Business process redesignproject success the role ofsoc

Business process redesign
project success: the role of
socio-technical theory
Junlian Xiang
Ted Rogers School of Management, Ryerson University,
Toronto, Canada, and
Norm Archer and Brian Detlor
DeGroote School of Business, McMaster University, Hamilton,
Canada
Abstract
Purpose – The purpose of this paper is to seek to advance
business process redesign (BPR) project
research through the generation and testing of a new research
model that utilizes formative constructs
to model complex BPR project implementation issues. Instead
of looking at management principles,
the paper examines the activities of improving business
processes from the project perspective.
Design/methodology/approach – A survey of 145 managers and
executives from medium and
large-sized USA and Canadian companies was used to validate
the model.
Findings – The model, based on socio-technical theory, includes
three implementation components
(change management, process redesign, and information and
communication technology
infrastructure improvement), and links the effects of these

components to BPR project outcomes.
The empirical findings indicated that all three implementation
components had a significant impact
on BPR project success, with change management having the
greatest effect. Interestingly, the results
also showed that productivity improvement was no longer the
main focus of companies carrying out
BPR projects; instead, improvement in operational and
organizational quality was more important.
Research limitations/implications – The main limitation of this
study is its generalizability
with respect to company size and organizational culture. The
sample in this study was drawn from
medium- and large-sized companies in Canada and the USA, but
small-sized organizations were
excluded from this study due to their distinct features (e.g.
superior flexibility or ability to reorient
themselves quickly). Also, this study controlled the variable of
organizational culture by limiting
respondents to Canada and US companies. It would be very
interesting to investigate BPR project
implementations in other countries where the organizational
working culture may be different.
Practical implications – Based on the findings of this study,
BPR practitioners can refer to the three
BPR project implementation components and then prioritize and
sequence the tasks in a BPR project
to achieve their preset BPR goals.
Originality/value – This is the first study which utilizes
formative constructs to validate the
important BPR project components.
Keywords Change management, Business process management,
Business process redesign,
Information and communication technology infrastructure,
Socio-technical theory

Paper type Research paper
1. Introduction
Business processes have drawn a great deal of attention from
industrial practitioners
and academic researchers since the 1990s because of their great
potential for improving the
efficiency and effectiveness of organizations. The roots of
business process focussed
research can be traced back to business process reengineering,
promoted by Hammer
and Davenport et al. (Hammer and Champy, 1993; Davenport,
1993), that described it
The current issue and full text archive of this journal is
available at
www.emeraldinsight.com/1463-7154.htm
Received 26 October 2012
Revised 22 January 2013
5 April 2013
28 July 2013
19 September 2013
Accepted 21 September 2013
Business Process Management
Journal
Vol. 20 No. 5, 2014
pp. 773-792
r Emerald Group Publishing Limited
1463-7154

DOI 10.1108/BPMJ-10-2012-0112
This research was supported by a grant from the Social Sciences
and Humanities Research
Council of Canada.
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Business process
redesign project
success
as a radical redesign of business processes resulting in a
singular transformation.
However, researchers soon realized that better results were
obtained when organizations
started with a revolutionary design phase, followed by actually
implementing changes in
an evolutionary manner ( Jarvenpaa and Stoddard, 1998). Later
on, a more general term
business process management (BPM) was widely adopted by
many researchers in the
business process focussed research context. BPM is defined as
an integrated management
philosophy and set of practices that includes incremental change
and radical change in
business processes, and emphasizes continuous improvement,
customer satisfaction,
and employee involvement (Hung, 2006; Houy et al., 2010).
BPM covers concepts such
as total quality management, business process reengineering,
business process redesign

(BPR), business process improvement, etc.
Usually BPM emphasizes different phases along its life cycle. A
complete review of
various BPM life cycles has been provided by Houy et al.
(2010). The current study
examines a specific group of business process focussed projects,
i.e. BPR. Instead of
looking at management principles, we examine the activities
involved in improving
business processes from the project implementation perspective.
Therefore, the term
BPR is used in this study. It is defined as a deliberate (planned)
change, typically
enabled by information technologies (IT) in an attempt to
redesign and implement
business processes to achieve performance breakthroughs in
quality, speed, customer
service, cost, etc. (Grover and Jeong, 1995).
Although extensive research has been carried out in the BPR
area, a recent article
has shown a continuing increase in interest in this field (Houy
et al., 2010). One of the
reasons for this interest is probably that the failure rate of BPR
projects still remains
high (Žabjek and Štemberger, 2009). Furthermore, the increased
interest in this
field implies that there are limitations in existing research
results. For example, studies
that do exist tend to be case study reports, making it difficult to
generalize findings
that yield consistent results (Bradley, 2008). Many previous
studies have carefully
examined the readiness of an organization to embark on a BPR
project (Fenelon,

2002; Abdolvand et al., 2008; Aghdasi et al., 2010). Some have
surveyed the best
practices of BPR project implementation (Mansar and Reijers,
2007). A few others
have started to measure outcomes related to BPR and IT
portfolios (Ramirez et al.,
2010; Ozcelik, 2010). However, as indicated by a recent
literature review, “[y]
most approaches concentrate on what needs to be done before
and after the
improvement act, but the act of improving itself still seems to
be a black box”
(Zellner, 2011, p. 1). Our observations are similar to the results
of Zellner’s study; i.e.
few studies have focussed on measuring and modeling what
organizations should do
during project implementation. Therefore, there is a need for
more rigorous research
in this area, specifically with regard to BPR project
implementation, to determine
and better understand how BPR project success rates can be
improved. Lastly,
few published studies have been able to address the
complexities of the BPR problem
in one research model. One reason is that it is almost impossible
to use traditional
reflective constructs to model such a complex problem. The
appropriate technique
to use in these situations is the application of formative
constructs, but this has
been neglected in the past ( Jarvis et al., 2003; Diamantopoulos
et al., 2008; Petter
et al., 2007).
The goal of this investigation is to model important BPR project
implementation

