Applying blockchain to supply chain financing is an effective way to solve the problems of financing difficulties, high financing costs, and slow financing for small and medium-sized enterprises (SMZEs). Using evolutionary game theory, this study constructs a tripartite game model and analyzes the influence of blockchain technology on the evolutionary stability strategies for financial institutions (FIs), core enterprises (CEs), and SMZEs, in which the default losses of CEs and SMZEs are assumed to be dynamic. The results of this study are as follows: (1) When CEs and SMZESs’ default losses are lower than some critical value, they tend to break their promises. (2) When accounts receivable are greater than some critical value, CEs cannot repay on time because they can make a relatively large profits from delayed repayment, whereas SMZEs can be constrained to be trustworthy. Finally, the results using numerical simulation show that both relatively large default losses and enough large, trustworthy income sources can make CEs and SMZEs tend to keep their promises; in turn, CEs would be non-paying and the SMZEs tend to be trustworthy for relatively large accounts receivable. The results provide theoretical support for realizing healthy and sustainable development for supply chain finance.

The water environment treatment public-private partnership (PPP) project has a long cooperation period, large investment scale, high technical requirements, and more complex risks, which are very important to identifying and preventing risks. This paper establishes a risk evaluation model for water environmental treatment PPP projects based on the intuitionistic fuzzy Multi-Objective Optimization on the basis of a Ratio Analysis plus the full Multiplicative form (MULTIMOORA) improved Failure Mode and Effects Analysis (FMEA) method. Firstly, the risk indicators system of the water environmental treatment PPP project was constructed through the literature frequency statistics method and semi-structured interviews. Subsequently, the intuitionistic fuzzy FMEA method was used to assess the risk factors in terms of three aspects—occurrence(O), severity(S), and non-detectability(D)—and gather expert information, and the expert assessment method and deviation maximization model method were applied to assign the risk factors. Finally, Intuitionistic fuzzy Multi-Objective Optimization on the basis of a Ratio Analysis plus the full Multiplicative form (IF-MULTIMOORA) was applied to determine the risk indicator ranking and was combined with the water environmental treatment PPP project in Pingyu for example verification. The results show that the top five risk levels of PPP projects in Pingyu water environmental treatment are financing risk (changing financing conditions/high costs), market changes, government intervention and credit problems, imperfect legal and regulatory systems, and inflation. The risk assessment model proposed in this paper enables: (1) the evaluation of risk indicators from three perspectives, which is more accurate and comprehensive; (2) the introduction of intuitionistic fuzzy risk factor language variables to reasonably represent expert views; (3) the use of IF-MULTIMOORA for risk ranking to avoid the problem that RNP is the same and difficult to rank. This paper has important practical significance in promoting risk prevention and achieving the sustainable development of water environment treatment PPP projects.

Pythagorean fuzzy sets (PFSs), as an extension of intuitionistic fuzzy sets (IFSs) for dealing with uncertainty information, have attracted considerable attention in the decision-making area. The Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method is one of the most popular decision-making approaches. In the TOPSIS method, the desired alternative should have not only the shortest distance from the positive ideal solution, but also the farthest distance from the negative ideal solution. Similarity measures play an important role in assessing the degree between ideal and proposal alternatives in decision-making. Thus, this paper aims to provide an extended TOPSIS by developing new similarity measures with PFSs and applying it to multi-criteria decision-making (MCDM) problems. The main contributions of this paper are as follows: (1) development of three new similarity measures with PFSs, and investigation of their properties; (2) extension of the TOPSIS method based on the proposed similarity measures; and (3) establishment of a Pythagorean fuzzy decision-making method using the improved TOPSIS method. A case study on the selection of a project delivery system is conducted to show the applicability of the presented approach.

Purpose: The optimal payment in the whole operation and maintenance period of water environment treatment PPP projects has become the main approach to realize sustainable development of projects. This study is aimed at constructing an effective payment model for the whole life period of projects to achieve win-win among all stakeholders, so as to provide a theoretical reference and managerial implications for the public sector in the whole operation and maintenance period.Design/methodology/approach: In the whole operation and maintenance period of water environment treatment PPP projects, this article investigates how the public sector optimizes the payment in the whole operation and maintenance period of projects. Firstly, the projects' whole operation and maintenance period is divided into several stages according to the performance appraisal period. And then, the multi-stage dynamic programming model is constructed to design the payment construct model for the public sector in each performance appraisal stage. The payment from the public sector is the decision variable, and the deduction from the private sector is a random variable.Findings: The optimal payment model showed that the relatively less objective weight of public sector leaded to its relatively more total payment and vice versa. Therefore, the sustainable development of the projects can only be ensured when the objective weights both of them should be balanced. Additionally, the deduction from the performance appraisal of private sector plays an important role in the model construction. The larger deduction the private sector undertakes, the smaller profits private sector has. Since the deduction at each stage is a random variable, the deduction varies with the different probability distributions obeyed by the practical deduction in each stage.Research limitations/implications: The findings from this study have provided theoretical and application references, and some managerial implications are also given. First, the improvement of the pricing system of public sector should be accelerated. Second, the reasonable profit of the private sector must be guaranteed. While pursuing the maximization of social benefits, the public sector should make full use of the price sharing mechanism in the market and supervise the real income situation of the private sector. Third is increasing the public to participate in pricing. Additionally, it is a limitation that the deduction is assumed to conform to a uniform distribution in this study. Other probability distributions on deduction can be essentially further sought, so as to be more line with the actual situation of the projects.Originality/value: The optimal payment in whole operation and maintenance period of the projects has become an important issue, which is a key to project success. This study constructs a multi-stage dynamic programming model to optimize payment in the whole period of projects. Additionally, this study adds its value through deeply developing the new theories of optimal payment to more suitable for the practical problems, so that to optimize the design of payment mechanism. Meanwhile, a valuable reference for public and private sectors is provided to ensure the sustainable development of the projects.