Developing a new cash flow expenditures model considering the flexibilities offered by the design-build-finance (DBF) and public-private partnership (P3) project delivery methods

GEORGIA DOT RESEARCH PROJECT NO. 18-13
FINAL REPORT
DEVELOPING A NEW CASH FLOW EXPENDITURES MODEL CONSIDERING THE FLEXIBILITIES OFFERED BY THE
DESIGNBUILDFINANCE (DBF) AND PUBLICPRIVATE PARTNERSHIP (P3) PROJECT DELIVERY METHODS
OFFICE OF PERFORMANCE-BASED MANAGEMENT AND RESEARCH
600 W. PEACHTREE STREET NW ATLANTA, GA 30308

1. Report No.

2. Government Accession No. 3. Recipient's Catalog No

FHWA-GA-21-1813

N/A

N/A

4. Title and Subtitle

5. Report Date

Developing a New Cash Flow Expenditures Model

December 2020

Considering the Flexibilities Offered by the Design

6. Performing Organization Code

BuildFinance (DBF) and PublicPrivate Partnership (P3)

Project Delivery Methods

N/A

7. Author(s)

8. Performing Organ. Report No.

Baabak Ashuri, Ph.D., DBIA. https://orcid.org/0000-0002-

4320-1035; Yunping Liang; Minsoo Beak, Ph.D.;

N/A

Mingshu Li; Shiqin Zeng

9. Performing Organization Name and Address

10. Work Unit No.

Economics of Sustainable Built Environment (ESBE) Lab N/A

Georgia Institute of Technology

11. Contract or Grant No.

280 Ferst Drive, Atlanta, GA 30332-0680

RP 18-13

12. Sponsoring Agency Name and Address

13. Type of Report and Period Covered:

Georgia Department of Transportation,

Final; August 2018 December 2020

Office of Performance-based

14. Sponsoring Agency Code

Management and Research,

N/A

600 W. Peachtree Street NW, Atlanta, GA 30308

15. Supplementary Notes

Conducted in cooperation with the U.S. Department of Transportation, Federal Highway Administration.

16. Abstract

State departments of transportation (state DOTs) have implemented transportation financial plans to

utilize federal and state transportation funding within at least a four-year horizon and possibly longer. It

is critical for state DOTs to maintain adequate cash balance that helps establish a clear transportation

plan and program. Over the past decades, an array of alternative project delivery methods has been

introduced to enhance the financing capabilities of the state DOT. The new delivery methods need to be

properly treated in developing more realistic cash flow models for the project expenditures. The

overarching objective of this research is to develop a forecasting model for expenditure cash flow for the

GDOT design and construction program, taking into account flexibilities offered by the innovative

project delivery methods, such as designbuild (DB), designbuildfinance (DBF) and publicprivate

partnership (P3). To achieve the research objectives, current state of the practices in schedule of value

and payment for design and construction activities in several state DOTs are reviewed and best practices

are identified. An expenditure cash flow forecasting model is developed for transportation designbuild

projects via a case-based reasoning (CBR) approach. The developed model generates accurate forecasts

with limited training data and high-level describable project attributes. The proposed model can handle

inputs with missing data. An Excel Visual Basic for Application (VBA) tool is developed for project

managers by using the proposed CBR model. The significance of the developed cash flow model lies on

its capabilities to inform the Department about its actual future financial obligations and, thereby,

effectively use its limited capital to deliver more needed projects. The new cash flow model shows

opportunities for deferred payments and other savings anticipated in the alternative delivery models. The

proposed model was tested and confirmed by all the completed transportation designbuild projects in

the State of Georgia, ranging from April 2007 to January 2020.

17. Key Words

Cash Flow, Case-Based Reasoning, Design-Build,

Financial Analysis

19.Security Classification 20. Security Classification

(of this report)

(of this page)

Unclassified

Unclassified

18. Distribution Statement

21. Number of Pages 22. Price

109

Free

ii

GDOT Research Project No. 18-13 Final Report
DEVELOPING A NEW CASH FLOW EXPENDITURES MODEL CONSIDERING THE FLEXIBILITIES OFFERED BY THE DESIGNBUILDFINANCE (DBF) AND PUBLICPRIVATE PARTNERSHIP (P3) PROJECT DELIVERY METHODS
By Baabak Ashuri, Ph.D., DBIA
Yunping Liang Minsoo Beak, Ph.D.
Mingshu Li Shiqin Zeng
Georgia Institute of Technology
Contract with Georgia Department of Transportation
In cooperation with U.S. Department of Transportation Federal Highway Administration
December 2020 The contents of this report reflect the views of the authors who are responsible for the facts and the accuracy of the data presented herein. The contents do not necessarily reflect the official views or policies of the Georgia Department of Transportation or the Federal Highway Administration. This report does not constitute a standard, specification, or regulation.
iii

TABLE OF CONTENTS
LIST OF TABLES............................................................................................................ vi LIST OF FIGURES......................................................................................................... vii EXECUTIVE SUMMARY ............................................................................................ viii ACKNOWLEDGMENTS................................................................................................ xi CHAPTER 1. INTRODUCTION..................................................................................... 1 CHAPTER 2. SCHEDULE OF VALUES AND PAYMENT FOR DESIGN AND
CONSTRUCTION ACTIVITIES............................................................................ 4 Introduction............................................................................................................................. 4 Practices of State DOTs' Schedule of Values for DB Contracts......................................... 8
Georgia DOT....................................................................................................................11 Florida DOT.....................................................................................................................13 Virginia DOT ...................................................................................................................15 Delaware DOT .................................................................................................................16 New York State DOT ......................................................................................................19 Updates to the Schedule of Values....................................................................................... 21 Approval and Disapproval of Progress Payments ............................................................. 22 Georgia DOT....................................................................................................................23 Florida DOT.....................................................................................................................25 Maryland DOT ................................................................................................................27 Incentives for Early Completion.......................................................................................... 28 Cost-loaded Schedules for Design and Construction Activities........................................ 30 Price Adjustment Clauses in Progress Payments............................................................... 32 Georgia DOT....................................................................................................................34 Maryland DOT ................................................................................................................35 North Carolina DOT .......................................................................................................36 Virginia DOT ...................................................................................................................37 Summary................................................................................................................................ 40
iv

CHAPTER 3. CONSTRUCTION EXPENDITURE FLOWS FORECASTING TOOL FOR TRANSPORTATION DESIGNBUILD PROJECTS .................. 42 Introduction........................................................................................................................... 42 Research Objectives.............................................................................................................. 44 Methodology .......................................................................................................................... 46 Data ................................................................................................................................... 47 Model Development.........................................................................................................53 Results .................................................................................................................................... 66
CHAPTER 4. USER MANUAL OF THE DEVELOPED EXCEL VISUAL BASIC FOR APPLICATION (VBA) TOOL ..................................................................... 78 Purpose of the Tool ............................................................................................................... 78 Structure of the Tool............................................................................................................. 79 Home Page (figure) ............................................................................................................... 79 Input Data Page...............................................................................................................80 Cash Flow Prediction Results Page (figure 22).............................................................89
CHAPTER 5. CONCLUSIONS ..................................................................................... 91 REFERENCES ................................................................................................................ 94
v

LIST OF TABLES
Table 1. Summary of state DOTs' SOV practices for DB projects................................................. 9 Table 2. Form of DB SOV of Georgia DOT's I-16 at I-95 Improvement Projects....................... 12 Table 3. Form of design and construction SOV of the Florida DOT's I-4 Ultimate project......... 14 Table 4. A schedule of items for the Virginia DOT's DB I-64 project. ........................................ 16 Table 5. Form of Delaware DOT's schedule of values for replacement of Bridge 3-156............. 18 Table 6. Form of New York State DOT's SOV for a DB project. ................................................ 20 Table 7. Provisions for updating/revising SOV for a DB project. ................................................ 22 Table 8. Summary of state DOTs' provision for approval and disapproval of progress
payments. ................................................................................................................................ 23 Table 9. Examples of state DOTs' early completion incentives for DB contracts........................ 29 Table 10. Provisions for cost-loaded schedule for state DOTs' DB projects. ............................... 32 Table 11. Summary of state DOTs' price adjustment provisions in DB contracts........................ 33 Table 12. Eligible bid items for Georgia DOT's price adjustments. ............................................. 34 Table 13. Eligible bid items for Maryland DOT's price adjustments. .......................................... 35 Table 14. Eligible items for North Carolina DOT's price adjustments. ........................................ 36 Table 15. Projects used for model development............................................................................ 48 Table 16. Project-specific attributes. ............................................................................................. 50 Table 17. External attributes.......................................................................................................... 52 Table 18. Comparison of different retrieval configurations. ......................................................... 76 Table 19. Pearson correlation test on the relations of prediction accuracy and project size. ........ 77
vi

LIST OF FIGURES
Figure 1. Image. Georgia DOT's Form of Payment Request. ....................................................... 24 Figure 2. Screenshot. Asphalt material items eligible for price adjustment in the Virginia
DOT DB contract.................................................................................................................... 39 Figure 3. Screenshot. Standard bid items eligible for steel price adjustment in the Virginia
DOT DB contract.................................................................................................................... 39 Figure 4. Map. Georgia district map. ............................................................................................ 51 Figure 5. Chart. Model development steps.................................................................................... 53 Figure 6. Graphs. Cumulative expenditure curve fitting for the designbuild projects. ............... 55 Figure 7. Graphs. Forecasted cumulative expenditure cash flow for the designbuild
projects.................................................................................................................................... 68 Figure 8. Graph. Distribution of MAE values of predictions. ....................................................... 74 Figure 9. Image. Map of project network based on similarities. ................................................... 75 Figure 10. Screen capture. Home page.......................................................................................... 80 Figure 11. Screen capture. Input Data page................................................................................... 80 Figure 12. Screen capture. GDOT website for asphalt and fuel index. ......................................... 82 Figure 13. Screen capture. Retrieving PPI data (1). ...................................................................... 83 Figure 14. Screen capture. Retrieving PPI data (2). ...................................................................... 84 Figure 15. Screen capture. Retrieving PPI data (3). ...................................................................... 85 Figure 16. Screen capture. Retrieving JOLTS data (1). ................................................................ 86 Figure 17. Screen capture. Retrieving JOLTS data (2). ................................................................ 86 Figure 18. Screen capture. Retrieving JOLTS data (3). ................................................................ 87 Figure 19. Screen capture. Retrieving JOLTS data (4). ................................................................ 87 Figure 20. Screen capture. Retrieving JOLTS data (5). ................................................................ 88 Figure 21. Screen capture. Retrieving JOLTS data (6). ................................................................ 88 Figure 22. Screen capture. Cash Flow Prediction Results page. ................................................... 89
vii

