Keywords: Business Process Re-engineering, Delivering
Speed, Service Organization.
1. BACKGROUND
Today’s organizations are generically different in design
compared to some years back. Organizations have been changing from time to time
due to changes in technology and customers’ demands (HAMMER & CHAMPY, 1993;
BROERSMA, 1997; HESSON, 2007; BANHAM, 2010). The advancement in new technology
forces organizations to modernize their processes, thereby fostering their
competitive advantages (LAUDON & LAUDON, 2006). Also, the customers’
demands have been the factor that causes organization to change. Organizational
failure to meet customers’ demand and/or expectations forces customers to shift
to other service providers (HEIZER & RENDER, 2011). Therefore,
organizations have been working hard to improve their business processes in
order to improve or maintain their services for retaining and/or attracting
more customers.
In this regard, organizations have to re-invent their
business processes. There are several techniques that can be used by
organizations to reinvent their business processes. The techniques include Six
Sigma, Lean, Total Quality Management (TQM) and Business Process Re-engineering
(BPR), to mention the few (SLACK, et al., 2007). Among these techniques, BPR is
considered as the most appropriate in today’s business environment because it
improves organizational performance (OP) (HAMMER & CHAMPY, 1993).
BPR
was introduced in early 1990, earlier in private business sector and later
in the public business sector to help organizations improve OP (JOHANSSON,
et al., 1993). In U.S, BPR was introduced in nineteenth century when division of
labour didn’t work anymore. Thus, BPR substituted division of labour approach
to business operations. In many countries, organizations adopted BPR technique
in order to improve business processes for improved OP; often through reduced
cost, improved quality and customer services. The other dimensions of OP that
are associated with BPR are speed, process efficiency, effectiveness and
productivity (HAMMER & CHAMPY 1993; CARTER,
1995; MUTHU, et al., 1999).
According
to Adeyemi and Aremu (2008), BPR became useful weapon for organizations that
seek improvement in current OP. For instance, mechanizing business processes
removes and/or combines some business processes hitherto done by workers, and
the net effect is reduced number of employees and reduced operational costs (MAUREEN,
et al., 1995; HARTIGH & SEGVELD, 2011; WÖLFL, 2011; GUMMESSON, 1998).
BPR technique focuses on how work is organized presently,
not how it had been done for the past years, given the today’s technologies and
demand of customers (BROERSMA, 1997; HESSON, 2007; BANHAM, 2010). Furthermore,
the today’s competitive environment compels organizations to re-engineer their
business processes to effect perfect service delivering for customer
satisfaction (MOTHOBI, 2002). For sure, discovery of the BPR technique has been
of great importance to organizations.
Before the
emergency of BPR, organizations divided works into small and simple tasks. This
led the structure of organizations becoming functional in order to manage the
divided works. The functional structures later encountered operational
problems, especially when local competitive environment changed beyond what
could be recognized (CHEN, 2001). The operational problems, mainly planning and
budgeting, ultimately led to the end of the division of works and/or labour
strategy. It forced organizations to look for other strategies that will enable
them to improve their OP.
In
addition to the operational problems, present organizations face competition
from the global business environment and the complexity of customers’ tastes.
While technological advancement logically leads to competitive global business,
awareness and education on consumerism leads to complexity of customers’
tastes. Therefore, organizations are forced to improve their business processes
in order to cope with business competition while meeting customers’ demands, need
and desire (HEIZER & RENDER, 2011; HAMMER, 1990; LAUDON & LAUDON, 2006).
Service organizations play
an important role in both social and economic development of a country. For
instance, service industry in Tanzania accounts for about 50% in GDP (CIA, 2013).
Therefore, the growth and sustainability of service industry is vital since it
has significance contribution to economy. Due to the nature of business processes and the demand of customers,
service organizations are labour intensive compared to manufacturing
organizations (LEVITT, 1981). In that case, a proper re-engineering of business
processes in service industry need to be undertaken in order to reduce labour
costs for improved OP such as timely
service delivery to customers., service quality and reduction
operational cost (XIAOLI, 2011).
