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Green innovation in the logistics industry is critical to mitigating environmental crises and ensuring sustainable development. In this study, a two-echelon logistics service supply chain (LSSC) is constructed consisting of a logistics service provider (LSP), a logistics service integrator (LSI), and customers. The LSP and the LSI collaborate to provide high-quality green logistics service products (GLSPs) to customers. Strategic cooperation is established between upstream and downstream enterprises in the form of supportive investment and cost-sharing to strengthen inter-organizational relationships; the LSI may show overconfidence in both the impact of his green innovation effort on demand expansion and control power in the vertical LSSC. By solving the LSI-led Stackelberg game, we find that: First, the innovation cost coefficients and the payment ratio affect optimal decisions, including the optimal level of GLSP design innovation, level of GLSP delivery innovation, price of the GLSP, and LSI's optimal expected utility. Second, relationship strength positively impacts optimal decisions; its impact on the LSI's optimal expected utility is related to the upper limit of the LSI's supportive investment for the LSP. Third, the LSI's overconfidence positively impacts the optimal decisions and the LSI's optimal expected utility, while it harms the LSI's optimal real utility; the impacts of the LSI's overconfidence and inter-organizational relationship strength are additive. Finally, a "green subsidy and loss-sharing" incentive contract is proposed, which can improve both the levels of design and delivery innovation, as well as the LSSC members' real utilities. The findings may provide new insights for LSSC green innovation practitioners. [ABSTRACT FROM AUTHOR]

We study theoretically and empirically the relation between altruism and incentive contract design. Theoretically, we extend Fischer and Huddart (2008) to investigate how social norms reinforce managers' altruistic preferences, thus affecting the optimal contract design related to incentive strength and performance measurement. Empirically, we draw on the notion of an organization's work climate to capture managers' altruistic preferences. Using data collected from a sample of 557 managers, we find that in a work climate where managers are mostly out for themselves, firms have lower pay-for-performance sensitivity and place a greater weight on aggregate performance measures. In addition, respondents report that they engage more in undesirable actions that are unproductive and costly to firm owners. In contrast, in a work climate where managers care about others (including peers in their organizational unit), firms place lower weights on aggregate performance measures. At the same time, respondents report that they supply more effort and engage less in undesirable actions. [ABSTRACT FROM AUTHOR]

In China, supply chain finance is still in infancy. However, it is the problems of information sharing, trust transfer, and risk management that have been making it difficult to meet the financing needs of small- and medium-sized enterprises (SMEs) in supply chain. The emerging blockchain technology, with its unique decentralization, traceability, and other characteristics, has found a digital solution for traditional supply chain finance. Although blockchain has attracted widespread attention and there are more general descriptions of blockchain application areas, there are few researches on the impact mechanisms of blockchain in-depth. Especially in the field of supply chain finance, there is little research on optimal incentive contract in online supply chain finance empowered by blockchain technology. Therefore, this paper explores the influence of blockchain technology maturity on participants, and thus finds the optimal incentive contract in online supply chain empowered by blockchain technology. Because of the mastery of blockchain technology, platforms believe they are well protected against risk and may behave irrationally. Therefore, this paper considers the overconfident behavior of blockchain supply chain finance platform in actual operation, and then applies the principal-agent model and incentive theory to design the incentive mechanism between platforms, banks, and central banks. Finally, numerical analyses show that overconfident behavior and the maturity of blockchain technology have an impact on the optimal decision for the whole supply chain. [ABSTRACT FROM AUTHOR]

Corporations have recently started incorporating employees' prosocial preferences into their incentive schemes, including charitable donations (corporate giving). These donations are mainly discussed in conjunction with the external effects of a firm's CSR strategy. However, this experiment examines the effect of donations on internal firm operations. Specifically, we investigate whether the presence and structure of corporate giving influences employees' excessive risk-taking. Such prosocial activities may remediate misaligned incentives often cited as drivers for employees to take excessive risks. Contrary to widespread practice, our experimental evidence suggests that firms could constrain employees' excessive risk-taking by linking existing contributions to project rather than corporate performance, thus providing boundaries around an employee's involvement in CSR initiatives. We identify project-level giving as an unexplored CSR benefit and infer that personal responsibility effectively changes an employee's incentive package. Our findings suggest an inverted U-shape curve of effectiveness. [ABSTRACT FROM AUTHOR]

