Understanding Evolution in Technology Ecosystems

Topics: Computer data storage, Technology, Innovation Pages: 15 (4828 words) Published: February 5, 2013
CACM Reference Number: A2612

Gediminas Adomavicius, Jesse Bockstedt, Alok Gupta, and Robert J. Kauffman Department of Information and Decision Sciences Carlson School of Management, University of Minnesota {gadomavicius, jbockstedt, agupta, rkauffman}@csom.umn.edu

The current technological environment is becoming increasingly complex, and managers are faced with new challenges related to technology forecasting, technology investment and adoption, and new product development. The technology ecosystem model provides a principled approach to understanding evolution of technology artifacts and environment by taking into account the interdependent nature of related technologies. UNDERSTANDING TODAY’S DYNAMIC TECHNOLOGY ENVIRONMENT The current environment of business technology can be a complex place to navigate for senior managers making decisions about new product development, technology investment, and technology planning. Many industry analysts recognize that it is difficult, if not impossible, to accurately predict future technological advances. However, successful managers and entrepreneurs in today’s fast-paced, on-demand world have to understand the nature of technological change and evolution in order to accurately forecast and take advantage of investment and market opportunities. For example, there is no doubt that the VoIP industry presents huge technology investment opportunities – the VoIP equipment market is forecast to reach $8.5 billion by 2008 (Frost and Sullivan 2005). However, converging technology capabilities in this industry are making it challenging to know how VoIP will evolve, which further emphasizes the financial importance of accurate technology forecasts. There has been extensive research on the nature of innovation and technological change which provides many theories of technological evolution and numerous methods for technological forecasting. (See Porter et al. 1991 and Ziman 2000 for examples.) A critique of these models, however, is that in discussions of innovation and technology evolution, technologies are often considered individually. Instead, we argue, it is necessary to consider a system of interrelated technologies and environmental factors that influence the evolution and development of a given technology. We propose a technology ecosystem model for understanding the dynamic nature of technological evolution. The model is designed to help analysts identify the important relationships between multiple technologies that potentially affect their business decisions. The model outlines three specific roles technologies can play within an 1

CACM Reference Number: A2612 ecosystem and nine paths of influence that describe the types of impact technology roles can have on one another. Examples throughout the article illustrate various aspects of the model. TECHNOLOGY AS AN ECOSYSTEM The term technology ecosystem emphasizes the organic nature of technological development that is often absent in forecasting and analytical methods. In the biological sciences, ecosystems are composed of a population of organisms, a set or resources, and external environmental forces. Similarly, technologies coexist in an environment containing populations of technologies organized as overlapping hierarchies with many interdependent relationships (Adomavicius et al. 2007). By considering a technology ecosystem, a manager can more successfully identify factors that may impact innovation, development, and adoption of new technologies. Technology Roles We identify three specific roles that technologies can play within an ecosystem: (1) component, (2) product and application, and (3) support and infrastructure. By acting through these roles, classes of technologies influence the evolution and development of each other. The component role describes technologies when they are used as components in more complex technologies. For example, RAM chips, microprocessors,...

References: Adomavicius, G., J.C. Bockstedt, A. Gupta, and R.J. Kauffman. 2007. Technology roles in an ecosystem model of technology evolution. Information Technology and Management, 8(2), in press. CXO Media Inc. October 14, 2003. Executive summaries: Data storage. CIO Magazine Online. www.cio.com/summaries/infrastructure/storage/, last accessed November 27, 2006. Digital Technology Center Intelligent Storage Consortium (DISC) 2005. What is intelligence as it relates to storage? Intelligent Storage. www.dtc.umn.edu/disc/what.html, last accessed November 27, 2006. Frost and Sullivan. February 17, 2005. VoIP future outlook: Revenue forecast. Telephony Online. telephonyonline.com/voip/metrics/voip_revenue_forecast_021705/, last accessed November 27, 2006. Kher, V., and Y. Kim. November 2003. Decentralized authentication mechanism for objectbased storage devices. In Proceedings of the IEEE Security in Storage Workshop, Washington DC, IEEE Computing Society Press, Los Alamitos, CA, 1-10. Montalbano, E. August 29, 2005. Microsoft releases Windows File System beta. PC World Online. www.pcworld.com/article/id,122342-page,1/article.html, last accessed November 27, 2006. Morris, R. J. T., and B. J. Truskowski. 2003. The evolution of storage systems. IBM Systems Journal, 42(2): 205-217. Porter, A. L., A. T. Roper, T. W. Mason, F. A. Rossini, and J. Banks. 1991. Forecasting and Management of Technology. Wiley-Interscience, New York, NY. Roush, W. October 2003. The Internet reborn. Technology Review, 28-37. Service, R. July 2005. Intel’s breakthrough. Technology Review, 62-65. Ziman, J. M. (Ed.) 2000. Technological Innovation as an Evolutionary Process. Cambridge University Press, London, United Kingdom. 12
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