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This study aimed to address a gap in subcontractor management by focusing on previously unexplored complexities surrounding subcontractor management in developing countries. While past studies concentrated on selection and relationships, this study delved into how effective subcontractor management impacts project success.

This study used the Bayesian Network analysis approach, through a meticulously developed questionnaire survey refined through a piloting stage involving experienced industry professionals. The survey was ultimately distributed among participants based in Accra, Ghana, resulting in a response rate of approximately 63%.

The research identified diverse components contributing to subcontractor disruptions, highlighted the necessity of a clear regulatory framework, emphasized the impact of financial and leadership assessments on performance, and underscored the crucial role of main contractors in Integrated Project and Labour Cost Management with Subcontractor Oversight and Coordination.

Previous studies have not considered the challenges subcontractors face in projects. This investigation bridges this gap from multiple perspectives, using Bayesian network analysis to enhance subcontractor management, thereby contributing to the successful completion of construction projects.

Climate change-related weather events significantly affect rice production. In this paper, we investigate the impact of and interrelationships between agriculture inputs, climate change factors and financial variables on rice production in India from 1970–2021.

This study is based on the time series analysis; the unit root test has been employed to unveil the integration order. Further, the study used various econometric techniques, including vector autoregression estimates (VAR), cointegration test, autoregressive distributed lag (ARDL) model and diagnostic test for ARDL, fully modified least squares (FMOLS), canonical cointegrating regression (CCR), impulse response functions (IRF) and the variance decomposition method (VDM) to validate the long- and short-term impacts of climate change on rice production in India of the scrutinized variables.

The study's findings revealed that the rice area, precipitation and maximum temperature have a significant and positive impact on rice production in the short run. In the long run, rice area (ß = 1.162), pesticide consumption (ß = 0.089) and domestic credit to private sector (ß = 0.068) have a positive and significant impact on rice production. The results show that minimum temperature and direct institutional credit for agriculture have a significant but negative impact on rice production in the short run. Minimum temperature, pesticide consumption, domestic credit to the private sector and direct institutional credit for agriculture have a negative and significant impact on rice production in the long run.

The present study makes valuable and original contributions to the literature by examining the short- and long-term impacts of climate change on rice production in India over 1970–2021. To the best of the authors’ knowledge, The majority of the studies examined the impact of climate change on rice production with the consideration of only “mean temperature” as one of the climatic variables, while in the present study, the authors have considered both minimum as well as maximum temperature. Furthermore, the authors also considered the financial variables in the model.

The study aims to address a critical gap in existing healthcare payment schemes and care service pricing by recognizing the influential role of patients' decisions on self-management efforts. These decisions not only impact health outcomes but also shape the demand for care, subsequently influencing care costs. Despite the significance of this interplay, current payment schemes often overlook these dynamics. The research focuses on investigating the implications of a novel behavior-based payment scheme, designed to align incentives and establish a direct connection between patients' decisions and care costs. The primary objective is to comprehensively understand whether and how this innovative payment scheme structure influences key stakeholders, including patients, care providers, insurers and overall social welfare.

In this paper, we propose a game-theoretical model to incorporate the performance of self-management with the demand for healthcare service, compare the patient's effort decision for self-management and provider's price decision for healthcare service under a behavior-based scheme with that under two implemented widely payment schemes, that is, co-payment scheme and co-insurance scheme.

Our findings confirm that the behavior-based scheme incentives patient self-management more than current schemes while reducing their possibility of seeking healthcare service, which indirectly induces the provider to lower the price of the service. The stakeholders' utility under various payment schemes is sensitive to the cost of treatment and the perceived health utility of patients. Especially, patient health awareness is not always benefited provider profit, as it motivates patient self-management while diminishing the demand for care.

We provide a novel framework for characterizing behavior-based payment schemes. Our results confirm the need for modification of the current payment scheme to incentivize patient self-management.

The paper aims to elucidate effective strategies for promoting the adoption of green technology innovation within the private sector, thereby enhancing the value of public–private partnership (PPP) projects during the operational phase.

Utilizing prospect theory, the paper considers the government and the public as external driving forces. It establishes a tripartite evolutionary game model composed of government regulators, the private sector and the public. The paper uses numerical simulations to explore the evolutionary stable equilibrium strategies and the determinants influencing each stakeholder.

The paper demonstrates that government intervention and public participation substantially promote green technology innovation within the private sector. Major influencing factors encompass the intensity of pollution taxation, governmental information disclosure and public attention. However, an optimal threshold exists for environmental publicity and innovation subsidies, as excessive levels might inhibit technological innovation. Furthermore, within government intervention strategies, compensating the public for their participation costs is essential to circumvent the public's “free-rider” tendencies and encourage active public collaboration in PPP project innovation.

By constructing a tripartite evolutionary game model, the paper comprehensively examines the roles of government intervention and public participation in promoting green technology innovation within the private sector, offering fresh perspectives and strategies for the operational phase of PPP projects.

