A comprehensive framework for evaluating key project requirements.
Yang, Li-Ren ; Chen, Jieh-Haur ; Huang, Chung-Fah 等
Introduction
Many studies have shown that preproject planning effort may
contribute to project performance in terms of cost, schedule, and
operational characteristics (CII 1995; Griffith, Gibson 1995; Griffith
et al. 1999; Sobotka, Czarnigowska 2005). Thus, preproject planning
process is critical to the success of any capital facility project. The
development of project requirements definition is one of the major
subprocesses. It is the process by which projects are defined and
prepared for execution (Cho, Gibson 2001). Additionally, it is the stage
where project risk assessments are undertaken and the specific project
execution methods are analyzed. Success during the detailed design,
construction, and start-up phases of a project is highly dependent on
the level of effort expended during this stage (Cho, Gibson 2001; Yang,
Wei 2010).
In recent years, there has been a growing trend towards increased
preproject planning effort on Architect/ Engineering/Construction
(A/E/C) capital facility projects. Some construction organizations adopt
the best industry practices for project planning in the attempt to
reduce the cost and schedule of a project. These companies also examine
their operations for ways to improve stakeholder satisfaction. However,
since the importance of practices can be rather intangible, this has
slowed the adoption of project planning practice. Accordingly, the
importance of project planning has been one of the major issues for both
industry and academic fields. Many studies indicated that one of the
major challenges in construction management is the definition of project
requirements (Radujkovic et al. 2010; Toor, Ogunlana 2010). In order to
understand the issue, there is a need for quantification of
prioritization of project requirements. Research on prioritization of
project requirements should offer guides to project planning process.
Requirements definition and management (RDM) is the term used to
describe the process of eliciting, documenting, analyzing, prioritizing,
and agreeing on requirements, and then controlling, managing, and
overseeing changes and risk (Oberg et al. 2000; Zowghi 2002).
Requirements quality affects work performed in subsequent phases of a
project. Thus, the compliance with requirements is crucial to the
success of a project. The building sector suffers from poor or
incomplete requirements definition (Gibson et al. 1997; Cho et al.
1999). Early planning in many cases is not performed well in the
construction industry (Cho, Gibson 2001). While many studies have
promoted project planning as a means to enhance project performance,
very few published studies in construction have explored the importance
of project requirements from the perspectives of major stakeholders.
Additionally, there is little evidence to support the relationships
between levels of requirements definition and project performance.
Empirical evidence that supports the importance of building project
requirements is lacking. Thus, developing such support will illustrate
the benefits of preproject planning. The primary objective of this
research was to develop a comprehensive framework for evaluating key
building project requirements. Analytical network process has been used
to construct the framework in this study. The second objective was to
identify and prioritize important project requirement using the ANP. The
third objective was to examine the impact of requirement completeness on
project success. In addition, this research employed both questionnaire
survey and interview methods for data collection. A fourphase approach
was used to measure the prioritization of building project requirements
and explore the benefits of requirements definition.
1. Literature Review
A considerable body of research has been conducted on planning in
the A/E/C industry. Much of the project/construction management
literature relevant to this research is associated with the use of
planning tools, guides to project planning, and the expected benefits
associated with planning. Concerning the use of planning tools, Dumont
et al. (1997) focused on developing a tool for assessing the levels of
project definition. The tool, project definition rating index (PDRI) for
Industrial Projects, can assist in calculating a total score
representing the level of project definition. Cho and Gibson (2001)
introduced the PDRI for building projects. Their research concluded that
the PDRI is also an effective tool that applies to building projects.
Heesom and Mahdjoubi (2004) investigated trends of four-dimensional
computer aided design (4D CAD) applications for construction planning.
They developed a model to identify the attributes required for use with
each of the various applications of 4D CAD simulations. Ahmed et al.
(2003) explored the applicability of quality function deployment (QFD)
in the civil engineering capital project planning process. The findings
suggested that QFD can be employed in the project planning process as a
road map to keep track of the original requirements and facilitate good
communication across the hierarchy. Additionally, it is also a useful
tool for evaluating project alternatives. Ozdoganm and Birgonul (2000)
built a decision support framework for project planning. They stated
that the decision support framework can help project companies to define
the risk sharing scenarios under which a project becomes viable and
identify effective risk mitigation strategies. Gidado (2004) proposed a
simple systemic approach that can be used in practice to improve and
standardize the process of the prime contractor's planning of
construction projects. Their work concluded that the implementation of
the system of pre-construction planning may produce value in project
system implementation. Furthermore, Laufer et al. (1999) developed a
valuable tool to manage the decision-making process during the planning
of a project. Gibson et al. (1995) also presented a validated process
map describing the major subprocesses of preproject planning. Finally,
Islam and Faniran (2005) developed a structural equation model (SEM) for
quantifying the influence of situational factors in project
environments. The findings indicated that the project environment has a
dominant significant influence on the potential effectiveness of project
planning efforts. In summary, above prior studies indicated that project
planning plays an important role in construction.