components, as well as to test the impact of these components
on BPR project success.
Various facets of BPR project outcomes were used in order to
examine how BPR project
implementation components would bring performance
improvements.
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To achieve this goal, the researchers began with a review of the
BPR literature on
project success factors, and then identified one important BPR
enabler and three
implementation components, using socio-technical theory (STT)
as a guide. These
formed the basis of the study’s research model. The paper
continues with the
development of the theoretical model and hypotheses. After
carefully examining the
causal relationships between the BPR project implementation
components and their
measures, formative constructs were judged to be the
appropriate way to model those
components. The research method involved validating the
model, through a survey
administered to 145 managers and executives from medium and
large US and Canadian
companies; responses are analyzed using structural equation
modeling techniques,
involving partial least squares (PLS). Next, the research results
are presented and

analyzed. Lastly, the implications of the research are discussed.
2. Theoretical model and hypotheses
2.1 STT and BPR project implementation components
From the early 1990s to the mid 2000s, few theories were used
to inform or guide BPR
project research. Rather, most of the literature reported during
this period merely listed
BPR project success factors identified through case study
research (Grover et al., 1998).
However, since the mid 2000s, BPR researchers have started to
borrow theories from
other areas of research and apply these to the BPR context
(Newell et al., 2000; Sarker
and Lee, 2002; Sarker et al., 2006). As a result, initial
frameworks (Grover and Jeong,
1995), models (Ifinedo and Nahar, 2009; Law and Ngai, 2007),
and constructs (Guha and
Grover, 1997) have been developed. Of these, STT appears to
be promising.
STT views the organization as a work system with two
interrelated subsystems:
the technical system and the social system (Bostrom and
Heinen, 1977). The technical
system is concerned with the processes, tasks, and technology
needed to transform
inputs such as raw materials to outputs such as products; the
social system is
concerned with the relationships among people and their
attitudes, skills, and values.
The outputs of a work system are a result of the joint interaction
between these
two subsystems.
A critical important enabler for BPR project success, regarding

the social aspect
of STT, is top management support (TMS). Top management
plays an important
role in BPR projects as suggested by STT (Markus, 1983). “This
type (supportive) of
leadership offers a vision of what could be and gives a sense of
purpose and meaning
to those who would share that vision. It builds commitment,
enthusiasm, and excitement.
It creates a hope in the future and a belief that the world is
knowable, understandable,
and manageable. The collective energy that transforming
leadership generates,
empowers those who participate in the process [y]” (Roberts,
1984, as cited in
Lashway, 2006, p. 91). As claimed in project management
research, “top management
support is the most important critical success factor for project
success and is not
simply one of many factors” (Young and Jordan, 2008, p. 1).
Numerous surveys and
case studies have shown that TMS is one of the most highly
ranked success factors in
BPR project practice (Fui-Hoon Nah et al., 2003; Grover and
Jeong, 1995; Herzog et al.,
2009). Grover and Jeong (1995) identified the lack of TMS as a
serious problem
impeding the success of business process reengineering
implementations. Strong
support from top management is also necessary to resolve any
conflicts of interest
among the various parties involved (Ahadi, 2004). Therefore,
this study hypothesizes
that TMS would positively impact BPR project success.
However, this study takes a
further step to explore what are the important components in the

BPR project
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Business process
redesign project
success
implementation and to evaluate how TMS affects BPR project
success through the
project implementation components. This brings us to our first
hypothesis:
H1. Stronger TMS will result in a better BPR project
implementation procedure.
When exploring BPR project implementation components, this
study considers both
the technical and the social dimensions, and their interactions.
As Grover and Jeong
(1995) point out, STT emphasizes the impact of the changes to
technical and human
resources on altered tasks or processes. As such, technical
resources, human resources,
and altered tasks/processes are reflected in this study as three
implementation components:
information and communication technology infrastructure
(ICTI) improvement, change
management, and process redesign.
ICTI is the technology foundation dealing with the IT
capabilities on which
processes and humans rely, such as networks, databases, data

inter-exchange, etc. for
transforming inputs to outputs (Law and Ngai, 2007). The
capabilities of ICTI consist
of a wide spectrum of components, including ICTI platforms,
standards, policies, and
different types of service arrangements.
Change management includes the methods through which
attitudes, skills, and
values of the people in the system are managed and transformed
(Huq et al., 2006).
Change management is the soft part of the change process since
it addresses human
resource problems within organizations, such as employee
resistance and structural
adjustments. It requires effectively balancing forces in favor of
change over forces
of resistance from organizations, groups, and individuals (Guha
and Grover, 1997;
Markus, 1983).
Process redesign can be thought of as the interaction of the
social and technical
aspects of STT. For example, people (such as employees,
customers, etc.) work to get
expected outputs by following company procedures that
implement specific business
processes, supported mainly by IT.
When applying STT to BPR project implementations, it is
important to understand
that, whether companies have fixed process goals (e.g. BPR
projects that follow
external rules enforced for ERP systems implementations) or
they design processes
that fit their own requirements, new processes cannot work well