EXECUTIVE SUMMARY
State departments of transportation (state DOTs) have implemented transportation financial plans, such as transportation improvement programs (TIPs) and statewide transportation improvement programs (STIPs), to utilize federal and state transportation funding within at least a four-year horizon and possibly longer. It is critical for state DOTs to maintain adequate cash balance that helps establish a clear transportation plan and program. An accurate construction expenditure forecasting model would help state DOTs by presenting a realistic view of expenditures in a given fiscal period. The significance of an accurate cash flow model lies in the capabilities to inform the Department about its actual future financial obligations and, thereby, effectively use its limited capital to deliver more needed projects. Over the past decades, an array of alternative project delivery methods has been introduced to enhance the financing capabilities of the state DOT. The new delivery methods need to be properly handled in developing more realistic cash flow models for the project expenditures. The new cash flow model would show opportunities for deferred payments and other savings anticipated in the alternative delivery models.
The overarching objective of this research is to develop a forecasting model for expenditure cash flow for the Georgia DOT (GDOT) design and construction program, taking into account flexibilities offered by the innovative project delivery methods, such
viii

as designbuild (DB), designbuildfinance (DBF) and publicprivate-partnership (P3). To achieve the research objectives, current "state of the practice" in schedule of value (SOV) and payment for design and construction activities in several state DOTs is reviewed, and best practices are identified. Finally, an expenditure cash flow forecasting model is developed for transportation designbuild projects via a case-based reasoning (CBR) approach. The developed model could generate accurate forecasts with limited training data and high-level describable project attributes, and it could handle inputs with missing data. An Excel Visual Basic for Application (VBA) Tool is developed for project managers by using the proposed CBR model.
The first half of the research was performed to review the current state of the practice in state DOTs regarding the SOVs and progress payments of DB and other innovative project delivery for highway projects. The findings of the first part of the research are summarized as the following recommendations, which should be effective for enhancing the practice of progress payment management:
A well-established SOV helps the Department develop a project-specific basis for reviewing and approving the designbuilder's work and developing a periodic pay estimate throughout the project.
An updated SOV that accommodates any changes in the scope of work is essential to smooth execution of the progress payment and a successful DB project.
ix

A detailed/updated payment breakdown for progress payments helps the Department approve/disapprove the payment to the contractor and reduce disputes.
Including early completion incentives in the DB request for proposals (RFP) can encourage the designbuilder to not only finish the project on time but also minimize the impact on the communities in which the projects are constructed.
A well-defined cost-loaded critical path method (CPM) schedule enables the Department to establish the expected cash flow for the life of the project.
Establishing and providing specific bid items that are eligible for price adjustments in a contract provides the Department with a more accurate and dynamic adjustment tool for payments.
The second half of the research effort is to develop a forecasting model suitable for transportation designbuild projects to be awarded. The proposed model was tested and confirmed by all the completed transportation designbuild projects in the state of Georgia, ranging from April 2007 to January 2020. A straightforward user manual is also provided to give users step-by-step guidance on how to use the software, along with snapshots of data entry and results publication.
x

ACKNOWLEDGMENTS
The research reported herein was sponsored by the Georgia Department of Transportation through Research Project Number 18-13. The authors acknowledge and appreciate the help from Mr. Darryl VanMeter, Mr. Andrew Hoenig, and Mr. Stephen Lively. Their invaluable assistance and insight were critical to the completion of this research. Mr. John Hancock and Ms. Lenicia Rogers-Lattimore shared their knowledge and experience on the application of cost estimation and risk management practices throughout the course of this project. The authors also thank Dr. Yashovardhan Jallan, Ms. Supriya Kamatkar, Mr. Sunil Thapa, Mr. Phani Kumar Aluri, and Ms. Gnana Deepthi Guduru, who have helped us throughout the progress of this research project.
xi

CHAPTER 1. INTRODUCTION
Funding availability plays a major role in determining strategic priorities for the longrange statewide transportation development plan (LRSTP). State Departments of Transportation (state DOTs) have implemented transportation financial plans, such as transportation improvement programs (TIPs) and statewide transportation improvement programs (STIPs), to utilize federal and state transportation funding within at least a fouryear horizon, and possibly longer. It is critical for state DOTs to maintain an adequate cash balance that helps establish a clear transportation plan and program (NASEM 2017). In recent years, a variety of issues, including changing economic conditions, delayed federal transportation reauthorization bills, and the declining value of fuel tax, have affected the ability of the states to provide an adequate budget for building new capacity and performing necessary maintenance on existing infrastructure (Rall et al. 2010). Considering significant uncertainty about project cost and construction market conditions, state DOTs have faced great challenges to manage construction expenditure cash flow of transportation projects (Camph 2008). Under these circumstances, an accurate construction expenditure forecasting model would help state DOTs by presenting a realistic view of expenditures in a given fiscal period.
Over the past two decades, an array of alternative project delivery methods has been introduced, in order to facilitate access to capital markets and encourage the private
1

sector's participation in transportation project development. Introduction of alternative project delivery methods provides significant opportunities to enhance the financing capabilities of the state DOT. The new delivery methods need to be properly handled in developing more realistic cash flow models for the project expenditures.
The cash flow model shows opportunities for deferred payments and other savings anticipated in the alternative delivery models. The significance of the new cash flow models lies in their capabilities to inform the Department about its actual future financial obligations, and, thereby, effectively use its limited capital to deliver more needed projects.
The major objective of this research is to develop a new cash flow expenditures model for the Georgia Department of Transportation (GDOT) design and construction program, taking into account flexibilities offered by innovative project delivery methods, such as designbuild (DB), designbuildfinance (DBF) and publicprivate partnership (P3). To achieve the research objectives, the following tasks have been done, and the report is structured as follows:
Chapter 2: Review of the state of the practice of cash flow forecasting in other state DOTs. Through comprehensive content analysis of documents (i.e., requests for proposals [RFPs], price proposals, and designbuild manuals), this chapter reviews the current practice of state DOTs in the following areas: (1) use
2

of a schedule of values (SOV) for DB contracts, (2) updates to the schedule of values, (3) approval and disapproval of progress payments, (4) incentives for early completion for DB contracts, (5) use of cost-loaded schedules for design and construction activities, and (6) use of price adjustment clauses in progress payments. Recommendations are given on how to improve the progress payment of DB and other innovative project delivery for highway projects. Chapter 3: Construction expenditure flows forecasting tool for transportation designbuild projects. A forecasting model is developed via a case-based reasoning (CBR) approach. By utilizing 19 project-specific attributes that are available for Georgia Department of Transportation (GDOT) projects at the time that the designbuild contracts are awarded, the model generates two types of predictions: periodic construction expenditure flow and cumulative construction expenditure flow. The proposed model was tested and confirmed by all the completed transportation designbuild projects in the state of Georgia, ranging from April 2007 to January 2020. Chapter 4: User manual for the developed Excel Visual Basic for Application (VBA) Tool. A straightforward and step-by-step description of how to use the software, along with snapshots of data entry and results publication, is provided. Chapter 5: Conclusions. A summary of the research findings is presented.
3

CHAPTER 2. SCHEDULE OF VALUES AND PAYMENT FOR DESIGN AND CONSTRUCTION
ACTIVITIES
INTRODUCTION A schedule of values is a detailed schedule providing a complete breakdown of the lump sum contract price and change orders into components that represent work or cost codes. Developing an SOV relies heavily on the selection of delivery methods (e.g., designbid build [DBB] and designbuild) for a highway project.
Major differences between the SOV of designbidbuild and designbuild projects are summarized as follows:
SOV of DBB Projects: o Being used with a unit price payment method for the construction progress. o Including unit price items and their measured quantities. o Being bases payments to the contractor on detailed take-offs.
SOV of DB Projects: o Being used with a lump-sum payment method for both the design and construction progress. o Including lump-sum items.
4

o Being bases payments to the contractor on the submitted monthly pay estimates.
Most DBB projects utilize a unit price payment method, where unit price items and their measured quantities are listed in the bid tab (FHWA 2018). Under a traditional unit-price contract, the owner typically selects the lowest bid for a project submitted by a contractor. The submitted bid for a project is computed by multiplying the submitted unit price by the contractor and the estimated quantity of each bid item by the owner. The owner makes payments to the contractor based on detailed take-offs of installed quantities for each unit-priced item. Thus, the owner should be able to inspect and monitor the contractor's progress and measure actual quantities installed (Scott and Mitchell 2007).
In contrast to DBB projects, DB projects commonly use a lump-sum payment method, where a value or budget for both design and construction progress split into an SOV based on each major feature of work (e.g., bridge projects, bridge painting, and guardrail) (Koch et al. 2010). Under a lump-sum contract, contractors develop quantity take-offs to estimate a lump-sum item for a project using the plans provided by the owner. An SOV for the DB project is developed by the selected contractor for design and construction activities. Based on consent on a payout schedule in the SOV or a cost-loaded critical path method schedule between the owner and contractor, the contractor is responsible to prepare and submit monthly pay estimates based on progress as a percentage of the lump-
5

sum prices. Under a lump-sum contract, the owner focuses more on monitoring and ensuring the quality of the work, rather than measuring and documenting quantities (Scott and Mitchell 2007).
In addition to the SOV, establishing a payment mechanism for both design and construction progress is paramount to the success of DB and other innovative project delivery projects (e.g., designbuildfinance, designbuildfinanceoperatemaintain [DBFOM], or other forms of P3s). The most common approach for calculating progress payment for DB and DBF contracts is a lump-sum payment method. In the DB/DBF contract, the designbuilder is required to assign a value (budget) of every activity or progress on an SOV, a compilation of the values of the various phases of the work (DeWitt et al. 2005, Koch et al. 2010).
In a DB contract, the owner makes a payment for the completion of each major feature of work (e.g., design completion, foundation, and superstructure), which are defined by the designbuilder. The owner also uses the completion of predetermined milestones for payment (e.g., fifty percent of design completion, ninety percent of design completion, and certain project completion thresholds), which is defined as a milestone payment method (Koch et al. 2010, Titus-Glover et al. 2016).
In a DBF contract, the Department defers payment either completely or partially to the designbuilder over the construction period. The designbuilder is responsible for the
6

design work, construction activities, and financing for all or a portion of the project, while the Department retains responsibility for the long-term operation and maintenance of the project. Furthermore, DBFOM contracts as a form of publicprivate partnership projects typically use milestone payments and availability payments (i.e., a performance-based payment) during the construction and operation periods (FHWA 2020). On the condition that the project meets defined performance specifications and specific project milestones, the owner makes a periodic payment for the concessionaire to compensate for designing, constructing, operating, and maintaining the project for a set concession period. To compensate for the costs of the design and construction activities, the owner uses revenue streams from taxes, fees, and/or tolls (FHWA 2017a). To determine the amount of the availability payment, a competitive procurement is utilized to select the bidder that submits the lowest availability payment. The availability payment approach allows the owner to attract more bidders and avoid risks of construction cost overruns and late completion, and risk related to operations, maintenance, and rehabilitation (Poole 2017). The following sections provide a summary of state DOTs' practices of the SOV and payment approaches for DB contracts.
7

PRACTICES OF STATE DOTS' SCHEDULE OF VALUES FOR DB CONTRACTS State DOTs in the United States utilize a scheme of the SOV for DB projects. The designbuilder is requested to develop and submit the SOV to the Department for approval. The Department uses the submitted SOV as the basis of payment for work completed at a specified time of the project duration. The designbuilder is required to update the SOV to ensure that the SOV accurately accounts for the scope and financial changes of a project.
Under DB contracts, the SOV typically contains three major elements: work items, unit price, and the total contract price. Since the designbuild contract is procured with a lump-sum agreement, the items for the DB SOV are less detailed, compared to the SOV in the traditional delivery method. The classifications/categories of the work items/project components on the SOV vary from Department to Department. State DOTs' SOVs present a wide range of required levels of details of SOV. For instance, Georgia, Florida, and Delaware DOTs require two levels of details for SOV, consisting of major work categories and lump-sum work items, while Virginia and Maryland DOTs require a list of lump-sum items in their SOV. Table 1 provides a summary of state DOTs' SOV practices for DB projects. Examples of several state DOTs--Georgia, Florida, Delaware, Virginia, Tennessee, and New York--are also provided.
8

Table 1. Summary of state DOTs' SOV practices for DB projects.

State DOT
Georgia DOT (GDOT 2018a)
Florida DOT (FDOT 2014)
Delaware DOT (DelDOT 2007)
Virginia DOT (VDOT 2014)

Definition of SOV
An itemized list that establishes the value or cost for each major element of the design build work.
SOV is used as the basis for progress payments.
A sufficient breakdown of each bid item for the costs of work and such other information that enable the Department to evaluate the progress of work and the value.
A basis for computing and/or verifying the contractor's progress payment requests.
The submitted SOV by the designbuilder is used as the basis of payment.
The SOV contains the list of project components (work items), project component values, and total lump-sum proposal price for a project.
The schedule of items (SOI), which is a corresponding term for the SOV, is used.
The designbuilder develops the SOI that contains proposed pay items, unit of measure, price/unit, and aggregate budgeted units and costs for all activities.

