Inefficiencies in Digital Advertising Markets

Digital advertising markets are growing and attracting increased scrutiny. This article explores four market inefficiencies that remain poorly understood: ad effect measurement, frictions between and within advertising channel members, ad blocking, and ad fraud. Although these topics are not unique to digital advertising, each manifests in unique ways in markets for digital ads. The authors identify relevant findings in the academic literature, recent developments in practice, and promising topics for future research

The viability of spectrum trading markets

Spectrum trading markets are of growing interest to many spectrum management agencies. They are motivated by their desire to increase the use of market based mechanisms for spectrum management and reduce their emphasis on command and control methods. Despite the liberalization of regulations on spectrum trading in some countries, spectrum markets have not yet emerged as a key spectrum assignment component. The lack of liquidity in these markets is sometimes cited as a primary factor in this outcome. This work focuses on determining the conditions for viability of spectrum trading markets by considering scenarios with different market structures, number of trading participants and amount of tradable spectrum. We make use of Agent-Based Computational Economics (ACE) to analyze each market scenario and the behaviors of its participants. Our models indicate that spectrum markets can be viable in a service if sufficient numbers of market participants exist and the amount of tradable spectrum is balanced to the demand. We use the results of this analysis and the characteristics of the viable markets found to make recommendations for the design of spectrum trading markets. Further work will explore more complicated scenarios. ©2010 IEEE

Market Based Approaches for Dynamic Spectrum Assignment

Abstract—Much of the technical literature on spectrum sharing has been on developing technologies and systems for non-cooperative) opportunistic use. In this paper, we situate this approach to secondary spectrum use in a broader context, one that includes cooperative approaches to Dynamic Spectrum Access (DSA). In this paper, we introduce readers to this broader approach to DSA by contrasting it with non-cooperative sharing (opportunistic use), surveying relevant literature, and suggesting future directions for researc

Interaction between intelligent agent strategies for real-time transportation planning

In this paper we study the real-time scheduling of time-sensitive full truckload pickup-and-delivery jobs. The problem involves the allocation of jobs to a fixed set of vehicles which might belong to dfferent collaborating transportation agencies. A recently proposed solution methodology for this problem is the use of a multi-agent system where shipper agents other jobs through sequential auctions and vehicle agents bid on these jobs. In this paper we consider such a multi-agent system where both the vehicle agents and the shipper agents are using profit maximizing look-ahead strategies. Our main contribution is that we study the interrelation of these strategies and their impact on the system-wide logistical costs. From our simulation results, we conclude that the system-wide logistical costs (i) are always reduced by using the look-ahead policies instead of a myopic policy (10-20%) and (ii) the joint effect of two look-ahead policies is larger than the effect of an individual policy. To provide an indication of the savings that might be realized with a central solution methodology, we benchmark our results against an integer programming approach

Business Models For Transport eBusiness

In this paper authors are presenting expectations from electronic commerce and its connotations on transport logistics. Based on trends, the relations between the companies in the international transport have to be strengthened using Internet business models. In the paper authors are investigating e-business information models for usage in transportbusiness models, eBusiness, digital economy, transport

Intelligent Agents for Disaster Management

ALADDIN [1] is a multi-disciplinary project that is developing novel techniques, architectures, and mechanisms for multi-agent systems in uncertain and dynamic environments. The application focus of the project is disaster management. Research within a number of themes is being pursued and this is considering different aspects of the interaction between autonomous agents and the decentralised system architectures that support those interactions. The aim of the research is to contribute to building more robust multi-agent systems for future applications in disaster management and other similar domains