Journal of Organization and Human Behaviour

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

An Exploration of Enhancing Adoption and Agility in Technological Changes


Affiliations
1 Department of Management Sciences, Savitribai Phule Pune University, Pune, Maharashtra, India
     

   Subscribe/Renew Journal


In the present paper, the optimal way of increasing employee’s adoption and agility in technological changes and the proper designed strategies suggested by scholars to managers as policy makers to manipulate these technological changes and develop the foremost approach to control unexpected changes in companies are explored. After investigating related works and scrutinising numerous approaches surrounding managing technological changes; it is perceived a successful technological change management depends, to a great extent, on employees’ capabilities to be more adopted and agile in implementing new technologies satisfactorily. Since employees play the main role in accomplishing technological tasks, they should possess skills related to those new technologies. As keeping regular employees has some obstacles mentioned in the following; the optimal option of having skilled staff with more adoption and agility in technological changes can be produced through contingent workforce system in the light of vintage human capital model in this study. Besides, technology diffusion theory is considered marginally in this paper to manifest the presence of employees’ adoption and agility in technological changes.

Keywords

Technological Change, Adoption, Agility, Contingent Workforce, Technology Diffusion, Vintage Human Capital Model.
Subscription Login to verify subscription
User
Notifications
Font Size

  • Attewell, P. (1992). Technology diffusion and organizational learning: The case of business computing. Organization Science, 3(1), 1-19.

  • Bartel, A. P., & Lichtenberg, F. R. (1987). The comparative advantage of educated workers in implementing new technology. Review of Economics and Statistics, 69, 1-11.

  • Baskerville, R. L., Mathiassen, L., & Pries-Heje, J. (2005). Business agility and information technology diffusion. Springer, Atlanta, Georgia, U.S.A.

  • Bass, F. M. (1969). A new product growth for model consumer durables. Management Science, 15(5), 215-227.

  • Borjesson, A., Martinsson, F., & Timmeras, M. (2006). Agile improvement practices in software organizations. European Journal of Information Systems, 15(2), 169-182.

  • Bureau of Labor Statistics. (2005). Contingent and alternative employment arrangements. U.S. Bureau of Labor Statistics. Retrieved from http://www.bls.gov/news.release/conemp.nr0.htm

  • Chari, V. V., & Hopenhayn, H. (1987). Vintage human capital, growth, and the diffusion of new technology. Federal Reserve Bank of Minneapolis Research Department. Working Paper 375.

  • Chari, V. V., & Hopenhayn, H. (1991). Vintage human capital, growth, and diffusion of new technology. The Journal of Political Economy, 99(6), 1142-1165.

  • Christie, I., Northcott, J., & Walling, A. (1990). Employment effects of new technology in manufacturing. Policy Studies Institute, 716. ISBN: 0853744955

  • Comin, D. A., & Hobijn, B. (2010). An exploration of technology diffusion. American Economic Review, 100(5), 2031-2059.

  • Comin, D. A., Dmitriev, M., & Rossi-Hansberg, E. (2012). The spatial diffusion of technology. CEPR Discussion Paper 9208 and NBER Working Paper 18534.

  • Dally, K. A. (1997). Managing the contingent workforce: Lessons for success. Queen’s University Industrial Relations Centre (IRC). ISBN: 0-88886-452-3

  • Dellaert, N., Jeunet, J., & Mincsovics, G. (2008). Budget allocation for permanent and contingent capacity under stochastic demand. Working paper, Technische Universiteit Eindhoven, The Netherlands.

  • Gartside, D., Silverstone, Y., Farley, C., & Cantrell, S. M. (2013). Trends reshaping the future of HR. The rise of the extended workforce. Accenture Institute for High Performance.

  • Heffron, F. (1968). Organization theory and public organizations. New Jersey.

  • Helpman, E., & Rangel, A. (1998). Adjusting to a new technology: Experience and training. National Bureau of Economic Research (NBER) Working Paper 6551.

