The  impact of IT-enhanced organizational learning on performance: evidence from Chile

Enrique Carlos Canessa-Terrazas; Francisco Javier Morales-Flores; José Oreste Maldifassi-Pohlhammer

doi:10.17533/udea.redin.n82a08

Authors

Enrique Carlos Canessa-Terrazas Adolfo Ibáñez University
Francisco Javier Morales-Flores University of Colorado Boulder
José Oreste Maldifassi-Pohlhammer Adolfo Ibáñez University https://orcid.org/0000-0001-9577-8509

DOI:

https://doi.org/10.17533/udea.redin.n82a08

Keywords:

organizational learning, information technology, exploration, exploitation, structural equations modeling

Abstract

The link between information technology (IT) and organizational learning has been an important subject of study since the early 1990s. However, it is still not clear whether or not IT-enhanced organizational learning positively influences organizational performance. In this paper we posit that the impact of IT on the performance of firms will differ depending on the main usage of the IT system: for exploration or for exploitation. Based on data of Chilean organizations, we found that there exists a positive impact of using IT for exploitation on organizational performance; and that the use of IT for exploration has a positive impact on organizational change.

|Abstract

= 321 veces | PDF

= 237 veces|

Downloads

Author Biographies

Enrique Carlos Canessa-Terrazas, Adolfo Ibáñez University

Associate Professor. Faculty of Engineering and Sciences.

Francisco Javier Morales-Flores, University of Colorado Boulder

Leeds School of Business.

José Oreste Maldifassi-Pohlhammer, Adolfo Ibáñez University

Associate professor. Faculty of Engineering and Sciences.

References

D. Robey, M. Boudreau, and G. Rose, Information Technology and Organizational Learning: A Review and Assessment of Research, 1999. [Online]. Available: http://citeseerx.ist.psu.edu/viewdoc/downloaddoi=10.1.1.11.6&rep=rep1&type=pdf. Accessed on: Oct. 10, 2016.

M. Alavi and D. Leidner, “Review: Knowledge Management and Knowledge Management Systems: Conceptual Foundations and Research Issues,” MIS Quarterly, vol. 25, no. 1, pp. 107-136, 2001.

G. Kane and M. Alavi, “Information Technology and Organizational Learning: And Investigation of Exploration and Exploitation Processes,” Organization Science, vol. 18, no. 5, pp. 796-812, 2007.

D. Robey, M. Boudreau, and G. Rose, “Information technology and organizational learning: a review and assessment of research,” Accounting, Management and Information Technologies, vol. 10, no. 2, pp. 125-155, 2000.

D. Garvin, “Building a Learning Organization,” Harvard Business Review, vol. 71, no. 4, pp. 78-91, 1993.

J. March, “Exploration and Exploitation in Organizational Learning,” Organization Science, vol. 2, no. 1, pp. 71-87, 1991.

J. Real, A. Leal, and J. Roldán, “Information technology as a determinant of organizational learning and technological distinctive competencies,” Industrial Marketing Management, vol. 35, no. 4, pp. 505-521, 2006.

M. Tippins and R. Sohi, “IT competency and firm performance: is organizational learning a missing link?,” Strategic Management Journal, vol. 24, no. 8, pp. 745-761, 2003.

T. Powellm and A. Dent, “Information Technology as Competitive Advantage: The Role of Human, Business, and Technology Resources,” Strategic Management Journal, vol. 18, no. 5, pp. 375-405, 1997.

B. Chakravarthy, “Adaptation: A Promising Metaphor for Strategic Management,” The Academy of Management Review, vol. 7, no. 1, pp. 35-44, 1982.

K. Eisenhardt and J. Martin, “Dynamic capabilities: what are they?,” Strategic Management Journal, vol. 21, no. 10-11, pp. 1105-1121, 2000.

D. Teece, G. Pisano, and A. Shuen, “Dynamic Capabilities and Strategic Management,” Strategic Management Journal, vol. 18, no. 7, pp. 509-533, 1997.

M. Zollo and S. Winter, “Deliberate Learning and the Evolution of Dynamic Capabilities,” Organization Science, vol. 13, no. 3, pp. 339-351, 2002.

S. Auh and B. Menguc, “Balancing exploration and exploitation: The moderating role of competitive intensity,” Journal of Business Research, vol. 58, no. 12, pp. 1652-1661, 2005.

C. Fiol and M. Lyles, “Organizational Learning,” The Academy of Management Review, vol 10, no. 4, pp. 803-813, 1985.

G. Huber, “Organizational Learning: The Contributing Processes and the Literatures,” Organizational Science, vol. 2, no. 1, pp. 88-115, 1991.

B. Pentland, “Information systems and organizational learning: The social epistemology of organizational knowledge systems,” Accounting, Management and Information Technologies, vol. 5, no. 1, pp. 1-21, 1995.

