Automation in Construction 16 (2007) 569 – 575
www.elsevier.com/locate/autcon
Supply chain optimization tool for purchasing decisions in
B2B construction marketplaces
D. Castro-Lacouture a,⁎, A.L. Medaglia b , M. Skibniewski c
a
c
Building Construction Program, Georgia Institute of Technology, Atlanta, GA 30332-0680, USA
b
Departamento de Ingeniería Industrial, Universidad de Los Andes, Bogotá, Colombia
Department of Civil and Environmental Engineering, University of Maryland, College Park, MD 20742-3021, USA
Accepted 28 August 2006
Abstract
Current initiatives for e-commerce deployment in the construction industry are related to the establishment of business-to-business (B2B)
marketplaces, which allow large communities of buyers and suppliers to meet and trade with each other. Although these efforts have included
aspects of interoperability, database management and security protocols, trading mechanisms in the supply chain have not been properly
evaluated. Buyers of construction materials interact with material suppliers in a marketplace environment, thus striving for the best possible spot
buy offer. This paper addresses the purchase of construction materials as the last component in the supply chain. A tool for optimizing purchasing
decisions in B2B construction marketplaces is presented.
© 2006 Elsevier B.V. All rights reserved.
Keywords: B2B; Marketplace; Steel reinforcement; Optimization; Data envelopment analysis (DEA)
1. Introduction
The development and implementation of business-to-business
(B2B) marketplaces in the construction industry have opened a
gateway for buyers and suppliers. Over the last few years, construction companies have been conducting their business using
web-based trading mechanisms. E-commerce has provided an
expanded marketplace within which buyers and suppliers can
communicate directly, enabling them to buy and sell from each
other at a dynamic price which is determined in accordance with
the rules of the exchange.
An electronic marketplace is defined as an interorganisational information system that allows the participating buyers
and sellers in a particular market to exchange information about
prices and product offerings, thus matching them, facilitating
the exchange of information, goods, services and payments and
providing an institutional infrastructure that enables the efficient
⁎ Corresponding author. Tel.: +1 404 385 6964; fax: +1 404 894 1641.
E-mail address: [email protected] (D. Castro-Lacouture).
0926-5805/$ - see front matter © 2006 Elsevier B.V. All rights reserved.
doi:10.1016/j.autcon.2006.08.005
functioning of the market [1,2]. Although the behaviour of a
pure market is still maintained, in which a buyer can compare
different possible suppliers and select the best combination of
design and price, the use of information technology is likely to
decrease the costs of tasks such as selecting suppliers, establishing contracts, scheduling activities and budgeting resources
[3]. There are different types of marketplace for on-line trading:
commodity and differentiated markets. In the former, electronic
marketplaces can promote price competition among sellers by
increasing the availability of price information. In the latter,
characterized by heterogeneous consumer tastes and a variety of
product offerings, the role of an electronic marketplace is to
provide information about the existence and the price of a seller.
In the construction industry, the domain of the electronic
market is very distinctive. Since construction materials can be
considered commodities (e.g., cement, rebar, aggregate, etc.),
the variety of product offerings and the need for considering
both the price of a particular seller and the characteristics of the
corresponding product offering make it a differentiated marketplace. It is true that rebar is sold in tons, but the technical
characteristics of each bar are important at the time of purchase,
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D. Castro-Lacouture et al. / Automation in Construction 16 (2007) 569–575
as well as delivery times that will have implications in the
different stages of the project supply chain.
The most important benefits provided by the web-based
marketplaces are related to the permanent availability of trading
information and to the possibility of facilitating trading transactions. Users log onto the system as either buyers or sellers of
construction materials. Sellers can upload their product information and find out summary information about their customers
and their transactions. Buyers can search certain types of products, giving their requirements such as quality, price, type,
strength, etc., or they can browse the products on display. With
the use of mobile agents, the B2B e-trading marketplaces can be
connected, thus keeping member information in a database,
querying and ordering construction materials based on
availability and location [4].