The operation of water environment treatment Public-Private Partnership projects (WETP-PPP) is crucial to the project effectiveness. However, there are often problems in projects that attach importance to construction and neglect operation management, which seriously affect the project operation effect. To ensure the good operation effect of the WETP-PPP, an evolutionary game model of the regulation strategy during the operation period of WETP-PPP is constructed.

An evolutionary game model of regulation is established which considers the government, the project company and the public in water environment treatment Public-Private Partnership projects (WETP-PPP). Five scenarios of equilibriums and the game's evolutionary stable strategies are analyzed, and the corresponding stability conditions are then obtained. Finally, through the simulation, the influence of different factors on the choice of the three-party strategy is analyzed.

First, the key factors that affect the evolution game are the regulation costs and performance rewards of the government, the project company's operation costs and penalties for opportunism and the public supervision costs and rewards. Second, in order to ensure the operation effect, the government needs the performance incentive from the superior government. Third, the public's supervision enthusiasm needs to be mobilized by the government. Last, the penalty strength of speculative operation should be strong enough to play a deterrent role.

The theoretical research in this paper has some limitations. Initially, due to the large number of participants in WETP-PPP, in addition to the government department, the project company and the public studied in this paper, it also involves the consulting industry and financial institutions. In the future, more participants can be added to form four-party interest relationships and conduct four-party evolutionary game research. Second, the operation environment of WETP-PPP is complex and changeable, and various influencing factors are intertwined, the number of parameters involved in this paper is limited, and further detailed research is needed in the future.

Based on the evolutionary game theory, this article discusses the evolution law of the tripartite game behavior of the government department, the project company and the public, which is helpful to clarify the strategy evolution path of the tripartite in the WETP-PPP, and the generation condition and evolution mechanism of the equilibrium strategy of the tripartite game. The key parameters affecting the tripartite strategy selection are analyzed through simulation, which can provide reference for the government department to formulate relevant measures. At the same time, it broadens the application field of evolutionary games and supplements the research on the management mechanism of WETP-PPP during the operation period.

Based on the evolutionary game theory, this paper introduces the supervision behavior of the public, which can provide a new perspective for researchers to conduct relevant research. Secondly, for the regulation during the operation of WETP-PPP, this paper can provide reference for the government department to establish a scientific public supervision system, improve the government supervision mechanism and other relevant measures, which can help promote the public supervision willingness, improve the regulation efficiency of the government and guide the project company to reduce speculation, so as to ensure the effect of water environment management.

This paper focuses on the regulation of WETP-PPP during the operation period to research interactions among the government, the project company and the public. Based on the analysis of the evolutionary game, some suggestions are put forward, such as perfecting the government regulation mechanism, optimizing the reward and punishment system for the project company and broadening the channels of public supervision. The research results of this paper can provide support for the government's regulation of WETP-PPP and ensure the project operation effect.

Nucleic acid testing is an effective method of accurate prevention and control and a key measure to block the spread of the epidemic. However, the fraud in nucleic acid testing occurred frequently during epidemics. This paper aims to provide a viable scheme for the government to strengthen the supervision of nucleic acid testing and to provide a new condition for the punishment for the negative act of the government and the upper limit of the reward for nucleic acid testing institution of no data fraud.

This paper formulates an evolutionary game model between the government and nucleic acid testing institution under four different mechanisms of reward and punishment to solve the issue of nucleic acid testing supervision. The authors discuss the stability of equilibrium points under the four distinct strategies and conduct simulation experiments.

The authors find that the strategy of dynamic reward and static penalty outperforms the strategies of static reward and static penalty, dynamic reward and static penalty, static reward and dynamic penalty, dynamic reward and dynamic penalty. The results reveal the appropriate punishment for the negative act of the government can enhance the positivity of the government's supervision in the strategy of dynamic reward and static penalty, while the upper limit of the reward for nucleic acid testing institution of no data fraud cannot be too high. Otherwise, it will backfire. Another interesting and counterintuitive result is that in the strategy of dynamic reward and dynamic penalty, the upper limit of the penalty for data fraud of nucleic acid testing institution cannot be augmented recklessly. Otherwise, it will diminish the government's positivity for supervision.

Most of the existing evolutionary game researches related to the reward and punishment mechanism and data fraud merely highlight that increasing the intensity of reward and punishment can help improve the government's supervision initiative and can minimize data fraud of nucleic acid institution, but they fall short of the boundary conditions for the punishment and reward mechanism. Previous literature only study the supervision of nucleic acid testing qualitatively and lacks quantitative research. Moreover, they do not depict the problem scenario of testing data fraud of nucleic acid institution regulated by the government via the evolutionary game model. Thus, this study effectively bridges these gaps. This research is universal and can be extended to other industries.

The purpose of the paper is to construct a model that considers video purchase and then identifies the logical relationships implied by the parameters to explore video platform operation mechanisms.

The authors analyzed the video platform system using a mathematical modeling approach and numerical optimization techniques. Through pricing decisions, the authors obtained equilibrium results for the profitability of the video platforms and analyzed the favorable market factors. The authors then extended the model by analyzing the competitive strategies of the two video platforms in the market.

