Agent-based simulation of electricity markets: a literature review

Liberalisation, climate policy and promotion of renewable energy are challenges to players of the electricity sector in many countries. Policy makers have to consider issues like market power, bounded rationality of players and the appearance of fluctuating energy sources in order to provide adequate legislation. Furthermore the interactions between markets and environmental policy instruments become an issue of increasing importance. A promising approach for the scientific analysis of these developments is the field of agent-based simulation. The goal of this article is to provide an overview of the current work applying this methodology to the analysis of electricity markets. --

Market-based Recommendation: Agents that Compete for Consumer Attention

The amount of attention space available for recommending suppliers to consumers on e-commerce sites is typically limited. We present a competitive distributed recommendation mechanism based on adaptive software agents for efficiently allocating the 'consumer attention space', or banners. In the example of an electronic shopping mall, the task is delegated to the individual shops, each of which evaluates the information that is available about the consumer and his or her interests (e.g. keywords, product queries, and available parts of a profile). Shops make a monetary bid in an auction where a limited amount of 'consumer attention space' for the arriving consumer is sold. Each shop is represented by a software agent that bids for each consumer. This allows shops to rapidly adapt their bidding strategy to focus on consumers interested in their offerings. For various basic and simple models for on-line consumers, shops, and profiles, we demonstrate the feasibility of our system by evolutionary simulations as in the field of agent-based computational economics (ACE). We also develop adaptive software agents that learn bidding strategies, based on neural networks and strategy exploration heuristics. Furthermore, we address the commercial and technological advantages of this distributed market-based approach. The mechanism we describe is not limited to the example of the electronic shopping mall, but can easily be extended to other domains

Modeling toothpaste brand choice: An empirical comparison of artificial neural networks and multinomial probit model

Copyright @ 2010 Atlantis PressThe purpose of this study is to compare the performances of Artificial Neural Networks (ANN) and Multinomial Probit (MNP) approaches in modeling the choice decision within fast moving consumer goods sector. To do this, based on 2597 toothpaste purchases of a panel sample of 404 households, choice models are built and their performances are compared on the 861 purchases of a test sample of 135 households. Results show that ANN's predictions are better while MNP is useful in providing marketing insight

Q-Strategy: A Bidding Strategy for Market-Based Allocation of Grid Services

The application of autonomous agents by the provisioning and usage of computational services is an attractive research field. Various methods and technologies in the area of artificial intelligence, statistics and economics are playing together to achieve i) autonomic service provisioning and usage of Grid services, to invent ii) competitive bidding strategies for widely used market mechanisms and to iii) incentivize consumers and providers to use such market-based systems. The contributions of the paper are threefold. First, we present a bidding agent framework for implementing artificial bidding agents, supporting consumers and providers in technical and economic preference elicitation as well as automated bid generation by the requesting and provisioning of Grid services. Secondly, we introduce a novel consumer-side bidding strategy, which enables a goal-oriented and strategic behavior by the generation and submission of consumer service requests and selection of provider offers. Thirdly, we evaluate and compare the Q-strategy, implemented within the presented framework, against the Truth-Telling bidding strategy in three mechanisms – a centralized CDA, a decentralized on-line machine scheduling and a FIFO-scheduling mechanisms

Neo-Schumpeterian Simulation Models

The use of simulation modelling techniques by neo-Schumpeterian economists dates back to Nelson and Winter’s 1982 book “An Evolutionary Theory of Economic Change”, and has rapidly expanded ever since. This paper considers the way in which successive generations of models have extended the boundaries of research (both with respect to the range of phenomena considered and the different dimensions of innovation that are considered), and while simultaneously introducing novel modelling techniques. At the same time, the paper will highlight the distinct set of features that have emerged in these neo-Schumpeterian models, and which set them apart from the models developed by other schools. In particular, they share a distinct view about the type of world in which real economic agents operate, and a invariably contain a generic set of algorithms. In addition to reviewing past models, the paper considers a number of pressing issues that remain unresolved and which modellers will need to address in future. Notable amongst these are the methodological relationship between empirical studies and simulation (e.g. ‘history friendly modelling’), the development of common standards for sensitivity analysis, and the need to further extend the boundaries of research in order to consider important aspects of innovation and technical change.macroeconomics ;

Risk Perceptions, Social Interactions and the Influence of Information on Social Attitudes to Agricultural Biotechnology

We assess Canadian’s risk perceptions for genetically modified (GM) food and probe influences of socio-economic, demographic and other factors impinging on these perceptions. An internet-administered questionnaire with two stated choice split-sample experiments that approximate market choices of individual grocery shoppers is applied to elicit purchase behavior from 882 respondents across Canada. Data are collected to assess the influence on respondents’ choices for a specific food product (bread) of 1) product information which varies in content and by source and 2) information provided through labeling. These data also enable: a) analysis of trade-offs made by consumers between possible risks associated with GM ingredients and potential health or environment benefits in food and b) assessment of influences on respondents’ search for/access of product information. We rigorously document the extent and type of variation in Canadian consumers’ attitudes and risk perceptions for a selected GM food. This is pursued in analysis of experiment 1) data using a latent class model to analyze 445 consumers’ choices for bread products. We identify four distinct groups of Canadian consumers: 51% (value seekers) valued additional health or environmental benefits and were indifferent to GM content; traditional consumers (14 %) preferred their normally-purchased food; fringe consumers (4%) valued the health attribute and could defer consumption. Another 32 % (anti-GM) strongly opposed GM ingredients in food irrespective of introduced attributes. Thus there is a dichotomy in Canadian attitudes to GM content in food: a small majority of the sample (55 per cent) perceive little or no risk from GM food, but this is strongly opposed by 46% of respondents. Differences in gender, number of children in the household, education, and age are associated with the likelihood of segment membership. We also report on the search for information on characteristics of the GM food by a sample of 445 respondents with opportunity for voluntary access to related information through hyperlinks in the survey. Slightly less than half actually sought such information. Gender, employment status, rural or urban residency and the number of children in the household all affected the probability that respondents would access information. A further research component examines product choices made in the context of two common GM labeling policies: mandatory and voluntary labeling. We find these two types of strategies to have distinctive impacts on consumers and on measures of social welfare. Knowledge of these may help policy makers to make more informed analyses of the alternative labeling policies. Specific findings also provide base-line measures of Canadians’ attitudes to risks of GM technology in the context of food and environmental risks, as well as documenting the importance of context influences and reference points on consumers’ preferences for GM food. We also develop methodological improvements for accurately estimating the value of information on a negative attribute. The project built upon initial findings from a previous AARI project (#AARI Project #2000D037) and is complemented by research supported through a Genome Prairie GE3LS (Genetics, Ethics, Environment, Economics, Law and Society) project: “Commercialization and society: its policy and strategic implications.”Research and Development/Tech Change/Emerging Technologies,

MEASURING U.S. CONSUMER PREFERENCES FOR GENETICALLY MODIFIED FOODS USING CHOICE MODELING EXPERIMENTS: THE ROLE OF PRICE, PRODUCT BENEFITS AND TECHNOLOGY

Food biotechnology promises to deliver a wide range of enhanced consumer benefits. This study models consumer's willingness to trade-off the potential risks of GM foods with the possibility of extracting significant benefits. The results of the choice modeling experiments reflect how different attributes of price, product benefits, and technology influence consumer demand for genetically modified food products. The results suggest that direct health, environmental, and production related benefits have a positive effect on choice. The results also generally show that genetic modification is viewed negatively, with use of bacterium and animal based genetic modification being viewed more negatively than the use of plant based genetic modification.Research and Development/Tech Change/Emerging Technologies,