Agent-based transportation planning compared with scheduling heuristics

Here we consider the problem of dynamically assigning vehicles to transportation orders that have di¤erent time windows and should be handled in real time. We introduce a new agent-based system for the planning and scheduling of these transportation networks. Intelligent vehicle agents schedule their own routes. They interact with job agents, who strive for minimum transportation costs, using a Vickrey auction for each incoming order. We use simulation to compare the on-time delivery percentage and the vehicle utilization of an agent-based planning system to a traditional system based on OR heuristics (look-ahead rules, serial scheduling). Numerical experiments show that a properly designed multi-agent system may perform as good as or even better than traditional methods

EDI and intelligent agents integration to manage food chains

Electronic Data Interchange (EDI) is a type of inter-organizational information system, which permits the automatic and structured communication of data between organizations. Although EDI is used for internal communication, its main application is in facilitating closer collaboration between organizational entities, e.g. suppliers, credit institutions, and transportation carriers. This study illustrates how agent technology can be used to solve real food supply chain inefficiencies and optimise the logistics network. For instance, we explain how agribusiness companies can use agent technology in association with EDI to collect data from retailers, group them into meaningful categories, and then perform different functions. As a result, the distribution chain can be managed more efficiently. Intelligent agents also make available timely data to inventory management resulting in reducing stocks and tied capital. Intelligent agents are adoptive to changes so they are valuable in a dynamic environment where new products or partners have entered into the supply chain. This flexibility gives agent technology a relative advantage which, for pioneer companies, can be a competitive advantage. The study concludes with recommendations and directions for further research

Research Framework, Strategies, And Applications Of Intelligent Agent Technologies (IATs) In Marketing

In this digital era, marketing theory and practice are being transformed by increasing complexity due to information availability, higher reach and interactions, and faster speeds of transactions. These have led to the adoption of intelligent agent technologies (IATs) by many companies. As IATs are relatively new and technologically complex, several definitions are evolving, and the theory in this area is not yet fully developed. There is a need to provide structure and guidance to marketers to further this emerging stream of research. As a first step, this paper proposes a marketing-centric definition and a systematic taxonomy and framework. The authors, using a grounded theory approach, conduct an extensive literature review and a qualitative study in which interviews with managers from 50 companies in 22 industries reveal the importance of understanding IAT applications and adopting them. Further, the authors propose an integrated conceptual framework with several propositions regarding IAT adoption. This research identifies the gaps in the literature and the need for adoption of IATs in the future of marketing given changing consumer behavior and product and industry characteristics

Research Framework, Strategies, And Applications Of Intelligent Agent Technologies (IATs) In Marketing

In this digital era, marketing theory and practice are being transformed by increasing complexity due to information availability, higher reach and interactions, and faster speeds of transactions. These have led to the adoption of intelligent agent technologies (IATs) by many companies. As IATs are relatively new and technologically complex, several definitions are evolving, and the theory in this area is not yet fully developed. There is a need to provide structure and guidance to marketers to further this emerging stream of research. As a first step, this paper proposes a marketing-centric definition and a systematic taxonomy and framework. The authors, using a grounded theory approach, conduct an extensive literature review and a qualitative study in which interviews with managers from 50 companies in 22 industries reveal the importance of understanding IAT applications and adopting them. Further, the authors propose an integrated conceptual framework with several propositions regarding IAT adoption. This research identifies the gaps in the literature and the need for adoption of IATs in the future of marketing given changing consumer behavior and product and industry characteristics

Understanding Online Reverse Auction Determinants of Use: A Multi-Stakeholder Case Study

Various interorganizational systems (IOS) such as Electronic Data Interchange (EDI) and Supply Chain Management Systems (SCMS) have attracted significant attention among information system (IS) researchers. However, IS scholars have taken less interest in Online Reverse Auctions (ORAs), a widely used IOS in online business-to-business transactions. This study examines the factors that enable and/or inhibit ORA use from the perspective of buyers and suppliers, as well as the potential role of the institutional context based on a case study of a French retailer. Building on 122 semi-structured interviews collected in two stages with various stakeholders from the interorganizational community (buyers, suppliers and technology initiators), we demonstrate the extent to which the determinants of ORA use differ between buyers and suppliers (e.g. perceived outcomes, capabilities required to use ORAs). We then show how a change in the institutional context not only failed to redress distrust between buyers and suppliers, but also created new barriers to ORA use by introducing controls and sanctions that outweighed the economic benefits of ORA use among buyers. We contribute to the IS literature by demonstrating the role of strategic capabilities in shaping use. While the IS literature acknowledges the institutional context as a determinant of use, little is known about the extent to which a change in the institutional context may affect ORA use. Our research shows the extent to which legislation can trigger IT discontinuance because of the perceived risk introduced

