Emerging Requirements for Technology Management: A Sector-based Scenario Planning Approach

Authors

  • Simon Patrick Philbin Imperial College London

DOI:

https://doi.org/10.4067/S0718-27242013000400004

Keywords:

technology management, technology forecasting, scenario planning, healthcare, energy, higher education

Abstract

Identifying the emerging requirements for technology management will help organisations to prepare for the future and remain competitive. Indeed technology management as a discipline needs to develop and respond to societal and industrial needs as well as the corresponding technology challenges. Therefore, following a review of technology forecasting methodologies, a sector-based scenario planning approach has been used to derive the emerging requirements for technology management. This structured framework provided an analytical lens to focus on the requirements for managing technology in the healthcare, energy and higher education sectors over the next 5-10 years. These requirements include the need for new business models to support the adoption of technologies; integration of new technologies with existing delivery channels; management of technology options including R&D project management; technology standards, validation and interoperability; and decision-making tools to support technology investment.

Downloads

Download data is not yet available.

Author Biography

Simon Patrick Philbin, Imperial College London

Dr Simon P Philbin is Associate Director of Enterprise Projects at Imperial College London and also Visiting Fellow at Imperial College Business School.  Dr Philbin holds a BSc (University of Birmingham) and PhD (Brunel University), both in chemistry as well as an MBA with Distinction from the Open University Business School.  He is published widely across several areas including project management, systems engineering, university-industry research collaboration and chemistry.  Dr Philbin is a recipient of the Merritt Williamson best paper award from the American Society for Engineering Management and the Rod Rose best paper award from the Society of Research Administrators International.

References

ALLEN, I. E., Seaman, J. (2011). Going the Distance: Online Education in the United States, 2011. Babson Survey Research Group.

AMER, M., Daim, T. U., Jetter, A. (2013). A review of scenario planning. Futures, 46, 23-40.

ANDERSON, S., Newell, R. (2004). Prospects for carbon capture and storage technologies. Annual Review of Environment and Resources, 29, 109-142.

BASHIR, R. (2013). Direct DNA Sequencing Using Nanopore Sensors. Genetic Engineering & Biotechnology News, 33(7), 34-35.

BEGLEY, C. G., Ellis, L. M. (2012). Drug development: Raise standards for preclinical cancer research. Nature, 483(7391), 531-533.

BOOTH, H. (2006). Demographic forecasting: 1980 to 2005 in review. International Journal of Forecasting, 22(3), 547–581.

BJERRUM, O. J. (2002). New Safe Medicines Faster: a proposition for a pan-European research effort. Nature Reviews Drug Discovery, 1, 395-398.

BOELLAARD, R., et al. (2010). FDG PET and PET/CT: EANM procedure guidelines for tumour PET imaging: version 1.0. European Journal of

Nuclear Medicine and Molecular Imaging, 37(1), 181-200.

CASALINO, L., Magnani, D., De Falco, S., Filosa, S., Minchiotti, G., Patriarca, E. J., De Cesare, D. (2012). An Automated High Throughput Screening-

Compatible Assay to Identify Regulators of Stem Cell Neural Differentiation, Molecular Biotechnology, 50(3), 171-180.

CHAWLA, K. K. (2009). Composite Materials: Science and Engineering, 3rd Edition, Springer.

COOPER, R., Wootton, A. B. and Bruce, M. (1998). “Requirements capture”: theory and practice. Technovation, 18 (8/9), 497-511.

COOPER, S. Sahami, M. (2013). Reflections on Stanford's MOOCs. Communications of the ACM, 56(2), 28-30.

DE BELLIS, N. (2009). Bibliometrics and Citation Analysis: from the Science Citation Index to Cybermetrics. Scarecrow Press.

FYE, S. R., Charbonneau, S. M., Hay, J. W., Carie A. Mullins, C. A. (2013). An examination of factors affecting accuracy in technology forecasts. Technological Forecasting and Social Change, 80(6), 1222-1231.

GARCIA, M. L. Bray, O. H. (1998). Fundamentals of Technology Roadmapping. NM: Sandia National Laboratories Report, SAND97-0665, 3-34.

GERDSRI, N., Vatananan, R. S., Dansamasatid, S. (2009). Dealing with the dynamics of technology roadmapping implementation: A case study. Technological Forecasting and Social Change, 76(1), 50–60.

HSIAO, C. J., Hing E. (2012) Use and characteristics of electronic health record systems among office-based physician practices: United States, 2001–2012. NCHS Data Brief, No. 111. Hyattsville, MD: National Center for Health Statistics.

IRFAN, M. F., Muhammad R. Usman, M. R., K. Kusakabe, K. (2011). Coal gasification in CO2 atmosphere and its kinetics since 1948: A brief review. Energy, 36(1), 12-40.

JOHNSTONE, D. B., Arora, A., Experton, W. (1998). The financing and management of higher education: A status report on worldwide reforms. Washington, DC: World Bank.

LEA, M. R., Jones, S. (2011). Digital literacies in higher education: exploring textual and technological practice. Studies in Higher Education, 36(4), 377-393.