While the above authors promoted the adoption of planning tools,
other researchers have also been active in exploring the relationships
between planning and project outcomes. Several researchers have
identified the importance of planning and its impacts on the performance
of capital facility projects or construction organizations. Kaka et al.
(2003) evaluated the effects of project planning on the cost flow
curves. Lee et al. (2005) examined the relative impacts of selected
practices on project cost and schedule. They argued that pre-project
planning is one of the critical practices indicating dominant impact on
both cost and schedule performance. Hamilton and Gibson (1996) focused
on measurement and benchmarking of the preproject-planning process for
capital construction. The study concluded that a complete scope
definition prior to project execution may contribute to project success.
Griffith and Gibson (2001) identified the important characteristics of
alignment during the preproject phase of industrial capital projects.
The results suggested that alignment effort has a positive effect on
project performance. Handa and Adas (1996) illustrated a methodology for
predicting the level of organizational effectiveness in construction
firms. The results indicated that level of planning by management is
highly significant in predicting the level of organizational
effectiveness in the construction firms. Finally, a study conducted by
Construction Industry Institute (CII) indicated that higher levels of
preproject planning effort may result in substantial cost and schedule
savings (CII 1995).
Requirements definition is an important component of effective
project planning. The literature stated that the problems related with
requirements definition are one of the main reasons for project failures
(Radujkovic et al. 2010; Toor, Ogunlana 2010). Resarch suggested that
most of the project requirements were difficult to identify and some
were not clear and well organized (Oberg et al. 2000). Prior research
also indicated that 40% of the requirements generate rework during the
project life cycle (Zowghi 2002). It is evident that the earlier a
problem is detected during the preproject planning phase, many other
problems are minimized in the following phases. Thus, requirements
definition is often cited as one of the most important, but difficult,
phases of a project (Brooks 1987). The results of previous studies
indicated a correlation between requirements definition effort and
project performance (Damian, Chisan 2006; Procaccino et al. 2002; Brooks
1987; Kauppinen et al. 2004; Herbsleb, Goldenson 1996; Huang, Hsueh
2010; Radujkovic et al. 2010; Toor, Ogunlana 2010; Yang et al. 2011).
A review of the literature suggests that the use of project
planning as a means to enhance project performance has been widely
supported. Generally, many researchers have argued that planning
provides significant benefits to projects (Laslo 2010; Gorog 2009;
Winch, Kelsey 2005; Wyk et al. 2008; Kwak, Smith 2009; Reed, Knight
2010; Artto et al. 2008; Hanna, Skiffington 2010). Prior research have
also indicated that increased levels of scope definition during the
preproject planning phase may improve the accuracy of cost and schedule
estimates as well as the probability of meeting or exceeding project
objectives (Griffith, Gibson 1995; Hackney 1992; Hamilton, Gibson 1996;
Merrow 1988; Dumont et al. 1997).
The results of previous studies indicated a correlation between
requirements definition and management (RDM) effort and project
performance. Additionally, a review of the literature suggests that RDM
effort may improve requirements quality in terms of correctness,
consistency, and completeness, which subsequently affecting the
performance of a project (Damian, Chisan 2006; Procaccino et al. 2002;
Brooks 1987; Kauppinen et al. 2004; Herbsleb, Goldenson 1996; Radujkovic
et al. 2010; Huang, Hsueh 2010; Toor, Ogunlana 2010). This study extends
previous studies by addressing the impact of requirements completeness
on project performance in the building industry. Based on the relevant
literature, the following hypothesis was postulated and tested:
H: Requirements completeness positively influences building project
performance.
While the diverse benefits of preproject planning have received
substantial attention, the number of studies dealing with the importance
of project requirements is rather scarce. This research adds to the
literature in two valuable ways. First, it develops a comprehensive
framework for evaluating key project requirements in the building
sector. Second, it offers important results on prioritization of
building project requirements and their impacts on project success.
2. Phase 1 research
This research was divided into four phases (see Figure 1). Phase 1
included determining the applicability of the proposed project
requirements. A survey was developed to investigate the degree, if any,
to which the proposed requirements apply to building projects. The
survey was designed to include requirements that were thought to have
substantial impact on building projects. The listing of project
requirements, which resulted from both brainstorming and a literature
search (Dumont et al. 1997; Cho, Gibson 2001), contained over 100 items.
Therefore, a systematic method for eliminating some of the less
important requirements was developed. Each requirement was then tested
to ensure it applies to building projects. As such, identification of
the requirements was based on previous studies and interviews with
construction practitioners. The industry interviews encompassed 11
executives from the Owner, Architect/Engineering (A/E), and General
Contractor (GC) groups. Each of the professionals has over 20 years of
senior management experience in the industry. For each proposed project
requirements, the survey asked the participants to assess the extent to
which individual requirements apply to projects in the building sector.
