Antonio Soares Aguiar, K. (Ram) Ramamurthy
IT Department, Atlantic University, Oeiras, Portugal
Sheldon B. Lubar School of Business, University of Wisconsin-Milwaukee, Milwaukee, U.S.A.
Antonio Palma Reis
Department of Management, ISEG - Technical University of Lisbon, Lisbon, Portugal
Keywords: EPS Implementation, Systems Integration, Power Balance, Green Procurement Performance.
Abstract: Information Technology (IT) can help generate a positive contribution, not only to the economic growth but
also to a better environment. In this context, our paper aims to analyze the role of electronic procurement
systems (EPS) implementation and use on the firm’s green procurement performance. We propose a
conceptual model to explain the role of EPS Implementation on procurement performance where the
environment component is also included. We hypothesize that: (1) procurement performance is affected by
the extent of EPS implementation success; and (2) the relationship between EPS implementation success
and procurement performance is moderated by both the power balance (between the focal firm and its
suppliers) as well as the extent of internal and external systems integration. Additionally we propose a
research methodology to empirically test the conceptual model and associated hypotheses.
The main objective of this research is to examine the
potential relationship between procurement
performance (measured not only by the traditional
efficiency and effectiveness criteria but also by a
new environmental dimension) and the
implementation of an electronic procurement system
(EPS). The current understanding of this association
can be enhanced by considering the specific role of
power balance between the firm and its suppliers
and EPS integration with both internal and external
(suppliers) systems.
Procurement, public and private, of goods and
services that are friends of the environment is a
possible definition of green procurement. The
application and effective use of this concept by the
buying organizations could generate significant
economical and environmental benefits. Taking into
account the public sector, one knows that around
16% of European Union wide GDP is for purchasing
goods and services. In what concerns to the private
sector, almost one half of the sales revenue of
business firms is typically spent in acquiring inputs
(goods and services) from external suppliers. Most
of that extensive budget is spent in products that
could easily be replaced by products with better
environmental characteristics. Just as an example, if
all public authorities across the EU demanded green
electricity, this would save the equivalent of 60
million tonnes of CO2, which is equivalent to 18%
of the EU's greenhouse gas reduction commitment
under the Kyoto Protocol. Because the electronic
procurement systems (EPS) are designed to store
and process large amounts of data about product
characteristics as well as suppliers, we see this type
of information system as an enabler for
organizations to significantly contribute to the
improvement of the environment. So, this paper
presents one main research question and two
additional accessory research questions: (1) Is there
a relationship between procurement performance
and EPS implementation success? (1a) Does power
balance moderate this relationship? (1b) Does EPS
Soares Aguiar A., Ramamurthy K. and Palma Reis A. (2010).
In Proceedings of the Multi-Conference on Innovative Developments in ICT, pages 32-38
DOI: 10.5220/0002960900320038
integration with both the firm’s internal and external
information systems moderate this relationship?
Getting answers to these research questions can
not only give firms one more management
instrument to improve their procurement
performance but also enable academics to use this
model to enrich the curricula and develop further
research. Based on the previously introduced
research questions, a theoretical framework as well
as the associated research hypotheses are developed
on Section 2. In Section 3 we propose a research
methodology that can be used to test the hypotheses
and find the answers to the former research
questions. Section 4 presents some limitations and
difficulties we will have to deal with along this
study. Finally, Section 5 presents the conclusions
and, since this is a research in progress paper, a
work plan to complete the research projects is also
The conceptual model that we propose is presented
in Figure 1. This conceptual model posits three
predictors for procurement performance: (1) EPS
implementation success; (2) power balance between
the focal firm and their main suppliers; and (3) EPS
integration with both internal information system
and external (main suppliers) information systems;
while controlling for firm size, EPS age and industry
effects. Next, we discuss in some detail each model
component while developing the study hypotheses.
Figure 1: A Conceptual Model for Procurement
2.1 Procurement Performance
Procurement performance is the final
dependent/endogenous variable in the model.
Typically, procurement consists of five stages:
search, negotiation and pricing or price discovery,
ordering, order coordination, and payment (Leenders
et al. 2002; Premkumar et al. 2005). Weele (2000)
developed a Procurement Performance Model where
effectiveness (product price) and efficiency (process
cost) were the main variables to evaluate. Using that
model, Kumar et al. (2005) developed a procurement
performance measurement system that could be used
by organizations in the health industry. In
accordance with these studies, the highest priorities
for procurement managers surveyed in Williams and
Hardy (2007) and Tanner et al. (2008) were
reductions in both purchase price (effectiveness) and
process costs of procurement (efficiency). Taking
into account both practitioners and researchers we
plan to use these variables to capture the impact of
EPS use on procurement performance. Additionally,
since EPS use can also have an impact at the
environmental level we are also interested in
capturing these possible benefits (waste and carbon
dioxide reduction) that can emerge from a successful
EPS implementation and use.