unless people issues
are resolved and IT support is suitable. In this way, the effects
of ICTI improvement
and change management are reflected through the redesigned
processes. Business
processes can never work without both operators (people) and
carriers (technical
implementation) (Davenport, 1993).
Given the above discussion, our first hypothesis can be
decomposed into three sub-
hypotheses. That is, TMS is hypothesized to positively affect
the three implementation
components. Hence:
H1 (a, b, c). Stronger TMS will result in better levels of change
management, BPR,
and ICTI improvement, respectively.
2.2 BPR Project outcomes and success
BPR project success is defined as the advantageous outcomes
that a BPR project
achieves for an organization. It is improper to use a single
financial criterion
(e.g. cost reduction itself) to evaluate BPR project outcomes.
Grover used two different
perspectives: perceived level of success and goal fulfillment, to
evaluate BPR success
(Grover and Jeong, 1995). The perceived level of success seeks
to assess the degree of
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attainment in relation to the targets, and the goal fulfillment
perspective determines
success by attainment of a normative state (Hamilton and
Chervany, 1981).
The second perspective, goal fulfillment, is based on the
commonly emphasized
goals of BPR projects. Four categories of outcomes were
adopted in our study
(Raymond et al., 1998): first, operational quality improvement,
or improved quality in
goods and services (e.g. customer service and satisfacti on);
second, organizational quality
improvement, or improved quality of organizational
coordination and communication
(e.g. lessened managerial hierarchy, improved task enrichment,
and reduced bureaucracy);
third, cost savings, involving administrative and production cost
savings (in terms
of return on investment, personnel costs, operational costs, and
profits); and fourth,
productivity improvements that result from increased
productivity of workers and
managers (more units produced, fewer delays).
In order to examine the effect of the three implementation
components, their impact
was tested on each of the four categories of outcomes,
hypothesized as follows:
H2 (a, b, c, d). A higher level of change management will result
in a higher level of
operational quality improvement, organizational quality
improvement,

cost savings, and productivity, respectively.
H3 (a, b, c, d). A higher level of BPR will result in a higher
level of operational
quality improvement, organizational quality improvement, cost
savings, and productivity, respectively.
H4 (a, b, c, d). A higher level of ICTI improvement will result
in a higher level
of operational quality, organizational quality, cost savings, and
productivity, respectively.
The researchers were also interested in how these categories of
outcomes would
contribute to the perceived level of project success. Different
BPR projects may target
different fulfillment goals. It is important to understand what
company goals are
focussed on through BPR projects because different goals may
trigger different
emphases in their BPR project implementation components.
Thus:
H5 (a, b, c, d). A higher level of operational quality
improvement (organizational
quality improvement, cost savings, or productivity,
respectively)
from a BPR project will result in a higher level of perceived
BPR
project success.
The research model built from this study is summarized in the
path model in Figure 1.
The model examines how TMS affects BPR project
implementation components, which
in this study includes change management, process redesign,

and ICT infrastructure
improvement; the model further examines how these BPR
project implementation
components would affect BPR project outcomes (operational
quality improvement,
H2
H3
H4
H5
H1
BPR Project Outcomes
- Operational quality improvement
- Organizational quality improvement
- Cost savings
- Productivity
BPR Project Implementation
Components
- Change management
- Process redesign
- ICTI improvement
Top
Management
Support
BPR
Project
Success Figure 1.
Research model

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Business process
redesign project
success
organizational quality improvement, cost savings, and
productivity) and ultimately
BPR project success.
3. Research methods and data analysis
3.1 Construct operationalization
Three constructs for modeling BPR project implementation were
created: change
management, process redesign, and ICTI improvement. Each
was modeled as a
second-order construct and each of their first-order dimensions
was operationalized as
a latent variable. Researchers (e.g. Jarvis et al., 2003;
Diamantopoulos et al., 2008; Petter
et al., 2007) advocate examining constructs carefully before
classifying them into
reflective or formative categories. Jarvis et al. (2003) and Petter
et al. (2007) proposed
criteria and decision rules on how to determine if a construct
should be modeled
as formative or reflective. All three of these constructs were
identified as formative
second-order and reflective first order constructs, based on their
recommended approach.
The construct of change management aims to assess the extent

to which a BPR
project utilizes change management practices. Three measures,
as suggested in the
literature, were developed to assess this construct: first, change
management at the
organizational level, to assess the impact of change management
on organizational
culture change and human resources system change (Al-Mashari
and Zairi, 1999);
second, change management at the employee level, to assess the
impact of change
management such as empowerment, communication and training
on employee
resistance (Grover and Jeong, 1995; Al-Mashari and Zairi,
1999); and third, change
management at the stakeholder level, to assess the impact of
change management on
stakeholder resistance and commitment (Oakland and Tanner,
2007; Paper and Chang,
2005). The items for measuring the three dimensions were
adapted from previous
studies (Ramirez et al., 2010; Al-Mashari and Zairi, 1999;
Grover and Jeong, 1995;
Oakland and Tanner, 2007; Paper and Chang, 2005), and their
dimensions were used as
indicators to create the super-ordinate construct. The change
management scale is
shown in Table I.
The process redesign construct assesses the extent to which
process redesign
practices were used in a BPR project. This study adopted the
two dimensions of
process redesign (Attaran, 2003): technical redesign and social
redesign. Technical
redesign (PR_T) is used to redesign the allocation of the

process workload; social
redesign (PR_S) is used to redesign the allocation of personnel
workloads. The items
for measuring the two dimensions were adapted from Mansar
and Reijers’ studies
(Mansar and Reijers, 2005). The process redesign scale is
shown in Table II.
Dimensions Item ID Measurement
Organizational level CM_OL1 Reward/motivation and
compensation systems
CM_OL2 Human resource policies
CM_OL3 Organization’s receptivity to change
CM_OL4 An effective culture for organizational change
Employee level CM_EL1 Communicate the reasons for change
to employees
CM_EL2 Empower relevant employees for change
CM_EL3 Provide adequate training for relevant employees
Stakeholder level CM_SL1 Communicate vision to stakeholders
CM_SL2 Solicit feedback from stakeholders
Table I.
Change management
construct and
measurements
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In this study, ICTI improvement assessed the extent to which a
company’s ICTI
capabilities have been improved through a BPR project. The
four dimensions of
ICTI improvement (network communications, data integration,
training, and, facilities
and management) and their corresponding items as proposed by
Law and Ngai (2007)
were adopted to create the super-ordinate construct. The ICTI
improvement scale is
shown in Table III.
TMS, a well developed construct in the IS literature, was
operationalized as the
extent to which top management provided support and
commitment to a BPR project.
Five items were chosen and minor modifications were made to
fit the context of BPR
projects (see Appendix 1), including top management’s
understanding and support of
the BPR project, as well as top management’s funding and
communication support
(Grover and Jeong, 1995).
BPR project success was measured from two perspectives. The
first perspective
was an overall perception of success (Grover and Jeong, 1995).
A two-item scale was
used to assess this perspective of success regarding to the
achievements from a BPR
project (see Appendix 1). The second was a goal-specific
perception (Altinkemer,
2011; Raymond et al., 1998). The four facets of BPR project
outcomes adopted
from (Raymond et al., 1998) were used to measure goal-specific
success in this