This paper addresses the purchase of the construction materials as the last component in the supply chain. Although there is
considerable literature on electronic marketplaces, and the
framework for establishing an open e-trading marketplace in
construction has been described in previous research, a tool for
optimizing B2B transactions in the purchase of construction
materials is needed and is presented in this paper. Buyers of
construction materials can interact with material suppliers, or
sellers, in a marketplace environment. Steel reinforcement for
concrete (rebar) will be used as a typical construction material.
The methodology consists of presenting and validating a
supply chain optimization tool with hypothetical data, in the
context of a rebar marketplace. The data required by the supply
chain optimization tool is comprised of past completed transactions in the marketplace or previous matches between buyers
and sellers. This data is originated from the marketplace or from
the purchasing agent who keeps track of the activity on a given
rebar exchange. The supply chain optimization tool acts as a
decision support system for analyzing past transactions in the
marketplace in search of efficient and inefficient transactions.
2. Benefits of electronic markets
B2B electronic markets function as digital intermediaries that
focus on specific business functions and set up virtual marketplaces where firms participate in buying and selling activities
after they obtain membership [5]. Marketplaces create value by
bringing buyers and sellers together to create transactional
immediacy and supply liquidity, and by supporting the exchange
of demand and supply information. E-procurement is defined as
utilizing electronic media, including the Internet, to streamline
as many steps in the procurement process as possible. The major
benefits of adopting e-procurement systems are reduced operating costs and searching costs, which lead to high returns on
investments.
This paper discusses the application of a supply chain
optimization tool to the purchase of rebar. The rebar market is
very suitable for this study given its applicability for both
commodity and differentiated marketplaces. Most of the times,
rebar is bid and purchased based on price-per-ton competition
among suppliers, typical of a commodity marketplace. On the
other hand, based on the design demands or unique project
characteristics, a differentiated marketplace appears with heterogeneous consumer needs and a variety of product offerings
aimed to fulfil those needs (e.g., high tensile strength rebar).
The preliminary stages of rebar procurement feature long
periods of quantity takeoff revisions, cost estimation, quality
assurance and procurement. These delays translate into expensive activities for construction companies and rebar suppliers,
and into time overspent for activities that could be automated.
E-procurement should reduce uncertainties by enabling the
ordering, at a convenient price, of the precise types and quantities of materials needed to install on the subsequent workday,
resulting in higher quality of the implementation of the just-intime concept. Moreover, contractors may find the way of
tracking the status of critical orders, thus knowing instantly
when a supplier has run out of an already ordered item. Contractors want the purchase-related information to be entered just
once, flowing easily throughout the life cycle of their projects,
from the estimate and bid to the purchase order, and then into
home–office systems such as job costing and accounting [6].
The steel industry made an attempt to create an interactive
global marketplace named e-Steel, which provided an interactive online marketplace enabling both buyers and sellers to
initiate a transaction, specify product details, target offers or
inquiries to specific members, and negotiate and close contracts
[7].
3. Marketplaces in the procurement of construction materials
The application of e-commerce approaches to the procurement of construction materials has been subject of research in
the past few years [4,8]. These research efforts have proposed
initiatives for e-commerce deployment in the construction industry with the creation of B2B e-trading marketplaces, which
allow large communities of buyers and suppliers to meet and
trade with each other. One initiative is the e-Union, a prototype
system that utilizes web services technology to provide sharing
between construction material e-commerce systems, therefore
bridging the lack of interoperability between the material
databases. The unique feature of a B2B e-trading marketplace is
that it brings multiple buyers and sellers together in one central
market space and enables them to buy and sell from each other
at a dynamic price which is determined in accordance with the
rules of the exchange. The automation of rebar workflows have
been addressed in previous research, in which a B2B e-work
system was designed and validated [9,10]. The scope of the
B2B e-work system is limited to streamlining the workflow
during the take-off, estimating and bidding stages of the preconstruction interactions among supplier, contractor and
designer. This paper proposes the optimization of the transaction process using a supply chain optimization tool, a decision
support system for B2B purchases.