C. Argyris and D. Schön, Organizational Learning: A Theory of Action Perspective, 1st. ed. Reading, USA: Addison Wesley, 1978.

F. Vermeulen and H. Barkema, “Learning through Acquisitions,” The Academy of Management Journal, vol. 44, no. 3, pp. 457-476, 2001.

Z. Simsek, “Organizational Ambidexterity: Towards a Multilevel Understanding,” Journal of Management Studies, vol. 46, no. 4, pp. 597-624, 2009.

C. Gibson and J. Birkinshaw, “The Antecedents, Consequences, and Mediating Role of Organizational Ambidexterity,” The Academy of Management Journal, vol. 47, no. 2, pp. 209-226, 2004.

A. Lewin, C. Long, and T. Carroll, “The Coevolution of New Organizational Forms,” Organization Science, vol. 10, no. 5, pp. 535-550, 1999.

J. Baum, S. Li, and J. Usher, “Making the Next Move: How Experiential and Vicarious Learning Shape the Locations of Chains’ Acquisitions,” Administrative Science Quarterly, vol. 45, no. 4, pp. 766-801, 2000.

F. Rothaermel and D. Deeds, “Exploration and Exploitation alliances in biotechnology: a system of new product development,” Strategic Management Journal, vol. 25, no. 3, pp. 201-221, 2004.

M. Subramani, “How Do Suppliers Benefit from Information Technology Use in Supply Chain Relationships?,” MIS Quarterly, vol. 28, no. 1, pp. 45-73, 2004.

R. McGrath, “Exploratory Learning, Innovative Capacity and Managerial Oversight,” The Academy of Management Journal, vol. 44, no. 1, pp.118-131, 2001.

B. Levitt and J. March, “Organizational Learning,” Annual Review of Sociology, vol. 14, pp. 319-340, 1988.

Z. He and P. Wong, “Exploration vs. Exploitation: An Empirical Test of the Ambidexterity Hypothesis,” Organization Science, vol. 15, no. 4, pp. 481-494, 2004.

Z. Simsek, C. Heavey, J. Veiga, and D. Souder, “A Typology for Aligning Organizational Ambidexterity’s Conceptualizations, Antecedents, and Outcomes,” Journal of Management Studies, vol 46, no. 5, pp. 864-894, 2009.

S. Mithas and R. Rust, “How Information Technology Strategy and Investments Influence Firm Performance: Conjecture and Empirical Evidence,” MIS Quarterly, vol. 40, no. 1, pp. 223-245, 2016.

E. Brynjolfsson, “The Productivity Paradox of Information Technology,” Communications of the ACM, vol. 36, no. 12, pp. 66-77, 1993.

G. W. Loveman, “An Assessment of the Productivity Impact on Information Technologies,” in Information Technology and the Corporation of the 1990s, 1st ed., T. J. Allen and M. S. Scott (eds). Cambridge, USA: MIT Press, 1994, pp. 17-78.

N. Carr, “IT Doesn’t Matter,” Harvard Business Review, vol. 81, no. 5, pp. 41-49, 2003.

N. Sanders, “Pattern of information technology use: The impact on buyer-supplier coordination and performance,” Journal of Operations Management, vol. 26, no. 3, pp. 349 367, 2008.

G. DeSanctis and M. Poole, “Capturing the Complexity in Advanced Technology Use: Adaptive Structuration Theory,” Organization Science, vol. 5, no. 2, pp. 121-147, 1994.

M. Hitt, M. Dacin, E. Levitas, J. Arregle, and A. Borza, “Partner Selection in Emerging and Developed Market Contexts: Resource-Based and Organizational Learning Perspectives,” The Academy of Management Journal, vol 43, no. 3, pp. 449-467, 2000.

R. Hoskisson, L. Eden, C. Lau, and M. Wright, “Strategy in Emerging Economies,” The Academy of Management Journal, vol 43, no. 3, pp. 249-267, 2000.

R. Kline, Principles and Practice of Structural Equation Modeling, 3rd ed. New York, USA: The Guilford Press, 2011.

J. Nunnally, Psychometric Theory, 2nd ed. New York, USA: McGraw Hill, 1978.

E. Babbie, The practice of social research, 11th ed. Belmont, USA: Wadsworth, 2007.

J. Hair, W. Black, B. Babin, and R. Anderson, Multivariate Data Analysis, 7th ed. New York, USA: Pearson Prentice Hall, 2010.

L. Hu and P. Bentler, “Cutoff Criteria for Fit Indices in Covariance Structure Analysis: Conventional Criteria versus New Alternatives,” Structural Equation Modeling, vol. 6, no. 1, pp. 1-55, 1999.

M. Cheung, “Constructing Approximate Confidence Intervals for Parameters With Structural Equation Models,” Structural Equation Modeling, vol. 16, no. 2, pp. 267-294, 2009.