2.2 EPS Implementation Success and
Procurement Performance
In general, IT implementation success can be
evaluated not only through the effective use of the
system and user satisfaction but also at the Project-
Level (Finch 2003; Schwalbe 2007). Even though
users could use an IS it does not mean that they are
satisfied or feel comfortable using it. According to
Subramaniam and Shaw (2002) satisfaction is
affected by how well the IT is perceived to meet
user expectations. If the EPS is easy to use, allows
users to have lower cycle times on their orders or
allows them to access information quickly and with
minimum effort, user satisfaction could increase and
so would the EPS implementation success. On the
other hand, if an employee had the habit of going
physically to the purchase department in order to
request some items, s/he would probably have had
an informal and perhaps a pleasant conversation
with people around. Producing the order requisition
at the employee’s own computer keyboard
drastically reduces these unofficial meetings and
perhaps some satisfaction. When a firm is able to
implement an information system paying attention to
the appropriate implementation factors and it is
being used satisfactorily by employees (based on
DeLone and McLean (2003) updated model) it will
bring net benefits for the organization. In the context
of EPS one could say that with effective
consideration of the factors identified and defined by
Cooper and Zmud (1990) during the stages of the
implementation process one would expect that the
use of EPS will have a positive impact on the
procurement performance of the organization. Based
on these arguments we posit that:
H1: Higher levels of EPS implementation
success are positively associated with higher levels
of procurement performance.
2.3 EPS Implementation Success,
Power Balance and Procurement
While we argue above that EPS implementation
success could result in improved procurement
performance we also note EPS is an inter-
organizational system (IOS). In the context of IOS
the extent of dependence and an ability to exercise
power and control determines the balance of power
between the focal firm and its key suppliers, and has
often been cited as a key factor both in terms of
deciding on and setting the design parameters for
such systems as well as in terms of nature and extent
to which the systems would be managed and used.
Following the old adage that a chain is only as
strong as its weakest link, unless EPS is used by
both the focal firm and its major suppliers its
implementation can neither be deemed to be a
success nor is it likely to result in improved
performance. There is evidence to indicate that
dependence (of customer-supplier) and power have a
significant role in the decision to adopt and use these
systems (Wey and Gibson, 1991; Hart and Saunders,
1997). In a typical supplier-customer interaction
there is a certain amount of built-in dependency in
the relationships between the two parties given that
each is dependent on the other for resources that are
subsequently exchanged (Pfefer and Salancik, 1978).
The party that is less dependent on the other (e.g.,
has alternate sources for required resources) would
be in a position to exert greater control and power
over the inter-organizational transactional context
(Stern and Kaufman, 1985; Oliver, 1990; Hart and
Estrin, 1991). Research in marketing has found that
exercise of such power and control has a significant
influence on various aspects of inter-organizational
relationships such as decisions related to, for
instance, the system’s design parameters (Copeland
and McKenney, 1988), transaction parameters
(price, delivery schedule etc.), channel conflict, and
channel performance (Gaski, 1984). Based on these
discussions we posit that:
H2: The effect of EPS implementation success on
procurement performance will be low in contexts
where the balance of power is not in favor of the
focal firm; conversely, the effect will be high in
contexts where the balance of power is in favor of
the focal firm.
2.4 EPS Implementation Success
Systems Integration and
Procurement Performance
As a large-scale system that can involve several
business processes within a firm and its numerous
trading partners across the supply chain, an e-
procurement system requires huge investments in
terms of acquisition, implementation, integration,
training, and maintenance, placing tremendous strain
on company resources (Talluri et al. 2006). Barua et
al. (2004) defined the concept of systems integration
as the extent to which a firm integrates its various IT
systems to provide visibility to customer and
supplier data and to allow online information sharing
and transaction execution across the value chain. A
distinction can be made between internal processes
integration and external processes integration
(Porter, 1985; Williamsson, 1985). With regard to
internal processes, the integration of primary
processes (e.g., those integrating primary activities
and directly producing the outputs of the firm) can
be distinguished from the integration of secondary
processes, those that support secondary activities
(Barki and Pinsonneault, 2005). According to
Williamsson (1985), external processes integration
can also be separated according to whether they
integrate customers (direct forward integration),
suppliers (backward integration), or third parties for
instance, banks or government entities (lateral
integration). Since the focus of the analysis is the
procurement performance we are interested not only
in the effect of EPS integration with the firm’s main
suppliers (external backward integration) but also in
the effect of EPS integration with the firm’s internal
processes (internal process integration). We confine
only to the main suppliers of the firm because,
according to Talluri et al. (2006) at this stage of
evolution of the EPS life cycle it is not plausible that
all the suppliers could be integrated with the firm.