The authors find that advertiser profitability, ad nuisance, video sensitivity and video creator network effects are important factors influencing the pricing strategy of video platforms. During positive market conditions, video platforms tend to lower their prices until they absorb enough users. As market conditions change, the price adjustment strategies of video platforms are affected by parameter changes and inter-parameter relationships.

The study considers the network effects of video creators, which provides a realistic reference for scholars and managers. In addition, the authors consider the bargaining power of platforms when purchasing content. The authors provide a fresh perspective for scholars while filling a gap in the field as video platforms can acquire a portion of the content on the market by setting a purchase price.

Risk response decisions (RRDs) are vital for project risk mitigation. Although past research has focused on RRDs for independent single projects, it has scarcely explored how to make RRDs for single projects in project portfolios (SPPPs). Consequently, this study aims to bridge the gap in extant literature by developing an integrated approach to select risk response strategies (RRSs) for SPPPs considering objective adjustments and project interdependencies (PIs).

An integrated quality function deployment (QFD) method was used throughout this study. More so, a balanced score card (BSC) and stratified-Z-numbers-full consistency method (SZFUCOM) was applied to identify SPPP success criteria (SP3SC) to determine their weights. In addition, a spherical fuzzy set-design structure matrix (SFDSM) was used to quantify the correlation between the risks and the relationship between the risks and the predecessor projects. Consequently, the relationships between the risks and SP3SC and RRSs were described by the spherical fuzzy set (SFS) and Z-numbers, respectively. Besides, the results are weaved into QFD to transform SP3SC into risks and then into RRSs, while a linear optimization model is used to obtain the optimal RRSs. Lastly, a construction project portfolio (PP) was used to test the veracity of the results to prove their validity.

The approach to RRDs for single projects is observed to be different from that of SPPPs. In addition, this study finds that project portfolio objective adjustments (PPOAs) and PIs have significant impacts on RRDs given that they influence the risk priorities of independent single projects and SPPPs. Moreover, the application of an integrated QFD effectively synthesized the results from the findings of this study, as well as enabled companies to determine robust RRSs. Finally, the consistency results of the SZFUCOM were better than those of the triangular fuzzy number-full consistency method.

The study innovatively explores the method of RRDs for SPPP, which has been ignored by past research. SP3SC highly compatible with PP success is determined. Z-numbers are first used to evaluate the effect of RRSs to enhance the robustness of RRDs. The study proposes a method of RRDs comprehensively considering PPOAs and PIs, which provides robust methodological guidance for SPPP managers to control risks.

To maximize the network total profit by calculating the difference between costs and revenue (first objective function). To maximize the positive impact on the environment by integrating GSCM factors in RL (second objective function). To calculate the efficiency of disassembly centers by SDEA method, which are selected as suppliers and maximize the total efficiency (third objective function). To evaluate the resources and total efficiency of the proposed model to facilitate the allocation resource process, to increase resource efficiency and to improve the efficiency of disassembly centers by Inverse DEA.

The design of a closed-loop logistics network for after-sales service for mobile phones and digital cameras has been developed by the mixed-integer linear programming method (MILP). Development of MILP method has been performed by simultaneously considering three main objectives including: total network profit, green supply chain factors (environmental sustainability) and maximizing the efficiency of disassembly centers. The proposed model of study is a six-level, multi-objective, single-period and multi-product that focuses on electrical waste. The efficiency of product return centers is calculated by SDEA method and the most efficient centers are selected.

The results of using the model in a case mining showed that, due to the use of green factors in network design, environmental pollution and undesirable disposal of some electronic waste were reduced. Also, with the reduction of waste disposal, valuable materials entered the market cycle and the network profit increased.

(1) Design a closed-loop reverse logistics network for after-sales services; (2) Introduce a multi-objective multi-echelon mixed integer linear programming model; (3) Sensitivity analysis use Inverse-DEA method to increase the efficiency of inefficient units; (4) Use the GSC factors and DEA method in reverse logistics network.

We attempt to construct a grey three-way conflict analysis model with constraints to deal with correlated conflict problems with uncertain information.

In order to address these correlated conflict problems with uncertain information, considering the interactive influence and mutual restraints among agents and portraying their attitudes toward the conflict issues, we utilize grey numbers and three-way decisions to propose a grey three-way conflict analysis model with constraints. Firstly, based on the collected information, we introduced grey theory, calculated the degree of conflict between agents and then analyzed the conflict alliance based on the three-way decision theory. Finally, we designed a feedback mechanism to identify key agents and key conflict issues. A case verifies the effectiveness and practicability of the proposed model.

The results show that the proposed model can portray their attitudes toward conflict issues and effectively extract conflict-related information.

By employing this approach, we can provide the answers to Deja’s fundamental questions regarding Pawlak’s conflict analysis: “what are the underlying causes of conflict?” and “how can a viable consensus strategy be identified?”