Payment Method
Payment is based on a percent complete for each activity as per the approved SOV.
Besides, Georgia DOT's Program Management Consultant Project Manager (PMC-PM) is responsible for processing payments based on the approved SOV.
Based on the schedule of values, the designbuilder develops the payout schedule, which is used as the basis for monthly payment for the percentage of work completed.

Required Level of Detail for SOV
1st Level: Design and Construction
2nd Level: Lump-Sum Work Items
1st Level: Major Category Items
2nd Level: Lump-Sum Work Items

The designbuilder makes requests for periodic payment using the form of RPP (Request for Periodic Payment) for the specified project component.

1st Level: Project Sections
2nd Level: Project Components

The designbuilder develops the cost-loaded project schedule based on the schedule of items.
The cost-loaded project schedule is used as the basis for progress payments.

1st Level: Lump-Sum Work Items

9

Table 1 (Continued). Summary of state DOTs' SOV practices for DB projects.

State DOT
Tennessee DOT (TDOT 2017)
New York State DOT (NYSDOT 2005
)
Maryland DOT (MDOT 2018a)

Definition of SOV
The SOI for a DB contract, which includes the list of pay items, is used.
The designbuilder assigns the value of work on the SOI.
The SOV contains the list of work items or project component for a DB project.
The SOV also includes the prices for the project components and the sum of the lump sum prices.
Maryland DOT provides to the designbuild team the schedule of prices (SOP), which contains all work for a DB project.
The designbuild team is requested to fill the SOP and include it in the price proposal.

Payment Method
Submission of progress schedules with the SOI is required for reimbursement monthly.
Progress schedule is sent to the designated Department contact person for verification of progress.
Based on the SOV, the designbuilder develops a proposal periodic payment schedule (PPS-P), which contains the distribution of the proposal price throughout the contract.
The PPS-P is used as the basis of periodic payment to the designbuilder along with the SOV
For a lump-sum contract, the contractor prepares an acceptable breakdown of the lump-sum contract price that shows the amount for each principal category of the work.
The Administration pays the contractor monthly for the contract value of the work according to the procurement officer's estimate of quantity satisfactorily performed (MDOT 2018b).

Required Level of Detail for SOV
1st Level: Project Management and Engineering & Construction
2nd Level: Lump-Sum Work Items
1st Level: Project Components
1st Level: Items of Work

10

Georgia DOT Georgia DOT requests the DB firm to submit a schedule of values, which is a tabular layout that lists all payment activities for the design and construction. For example, table 2 provides the form of the DB SOV used for GDOT's I-16 at 1-95 interchange reconstruction and I-16 widening from I-95 to I-516 project. The Georgia DOT's DB SOV is divided into two major sections: design complete and construction completion. It contains detailed information about activities, units of measure, quantities of the activities, unit prices, total prices, subtotals for the design and construction complete, and the sum of SOV (GDOT 2018a).
11

Table 2. Form of DB SOV of Georgia DOT's I-16 at I-95 Improvement Projects.

Activity Description
DESIGN COMPLETE Design Cost & Support Work Zone Law Enforcement Permits Insurance & Bonds ROW DB Team Project Management and Administration
CONSTRUCTION COMPLETE Final Acceptance Developer Quality Management Field Office Erosion Control Traffic Control Earthwork & Roadway Removals Drainage Barrier & Guardrail Base and Paving Landscaping ITS, Tolling & Signals Structural Walls Bridges Pavement Markings Sound Barriers Mobilization Maintenance During Construction Utilities Signs & Overhead Sign Structures Lighting Structural Removal/Demo Hazardous Materials/Environmental Mitigation Record Drawing (As-Builts) Completion of Punch List Final Close-Out Demobilization TRAINING HOURS

Unit Quantity

Unit Price

N/A

N/A

N/A

LS

1

$

LS

1

$

LS

1

$

LS

1

$

LS

1

$

LS

1

$

Design Complete

N/A

N/A

N/A

LS

1

$

LS

1

$

LS

1

$

LS

1

$

LS

1

$

LS

1

$

LS

1

$

LS

1

$

LS

1

$

LS

1

$

LS

1

$

LS

1

$

LS

1

$

LS

1

$

LS

1

$

LS

1

$

LS

1

$

LS

1

$

LS

1

$

LS

1

$

LS

1

$

LS

1

$

LS

1

$

LS

1

$

LS

1

$

LS

1

$

HR

50,000 $

Construction Complete

Sum of Schedule of Values

Total Price
N/A $ $ $ $ $ $ $
N/A $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $

12

Florida DOT The Florida DOT requests that the developer submit an SOV that contains a sufficient breakdown of each bid item for the costs of work in the price proposal. The Florida DOT uses the SOV to evaluate the progress of the work and the value. For example, table 3 shows the form of an SOV used for the Florida DOT's DBFOM I-4 Ultimate project. The SOV for the I-4 Ultimate project contains detailed line items on 16 major sections. In addition, the Florida DOT tracks and monitors the completion of the design and construction progress (FDOT 2014). The sections and items of the SOV can vary from project to project. Compared to the Georgia DOT's SOV, the work items for a project in the Florida DOT's SOV are categorized into detailed sections of project components, such as Engineering Services, Utility Relocations, and Mobilization. In addition, the Florida DOT's SOV contains a column of % of Design & Construction to track the percent completion of the work items.
13

Table 3. Form of design and construction SOV of the Florida DOT's I-4 Ultimate project.(FDOT 2014)
Notes: *Proposers are required to fill in costs associated with design and construction and maintaining the
Project Site during the Construction Period only. Other costs including, but not limited to, financing, operation, and maintenance shall not be included in this form. Each line item shall reflect the fully inflated cost for that
item. **Proposers are required to fill in additional items that are classified as "Miscellaneous." Use the
additional space provided within each section.
14

Virginia DOT Virginia DOT utilizes the schedule of items (i.e., SOV) in which the designbuilder defines the quantity of each pay item and its price (VDOT 2014). Virginia DOT requires the developer to submit the Price Proposal Form, which contains the Price Proposal Cost Breakdown Summary for design, construction, quality assurance, quality control services, and all other costs. Moreover, Virginia DOT asks the developer to identify quantities and costs of each proposed pay item in a schedule of items, which serves as the basis for progress payments. Table 4 shows part of an SOI for the Virginia DOT's DB I-64 project, provided by the developer. One of the main differences between the Georgia DOT's SOV and the Virginia DOT's SOI is that the work items are listed in the SOI without any categories. The Virginia DOT's SOV for the DB project contains not only lump-sum items but also unit-price items with their units. Any pay items considered for price adjustments should be identified in VDOT's schedule of items.
15

Table 4. A schedule of items for the Virginia DOT's DB I-64 project.

VDOT Item Code 1

Item Description
Design Service

Fuel (F) or Price (P) Adjustment

Approximate Quantity

Units1

Budgeted Cost ($)

1 LS

42,000,000.00

QA (Construction)

1 LS

6,282,000.00

QC (Construction)

1 LS

10,300,000.00

100 Mobilization

1 LS

20,350,000.00

101 Construction Surveying

1 LS

6,126,320.00

Project Management

1 LS

20,000,000.00

Wrecker Service

1 LS

1,000,000.00

Field Office

1 LS

4,139,754.55

Insurance

1 LS

6,605,000.00

Bond

1 LS

2,820,000.00

100110 Clearing & Grubbing

F

64 ACRE

896,000.00

100120 Regular Excavation

F

157,102 CY

2,513,632.00

100125 Grading

F

764,086 SY

1,910,215.00

100152 Embankment

F

128,690 CY

2,187,730.00

100272 Select Backfill TOTAL

F

38,599 CY

154,396.00

$ 409,595,765.00

Note: 1Use five-digit work item codes and units of measure that are consistent with Virginia DOT's list of standard and non-standard item codes (i.e., 00100-Mobilization; 00120-Regular Excavation, etc.).

Delaware DOT Delaware DOT uses the schedule of values for DB contracts as a baseline progress schedule. The designbuilder is requested to complete and submit the SOV to the Department, including a lump-sum price (i.e., the project component value) for each project component on the SOV. Table 5 provides the form of the schedule of values for the Delaware DOT's Bridge 3-156 DB replacement project. The SOV consists of four sections (Project Sections AD) with the list of project components (i.e., work items). In addition, the designbuilder includes the project component values (lump-sum price) into

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each project component in the SOV. The cumulative total of all lump-sum prices included on the SOV is the total lump-sum contract price for the project (DelDOT 2007). Compared to the Georgia DOT's SOV, the Delaware DOT divides the SOV into several sections, which contain proposed project components. The Delaware DOT requires the contractor to provide values for all project components in an SOV. However, the Delaware DOT's SOV does not have a unit of measurement and estimated quantity for the project components.
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Table 5. Form of Delaware DOT's schedule of values for replacement of Bridge 3-156. (DelDOT 2007)
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New York State DOT New York State DOT requests the designbuilder to prepare a schedule of values for a DB contract. The designbuilder coordinates with the Department in preparation for the SOV. Also, the designbuilder allocates a breakdown of the contract sum to the various portions of the work by taking into account labor, material, and major equipment costs. New York State DOT provides the designbuilder with the form of the SOV as a guide to establish line items for it (NYSDOT 2005). Table 6 shows the form of the SOV, which consists of a list of items or components, a unit of measure, and the unit price. One of the major differences between the Georgia DOT's SOV and the New York State DOT's SOV is that the New York State DOT uses the unit price items with their units of measurement for the DB project's SOV. In the New York State DOT's SOV, the contractor is required to provide the unit prices for each work item. Moreover, the New York State DOT's SOV does not contain the design development component.
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Table 6. Form of New York State DOT's SOV for a DB project. (NYSDOT 2005)

Section No.

Description of Item of Component(1)

Unit of Measure

Unit Price(2)

[Instructions: Develop a project-specific list to fit each project. The list on this template is for illustrative purposes only.]

Clearing and Grubbing Unclassified Excavation Borrow Sub-excavation Unsuitable Material Excavation Structure Excavation Structure Backfill Bituminous-Treated base Base Course Open-Graded Friction Course Minor Paving Plant-Mix Bituminous Pavement (Superpave)
Mechanically-Stabilized Earth Retaining Structures Portland Cement Concrete, Class AA Portland Cement Concrete, Class A Concrete Structures, Structural Concrete, Class A Super Structure Concrete Reinforced Concrete for Minor Structures Flowable Fill Pipe Culverts

Hectare Cu M Cu M Cu M Cu M Cu M
Cu M Cu M Sq M/cm of Depth Sq M Sq M Sq M/cm of Depth Sq M (Face Area) Cu M Cu M Cu M Cu M Cu M
Cu M

Notes: (1) Proposal shall provide additional descriptions as necessary to fully describe the Work covered by the unit prices shown; (2) Unit prices shall cover all construction costs to provide the item or component listed installed and in place per Contract Documents Part 2.