3.1. Online purchasing of construction materials in the US
It is widely believed that e-commerce can provide advantageous situations for both suppliers and buyers in the supply
chain. In spite of the massive use of the Internet for information
D. Castro-Lacouture et al. / Automation in Construction 16 (2007) 569–575
571
more timely responses to information requests, cost reductions
efforts, and enhanced employee productivity.
In spite of the featured capabilities for data control, Home
Depot and Lowe's still lack an integrated system that would
allow customers to adequately perform transactions by fully
satisfying the product requirements and delivery demands. The
efficiency of every individual e-trading site has proven successful for the internal data flow management and inventory
control, but not for transaction efficiency.
3.2. Estimation and procurement of rebar
exchange, the construction industry has not found yet an
adequate platform for material purchase and procurement.
Construction material retailers are using portals to sell their
products, thus lacking dynamic pricing or trading strategies that
could benefit both suppliers and buyers.
In the US construction industry, Home Depot and Lowe's are
presently utilizing e-commerce approaches for their retailing
practices [9]. These retail companies are also implementing
B2B solutions for the sharing of information among customers,
stores, suppliers and employees. Home Depot has point-of-sale
(POS) terminals at stores or available in the website. When
customers want to buy an appliance, they enter the order into the
POS system, which is connected to the supplier's inventory and
distribution systems. It allows consumers to buy appliances
directly from the supplier through Home Depot and schedule an
appointment to have the refrigerator delivered and installed at
the customers' convenience. On a different e-procurement approach, Lowe's employees are able to understand what is going
on at any store location. Regional vice presidents and district
managers can quickly view sales and inventory trends at any
store and make decisions that add value to the bottom line. As a
result of using the MicroStrategy platform, Lowe's is realizing
significant benefits through improved merchandising decisions,
Quantities of reinforcing steel are calculated by adding up bar
lengths according to size and converting the total length into
weight. The size number of the bar indicates the diameter in
eighths of an inch or millimetres for metric sizes. This weight
can be expressed in pounds (lb), hundred weight (CWT) or tons.
It is customary to include bar laps as additional quantities in the
total weight. These additional quantities may represent around
10% of the steel reinforcing bars used in the structure. Lap
lengths are calculated using the provisions of a building code.
The factors that affect the cost of reinforcing steel can be
classified as delivery factors and specification factors. Delivery
factors are those that influence the shipment and procurement
conditions of the purchase. For instance, some examples of
delivery factors are supplier proximity, expected delivery time,
potential delays, construction schedule, quantities, presence of
alternative suppliers, etc. On the other hand, specification factors
are inherent to the manufactured product, for example [11]: bar
grade, tensile strength, whether bars are deformed, have ridges
of indentations on their surface, or if they can be smooth, extent
to which bars must be fabricated, cut and bent, and the complexity therein, and whether bars can be plain or must be galvanized or epoxy-coated.
Reinforcing steel can be epoxy-coated either before or after it
is fabricated, and epoxy coating will typically add about 25% to
the installed price of reinforcement [12]. Reinforcing bars are
usually deformed, featuring ridges that provide bonding with
the adjacent concrete. Fig. 1 shows a typical steel reinforcing
bar featuring various marks according to several specification
factors such as manufacturer, size, type and grade. The grade
corresponds to the steel yield point in thousands of pounds per
square inch.
In the United States, the size designations of rebar are
specified by the American Society for Testing and Materials
(ASTM). Most bars are deformed; they have a pattern rolled
Fig. 2. Optimization tool owned by buyer.
Fig. 3. Optimization tool owned by seller.
Fig. 1. Steel reinforcing bar description (adapted from [13]).
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D. Castro-Lacouture et al. / Automation in Construction 16 (2007) 569–575
ratio between outputs and inputs. In other words, a purchase
transaction is efficient if it gets more outputs (e.g., quantity and
number of features) for fewer inputs (e.g., lead time and price).
5. Optimization of business practices
Fig. 4. Optimization tool owned by marketplace.
onto them that helps the concrete get a grip on the bar. Plain bars
are also manufactured, but are used only in particular situations
in which the bars are expected to slide (e.g., crossing expansion
joints in a bridge). The size designations are based on the
diameter in eighths of an inch of a plain round bar having the
same weight per foot as the deformed bar.