This survey offered respondents three optional responses: applicable,
not applicable, or need to be revised. The survey allowed the
participants to offer additional comments on a potential revision. The
refined assessment items were included in the Phase 2 survey
questionnaire. Finally, the Phase 2 survey makes use of 81 project
requirements in assessing their relative importance.
Fig. 1. Research methodology
Phase 1: Determine the applicability of the proposed project
requirements
1. A survey was developed to investigate the degree to which the
proposed requirements apply to building projects.
2. Three optional responses: applicable, not applicable, or need to
be revised.
3. The listing of project requirements resulted from brainstorming
and a literature search.
4. The interviews encompassed 11 executives from the Owner, A/E,
and GC groups.
Phase 2: Explore the factors of building project requirements
1. A questionnaire was developed based on the results of the work
done in Phase 1.
2. Pre-test for the clarity of questions.
3. Assess how important each of the requirements is for planning
building projects.
4. Responses are given on 7-point scale, from 1(not at all
important) to 7 (very important).
5. The sample focused on from the Owner, A/E, and GC groups.
Phase 3: Prioritize important project requirement
1. Use analytical network process (ANP).
2. The clusters and nodes are based on the requirement categories
and items identified in Phase 2.
3. Pairwise comparisons of the elements in each level are conducted
with respect to their relative importance towards their control
criterion.
4. Use Saaty's 9-point scale.
5. For acceptable inconsistency, CR must be less than 0.10 (Saaty
1980).
6. The survey included responses from project managers.
Phase 4: Examine the associations between requirements completeness
and project success
1. Use structural equation modeling (SEM).
2. Confirmatory factor analysis (CFA) model.
3. The structural model includes a set of exogenous and endogenous
variables in the model, together with the direct effects (path
coefficient) connecting them.
4. Goodness of fit statistics can be computed to determine whether
the model is appropriate or needs further revision.
3. Phase 2 research
3.1. Procedure
Phase 2 of the research entailed exploring the factors of building
project requirements. In other words, the purpose of Phase 2 was to
determine key requirement categories and items. A questionnaire was
developed based on the results of the work done in Phase 1. As such, the
81 project requirements identified in Phase 1 were included in the Phase
2 questionnaire. Additionally, copies of a draft survey were sent to
several industry professions to pre-test for the clarity of questions.
Their insights were also incorporated into the final version of the
survey questionnaire. The questionnaire was used to assess how important
each of the requirements is for planning building projects. Responses
are given on 7-point scale, from 1 (not at all important) to 7 (very
important).
This research employed survey methodology for Phase 2 data
collection. The survey instrument was used to measure the relative
importance of building project requirements from the viewpoints of major
stakeholders involved in projects. Thus, the sample for Phase 2 research
focused on the Owner, Architect/Engineering, and General Contractor
groups in the Taiwanese building industry. Individuals interested in
participating in this phase were identified by a search from a number of
industry associations. The Owner' sample was selected from various
public and private owners. In addition, the A/E's sample was
selected from the National Association of Architect, Taiwan and Chinese
Association of Engineering Consultants. On the other hand, the sample of
GC was drawn from members of General Contractors Association, Taiwan.
The survey questionnaire was sent to more than 800 senior practitioners
on June 30, 2008. Some of the organizations were then contacted via
phone or email to identify the manager or the person involving in
building projects by name and title. Reminders were sent by e-mail or
phone after survey mailing. The initial mailing elicited 89 usable
responses. Finally, four weeks after the initial mailing, a second
mailing of the survey was made to non-respondents. A reminder letter,
too, followed the second mailing. An additional 46 usable responses were
returned. In summary, of the 811 questionnaires sent, 137 were returned.
The overall response rate was 17.12 percent. Among the returned surveys,
2 were discarded since they contained too many missing values.
Ultimately, 135 survey responses were used in the analysis.
3.2. Participants and data analysis
The sample was composed of 39 practitioners from the Owner group.
With respect to years of experience, 17.95 percent of the respondents
are more than 20, 12.82 percent are between 16 and 20, 25.64 percent are
between 11 and 15, 23.08 percent are between 6 and 10, and the remaining
20.51 are less than 6. Furthermore, 35.90 percent of the respondents
indicated that they held a Master's degree, while another 28.21
percent held a Bachelor's degree. The remaining 35.90 percent held
an associate's degree. The sample consisted of 62 practitioners
from the Architect/Engineering group. With respect to years of
experience, 23.73 percent of the respondents are more than 20, 13.56
percent are between 16 and 20, 32.20 percent are between 11 and 15,
20.34 percent are between 6 and 10, and the remaining 10.17 are less
than 6. Furthermore, 57.63 percent of the respondents indicated that
they held a Master's degree, while 42.37 percent held a
Bachelor's degree. Additionally, the sample also included 34
professionals from the General Contractor group. With respect to
education, 30.30 percent of the respondents indicated that they held a
Master's degree, while another 45.45 percent held a Bachelor's
degree. The remaining 24.24 percent held an associate's degree. The
sample was randomly selected from the population. Based on sampling
frame (i.e. a list of all those within a population who can be sampled)
provided by the industry associations, the structure of the population
is similar to that of the sample.