study because it is relevant to this study. These included
operational quality
improvement (OpQI), organizational quality improvement
(OrQI), cost savings (CS),
and productivity (PROD).
Technical redesign PR_T1 Eliminating unnecessary tasks
PR_T2 Combining or dividing tasks
PR_T3 Re-sequencing tasks in processes
PR_T4 Paralleling tasks
PR_T5 Integrating business processes
Social redesign PR_S1 Empowering workers with more
decision-making authority
PR_S2 Assigning workers to perform as many steps as possible
for
single orders
PR_S3 Making human resources more specialized or more
generalized
PR_S4 Minimizing the number of departments, groups, and
persons
Table II.
Process redesign construct
and measurements
Network communications ICTII_NC1 Improving networks
linked with suppliers
ICTII_NC2 Improving networks linked with customers

Data integration ICTII_DI1 Improving data sharing across the
company
ICTII_DI2 Reducing/eliminating data duplication
ICTII_DI3 Improving standardization of data element
definitions
Training ICTII_TR1 Improving IT training programs
ICTII_TR2 Improving user training
ICTII_TR3 Improving IT personnel training
IT facilities and management ICTII_FM1 Increasing capacity of
servers
ICTII_FM2 Reducing regular preventive maintenance down
time
ICTII_FM3 Increasing expertise to manage IT facilities
ICTII_FM4 Increasing satisfaction with IT services
ICTII_FM5 Improving IT administration standards and
procedures
Table III.
ICTI improvement
construct and
measurements
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success
The measurements for TMS and BPR project success, as well as
for the three BPR

project implementation components, are listed in the
questionnaire that was used (see
Appendix 1).
3.2 Content validity test before data collection
Before data collection, two steps were taken to ensure content
validity. The first
step was a Q-Sorting test on the three formative constructs. The
goal of Q-sorting
was to verify the dimensions or categories of the items that
were drawn from the
literature. Hence, a one-round Q-Sort was sufficient for this
purpose. Five participants
knowledgeable in the IS area, but with no prior knowledge of
this study, were asked
to examine a series of descriptive items that would be used for
each of the constructs
and to place each of them into one of several categories
composed of the formative
constructs. The measures and constructs theoretically identified
by the researchers
fully matched the results of the Q-sort, after clarifying a
misunderstanding of the only
unmatched category (social-based process redesign).
The second step used an expert panel. The instrument was
examined by one
academic researcher and two industrial experts for its content
validity and was
improved according to their opinions.
3.3 Data collection methods
The data collection process was approved by the Research
Ethics Board of a major
university. Considering that small-sized companies may not
have well-defined business

processes or their business processes may not heavily rely on IT
or ICTI solutions,
data collection was limited to medium and large companies
(each with 100 or more
employees) in the USA and Canada that had undertaken a BPR
project in the past three
years. All respondents had participated in at least one such BPR
project.
The researchers used an internet panel of potential respondents,
chosen from the
existing database of a commercial survey agency. In total, 21
percent of the targeted
business professionals (294 out of 1,481) qualified under the
requirements indicated
above. Among the 294 qualified business professionals, 155
completed the survey,
yielding an overall response rate of 52 percent. Ten of the 155
cases were dropped
because participants failed to complete a number of the scales.
For missing data in the
remaining 145 cases, Little’s MCAR test (Little and Rubin,
2002) showed that these
values were missing completely at random (Little’s MCAR test:
w2¼7.358, Sig.¼
0.393). The missing data were replaced by mean values.
Table IV provides demographics of industry distributions and
respondent department
distributions.
3.4 Analysis method
SmartPLS 2.0 (Ringle et al., 2005) was used to analyze the data,
as it allows latent
constructs to be modeled either as formative or reflective
indicators as was the case

with this study’s data, and it is appropriate for exploratory
studies (Chin, 1998).
Because the model contains three second-order variables, the
researchers created
super-ordinate second-order constructs using factor scores for
the first-order construct
(Chin et al., 2003).
PLS works well with smaller sample sizes. The most frequently
used rule for
minimum sample size in PLS was proposed by Chin (1998, p.
311): “one simply has to
look at the arrow scheme and find the largest of two
possibilities: (a) the block with the
largest number of formative indicators (i.e. largest measurement
equation); or (b) the
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dependent LV with the largest number of independent LVs
impacting it (i.e. largest
structural equation) [y] the sample size requirement would be
10 times either (a) or
(b), whichever is the greater.”
The research model in this study involves three formative
constructs: change
management, process redesign, and ICTI improvement, which
have 3, 2, and 4
formative indicators, respectively. As for the structural
equation, the dependent LV

