scholarly journals Green Supplier Evaluation and Selection with an Extended MABAC Method Under the Heterogeneous Information Environment

2019 ◽  
Vol 11 (23) ◽  
pp. 6616 ◽  
Author(s):  
Xu ◽  
Shi ◽  
Zhang ◽  
Liu
Keyword(s):  
Automobile Industry ◽  
Selection Model ◽  
Information Environment ◽  
Production Performance ◽  
Supplier Evaluation ◽  
Interval Numbers ◽  
Heterogeneous Information ◽  
Decision Context ◽  
Green Production ◽  
Green Suppliers

With the increasing awareness of global environmental protection, green production has become a significant part for enterprises to remain in a competitive position. For a manufacturing company, selecting the most suitable green supplier plays an important role in enhancing its green production performance. In this paper, we develop a new green supplier evaluation and selection model through the combination of heterogeneous criteria information and an extended multi-attributive border approximation area comparison (MABAC) method. Considering the complexity of decision context, heterogeneous information, including real numbers, interval numbers, trapezoidal fuzzy numbers, and linguistic hesitant fuzzy sets, is utilized to evaluate alternative suppliers with respect to the selected criteria. A maximizing consensus approach is constructed to determine the weight of each decision-maker based on incomplete weighting information. Then, the classical MABAC method is modified for ranking candidate green suppliers under the heterogeneous information environment. Finally, the developed green supplier selection model is applied in a case study from the automobile industry to illustrate its practicability and efficiency.

scholarly journals A Multi-Attribute Decision Method under Uncertainty Environment Conditions—The Green Supplier Evaluation Perspective

2021 ◽  
Vol 18 (1) ◽  
pp. 344
Author(s):  
Hao Xu ◽  
Liuxin Chen ◽  
Qiongfang Li ◽  
Jianchao Yang
Keyword(s):  
Environmental Pollution ◽  
Evaluation Method ◽  
External Environment ◽  
Environmental Indicators ◽  
Supplier Evaluation ◽  
Uncertain Environment ◽  
Green Suppliers ◽  
Uncertainty Environment ◽  
Selection Of

Due to the continuous changes of political environment, consumption habits, technological progress and other factors, the external environment of enterprises is full of uncertainty. The turbulence of external environment is not conducive to the long-term operation and development of enterprises, but also brings great challenges to the selection of suppliers. This makes the competition of enterprises focus on how to choose long-term cooperation suppliers in the uncertain external environment. In addition, due to the deterioration of the global environment, governments pay more and more attention to environmental pollution, and consumers are more and more inclined to green consumption, which makes many companies pay more and more attention to environmental indicators when selecting suppliers. In the case of external environment turbulence and serious environmental pollution, the evaluation and selection of green suppliers in uncertain environment is particularly important for the long-term development of enterprises. What’s more, when the supplier’s capability gap is small, the decision-maker often hesitates among several suppliers. In this paper, the hesitant fuzzy is used to describe the hesitant psychology of decision-makers in selecting suppliers, the variance fluctuation is used to describe the characteristics of hesitant fuzzy numbers, and the probability is used to measure the uncertainty of the environment. A green supplier evaluation model under the uncertainty environment is proposed, which comprehensively evaluates the green suppliers under the uncertain environment. Furthermore, it is compared with other methods that do not consider the uncertainty and the adaptability of evaluation method and right confirmation method, so as to reflect the influence of uncertainty to green supplier evaluation and the importance of adaptability of evaluation method and right confirmation method.

Implementation of green supplier development process model in Indian automobile industry

2018 ◽  
Vol 29 (5) ◽  
pp. 938-960 ◽  
Author(s):  
Shivangi Viral Thakker ◽  
Santosh B. Rane
Keyword(s):  
Automobile Industry ◽  
Process Model ◽  
Large Scale ◽  
Manufacturing Industry ◽  
Supplier Development ◽  
Journal Articles ◽  
Content Type ◽  
Automobile Components ◽  
Green Suppliers

Purpose The purpose of this paper is to develop a green supplier development (GSD) process model and validate the model with a case study in Indian automobile industry. Design/methodology/approach A literature survey of peer-reviewed journal articles, survey reports and paradigmatic books with managerial impact is done for the research. The process of GSD is modeled using stage-gate approach and KPIV and KPOV of the process are determined. The process model is implemented in an Indian automobile components manufacturing industry for validation. Findings The industry implemented the model with ten suppliers and was able to successfully convert seven of them into Green suppliers. Remaining three suppliers were asked to repeat the process again or terminate the contracts. Model implementation took around three years starting from planning of resources and finances to actual development of suppliers. Research limitations/implications The model implementation was done with a small automobile industry and hence the validation and implications may be generalized by taking the case study further in different industries. It would be beneficial to test the model with case studies of large-scale industries. Practical implications The process model for implementing GSD activities will help managers in taking complex investment decisions. The stages and process inputs and outputs are clearly defined which helps the managers to successfully develop the suppliers. Originality/value This paper puts forward the process model that should be implemented for the successful development of green suppliers. It might represent new opportunities for rigorous and relevant research in the area of green supply chain.

