Evaluation of government investment using nested probabilistic linguistic preference relations based on graph theory

Abstract

Government investment, as a major government function, is closely related to national development and economic growth. It plays a key role to maximize the benefits of this fund, which requires the government to choose the optimal investment plan. Considering the complex and uncertain decision-making environment, we propose the nested probabilistic linguistic preference relation (NPLPR) based on the nested probabilistic linguistic term sets (NPLTSs), to express preference information from the qualitative and quantitative angle. According to graph theory, we define a consistency index and an acceptable consistency of NPLPR to measure the additive consistency. Based on which, we establish a novel algorithm for unacceptable consistent NPLPR to meet the acceptable consistency. Finally, projects in government investment are evaluated by the proposed decision-making method, and some comparative analyses, discussions, and implications are provided from three angles. This study provides a new perspective for scholars to make scientific and rational decisions with the help of technological and economic development in various fields.

Keywords

• government investment
• nested probabilistic linguistic term sets
• nested probabilistic linguistic preference relation
• consistency check
• graph theory
• cognitive decision-making