with the largest number of independent LVs impacting it is
overall success, which has
four paths leading into it. Therefore, the minimum sample size
requirement for this
study is 10 � 4, or 40.
Another rule that should be considered for sample size is that
there is a need for
doing a principal components factor analysis on the indicators
for all the constructs
for an exploratory study such as this. Everitt (1975)
recommended that the proper
case-to-indicator ratio range for PCA should be at least 10. The
largest construct
considered, i.e. ICTI improvement, has 13 indicators, although
they are divided into
four dimensions. Therefore, according to this rule, the minimum
sample size
requirement is 13 � 10, or 130. The number of valid cases
collected was145, meeting
this criterion.
4. Analysis and results
4.1 Validity and reliability tests
For reflective constructs, their convergent validity, discriminant
validity, and reliability
were examined through the measurement model.
Convergent validity for reflective constructs is assumed when
the loadings of their
items are above 0.7 and are significant at the 0.05 level (Gefen
and Straub, 2005).
The results showed that all the item loadings were above 0.7,
except for two items:
OpQI1 from the operational quality improvement construct
(0.668) and CS4 from the

cost savings construct (0.655). These two items were removed
from further analysis
and PLS was rerun. Once done, the item loadings were all above
0.7 and significant at
the 0.001 level. It can be concluded that convergent validity for
the reflective constructs
was shown.
To test discriminant validity, we examined the table of item
loadings and cross
loadings (see Appendix 2) and the table of correlations among
constructs (see Table V).
The results showed that all item loadings for the constructs they
were intended to
n % n %
Industry Department
Financial 23 15.8 Human resources 7 4.8
Healthcare and Pharmaceutical 17 11.7 Information
Technology/systems 42 29.0
Manufacturing 16 11.0 Sales and/or marketing 24 16.6
Government 15 10.3 Production and/or manufacturing 19 13.1
Entertainment and others 12 8.3 Customer services 20 13.8
IT 10 6.9 Finance 14 9.7
Telecommunication 10 6.9 Management 9 6.2
Retail and Wholesale 7 4.8 Other 10 6.9
Education 6 4.1
Transportation 6 4.1
Food 5 3.4
Other 18 12.6
Total 145 100 Total 145 100
Table IV.
Industry distribution and
respondents’ department

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measure were above 0.7, and that they loaded less on the other
constructs. The square
roots of the average variance extracted (AVE) are shown as
shaded results on the
diagonal of Table V for all the reflective constructs. These
results were all above 0.7
(note that AVE is not applicable for the formative constructs),
and exceeded that
construct’s correlations with other constructs. Hence, the
constructs were shown to
have adequate discriminant validity.
Composite reliability coefficients for all the reflective
constructs in the PLS model
were above 0.7 (see the reliability column in Table V). Hence,
they passed the reliability
test (Gefen and Straub, 2005).
For the three formative constructs, the researchers first tested
their validity by
examining their item weightings. As shown in Table VI, all the
item weights, except for
ICTII_FM, were significant. A decision to remove this
dimension (i.e. IT facilities and
management) from the ICTI improvement construct was made
because its original

literature source (Law and Ngai, 2007) was not very clear about
this dimension in any
case. After removing this dimension, PLS was rerun.
Second, multicollinearity was checked in the measures of the
formative constructs,
and the variance inflation factors (VIF) values for all the
formative indicators
ranged from 1.408 to 3.119, below the strict cut-off threshold of
3.3 (Petter et al., 2007).
Correlations among the formative indicators were then
examined for reliability.
Correlations between the formative indicators of ICTI
improvement were 0.314, 0.325,
0.480 ( po0.01 in each case); those for change management were
0.548, 0.712, 0.674
( po0.01 in each case); and for process redesign it was 0.587 (
po0.01). The results
Reliability (1) (2) (3) (4) (5) (6)
(1) Top management support 0.916 0.829
(2) Operational quality improvement 0.97 0.484*** 0.974
(3) Organizational quality improvement 0.886 0.449*** 0.452
0.814
(4) Cost savings 0.890 0.546*** 0.600 0.636 0.854
(5) Productivity 0.893 0.399*** 0.634 0.596 0.615 0.822
(6) BPR project success 0.981 0.626*** 0.620** 0.667***
0.791*** 0.616 0.981
Notes: The italic numbers in the diagonal row are square roots
of the average variance extracted.
*po0.05; **po0.01; ***po0.001
Table V.
Correlations among

constructs
Construct Items Weights t-value p-value
Change management CM_EL 0.592 4.548 ***
CM_OL 0.236 2.235 *
CM_SL 0.329 2.863 **
Process redesign PR_T 0.673 5.754 ***
PR_S 0.439 3.420 ***
ICTI improvement ICTII_NC 0.361 3.125 **
ICTII_DI 0.466 4.340 ***
ICTII_TR 0.473 5.143 ***
ICTII_FM 0.005 0.0397 ns
Notes: ns, not significant. *po0.05; **po0.01; ***po0.001
Table VI.
Weights of the indicator
variables for formative
constructs
782
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20,5
indicate that the formative indicators belonged to their own sets
respectively, even if
they do not need to be correlated with one another (Pavlou and
Sawy, 2006).
4.2 Structural model assessment

At the same time as PLS analysis estimates the measurement
model, it also provides
estimates of the structural model, i.e. the relationships between
constructs or path
coefficients. In order to interpret their significance,
bootstrapping was run with 500
re-samples. The estimates of the resulting structural model are
shown in Figure 2.
The results show that most of the paths hypothesized (15 out of
19) were statistically
validated. Only four of them were not supported (as denoted in
the dashed lines
in Figure 2).
It is evident from Figure 2 that the model demonstrated
moderate to high explanatory
power. The R2 value for the BPR project success construct was
0.697 (i.e. it explained
69.7 percent of the variance in BPR project success). This is a
relatively good result for an
exploratory study such as this. The R2 values for the other
endogenous constructs
ranged from 0.167 to 0.511.
5. Discussion
5.1 Impact
As mentioned earlier, BPR project implementation itself has
previously seemed to be
regarded as a black box and few studies have focussed on
measuring and modeling
what organizations should do during project implementation
(Zellner, 2011, p. 1).
This study tries to open this black box and to explore inside the
BPR project
implementation process. By identifying three important BPR

components based on the STT, this study has created a
multivariate research model
0.237*
R 2 = 0.511
R 2 = 0.697
R 2 = 0.458Notes: *p< 0.05; **p< 0.01; ***p< 0.001
R 2 = 0.167
R 2 = 0.227
R 2 = 0.494
R 2 = 0.443
0.056
0.397***
0.236***
0.178*0.283*
0.275***
0.145
0.104
0.500***
0.476***