LUTZ, C., Lehr, U., Wiebe, K. S. (2012). Economic effects of peak oil. Energy Policy, 48, 829-834.

MANN, D. L. (2003). Better technology forecasting using systematic innovation methods. Technological Forecasting and Social Change, 70(8), 779-795.

MARINGE, F., Foskett, N. (2010). Globalization and internationalization in higher education: Theoretical, strategic and management perspectives. Continuum.

MORRISON. L. G., Yardley, L., Powell, J., Susan Michie, S. (2012). What Design Features Are Used in Effective e-Health Interventions? A Review Using Techniques from Critical Interpretive Synthesis. Telemedicine and e-Health, 18(2), 137-144.

NAWAZ, A., Kundi, G. M. (2011). Users of e-learning in higher education institutions (HEIs): perceptions, styles and attitudes. International Journal of Teaching and Case Studies, 3(2), 161-174.

NO, H. J., Park, Y. (2010). Trajectory patterns of technology fusion: Trend analysis and taxonomical grouping in nanobiotechnology, Technological Forecasting and Social Change, 77(1), 63-75.

OKOLI, C., Pawlowski, S. D. (2004). The Delphi method as a research tool: an example, design considerations and applications. Information & Management, 42(1), 15–29.

ORSZAG, P. R., Ellis, P. (2007). The challenge of rising health care costs-a view from the Congressional Budget Office. New England Journal of Medicine, 357(18), 1793-1795.

PEIDONG, Z., Yanli, Y., Yonghong, Z., Lisheng, W., Xinrong, L. (2009). Opportunities and challenges for renewable energy policy in China. Renewable and Sustainable Energy Reviews, 13(2), 439-449.

PHAAL, R., Farrukh, C. J. P., Probert, D. R. (2004). Technology roadmapping—A planning framework for evolution and revolution. Technological Forecasting and Social Change, 71(1-2), 5-26.

PHILBIN, S. (2008). Process model for university-industry research collaboration", European Journal of Innovation Management, 11(4), 488-521.

RAMKRISHNA, S. (2008). Biotechnology in petroleum recovery: The microbial EOR. Progress in Energy and Combustion Science, 34(6), 714-724.

RATNER, M. (2011). Pfizer reaches out to academia—again. Nature Biotechnology, 29, 3-4.

ROPER, A. T., Cunningham, S. W., Porter, A. L., Mason, T. W., Rossini, F. A., Banks, J. (1991). Forecasting and Management of Technology, 2nd Edition,

Wiley & Sons, New York.

SCHOEMAKER, P. J. H. (1995). Scenario planning: a tool for strategic thinking. Sloan Management Review, 36(2), 25-40.

SHIN, T. (1998). Using Delphi for a Long-Range Technology Forecasting, and Assessing Directions of Future R&D Activities The Korean Exercise. Technological Forecasting and Social Change, 58(1-2), 125-154.

SUTCLIFFE, A.G., Maiden, N.A.M., Minocha, S., Manuel, D. (1998). Supporting scenario-based requirements engineering. IEEE Transactions on Software Engineering, 24(12), 1072-1088.

TRAINER, T. (2012). A critique of Jacobson and Delucchi’s proposals for a world renewable energy supply. Energy Policy, 44, 476-481.

U.S. ENERGY INFORMATION ADMINSTRATION (2011). International Energy Outlook, DOE/EIA-0484.

WAGNER, J., Armstrong, K. (2010). Managing environmental and social risks in international oil and gas projects: Perspectives on compliance, Journal of

World Energy Law & Business, 3(2), 140-165.

WANG, D. H.-M., Yu, T. H.-K., Liu, H.-Q. (2013). Heterogeneous effect of high-tech industrial R&D spending on economic growth. Journal of Business Research, 66(10), 1990-1993.

WACK, P. (1985). Scenarios: uncharted waters ahead. Harvard Business Review, 63(5), 72-89.

WATTS, R, J., Porter, A. L. (1997). Innovation forecasting. Technological Forecasting and Social Change, 56(1), 25–47.

YAGER, P., Edwards, T., Fu, E., Helton, K., Nelson, K., Tam, M. R., Weigl, B. H. (2006). Microfluidic diagnostic technologies for global public health,

Nature, 442, 412-418.

YANG, J., Wei, Z., Chengzhi, L. (2009). Optimal design and techno-economic analysis of a hybrid solar–wind power generation system. Applied Energy, 86(2), 163–169.

ZINKLE, S. J. (2005). Advanced materials for fusion technology. Fusion Engineering and Design. 74(1-4), 31-40.

ZWEIBEL, K. (1990). Harnessing solar power: The photovoltaics challenge. Plenum Press: New York.

Downloads

Published

2013-09-24

How to Cite

Philbin, S. P. (2013). Emerging Requirements for Technology Management: A Sector-based Scenario Planning Approach. Journal of Technology Management & Innovation, 8(3), 34–44. https://doi.org/10.4067/S0718-27242013000400004

Issue

Section

Research Articles