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UPDATES TO THE SCHEDULE OF VALUES Updating and revising the SOV as the project progresses is critical to the success of DB projects. The SOV should be continuously updated to account for complete activities, changes to the work sequence, changes to the scope of work, and other events that affect project completion (i.e., change order and adjustment of the contract price). The SOV is typically updated by the contractor by accumulating schedule change information for a payment period and is then submitted to the owner (Koch et al. 2010). The updating process for the project schedule can be completed by the agreement between the Department and the contractor.
In addition, approved change orders should be incorporated into the SOV to accurately reflect the financial changes during the construction. Change orders can be added to the SOV by increasing or decreasing the scope of an existing activity or creating new individual activities for change orders (Koch et al. 2010). Maintaining the most current SOV is critical, as it provides essential information for planning for efficient contract execution, monitoring the project for payments, and providing communication between the owner and the contractor (Molenaar et al. 2005). Several state DOTs--Tennessee, South Carolina, and New York--clearly stipulate updating and revising the SOV in a request for proposals for DB projects, which are provided in table 7. Compared to other state DOTs, such as Tennessee, South Carolina, and New York, the Georgia DOT explicitly states all the premises required for updating the SOV for DB projects.
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Table 7. Provisions for updating/revising SOV for a DB project.

State DOTs
Georgia DOT (GDOT 2018a)
Tennessee DOT (TDOT 2017) South Carolina DOT (SCDOT 2018) New York State DOT (NYSDOT 2016)

Description
The DB team updates and revises the SOV during the progress of the work when a revised baseline schedule is submitted, when the State Road and Tollway Authority (SRTA) requests, or when the contract sum is required to be adjusted to reflect according to the supplemental agreement(s). The designbuilder should update, adjust, and document the contract amount according to the change order. The contract amount should be reflected immediately in the critical path method (CPM) schedule. The contractor updates the schedule of values and the CPM schedule to reflect the adjustment in the contract price. The contractors submit the updated schedule of values to the Department for approval.
The designbuilder updates and resubmits the schedule of values when change orders affect the list of the project components.

APPROVAL AND DISAPPROVAL OF PROGRESS PAYMENTS
As a tool for tracking monetary change and quantitative change, a schedule of values in DB contracts plays a critical role during design and construction activities in ensuring that the owner and developer have the same understanding of the financial implications to their standard business practice for aligning goals and quality requirements and avoiding disputes (Koch et al. 2010). A progress payment is made based on the SOV and work performed through the payment period for DB projects. The developer typically requests the progress payment monthly. Based on the completed-to-date quantities of work, the Department pays the developer an undisputed percentage for the work performed during the period covered by the application for payments. Table 8 provides the summary of state DOTs' provision for approval and disapproval of progress payments for DB contracts.

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Table 8. Summary of state DOTs' provision for approval and disapproval of progress payments.

State DOT
Georgia DOT (GDOT 2018a)

Description
The designbuild team submits a draft payment request to Georgia DOT, which contains the amount to be payable for each line SOV line item and amounts due under Supplemental Agreements. Next, the designbuild team holds the Payment Request Review Meeting with Georgia DOT to finalize the draft payment request. The designbuild team submits the final payment request based on the approved draft payment request to the State Road and Tollway Authority for review and processing for the progress payment. With the Georgia DOT's approval of the Payment Request, the SRTA makes payment on approved amounts to the design build team.

Florida DOT (FDOT 2020a)
Maryland DOT (MDOT 2018a)

Approval of progress payment for the work completed by the designbuild firm is made by the Department's project manager/engineer through reviewing the quality and quantity of the work and comparing the reported percent complete against actual work accomplished.
The designbuild team submits an itemized Progress Payment Breakdown and supporting documentation (i.e., a written Application for Progress Payment), as a basis for payment, to the Administration. For a DB project, the designbuild team submits the monthly estimate based on a percentage applied to each lump-sum item. Based on the approval of the Administration, progress payment can be made to the designbuild team on a monthly basis. The Administration can request to submit additional detail/updates of the Payment Breakdown from the design build team in order to process progress payments.

Georgia DOT Georgia DOT requires the DB team to submit a draft payment request to Georgia DOT, who acts as a payment review and approval agent for SRTA. In the draft payment request, the DB team provides information about the amount asserted to be payable for each SOV line item and amount due under supplemental agreements. Figure 1 shows the form for payment requests for the DB contract. Georgia DOT uses the baseline schedule and monthly progress schedule to form the basis of payment for the project. The design build team is required to submit the progress schedule that describes the sequence and duration of the activities comprising the plans to accomplish the work within the contract

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time. Also, the DB team should submit an updated project SOV when the progress schedule is submitted for the payment for the project. Once the Georgia DOT approves the draft payment request, the DB team submits the final payment request to the SRTA. After the SRTA's final review and approval, the DB team receives progress payments (GDOT 2018a).
Figure 1. Image. Georgia DOT's Form of Payment Request. The Georgia DOT will not make payment to the designbuild team if there is an acceptance of any defective work or improper materials. In addition, the Georgia DOT withholds payments if the DB team does not comply with the following conditions (GDOT 2018a):
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a. Released for Construction Documents are on Site for the Work being performed; b. Released for Construction Documents have been checked and reviewed, and design
documentation has been maintained, in accordance with the Contract Documents; and c. Nonconforming Work Items are corrected and/or resolved to the satisfaction of GDOT.
Moreover, Georgia DOT includes the Office of Innovative Delivery program management consultant construction manager (OID PMC-CM) in delivering the DB contract. The OID PMC-CM's responsibility includes processing payments based on the approved SOV with the detailed breakdown of lump-sum items, providing comments on any critical path method schedule submittals, and monitoring the status of the project based on the approved SOV (GDOT 2018b). In addition to the schedule of value, the PMC-CM uses the American Association of State Highway and Transportation Officials' (AASHTO) AASHTOWare Project SiteManagerTM construction management software to prepare the necessary paperwork and approve the pay estimate (GDOT 2017). The process of project documentation, reporting, and tracking is critical for the Georgia DOT to validate that the work on each paid activity has occurred.
Florida DOT The Florida DOT determines the monthly progress and certifies the value of work performed by the designbuild firm on the project during each month based on the
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designbuild firm's approved pay schedule (i.e., schedule of values). The designbuild firm submits the monthly estimates to the Department engineer for approval for progress payments for the work. Once the Engineer approves the monthly estimate, the design build firm receives payments. If the designbuild firm fails to submit an acceptable schedule or monthly updates within the time frame, the Engineer withholds monthly payments for the work. The Florida DOT withholds payment when the designbuild firm does not meet the performance criteria (i.e., defective work or failure to comply with contract-agreed conditions). For instance, if the Department discovers any defective work or material or has reasonable doubt about any part of the complete work, the Department withholds payment until the designbuild firm has resolved the defective work and any causes of doubt. Also, the Department holds progress payment if the designbuild firm fails to comply with the following conditions within 60 days after beginning work (FDOT 2009):
a. Comply with and submit required paperwork relating to prevailing wage rate provisions, Equal Employment Opportunity, On-The-Job-Training, and Affirmative Action;
b. Comply with the requirement to report all necessary information, including actual payments to DBEs [Disadvantaged Business Enterprises], all other subcontractors and major suppliers, through the Internet-based Equal Opportunity Reporting System;
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c. Comply with or make a good faith effort to ensure equal employment opportunity for minorities and females hiring goals; and
d. Comply with or make a good faith effort to meet On-The-Job-Training goals. One of the major differences of the approval process for progress payments between the Georgia DOT and the Florida DOT is that the Florida DOT approves the progress payment within the Department with a project manager/engineer's review and approval, while the Georgia DOT needs final approval for progress payment from SRTA for P3 contracts and uses the OID PMC-CM for processing the progress payments.
Maryland DOT Maryland DOT requests that the designbuild team submit an itemized cost breakdown to establish pay items, which is used as the basis of the approval for progress payment. A cost breakdown is a realistic and documentable presentation of the costs for the major elements of work, comprising the lump-sum price for the work (e.g., Clearing & Grubbing, Mobilization, Design Engineering, As-Built Drawings, and Pavement Markings). To make effective the progress payment, the designbuild team should provide a more detailed progress payment breakdown to the Department. The unbalanced cost breakdown submitted by the designbuild team will not be approved until the breakdown is acceptable (MDOT 2009).
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To generate the payment to the contractor, Maryland DOT utilizes the Maryland Construction Management System (MCMS) software to monitor the project CPM and cash flow schedules, and review and process progress and final payments (MDOT 2016). The designbuild team submits the monthly estimates, a percentage of each lump-sum item, to the Maryland DOT. The Maryland DOT verifies the accuracy of the percentage for each work item and coordinates with the area engineer for acceptance of the estimate. The approved monthly estimates are entered in the MCMS system and finalized for processing the payment to the contractor (MDOT 2013).
The designbuild team should submit a written Application for Progress Payment to the Administration to receive payment for the work monthly. The Maryland DOT will withhold the applicable payment in whole or in part if the Application for Progress Payment is inconsistent with the payment breakdown, the projected schedule of payments, or the actual progress of work (MDOT 2016). Compared to the Georgia DOT's approval and disapproval process for progress payments, the Maryland DOT's approval for progress payment in P3 projects is made within the Department.
INCENTIVES FOR EARLY COMPLETION An incentive for early completion is a contract provision with which the developer receives a certain amount of money for each day when identified critical work is complete ahead of schedule. Early completion is defined as completing all the specified
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work in the plans and specifications and as meeting the Department's satisfaction for the final acceptance before the original completion date. The incentive for early completion is commonly used for critical projects where traffic inconvenience and delays need to be minimized. The incentive amount/bonuses for early completion are highly dependent on delivery methods (e.g., DB, DBFM, and DBFOM) and performance items (e.g., traffic control and maintenance costs, detour costs, and road user cost) (FHWA 2017b). Table 9 provides examples of state DOTs' early completion incentives for DB contracts. State DOTs, including Virginia, California, and Florida, use early completion incentives to expedite the completion of a project.

Table 9. Examples of state DOTs' early completion incentives for DB contracts.

State DOT
Virginia DOT (VDOT 2019a)
California Department of Transportation (Caltrans) (Caltrans 2008)
Florida DOT (FDOT 2020b)

Description
"No Excuse Incentive" Virginia DOT pays a financial incentive to the Contractor for meeting the requirements of Early Completion before the fixed Completion Date. The Contractor should complete all the work as detailed in the Plans and Specifications to the Department's satisfaction for the final acceptance. The Engineer will hold responsibility in determining the early completion. "No Excuse Incentive" Caltrans uses an Incentive Provision to motivate the contractors to complete the project within the established completion date. If the contractor completes the work on or before the completion date, the contractor receives the incentive.
"No Excuse Bonus" Florida DOT uses the No Excuse Bonus concept to shorten the construction time by providing the contractor with a substantial bonus to complete required work within a specified time frame. The intention of the No Excuse Bonus is to encourage the contractor to keep the project on schedule and reward a contractor for early completion.

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COST-LOADED SCHEDULES FOR DESIGN AND CONSTRUCTION ACTIVITIES
Under lump-sum contracts for design and construction activities, the payment schedule of values should be developed for securing the Department from overpayments, compensating the designbuilders fairly for completed work, and defining the project's cash flow through earned value analysis (Molenaar et al. 2005). To establish a payment schedule for a DB project, the designbuilder is required to submit a cost-loaded schedule, along with the SOV in the price proposal, for the owner's approval, which is also called cost-loaded critical path method schedules, that show the expected cash flow for the life of the project. In cost-loaded schedules, the designbuilder determines and assigns appropriate cost values to individual schedule activities or groups of activities in each payment period.
The cost values for individual schedule activities in each pay period are the accumulated costs, including all the direct costs associated with each work item and indirect costs and profit margins. Once the cost-loaded schedules are approved by the owner, they become the baseline schedule to calculate earned value along with periodic progress payments (Koch et al. 2010). In other words, the cost-loaded schedules play an important role in earned value analysis, which enables the owner and the designbuilder to measure a project's progress at each payment period and revise schedule milestones of the design development and construction. Thus, if there are any changes to the scope of an existing activity or the project's critical path, the cost-loaded schedules should be updated by the
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designbuilder to provide the most current schedule for the project, used as a reliable basis for decisions related to progress payments. Several state DOTs, including Georgia, Tennessee, South Carolina, and Virginia, have provisions of a cost-loaded schedule for their DB projects, which are provided in table 10. For example, one of the distinct differences between state DOTs is that Virginia DOT requires the DB contractor to submit a cost-loaded schedule for complex, high-risk, and costly megaprojects, while a cost-loaded schedule is optional for other projects (i.e., maintenance, simple construction, and slightly complex projects).
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Table 10. Provisions for cost-loaded schedule for state DOTs' DB projects.