The delegating computation has become an irreversible trend, together comes the pressing need for fairness and efficiency issues. To solve this problem, we leverage game theory to propose a smart contract-based solution. First, according to the behavioral preferences of the participants, we design an incentive contract to describe the motivation of the participants. Next, to satisfy the fairness of the rational delegating computation, we propose a rational delegating computation protocol based on reputation and smart contract. More specifically, rational participants are to gain the maximum utility and reach the Nash equilibrium in the protocol. Besides, we design a reputation mechanism with a reputation certificate, which measures the reputation from multiple dimensions. The reputation is used to assure the client's trust in the computing party to improve the efficiency of the protocol. Then, we conduct a comprehensive experiment to evaluate the proposed protocol. The simulation and analysis results show that the proposed protocol solves the complex traditional verification problem. We also conduct a feasibility study that involves implementing the contracts in Solidity and running them on the official Ethereum network. Meanwhile, we prove the fairness and correctness of the protocol. [ABSTRACT FROM AUTHOR]

The degree of knowledge investment of partners is the key to success for cooperative innovation in project-based supply chain. The intangibility and unverifiability of their knowledge investment lead to the double moral hazard which will hinder the smooth progress of cooperative innovation. In order to stimulate the knowledge investment of partners for cooperative innovation in project-based supply chain, this paper has designed formal contract and relational contract of knowledge investment with principal-agent theory, and then the incentive effects of contracts are analyzed. We find that the formal contract cannot motivate their knowledge investment effectively; the degree of knowledge investment and the revenue of participants for cooperative innovation under the relational contract are not less than that under the formal contract for all discount rate; the incentive effect of the relational contract is getting more obvious as the discount rate increases. When the discount rate reaches a certain threshold value, the optimal degree of knowledge investment and revenue of participants for cooperative innovation can be achieved through the relational contract. At last, the effectiveness of the conclusions is verified through numerical example. [ABSTRACT FROM AUTHOR]

A suitable and attractive contract may bring large profits and lower the risk caused by uncertain information in project management; thus, how to design incentive contracts under uncertainty has been the most pressing demand for the owner. This paper investigates the project incentive contract design problem with random asymmetric information, in which a risk-neutral owner (he) engages a risk-averse contractor (she) to complete a project. The contractor’s construction capacity is private information and characterized as a random variable. Furthermore, two incentive contracts, duration-based contract and deadline-based contract, are designed, where the owner offers a fixed payment and a penalty or bonus factor based on the real project duration and a predetermined deadline for the contractor in these two different contracts. Then, a project duration contract and a deadline-based contract model are developed with the purpose of maximizing the owner’s expected payoff, respectively. The optimal contracts are investigated, and the values of the contractor’s construction capacity information for the owner under these two contracts are quantified. The results show that the owner benefits better from getting more construction capacity information and should commit an information rent to the contractor due to asymmetric information, which distorts the penalty factor under both contracts. Moreover, regardless of contract type, the deadline has no effects on the owner’s incentive term and only affects the fixed payments. Further, the contractor is more likely to keep information private, while the owner benefits more from knowing the contractor’s construction capacity when the deadline-based contract is used. [ABSTRACT FROM AUTHOR]

The R&D project manager tends to misreport risk aversion magnitude and shirk under uncertain environment for acquiring information rent and risk premium, which brings a significant challenge for the firm when designing compensation contracts. We consider an agency problem where a firm employs a manager who has private information about his risk aversion magnitude and unobservable efforts to implement a R&D project through a menu of incentive contracts. Both the subjective assessments about the risk aversion degree and the project variability are characterized as uncertain variables. Within the framework of uncertainty theory and principal-agent theory, we investigate the impacts of information asymmetry on the optimal compensation contracts and the firm’s profits under four information structures. We demonstrate that, counterintuitive as it sounds, the manager’s optimal contract under full information is the same as that under pure adverse selection. Nevertheless, compared to the case under full information, the firm should distort the commission rate upwards under pure moral hazard and dual asymmetric information. We also show that when the manager’s efforts are observable, hidden information about the risk aversion magnitude has no effect on the firm’s profit. However, when unobservable, private risk aversion degree always brings about information rent and induces a loss for the firm’s profit. Finally, our study provides managerial recommendations on mitigating the adverse impacts caused by asymmetric information. [ABSTRACT FROM AUTHOR]

