Investment risk assessment of coal-fired power plants in countries along the Belt and Road initiative based on ANP-Entropy-TODIM method

Yuan, Jiahai; Li, Xinying; Xu, Chuanbo; Zhao, Chen; Liu, Yuanxin

doi:10.1016/j.energy.2019.04.038

Cited by 124 publications

(54 citation statements)

References 55 publications

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“…It is a very important financial decision that can directly affect the enterprise's development. As mentioned before, the nature of investment decision making problems along the B&R is often complicated and uncertain, and MADM methods will be effective for dealing with such problems (Yuan et al, 2019;Duan et al, 2018). It is noted that the investment environment often remains uncertain, and uncertainty is an important factor in MADM process (Bolturk, 2018;Liu et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

INVESTMENT DECISION MAKING ALONG THE B&R USING CRITIC APPROACH IN PROBABILISTIC HESITANT FUZZY ENVIRONMENT

Wang

Zhang

Chen

2020

Journal of Business Economics and Management

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The Belt and Road (B&R) Initiative receives enthusiastic response, the aim of which is to develop cooperative partnerships with countries along the routes and build a community of common destiny. So far, Chinese companies have invested in many different countries along the B&R. Generally, the investment decision making problems are characterized by high risk and uncertainty. Then how to make an appropriate investment decision will be a thorny issue. In this paper, probabilistic hesitant fuzzy set (PHFS) is used for handling uncertainty in multiple attribute decision making (MADM), and the criteria importance through intercriteria correlation (CRITIC) approach is extended to obtain attribute weights, no matter whether the weight information is incompletely known or not. Considering that the existing probabilistic hesitant fuzzy distance measures fail to meet the condition of distance measure, a new distance between PHFSs is proposed and applied to investment decision making for countries along the B&R. In the last, comparative analyses are performed to illustrate the advantages of the presented approach.

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Section: Introductionmentioning

confidence: 99%

INVESTMENT DECISION MAKING ALONG THE B&R USING CRITIC APPROACH IN PROBABILISTIC HESITANT FUZZY ENVIRONMENT

Wang

Zhang

Chen

2020

Journal of Business Economics and Management

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“…Compared with other methods, the entropy method can effectively avoid the subjectivity of index weighting, and objectively conduct evaluations [30][31][32]. Therefore, referring to the literature above, the entropy method was used to calculate the comprehensive evaluation index of resilience of smart cities.…”

Section: The Entropy Evaluation Methodsmentioning

confidence: 99%

Temporal and Spatial Differences in the Resilience of Smart Cities and Their Influencing Factors: Evidence from Non-Provincial Cities in China

et al. 2020

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Based on the sample data of 81 non-provincial smart cities in China in 2017, the comprehensive evaluation index of the resilience of sample cities is calculated by using the entropy method, and the spatial differences of different factors on the resiliency are analyzed by using the geographical weighted regression (GWR) model. The conclusions are as follows: Firstly, the comprehensive evaluation index of the resilience of smart cities presents a spatial distribution characteristic of decreasing from the east to the west. At the same time, the resilience comprehensive index, the public infrastructure resilience capacity index, the economic development resilience index, the social security resilience index, and the ecological environment resilience index of smart cities have obvious agglomeration effects on their geographical spaces. Secondly, the public infrastructure resilience capacity index and the ecological environment resilience index are both low with a discrete distribution, while the economic development resilience index and the social security resilience index are both high with a concentrated distribution. Thirdly, different factors have significantly positive effects on the resilience of smart cities. In particular, the public infrastructure capacity resilience index decreases from the north to the south with the spatial distribution pattern of concentration, the economic development resilience index and the ecological environment resilience index of smart cities decrease from the east to the west with a concentrated spatial distribution pattern, and the social security resilience index of smart cities decreases from the southwest to the northeast with a concentrated spatial distribution pattern. Therefore, it is necessary to enhance awareness of smart cities, strengthen the driving force of science and technology innovation, strengthen public infrastructure and service construction, and continuously improve the rapid resilience of smart cities.

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“…Yuan and Li et al evaluated the overseas investment risk of coal-fired power plants in countries along the Belt and Road initiative. The results showed that Singapore had the lowest risk of coal power investment, followed by New Zealand and Thailand [18]. Kun and Fang discussed the advantages of China's thermal power technology and the drawbacks of overseas investment in environmental protection [19].…”

Section: Literature Review and Research Backgroundmentioning

confidence: 99%

Environmental Stress Testing for China’s Overseas Coal Power Investment Project

et al. 2019

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The advance of the Chinese “Belt and Road” initiative encourages increased overseas investment in coal power projects. However, it also brings about external environmental risks. In this paper, we use the approach of environmental stress testing to examine China’s overseas coal power investment projects by focusing on two countries: Indonesia and Vietnam. We first identify five key testing factors (i.e., coal price, utilization hours, exchange rate, carbon tax, and environmental protection requirements) by examining the market regulation and the environmental risks of coal power projects along the “Belt and Road” countries. Then, we observed changes in the enterprise value and internal rate of return (IRR) by setting different scenarios in which the values of the five stress factors varied. The results show that (1) the economics of coal-fired projects in Indonesia is most sensitive to exchange rate, while the economics of coal projects in Vietnam is most sensitive to coal price; (2) the pressure of nationally determined contributions (NDC) goals on environmental protection will push the “Belt and Road” countries to implement more stringent environmental regulation, which will reinforce environmental stress on overseas coal power investment. These results have important policy implications for the enterprise, industry, and Chinese government.

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Investment risk assessment of coal-fired power plants in countries along the Belt and Road initiative based on ANP-Entropy-TODIM method

Cited by 124 publications

References 55 publications

INVESTMENT DECISION MAKING ALONG THE B&R USING CRITIC APPROACH IN PROBABILISTIC HESITANT FUZZY ENVIRONMENT

INVESTMENT DECISION MAKING ALONG THE B&R USING CRITIC APPROACH IN PROBABILISTIC HESITANT FUZZY ENVIRONMENT

Temporal and Spatial Differences in the Resilience of Smart Cities and Their Influencing Factors: Evidence from Non-Provincial Cities in China

Environmental Stress Testing for China’s Overseas Coal Power Investment Project

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