State DOT
Georgia DOT (GDOT 2018a)
Tennessee DOT (TDOT 2017)
South Carolina DOT (SCDOT 2018)
Virginia DOT (VDOT 2012)

Description
Georgia DOT requests the DB team to submit the cost-loaded schedule that includes any milestone deadlines and schedule activity start and finish dates (or any durations) with assigned dollar amounts for all scheduled activities. The DB team revises and updates the cost-loaded schedule to ensure the proposed expenditure remains under the Annual Cumulative Payment Caps. The designbuilder is required to prepare and submit a project CPM schedule, including time and cost-loaded, to the Department for review and acceptance. The cost-loaded CPM should be updated by the designbuilder from time to time following contract requirements and depicting the following components: (a) pay items and subordinated activities and their respective prices; (b) duration, sequences, and interrelationships that represent designbuilder's work plans; (c) designbuilder's work structure for designing, constructing, and completing the project; and (d) the contract amount, distributed over the term of the contract. South Carolina DOT uses the cost-loaded CPM schedule for progress payments requested by and made to the contractor. The cost-loaded CPM schedule should be updated by the contractor to reflect the adjustment in the contract price. Virginia DOT uses a cost-loaded schedule for Category IV and V projects, representing complex, high-risk, and medium- to large-size projects and very complex and very costly mega-projects, respectively. The cost-loaded schedule is used to generate the time-distributed cost data on which the progress earning schedule is based. Thus, the cost-loaded schedule allows the Department to track the costs and assess the progress of the activity and the amount of time needed to complete the work. The costloaded schedule is prepared and revised by the contractor to reflect the current status of the work and any changes in the contractor's current work plan.

PRICE ADJUSTMENT CLAUSES IN PROGRESS PAYMENTS The volatility of construction materials such as asphalt, fuel, cement, and steel can result in difficulty for contractors to prepare accurate bids. A price adjustment clause (PAC) is a risk-sharing strategy that partially protects the contractor against unforeseen price increases in material or fuel that may occur between contract award and implementation of the work. With the PAC, the Department agrees to share the risk for escalating prices and pays the developer for any increases exceeding an agreed threshold (Newcomb et al.
32

2012). With the PAC provision, payments are typically adjusted based on unit price and an adjustment factor for material price changes. However, since the DB contract uses the lump-sum payment method, the Department should develop special provisions for DB contracts that provide base quantities and prices for all contract work to calculate price adjustments (FHWA 2017c). Some state DOTs (e.g., North Carolina and Virginia) include provisions for PACs for certain materials (e.g., asphalt, fuel, and cement) for their DB contracts. Table 11 provides examples of state DOTs' price adjustment provisions included in the DB contracts.

Table 11. Summary of state DOTs' price adjustment provisions in DB contracts.

State DOT

Description

Georgia DOT includes a special provision for Price

Georgia DOT Adjustments in the DB contract to share the risk of



(GDOT 2011) fluctuations in material prices.

Maryland DOT includes the provision of Price



Adjustments in the DB contract to provide additional Maryland DOT compensation to the designbuild team or credit to (MDOT 2018a) the administration for the fluctuation in the cost of

construction materials.

North Carolina DOT uses Price Adjustments



North Carolina Provisions to share the risk of the unusual price



DOT

fluctuation and minimize the cost effects of the price

(NCDOT 2018a) uncertainty for construction materials used in the

construction.

Virginia DOT (VDOT 2019a)

Virginia DOT uses Price Adjustment Provisions to



adjust monthly progress payments to take into account

cost changes in construction materials used on



specific items of work.

Types of Price Adjustment
Fuel Asphalt Cement
Diesel Fuel Asphalt Binder
Diesel Fuel Asphalt Binder Asphalt Concrete Plant Mix
Fuel Steel Asphalt Binder

33

Georgia DOT The Georgia DOT utilizes price adjustments for DB projects to deal with uncertainty in the future price of construction materials. For instance, the Georgia DOT included special provisions of price adjustment in the interchange construction project for connector ramps on I-85/SR 403/SR 400. In the special provision, the Georgia DOT provided the list of eligible bid items for fuel and asphalt cement price adjustments. Table 12 shows eligible bid items for price adjustments (GDOT 2011).

Table 12. Eligible bid items for Georgia DOT's price adjustments.

PAC
Eligible Items (Units)

Fuel Price Adjustments
Excavation (Cubic Yard) Graded Aggregate Base
(Ton) Hot Mix Asphalt (Ton) Portland Cement Concrete
Pavement (Square Yard)

Asphalt Price Adjustments
Hot Mix Asphaltic Concrete o Asphalt Cement used for Bituminous Tack cost (Ton) o Asphalt Cement used for Bituminous Surface Treatment

The Georgia DOT uses a fuel price index, computed on a monthly basis for both gasoline and diesel fuel, and an asphalt cement price index, posted on the Georgia DOT web page (i.e., http://www.dot.ga.gov/PS/Materials/AsphaltFuelIndex). The Georgia DOT states that price adjustments will be applicable on projects with greater than or equal to 366 Calendar Days (i.e., contract duration) from the Contract Letting Date to the specified completion date (GDOT 2011).

34

Maryland DOT The Maryland DOT uses price adjustment for DB projects to provide additional compensation to the contractor or credit to the Administration for the fluctuation in the cost of materials. The price adjustment provisions for diesel fuel and asphalt binder were included in the Maryland DOT's DB project, vehicle safety conditions, and traffic operation improvement along US 113. Table 13 presents the Maryland DOT eligible bid items for price adjustments (MDOT 2018a).

Table 13. Eligible bid items for Maryland DOT's price adjustments.

PAC
Eligible Items (Units)

Diesel Fuel
Excavation (Cubic Yard) Structure Concrete (Cubic
Yard) Aggregate Base (Ton) Hot Mix Asphalt (Ton) Rigid Concrete Pavement
(Square Yard)

Asphalt Binder
Asphalt Binder

The Maryland DOT uses the prevailing base index price for Performance Grade (PG) 64-22 (PG64s-22) asphalt binder and the On-Highway Diesel Fuel Price for the Central Atlantic Region published by the U.S. Department of Energy, Energy Information Administration (https://www.eia.gov/dnav/pet/pet_pri_gnd_a_epm0_pte_dpgal_w.htm). In addition, the price adjustment can be made when there is more than a 5 percent increase or decrease between the index price for the month of placement and the prevailing base index price (MDOT 2018a). One of the distinct differences between the Georgia DOT's PAC and the Maryland DOT's PAC is the base index price for the fuel
35

price. Maryland DOT uses the Diesel Fuel Price for the Central Atlantic Region, while Georgia DOT uses the Georgia average prices for the fuel price adjustment.

North Carolina DOT The North Carolina DOT's DB contracts include provisions of price adjustments for fuel and asphalt binder. The North Carolina DOT provides the list of eligible items in the Department Standard Specification. Table 14 presents the eligible items for fuel and asphalt binder price adjustment (NCDOT 2018b). Also, the price adjustment provisions were included in the North Carolina DOT's bridge replacement project in Cumberland County (NCDOT 2018a).

Table 14. Eligible items for North Carolina DOT's price adjustments.

Asphalt Binder

PAC

Fuel Price Adjustment

Price

Adjustment

Unclassified Excavation (Cubic Yard)

Asphalt Binder

Borrow Excavation (Cubic Yard)

for Plant Mix

Class IV Subgrade Stabilization (Ton)

Aggregate Base Course (Ton)

Sub-Ballast

Asphalt Concrete Base Course, Type ____ (Ton)

Asphalt Concrete Intermediate Course, Type ____

(Ton)

Asphalt Concrete Surface Course, Type ____

(Ton)

Eligible Items (Units) Open-Graded Asphalt Friction Course (Ton)

Permeable Asphalt Drainage Course, Type ____

(Ton)

Sand Asphalt Surface Course, Type ____ (Ton)

Aggregate for Cement Treated Base Course (Ton)

Portland Cement for Cement Treated Base Course

(Ton)

__" Portland Cement Concrete Pavement (Square

Yard)

Concrete Shoulders Adjacent to __" Pavement

(Square Yard)

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The North Carolina DOT uses the monthly selling price of asphalt binder and the base index price for Diesel #2 Fuel in adjusting the payment. For instance, the price for asphalt binder is adjusted by adding the difference (+ or -) of the base price index for asphalt binder for plant mix subtracted from the monthly selling price multiplied by the total theoretical quantity of asphalt binder (NCDOT 2018b). Compared to the eligible items of the Georgia DOT's fuel price adjustment, the North Carolina DOT has more eligible items for the fuel price adjustment, such as stabilization, open-graded asphalt friction course, and sand asphalt surface course.
Virginia DOT The Virginia DOT uses price adjustment clauses for DB projects. For instance, in the I-81 bridge replacement project, the Virginia DOT included the provision of price adjustment clauses for asphalt, fuel, and steel. The Virginia DOT included the list of eligible bid items of asphalt and steel for a price adjustment to the bid proposal and contract of the I-81 bridge replacement project. Figure 2 and figure 3 provide screenshots of the list of eligible bid items for asphalt and steel price adjustments for the bridge replacement project. The Virginia DOT uses the monthly statewide average price of asphalt materials obtained from suppliers, the diesel fuel prices published by the U.S. Department of Energy, and the producer price index published by the Bureau of Labor statistics for asphalt, fuel, and steel price adjustments, respectively. When there is a greater than 10 percent change between the current index (i.e., the unit price of all asphalt placed) and
37

the base index (i.e., the monthly statewide average price) during the middle of the month, the price adjustment is triggered. The designbuilder, then, submits a letter to the Department for the price adjustment. There are three major components used in the adjustment calculations, including base index, current index, and quantity of the construction material put in place during the month. The calculations for a price adjustment should be separated from the monthly progress payment for work packages and will not be included in the total cost of work for the determination of progress or for extension of contract time (VDOT 2016). One of the major differences between the Georgia DOT's PAC and the North Carolina DOT's PAC is that the Virginia DOT includes steel in the price adjustments for the DB contract. In addition, the Virginia DOT provides a more detailed list of eligible items for price adjustments in both the contract and the Department specifications.
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Figure 2. Screenshot. Asphalt material items eligible for price adjustment in the Virginia DOT DB contract.
Figure 3. Screenshot. Standard bid items eligible for steel price adjustment in the Virginia DOT DB contract. 39