After data are collected, a preliminary data analysis was
conducted. Factor analysis was employed to reduce the building project
requirements into several factors. The items associated with these key
factors were selected to assess requirements quality in Phase 3.
4. Phase 3 research
4.1. ANP decision model
To address the issue regarding prioritization of project
requirements, this research employed the analytic network process as a
suitable multicriteria decision analysis tool. The ANP technique is a
general form of the analytic hierarchy process (AHP) (Saaty 1996). AHP
is one of the most commonly used multicriteria decision analysis tools.
This approach requires a hierarchic structure where criteria are
mutually independent. However, evaluation criteria could be
interdependent to each other. ANP was shown to be effective in
addressing such complexity of interactions in the structure.
The ANP model includes all contributive factors (clusters and
nodes) and their possible direct interactions in the decision structure.
The clusters and nodes used in the model are based on the requirement
categories and items identified in Phase 2.
4.2. Processing procedures and data gathering
In the ANP model, pairwise comparisons of the elements in each
level are conducted with respect to their relative importance towards
their control criterion (Saaty 1996). As such, with respect to any
criterion, pairwise comparisons are performed in two levels (i.e. the
element level and the cluster level comparison). The intensity assigned
to the comparison process between factors was made using Saaty's
9-point scale. Saaty (1988) has suggested a scale of 1 to 9 when
comparing two components, with a score of 1 representing indifference
between the two components and 9 being overwhelming dominance of the
component under consideration over the comparison component. After all
pairwise comparisons were completed, the priority weight vector was
computed. In addition, the inconsistency of judgments was checked using
the consistency ratio (CR). For acceptable inconsistency, CR must be
less than 0.10 (Saaty 1980). The column vectors from the limit matrix
were also normalized according to clusters to provide the overall
priorities. Group assessment was integrated using geometric mean (Saaty
1980). Finally, the priority of the building project requirements was
identified. The calculations were implemented through the software
Superdecisions.
Since evaluation criteria could be interdependent to each other in
the ANP model, the respondents should have a view of the project that
crossed functional boundaries and organizational levels and understand
the interdependency among the project requirements. Thus, only project
managers involved in the project from start to end are qualified to
participate in the study. The qualifications assured that respondents
understand the relationships among the criteria investigated in the
survey. The survey included responses from 18 project managers in the
building industry. The sample size is adequate for ANP/AHP analysis
(Tseng et al. 2011; Vidal et al. 2011; Mahdi, Alreshaid 2005). With
respect to years of experience, all of the respondents had more than 10
years of experience in the building industry.
Kendall's W was used for assessing agreement among the 18
raters. The Kendall's W coefficient is 0.76, which indicates a fair
degree of agreement. A coefficient of unity (i.e. 1.0) signifies perfect
agreement, and a coefficient greater than 0.70 represents strong
agreement (Okoli, Pawlowski 2004; Schmidt 1977). Thus, the results show
significant agreement among these respondents.
5. Phase 4 research
5.1. Survey process and structure
The primary objective of this research was to develop a
comprehensive framework for evaluating key building project
requirements. The second objective was to identify and prioritize
important project requirement using the analytical network process
(ANP). The two objectives are associated with the scope of research in
Phase 2 and Phase 3. After identifying the "key" requirement
categories and items, Phase 4 of the research employed structural
equation modeling (SEM) analysis to examine the associations between
completeness of the "important" requirements identified in
Phases 2 and 3 and project success. Thus, the third research objective
pertains to the scope of research in Phase 4. A data collection tool was
used to assess the relationships. The survey instrument was used to
measure levels of requirements completeness and the performance of
building projects. The data collection tool was developed based on the
items used in Phase 3 research and variables used in previous studies.
The survey was composed of three sections: 1) levels of requirements
definition; 2) project performance; and 3) project and personal
information. The first section measured completeness of project
requirements. The items in the ANP model were employed to investigate
requirement completeness on the subjective project. In other words, this
section evaluated levels of completeness of the requirements used in the
ANP model. In addition, the second section investigated overall project
performance.
Finally, the third section obtained information concerning the
project and the respondent. Hypotheses were developed and tested to
determine the statistical significance of the hypothetical
relationships.