In reducing operational costs and improving delivering
speed, BPR supports the linking of customers with service organizations through
improving business processes; often by
adjusting, combining and networking business processes (HESSON, 2007). The contribution of BPR in increased/improved
productivity and service quality and in lowered operational cost and cycle time
is on the rise for many organizations (COVERT, 1997; ADEYEMI & AREMU, 2008;
XIAOLI, 2011). Thus, BPR brings
customer satisfaction and strengthen the domestic and international market
competition among service organizations.
2. PROBLEM STATEMENT
According to Al-Mashara,
et al (2001), most organizations, knowingly or otherwise, are involved in BPR.
The pressure for survival in the market and the need to prevent complacency has
prompted them to adapt BPR technique. Also, the motivation of adapting BPR
technique comes from the desire of organizations to close competitive gaps and
achieving superior performance standards.
Despite the potentiality and
popularity of BPR, organizations adopt the technique in an ad-hoc manner. Furthermore,
the mixed performance outcomes for organizations that have implemented BPR
prompts to conclude that there is still a gap in knowledge regarding the
influence of BPR on delivering speed (O’NEILL & SOHAL, 1999). Therefore,
the main objective of the current paper is to assess and explain the effect of
BPR on delivering speed of service organizations in Tanzania.
More specifically, the
current paper aims at assessing the influence of BPR on delivering speed in
service organizations. The research question to be answered is; what is the
effect of BPR on delivering speed in service organizations? The tentative
answer to this probing question in form of a null hypothesis to be tested is:
Ho1: BPR has no correlation
with delivering speed in service organizations.
3. LITERATURE REVIEW
3.1.
Business
Process Re-engineering
Business
process re-engineering is a process design, process management, and process
innovation. Re-engineering involves revising organizational processes. That
means, designing the core business process instead of analyzing the current
one. It involves re-configuration of works to serve customers better.
Re-engineering forces organizations to challenge the way they run and redesign
organizations around the desired outcomes rather than functions or departments.
It also forces a new way of thinking (ATTARAN, 2004).
BPR is a
technique about dramatic process improvement. According to Chen (2001), BPR is
known by many names, such as, core process redesign, new industrial engineering
and working smarter. All of them imply the same concept which focuses on
integrating both business process redesign and IT use to support the
re-engineering work. According to Hammer and Champy (1993), BPR is the fundamental rethinking and radical
redesign of business processes to achieve dramatic improvements in critical
contemporary measures of performance, such as cost, quality, service, and speed.
In
any organization, business processes are characterized by three elements:
inputs (data, such as customer inquiries or materials), processes (where
customers or materials go through several stages which may be time and money
consuming) and output (delivery of expected results). In this system, a
problematic part is processing of what is required by a customer. To deliver
what is required by customers on time, organizations need to perfect their
business processes. In this case, BPR is the technique that can be used to
perfect the business processes. In the intervention, BPR involves discovering
how business processes currently operates, how to redesign these processes to
eliminate the wasted or redundant effort and improve efficiency and how to
implement the process change in order to gain competitiveness (CHEN, 2001).
According to Sherwood-Smith (1994) as quoted in Chen (2001), BPR is seeking to
invent new ways of organizing tasks, people and redesigning IT systems so that
processes support the organization to realize its goals.
3.2.
Activities
of Business Process Re-engineering
From
literature review, it has been identified that, BPR entails activities of
business processes renovation, automation and networking. The activities of BPR
are presented and discussed as follows:-
Business
process renovation – It is the redesigning of business processes for the
purpose of improving business operations. Renovation process involves
streamlining key business processes, making of succession or continuity of
progression of work activities and sometimes combining other business processes
(SIMON, 1994; COVERT, 1997; ZYGIARIS, 2000; SHIN & JEMELLA, 2002; DEBELA,
2009). Before the automation, organizations need to renovate their business
processes in order to avoid automating non-value adding business processes. For
instance, Hammer (1990) suggested that “in
order to achieve significant benefits, it is not sufficient to computerize the
old ways, but a fundamental redesign of the core business processes is
necessary”.
The fundamental redesign of the core
business process enable the organization renovate business process by
identifying which business processes are redundant and can be removed, grouping
similar activities together, replacing old machines with new ones, keeping gangways
clear and keeping business sections with high frequency of to-from movement
close together (AL-MASHARA et al., 2001; MILE,
et al., 2002; MAGUTU, et al., 2010).
