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Based on dual information asymmetry, the two-stage segmented compensation mechanism for technological innovation of civilian enterprises’ participation in military (CEPIM) has been discussed.

On the basis of the traditional principal-agent problems, the incentive compatibility condition is introduced as well as the hybrid incentive compensation model is established, to solve optimal solution of the compensation parameters under the dynamic contract condition and the validity is verified by numerical simulation.

The results show that: (1) The two-stage segmented compensation mechanism has the functions of “self-selection” and “stimulus to the strong”, (2) It promotes the civilian enterprises to obtain more innovation benefit compensation through the second stage, (3) There is an inverted U-shaped relationship between government compensation effectiveness and the innovation ability of compensation objects and (4) The “compensable threshold” and “optimal compensation threshold” should be set, respectively, to assess the applicability and priority of compensation.

In this paper, through numerical simulation, the optimal solution for two-stage segmented compensation, segmented compensation coefficient, expected returns for all parties and excess expected returns have been verified under various information asymmetry. The results show that the mechanism of two-stage segmented compensation can improve the expected returns for both civilian enterprises and the government. However, under dual information asymmetry, for innovation ability of the intended compensation candidates, a “compensation threshold” should be set to determine whether the compensation should be carried out, furthermore an “optimal compensation threshold” should be set to determine the compensation priority.

The construction industry has long been criticized for unethical conduct. The owner usually manages the contractor's opportunistic behaviors by employing a professional supervisor, but there is a risk of covert collusion between the supervisor and contractor. Based on the principal–agent theory and collusion theory, this paper aims to investigate optimal collusion-proof incentive contracts.

This paper presents a game-theoretic framework comprising an owner, supervisor and contractor, who interact and pursue maximized self-profits. Built upon the fixed-price incentive contract, cost-reimbursement contract, and revenue-sharing contract, different collusion-proof incentive contracts are investigated. A real project case is used to validate the developed model and derived results.

This paper shows that the presence of unethical collusion undermines the owner's interests. Especially, the possibility of agent collusion may induce the owner to abandon extracting quality information from the supervisor. Furthermore, information asymmetry significantly affects the construction contract selection, and the application conditions for different incentive contracts are provided.

This study still has some limitations that deserve further exploration. First, this study explores contractor–supervisor collusion but ignores the possibility of the supervisor abusing authority to extort the contractor. Second, to focus on collusion, this paper ignores the supervision costs. What's the optimal supervision effort that the owner should induce the supervisor to exert? Finally, this paper assumes that the colluders involved always keep their promises. However, what if the colluders may break their promises?

Several collusion-proof incentive contracts are explored in a project management setting. The proposed incentive contracts can provide the project owner with effective and practical tools to inhibit covert collusion in construction management and thus safeguard construction project quality.

This study expands the organization collusion theory to the field of construction management and investigates the optimal collusion-proof incentive contracts. In addition, this study is the first to investigate the effects of information asymmetry on contract selection.

Construction projects have become increasingly long, complex and costly with waste and inefficiencies and often fail to achieve the desired results. Integrated project delivery (IPD) is believed to change these problems. A reasonable and fair profit distribution mechanism is a critical factor for ensuring the success of the IPD projects. This study aims to investigate the strategies of all participants in the profit distribution of an IPD project with respect to the factor of the effort level.

This study describes the influence of owners and participants on profit distribution due to their respective efforts in the IPD project alliance. The influence of effort level on profit distribution is discussed based on the Holmstrom-Milgrom model of asymmetric information game theory and principal-agent theory, combined with incentive compatibility (IC) constraints and individual rationality (IR) constraints.

The results show that the optimal level of effort by each participant optimizes the profit distribution of an IPD project. At the same time, in the revenue incentive contract, the effort level of the participants is positively correlated with the profit distribution, proportional to their contribution coefficient and inversely proportional to the square of the cost of their creative activities in terms of effort. Each party of an IPD project can adopt a series of measures to improve their own effort level and choose the optimal level of effort based on the profit distribution, while satisfying their own utility maximization.

This study introduces the Holmstrom-Milgrom model in the principal-agent theory to explore the influence of the effort level on profit distribution in IPD projects. The quantitative model can contribute to establish a fair and efficient profit distribution scheme for the IPD projects.

