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Competitive Benchmarking: An IS Research Approach to Address Wicked Problems with Big Data and Analytics

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  • Ketter, W.
  • Peters, M.
  • Collins, J.
  • Gupta, A.

Abstract

Wicked problems like sustainable energy and financial market stability are societal challenges that arise from complex socio-technical systems in which numerous social, economic, political, and technical factors interact. Understanding and mitigating them requires research methods that scale beyond the traditional areas of inquiry of Information Systems (IS) “individuals, organizations, and markets” and that deliver solutions in addition to insights. We describe an approach to address these challenges through Competitive Benchmarking (CB), a novel research method that helps interdisciplinary research communities to tackle complex challenges of societal scale by using different types of data from a variety of sources such as usage data from customers, production patterns from producers, public policy and regulatory constraints, etc. for a given instantiation. Further, the CB platform generates data that can be used to improve operational strategies and judge the effectiveness of regulatory regimes and policies. We describe our experience applying CB to the sustainable energy challenge in the Power Trading Agent Competition (Power TAC) in which more than a dozen research groups from around the world jointly devise, benchmark, and improve IS-based solutions.

Suggested Citation

  • Ketter, W. & Peters, M. & Collins, J. & Gupta, A., 2015. "Competitive Benchmarking: An IS Research Approach to Address Wicked Problems with Big Data and Analytics," ERIM Report Series Research in Management ERS-2015-015-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:eureri:79158
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    References listed on IDEAS

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    1. Wolfgang Ketter & John Collins & Maria Gini & Alok Gupta & Paul Schrater, 2012. "Real-Time Tactical and Strategic Sales Management for Intelligent Agents Guided by Economic Regimes," Information Systems Research, INFORMS, vol. 23(4), pages 1263-1283, December.
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    4. Herbert A. Simon, 1996. "The Sciences of the Artificial, 3rd Edition," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262691914, December.
    5. Bae, Mungyu & Kim, Hwantae & Kim, Eugene & Chung, Albert Yongjoon & Kim, Hwangnam & Roh, Jae Hyung, 2014. "Toward electricity retail competition: Survey and case study on technical infrastructure for advanced electricity market system," Applied Energy, Elsevier, vol. 133(C), pages 252-273.
    6. A. Pyka & G. Fagiolo, 2007. "Agent-based Modelling: A Methodology for Neo-Schumpetarian Economics," Chapters, in: Horst Hanusch & Andreas Pyka (ed.), Elgar Companion to Neo-Schumpeterian Economics, chapter 29, Edward Elgar Publishing.
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    Cited by:

    1. Nguyen Anh Khoa Dam & Thang Le Dinh & William Menvielle, 2019. "A systematic literature review of big data adoption in internationalization," Journal of Marketing Analytics, Palgrave Macmillan, vol. 7(3), pages 182-195, September.
    2. Johannes Kaufmann & Philipp Artur Kienscherf & Wolfgang Ketter, 2020. "Modeling and Managing Joint Price and Volumetric Risk for Volatile Electricity Portfolios," Energies, MDPI, vol. 13(14), pages 1-19, July.

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    Keywords

    benchmarking; big data analytics; design science; energy information services; research competitions; smart grids; sustainability; virtual worlds;
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