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Xiaoya Wei

Bio: Xiaoya Wei is an academic researcher from Shaanxi Normal University. The author has contributed to research in topics: Supply chain & Carbon tax. The author has an hindex of 1, co-authored 1 publications receiving 15 citations.

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Journal ArticleDOI
TL;DR: In this paper, the impact of carbon taxes on supply chain and related operational decisions become hot topics and the research progress in these areas was systematically reviewed and summarized, and future directions were discussed from the perspectives of problem and method.
Abstract: Supply chain has received a great deal of attention both in academia and industry The carbon emissions from supply chain activities are the major concern, therefore, many governments have implemented carbon taxes to promote energy conservation and emission reduction Under this background, the impact of the carbon taxes on supply chain and the related operational decisions become hot topics This paper aimed to review the researches on supply chain management under carbon tax First, the descriptive results and a bibliometric analysis of identified articles during 2010–2019 was presented to clarify the development in this field Then, content analysis is conducted to classify the selected articles into facility location decisions, supplier selection and order quantity, low carbon technology choice and investment, production planning, transportation decisions, pricing decisions, joint decisions and supply chain coordination under carbon taxes The research progress in these areas was systematically reviewed and summarized Finally, future directions were discussed from the perspectives of problem and method

60 citations


Cited by
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Journal ArticleDOI
TL;DR: In this article, the authors used deep learning, support vector machine (SVM), and artificial neural network (ANN) algorithms to forecast GHG emissions from the electricity production sector in Turkey.

96 citations

Journal ArticleDOI
TL;DR: The results indicate that the most important topics today are: cyber-physical systems and smart manufacturing; deep learning and big data; and real-time scheduling algorithms.

58 citations

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TL;DR: Wang et al. as discussed by the authors constructed a DEA-GS (data envelopment analysis and grid search) model from a cost perspective to understand the emission reduction characteristics using a large sample of manufacturing firms from 2008 to 2011.

52 citations

Journal ArticleDOI
TL;DR: This paper proposes combining the rough DEMATEL method and the fuzzy VIKOR (FVIKOR) method to solve sustainable supplier selection problem and determines 15 sustainable supplier evaluation criteria from economic, environmental and social dimensions.
Abstract: In competitive global markets, sustainable suppliers are critical success factors for sustainable supply chain operations. Sustainable supplier selection must be based on a complex network of numerous indicators and experts’ fuzzy linguistic terms. Considering the correlation between the evaluation criteria and the ambiguity of the criteria values, this paper proposes combining the rough DEMATEL method and the fuzzy VIKOR (FVIKOR) method to solve sustainable supplier selection problem. We determine 15 sustainable supplier evaluation criteria from economic, environmental and social dimensions. We also apply the rough DEMATEL method to determine the weight of evaluation indicators that are interrelated or even conflicting and use the FVIKOR method to determine supplier rankings by converting the fuzzy linguistic terms into precise information. The practicability of the proposed method is verified by an example of sustainable supplier selection.

25 citations

Journal ArticleDOI
TL;DR: In this article , an integrated multi-criteria decision-making approach is proposed to achieve environmental sustainability, where the Best Worst Method is used to determine the relative importance of the barriers in the implementation of regulatory policies.

23 citations