4. Business problem
In an e-business marketplace environment, a purchasing
agent is faced with the problem of defining an advantageous
offer. For instance, suppose that in a rebar net market, an agent
needs to bid on rebar to be used in a construction project. Before
submitting the bid to the exchange, the agent needs to fully
understand the possible tradeoffs between quantity, delivery
time, price to be paid, and features (i.e., grade, surface, shape,
etc), among others. Through the use of the supply chain optimization tool, the agent is expected to solve the following
situations:
▪
▪
▪
▪
▪
Initial price to be offered in the bid
Quantity of material for an efficient offer
Tradeoffs between bid price, lead time and material quantity
Competitiveness of bid price
Sensitivity of bid price to product requirements
By offering an initial price for a certain weight of rebar,
efficiency in the transaction can be understood as a generalized
In order to obtain better results in terms of cash flow,
working capital turnover cost reduction or quality, businesses
are continuously searching for new tools. In recent years, online
reverse auctions have emerged as popular means for reducing
the price of purchased materials used in the production of
durable goods. This dynamic bidding process typically results
in significantly lower prices than the buyer has historically paid
[14]. However, net savings may also be lower due to various
factors such as buyer not selecting the lowest bid, changes in
price through post-online auction negotiation or buyer purchasing neither all nor any of the line items [15]. This situation,
coupled with the lack of knowledge of market prices and their
behaviour and especially the local optimization of product
design at the expense of optimizing the performance of the
entire enterprise, makes businesses prone to unfavourable
outcomes [16].
With the use of the proposed supply chain optimization tool,
the analytical capabilities of three different entities in the transaction environment (i.e., sellers, buyers and marketplace) can be
enhanced. The ownership of the supply chain optimization tool
determines the application and treatment of the information to
be entered in the transaction.
Fig. 2 shows a case in which the supply chain optimization
tools is owned by the buyer.
This information can be used for purchasing analysis. Fig. 3
illustrates the situation when the supply chain optimization tool
is owned by the seller.
A third case, shown in Fig. 4, occurs when the marketplace
owns the supply chain optimization tool.
Information about past transactions is collected and owned
by the marketplace. This arrangement allows marketplace parties involved (i.e., sellers and buyers) to acquire the value-added
analytical service and information through the payment of an
Table 1
Sample data for a rebar marketplace
Date
Buyer
Transaction Paid
Lead time Weight Bar size Grade
Surface
Shape
ID
(×1000 USD) (days)
(tons)
(×1000 lb/in.2) (EC = epoxy-coated, Reg = Regular)
10/03/2004
10/04/2004
11/14/2004
11/15/2004
11/15/2004
11/18/2004
11/22/2004
11/26/2004
12/03/2004
12/04/2004
12/05/2004
12/06/2004
12/07/2004
12/07/2004
Amb. Steel
Steelia Ltd
ZBW Steelers
STB Co.
ARC Inc.
Van Steel
Consteel Inc.
Imatek
STB Co.
Van Steel
Consteel Inc.
Steelers Associates
Amb. Steel
STB Co.
CRS-001
CRS-002
CRS-003
CRS-004
CRS-005
CRS-006
CRS-007
CRS-008
CRS-009
CRS-010
CRS-011
CRS-012
CRS-013
CRS-014
5.18
6.63
3.98
6.90
10.35
1.74
7.74
8.70
8.18
9.81
7.28
17.02
5.26
2.63
15.00
18.00
18.00
15.00
15.00
18.00
24.00
18.00
18.00
18.00
10.00
12.00
12.00
20.00
3.00
5.00
3.00
4.00
6.00
1.00
4.00
5.00
5.00
6.00
7.00
14.00
4.00
2.00
4.00
4.00
5.00
6.00
6.00
4.00
5.00
6.00
7.00
8.00
8.00
6.00
7.00
8.00
50
50
50
50
50
60
60
60
60
60
60
70
70
70
EC
Reg
Reg
EC
EC
EC
EC
EC
EC
EC
Reg
Reg
Reg
Reg
Straight
Single bend
Single bend
Straight
Straight
Straight
Single bend
Straight
Straight
Straight
Straight
Straight
Single bend
Single bend
D. Castro-Lacouture et al. / Automation in Construction 16 (2007) 569–575
Fig. 5. Efficient front generated by the optimization tool with one input and one
output.
access fee. The supply chain optimization tool uses quantitative
data from previous transactions. This information is valuable for
sellers and buyers and helps them make decisions regarding
purchases or sales over the marketplace.
