilding industry. In order to study the change cause of shipbuilding industrial structure, we decompose the I-O model to obtain the influential factors including domestic final demand, overseas export demand, intermediate input, intermediate demand import and final demand import. The results indicate that (1) the shipbuilding industry has a significant interdependence, which has showed the characteristics of high integration and interaction. Among the three different regions, the degree of interdependence of the Yangtze River Delta is most significant, followed by the Pearl River Delta and the Circum-Bohai region. (2) The interaction and integration of the shipbuilding industry have the trend of synchronous development. From the initial S-shapes of coastal distribution, the interaction gradually expands to inland cities radially. (3) The dependence of the shipbuilding industry has reduced but the self-supporting effect continuously strengthened, and industrialization is accelerating, which indicates the shipbuilding industry will further promote the optimization of industrial structure. (4) Shipbuilding industry has been expanding a lot, the main causes of changes in industrial structure are different, and the effect of intermediate inputs change plays a significant role in the Yangtze River Delta. In the Pearl River Delta, it is the changes effect of foreign export demand that counts. However, it is the effect of the final demand that makes contribution to the industrial structure change in Circum-Bohai-Sea region. Full article

(This article belongs to the Special Issue Sustainability of Economic and Management Systems: Perspectives of Uncertainty and Data Driven Optimization)

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11 pages, 858 KiB

Open AccessArticle

Using Fuzzy DEA for Green Suppliers Selection Considering Carbon Footprints

by Min-Chun Yu and Min-Hong Su

Sustainability 2017, 9(4), 495; https://doi.org/10.3390/su9040495 - 25 Mar 2017

Cited by 31 | Viewed by 4879

Abstract

Due to increasing global environmental awareness, supply chains that consider environmental protection tend to be favored by green-minded customers. In addition to adapting to the technology required for green supply chains and developing contingency plans, organizations must consider reducing their carbon footprint to [...] Read more.

Due to increasing global environmental awareness, supply chains that consider environmental protection tend to be favored by green-minded customers. In addition to adapting to the technology required for green supply chains and developing contingency plans, organizations must consider reducing their carbon footprint to meet corporate objectives and reducing their carbon footprint. To address this issue, this paper aims at establishing a decision-making process for buyers with sustainability in mind. A fuzzy data envelopment analysis (FDEA) model was developed to select the most suitable supplier. Production costs, lead time, and supply chain carbon footprints were used as the input criteria, and quality and demand quantity were used as the output criteria. Buyer-seller supply chains and non-cooperative and cooperative models were employed separately to calculate associative efficiency. Sensitivity analysis was conducted to understand the effects carbon footprints have on efficiency. This study found that suppliers with low carbon footprints exhibited poor efficiency, which may be attributed to the additional effort required to select raw materials. Additionally, suppliers with different supply chain operation models exhibited differing efficiencies. Therefore, suppliers must consider the balance between carbon footprint reduction and costs, and buyers must consider environmental criteria when selecting green suppliers. Full article

(This article belongs to the Special Issue Sustainability of Economic and Management Systems: Perspectives of Uncertainty and Data Driven Optimization)

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17 pages, 978 KiB

Open AccessArticle

Compromise between Short- and Long-Term Financial Sustainability: A Hybrid Model for Supporting R&D Decisions

by Kao-Yi Shen

Sustainability 2017, 9(3), 375; https://doi.org/10.3390/su9030375 - 4 Mar 2017

Cited by 9 | Viewed by 6428

Abstract

The debate of “short-termism” has gained increasing interests from various fields, ranging from management to economics; it mainly concerns the decisions or actions taken by businesses that might yield short-term returns at the cost of long-term value or sustainability. Previous studies have highlighted [...] Read more.

The debate of “short-termism” has gained increasing interests from various fields, ranging from management to economics; it mainly concerns the decisions or actions taken by businesses that might yield short-term returns at the cost of long-term value or sustainability. Previous studies have highlighted this dilemma faced by managers, mainly from the pressure of capital markets or short-sighted shareholders who crave for immediate financial outcomes; intelligent decision aids that can compromise between the short- and long-term financial sustainability, based on a company’s policy, are highly needed. Therefore, the aim of this study is to develop a multiple-rule-based hybrid decision model to support management teams on prioritizing new R&D projects, considering the financial prospects in dual timeframes (i.e., short- and long-term) for sustainability. Furthermore, in the presence of business uncertainty and the limited knowledge of managers on new projects, the intuitionistic fuzzy technique is incorporated. A case of selecting new R&D projects for an IC design company is illustrated using the proposed approach, and the financial data from a group of public-listed IC stocks from Taiwan are inducted to form the decision model. The findings not only support the IC design company to select new projects but also provide business insights to facilitate the understandings of this controversial issue in managerial practice. Full article

