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

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

Modellierungskonzepte der Synergetik und der Theorie der Selbstorganisation

Mnay models situated in the current research landscape of modelling and simulating social processes have roots in physics. This is visible in the name of specialties as Econophysics or Sociophysics. This chapter describes the history of knowledge transfer from physics, in particular physics of self-organization and evolution, to the social sciences. We discuss why physicists felt called to describe social processes. Across models and simulations the question how to explain the emergence of something new is the most intriguing one. We present one model approach to this problem and introduce a game -- Evolino -- inviting a larger audience to get acquainted with abstract evolution-theory approaches to describe the quest for new ideas.Comment: In German, extended first version, final version Ebeling, W., & Scharnhorst, A. (2015). Modellierungskonzepte der Synergetik und der Theorie der Selbstorganisation. In N. Braun & N. J. Saam (Eds.), Handbuch Modellbildung und Simulation in den Sozialwissenschaften (pp. 419--452). Wiesbaden: Springer Fachmedien Wiesbaden. doi:10.1007/978-3-658-01164-2 (in German

Agency and structure: a social simulation of knowledge-intensive industries

Modern knowledge-intensive economies are complex social systems where intertwining factors are responsible for the shaping of emerging industries: the self-organising interaction patterns and strategies of the individual actors (an agencyoriented pattern) and the institutional frameworks of different innovation systems (a structure-oriented pattern). In this paper, we examine the relative primacy of the two patterns in the development of innovation networks, and find that both are important. In order to investigate the relative significance of strategic decision making by innovation network actors and the roles played by national institutional settings, we use an agent-based model of knowledge-intensive innovation networks, SKIN.We experiment with the simulation of different actor strategies and different access conditions to capital in order to study the resulting effects on innovation performance and size of the industry. Our analysis suggests that actors are able to compensate for structural limitations through strategic collaborations. The implications for public policy are outlined

A new model for university-industry links in knowledge-based economies

In this paper, we apply the agent-based SKIN model (Simulating Knowledge Dynamics in Innovation Networks) to university-industry links. The model builds on empirical research about innovation networks in knowledge-intensive industries with procedures relying on theoretical frameworks of innovation economics and economic sociology. Our experiments compare innovation networks with and without university agents. Results show that having universities in the co-operating population of actors raises the competence level of the whole population, increases the variety of knowledge among the firms, and increases innovation diffusion in terms of quantity and speed. Furthermore, firms interacting with universities are more attractive for other firms when new partnerships are considered. These results can be validated against empirical findings. The simulation confirms that university-industry links improve the conditions for innovation diffusion and enhance collaborative arrangements in innovation networks

A new model for university-industry links in knowledge-based economies

In this paper, we apply the agent-based SKIN model (Simulating Knowledge Dynamics in Innovation Networks) to university-industry links. The model builds on empirical research about innovation networks in knowledge-intensive industries with procedures relying on theoretical frameworks of innovation economics and economic sociology. Our experiments compare innovation networks with and without university agents. Results show that having universities in the co-operating population of actors raises the competence level of the whole population, increases the variety of knowledge among the firms, and increases innovation diffusion in terms of quantity and speed. Furthermore, firms interacting with universities are more attractive for other firms when new partnerships are considered. These results can be validated against empirical findings. The simulation confirms that university-industry links improve the conditions for innovation diffusion and enhance collaborative arrangements in innovation networks