Furthermore, renovation brings about the sequencing of
works in a natural way which leads to less rework of tasks, which has been a
major source of delays in organizations (BROERSMA, 1997).
Business
process automation – It is the mechanization of business processes in
order to improve efficiency of the process by using ICT (SHIN & JEMELLA,
2002; DEBELA, 2009). IT plays a major role in BPR as it provides processes
automation. It allows the business to be conducted in different locations and
permits quicker delivery to customers and support rapid service provision and
paperless transactions. In general it allows an efficient and effective change
in the manner in which work is performed (ZYGIARIS, 2000). According
to Hammer (1990), the computerization is the use of IT in order to automate the
renovated business processes. Automation involves the use of IT, the
allocating of customer information from the database, facilitation of
information flow and programming a device or machine to function without frequent interaction of an operator (MILE, et al., 2002, HE, 2005).
Business
process networking – It is the linking
of activities/customers inside/outside the section/organization to improve
coordination by using IT. According to Zygiaris (2000) in the 1990s when telecommunication technologies were becoming abundant
and low costing, BPR was becoming a world-wide applicable managing technique
for business upgrade, enabled by the technology. Employees can easily operate
as a team using intranet/extranets, workflow and groupware applications and
eliminating distances. We can work together even though we are located in
different places. In this case, the
application of IT eases commutation (AL-MASHARA, et al., 2001; ATTARAN, 2004; HE,
2005); facilitate accessibility of organizational information (HE, 2005) and
linking managers/sections to different sections (HE, 2005). In this sense, IT
is enabler of BPR and improves competitive position of an organization (CHEN,
2001; SUNGAU & MSANJILA, 2012).
According to Hammer (1990), the
computerization is the use of IT in order to network the renovated business
processes. The computerization involves the networking different sections and
machines. However, the networking involves the linking different sections or
machines which have been re-engineered. The linking involves the enabling
communication, access to information and connects mangers to different sections
(CHEN, 2001; AL-MASHARA, et al., 2001; HE, 2005).
3.3.
Delivering
speed
Speed
is an element of timeliness (MAGUTU, et
al., 2010). Speed is a competitive dimension that enables one to make
the desired product or provide a service very quickly. OP is improved when the
duration taken for a customer to receive a product/service since the
requisition has been minimized/shortened (JONES, et al., 1997; CONVERT, 1997; SLACK, et al., 2007). Customers can
judge the organizational service as good or bad depending on the time spent
during consuming a service at an organization. In this regard, organizations
have to make sure that their business processes are effective enough in order
to provide services that delight their customers.
3.4.
Business
process re-engineering and delivering speed
From
literature review, it has been identified that BPR is the technique that
enables organizations to improve business processes. The improved business
processes facilitated organizations to minimize the time taken to service a
customer (SLACK, et al., 2007; HEIZER & RENDER, 2011). By so doing, BPR
enables the service organization to improve its service delivering speed (CONVERT, 1997; ATTARAN & WOOD,
1999; GUNASEKARAN, et al., 2000).
In improving service delivering speed, BPR plays
important roles of making succession or continuity of progression of work
activities (SHIN & JEMELLA; DEBELA, 2009), automating business processes
(HAMMER, 1990; LAUDON & LAUDON; 2006), keeping the sections with high to-from
movement close (AL-MASHARA, et al., 2001; TERZIOVSKI, et al., 2002; MAGUTU, et
al., 2010), linking different section which are far apart (ZYGIARIS, 2000) and
facilitating the communication between employees or employees and customers
(AL-MASHARA, et al., 2001; ATTARAN, 2004; HE, 2005).
In any BPR project, technology plays an important role in
supporting BPR. Among other roles, technology allows the rapid development of
various ready-to use best-practice templates that suits most needed business
processes, automate business processes, linking section and facilitates the
smooth flow of information between sections to mention few. All this shortens
the transition phase and minimizes the impact and duration of transition, and
so accelerates the time to benefit, till reaching the quality levels (SUNGAU
& MSANJILA, 2012).