It is necessary for one senior executive (she) to monitor her project manager (he) who conducts early research stage followed by a later development stage in new product development. In this paper, we analyze two monitoring mechanisms: (1) the idea information-based monitoring (IM) mechanism wherein the senior executive engages one supervisor to monitor the project manager's idea information; (2) the effort-based monitoring (EM) mechanism wherein the senior executive engages another supervisor to monitor the project manager's effort. Within the framework of uncertainty theory, we first present two classes of bilevel uncertain principal-agent monitoring models, and then derive their respective optimal incentive contracts. We find that the senior executive should set the incentive term as high as possible to motivate each supervisor to monitor the project manager's idea information and effort no matter how much the design idea value is. We also find that EM mechanism can always dominate IM mechanism when the monitoring costs are equal. Moreover, comparing with a no monitoring scenario, we identify two values of monitoring: the value of monitoring idea information and the value of monitoring effort. Our results show that adopting IM and EM mechanisms can improve the senior executive's profits obtained in the no monitoring scenario when the revenue uncertainty is sufficiently low. The results also indicate that the value of monitoring idea information decreases as the risk aversion level of the project manager improves, while the value of monitoring effort shows the opposite feature. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of decision criteria on incentives in a project management setting, where a project manager operates a project consisting of two tasks performed sequentially by two different subcontractors. The completion time is characterized as an uncertain variable, which depends on the subcontractor's unobservable effort of each task. Within the framework of uncertainty theory, four classes of uncertain principal agent models are presented under the expected value criterion and the critical value criterion. According to the structural characteristics, each model can be decomposed into two equivalent sub-models, which can be solved to obtain the optimal deadline-based incentive contracts via a two-step optimization method. Further, the interconnections among these contracts are discussed. It's demonstrated that the optimal deadline-based incentive contract depends on the confidence level of the party (either the project manager or the subcontractor) who adopts the critical value criterion. Meanwhile, the more conservative the subcontractor is, the higher the incentive coefficients will be. And the more conservative the project manager is, the lower the incentive coefficients will be. Finally, given some special confidence levels, it's interesting to find that the four models can be equivalent. [ABSTRACT FROM AUTHOR]

Despite the empirical relevance, the privatization literature paid little attention to the effects of the owner-manager relationship and the implications of foreign direct investment (FDI). We focus on these aspects, and show the relationship between privatization and greenfield FDI when the owners design strategic managerial incentive contracts. We show that there is complementarity between privatization and greenfield FDI. Whether incentive delegation (compared to no incentive delegation) increases the degree of privatization in the presence of FDI is ambiguous; it depends on whether the degree of privatization that attracts FDI is higher or lower than the degree of privatization that maximizes domestic welfare under FDI. [ABSTRACT FROM AUTHOR]

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We study contracts designed to remunerate a farmer for the production of an ecosystem service with the payment dependent on the results of the farmer’s actions and on weather conditions. Two contracts are proposed: the first takes into account both the results of the farmer’s actions and a weather variable that reflects the actual atmospheric conditions during the life of the contract; the second bases the payment on the results alone incorporating only the average effect of weather. Social welfare is optimal when both the results and the specific atmospheric conditions are taken into account; however, this type of contract may be less acceptable to the farmer due to his perception of the level of risk involved. [ABSTRACT FROM AUTHOR]

This paper studies options on the minimum/maximum of two average prices. We provide a closed-form pricing formula for the option with geometric averaging starting at any time before maturity. We show overwhelming numerical evidence that the variance reduction technique with the help of the above closed-form solution dramatically improves the accuracy of the simulated price of an option with arithmetic averaging. The proposed options are found widely applicable in risk management and in the design of incentive contracts. The paper also discusses some parity relationships within the family of average-rate options and provides the upper and lower bounds for the proposed options with arithmetic averaging. [ABSTRACT FROM AUTHOR]