0.666***
0.409***
0.251*
0.355***
0.280*
0.439***
Productivity
BPR
Project
Success
Cost savings
OrQI
Top
Management
Support
Change
Management
Process
Redesign
ICTI
Improvement

0.245**
0.143
OpQI
R 2 = 0.374
Figure 2.
Path model with PLS
analysis results
783
Business process
redesign project
success
using formative construct techniques, and successfully tested
the three components.
The analysis results are discussed in the following.
This study provides conclusive evidence that change
management significantly
affects all four facets of BPR project outcomes (operational
quality improvement,
organizational quality improvement, cost savings, and
productivity). This means
that no matter which of these project outcomes are goals set by
managers, change
management is a significant determinant in achieving these

goals. This finding is
especially useful for companies who undertake BPR projects,
for example, during the
implementation of ERP systems. Many ERP implementers find
themselves having to
re-engineer their existing processes to fit the software they are
implementing. At the
same time, because of the major impact of change management
on BPR project
success, they should avoid overlooking change management
issues while
implementing specific systems, if they wish to achieve truly
successful change (Huq
et al., 2006).
The empirical results from this study also indicate that process
redesign has a
significant impact on organizational quality improvement, cost
savings, and productivity,
but not on operational quality improvement. The reason for this
may be that operational
quality emphasizes product quality and/or customer service
quality, while process
redesign practices aim to improve business processes through
task elimination or
combination, or downsizing by removing unnecessary people,
groups, or departments
from business processes.
Of interest, this study showed that ICTI improvement was
significantly associated
with operational and organizational quality improvements. This
is probably because ICTI
improvement builds a convenient and fast communication
bridge among employees,
and between companies and customers, yielding improved

customer satisfaction and
better cooperation among employees (Bhatt, 2000; Law and
Ngai, 2007).
The non-significant influence of ICTI improvement on
productivity and cost
savings is perhaps not surprising. One study conducted by
Terziovski et al. (2003) also
found that there was no significant relationship between the
increased use of information
technology and process cycle time reduction. One implication
from this result is that
managers must reengineer their core processes from a customer
perspective (Terziovski
et al., 2003). Three more implications concerning productivity
and cost savings can be
suggested as a result of this study. First, emphasizing
productivity and cost savings
through IT does not appear to be the focus of recent BPR
projects; instead, IT
development seems more focussed on improving organizational
quality and operational
quality within organizations and with customers. Second, it may
be that companies are
willing to spend money on ICTI for improving the quality of
customer service and the
quality of employee working life, but not necessarily for
improving productivity or
reducing costs. Third, there may be a time lag before the effects
of BPR projects could be
felt or seen. The reason of this point can be understood from the
results of a recent study
which show that some of the firm performance measures (e.g.
labor productivity,
financial ratios, and operational performance) improve in a
decreasing manner after

change implementation, and peak within two to ten years in
general (Altinkemer, 2011).
The results obtained from this study can provide useful
recommendations for
BPR practitioners. First, TMS plays an important role in
realizing all three BPR
project implementation components (i.e. change management,
process redesign, and
ICTI improvement).
Second, change management must be seriously planned and
comprehensively
carried out in order to achieve BPR project success. Change
management involves
784
BPMJ
20,5
three dimensions: organizational level, employee level, and
stakeholder level. At the
organizational level of change management, human resource
policies, reward and
compensation systems should be properly reviewed and revised.
An effective culture
for organizational change should be created to increase the
likelihood of success. With
respect to the employee level of change management, it is
essential to deal effectively
with employee resistance, through improved communication,
employee empowerment,
or effective training. The stakeholder level of change

management requires adequate
communication with stakeholders to solicit their opinions on
BPR projects.
Third, managers need to carefully define BPR project goals:
does this project aim at
cost savings, productivity, or other goals? Starting from the
defined project goal,
the implementation components can then be assigned
appropriate priorities. This is
especially important in planning a project with limited project
resources.
5.2 Limitations and future research
The main limitation of this study is its generalizability with
respect to company size
and organizational culture. The sample in this study was drawn
from medium- and
large-sized companies in Canada and the USA. Small
organizations have their own
distinct features such as superior flexibility, ability to reorient
themselves quickly,
capacity for rapid decision making, and proximity to their
markets (Raymond et al.,
1998). Company size needs to be considered in the explanation
of such a study. As for
organizational culture, this study controlled this variable by
limiting respondents to
Canada and US companies. A recent literature review of BPM
shows that culture is still
a widely under-researched topic in BPM ( Jan vom and Theresa,
2011). Therefore, it would
be very interesting to investigate BPR project implementations
in other countries where
the organizational working culture may be different (Martinsons
et al., 2009).