Furthermore, BPR improves service
quality via delivering speed, such that BPR improves delivering speed (JONES,
et al., 1997; SLACK, et al., 2007) by shortening
cycle time in serving a customer, minimizing delays in serving a customer,
speed up communication, fastening decision making and shortening the period
taken to deliver a service since its request (AL-MASHARA, et al., 2001).
The above reviewed literature on BPR
and delivering speed enables to settle on a conceptual framework that was
subjected to empirical investigation. The framework describes the relationship
between BPR as exogenous construct and delivering speed as endogenous
construct. Figure 1 below summarizes the conceptual framework of the study.
|
Figure 1: Conceptual framework Source: Literature review |
Based on the literature review and
the above conceptual framework, an operational and/or statistical model in
linear form that guided the study is:
One null hypothesis was considered relevant for this
study; HO1: BPR has no
correlation with delivering speed in service organizations. The
corresponding statistical or operational null and alternative hypothesis was:
4. METHODOLOGY
4.1.
Justification of paradigm and methodology: This study has used a positivist paradigm in order
to generate hypothesis that are empirically tested. In this study, firstly,
intensive literature review was undertaken in order to narrow the gap between
the conceptual and research languages (NDUNGURU, 2007). The second step was to
collect and analyze data from survey. Thirdly, the structural equation modeling
of the surveyed data was formulated with both observable and unobservable
construct to study the interdependence of constructs. The constructs were
studied by using multi – items scales which were total aggregated to observed
and latent constructs (COFFMAN & MACCALLUM, 2005; VON DER HEIDT & SCOTT,
2007).
4.2.
Type
of Research Design: Since the study aimed at
determining the cause-effect relationship between exogenous construct and
endogenous construct, therefore, a cross-sectional survey design was used. The
design enabled the researchers to collect data at one point in time from many
study cases or units of inquiry (BURNS & BUSH, 2002). Furthermore the
design was selected because it enabled the researchers to collect large amount
of data from a sizeable population in a highly economical way (HAIR, et al.,
2003). Besides, the study was limited to service organizations that were known
to have practiced BPR in varying degrees and experiences. In controlling the
effect of intervening variables, the study used standardized regression
coefficient. The standardized regression coefficient has been used because even
if the ignored variables (intervening variables) are considered in the
analysis, they will not change the standardized regression coefficient of a
predictor on a criterion (KLINE, 2011).
4.3.
Constructs
and Operationalization of Constructs: Prior to designing the data collection questionnaire, the
operationalization of research constructs was very important (NDUNGURU, 2007).
The operationalization of constructs enabled to describe and define research
construct on which data were collected and pose specific item questions that
measured the research constructs that cannot be measured directly (HAIR, et
al., 2003) . Table 1 summarizes the study operationalization process adopted in
this study.
Table 1: Operationalization
of constructs
|
Construct |
Operationalization |
|
Renovation (Ren) |
The construct was measured using the
following items: - removing non-value adding activities (MAGUTU, et al.,
2010; MILE, et al., 2002; AL-MASHARA, et al., 2001), replacing old machines,
improvement of front and back offices (MILE, et al., 2002), keep clear
gangways and allocation of offices in
an organization |
|
Automation (Auto) |
The construct was measured using the
following items: - level of use of IT (MILE, et al., 2002), easy of locating
customers detail and IT infrastructures (MILE, et al., 2002; HE, 2005) |
|
Networking (Net) |
The construct was measured using the
following items: - easy of commutation (AL-MASHARA, et al., 2001; HE, 2005),
accessibility of organizational information
and linking managers to different sections (HE, 2005) |
|
Delivering Speed (Spe) |
The construct was measured using the
following items: - shortening of cycle time to serve a customer, reduction of
delays in serving customer, fastness of communication, fastness in decision
making and the period taken to deliver a service since its request (AL-MASHARA,
et al., 2001) |
Source: Constructed from literature review
4.4.
Study Area: The study area was Dar es Salaam city - Tanzania. The Dar es Salaam
city was selected because it is a major commercial city of Tanzania having head
offices.. The Dar es Salaam city enabled the researchers to collect enough data
for the study while minimizing data collection costs.
4.5.