(This article belongs to the Special Issue Sustainability of Economic and Management Systems: Perspectives of Uncertainty and Data Driven Optimization)

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15 pages, 4606 KiB

Open AccessArticle

The Suitability of Different Nighttime Light Data for GDP Estimation at Different Spatial Scales and Regional Levels

by Zhaoxin Dai, Yunfeng Hu and Guanhua Zhao

Sustainability 2017, 9(2), 305; https://doi.org/10.3390/su9020305 - 19 Feb 2017

Cited by 100 | Viewed by 10100

Abstract

Nighttime light data offer a unique view of the Earth’s surface and can be used to estimate the spatial distribution of gross domestic product (GDP). Historically, using a simple regression function, the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) has been used [...] Read more.

Nighttime light data offer a unique view of the Earth’s surface and can be used to estimate the spatial distribution of gross domestic product (GDP). Historically, using a simple regression function, the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) has been used to correlate regional and global GDP values. In early 2013, the first global Suomi National Polar-orbiting Partnership (NPP) visible infrared imaging radiometer suite (VIIRS) nighttime light data were released. Compared with DMSP/OLS, they have a higher spatial resolution and a wider radiometric detection range. This paper aims to study the suitability of the two nighttime light data sources for estimating the GDP relationship between the provincial and city levels in Mainland China, as well as of different regression functions. First, NPP/VIIRS nighttime light data for 2014 are corrected with DMSP/OLS data for 2013 to reduce the background noise in the original data. Subsequently, three regression functions are used to estimate the relationship between nighttime light data and GDP statistical data at the provincial and city levels in Mainland China. Then, through the comparison of the relative residual error (RE) and the relative root mean square error (RRMSE) parameters, a systematical assessment of the suitability of the GDP estimation is provided. The results show that the NPP/VIIRS nighttime light data are better than the DMSP/OLS data for GDP estimation, whether at the provincial or city level, and that the power function and polynomial models are better for GDP estimation than the linear regression model. This study reveals that the accuracy of GDP estimation based on nighttime light data is affected by the resolution of the data and the spatial scale of the study area, as well as by the land cover types and industrial structures of the study area. Full article

(This article belongs to the Special Issue Sustainability of Economic and Management Systems: Perspectives of Uncertainty and Data Driven Optimization)

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20 pages, 2704 KiB

Open AccessArticle

Income Driven Patterns of the Urban Environment

by Anibal Gusso, André Silva, John Boland, Leticia Lenz and Conrad Philipp

Sustainability 2017, 9(2), 275; https://doi.org/10.3390/su9020275 - 15 Feb 2017

Cited by 2 | Viewed by 5718

Abstract

This study investigates the land surface temperature (LST) distribution from thermal infrared data for analyzing the characteristics of surface coverage using the Vegetation–Impervious–Soil (VIS) approach. A set of ten images, obtained from Landsat-5 Thematic Mapper, between 2001 and 2010, were used to study [...] Read more.

This study investigates the land surface temperature (LST) distribution from thermal infrared data for analyzing the characteristics of surface coverage using the Vegetation–Impervious–Soil (VIS) approach. A set of ten images, obtained from Landsat-5 Thematic Mapper, between 2001 and 2010, were used to study the urban environmental conditions of 47 neighborhoods of Porto Alegre city, Brazil. Porto Alegre has had the smallest population growth rate of all 27 state capitals in the last two decades in Brazil, with an increase of 11.55% in inhabitants from 1.263 million in 1991 to 1.409 million in 2010. We applied the environmental Kuznets curve (EKC) theory in order to test the influence of the economically-related scenario on the spatial nature of social-environmental arrangement of the city at neighborhood scale. Our results suggest that the economically-related scenario exerts a non-negligible influence on the physically driven characteristics of the urban environmental conditions as predicted by EKC theory. The linear inverse correlation R² between household income (HI) and LST is 0.36 and has shown to be comparable to all other studied variables. Future research may investigate the relation between other economically-related indicators to specific land surface characteristics. Full article