scholarly journals NEW INTEGRATION OF MCDM METHODS AND QFD IN THE SELECTION OF GREEN SUPPLIERS

2016 ◽  
Vol 17 (6) ◽  
pp. 1097-1113 ◽  
Author(s):  
Morteza YAZDANI ◽  
Sarfaraz HASHEMKHANI ZOLFANI ◽  
Edmundas Kazimieras ZAVADSKAS
Keyword(s):  
Supply Chain ◽  
Operations Management ◽  
Evaluation System ◽  
Supplier Selection ◽  
Selection Problem ◽  
Internal Variables ◽  
Supplier Evaluation ◽  
Customer Requirements ◽  
Green Suppliers ◽  
Supplier Selection Problem

Currently, topics of operations management and supply chain systems have been gaining more interest of researchers. Efficiency in supply chain activities and operations management firstly benefit organisations. One of the main operations in supply chain systems is the collaboration with selected suppliers. Various models have been proposed in terms of supplier evaluation and selection studies. The invention of a new integrated frame for the building of an effective supplier evaluation system is a multi-attribute task that consists of several factors as external and internal variables. This paper delivers a creative integrated model of supplier selection problem using SWARA, QFD and a new MCDM tool called WASPAS. This work considers customer attitudes in the process of supplier evaluation. To give more weight to customer requirements, a new SWARA method has been designed; additionally, QFD and the house of quality matrix have been used to transform customer requirements into the supplier evaluation index. Finally, WASPAS has been used to rate the performance of suppliers and present supplier ranking scores. Application of initiative ways to propose a systematic supplier selection problem has always been encouraged by supply chain managers. This topic has been addressed in this paper as well.

scholarly journals Green hydrogen production by solar photocatalysis using Pt-TiO2 nanosheets with reactive facets

2021 ◽  
Vol 28 (2) ◽  
pp. 75-81
Author(s):  
Bin Wang ◽  
Daniel H C Wan ◽  
Altair T F Cheung ◽  
Denis Y C Leung ◽  
Xiao-Ying Lu ◽  
...  
Keyword(s):  
Hydrogen Production ◽  
Diffuse Reflectance Spectroscopy ◽  
Production Performance ◽  
Photocatalytic Hydrogen Production ◽  
X Ray ◽  
Transmission Electron ◽  
Tio2 Nanosheets ◽  
Production Of Hydrogen ◽  
Green Production ◽  
Renewable Hydrogen

Green production of hydrogen is essential for the development of a hydrogen economy. In this study, the photocatalytic water-splitting technology is developed to harness solar energy for production of renewable hydrogen. Pt-TiO2 nanosheets were fabricated by a facile hydrothermal method, followed by photo-reduction of Pt(acac)2 on B,F-codoped TiO2 with reactive facets. The as-prepared photocatalysts were characterised by transmission electron microscopy (TEM), X-ray diffraction (XRD), energy-dispersive X-ray spectroscopy (EDX) and UV-vis diffuse reflectance spectroscopy (DRS). The photocatalytic hydrogen production performance was systematically investigated under UV-visible irradiation. The parametric results indicate that the TiO2 nanosheet structure, Pt loading and photocatalyst concentration have significant impacts on the photocatalytic hydrogen production. The highest hydrogen production rate obtained is 5,086 μmol h-1g-1.

scholarly journals A Mean-Variance Portfolio Selection Model with Interval-Valued Possibility Measures

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Yunyun Sui ◽  
Jiangshan Hu ◽  
Fang Ma
Keyword(s):  
Portfolio Selection ◽  
Return Rate ◽  
Selection Model ◽  
Expected Return ◽  
Interval Numbers ◽  
Numerical Example ◽  
Mean Variance Portfolio ◽  
Portfolio Selection Model ◽  
Mean Variance ◽  
Interval Valued

In recent years, fuzzy set theory and possibility theory have been widely used to deal with an uncertain decision environment characterized by vagueness and ambiguity in the financial market. Considering that the expected return rate of investors may not be a fixed real number but can be an interval number, this paper establishes an interval-valued possibilistic mean-variance portfolio selection model. In this model, the return rate of assets is regarded as a fuzzy number, and the expected return rate of assets is measured by the interval-valued possibilistic mean of fuzzy numbers. Therefore, the possibilistic portfolio selection model is transformed into an interval-valued optimization model. The optimal solution of the model is obtained by using the order relations of interval numbers. Finally, a numerical example is given. Through the numerical example, it is shown that, when compared with the traditional possibilistic model, the proposed model has more constraints and can better reflect investor psychology. It is an extension of the traditional possibilistic model and offers greater flexibility in reflecting investor expectations.

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