Promoting technological innovation is important to address the complexity of major engineering challenges. Technological innovations include short-term innovations at the project level and long-term innovations that can enhance competitive advantages. The purpose of this study is to develop an incentive mechanism for the public sector that considers short-term and long-term efforts from the private sector, aiming to promote technological innovation in major engineering projects.

This study constructs an incentive model considering the differences in short-term and long-term innovation efforts from the private sector. This model emphasizes the spillover effect of long-term efforts on current projects and the cost synergy effect between short-term and long-term efforts. It also explores the factors influencing the optimal incentive strategies for the public sector and innovation strategies for the private sector.

The results indicate that increasing the output coefficient of short-term and long-term efforts and reducing the cost coefficient not only enhance the innovation efforts of the private sector but also prompt the public sector to increase the incentive coefficient. The spillover effect of long-term innovation efforts and the synergy effect of the two efforts are positively related to the incentive coefficient for the public sector.

This research addresses the existing gap in understanding how the public sector should devise incentive mechanisms for technological innovation when contractors acting as the private sector are responsible for construction within a public-private partnership (PPP) model. In constructing the incentive mechanism model, this study incorporates the private sector's short-term efforts at the project level and their long-term efforts for sustained corporate development, thus adding considerable practical significance.

Distributed photovoltaic (DPV) projects generally have output risks, and the production effort of the supplier is often private information, so the buyer needs to design the optimal procurement contract to maximise its procurement utility.

Based on the principal-agent theory, we design optimal procurement contracts for DPV projects with fixed payments and incentive factors under three situations, i.e. symmetry information, asymmetry information without monitoring and asymmetry information with monitoring. We obtain the optimal production effort and expected utility of the supplier, the expected output and expected utility of the buyer and analyse the value of the information and monitoring.

The results show that under asymmetric information without monitoring, risk-averse suppliers need to take some risk due to output risk, which reduces the optimal production effort of the supplier and the expected output and expected utility of the buyer. Therefore, when the monitoring cost is below a certain threshold value, the buyer can introduce a procurement contract with monitoring to address the asymmetry information. In addition, under asymmetric information without monitoring, the buyer should choose a supplier with a low-risk aversion.

Considering the output risk of DPV projects, we study the optimal procurement contract design for the buyer under asymmetric information. The results provide some theoretical basis and management insights for the buyer to design optimal procurement contracts in different situations.

As the complexity and uncertainty of megaprojects make it difficult for traditional management models to address the difficulties, this paper aims to design a performance incentive contract through IT applications, thereby promoting the formation of an information-based governance mechanism for megaprojects and facilitating the transformation and upgrading of the construction management model of megaprojects to informatisation.

This paper introduced IT applications into the performance assessment and used the proportion of IT applications replacing traditional manual management as a variable. It analysed different replacement ratios to obtain the optimal solution for the change of contractors behaviours and promote the optimal performance incentive for the informatisation in megaprojects.

The results show that under the condition of the optimal replacement ratio, achieving the optimal state of a mutual win-win situation is possible for the benefit of both sides. The counter-intuitive finding is that the greater the replacement ratio is not, the better, but those other constraints are also taken into account.

This study enriched the research of the performance configuration incentive from a practical perspective. It extended the research framework of IT incentive mechanisms in the governance of megaprojects from a management theory perspective. It clarified the role of IT applications in incentive mechanisms and the design process of optimal incentive contracts under different performance incentive states. The incentives made the contractors work harder to meet the owner's requirements, and it could improve the efficiency of megaprojects, thus better achieving megaproject objectives.

Users often struggle to select choosing among similar online services. To help them make informed decisions, it is important to establish a service reputation measurement mechanism. User-provided feedback ratings serve as a primary source of information for this mechanism, and ensuring the credibility of user feedback is crucial for a reliable reputation measurement. Most of the previous studies use passive detection to identify false feedback without creating incentives for honest reporting. Therefore, this study aims to develop a reputation measure for online services that can provide incentives for users to report honestly.

In this paper, the authors present a method that uses a peer prediction mechanism to evaluate user credibility, which evaluates users’ credibility with their reports by applying the strictly proper scoring rule. Considering the heterogeneity among users, the authors measure user similarity, identify similar users as peers to assess credibility and calculate service reputation using an improved expectation-maximization algorithm based on user credibility.

Theoretical analysis and experimental results verify that the proposed method motivates truthful reporting, effectively identifies malicious users and achieves high service rating accuracy.

The proposed method has significant practical value in evaluating the authenticity of user feedback and promoting honest reporting.

