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Envisioning and Enabling Sustainable Smart Markets

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  • Ketter, W.

Abstract

__Abstract__ Many of the world’s most urgent problems such as climate change, population growth, poverty, malnutrition and environmental degradation not only demand solutions but also require us to find more sustainable ways of living. Market mechanisms can be effective in solving large-scale resource allocation problems of this kind, but only if the market design reflects the social costs. The growth and spread of advanced information and communication technologies mean that new smart markets offer a way to achieve this and will become central to many areas of economic activity. However, the volumes of data and speed of transactions involved place a burden on human decisionmaking capabilities, and information systems can have a central role to play in helping to devise solutions – in particular, in developing intelligent software agents to provide decision support. This address looks at the challenges and opportunities involved for information systems researchers, and sets out an agenda for sustainable smart markets research, centered on collaborative approaches. It focuses on three overlapping areas: market and learning agent design; market evaluation using autonomous learning agents; and real-time decision support. Examples are included of current work on sustainable smart markets for electricity (smart grid) and for flowers (Dutch Flower Auctions).

Suggested Citation

  • Ketter, W., 2014. "Envisioning and Enabling Sustainable Smart Markets," ERIM Inaugural Address Series Research in Management EIA-2014-057-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam..
  • Handle: RePEc:ems:euriar:51584
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    References listed on IDEAS

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    More about this item

    Keywords

    Agent-based Decision Support; Competitive Benchmarking; Energy Information Systems; Sustainable Energy; Machine Learning; Mechanism Design; Preference Modeling; Smart Grid; Supply Chain Management;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D4 - Microeconomics - - Market Structure, Pricing, and Design
    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products

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