This study is the first BPR project implementation study to use
formative constructs
to measure relevant factors. A diligent literature search
screened feasible methods to
build and validate the three formative constructs. However,
more studies are needed in
order to improve our understanding of these constructs. For
example, the ICTI construct
needs to be improved. Law’s study (Law and Ngai, 2007) added
dimensions of facilities
and management (as defined in Section 3.1) to ICTI
improvement, but this study showed
this dimension was not an important contributor to ICTI
improvement. Hence, this
dimension of ICTI should be retested in future studies, so that
the domain specification
for ICTI improvement can be refined. Relevant studies in
defining and validating
dimensions of ICTI have been published recently (Fink and
Neumann, 2009; Sobol and
Klein, 2009), providing a better foundation for refining this
multidimensional construct.
Another limitation of this study concerns the sample size.
Although the sample
collected in this study was sufficient for PLS analysis, a larger
sample set would likely
generate more solid results.
6. Conclusions
The conclusions from our study are first, that STT has been
validated in the BPR project
implementation research context. The establishment of the BPR
model was based on the well-known aspects of STT, and

included the development of
three BPR project implementation components (i.e. change
management, process
redesign, and ICTI improvement). The results from analyzing
the research model
showed that the great majority of the variance in BPR project
measures of success
(69.7 percent) was explained through factors based on STT.
This provides a foundation
for utilizing STT in future BPR project research.
785
Business process
redesign project
success
Second, to the best of the researchers’ knowledge, this is the
first study to model
certain activities related to BPR project implementation as
formative constructs,
rather than with traditional reflective constructs. As such, this
study significantly
advances BPR project research. Formative indicators are often
neglected despite their
appropriateness in many instances, and a high percentage of
latent constructs have
therefore been found to be incorrectly modeled in many
research areas (e.g. marketing,
management information systems, organizational behavior, etc.)
( Jarvis et al., 2003;
Petter et al., 2007; Diamantopoulos et al., 2008). This
exploratory study successfully

built and validated three formative constructs for BPR project
implementation
components (i.e. change management, process redesign, and
ICTI improvement),
following existing guidelines for formative construct
development ( Jarvis et al., 2003;
Petter et al., 2007; Diamantopoulos et al., 2008).
Finally, a major achievement from this study is its contribution
to modeling BPR
project implementation components, based on various
dimensions that have been
identified from the existing literature, and the development and
validation of sound
constructs that could be used in structural equation modeling
(SEM) methodologies.
By achieving this, progress in BPR project research has
advanced significantly in the
utilization of quantitative methodologies to validate appropriate
research models in this
field, and to offer better generalizability of results than that
found in the existing literature.
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Appendix 1. Questionnaire for BPR Study
Have you participated in any BPR projects within the past 3
years?
(1) Yes-continue the survey.
(2) No-show the message: “For this survey we are seeking the
opinions of people in a
different target group than your own.” and exit.
How many people does the company employ worldwide?
(1) 500 or more employees-continue the survey.
(2) 100-499 employees-continue the survey.
(3) Fewer than 100 employees-show the message: “For this
survey we are seeking the
opinions of people in a different target group than your own.”
and exit.
Please recall ONE of the BPR projects in your company that
you have participated in,
and answer all of the following questions based on your
perceptions of this BPR project. There is

no right or wrong answer to any of these questions.
The main location in which the BPR project was undertaken was
in:
(1) United States
(2) Canada
Which department were you in at the time the BPR project was
undertaken?
(1) Human Resources
(2) Information Technology/Information Systems
(3) Sales and/or Marketing
(4) Production and/or Manufacturing
(5) Customer Services
(6) Finance
(7) Management
(8) Other (Please specify):
Industry: ______
(A 7-item Likert-type scale ranging from strongly disagree to
strongly agree was used
for all of the following statements.)
How would you evaluate top management support for the BPR
project?
a) Top management was favorable in the implementatio n of the
BPR project.
b) Top management was able to understand the concepts of the
BPR project.
c) Top management considered the BPR project to be important
to the company.
d) Top management effectively communicated its support for
the BPR project.
e) Top management provided adequate funding for the project.

How would you evaluate the following change management
items regarding your BPR project?
a) The BPR project properly reviewed and revised
reward/motivation and compensation systems.
b) The BPR project management made necessary changes in
human resource policies as a
result of the BPR implementation.
c) The BPR project stimulated the organization’s receptivity to
change.
d) The BPR project created an effective culture for
organizational change.
789
Business process
redesign project
success
e) The BPR project management effectively communicated the
reasons for change to
management and employees.
f) The BPR project management properly empowered relevant
employees.
g) The BPR project management provided adequate training for
personnel affected by the
redesigned processes.
h) The vision of the BPR project was communicated well to all
the stakeholders.
i) All the stakeholders were solicited for feedback on the
project.

j) BPR Strategic Initiatives.
Were the following process redesigns involved in your BPR
project?
a) The BPR project involved eliminating unnecessary tasks from
business processes.
b) The BPR project involved combining small tasks into
composite tasks or dividing large
tasks into workable smaller tasks.
c) The BPR project involved moving and resequencing tasks to
more appropriate places in
the processes.
d) The BPR project involved arranging tasks to be executed in
parallel.
e) The BPR project involved integration of business processes
with those of customers or
suppliers.
f) The BPR project involved empowering workers with more
decision-making authority.
g) The BPR project involved assigning workers to perform as
many steps as possible for
single orders.
h) The BPR project involved making human resources more
specialized or more generalized.
i) The BPR project involved minimizing the number of
departments, groups, and persons
involved in business processes.
How would you evaluate the improvement of the ICT
(Information and Communication
Technology) infrastructure capabilities in your company as a

result of the BPR project?
a) Networks which link the company and its main suppliers
were improved as a result of the
BPR project.
b) Networks which link the company and its main customers
were improved as a result of the
BPR project.
c) Information and data sharing across the company was
improved as a result of the
BPR project.
d) Duplication of data was reduced or eliminated as a result of
the BPR project.
e) The standardization of data element definitions across the
company was improved as
a result of the BPR project.
f) The company improved its IT training programs through the
BPR project.
g) Training of users was adequate through the BPR project.
h) Training of IT personnel was adequate through the BPR
project.
i) Company servers were increased in capacity as a result of the
BPR project.
j) Regular preventive maintenance down time was reduced as a
result of the BPR project.
k) The company had increased expertise to manage its IT
facilities after the BPR project.
l) Users were more satisfied with IT services as a result of the
BPR project.
m) IT administration standards and procedures were improved
as a result of the BPR project.