SUMMARY Establishing a payment mechanism (e.g., SOV, cost-loaded schedule, and incentives) for both design and construction progress is a critical task for delivering DB and other innovative project delivery (e.g., designbuildfinance, designbuildfinanceoperate maintain, and publicprivate partnership) projects. Thus, the primary objective of this chapter is to review the current state of the practice in state DOTs regarding the schedule of values and progress payments of DB and other innovative project delivery for highway projects.
Through a comprehensive content analysis of documents (i.e., RFPs, price proposals, and designbuild manuals) from other state DOTs, this research reviewed the current practice of state DOTs in the following areas: (1) use of a schedule of value for DB contracts, (2) updates to the schedule of values, (3) approval and disapproval of progress payments, (4) incentives for early completion for DB contracts, (5) use of cost-loaded schedules for design and construction activities, and (6) use of price adjustment clauses in progress payments.
The recommendations from this chapter are summarized as follows:
A well-established SOV helps the Department develop a project-specific basis for reviewing and approving the designbuilder's work and developing a periodic pay estimate throughout the project.
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An updated SOV that accommodates any changes in the scope of work is essential to smooth execution of the progress payment and a successful DB project.
A detailed/updated payment breakdown for progress payments helps the Department approve/disapprove the payment to the contractor and reduce disputes.
Inclusion of early completion incentives in the DB RFP can encourage the designbuilder to not only finish the project on time but also minimize the impact on the communities in which the projects are constructed.
A well-defined cost-loaded critical path method schedule enables the Department to establish the expected cash flow for the life of the project.
Establishing and providing specific bid items that are eligible for price adjustments in a contract provides the Department with a more accurate and dynamic adjustment tool for payments.
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CHAPTER 3. CONSTRUCTION EXPENDITURE FLOWS FORECASTING TOOL FOR TRANSPORTATION
DESIGNBUILD PROJECTS
INTRODUCTION The work on forecasting expenditure cash flow for transportation projects is relatively underrepresented in the literature. Two studies were focused on fitting a mathematical function to model the cash flow of expenditure records of transportation projects. In the first study, Jarrah et al. (2007) classified Texas DOT projects from 2001 to 2003 into 10 groups based on their project types and contract amounts. For each group, Jarrah et al. fitted a single-variable polynomial function to model expenditure cash flows (the single variable was time). In the second study, Liu et al. (2015) fitted several mathematical functions to model the cash flow expenditures of two North Carolina DOT transportation megaprojects, including a linear polynomial model, quadratic polynomial model, cubic polynomial model, quartic polynomial model, exponential model, and rational model. Liu et al. found that, for the two studied megaprojects, quartic polynomial models provided the best fit to model expenditure cash flows.
Linear regression analysis and neural network analysis were also used to estimate the cash flow expenditures of transportation projects. Mills and Tasaico (2005) developed
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two polynomial regression models using time and project attributes, including number of active contracts, size, duration, engineering type, contract type, region, and weather, as inputs to estimate monthly payments for transportation projects completed by the North Carolina DOT between 2000 and 2002. However, the developed regression models did not show a reasonable accuracy beyond a 12-month forecasting horizon. Chao and Chien (2009) applied neural network analysis to estimate the parameters of polynomial functions that are used to estimate the expenditure curves of six subprojects of the second freeway in Taiwan. Contract amount, duration, type of work, and location were used as the inputs to the neural network models to estimate the coefficients of the developed polynomial functions.
However, none of the existing studies focused on forecasting expenditure cash flow of transportation designbuild projects. Designbuild has been increasingly used by state DOTs to expedite project delivery and utilize innovative ideas to improve the project performance (USDOT 2006). Cash flow estimating models built based on expenditure records of traditional designbidbuild projects are inherently limited for forecasting the expenditure cash flow of designbuild projects. DB projects include payments for several services that do not exist in DBB projects. Most importantly, a DB contract includes a design fee to complete detailed design services for the project, as the engineer of record is part of the DB team. Other services, such as design quality management and construction quality assurance services, are also parts of DB contracts.
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The pattern of expenditure is different in DB projects, as designbuilders strive to overlap design and construction services as much as possible, in order to expedite project delivery (i.e., packaging of work to facilitate fast-tracking). At the outset of awarding a typical DB contract, only high-level information is available to develop a conceptual cost estimate for the project. Since design has not been finalized, the exact quantities are not determined to develop a detailed cost estimate for the project. This issue represents a big difference between DB and DBB projects that makes estimating the project payouts more difficult for DB projects. Therefore, using expenditure records of designbidbuild projects as inputs to develop a forecasting model for the anticipated expenditure cash flow of a DB project is not appropriate. This research for the first time aims to develop a forecasting model to estimate the expenditure cash flow of transportation designbuild projects.
RESEARCH OBJECTIVES The overarching objective of this chapter is to develop a new expenditure cash flow forecasting model for transportation designbuild projects. The proposed forecasting model should be able to generate accurate forecasts with limited training data. In addition, it should be applicable to transportation DB projects with different compositions of tasks. Lastly, the proposed forecasting model should be able to utilize high-level describable attributes and to handle missing values in input, which might be a common problem in the conditions specified in this study.
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The existing forecasting models for the designbidbuild projects to be awarded are not suitable for transportation designbuild projects. The reasons are threefold. First, existing models rely on a large database, which may not be always accessible. For instance, Mills and Tasaico (2005) used 336 completed projects awarded by the North Carolina DOT between August 2000 and June 2002. Jarrah used 245 completed projects awarded by the Texas DOT between September 2001 and December 2003. On the contrary, in the same time periods, there were only two DB projects awarded by the North Carolina DOT (NCDOT n.d.) and no DB projects awarded by the Texas DOT (TxDOT 2019), correspondingly.
Second, existing models are based on simple curve-fitting of each type of project. However, as transportation owner agencies tend to use designbuild to handle project complexity and to transfer risks (Demetracopoulou et al. 2020), a designbuild project may comprise tasks of different types, making it hard to classify designbuild projects in the way designed for designbidbuild projects. For example, bridge replacement is a project type defined by the Texas DOT, for which Jarrah et al. (2007) fit individual polynomial models to represent. Yet, in addition to the task of bridge replacement, the Northwest Corridor Express Lane project in the state of Georgia, for instance, also includes other types of tasks by definition within the Georgia DOT (GDOT 2015), such as new location roadway, location-specific improvement, and widening.
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Third, existing models require too much detailed information, such as for scheduling. As a result of the integrated designbuild process, detailed scheduling information of DB projects does not exist at the pre-award phase. Only high-level describable project attributes that are available at the stage of preliminary design could be used as input for the forecasting model, such as contract amount and location. Moreover, there might be missing values in the input data, which is partially due to the unavailability of project classification by types. For example, design speed is crucial for a highway rehabilitation project, but it is not applicable for a pedestrian construction project.
METHODOLOGY An approach based on case-based reasoning and a genetic algorithm is developed in this project for creating a forecasting model for expenditure cash flow of transportation designbuild projects. Case-based reasoning is a data mining technique rooted in the notion that the solution of a new problem comes from the experience of solving previous problems in similar situations (Richter and Weber 2013). To generate a forecast for a new case, case-based reasoning retrieves existing cases with the highest similarities to the new case and then integrates the cash flows of the selected existing cases by taking the weighted average. The population of existing cases increases as the completed cases accumulate.
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Data A database of 33 transportation designbuild projects completed between April 2007 and January 2020 in the state of Georgia is used as the basis to create the forecasting model. The 33 projects are listed in Table 15 provides an overview of 19 project-specific attributes that were available for these GDOT projects at the time that the designbuild contracts were awarded. These attributes were taken from two sources: DB fact sheets published by GDOT (GDOT 2020) and GeoPI. GeoPI is a search engine designed to help users locate any GDOT-related data or documentation.
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Table 15. Projects used for model development.

Project Name
I-85 at KIA Interchange I-75 Southbound Auxiliary Lane (from I-675 to Eagles Landing Parkway) SR 400 @ Hammond Drive (Half Diamond Interchange) SR 204 Spur Bridge Replacement (over Skidaway Narrows) I-575 @ Ridgewalk Pkwy Interchange I-20 EB from I-285 to Panola Road (Collector Distributor System) SR 400/I-85 Connector Ramps Jimmy Deloach Connector (South of I-95 to SR 307/Bourne Avenue) I-75 NB Auxiliary Lane (Eagles Landing Pkwy to I-675 incl Walt Stephens Bridge Replacement) SR 400 NB Ramp Extension (Abernathy Rd) & SR 400 NB Lane Extension (McFarland to Big Crk Greenway) I-285 Variable Speed Limit Signs SR 400 @ Northridge Rd I-75 Managed Lanes (SR 155 to I-675/SR 138) SR 47 @ Little River 10.5 MI SE of Lincolnton Safe Routes to Schools (Various Locations) SR 316 @ Walther Blvd Grade Separation Weigh-in-Motion (WIM) Scales FY 14 incl Mainline WIM Software/Integration I-285 Ramps @ CR 209/Riverside Drive Roundabouts SR 21 @ I-95 Diverging Diamond Interchange (DDI) SR 400 Widening from McFarland Rd to SR 369 I-85 Managed Lanes Extension (Old Peachtree Road to CR 134/Hamilton Mill Road) SR 299 @ I-24 Bridge Replacement (Accelerated Bridge Construction) FY 16 Bridge Replacement Batch 1 FY 16 Bridge Replacement Batch 2 FY 16 Bridge Replacement Batch 3 FY 16 Bridge Replacement Batch 4 FY 16 Bridge Replacement Batch 5 CS 1868/Courtland Street @ CSX RR/MARTA/Decatur Street Northwest Corridor I-85 Widening CR 134/Hamilton Mill Road to SR 211 FY 17 Bridge Replacement Batch 1 FY 17 Bridge Replacement Batch 2 I-85 Corridor Bridges

Project ID
8232 8274
8415 8651 6043 9542 7623808690
10126
10311_10290
10782 7515809156_9157 2323100010401_0010403_0010394 10425 12683
10925 12722 13367 110600-
11682
14174 14175 14176 14177 14178 752015-
11061015523 15524 15436

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The project-specific attributes, as described in table 16, are basic conceptual information about the project scope and its basic design parameters at the time the project is getting under contract, for example, design traffic and design speed. According to the GDOT classification (GDOT 2015), projects can be grouped into seven major project types, i.e., bridge replacement, bridge maintenance, interchange reconstruction, location-specific improvement, systemic improvement, widening, and new location roadway. A design build project can belong to more than one project type. For example, a project may contain intersection reconstruction and traffic signal upgrades along the road. Of the 33 projects, 13 can be labeled as more than one project type. Table 16 provides detailed descriptions of 11 project-specific attributes that will be used as inputs in the model to forecast expenditure cash flow of designbuild projects. Of these 11 attributes, two variables are numerical attributes, two variables are categorical attributes, and seven variables are binary attributes. A range of possible values for these attributes is also provided in Table 16.
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Table 16. Project-specific attributes.

Project-specific Attribute
Contract amount Contract duration
Regional district
Procurement method Bridge replacement Bridge maintenance Interchange reconstruction Location-specific improvement
Systemic improvement
Widening New location roadway

Description
Numerical, ranging from $1,428,267 to $647,166,673, with mean $48,113,526, extracted from DB fact sheet Numerical, the period between two dates: notice to proceed date and completion date, ranging from 234 days to 1763 days, with mean 924 days, extracted from DB fact sheet Categorical: {regional district 1 to regional district 7}, GDOT has seven district offices throughout the state of Georgia, as shown in Figure 4 (GDOT 2018c), extracted from GeoPI Categorical: {one phase low bid, two phase low bid, best value}, extracted from DB fact sheet Binary, a type of project, classified by GDOT, extracted from GeoPI Binary, a type of project, include bridge painting, and repair & rehabilitation, classified by GDOT, extracted from GeoPI Binary, a type of project, classified by GDOT, extracted from GeoPI Binary, a type of project, including the construction of roundabout & intersections, traffic signals, pedestrian upgrades, lighting, and IT & operational improvements, classified by GDOT, extracted from GeoPI Binary, a type of project, including the construction of guardrail & cable barrier, edge line & centerline rumble strips, sharp curve treatments, sign upgrades, railroad crossing safety, and noise wall, classified by GDOT, extracted from GeoPI Binary, a type of project, including the construction of passing lanes and climbing lanes, classified by GDOT, extracted from GeoPI Binary, a type of project, classified by GDOT, extracted from GeoPI

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Figure 4. Map. Georgia district map.
In addition to project-specific attributes, several external attributes are also considered in modeling expenditure cash flow of transportation designbuild projects. Earlier research conducted by one of the authors (Baek and Ashuri 2019) showed that several variables representing local transportation construction market conditions have significant impact on submitted bid prices for projects. Table 17 represents six external attributes with the greatest impact on submitted bid prices. Two of these attributes represent how busy the local transportation market is on the same month as the designbuild contract is executed, total number of projects and total value of projects awarded by GDOT. Data of these two
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attributes are extracted from Bid Express. Bid Express is an online system containing information about past proposals, bid prices, and bidders of the Georgia highway projects. The other four attributes represent local transportation market conditions as far as key materials, labor, and equipment: Georgia Fuel Price Index, Georgia Asphalt Cement Price Index (published by the GDOT Office of Materials on a monthly basis), Job Opening and Labor Turnover Index, and Producer Price Index for Construction Machinery Manufacturing (available from the U.S. Bureau of Labor Statistics). Table 17 provides detailed descriptions of these six external attributes that will be used as inputs in our model to forecast expenditure cash flow of designbuild projects. All these attributes are numerical; a range of possible values is also provided in Table 17.