Norms of Punishment: Experiments with students and the General Population

Norms of cooperation and punishment differ across societies, but also within a single society. In an experiment with two subject pools sharing the same geographical and cultural origins, we show that opportunities for peer punishment increase cooperation among students but not in the general population. In previous studies, punishment magnified the differences across societies in people\u2019s ability to cooperate. Here, punishment reversed the order: with punishment, students cooperate more than the general population while they cooperate less without it

Emotions and Emotion Regulation in Economic Decision Making

By employing the methodology of experimental economics, the thesis examines the influence of emotions on decision making in electronic auction markets. Subjects\u27 emotional processes are measured by psychophysiological indicators, helping to decipher the coherence of information, emotion (regulation) and decision making. Four chapters build the main body of the thesis and all are constructed similarly: introduction, design, method, results, limitations, theoretical and managerial implications

A Mechanism Design Approach to Bandwidth Allocation in Tactical Data Networks

The defense sector is undergoing a phase of rapid technological advancement, in the pursuit of its goal of information superiority. This goal depends on a large network of complex interconnected systems - sensors, weapons, soldiers - linked through a maze of heterogeneous networks. The sheer scale and size of these networks prompt behaviors that go beyond conglomerations of systems or `system-of-systems\u27. The lack of a central locus and disjointed, competing interests among large clusters of systems makes this characteristic of an Ultra Large Scale (ULS) system. These traits of ULS systems challenge and undermine the fundamental assumptions of today\u27s software and system engineering approaches. In the absence of a centralized controller it is likely that system users may behave opportunistically to meet their local mission requirements, rather than the objectives of the system as a whole. In these settings, methods and tools based on economics and game theory (like Mechanism Design) are likely to play an important role in achieving globally optimal behavior, when the participants behave selfishly. Against this background, this thesis explores the potential of using computational mechanisms to govern the behavior of ultra-large-scale systems and achieve an optimal allocation of constrained computational resources Our research focusses on improving the quality and accuracy of the common operating picture through the efficient allocation of bandwidth in tactical data networks among self-interested actors, who may resort to strategic behavior dictated by self-interest. This research problem presents the kind of challenges we anticipate when we have to deal with ULS systems and, by addressing this problem, we hope to develop a methodology which will be applicable for ULS system of the future. We build upon the previous works which investigate the application of auction-based mechanism design to dynamic, performance-critical and resource-constrained systems of interest to the defense community. In this thesis, we consider a scenario where a number of military platforms have been tasked with the goal of detecting and tracking targets. The sensors onboard a military platform have a partial and inaccurate view of the operating picture and need to make use of data transmitted from neighboring sensors in order to improve the accuracy of their own measurements. The communication takes place over tactical data networks with scarce bandwidth. The problem is compounded by the possibility that the local goals of military platforms might not be aligned with the global system goal. Such a scenario might occur in multi-flag, multi-platform military exercises, where the military commanders of each platform are more concerned with the well-being of their own platform over others. Therefore there is a need to design a mechanism that efficiently allocates the flow of data within the network to ensure that the resulting global performance maximizes the information gain of the entire system, despite the self-interested actions of the individual actors. We propose a two-stage mechanism based on modified strictly-proper scoring rules, with unknown costs, whereby multiple sensor platforms can provide estimates of limited precisions and the center does not have to rely on knowledge of the actual outcome when calculating payments. In particular, our work emphasizes the importance of applying robust optimization techniques to deal with the uncertainty in the operating environment. We apply our robust optimization - based scoring rules algorithm to an agent-based model framework of the combat tactical data network, and analyze the results obtained. Through the work we hope to demonstrate how mechanism design, perched at the intersection of game theory and microeconomics, is aptly suited to address one set of challenges of the ULS system paradigm - challenges not amenable to traditional system engineering approaches