5.2. Sample selection and data collection
An industry-wide survey of requirements definition effort and
performance on building projects was conducted in Taiwan between March
2009 and February 2010. In order to obtain an adequate sample for
structural equation modeling analysis, More data were collected between
October and December 2011. The data collection tool was developed to
collect project-based data. Project responses were collected through
personal interviews. Individuals interested in participating in this
phase were identified by a search from various industry associations. In
order to obtain a truly representative sample, not only was the
geographic mix of projects intentionally diverse, but a diverse mix of
participation was sought with respect to project size. Additionally, a
specified mix of team size was targeted in order to obtain a
representative sample of the industry. More than 200 projects were
investigated and some were not included in the analysis because they
contained insufficient information. In addition, the projects were
examined to ensure that no duplicate project information was collected.
Ultimately, 208 survey responses were used in the analysis. Table 1
presents characteristics of sampled projects.
The sample's respondents consisted of project managers,
project directors, project planners, and project superintendents. With
respect to years of experience, 7.7 percent are more than 20, 19.7
percent are between 16 and 20, 21.6 percent are between 11 and 15, 33.2
percent are between 5 and 10, and the remaining 17.8 percent are less
than 5. Additionally, 4.8 percent of the respondents indicated that they
held a Master's degree, while another 45.7 percent held a
Bachelor's degree. Additionally, 41.8 percent of the respondents
indicated that they held associate's degree. The remaining 6.7
percent held a high school diploma.
5.3. Variable measurement and index development
As previously discussed, completeness of project requirements was
evaluated based on the items selected from the ANP model. Respondents
were asked to indicate how successful their projects have been in
achieving completeness for each item. A six-point scale was utilized
with 1 = not at all successful and 6 = extremely successful. Based on
Cho and Gibson (2001) and Dumont et al. (1997), a detailed definition of
the requirements is presented in Appendix A.
On the other hand, questions from Muller and Turner (2007), Pinto
and Slevin (1988), Larson and Gobeli (1988), Keller (1994), Freeman and
Beale (1992), Shenhar et al. (1997), and Westerveld (2003) were adapted
to measure building project performance. Each item was rated on a
6-point scale, where 1 represented strongly disagree and 6 represented
strongly agree.
5.4. Dealing with validity and reliability
The content validity of the survey used in Phase 4 was tested
through a literature review and interviews with practitioners. In other
words, the survey items were based on previous studies and discussions
with these industry executives. The industry interviews encompassed nine
construction industry executives. A specified group involvement was also
targeted in order to acquire a comprehensive knowledge from different
perspectives. The industry interviews encompassed nine executives from
the Owner, A/E, and GC groups (three practitioners from each group).
Each of the professionals has over 20 years of senior management
experience in the industry. The refined assessment items were included
in the final survey. Finally, copies of a draft survey were sent to
several industry professions to pre-test for the clarity of questions.
Their insights were also incorporated into the final version of the
survey. The construct validity was tested by factor analysis. Factors
were extracted using Varimax rotation. As suggested by Hair et al.
(1995), an item is considered to load on a given factor if the factor
loading from the rotated factor pattern is 0.50 or more for that factor.
Cronbach's coefficient ([alpha]) was also computed to test the
reliability and internal consistency of the responses. The values of
Cronbach's [alpha] above 0.7 are considered acceptable and those
above 0.8 are considered meritorious (Nunnally 1978; Carmines, Zeller
1979; Litwin 1995).
6. Results and Analysis
6.1. Identification of key project requirement categories and items
In Phase 2 of this study, factor analysis with Varimax rotation was
used to identify key requirement factors. Eigenvalue greater than one
was used to determine the number of factors in the data set (Churchill
1991). Only variables with a factor loading greater than 0.5 were
extracted (Hair et al. 1995). Figure 2 presents the scree plot. The 81
items of project requirements investigated are classified into six
factors. In other words, the results indicated that six factors were
found to underlie the various sets of project requirements in the
building sector. Twenty-four items were dropped due to low factor
loading. Additionally, the factor loadings for the other items range
from 0.505 to 0.804. The six constructs categorized are project design
parameter, project plan, site information, project control, project
strategy, and building programming.
Cronbach's coefficient (a) was computed to test the
reliability and internal consistency of the responses. Reliability was
assessed for project design parameter at 0.962, project plan at 0.935,
site information at 0.944, project control at 0.913, project strategy at
0.862, and building programming at 0.870. In addition, the relative
importance for the survey items is presented in Table 2.
[FIGURE 2 OMITTED]
6.2. Factor structure of project performance
Factor analysis was also used to decide the grouping of project
success. The items of project performance construct are classified into
four factors. The subscales are schedule success, cost success, quality
performance, and overall benefit. Reliability was assessed for schedule
success at 0.914, cost success at 0.920, quality performance at 0.944,
and overall benefit at 0.918. All of the a values for the sub-dimensions
are above 0.9, indicating a high level of internal consistency among the
project performance items.
6.3. Decision model
The listing of project requirements, which resulted from factor
analysis in Phase 2, contained 58 items (see Table 2). This list was too
long to allow respondents to complete the ANP survey in a reasonable
amount of time. Therefore, the five most important project requirements
for each of the six requirement categories were selected for further ANP
analysis. Finally, the data collection tool makes use of 30 project
requirement items in assessing prioritization.