Table 17. External attributes.

External Attributes
Georgia fuel price index
Georgia asphalt cement price index
Producer price index for construction machinery manufacturing Job opening and labor turnover index
Monthly number of projects awarded in Georgia Monthly value of projects awarded in Georgia

Description
Numerical, an average selling price of fuel that is collected from approved local fuel suppliers as reported in GDOT's monthly survey, ranging from $1.73/gal to $3.86/gal, with mean $2.75/gal Numerical, an average selling price of asphalt cement that is collected from approved local asphalt cement suppliers as reported in GDOT's monthly survey, ranging from $304/ton to $623/ton, with mean $465/ton Numerical, an index measuring changes in prices received for the output of the construction machinery manufacturing sold to another industry, ranging from 116 to 139, with mean 133 Numerical, an index that represents the number of hires during the entire month as a percent of total employment, ranging from 176 to 566, with mean 358 Numerical, the number of projects awarded in each month and in the same county as of the project in the state of Georgia, ranging from 4 projects to 110 projects, with mean 30 projects Numerical, the total dollar value of projects awarded in each month and in the same county as of the project in the state of Georgia, ranging from $1,851,745 to $335,990,273, with mean $124,895,413

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Considering the relatively small number of designbuild projects in the dataset, casebased reasoning is selected as an appropriate method to develop a forecasting model for expenditure cash flow. Case-based reasoning is a powerful data mining algorithm for cases with a relatively small number of data points and a relatively large number of attributes describing each data point (Richter and Weber 2013). CBR is also found to have flexibility in terms of handling missing data and self-updating with new cases (Arditi and Tokdemir 1999). Model Development As Figure 5 shows, the development of the cash flow forecasting model comprises 10 steps. Each step is elaborated in this section.
Figure 5. Chart. Model development steps. 53

Step 1: Finding an appropriate function that best fits the expenditure records of each designbuild project in the dataset

First, the cumulative expenditure records of each designbuild project are plotted on a

graph where the horizontal axis represents project timeline progress as a percentage of

total project duration, and the vertical axis represents the cumulative payment as a

percentage of total project price. Figure 6 shows the plotted cumulative expenditure

records of all 33 designbuild projects in the dataset. The projects are labeled as project

#3, #10, #23, and #33. Three types of functions are tried to fit to the cumulative

expenditure records of designbuild projects in the dataset: cubic polynomial, quartic

polynomial, and beta functions. It can be seen that the beta function is overall the best fit

for cumulative expenditure records for these projects. In addition to providing a high level of accuracy in fitting the plotted points, the formulation of the beta function satisfies

the non-decreasing property of a cumulative expenditure function. The beta function is

defined by Eq. 1:

() =

0 -1(1-)-1 01 -1(1-)-1

(1)

where and are shape parameters that are estimated for each project, is the point in the project timeline (measured by percentage of total project duration) for which the

cumulative expenditure () (measured by percentage of total project cost) is calculated by the developed beta function.

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Figure 6. Graphs. Cumulative expenditure curve fitting for the designbuild projects.
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Figure 6 (Continued). Graphs. Cumulative expenditure curve fitting for the design build projects.
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Figure 6 (Continued). Graphs. Cumulative expenditure curve fitting for the design build projects.
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Figure 6 (Continued). Graphs. Cumulative expenditure curve fitting for the design build projects.
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Figure 6 (Continued). Graphs. Cumulative expenditure curve fitting for the design build projects.
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Figure 6 (Continued). Graphs. Cumulative expenditure curve fitting for the design build projects.
Step 2: Calculating Attribute Similarities The case-based reasoning algorithm uses the similarity between a project and other projects in the dataset to forecast the expenditure cash flow for the project. Higher project similarities imply higher similarities in cash flows. Project similarity is obtained by taking the weighted average of attribute similarity values. Attribute similarities are values
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ranging from 0 to 100 where a large value indicates high-level similarity. There are two types of project attributes in the model: numerical attributes and categorical attributes (including binary variables). When comparing the similarity of attribute s between project i and project j, the value is defined as Eq. 2 if attribute s is numerical, and the value is defined as Eq. 3 if attribute s is categorical. Attribute similarities are calculated between each project attribute of any two projects in the dataset.

,,

=

(1 -

) ,-,
,-,



100

(2)

,, = 1000

if , = ,

(3)

where ,, = the similarity of attribute s between project i and project j; , = the value of attribute s in project i; , = the maximum value of attribute s in all the projects in the dataset; and , = the minimum value of attribute s in all the projects in the dataset.

Step 3: Initializing Attribute Weights The overall project similarity is the weighted average of the calculated attribute similarities in the previous step. The computed attribute similarities are rolled up to determine the project similarity using appropriate weights. Finding the right weights is an optimization problem that needs to be solved. The weights are decision variables in this optimization problem. The objective function is to minimize the difference between the

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predicted expenditure curve and the actual expenditure cash flow curve. The initial sets of attribute weights are randomly generated with values between 0 and 100.

Suppose there are k designbuild projects in the dataset. In this step, the k projects are split into two subsets. The first subset contains only one project, denoted by project x hereafter. The second subset contains all the remaining k-1 projects that will be used for building the forecasting model. The second subset is referred to as the model building subset hereafter. The k-1 projects are used to determine an optimal set of attribute weights by which the overall error of cash flow estimating for k-1 projects is minimized. The optimal set of attribute weights will be applied on the project to be forecasted (project x), in order to predict its expenditure cash flow curve.

Step 4: Calculating Project Similarities

Consider a project in the model building subset, project y. Suppose project z is another project in the model building subset. The similarity between projects y and z is defined as Eq. 4, i.e., the weighted average of attribute similarities calculated in step 2 with the attribute weights selected in step 3.

= = 1(,,)

,

= 1

Eq. (4)

where , = the project similarity between project y and project z; = the weight for attribute s; and = the total number of project attributes. Using the same set of

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attribute weights, project similarities are calculated between any two projects in the model building subset.
Step 5: Identifying the Most Similar Projects to Project y in the Model Building Subset Projects in the model building subset with the highest project similarities to project y are selected to retrieve information for estimating the expenditure cash flow of project y. The top five similar projects with the greatest values of project similarities PS calculated in step 4 are identified. The cumulative expenditure cash flows of these five projects are used to estimate the cumulative cash flow of project y. Choosing the top five similar cases in the dataset is a recommended approach in the case-based reasoning literature, as five has been identified as an appropriate number of similar cases for building the prediction model (Ahna et al. 2017). The estimated results will be examined to ensure that selecting the top five similar cases leads to the best possible estimation for cumulative expenditure curves. The retrieval process described in this step is conducted for each of the k-1 projects in the model building subset.
Step 6: Generating Estimated Cash Flow The value of cumulative expenditure for project y is calculated at any point of time using the corresponding values of the top similar projects in the model building subset. Calculated project similarities are used as weights applied to the corresponding cumulative expenditure values of the top five similar projects. At any point in time during
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the project timeline (t), estimated cumulative expenditure for project y, denoted by (), is calculated using Eq. 5.

()

=

5=1(,()) 5=1 ,

(5)

where ()= cumulative expenditure of the cash flow of the retrieved project at time (t); , = the project similarity between project y and the retrieved project. The estimating process described in this step is performed on each of the k-1 projects in

the model building subset.

Step 7: Calculating Estimation Error The estimation error for project y is measured by mean absolute error (MAE) using Eq. 6.

= 0100%() - ()

(6)

where () = cumulative expenditure during the project timeline (t) of the estimated cash flow; and () = cumulative expenditure during the project timeline (t) of the actual cash flow. The MAE described in this step is calculated for each of the k-1 projects in the model building subset. The overall error of each set of attribute weights is computed by taking the average value of MAE for all k-1 estimated cash flows.

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Step 8: Using Genetic Algorithm to Search for the Optimal Set of Attribute Weights The space of attribute weights needs to be searched to find an optimal set of attribute weights that provides the lowest reasonable estimation error across all projects in the model building subset. A genetic algorithm is used to evolve the initial sets of attribute weights and search for the optimal set of attributes. The genetic algorithm has good capability to handle nonlinear optimization problems (Pal and Shiu 2004). The solution domain of the genetic algorithm is the sets of attribute weights. The fitness value of each set of attribute weights is its overall estimation error calculated in step 7. Fitness proportionate selection is used as the selection method of the genetic algorithm, in which the probability of each existing set of attribute weights to breed a new generation of weights is inversely proportional to its overall estimation error. Crossover and mutation are used as the genetic operators of the genetic algorithm to generate a new generation of weights. Crossover and mutation rates are set at 0.9 and 0.01, respectively. For each newly generated set of attribute weights, steps 47 are repeated. The genetic algorithm stops when the number of maximum generations is reached. In this study, the maximum generation is set as 500, following the rule of thumb given in the literature (Ahmed and Deb 2013, Zhang et al. 2009). Upon completion of this step, an optimal set of attribute weights is found for providing the best estimates for expenditure cash flows of k-1 projects in the model building subset.
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Step 9: Applying the Optimal Weights to Predict the Expenditure Curve of Project x The optimal set of attribute weights obtained in step 8 is used to forecast the cash flow expenditure curve of project x. The optimal weights are used to calculate the project similarities between project x and each of the k-1 projects in the model building subset using Eq. 4. The top five similar projects to project x are identified based on the greatest values of project similarities, and the value of cumulative expenditure for project x is calculated at any point in time using the corresponding values of these similar projects in the model building subset. The MAE measure described in Eq. 5 is used to calculate the error of forecasting the cash flow expenditure of project x.
Step 10: Conducting Leave-One-Out Cross-Validation A leave-one-out cross-validation (LOOCV) method is used to assess the accuracy of the developed case-based reasoning model. Completion of steps 39 results in the forecasted expenditure cash flow of one project in the dataset, project x. The same steps 39 will be repeated to forecast cash flow expenditure curves of the other k-1 projects in the dataset. In all, k rounds of the developed partitioning-training-forecasting process are conducted to predict expenditure cash flows of all projects in the dataset.
RESULTS The expenditure cash flow curve of each designbuild project in the dataset is forecasted using information from the other 32 designbuild projects in the dataset. Thirty-three
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forecasts are made using the developed case-based reasoning model, in order to evaluate the accuracy of the forecasting method. Figure 7 shows forecasted cumulative expenditure cash flow for all 33 designbuild projects in the dataset. The values of shape parameters and are specified for each forecasted beta function in the graph. The forecasted error term, i.e., MAE, is also identified for each predicted cumulative expenditure curve. Figure shows the distribution of MAE values of all predictions and associated minimum value, maximum value, and standard deviation.
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Figure 7. Graphs. Forecasted cumulative expenditure cash flow for the designbuild projects.
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Figure 7 (Continued). Graphs. Forecasted cumulative expenditure cash flow for the designbuild projects.
69