The
study population: The target population
comprised of all service organizations in Tanzania. Furthermore, the study
targeted all service organizations which have been in operations for more than
two years because assessing OP for organizations with less than two years of
operations is illogical (OSTGAARD & BIRLEY, 1996). However, from the
collected data, it was identified that eight service organizations were
established after the year 2009. These service organizations were retained for
further analyses in order to meet the minimum sample size requirement for the
study depending on the number of parameters under the study (KLINE, 2005).
The sampled population included banking, public utility and pension fund
sectors. Other sectors were insurance, health services, airline and
communication. According to HAIR, et al (2003), the identified target
population took note of the study objectives and scope, access to the study
cases, familiarity with the topic of interest, time-frame and resource
availability. The selected sectors were considered on account of having
practiced and/or experienced BPR. The units of inquiry were service organizations;
however, managers were the respondents.
4.6. Sample
size and sampling method: A rule of thumb dictates
that if proportion of target population having characteristics of interest is the samples size of
is considered adequate
provided that
is the tolerated risk
for estimating the proportion (NDUNGURU, 2007). In this study a 10% risk was
considered acceptable and thus the 100 service organization constituted the
sample size. Empirically, similar studies used sample size of 80 (ADEYEMI &
AREMU, 2008), 110 (HE, 2005), 39 (MAGUTU, ET AL., 2008) and 70 (ALTINKEMER,
1998), to mention few.
Given the absence of a comprehensive sampling frame of service
organizations in Tanzania, quota sampling method was used to select
organizations. This non-probability method is a variant of stratified sampling
that is recommended in scientific studies in the absence of comprehensive
sampling frame (NDUNGURU, 2007). From the purposively selected sectors, specified
proportions of service organizations were purposively identified and selected
from a list of organizations obtained from National Bureau of Statistics (NBS)
(SAUNDERS, ET AL., 2005).
From the list of organizations, physical addresses of purposively selected
organizations guided the researchers to reach the sampled service
organizations. In total, 95 service organizations responded to the
questionnaires, being thirty (30) banking, three (3) public utility, three (3)
pension fund, eighteen (18) insurance, twenty eight (28) health, seven (7)
airline and six (6) telecommunication organizations.
4.7. Data
Collection Methods: Data were
collected by using questionnaires (5-point Likert scale) with items for each
construct. The questionnaire collected categorical data which during data
analysis were assumed to be interval scale data (PERRY, 1998). Section managers
were given questionnaires and they were asked to fill in. Questionnaires were
collected on agreed dates. Upon collecting a questionnaire, it was checked for
inconsistency and error.
4.8.
Data analysis: The data analysis included preliminary, descriptive
and inferential. Preliminary analysis was confined to response coding, data
cleaning and screening, and normality testing. In addition, reliability and
validity testing and factor analysis were also undertaken. Factor loadings of
at least 0.30 were considered for total aggregation (COFFMAN & MACCALLUM,
2005; PALLANT, 2007; SAUNDERS, ET AL., 2005). In addition, univariate and
multivariate outlier analysis was undertaken by assessing Z-score and
Mahalanobis distance. From the results,
all z – score ranged between -2.77494 and 2.20715 indicating that there was no
univariate outlier in all constructs of the study as Z-score are within
recommended values, between ±3 (KLINE, 2005). For the case of multivariate
outlier, assessment was done using Mahalanobis distance. The assessment was
done as outliers may be resulted after a combination of several constructs (KLINE, 2005). The entered
data were found to have no multivariate outlier as p values were less than
0.001.
Furthermore, the assessment of normality indicated that, data were
univariate normally distributed as all skewness indices were less than 3.0 and
the kurtosis indices were less than 10.0 (KLINE, 2005). In assessing
multivariate analysis, the Kortosis critical ratio (c.r) values was 1.523,
which is less than 1.96, indicating the presence multivariate normal
distribution of data. Therefore, the subsequent analyses (mainly hypothesis
testing) can use parametric formulas, such as Maximum Likelihood (ML)
estimations as used in SEM (TABACHNICK & FIDELL, 2001).
Descriptive analysis was confined to computing basic statistics and
frequency distributions. Both measurement model and factor analyses were done,
in the measurement model analysis; items that factor loaded below 0.3 were
eliminated and that which loaded above 0.3 were factor analyzed to identify
which items were factored out as one construct (COFFMAN & MACCALLUM, 2005).