This study aims to examine the impact of board characteristics on firm performance while also exploring the influential mechanisms that help Chinese listed companies establish effective boards of directors and strengthen their corporate governance mechanisms.

This paper uses machine learning methods to investigate the predictive ability of the board of directors' characteristics on firm performance based on the data from Chinese A-share listed companies on the Shanghai and Shenzhen stock exchanges in China during 2008–2021. This study further analyzes board characteristics with relatively strong predictive ability and their predictive models on firm performance.

The results show that nonlinear machine learning methods are more effective than traditional linear models in analyzing the impact of board characteristics on Chinese firm performance. Among the series characteristics of the board of directors, the contribution ratio in prediction from directors compensation, director shareholding ratio, the average age of directors and directors' educational level are significant, and these characteristics have a roughly nonlinear correlation to the prediction of firm performance; the improvement of the predictive ability of board characteristics on firm performance in state-owned enterprises in China performs better than that in private enterprises.

The findings of this study provide valuable suggestions for enriching the theory of board governance, strengthening board construction and optimizing the effectiveness of board governance. Furthermore, these impacts can serve as a valuable reference for board construction and selection, aiding in the rational selection of boards to establish an efficient and high-performing board of directors.

The study findings unequivocally demonstrate the superiority of nonlinear machine learning approaches over traditional linear models in examining the relationship between board characteristics and firm performance in China. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. The study reveals that the predictive performance of board attributes is generally more robust for state-owned enterprises in China in comparison to their counterparts in the private sector.

This study aims to develop a Stackelberg Game Model for seeking the optimal subsidy plans with varying levels of government financial capability (GFC). Furthermore, the scenario-based analysis is conducted and will enable governments to identify a comprehensive subsidy plan as follows: improve project performance and optimise social welfare.

A Stackelberg Game Model is developed to optimise the effectiveness of subsidies on the performance of public-private partnerships (PPPs).

According to the scenarios that are generated from the model, governments that are confronting with limited public budgets could reduce the intensity of performance incentives and increase the participation-oriented subsidy. Whilst a participation-oriented subsidy can stimulate private organisations’ willingness to participate in infrastructure PPPs, a performance-oriented subsidy is capable of facilitating the projects’ performances. Intuitively, the performance-oriented subsidy enables the private entities of PPPs to improve their efforts on the projects to realise higher profits. However, the participation-oriented subsidy is unable to affect the level of their effort spent on the projects. To satisfy both parties’ expectations in a PPP, the performance-oriented subsidy needs to be prioritised for a purpose of enabling higher quality outputs.

The game model developed in this study contributes to the literature by offering new insight into the underlying mechanism of governments and private entities, in terms of their decision-making for subsidy planning and contributions (i.e. resource allocation and spending) during the life-cycle of PPPs. This research enriches the government subsidy model by revealing the effects of the GFC and clarifies the impacts of two different schemes of subsidy on the performance of PPPs.

The government has been conventionally viewed as being omnipotent to provide PPPs with a wide range of subsidies. However, the subsidies are not unlimited, due to GFC. In addressing this void, this study has modelled the impacts of government subsidy plans with a consideration of GFC-related constraints. The combined effects of the participation- and performance-oriented subsidies on the project performance of PPPs have been examined.

The purpose of this paper is to study the impact of government supervision and market environment on farmers' pesticide application behavior, as well as the intermediary effect of farmers' literacy, and investigate the substitution effect between government supervision and market environment.

In this paper, logit and Poisson regression models were used to investigate the comprehensive impact of government supervision and market environment on farmers' pesticide application behavior, and the intermediary effect model is used to examine the intermediary effect of farmers' literacy.

Government supervision is an important constraint for the formation of individual behavior paradigm, but it has both positive and negative effects, depending on different instruments. The market subject constraint and market incentive are two important ways that the market environment affects Chinese farmers' pesticide application behavior. Farmers' literacy plays a partial mediating role in the influencing mechanism of government and market factors. The government supervision and market environment, two different constraint forces, have substitution effects in the process of regulating farmers' pesticide application behavior.

In the influence mechanism, farmers' literacy, such as values, responsibilities and skill requirement related to scientific pesticide use, was included into the analysis framework as intermediary variables. The authors found that government supervision and market environment not only directly affect farmers' pesticide application behavior but also indirectly affect farmers' pesticide application behavior through farmers' literacy.