458
Views
4
CrossRef citations to date
0
Altmetric
Articles

Transaction Costs and Efficiency in Design-Build Contracting: Empirical Evidence from the Transportation Infrastructure Sector in Oregon

Pages 1230-1258 | Published online: 25 Mar 2019
 

Abstract

Design-build (DB) contracting as a type of public–private partnerships (PPPs) has been widely used as an alternative to the traditional contracting-out and the in-house provisions for the delivery of infrastructure in the United States. The research question this article seeks to answer is whether the efficiency motive helps explain the use of DB contracting compared to traditional contracting-out, the design-bid-build (DBB), in public infrastructure delivery. By using the transaction cost economics approach, I assessed whether DB contracting is selected to minimize transaction costs in certain infrastructure transactions that would later lead to more efficient results for those infrastructure transactions. By employing a two-stage empirical strategy (the nonparametric data envelopment analysis and the instrumental variable two-stage least squares regression approach), I examined 59 bridge and combination bridge-roadway projects in Oregon that were completed during 2005–2015 using both DB and DBB contracting. I found that when the transaction is complex, the assets in the transaction are specific, and the size of the transaction is large, the use of DB contracting significantly increases the efficiency score by 46 percentage points. The findings suggest that the transaction costs economizing motive underlies the choice of governance structure in public service deliveries.

Notes

Notes

1 In the United States, design-build contracting is considered as a type of PPPs with the least private involvement, although it is not common worldwide. As defined by the Federal Highway Administration, “A public–private partnership is a contractual agreement formed between public and private sector partners, which allows more private sector participation than is traditional. The agreements usually involve a government agency contracting with a private company to renovate, construct, operate, maintain, and/or manage a facility or system” (U.S. Department of Transportation, Report to Congress on Public–Private Partnerships, 2004). With this definition, PPPs encompass: (1) Design-Build (DB) and/or Operation and Maintenance (O&M) contracts; (2) Design-Build-Operate-Maintain (DBOM) contracts; (3) Design-Build-Finance (DBF) or other private financing; (4) Design-Build-Finance-Operate-Maintain (DBFOM), Design-Build-Finance-Operate (DBFO), or long-term concession; (5) Build-Transfer-Operate (BTO) or Lease-Build-Operate (LBO); and (6) Build-Own-Operate-Transfer (BOOT) or Build-Operate-Transfer (BOT) (Rall, Reed, & Farber, Citation2010, p. 4).

2 Initially, a growing need for infrastructure that has outpaced the supply of public funds was the key factor that has led public agencies to delegate some of their infrastructure responsibilities to the private sector by using PPP contracts (Savas, 2000, p. 237).

3 The fact that local governments in the United States could issue municipal bonds for local infrastructure development could be one of the reasons.

4 This project was started in 2005 but suspended in 2011. The private sector, Granite Construction, received a notice of default from ODOT in 2011 due to delay issues related to the unanticipated and continuing adverse geotechnical conditions and landslides on the project site. The project was completed in 2016, seven years later than the initial projected completion date. It also experienced cost overruns of more than $200 million, more than double its original budget of $153 million (Day, Citation2016).

5 After six years of operation under the DBFO scheme, the California Department of Transportation (Caltrans) had to break the noncompete clause in the contract that prohibits Caltrans from developing a new highway around the 91 express lanes to guarantee the revenue of the private agency (California Private Transportation Company [CPTC]). Demands for additional freeway capacity has pushed Caltrans to build free roads that compete with the State Route 91 express lanes toll way. The dispute between Caltrans and CPTC ended up in court, resulting in the reaffirmation of the noncompete clause in 1999. Due to these lengthy controversies, the facility was finally taken over by the Orange County Transportation Authority (OCTA) in 2003. OCTA acquired the franchise from CPTC, while it retains operation of the toll road (the subsidiary of CPTC) under a short-term contract agreement.

6 Transaction costs are central in a contractual relationship. It includes the costs of ascertaining the price of the goods and services transacted, the costs of negotiating the attributes of the partnership, and the costs of protecting and enforcing the partnership agreement.

7 By definition, bounded rationality is “human behavior [that] is intendedly rational but only limitedly so” (Simon & Barnard, Citation1947, p. xxiv).

8 DEA is a nonparametric approach that measures efficiency based on multiple inputs and multiple outputs to construct the best practice frontier so that the radial distance of each project to the best practice frontier represents each project efficiency index. This study uses DEA because, as a nonparametric approach to measuring efficiency and productivity, DEA does not require any functional form for empirical estimation as required by the parametric approach, such as the stochastic frontier analysis (Aigner, Lovell, & Schmidt, Citation1977). The weakness of DEA is that it assumes that there are no errors, so any error will be reflected in the efficiency score. Moreover, DEA is very sensitive to outliers and can treat them as the benchmark for the efficiency measurement. This study excludes outliers with careful consideration. Meanwhile, one of the advantages of DEA is that it can handle multiple inputs and outputs quite readily and it allows for straightforward calculations of technical efficiency (Kwoka, Pollitt, & Sergici, Citation2010, p. 95). This feature is particularly advantageous to this study as it allows this study to compare infrastructure projects that have different output mixes.

9 I measured the efficiency index using the OnFront 2 software package developed by Färe and Grosskopf (Citation2000).

10 I test this assumption by regressing the award amount on the dummy of county funding and other controls (type of project, type of work, rural county dummy, and the number of change orders). The results suggest that the presence of county funding is negatively associated with the award amount (the coefficient is –5654448, which is significant at the 5% level).

11 Since ODOT has to prepare all the data on DB and DBB projects, based on the discussion with the performance program manager, this study uses all DBB bridges and roadway projects completed during a shorter period of time, which is 2010–2015, rather than randomly choosing DBB projects completed during the period of DB projects, which is 2005–2015. However, two DBB bridge projects are excluded from the analysis as they depend on a different type of technology than the 13 DB projects, thus become the outliers to the rest of the projects. They are salt use mitigation for bridge projects that mainly consisted of overlaying or sealing the bridge decks as part of a larger effort to mitigate corrosion. Because the technology is simple, it takes little time to design the project. With minimal resources in terms of costs and time, these projects generate a large amount of output, in terms of the number of bridge sites and the square footage of bridge decks that are repaired. Since the DEA method is very sensitive to outlying data, these two projects would have been deemed the only efficient projects while the rest would have been deemed highly inefficient. With a confirmation from the performance manager in ODOT, these two projects are excluded.

Additional information

Funding

This research is supported by the Indonesia Endowment Fund for Education (LPDP), Grant #PRJ-4588/LPDP.3/2016 for the research and the United States Agency for International Development (USAID) through the Sustainable Higher Education Research Alliance (SHERA) Program for Universitas Indonesia’s Scientific Modeling, Application, Research and Training for City-centered Innovation and Technology (SMART CITY) Project, Grant #AID-497-A-1600004, Sub Grant #IIE-00000078-UI-1 for the publication.

Notes on contributors

Yohanna M. L. Gultom

Yohanna M. L. Gultom is a lecturer in the Department of Economics, Faculty of Economics and Business, Universitas Indonesia, Depok, Indonesia.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 323.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.