Indeed, EPS integration is a process of continuous
evolution when organizations have resources to
assign to that activity and are willing to be persistent
at those efforts. Thus, this study focuses its attention
on measuring the extent to which EPS is integrated
with different information systems within the
organization such as the ERP or even CRM systems.
The literature presents several studies showing that
the higher the extent of integration the greater the
benefits for the organization (Frohlich and
INNOV 2010 - International Multi-Conference on Innovative Developments in ICT
Westbrook, 2001; Frohlich, 2002; Subramaniam,
2003). Indeed, if the use of EPS can (1) automate the
order scheduling and fulfillment processes; (2)
support the operations or production planning,
scheduling, and shipment; (3) foster the access to the
supplier’s databases, for instance, to enable the firm
to track the status of an issued order; and (4) allow
the firm to receive electronic invoices from the
suppliers directly on its accounting system, then
chances are that the overall procurement
performance of the firm would improve. However,
based on Saeed et al. (2005) the impact of external
integration on process efficiency is significant for
higher levels of integration and not significant for
lower levels of integration. Based on the foregoing
discussion we posit that:
H3a: The effect of EPS implementation success
on procurement performance is low in contexts of
lower integration of EPS with other internal systems
of the firm; conversely, the effect is high in contexts
of higher integration of EPS with other internal
systems of the firm.
H3b: The effect of EPS implementation success
on procurement performance is low in contexts of
lower systems integration between the focal firm and
its main suppliers; conversely, the effect is high in
contexts of higher systems integration between the
focal firm and its main suppliers.
There are some parameters that should be evaluated
in order to design a research project (Sekaran, 2003):
the purpose of the study, the type of the research, the
unit of analysis, the time schedule, and the research
environment. Beyond that, this section also
describes the universe of the study, the data
collection methods, pretest of the survey, and, the
measurement issues.
The purpose of the study depends on the stage of
knowledge development on the topic under analysis.
A study may be either exploratory in nature,
descriptive, or it may test hypotheses. The purpose
of this study is to validate a model to explain
procurement performance based on EPS
implementation success, the power balance between
the focal firm and its suppliers and the systems
integration of the EPS and internal and external
systems. The validation of the model depends on the
test of three hypotheses proposing the relationships
between the model’s variables presented in Fig. 1.
The type of research can be causal or
correlational. A causal research is supposed to meet
the following criteria: 1) the cause must happen
before the effect; 2) variations observed in causes
should lead to systematic variations on effects; and
3) variations on the effects should not be assigned to
other factors except the causes (Reto e Nunes,
1999). Since the present research may not warrant
these conditions, this study must be considered
The unit of analysis is a research design choice
that is associated with the level of data aggregation.
In this research, the unit of analysis is the firm.
With regard to time schedule, a study may be
longitu-dinal or cross-sectional (Sekaran, 2003). A
study is longitudinal when the data about the unit of
analysis are collected at multiple points in time.
When the data regarding the unit of analysis are
collected on a single moment in time, the study is
cross-sectional. Since the data for this research is
planned to be collected just once and refers to just
one moment in time, this study is cross–sectional.
The research environment refers to the extent of
interference of the researcher in the location where
the phenomena occur. Therefore, we can have a field
study, a field experiment, or a laboratory
experiment. Field experiments and laboratory
experiments should be carried out when the purpose
of the research is to establish casual relationships. In
such a research environment, the interference of the
researcher is moderate to high. Field studies are
conducted when the researcher intends to perform
correlational studies with minimal interference,
which is the present case.
Regarding the universe of the study, we think
that a given phenomenon should be analyzed where
it occurs. In Portugal, EPS is nowadays a
phenomenon of the large companies. So, we have
selected the 2500 largest companies operating in
Portugal as the sampling frame to empirically test
the model presented in section III.
With regard to the data collection method we
plan to use a primary data source. Data will be
collected through a questionnaire that will be
available on the Web. Beyond the Web site, we will
also develop a database with information that will
allow us to send emails to chief procurement officers
of the targeted companies.
The questionnaire will be pretested through
interviews with procurement managers and IT
managers to assess its initial validity and overcome
any other inherent problems.
Operationally defining a concept to render it
measurable is done by looking at the behavioral
dimensions, facets, or properties denoted by the
concept. These are then translated into observable
and measurable elements (indicators) so as to
develop an index of measurement of the concept.
The measurement of constructs is developed
according to information shown on Table 1 through
Table 5. There, we show the concepts of the
theoretical model presented on Section II, the
indicators, the scales, and the sources used.
In this study, we want to test an association
between one metric dependent variable, the
procurement performance (PP, See Table 1) and a
set of metric independent variables (See Table 2 to
Table 5). As a consequence of the developed
conceptual model in Figure 1 and based on the
definitions in the previously introduced Tables (1 to
5), we can write that:
PP = β
+ β
*EIS + β
*PB + β
*II + β4
*EI + β
*(EIS*PB) + β
*(EIS*II) +β
where, the I
’s (k = 8, 9, 10) stands for the industry
dummies (three broad groups are considered for
analysis: manufacturing, commerce and services).