Figure 7 (Continued). Graphs. Forecasted cumulative expenditure cash flow for the designbuild projects.
70

Figure 7 (Continued). Graphs. Forecasted cumulative expenditure cash flow for the designbuild projects.
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Figure 7 (Continued). Graphs. Forecasted cumulative expenditure cash flow for the designbuild projects.
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Figure 7 (Continued). Graphs. Forecasted cumulative expenditure cash flow for the designbuild projects.
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Figure 8. Graph. Distribution of MAE values of predictions. Figure shows the connection of the 33 completed transportation designbuild projects involved in this study, on the basis of their mutual similarities. Each node represents a project, and each arrow represents a connection. For a project to be forecasted, only the five most similar existing projects would be used to build connections. For an arrow, the start node denotes the project to be forecasted, while the end node denotes an existing project to be used for generating prediction. As shown in figure, the connections between projects are evenly distributed, which implies that the proposed algorithm is capable of capturing the inherent similarities between seemingly unrelated designbuild projects.
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Figure 9. Image. Map of project network based on similarities.
Other configurations can be examined to assess how changes in the number of similar projects may impact the accuracy of the proposed forecasting model. Table 18 summarizes the accuracy level of the forecasting method under different scenarios for configurations of similar projects, i.e., using the top three, five, seven, and nine similar projects for predicting the cash flow. The results show that the mean value of MAE is higher when the top seven or nine similar projects are used for forecasting. The accuracy levels of the top three or five similar projects are fairly close to each other, but the accuracy range for the top five is lower than that for the top three. Therefore, five is considered the appropriate number of similar projects in the developed case-based reasoning method for cash flow forecasting. This number is consistent with some other
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applications of a case-based reasoning method in the literature (Ahna et al. 2017, Kwon et al. 2019).

Table 18. Comparison of different retrieval configurations.

Retrieval Configuration
3 similar projects 5 similar projects 7 similar projects 9 similar projects

Maximum MAE
0.240 0.224 0.223 0.225

Minimum MAE
0.015 0.017 0.024 0.029

Mean MAE
0.095 0.096 0.111 0.119

Standard Deviation of
MAE
0.052
0.046
0.038
0.038

In the literature, researchers developed different forecasting models for projects of different sizes (measured by contract amount and contract duration) (Mills and Tasaico 2005, Jarrah et al. 2007). Therefore, the authors of this study calculate the correlations between forecast accuracy and project size to examine if the proposed CBR model has consistent performance over projects of different sizes. As shown in table 19, the forecast accuracy of the proposed CBR model has weak correlations with either contract amount or contract duration. In other words, the accuracy of predictions generated by the proposed model is independent of the size of the transportation designbuild projects. However, due to the limited existing completed transportation designbuild projects, the results of the Pearson correlation test are not statistically significant. More completed projects are required to validate the results of the Pearson correlation test.

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Table 19. Pearson correlation test on the relations of prediction accuracy and project size.

Relations
Contract amount vs. forecast error Contract duration vs. forecast error

Correlation Coefficient
0.056
-0.052

Degree of Freedom
31
31

p-value
0.757 0.772

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CHAPTER 4. USER MANUAL OF THE DEVELOPED EXCEL VISUAL BASIC FOR
APPLICATION (VBA) TOOL
PURPOSE OF THE TOOL The purpose of the Excel Visual Basic for Application tool is to provide a data-driven forecasting model on construction expenditure cash flow. Project managers can use this tool to help decision-making in the practice of project planning and in the practice of progress management and cash flow management. The prediction on expenditure cash flow generated by this tool happens in the construction phase and does not contain the cost incurred outside the ownerdeveloper contract, such as the cost of preliminary engineering and agent fees.
This tool is designed for designbuild and designbuildfinance projects. After entering high-level, describable project attributes that are available for the projects to be awarded, the user could have predictions on the periodic payment obligations, cumulative payment obligations, and amount financed by the designbuilders. This tool sets up a public funding module by enabling users to manually enter the Fiscal Year available funding. This VBA tool is a stepping-stone for intelligent project management. It aims at serving project managers with data-driven predictions, which are complementary to the experience and expert judgement of project managers.
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STRUCTURE OF THE TOOL The tool has three pages, which are introduced below.
HOME PAGE (figure) The Home page contains links to the Input Data page, the Results page, and this user manual. When opening the tool, only the "Input data" button is activated.
Click the "Input data" button to enter project attributes. Successful completion of the Data Entry form brings back the home page and activates the "Predict the expenditure cash flow" button.
Click the "Predict the expenditure cash flow" button to activate the "Results" button.
Click the "Results" button to access the Cash Flow Prediction Results sheet. Click the "Erase Info and Start Over" button to erase all information of the
current project and start over with another project. Note: Save the previous project information manually. Click the "Manual" button to open and close the Manual page.
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Figure 10. Screen capture. Home page. Input Data Page The Input Data page allows entry of project identification information and attributes through manual entry fields, drop-down menus, and links (figure).
Figure 11. Screen capture. Input Data page. Following are detailed instructions on the project attributes to be input.
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Basic Information o This section is for notation only and includes the Project name and Project ID. The input values will not impact the calculation and prediction results.
Project Information o NTP Date, Completion Date, and Contract Amount are required. o All other attributes are optional. Note: Complete and accurate input helps to generate accurate prediction results. o A project may run along more than one district. Select the District in which the majority of the project lies.
Does the Project Include the Following Elements? o Related information can be found in the Concept Report, Preliminary Field Plan Review (PFPR) Report, and Final Field Plan Review (FFPR) Report.
Price Indexes of Key Items o Related information can be found from the GDOT website (figure), whose link is provided next to the input cells. (Use the project letting date to retrieve the data.)
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Figure 12. Screen capture. GDOT website for asphalt and fuel index.
Indicators for Level of Activities in the Transportation Construction Market o Total Number of Projects Awarded in the Current Month in the State of Georgia cannot be less than 1. o Total Dollar Value of Projects Awarded in the Current Month in the State of Georgia cannot be less than the number for Construction Amount ($) on the Data Entry page. o Related information can be found from the BidExpress website, whose link is provided next to the input cells. (Use the project letting date to retrieve the data.) Note: The GDOT Office of Construction Bidding Administration can help provide related information (i.e., the project letting date, total number of projects awarded in the current month in the State of Georgia, and total dollar value of projects awarded in the current month in the State of Georgia).
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Macroeconomic Indicators o Related information can be found from the U.S. Bureau of Labor Statistics website, whose link is provided next to the input cells. (Use the project letting date to retrieve the data.) o To retrieve PPI data, select the US Bureau of Labor Statistics PPI link and follow these steps: Select "Multi-screen Data Search" under Industry Data on the Featured PPI Databases page (figure 13).
Figure 13. Screen capture. Retrieving PPI data (1).
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Select "33312- Construction machinery manufacturing" by clicking on it once (figure 14).
Figure 14. Screen capture. Retrieving PPI data (2).
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Select "33312- Construction machinery manufacturing" by clicking on it once (figure 15).
Figure 15. Screen capture. Retrieving PPI data (3). Click the "Next form" button. o To retrieve JOLTS data, select the US Bureau of Labor Statistics JOLTS link and follow these steps: Under Job Openings and Labor Turnover Survey (JOLTS), select
"Multi-screen Data Search" (figure 16).
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Figure 16. Screen capture. Retrieving JOLTS data (1). Select "230000 Construction" by clicking on it once (figure 17).
Figure 17. Screen capture. Retrieving JOLTS data (2). Click the "Next form" button.
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Select "00 Total US" (figure 18).
Figure 18. Screen capture. Retrieving JOLTS data (3). Select "HI Hires" (figure 19).
Figure 19. Screen capture. Retrieving JOLTS data (4). 87

Select "L Level- In Thousands" (figure 20).
Figure 20. Screen capture. Retrieving JOLTS data (5). Select the checkbox for "Not Seasonally Adjusted" (figure 21).
Figure 21. Screen capture. Retrieving JOLTS data (6). Click the "Retrieve data" button.
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After filling the cells, click the "Save" button to go to the next step. Cash Flow Prediction Results Page (figure 22) The Cash Flow Prediction Results page allows the user to check and customize the prediction results. To get the results, follow the three steps shown in figure 22:
Step 1: Enter the Public Funding Available for each Fiscal Year. Step 2: Select the unit for Timeline (i.e., Month, Quarter, or Year). Step 3: Click the "Calculate" button.
Figure 22. Screen capture. Cash Flow Prediction Results page.
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For more information about the tool, contact Dr. Baabak Ashuri at the Georgia Institute of Technology:
Baabak Ashuri, Ph.D., DBIA, CCP, DRMP Professor, School of Civil & Environmental Engineering | School of Building
Construction Fellow, Brook Byers Institute for Sustainable Systems (BBISS) Director, Economics of the Sustainable Built Environment (ESBE) Lab Georgia Institute of Technology 280 Ferst Drive Atlanta, GA 30332-0680 Phone: (404) 385-7608 E-mail: baabak@gatech.edu
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CHAPTER 5. CONCLUSIONS
This research aims to develop a forecasting model for expenditure cash flow for the GDOT design and construction program, taking into account flexibilities offered by innovative project delivery methods, such as designbuild, designbuildfinance, and publicprivate partnerships. To achieve the research objective, current state of the practice regarding the schedule of values and progress payments of DB and other innovative project delivery for highway projects in several state DOTs are reviewed and best practices are identified. Moreover, an expenditure cash flow forecasting model is developed for transportation DB projects via a case-based reasoning approach. The developed model can generate accurate forecasts with limited training data and high-level describable project attributes, and it can handle inputs with missing data. An Excel Visual Basic for Application Tool is developed for project managers by using the proposed CBR model.
The following recommendations are found to be effective for managing progress payment of highway projects:
A well-established SOV helps the Department develop a project-specific basis for reviewing and approving the designbuilder's work and developing a periodic pay estimate throughout the project.
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An updated SOV that accommodates any changes in the scope of work is essential to smooth execution of the progress payment and a successful DB project.
A detailed/updated payment breakdown for progress payments helps the Department approve/disapprove the payment to the contractor and reduce disputes.
Including early completion incentives in the DB RFP can encourage the design builder to not only finish the project on time but also minimize the impact on the communities in which the projects are constructed.
A well-defined cost-loaded critical path method schedule enables the Department to establish the expected cash flow for the life of the project.
Establishing and providing specific bid items that are eligible for price adjustments in a contract provides the Department with a more accurate and dynamic adjustment tool for payments.
Forecasting on future construction expenditure flow is the basis of determining the capability of project letting. However, the features of transportation designbuild projects make the existing forecasting models for projects to be awarded not applicable. To narrow the gap, the authors proposed a CBR model with three characteristics: (1) having the capability to make an accurate forecast, even with limited existing completed projects as a training set; (2) having the flexibility to accommodate the complexity of
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transportation designbuild projects, even if the project comprises various types of tasks; and (3) having the capability to provide accurate forecasts by using easily accessible high-level describable project attributes, even with missing data. Thirty-three completed designbuild projects awarded by GDOT prior to January 2020 were used to test the model. The proposed CBR model features three advantages. First, unlike the curve-fittingbased models in the literature, the forecasting performance of the proposed model is not impacted by contract amount and contract duration, which implies wider applicability and better accountability. Second, compared with the curve-fittingbased models, the proposed model has the capability to generate forecasts based on up-to-date project records. Third, the proposed similarity-based model enables better interpretability in comparison with the neural network models in the literature. The proposed model is based on the inherent connections between project features and expenditure flows, which overcomes the lack of interpretability of the existing black box machine learning methods.
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