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The effective and efficient motivation of the sales personnel affects the sales of a firm directly. The aim of this paper is to study the incentive effects of different compensation contracts under the framework of multi‐agent principal agent model, and it finds that the optimal contract is not the one that ties one salesperson's compensation to his own performance, but the one that ties his compensation to all the salespersons' performance. Factors that influence the incentive degree are also discussed. The purpose of this article is to design a reasonable incentive contract for salespersons where there are competitions between them.

A multi‐agent model where the efforts of one agent harm the performance of the other agent is established.

The optimal compensation of a salesperson is always composed of two parts: an incentive for an agent to improve his own performance and a disincentive for the agent to harm his colleague's performance, provided that there is a competition relationship between the two agents.

This model applies only to the rewards incentive of multi‐agents with competitive relationships.

The conclusion could be used anywhere when there are two agents with one's behavior harming the other's performance.

A multi‐agent model where the efforts of one agent harm the performance of the other agent is established to study the compensation design problems for agents.

The purpose of this paper is to investigate the impact of incentive contracts in multi-partner project teams (MPPTs) on the agents’ effort expenditure and project performance, analyze how the agents allocate their efforts between production and cooperation and offer suggestions for project managers on how to design incentive contracts.

The paper proposes a model of MPPT in which agents are inequity-averse and their effort expenditures are exogenously bounded. An extensive numerical example is presented in online Appendix 2 to illustrate the theoretical results.

The paper suggests that if the potential benefit of the agents’ cooperation in MPPT is high or if both agents exhibit inequity aversion and the efforts’ marginal costs are low, then group-based incentive contracts outperform individual-based incentive contracts. It also shows that the impact of the incentive contract on the agents’ effort expenditure and project team performance is correlated with several critical project attributes.

Fulfilling a need to study the design of incentive structures in MPPTs, the paper complements the existing literature in three ways. First, in contrast to single-partner project teams, it considers projects with multiple partners where cooperation between them enhances the project outcome. Second, rather than focusing on individual production problems, it considers multi-task projects with constrained efforts that must be allocated between production and cooperation. Third, it analyzes the effects of changes in the project attributes, incentive intensities and information transparency on the effectiveness of the contract.

Taking into account the importance of e‐commerce and the current applications of AI techniques in this area, this research aims to adequate the design of a multi‐agent system for the provisioning of e‐services in u‐commerce environments. This proposal is centred on the methods of evaluation in a u‐e‐commerce environment.

The multi‐agent systems (MAS) approach is based on an MAS model developed for AmI that has been redesigned to support u‐commerce. The use of a recommendation system, previously developed by the research group, is suggested for this MAS. The methodological proposal centres on the evaluation of this type of system.

The evaluation of this type of system is the principal problem of current research. Therefore, this is the main contribution of the paper.

The different evaluation methods that are proposed, whether qualitative or quantitative, offer the possibility of measuring the added value that the context can give to the use of e‐services in different domains of application. Qualitative evaluation should consider the customer as a central piece in the system. In addition, quantitative methods should objectively evaluate the contribution of context to the application.

At present, there is no single method for evaluating the benefits of different u‐commerce systems, so a new method needs to be found based on these techniques.

The research proposes an MAS designed for u‐commerce domains, analyzes the capacity of trust management techniques in this environment, and proposes several evaluation methods to show the benefits of context information in the use of e‐services. Several real developments are described to show the different applications of MAS in u‐commerce and how evaluation is carried out.

Supply chain management represents a critical competency in today’s global business environment and has been the focus of considerable, but mixed, information systems research. The research described in this paper builds on work in multi‐agent systems to argue that intelligent agents offer excellent potential and capability for supply chain management, and contributes to discussion and theory pertaining to electronic markets and supply chain disintermediation. Argues that the knowledge associated with intermediation work represents a key mediating variable between disintermediating technology and supply chain efficacy and discusses how intelligent agent technology can be employed to both intermediate and disintermediate the supply chain, attaining the cost and cycle‐time benefits of disintermediation without the attendant loss of human knowledge and expertise. The paper outlines a number of implications for theory and practice in information systems, and it formalizes some important research questions through a contingency framework to help stimulate and guide future work along these lines.

Knowledge discovery in databases (KDD) is a tedious and repetitive process. A challenge for the effective use of KDD is understanding and confirming its results derived from the harmonized process. To exploit the advantages of agents’ application, this paper aims to propose a conceptual model based on a multi-agent system (MAS) to control each step of the KDD process.

This paper reports the empirical findings of a survey conducted among academic and industrial sectors in Tehran, Iran. In this survey, the participants answered a questionnaire about the main factors of designing a suitable model for the KDD process based on MAS. The factor analysis reveals important insights of previous models developed by various researchers.

This research uses the survey results to find six critical success factors, continuity in refinement and improvement; learning and acting concurrently; loosely or tightly coupled approach for using technologies; cooperative, dynamic and flexible environment; documentation and reporting; and extracting and evaluating knowledge intelligently, for a proper conceptual model of the KDD process based on MAS.

The proposed model reflects all aspects of the KDD process by applying the intelligent agents for each process steps. In addition, this research only considers the Iran society; hence, it cannot be generalized to other nations, and it may need further research in other countries and to be implemented in real-world business domains.

This research helps organizations to adopt a proposed model and implement a KDD process to advantage the valuable knowledge that exists in their data resources.