In this study items in each construct, were grouped as one component.
Therefore, they were total aggregated to respective constructs (PALLANT, 2007).
Inferential analysis assessed the cause-effect relationship between
constructs; testing of the association, ascertaining direct effect and model fit
and testing of hypotheses (SAUNDERS, et al., 2005; KLINE, 2005).
5. RESULTS AND FINDINGS
The results and findings of the study are presented under
the headings of profile of respondents, structural measurement model and regression model.
5.1. Respondents
Profile
Table
2 presents the frequency distribution and percentage regarding sectors,
respondents and BPR experience of organizations studied.
Over representation of banking (31.6%), health (29.5%)
and insurance (18.9%) sectors does not mean that in Tanzania there are more
banks, health service and insurance organizations. The over representation
followed purposive selection of organizations. More of these organizations are
involved due to the evidence from literature review that more of them have
adopted the BPR technique (TERZIOVSKI, et al., 2002; SHIN, 2002; HE, 2005;
ADEYEMI & AREMU, 2008, MINYAN & TONGJAN, 2009; XIAOLI, 2011).
In this study majority of responds belong in operations
(28.4%) and human resource (38.9%) sections. More are from these two sections
because in most organizations, operations sections are ones knowledgeable about
business processes. In the other hand,
more human resource managers responded in this study because it is the section
which is responsible for providing organizational information to external
people.
Regarding experience, BPR practice is not a new feature
in the management of service organizations in Tanzania. This is evidenced by
findings of the study that majority (67.4%) of service organizations have
adopted BPR technique for over seven (7) years.
Table 2: Respondent Profile
|
Item |
Categories |
Number of Respondents |
Percentage |
|
Sector
of the organization |
Banking |
30 |
31.6 |
|
Health |
28 |
29.5 |
|
|
Insurance |
18 |
18.9 |
|
|
Public utility |
3 |
3.2 |
|
|
Communication |
6 |
6.3 |
|
|
Pension fund |
3 |
3.2 |
|
|
Airline |
7 |
7.4 |
|
|
Total |
95 |
100 |
|
|
|
|
|
|
|
Working
section of the respondent |
Operations |
27 |
28.4 |
|
Finance |
13 |
13.7 |
|
|
Marketing |
9 |
9.5 |
|
|
Quality |
1 |
1.1 |
|
|
Human resource |
37 |
38.9 |
|
|
General manager |
8 |
8.4 |
|
|
Total |
95 |
100 |
|
|
|
|
|
|
|
Experience
in practising BPR |
Less 2 years |
8 |
8.4 |
|
Between 2 and 6 years |
23 |
24.2 |
|
|
Between 7 and 10 years |
28 |
29.5 |
|
|
More than 10 years |
36 |
37.9 |
|
|
Total |
95 |
100 |
Source: Analysis of field data, 2012
5.2. Structural
measurement regression model
The
model show diagrammatical relationship between BPR (with its indicators) and
delivering speed. Furthermore, the model show error terms that take account for
non-considered factors that may have effect on delivering speed. The model is
presented below in Figure 2.
|
Figure 2: The model 1- Relationship between BPR and
delivering speed Source: Analysis of field
data, 2012 |
From the Figure 2, the factor loading of renovation
(Ren), Automation (Auto), and Networking (Net) are above 0.3. This indicates
that the items are good measures of BPR construct. From the Figure 2, the
results show that 1 standard deviation increase in BPR improves delivering
speed by 0.91 standard deviation. Since the model considers only standard
estimates, the effects of error terms are insignificant. The parameter that
appear just above the observed variable show how data deviates from the mean in
each observed variable.
5.3. Model
goodness of fit
This section presents different indices that have been
used to assess the model goodness of fit. The indices assessed include GFI,
AGFI, NFI, RFI, IFI, TLI, CFI and RMSEA as presented in Table 3 below.