The factors and items identified in Phase 2 were used to develop a
model that explicitly considers many of the important project
requirement found in literature and practice. This model was then used
to prioritize the project requirements. The structure used in this model
is presented in Figure 3. In other words, Figure 3 lists the 30 key
project requirements used in the ANP model. The relevant criteria are
structured in the form of a hierarchy. "Successful project
performance" was placed on the top of the hierarchy used for the
ANP model. In this model, the first level below the goal is the
requirement categories: project design parameter, project plan, site
information, project control, project strategy, and building
programming. The topmost elements (requirement categories) are
decomposed into subcomponents (requirement items). As shown in Figure 3,
criteria could be interdependent to each other for the category level
and the item level.
[FIGURE 3 OMITTED]
6.4. Prioritization based on ANP model
In analyzing the prioritization by using the ANP approach, the
priorities of the requirement categories and items were determined.
Table 3 shows the global priorities of the 30 criteria derived by taking
the limit of weighted supermatrix of the ANP model. The priorities of
the requirement categories in the model are also reported in Table 3.
For the category level, the two most important requirement categories in
the building sector were building programming and site information. For
the item level, five building project requirements (weights were over
0.05) stood out as being very important from the perspectives of project
managers: compartment requirements, reliability philosophy, open space
requirements, indoor rooms, and human resource management.
6.5. Impacts of requirement completeness on project success
Structural equation model (SEM) analysis was used to examine the
impact of requirement completeness on project performance. Two main
components are included in SEM: measurement model and structural model.
Prior to estimating the structural model, a confirmatory factor analysis
was conducted to verify the measurement model (Anderson, Gerbing 1988).
Multiple fit criteria were used to assess the overall fit of the model
(Bollen, Long 1993; Hair et al. 1995). In the proposed model,
"requirement completeness" and "project performance"
are a second order construct. For example, "project
performance" is considered to be a four-dimensional construct
composed of schedule success, cost success, quality performance, and
overall benefit. In other words, the latent variable (project
performance) is represented by four latent variables. The second order
approach was used to maximize the interpretability of both the
measurement and the structural models (Hair et al. 1995). The data were
analyzed using the AMOS/SPSS statistical package. The model refinement
was performed to improve the fit to its recommended levels as shown in
Table 4. Based on several trials resulting in elimination of some of the
items, all of the scales met the recommended levels. Furthermore, the
composite reliability for all constructs was above the 0.7 level
suggested by Nunnally (1978), indicating adequate reliability for each
construct. Thus, the results provide evidence that the scales are
reliable (see Table 4).
All of the factor loadings are statistically significant at the
five percent level and exceed the arbitrary 0.5 standard (Fornell,
Larcker 1981). In addition, all constructs have an average variance
extracted (AVE) greater than 0.5. Thus, these constructs demonstrate
adequate convergent validity. Discriminant validity evaluates whether
the constructs are measuring different concepts (Hair et al. 2006). The
discriminant validity of each constructs was assessed. First, a
procedure recommended by Bagozzi et al. (1991) was adopted. Each set of
construct measures was paired with another set of measures. Each model
was run twice, once by constraining the correlations between the two
constructs to unity and once by freeing this parameter (Li, Cavusgil
2000), then a chi-square difference test was conducted. The results show
that the chi-square values are significantly lower for the unstrained
models at the five percent level, which suggests that the constructs
exhibit discriminant validity.
Figure 4 presents results of the overall model fit in the
structural model. A feasible model was selected based on the recommended
Goodness-Of-Fit (GOF) measures and the model that satisfies both
theoretical expectations and GOF was finally selected for structural
equation modeling analysis (Molenaar et al. 2000). The overall fit
statistics indicated a very good fit for the model. The chi-square
statistic for the full measurement model was nonsignificant (p >
0.05) indicating a good fit between the data and the proposed model. The
normed fit index (NFI), comparative fit index (CFI), and goodness of fit
index (GFI), with values of 0.931, 0.951, and 0.909 respectively, were
all above the recommended acceptable 0.90 level (Chau 1997). In
addition, the adjusted goodness of fit index (AGFI = 0.852) was above
the 0.80 min imum recommended value. Finally, the root mean square error
of approximation (RMSEA) was 0.076, which was below the cut-off level of
0.08 recommended by Browne and Cudeck (1993).
The test of the hypothesis was based on the direct effects
(structural coefficients) among the constructs as shown in Figure 4. The
hypothesis proposed a positive relationship between requirement
completeness and project performance. This hypothesis was supported
since the standardized coefficient was 0.73 and statistically
significant (p < 0.001).
