Dynamic Contract Design of Product-Service Supply Chain considering Consumers’ Strategic Behavior and Service Quality

With increasing market competition and rapid development of service economy, more and more enterprises are shifting from providing products or services to providing product-service systems (PSSs) that integrate products and services, in order to improve competitiveness and profitability. Meanwhile, consumers have strategic delayed purchasing behavior when purchasing the PSS and high requirements for service quality. This paper investigates the two-period pricing and service quality decisions of product-service supply chain (PSSC) considering consumers’ strategic behavior under decentralized and centralized scenarios. The equilibrium results are compared in two scenarios. In order to eliminate performance loss under the decentralized scenario, we design two-period dynamic contracts to coordinate the PSSC. Furthermore, numerical simulation is provided to verify the feasibility of the contracts. The following conclusions can be drawn: (1) the higher the service input-efficiency, the more beneficial for alleviating consumers’ strategic purchase behavior under two scenarios, but this mitigation effect is more obvious under the centralized scenario. (2) Compared with the centralized scenario, the service quality is lower, the two-period PSS sales prices are higher, and the two-period profit is lower under the decentralized scenario. The proportion of service valuation (accounts for the valuation of PSS) will promote the widening of the service quality gap under two scenarios, but in some cases, the service input-efficiency will weaken the promotion effect of the proportion of service valuation. (3) The design of the two-period combined contracts depends on the proportion of service valuation. When the proportion of service valuation is high, the “two-period revenue sharing + service-cost sharing” combined dynamic contract can achieve PSSC perfect coordination. However, when the proportion of service valuation is low, it is necessary to design complexity combined dynamic contract which can achieve PSSC perfect coordination.

Linear capabilities for fully abstract compilation of separation-logic-verified code

Separation logic is a powerful program logic for the static modular verification of imperative programs. However, dynamic checking of separation logic contracts on the boundaries between verified and untrusted modules is hard because it requires one to enforce (among other things) that outcalls from a verified to an untrusted module do not access memory resources currently owned by the verified module. This paper proposes an approach to dynamic contract checking by relying on support for capabilities, a well-studied form of unforgeable memory pointers that enables fine-grained, efficient memory access control. More specifically, we rely on a form of capabilities called linear capabilities for which the hardware enforces that they cannot be copied. We formalize our approach as a fully abstract compiler from a statically verified source language to an unverified target language with support for linear capabilities. The key insight behind our compiler is that memory resources described by spatial separation logic predicates can be represented at run time by linear capabilities. The compiler is separation-logic-proof-directed: it uses the separation logic proof of the source program to determine how memory accesses in the source program should be compiled to linear capability accesses in the target program. The full abstraction property of the compiler essentially guarantees that compiled verified modules can interact with untrusted target language modules as if they were compiled from verified code as well. This article is an extended version of one that was presented at ICFP 2019 (Van Strydonck et al., 2019).

Optimal Monitoring Schedule in Dynamic Contracts

Monitoring in Dynamic Contract Design

Dynamic Contract Incentives Mechanism for Traffic Offloading in Multi-UAV Networks

Traffic offloading is considered to be a promising technology in the Unmanned Aerial Vehicles- (UAVs-) assisted cellular networks. Due to their selfishness property, UAVs may be reluctant to take part in traffic offloading without any incentive. Moreover, considering the dynamic position of UAVs and the dynamic condition of the transmission channel, it is challenging to design a long-term effective incentive mechanism for multi-UAV networks. In this work, the dynamic contract incentive approach is studied to attract UAVs to participate in traffic offloading effectively. The two-stage contract incentive method is introduced under the information symmetric scenario and the information asymmetric scenario. Considering the sufficient conditions and necessary conditions in the contract design, a sequence optimization algorithm is investigated to acquire the maximum expected utility of the base station. The simulation experiment shows that the designed two-stage dynamic contract improves the performance of traffic offloading effectively.

Reputation-Based Dynamic Contract Incentive Mechanism in Mobile Crowdsourcing Network

Mobile crowdsourcing network is a promising technology utilizing the mobile ter- minal’s sensing and computing capabilities to collect and process data. However, because the mobile users (MUs) have selfish characteristics, the MUs only aim at maximizing their benefits. Therefore, how to design an appropriate long-term incentive mechanism for the service provider (SP) in dynamic environments is an urgent problem. In this work, we investigate the reputation-based dynamic contract for mobile crowdsourcing network. A two-period dynamic contract is first investi- gated to deal with the asymmetric information problem in the long-term crowd- sourcing tasks. Reputation strategy is introduced to attract the MUs to complete the long-term tasks. The incentives of the contract and the implicit incentives of the reputation strategy are used together to encourage MUs to complete the long-term crowdsourcing tasks. The optimization strategy is formulated by adjust- ing the reputation coefficient to maximize the SP’s utility. The impact of MUs’ risk attitude and reputation impact factors on the incentive mechanism is studied through experiments. Numerical simulation results demonstrate that the optimal reputation-based contract design scheme is efficient in the Mobile crowdsourcing networks.