  • Hipple, S., & Stewart, J. (1996). Earnings and benefits of contingent and noncontingent workers. Monthly Labour Review, 119(10), 22-30.

  • Kandt, R. K. (2002). Organizational change management principles and practices. Jet Propulsion Laboratory, USA. Retrieved from http://trs-new.jpl.nasa.gov/dspace/handle/2014/10570

  • Kredler, M. (2008). Experience vs. obsolescence: A vintage-Human-Capital Model. MPRA Paper No. 10200: New York. Retrieved from http://mpra.ub.uni-muenchen.de/10200/

  • Ledez, R. E. (2008). Change management: Getting a tuned up organization. Business Intelligence Journal, European Management Development, 1(1), 111-119.

  • Lyytinen, K., & Rose, G. M. (2004). How agile is agile enough? Towards a theory of agility in software development. Case Western Reserve University, USA. Sprouts: Working Papers on Information Systems, 4(10). ISSN 1535-6078. Retrieved from http://sprouts.aisnet.org/4-10

  • Polivka, A. E., & Nardone, T. (1989). On the definition of contingent work. Monthly Labor Review, 112(12), 9-16.

  • March, J.G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71-87.

  • Markovic, M. R. (2008). Effective organizational change management. Serbian Journal of Management, 3(1), 119-125.

  • Qin, R., & Nembhard, D. A. (2010). Workforce agility for stochastically diffused conditions: A real options perspective. International Journal of Production Economics, 125(2), 324-334.

  • Rogers, E. M. (1995). Diffusion of innovations (4th ed.). New York: The Free Press.

  • Rosenberg, N. (1972). Factors affecting the diffusion of technology. Explorations in Economic History, 10(1), 3-33. Reprinted in Rosenberg, N. (1976), Perspectives on Technology, Cambridge: Cambridge University Press, pp. 189-212.

  • Svedaite, E., & Tamosiunas, T. (2013). Investigation of the advantages and disadvantages of temporary employment. Socialiniai tyrimai / Social Research, 1(30), 64-70. ISSN 1392-3110

  • Swanson, E. B. (1994). Information systems innovation among organizations. Management Science, 40(9), 1069-1088.

  • Weinberg, B. A. (2004). Experience and technology adoption. IZA DP No: 1051.

  • Wilson, D. R. (2010). Case study: Jeppesen gains agility with contingent workforce management. Gartner, ID Number: G00171831.

  • Yaghoubi, N. M., & Rahat Dahmardeh, M. (2011). Knowledge management; critical success factor in organizational agility. American Journal of Social and Management Sciences, 2(3), 272-277.


Abstract Views: 538

PDF Views: 0




  • An Exploration of Enhancing Adoption and Agility in Technological Changes

Abstract Views: 538  |  PDF Views: 0

Authors

Prafulla Pawar
Department of Management Sciences, Savitribai Phule Pune University, Pune, Maharashtra, India
Rahil Meymandpour
Department of Management Sciences, Savitribai Phule Pune University, Pune, Maharashtra, India

Abstract


In the present paper, the optimal way of increasing employee’s adoption and agility in technological changes and the proper designed strategies suggested by scholars to managers as policy makers to manipulate these technological changes and develop the foremost approach to control unexpected changes in companies are explored. After investigating related works and scrutinising numerous approaches surrounding managing technological changes; it is perceived a successful technological change management depends, to a great extent, on employees’ capabilities to be more adopted and agile in implementing new technologies satisfactorily. Since employees play the main role in accomplishing technological tasks, they should possess skills related to those new technologies. As keeping regular employees has some obstacles mentioned in the following; the optimal option of having skilled staff with more adoption and agility in technological changes can be produced through contingent workforce system in the light of vintage human capital model in this study. Besides, technology diffusion theory is considered marginally in this paper to manifest the presence of employees’ adoption and agility in technological changes.

Keywords


Technological Change, Adoption, Agility, Contingent Workforce, Technology Diffusion, Vintage Human Capital Model.

References