[FIGURE 4 OMITTED]
Conclusion and discussions
While the diverse benefits of preproject planning have received
substantial attention, the number of studies dealing with prioritization
of project requirements is rather scarce. The research results offer
guides to project planning process in the building sector. Findings from
this study are helpful to project planners in identifying relative
importance of building project requirements. Project managers can use
the research results to modify their current building project planning.
The findings show that building programming and site information have a
higher priority in requirement definition than project control, project
strategy, and project design parameter. Building programming and site
information are associated with fundamental project requirements. Many
other project requirements are dependent on the two categories of
requirements. This may explain why building programming and site
information are more important than the other requirement categories and
why the ranking of the requirements evaluated in Phase 2 (criteria are
mutually independent) and Phase 3 (criteria could be interdependent to
each other) is different. Among the sub-criteria, the five building
project requirements project managers considered most important were
compartment requirements, reliability philosophy, open space
requirements, indoor rooms, and human resource management. This
indicates that project planners need to be especially aware of the
importance of these project requirements during the plan ning of a
project. The findings also indicate that requirement completeness
contributes significantly to building project success.
The results suggest that the two most important requirement
categories were building programming and site information. With respect
to building programming, project managers must clearly define
compartment requirements, windows and doors, identify materials, and
indoor rooms, which contribute significantly to building project
success. Regarding site information, reliability philosophy and site
life safety considerations are very important requirements. Project
design criteria, project schedule control, project cost estimate, and
human resource management are also critical requirements that have
impacts on building project success. Project planners should prompt
different departments to cooperate in requirements definition and
exchange information so that each group is aware of the needs and
resources of the other. Additionally, offering team members with
education is also an important method to improve requirements definition
and management. Project managers should also deal properly with the
conflicts between different groups and encourage communication to
eliminate disagreement. They must promote trust between different
departments and educate team members to consider different perspectives.
This study has certian implications with respect to requirements
definition and management (RDM) practice. Project managers should
develop a complete requirements definition and management process to
manage building project requirements. They need to define a flexible
requirements definition and management process and integrate the process
with the project planning process. More importantly, they must involve
the owner group in improvement work. Training and continuous improvement
is also critical to requirements definition and management
implementation. Project managers should set goals for requirements
definition and management process improvement and conduct an
evolutionary improvement strategy. Testing the requirements definition
and management process in a pilot project is also important for building
project planning. In addition, they must measure the impact of the
requirements definition and management improvement efforts on building
project performance. Finally, they should conduct just-in-time training
to get project teams to apply the requirements definition and management
process in practice. On the other hand, project managers must also pay
attention to requirements quality and stability. They should use a
particular method to gather project requirements and adopt requirements
definition and management practice to make sure the requirements are
complete and accurate. Improvements in consistency, verifiability,
prioritization, and ambiguity elimination are also important issues for
building project planning. Project managers must also engage in
practices that control changes in project scope and owner requirements.
The paper provides value to practitioners by providing a general
model for project requirement evaluation and to researchers by
demonstrating a new application of ANP. This strategic decision making
tool assisted the project planners in development of project
requirements. Although the decision levels involved in any particular
project may be different depending on the activities involved, the ANP
model presented is a general model applicable to most building projects.
In addition, the basic framework in this model can be adapted to a
particular situation. Project managers may select a set of criteria
which are important for a particular project. In other words, a
criterion that a project manager considers to be critical may be added
to the general model. On the other hand, the model did not consider all
possible criteria. As discussed previously, the listing of project
requirements, which resulted from factor analysis, was too long to allow
respondents to complete the ANP survey in a reasonable amount of time.
Therefore, a systematic method for eliminating some of the less
important project requirements was developed. Depending on the project
environment, additional criteria could also be added. Additionally, the
weighting given each criterion in the ANP model may be dependent on the
particular situation of a proect.
The research results offer guides to project planning process.
Findings from this study are helpful to project planners in deciding
what priority each project requirement has in the building sector.
Project planners can use the research results to understand the
associations be tween requirement completeness and project success and
modify their current project planning. While the model presented
provides value, there are issues for future validation. Future research
may also develop different models to validate and compare their
efficacy. In addition, case studies may be conducted to validate the
models and determine which project alternatives would best meet the
company's goals. Another objective for future study is to develop
requirement evaluation models and investigate the prioritization of
project requirements for the other sectors (industrial or infrastructure
projects). Finally, Delphi approach can be used to achieve consensus of
opinion in the preference weightings.
Appendix A
Evaluation criteria for project requirements in the ANP model
Evaluation criteria for project design parameter:
Structural requirements and design: Structural system, Seismic
requirements; Foundation system; Corrosion control requirements/Required
protective coatings; Client specifications (e.g. basis for design loads,
vibration, deflection, etc.); Future expansion/flexibility
considerations; Design loading parameter (e.g. live/dead loads, design
loads, collateral load capacity, equipment/material loads, wind/snow
loads, uplift); Functional spatial constraints.