This model is consistent with our conceptual
framework in Figure 1 and the hypotheses defined
earlier. Testing the hypotheses is equivalent to
testing whether the coefficients β
’s (j = 1,5,6,7) are
significant or not, that is: (1) a significant and
positive coefficient β
means support for H1; (2) a
significant and positive coefficient β
support for H2; (3) a significant and positive
coefficient β
suggests support for H3a; and (4) a
significant and positive coefficient β
support for H3b; while significant and negative
coefficients imply inhibitors to procurement
Table 1: Measurement of variables in the conceptual
Concept Indicator Scale Source
Kumar et al.
EPS Internal
Integration (II)
EPS External
Integration (EI)
Power Balance
Wey and
Success (EIS)
et al. (2005)
Table 2: Green procurement performance indicators.
Indicator Description
The use of EPS has contributed to reducing the
price of products/parts/supplies that we
The use of EPS has contributed to reducing the
total costs in our procurement process
The use of EPS has contributed to buy new
products that allow us to reduce the waste
generated by the firm’s operations
The use of EPS has contributed to buy new
products that allow us to reduce the carbon
dioxide generated by the firm’s operations
Scale range (1= Strongly disagree; 7 = Strongly agree)
Table 3: EPS internal and external integration indicators.
Indicator Description
To what extent have you implemented web-
based processes to integrate EPS with your
company’s following systems?
Inventory consumption tracking, planning, and
control systems
Supplier payment/Accounts payable systems
Materials and product costing/accounting
Customer facing systems (e.g., sales order,
customer relationship, distribution, etc.)
To what extent have you implemented web-
based processes to integrate your EPS with
the following systems/processes at your main
Order scheduling and fulfillment
Operations (or Production) planning, scheduling,
and shipment
Allowing access to their databases (to enbale you
to track status of your order)
Accounting processes (e.g., billing, receivable,
claims, reconciliation…)
Scale range (0 = Not at all; 1= Rarely; 7 = Fully)
Table 4: Power balance indicators.
Indicator Description
Our firm primarily set prices and supply
terms/conditions for supplies to be procured
Our firm set the rules and procedures for order
placement and fulfillment
Our firm made most of the key decisions
regarding various design parameters for EPS
Our firm decided on enhancements/upgrades to
EPS and set standards for its use
Scale range (1= Strongly disagree; 7 = Strongly agree)
INNOV 2010 - International Multi-Conference on Innovative Developments in ICT
Table 5: EPS implementation success indicators.
Indicator Description
EIS1 EPS project did not violate the budgeted costs
Users are happy with the opportunity to use EPS to
perform their job
Users of EPS are using it to perform all the activities
of the procurement cycle (search, negotiation,
ordering, order coordination, and payment).
Scale range (1= Strongly disagree; 7 = Strongly agree)
We recognize that one big issue in the development
of this investigation will be data collection. In
Portugal, the executives do not have a good attitude
in responding to research inquiries. To be successful,
managers of those firms have to understand the
value of the research project and that's not an easy
job! Furthermore, even though our target is the 2500
larger firms in Portugal, we are aware of the low rate
of EPS adoption (around 20%, based on a study by
Soares-Aguiar and Palma-dos-Reis, 2008). So we do
expect some difficulties but we look forward to have
the wisdom and tools to overcome them.
We propose to empirically test a research model to
explain procurement performance based on EPS
implementation success, power balance between the
focal firm and its main suppliers, and EPS
integration with both internal and external (main
suppliers) information systems. If the hypotheses are
confirmed, then, the instrument can be used by both
academics and practitioners. While the academics
can use it for several purposes including further
research, the practitioners can apply it to improve
their green procurement performance measured by
the reductions on process cost, product price, waste
and carbon dioxide emission.
Since this is a research in progress paper, we
propose to empirically test the research model and
hypotheses using a large scale cross-sectional survey
study in the context of the 2500 relatively large
companies operating in Portugal. In order to
accomplish that task we plan to develop a data base
with information about the respondents (respondent
name, job title, email, company name, etc.),
implement a web-based survey, perform a pretest
and refine the instrument as necessary. After these
tasks have been completed, data collection will
follow. Care will be taken at various stages to ensure
that none of these steps is compromised to assure
satisfactory psychometric properties. Furthermore,
efforts will be made to ensure adequate sample
coverage to minimize inherent biases and sample
size to address concerns relating to statistical power
of the test. Given the contemporary nature and
importance of the domain of inquiry, it is gratifying
to note that a major association of purchasing
professionals has agreed to support the study by
requesting its members to respond to the survey.
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