(This article belongs to the Special Issue Sustainability of Economic and Management Systems: Perspectives of Uncertainty and Data Driven Optimization)

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18 pages, 1076 KiB

Open AccessArticle

The Financial Crisis and Co-Movement of Global Stock Markets—A Case of Six Major Economies

by Yonghong Jiang, Mengmeng Yu and Shabir Mohsin Hashmi

Sustainability 2017, 9(2), 260; https://doi.org/10.3390/su9020260 - 13 Feb 2017

Cited by 39 | Viewed by 6601

Abstract

This paper investigates the impact of recent financial crisis on six major stock markets during the three periods. To measure the impact of the crisis on different stock markets, we have applied a vector auto-regression (VAR) model and conducted Granger causality tests. The [...] Read more.

This paper investigates the impact of recent financial crisis on six major stock markets during the three periods. To measure the impact of the crisis on different stock markets, we have applied a vector auto-regression (VAR) model and conducted Granger causality tests. The data used in this study, consists of time series of daily stock market indices at closing time, in terms of local currency units of the world’s six major stock markets which were affected during the financial crisis, while the sample period was divided into several sub-periods. The main objectives of the research was to discover the degree of interdependence of the six stock markets and trace out the Granger causality relationships and dynamic responses of one market to in another in innovation, and to make a comparison on the degree of the co-movements in three periods, namely, the pre-crisis period, crisis period, and post-crisis periods. The results suggest that the financial crisis has reinforced the interdependence relationship of global stock markets. However, general co-movements of global stock markets persist even after the crisis and still remained stronger in some economies. Full article

(This article belongs to the Special Issue Sustainability of Economic and Management Systems: Perspectives of Uncertainty and Data Driven Optimization)

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19 pages, 8260 KiB

Open AccessArticle

DEA Efficiency of Energy Consumption in China’s Manufacturing Sectors with Environmental Regulation Policy Constraints

by Xiaoqing Chen and Zaiwu Gong

Sustainability 2017, 9(2), 210; https://doi.org/10.3390/su9020210 - 4 Feb 2017

Cited by 36 | Viewed by 7612

Abstract

Because overall energy consumption intensity in China’s manufacturing industry is extremely high, the study of energy efficiency in that industry, with an analysis of the policy impacts of energy intensity reduction and other key factors, will no doubt improve energy utilization in the [...] Read more.

Because overall energy consumption intensity in China’s manufacturing industry is extremely high, the study of energy efficiency in that industry, with an analysis of the policy impacts of energy intensity reduction and other key factors, will no doubt improve energy utilization in the industry and stimulate sustainable development within it. This paper uses 2004–2014 panel data of 28 manufacturing industries and a piecewise linear utility function to construct a data envelopment analysis (DEA) model of energy consumption with environmental regulations constraints. We also examine the DEA evaluation of energy efficiency in manufacturing industries. We integrate environmental regulations as qualitative variables into the energy consumption evaluation model to research the coupling effects on energy consumption intensity of energy consumption structure, opening up, environmental regulations, technological progress, and competition within industries. The research shows that energy efficiency policy intensity is not the major effect on the development of low or moderate energy-consumption industries, whereas low-energy-efficiency policy is very favorable for the development of high energy-consumption industries. Full article

(This article belongs to the Special Issue Sustainability of Economic and Management Systems: Perspectives of Uncertainty and Data Driven Optimization)

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14 pages, 409 KiB

Open AccessArticle

Comprehensive Evaluation on Employee Satisfaction of Mine Occupational Health and Safety Management System Based on Improved AHP and 2-Tuple Linguistic Information

by Jiangdong Bao, Jan Johansson and Jingdong Zhang

Sustainability 2017, 9(1), 133; https://doi.org/10.3390/su9010133 - 18 Jan 2017

Cited by 13 | Viewed by 5476

Abstract

In order to comprehensively evaluate the employee satisfaction of mine occupational health and safety management system, an analytic method based on fuzzy analytic hierarchy process and 2-tuple linguistic model was established. Based on the establishment of 5 first-grade indicators and 20 second-grade ones, [...] Read more.

