Understanding the Dynamics of Service-Oriented Architecture Implementation

Abstract

Despite the potential benefits, many organizations have failed in service-oriented architecture (SOA) implementation projects. Prior research often used a variance perspective and neglected to explore the complex interactions and timing dependencies between the critical success factors. This study adopts a process perspective to capture the dynamics while providing a new explanation for the mixed outcomes of SOA implementation. We develop a system dynamics model and use simulation analysis to demonstrate the phenomenon of “tipping point.” That is, under certain conditions, even a small reduction in the duration of normative commitment can dramatically reverse, from success to failure, the outcome of an SOA implementation. The simulation results also suggest that (1) the duration of normative commitment can play a more critical role than the strength, and (2) the minimal duration of normative commitment for a successful SOA implementation is associated positively with the information delay of organizational learning of SOA knowledge. Finally, we discuss the theoretical causes and organizational traps associated with SOA implementation to help IT managers make better decisions about their implementation projects.

Key words and phrases:

• normative commitment
• organizational traps
• service-oriented architecture (SOA)
• system dynamics
• tipping point

Supplemental Material

Supplemental data for this article can be accessed at the publisher’s website at http://dx.doi.org/10.1080/07421222.2015.1063284

Notes

1. We must emphasize the specificity and difference of SOA compared to traditional ERP systems. While ERP implementation often focuses on consolidating multiple information technology (IT) systems across an organization, SOA implementation focuses on improving an organization’s IS agility and flexibility. Because of this difference, the focus of this study is different from prior studies on ERP implementation.

2. For the online appendix, see http://web.mit.edu/smadnick/www/JMIS/OnlineAppendix.pdf. (This will be replaced by a permanent link.)

3. About 8,000 citations, according to Google Scholar. See https://scholar.google.com/scholar?cluster= 7563512649899599529&hl=en&as_sdt=0,22&sciodt=0,22.

4. This phenomenon of top management losing interest in efforts and reducing normative commitment was mentioned in many of our interviews. Sometimes normative commitment slowly faded away, and at other times there was an abrupt distraction (e.g., a change in management). To focus on the role played by the duration of normative commitment, in many of the simulations we assume that top management completely removes normative commitment at a certain time point, and we use a STEP function to model normative commitment. This simplified assumption may not be realistic in some cases, but it also does not compromise the key insights from our findings. As a robustness check, we ran the model assuming that top management reduces normative commitment at a constant rate (using a RAMP function), and we obtained qualitatively similar results.

5. For measurement consideration, a developer’s development productivity can be measured as the unit of software components, modules, or functional features.

Additional information

Notes on contributors

Xitong Li

Xitong Li is an assistant professor in the Department of Operations Management and Information Technology, HEC Paris, France. He received his Ph.D. in management from the MIT Sloan School of Management, and his Ph.D. in engineering from Tsinghua University. His recent research interests include the economic and social impacts of using online data/information, and innovative technologies using online data and services. His research has appeared, or is forthcoming, in Journal of Management Information Systems, ACM Transactions on Internet Technology, IEEE Communications Magazine, IEEE Transactions on Automation Science and Engineering, IEEE Transactions on Systems, Man, and Cybernetics, and other leading journals and conference proceedings. He won the Best Paper award at the Forty-Sixth Hawaii International Conference on System Sciences (HICSS).

Stuart E. Madnick

Stuart E. Madnick is the John Norris Maguire Professor of Information Technologies at the MIT Sloan School of Management and a Professor of Engineering systems at the MIT School of Engineering. He headed MIT’s Information Technologies Group for more than 20 years. He has degrees in electrical engineering, management, and computer science from MIT. His current research interests include disparate distributed information systems, database technology, software project management, social media, strategic use of information technology, and cybersecurity. He is author/coauthor of over 380 books, articles, and reports, including Operating Systems (McGraw-Hill, 1974) and Dynamics of Software Development (Prentice Hall, 1991). He has been active in industry, including projects such as IBM’s VM/370 operating system and Lockheed’s DIALOG information retrieval system.