6. Computational experiments
To illustrate the reports available with the proposed supply
chain optimization tool, hypothetical data was used, arising in
the context of a rebar marketplace (see Table 1). The data
required by the supply chain optimization tool is comprised of
past completed transactions in the marketplace or previous
matches between buyers and sellers. This data is originated
from the marketplace or from the purchasing agent who keeps
track of the activity on a given rebar exchange.
Table 1 contains sample data from a deformed rebar
exchange. Each row in the table contains information on a
successful purchase transaction for a given type of rebar. First, a
simple, yet illustrative case is considered in which the amount
paid (in thousands of dollars) is considered an input and the
weight (in tons) is considered an output. The rationale behind
the model is that if a company pays more, it should get more
tons of steel. Current efforts are well underway to incorporate
categorical outputs such as bar size, grade, surface coating, and
shape, often present in the rebar Net market. Underlying
optimization models can be incorporated to deal with this type
of outputs [17–20].
After running the model behind the supply chain optimization tool (see the Appendix), the efficient front shown in Fig. 5
is obtained.
The transactions with Transaction ID of CRS-006, CRS-011,
CRS-012, and CRS-014 are efficient and are labeled with stars.
They define an envelope in which all the transactions below it
are called inefficient. In other words, the efficient transactions
serve as a reference set of best buy offers. Suppose that the
buyer is thinking of making a bid similar to the transaction
CRS-010, this is, paying $9810 for 6 tons of rebar.
Fig. 6 shows the recommendation made by the optimization
tool. After analyzing the buyer's bid, the optimization tool
will recommend the bidder to lower its offer by $2530 and to
573
Fig. 6. Projecting an inefficient transaction onto the efficient front.
aggressively negotiate an additional ton of steel. After this
simple analysis of the previous transactions made in the
marketplace, the buyer may want to rethink the offer.
To unveil the full potential of the supply chain optimization
tool, a model is analyzed with two inputs: amount paid
(thousands of dollars) and lead time (days); and one output:
weight (in tons). The rationale behind this model is that if more
is to be paid or delivery time is to be longer, then more tons of
rebar are to be received. The supply chain optimization tool can
help analyze the past transactions in the marketplace in search
of efficient and inefficient transactions. In Fig. 7 efficient
transactions are labeled with a star and inefficient transactions
are labeled with a triangular cylinder.
A quick exploration of the output of the optimization procedure suggests that under this new model, transactions CRS-006,
CRS-011, CRS-012, CRS-013, and CRS-014 are considered
efficient.
On the other hand, Fig. 8 shows the projection onto the
efficient front of the inefficient transactions.
For instance, if an analyst is planning to make a spot buy offer
in the marketplace similar to transaction CRS-005, Fig. 8 (e) tells
Fig. 7. Efficient (stars) and inefficient (triangle) transactions generated by the
optimization tool with two inputs and one output.
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D. Castro-Lacouture et al. / Automation in Construction 16 (2007) 569–575
Fig. 8. Projection of inefficient transactions onto the efficient front.
the analyst that there is significant room to improve the bid. The
optimization tool suggests, in this case, that in order to make an
efficient bid, the analyst could ask the supplier to shorten the
delivery time in 5 days, obtain 1 more ton of steel, and lower its
price by $3070. Although this might not be possible at the
current market conditions, the analyst could use this information
to fine tune his offer or negotiate a better informed deal.
