An Evaluation of the Petroleum Investment Environment in African Oil-Producing Countries Based on Combination Weighting and Uncertainty Measure Theory

Abstract

Recognizing that the evaluation of the overseas petroleum investment environment is affected by many uncertain factors and that there are problems with current evaluation methods, this paper proposes a mathematical evaluation model of an overseas oil resources investment environment, based on a combination of the weighting and uncertainty measure theory. Combining international investment environment theory with the characteristics of the petroleum industry, this paper establishes an evaluation index system for the overseas petroleum investment environment and the linear uncertainty measure function of each index. Using the subjective weight obtained using an analytic hierarchy process together with the objective weight obtained using the entropy weight method, the optimal weight of each evaluation index was obtained using minimum relative information entropy. A multi-index evaluation matrix of the top 12 oil-producing countries in Africa was calculated. Finally, the credible degree recognition criterion was used to judge the order and level of the oil investment environment. This model provides an effective method for the evaluation of the overseas petroleum investment environment. The results show that Nigeria and Angola have the best investment climate, followed by Algeria, Egypt, and Libya. In general, Africa is an important strategic partner of China and is rich in oil resources. Although Africa’s oil industry is fraught with complex challenges and headwinds, challenges also present opportunities.

Evaluation of PPP-ABS investment environment based on combined weighting of level difference maximization and TOPSIS method

“…determine the indicator weights based on experience and knowledge, which can reflect the decision-maker’s preference but may make the evaluation results too subjective. Objective weighting methods, such as entropy [ 53 , 54 ], standard deviation [ 55 ], and criteria importance though intercrieria correlation (CRITIC) [ 56 ], determine the indicator weights based on actual data, but they do not consider the decision-maker’s preferences. The combined weighting method aims to combine the subjective and objective weights based on a specific principle.…”

“…The AHP method was proposed by T. L. Saaty in the early 1970s [ 51 , 58 ]. This method integrates quantitative and qualitative analysis to improve the accuracy of evaluation, and it is widely used in various fields of research [ 53 , 54 ]. The specific steps of the AHP method are as follows:…”

Risk Evaluation of Overseas Mining Investment Based on a Support Vector Machine

“…Therefore, to promote the sustainable, rational, orderly, and healthy development of overseas mining investment and to guide enterprises in the scientific assessment and prevention of overseas mining investment risks, an objective project is large, the cycle is long, and the unpredictable factors are numerous, so the resource-based enterprises face a greater risk [3][4][5]. Therefore, to promote the sustainable, rational, orderly, and healthy development of overseas mining investment and to guide enterprises in the scientific assessment and prevention of overseas mining investment risks, an objective summary of the rules of overseas mining investment and protection against investment risks has strong research value [4,[6][7][8][9][10][11][12]. Therefore, the aim of the present research was to explore how to use scientific methods to perform a quantitative and comprehensive evaluation of the risks faced by China's mining overseas investment, so as to guard against the risks of mining enterprises' overseas investment and protect the rights and interests of China's resources.…”

Sustainable Development of Energy, Water and Environment Systems (SDEWES)

“…The Special Issue concludes with its seventh contribution, by He and all, which mainly deals with economic aspects of sustainability [12]. Specifically, a novel mathematical modelling approach was developed and applied to assess African countries' petroleum investment environment.…”