In order to comprehensively evaluate the employee satisfaction of mine occupational health and safety management system, an analytic method based on fuzzy analytic hierarchy process and 2-tuple linguistic model was established. Based on the establishment of 5 first-grade indicators and 20 second-grade ones, method of improved AHP and the time-ordered Weighted Averaging Operator (T-OWA) model is constructed. The results demonstrate that the employee satisfaction of the mine occupational health and safety management system is of the ‘general’ rank. The method including the evaluation of employee satisfaction and the quantitative analysis of language evaluation information ensures the authenticity of the language evaluation information. Full article

(This article belongs to the Special Issue Sustainability of Economic and Management Systems: Perspectives of Uncertainty and Data Driven Optimization)

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16 pages, 1489 KiB

Open AccessArticle

A Fuzzy Expression Way for Air Quality Index with More Comprehensive Information

by Yujie Wang, Mingxuan Zhao, Yulin Han and Jian Zhou

Sustainability 2017, 9(1), 83; https://doi.org/10.3390/su9010083 - 9 Jan 2017

Cited by 7 | Viewed by 5778

Abstract

The Air Quality Index (AQI) is an evaluating indicator for the atmospheric environment released by various environmental monitoring centers to communicate the present air quality status to the public, which is calculated by the aid of the monitored concentrations of six common air [...] Read more.

The Air Quality Index (AQI) is an evaluating indicator for the atmospheric environment released by various environmental monitoring centers to communicate the present air quality status to the public, which is calculated by the aid of the monitored concentrations of six common air pollutants and relevant computational formulae. Considering that the historical data of daily overall AQI illustrated by the traditional expression way merely contain limited information about the original data, this paper puts forward a more concrete and intuitive way to express the air quality in the past day. By analyzing the data concerning individual air quality indices of pollutants gathered from five cities of China for six consecutive months and conducting the curve fitting, each sub-index is recommended to be set as a Gaussian fuzzy number. Accordingly, taking advantage of the novel operational law for fuzzy numbers, the fuzzy distribution and membership function of the daily overall AQI can be deduced immediately, which as a reference contributes to the users acquiring the information more intuitively and facilitates making plans or decisions. Subsequently, a case study taking Shanghai as a background is conducted to elaborate the application of the proposed approach. Furthermore, the line chart reflecting the overall air quality status in a past period is depicted, based on which an example of selecting a tourist destination is given to demonstrate its utilization. Full article

(This article belongs to the Special Issue Sustainability of Economic and Management Systems: Perspectives of Uncertainty and Data Driven Optimization)

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10 pages, 248 KiB

Open AccessArticle

Valuing Interest Rate Swap Contracts in Uncertain Financial Market

by Chen Xiao, Yi Zhang and Zongfei Fu

Sustainability 2016, 8(11), 1186; https://doi.org/10.3390/su8111186 - 18 Nov 2016

Cited by 14 | Viewed by 5457

Abstract

Swap is a financial contract between two counterparties who agree to exchange one cash flow stream for another, according to some predetermined rules. When the cash flows are fixed rate interest and floating rate interest, the swap is called an interest rate swap. [...] Read more.

Swap is a financial contract between two counterparties who agree to exchange one cash flow stream for another, according to some predetermined rules. When the cash flows are fixed rate interest and floating rate interest, the swap is called an interest rate swap. This paper investigates two valuation models of the interest rate swap contracts in the uncertain financial market. The new models are based on belief degrees, and require relatively less historical data compared to the traditional probability models. The first valuation model is designed for a mean-reversion term structure, while the second is designed for a term structure with hump effect. Explicit solutions are developed by using the Yao–Chen formula. Moreover, a numerical method is designed to calculate the value of the interest rate swap alternatively. Finally, two examples are given to show their applications and comparisons. Full article

(This article belongs to the Special Issue Sustainability of Economic and Management Systems: Perspectives of Uncertainty and Data Driven Optimization)

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Jump to: Research

1 pages, 124 KiB

Open AccessErratum

Erratum: Marzouk, M., et al. Assessing Environmental Impact Indicators in Road Construction Projects in Developing Countries. Sustainability 2017, 9, 843

by Mohamed Marzouk, Eslam Mohammed Abdelkader, Mohamed El-zayat and Ahmed Aboushady

Sustainability 2017, 9(10), 1736; https://doi.org/10.3390/su9101736 - 26 Sep 2017

Viewed by 3464

Abstract

The authors of this paper [1] have agreed they would like to add Eslam Mohammed Abdelkader as the second co-author, as he made a significant contribution to the research methodology [...]
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(This article belongs to the Special Issue Sustainability of Economic and Management Systems: Perspectives of Uncertainty and Data Driven Optimization)

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