Risks and Controls in Internet-Enabled Reverse Auctions: Perspectives from Buyers and Suppliers

Abstract

Internet-enabled reverse auctions (RAs) are touted as a means of making the procurement process more effective and efficient, but as is often the case with information technology (IT), there can be risks that managers need to be aware of and mitigate in order to realize the benefits. Using the Delphi methodology followed by semistructured interviews, we identify buyer and supplier perspectives on risk factors associated with RAs and the controls that can address key risk factors. We find that the risk factors map to (1) auction process governance, (2) organizational contingency, (3) buyer–supplier relationship, and (4) agency and transaction cost. Drawing on the findings, we advance an RA risk-control integrative model and formulate corresponding propositions (1) comparing buyers’ and suppliers’ perspectives on risks associated with RA use and (2) identifying controls to mitigate the risks. Our research contributes to theory by (1) surfacing that RAs introduce novel risks and that buyers and suppliers can have either similar or remarkably different views regarding particular risks, (2) showing how both buyers and suppliers can create information asymmetry and act opportunistically, and (3) uncovering the role of input controls, a type of control that has not received much attention in the literature on controls for IT initiatives, as an effective means of addressing most of the key risk factors. For practitioners, our study provides guidance about a wide range of risk factors that both parties could face when using RAs, the adverse consequences of these risk factors, and the controls that can be established to mitigate the key risk factors.

Key words and phrases:

• auctions risks
• Delphi methodology
• interfirm governance
• intrafirm governance
• online auctions
• online controls
• principal opportunism
• process governance
• reverse auctions
• reverse information asymmetry

Supplemental File

Supplemental data for this article can be found on the publisher’s website at10.1080/07421222.2017.1394071

Notes

1. http://reverseauctions.gsa.gov/reverseauctions/reverseauctions.

2. www.gao.gov/products/GAO-14-108/.

3. www.pwc.in/assets/pdfs/publications/2015/coal-block-auctions-a-win-or-a-winners-curse-indian-chamber-of-commerce.pdf.

4. Several practitioner articles, media reports, and other related academic papers also discuss RA risk factors. Beyond these 29 papers, the RA risk factors were repetitive. Hence, we focus on the 29 papers listed in Table 1.

5. Online Appendix B also lists corresponding adverse consequences. Risk factors are those factors that are identified as potentially leading to adverse consequences, such as lack of top management support and/or resistance by internal clients within a buying organization, which can limit the buyer’s ability to enforce the outcome of an RA. Since our objective is to identify and theoretically interpret the risk factors and their subsequent controls, our discussion of risk factors is organized according to their theoretical perspectives as shown in Table 2. Also, as was mentioned earlier, a list of 40 risk factors was developed from the RA literature. Like Table 2, Online Appendix B lists other papers that identified risk factors. Our study lists 25 risk factors that were not provided by the 29 papers discussed in our literature review.

6. It should be noted that the risk factors pertaining to organizational contingency (theoretical perspective 2), buyer–supplier relationship (theoretical perspective 3), and agency and transaction cost (theoretical perspective 4) may also have similar temporal characteristics, but they lack the linear sequential characteristics that process governance entails. Hence, examining them based on the phase in which they occur is inappropriate. Instead, they are examined according to the dimensions that exclusively characterize them.

7. While buyers were interviewed about the risk of a lack of competition in the auction, suppliers were interviewed about the adverse long-term impact on the supply base. No controls were suggested to address this risk factor. Experts suggested that this risk factor could not be controlled. Therefore, this risk factor is not bolded in Table 2.

Additional information

Notes on contributors

Chaitanya Sambhara

Chaitanya Sambhara ([email protected]; corresponding author) is an assistant professor of information systems and analytics at Miami University, Oxford, Ohio. He holds a Ph.D. in information systems and process innovation from Georgia State University. His research focuses on business value of information technology, risks, controls, and human capital and competence. His work has appeared in the proceedings of the International Conference on Information Systems, America’s Conference on Information Systems, and the annual conference of Production and Operations Management Society.

Arun Rai

Arun Rai ([email protected]) is Regents’ Professor at the Robinson College of Business at Georgia State University and holds the Robinson Chair of IT-Enabled Process Innovation and Supply Chains and the Harkins Chair of Information Systems. He serves as editor in chief for the MIS Quarterly. His research has focused on how firms can leverage information technologies in their strategies, relationships, and processes; how systems can be effectively developed and deployed; and how digital innovations can create business value and address societal problems such as digital inequality, poverty, health disparities, and infant mortality. Several of his research projects have been performed in collaboration with major corporations in automotive, hi-tech, health care, financial services, retail, and logistics and with not-for-profit organizations. He is a fellow of the Association for Information Systems and a Distinguished Fellow of the INFORMS Information Systems Society.

Mark Keil

Mark Keil ([email protected]) is a Distinguished University Professor at Georgia State University where he is the John B. Zellars Professor of Computer Information Systems in the J. Mack Robinson College of Business. He holds a D.B.A. degree from Harvard Business School. His research focuses on information technology project management and decision making. He has published more than 100 refereed journal articles, has served as senior editor or associate editor for many of the leading journals in the field of information systems, and as division chair for the Academy of Management (OCIS Division).

Vijay Kasi

Vijay Kasi ([email protected]) is a vice president with the global consulting firm A.T. Kearney and has more than 12 years of progressive industry and consulting experience. He holds a Ph.D. in computer information systems from Georgia State University. He works on strategic problems related to operations and supply chains, and consults with corporate clients in consumer packaged goods, retail, and other related industries. His research has been published in Journal of Management Information Systems, European Journal of Information Systems, and Journal of Information Management.