Table 3:
Goodness of fit of model 1
|
Model |
GFI |
AGFI |
NFI |
RFI |
IFI |
TLI |
CFI |
RMSEA |
|
Default
model |
0.999 |
0.992 |
0.998 |
0.990 |
1.009 |
1.058 |
1.000 |
0.000 |
|
Saturated
model |
1.000 |
|
1.000 |
|
1.000 |
|
1.000 |
|
|
Independence
model |
0.656 |
0.427 |
0.000 |
0.000 |
0.000 |
0.000 |
0.000 |
0.393 |
|
Recommended values: AGFI, NFI, RFI, IFI, TLI and CFI should be close
to 1 and 0 ≤ RMSEA ≤ 0.1 (HOOPER, ET AL., 2008; KLINE, 2005) |
||||||||
Source: Analysis of field data, 2012
The results in Table 3 indicate that the model goodness
of fit is very good as most indexes are close to 1 and that of RMSEA falls in
the recommended range. The findings based on these results are that the
research constructs are acceptable for scientific work.
5.4. Correlation
and regression analyses
The section presents the results of correlation and
regression analyses. The analyses are based on the assessments of hypotheses 1
(that made up Figure 1 of the study).
5.4.1. Correlation analysis
Table 4 is a correlation matrix of the key constructs,
BPR and delivering speed.
Table 4: Correlation matrix
|
Pearson correlations |
BPR |
Spe |
|
BPR |
1.00 |
|
|
Spe |
0.912 |
1.00 |
Source: Analysis of field data, 2012
From the results in Table 4, the correlation between BPR
and delivering speed is 0.912, which is significant at p < 0.05 (PRICE,
2000). The total variation of delivering speed explained by BPR is 83.7% (0.9122).
Therefore, adopting BPR technique improves delivering speed in service
organizations considered in this study.
5.4.2. Regression analysis
Table 5 presents the
results of regression analysis.
Table 5: Regression weights of model 1
|
Regressed
variables |
Unstandardized
regression weight |
S.E |
P Value |
Standardized
regression weight |
|
Spe<---
BPR |
1.102 |
0.458 |
0.016 |
.912 |
Source: Analysis of field data, 2012
From the results presented in Table 5 above, regression weights are
positive and significant; indicating that BPR is an important determining
factor of delivering speed in service organizations studied. The estimated
relationship between BPR and delivering speed is presented in equation 2 below.
5.4.3. Testing of hypothesis
The hypothesis guiding this study was: BPR has no correlation with delivering speed in
service organization or in statistical form. The p value indicates that the
standardized regression coefficient (β1) is significant. This
implies that the null hypothesis is rejected in favour of the alternative
hypothesis. It is therefore concluded
that BPR is an important factor that enhances delivering speed.
6. DISCUSSION OF FINDINGS AND CONCLUSION
6.1.
Discussion
of findings
The
purpose of the study was to explicate the effect of BPR on delivering speed in
service organizations in Tanzania. The paper provides a framework to understand
the way BPR technique can be used to improve the OP. In assessing the direct
effect of BPR on delivering speed, coefficient of BPR in equation (1) was
tested.
Based
on the findings of the study, the hypothesis was supported (the null hypothesis
was rejected). In the findings, it was found that BPR has significant positive
correlation with delivering speed in service organizations. The study found
that BPR improves delivering speed by 83.17%. The findings are supporting the
findings of Terziovski, Fitzpatrick and
O’Neill (2003) which found that BPR reduces cycle time by 27%, Hall, et al. (1993) which found that BPR improves delivering
speed by 44%, Yahya (2002) which found that BPR improves service delivering
speed, Debela (2009) which found that BPR improves service delivering speed by
65%, Tennant and Wu (2005) which found that BPR improves speed by improving
coordination and that of Champy (1995)
which found that BPR improves delivery speed by decreasing cycle time by 70%. Not only that the findings are in line with
theory stipulated by Slack, et al (2007) and that of Hammer and Champy (1993) that
BPR improves delivering speed. In this
case, the finding is supported by literature and the effect of BPR is presented
in equation 2 below.
6.2.
Conclusion
The
study has found that BPR improves delivering speed in service organizations.
The findings are in line with the idea that BPR improves delivering speed in
service organizations as identified in focused literature review. It is
therefore concluded that BPR is an important technique to be adopted by service
organizations to improve business processes for enhanced delivering speed,
which in turn reduces time taken to service customers.. The study recommend a
similar study to be done by using longitudinal design in order to study the
effect of BPR on delivering speed.
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