In a similar fashion, results from the optimization procedure
suggest that transactions CRS-007, CRS-008, CRS-009 and
CRS-010 also have room for improvement by shortening the
delivery time, obtaining more tons of steel, and lowering the price.
The outcome of the optimization tool will lead to an optimized
spot buy offer. In the case of transaction CRS-007, in order to
make an efficient bid, the analyst could ask the supplier to shorten
the delivery time in 14 days, obtain 3 more tons of steel, and lower
its price by $460. For the purposes of negotiating a better deal
with current inefficient spot offers, a similar approach can be
taken for transactions CRS-008, CRS-009 and CRS-010.
The purchasing analyst may use the information provided by
the optimization output in order to project other inefficient
transactions onto the efficient front. For instance, for that pur-
pose the analyst could ask the supplier to reduce the delivery
time of transaction CRS-003 in 3 days, or while shortening the
delivery time of transaction CRS-004 in 4 days, the buyer could
obtain 2 more tons of steel.
7. Conclusions and further research
Current developments on the design of B2B e-trading
marketplaces are concentrated on building robust architectures
and frameworks, while the evaluation by practitioners and researchers of mechanisms for optimizing purchasing decisions
has not been properly addressed.
This paper addresses the purchase of construction materials
as the last component in the supply chain, presenting a tool for
optimizing purchasing decisions in B2B construction marketplaces. With the use of a supply chain optimization tool, the
analytical capabilities of different entities in the B2B construction marketplace are improved, focusing on rebar as a typical
construction material. Implications for current practices of rebar
procurement are related to satisfaction of contractors and rebar
suppliers in terms of product price and specifications. Both
D. Castro-Lacouture et al. / Automation in Construction 16 (2007) 569–575
buyers and sellers will have a tool that will allow them to
successfully complete transactions, thus getting the best
arrangement in relation to price, delivery time and quantity of
rebar material.
Several optimization models are analyzed with two inputs:
amount paid (thousands of dollars) and lead time (days); and
one output: weight (in tons). The supply chain optimization tool
acts as a decision support system for analyzing past transactions
in the marketplace in search of efficient and inefficient transactions. It was demonstrated for the case of various transactions
that, in order to make an efficient bid, the purchasing analyst
could ask the supplier to shorten the delivery time in, obtain
more tons of steel, and lower its price for the purposes of
negotiating a better deal with current inefficient spot offers.
The research efforts in this area should focus on characterizing the optimization model to represent rebar in the context of
a differentiated marketplace, not only limiting the envelope
analysis to quantities of steel, delivery times and price. Current
efforts from the writers are well underway to incorporate
categorical outputs such as bar size, grade, surface coating, and
shape, often present in the rebar marketplace.
Appendix A. The supply chain optimization tool
The mathematical core behind the supply chain optimization
tool is based on the theory of data envelopment analysis (DEA)
[17]. In DEA, it is necessary to solve a sequence of linear programming models, one for each transaction. We have implemented the
DEA additive model [17] using the SAS language.
Let J be the set of past transactions in the rebar marketplace.
In the jargon of DEA, these transactions are also called the
decision making units (DMU). Let n be the number of past
transactions in the marketplace. Let I be the set of factors in a
transaction considered to be inputs (i.e., price). Let m be the
total number of inputs. Let R be the set of factors in a transaction considered to be outputs (i.e., tons of steel). Let s be the
total number of outputs. Let xij be the amount of input i in
transaction j. Let yrj be the amount of output r in transaction j.
Let λj be the efficient front projection multiplier for transaction
j. Let sr+ and si−, be the efficient front slack for output r and
input i, respectively.
In the DEA additive model [17], for each transaction j′ = 1,
…, n, the following linear optimization model is solved:
min
k̄;sþ ;s−
zj V ¼ −
subject to:
P
yrj kj −sþ
r
jaJ
P
−
xij xij kj þ si
jaJ
P
kj
jaJ
kj z0;
sþ
r z0;
s−i z0;
X þ
X −
raR
iaI
sr −
si
¼ yr; j V; 8raR
¼ xi; j V;
8iaI
¼ 1
8jaJ
8raR
8iaI
575
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