The applications of multi-agent systems (MASs) are considered to be among the most promising paradigms for detailed investigations and reliable problem-solving methods, and MAS applications make it possible for researchers and practitioners to better understand complex systems. Although a number of prior studies have been conducted to address complex issues that arise from construction projects, few studies have summarised the applications and discussed the capacity of MASs from the perspective of construction management. To fill the gap, this paper provides a comprehensive literature review of MAS applications from the perspective of construction management.

Web of Science and Scopus are the most commonly used international databases in conducting the literature reviews. A total of 86 relevant papers published in SCI-Expanded, SSCI and Ei Compendex journals related to the application of MASs from the perspective of construction management are selected to be analysed and discussed in this paper.

Based on the 86 collected publications, the utilisations of MASs to support the management of the supply chain and the improvement of project performance are identified from the perspective of construction management, the characteristics and barriers of current MAS applications are analysed, a framework for developing agent-based models to address complex problems is proposed, and future research directions of MAS applications are discussed.

This review can serve as a useful reference for scholars to enhance their understanding of the current research and guide future research on MASs. The proposed framework can help build agent-based models to address complex problems in construction management.

The aim of this paper is to address the problem of fault detection (FD) of linear continuous‐time multi‐agent systems.

A mixed H_∞/H₋ formulation of the FD problem using semi‐decentralized filters is presented.

It is shown that through a decomposition approach the drawbacks of the existing distributed FD design methods in multi‐agent systems can be effectively tackled. An extended linear matrix inequality (LMI) characterization is used to reduce the conservativeness of the design solution by introducing additional matrices in order to eliminate the couplings of the Lyapunov matrices with the agent's matrices.

It is shown that by applying the proposed decomposition approach the FD problem of multi‐agent systems can be solved by analyzing the problem of a set of decoupled systems whose order and complexity are equal to that of a single agent. This procedure will be useful for both simplifying the computational cost of the solution as well as for developing a fault detection filter having a semi‐decentralized architecture.

Application of this methodology to a network of micro‐air vehicles (MAVs) illustrates the effectiveness and capabilities of the proposed design methodology.

The feasibility of the use of reliable and self‐healing network of unmanned systems, cooperative networks, and multi‐agent systems will be significantly enhanced and improved by the development of advanced fault detection and isolation (FDI) technologies.

A semi‐decentralized fault detection (FD) methodology is developed for linear multi‐agent networked systems to reduce the order and complexity of the observers at each agent. A mixed H_∞/H₋ formulation of the FD problem by using semi‐decentralized filters is presented. Using this approach each agent can not only detect its own faults but also is able to detect its nearest neighbor agents’ faults.

The purpose of this paper is to explore the doer effect of service failure (SF), good prior experience (GPE) and recovery on overall customer satisfaction and repurchase intentions for multi-agents in tourism service supply chain (TSSC). It specifically focuses on internal and external failure and recovery.

The study employs a 2×2×3 between-subjects experimental design with 12 diverse scenarios. It aims to examine the main effects of GPE and the interaction effects of SF and recovery on overall customer satisfaction and repurchase intentions.

The main findings show that consumers do not show favorable behavioral outcomes when they have GPE with an affiliated party. Results of the experiments demonstrate that for hotels, there is no interaction effect between failure and recovery regarding overall customer satisfaction and repurchase intentions; however, for travel agencies, an interaction effect has been found. This indicates that an internal failure (by travel agency) should be recovered internally to increase the behavioral outcomes for travel agency. However, if there is an external failure (by hotel) then the essential thing is providing a recovery.

Although the service literature covers failure and recovery in diverse contexts, these concepts are rarely studied from a multi-agent perspective in the service supply chain literature. In such a chain, a failure by a different party may remain unresolved, and this may create a positive effect on another party, if they provide recovery for the failure. This means that the doer of the failure and/or recovery (the party responsible from the failure and/or recovery) may have an impact on behavioral outcomes. However, previous literature has neglected to focus on the important issue of which entity/party performs the failure and/or recovery, and the effect on behavioral outcomes. By focusing on a principal-agent relationship in a TSSC, the study aims to address this research gap.

The purpose of this study to improve the efficiency of customer acquisition and retention through the design of salary information disclosure mechanism.

This study develops a stylized game-theoretic model of delegating customer acquisition and retention, focusing on how firms choose delegation and wage information disclosure strategy.

The results confirm the necessity for enterprises to disclose salary information. When sales agents are risk neutral, firms should choose multi-agent (MA) delegation and disclose their wages. However, when agents are risk averse, firms may disclose the wages of acquisition agents or both agents in MA delegation, depending on the uncertainty of the retention market.

This paper contributes to the literature on delegation of customer acquisition and retention and demonstrates that salary disclosure can be used as a supplement to the incentive mechanism.

Sharing of risk benefits supplies network collaborations. The complex mix of heterogeneous collaborators in supply networks, however, also increases the complexity of the risk profiles of inter‐related components within these networks. For a given network collaboration, several structures of network relationship are possible, with each carrying distinctive risk implications. This paper seeks to develop a conceptual framework for analysing the differential risks in alternative network structures.

To capture the structural significance of inter‐organisational dependency in networks, alternative typology of network relationships is formulated using agency theory. Basic constructs were developed for analysing risks in supply networks, with configurations ranging from the single‐principal, single‐agent to the complex multi‐principal, multi‐agent scenarios.

The study finds that dynamics of risk in network systems depend not only on the typology of networks, but also on the functional role of each collaborator inherent in the network through agreements on supply and incentives, and supply performance.

The proposed framework provides a structured approach for identifying and assessing risk dynamics and their differential impacts on different levels of supply networks. It provides insights into the dynamics of risk events and identifies network configurations that are vulnerable to different levels of risk.