How would you evaluate the extent of achieved outcomes of the
BPR project for your company?
OpQI
a) The BPR project achieved product quality improvement.
b) The BPR project achieved customer services improvement.
c) The BPR project achieved customer satisfaction
improvement.
OrQI
a) The BPR project resulted in less managerial hierarchy.
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20,5
b) The BPR project reduced bureaucracy.
c) The BPR project improved internal users’ satisfaction.
d) The BPR project improved communication within the
company.
Cost Savings
a) The BPR project achieved a good return on investment.
b) The BPR project improved company profits.
c) The BPR project saved on operational costs.
d) The BPR project saved on personnel costs.
Productivity
a) The BPR project achieved more units produced or more

customers served per unit time.
b) The BPR project achieved fewer delays in production and/or
services.
c) The BPR project achieved shortened cycle time in production
and/or customer services.
d) The BPR project achieved lower error rates in production
and/or customer services.
Overall Success
a) Overall, this BPR project was successful.
b) Overall, this BPR project achieved favorable outcomes.
Thank you for your participation in our survey.
Appendix 2
TMS OpQI OrQI CS PROD Success CM PR ICTI
TS1 0.851 0.397 0.300 0.394 0.245 0.464 0.487 0.293 0.339
TS2 0.836 0.491 0.481 0.527 0.394 0.633 0.570 0.359 0.387
TS3 0.825 0.319 0.263 0.373 0.229 0.406 0.455 0.298 0.345
TS4 0.868 0.514 0.451 0.526 0.442 0.594 0.634 0.424 0.452
TS5 0.763 0.379 0.324 0.364 0.297 0.460 0.560 0.244 0.433
OpQI2 0.471 0.976 0.453 0.586 0.621 0.632 0.540 0.398 0.554
OpQI3 0.466 0.972 0.426 0.601 0.612 0.573 0.517 0.357 0.531
OrQI1 0.273 0.311 0.754 0.448 0.379 0.365 0.347 0.485 0.405
OrQI2 0.281 0.324 0.811 0.495 0.473 0.437 0.451 0.552 0.468
OrQI3 0.449 0.469 0.851 0.652 0.540 0.717 0.583 0.409 0.546
OrQI4 0.403 0.458 0.836 0.520 0.518 0.575 0.640 0.382 0.589
CS1 0.503 0.554 0.585 0.883 0.545 0.753 0.573 0.456 0.528
CS2 0.368 0.491 0.434 0.777 0.442 0.492 0.453 0.407 0.388
CS3 0.504 0.557 0.589 0.898 0.574 0.742 0.609 0.486 0.522
PROD1 0.234 0.601 0.319 0.513 0.754 0.407 0.340 0.446 0.382
PROD2 0.322 0.531 0.487 0.499 0.841 0.518 0.442 0.476 0.459
PROD3 0.344 0.598 0.497 0.565 0.870 0.511 0.457 0.464 0.503
PROD4 0.379 0.447 0.618 0.564 0.820 0.572 0.530 0.516 0.465

Success1 0.5935 0.642 0.643 0.7359 0.585 0.981 0.699 0.431
0.580
Success2 0.6286 0.668 0.665 0.7546 0.623 0.982 0.730 0.462
0.657
CM_EL 0.659 0.548 0.584 0.614 0.510 0.707 0.957 0.406 0.634
CM_OL 0.416 0.501 0.557 0.539 0.422 0.525 0.773 0.430 0.591
CM_SL 0.578 0.466 0.550 0.552 0.486 0.637 0.858 0.406 0.579
PR_T 0.405 0.482 0.521 0.530 0.565 0.479 0.462 0.937 0.555
PR_S 0.308 0.398 0.478 0.528 0.518 0.379 0.417 0.843 0.514
ICTI_NC 0.248 0.502 0.311 0.354 0.429 0.340 0.372 0.401
0.661
ICTI_DI 0.393 0.401 0.564 0.492 0.426 0.568 0.522 0.480 0.813
ICTI_TR 0.424 0.424 0.528 0.483 0.423 0.510 0.647 0.407
0.814
ICTI_FM 0.317 0.286 0.481 0.347 0.448 0.302 0.356 0.603
0.678
Table AI.
Item loadings and
cross-loadings
791
Business process
redesign project
success
About the authors
Dr Junlian Xiang is currently an Assistant Professor at the Ted
Rogers School of Business,
Ryerson University. She obtained her PhD in Information

systems from the DeGroote School of
Business, McMaster University. Her research interests lie in
business process redesign, change
management and ICT infrastructure. Dr Junlian Xiang is the
corresponding author and can be
contacted at: [email protected]
Dr Norm Archer is a Professor Emeritus in the DeGroote School
of Business at McMaster
University. In his research he is active, in collaboration with his
graduate students and
colleagues, in the study of organizational problems relating to
the implementation of eBusiness
approaches in health, business, and government organizations,
and the resulting impacts on
processes, employees, customers, and suppliers. He has
published over 100 refereed journal and
conference papers.
Dr Brian Detlor is an Associate Professor of Information
Systems at the DeGroote School of
Business, McMaster University in Hamilton, Ontario, Canada,
and the Chair of the McMaster
Research Ethics Board. He specializes and conducts research on
digital literacy, electronic
government, web information seeking, and web site adoption
and use.
To purchase reprints of this article please e-mail:
[email protected]
Or visit our web site for further details:
www.emeraldinsight.com/reprints
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BPMJ
20,5

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