Architectural design: Requirements for building location; Access
requirements; Nature/character of building design (e.g. aesthetics,
etc.); Construction materials; Acoustical considerations; Circulation
considerations; Color/material standards; Floor to floor height.
Site survey: A topography map with the overall plot and site plan;
Legal property descriptions with property lines; Drainage patterns;
Definition of final site elevation; Benchmark control systems; Setbacks,
access & curb cuts; Proximity to drainage ways; Existing facility
locations and conditions.
Electrical and mechanical design: Power sources with available
voltage & amperage; Special lighting considerations (e.g. lighting
levels, color rendition); Uninterruptable power source (UPS); Emergency
power requirements; Ability to use daylight in lighting;
Lightning/grounding requirements; Special ventilation or exhaust
requirements; Equipment/space special requirements with respect to
environmental conditions (e.g. air quality, special temperatures); Air
circulation requirements; Indoor design conditions (e.g. temperature,
humidity, pressure, air quality, etc.); Plumbing requirements.
Piping system requirements: Piping specialty items list; Piping
system criteria; Valve list with tag numbers; Tie-in list for all piping
tie-ins to existing lines; Piping stress analysis.
Evaluation criteria for project plan:
Owner approval requirements: Milestones for drawing approval by
phase; Durations of approval cycle compatible with schedule;
Individual(s) responsible for reconciling comments before return; Types
of drawings/specifications; Purchase documents and contract documents.
Design plan and approval: Design and approvals sequencing of
events.
Project design criteria: Level of design detail required; Climatic
data; Codes and standards; Utilization of design standards; Sole source
requirements for equipment or systems; Insurance underwriter
requirements. Evaluation of adjacent building: Type and size of adjacent
buildings; Condition assessment of adjacent buildings. Purpose of
building use: Identify building uses or functions.
Evaluation criteria for site information:
Fire protection: Fire protection practices at the site; Available
firewater supply (amounts and conditions); Fire monitors and hydrants.
Site life safety considerations: Special safety requirements unique
to the site; Wind direction indicator devices; Access and evacuation
plan; Available emergency medical facilities; Security considerations
(site illumination, access control, etc.).
Safety management: Fire resistant requirements; Explosion resistant
requirements; Area of refuge requirements in case of catastrophe; Safety
and alarm requirements; Eye wash stations; Safety showers; Deluge
requirements and foam; Fume hoods; Handling of hazardous materials;
Isolation facilities; Emergency equipment access; Data or communications
protection in case of disaster or emergency; Fall hazard protection; Gas
hazard detection; Ventilation requirements for restrooms, offices, and
industrial areas.
Safety procedures: Hazardous material handling; Interaction with
the public; Working at elevations/fall hazards; Evacuation plans and
procedures; Drug testing; First aid stations; Accident reporting and
investigation; Pre-task planning; Safety orientation and planning;
Safety incentives; Personal protective equipment.
Reliability philosophy: Critical systems redundancy;
Architectural/structural/civil durability; Mechanical/electrical/
plumbing reliability.
Evaluation criteria for project control:
Project schedule control: Milestones; Unusual schedule
considerations; Required submissions and/or approvals; Required
documentation and responsible party; Baseline vs. progress to date;
Critical pacing equipment delivery; Critical path activities;
Contingency or "float time"; Permitting or regulatory
approvals.
Project cost control: Financial (client/regulatory); Phasing or
area sub-accounting; Capital vs. non-capital expenditures; Report
requirements; Payment schedules and procedures; Cash flow
projections/draw down analysis; Cost code scheme/strategy; Costs for
each project phase; Periodic control check estimates; Change order
management procedure, including scope control.
Project cost estimate: Construction contract estimate; Professional
fees; Land cost; Furnishings; Administrative costs; Contingencies; Cost
escalation for elements outside the project cost estimate; Startup costs
including installation; Miscellaneous expenses.
Overview of work scope: This work statement overview is a complete
narrative description of the project that is discipline-oriented and
supports development of the project schedule and project cost estimate.
It sets the limits of work by each involved party and generally
articulates their financial, task, and contractual responsibilities. It
clearly states both assumptions and exclusions used to define the scope
of work.
Project control requirements: A functioning project control system
is in place for managing project baselines using earned value
techniques, variance analysis and effective reporting.
Evaluation criteria for project strategy:
Human resource management: Adequacy of staffing level; Extent of
training workforce; Extent of team-building activities; Extent of
rewarding high performance staff.
Economic analysis: Long-term operating and maintenance costs;
Resale/lease potential or in the case of institutional buildings, long
term use plans; Analysis of capital and operating cost versus sales or
occupancy and profitability.
Project strategy: Clearly defined project strategy.
Alternatives considerations: Major alternatives have been
identified and viable alternatives have been analyzed. Items to evaluate
include issues such as feasibility, stakeholder values, and safety.
Value-analysis process: Discretionary scope issues; Expensive
materials of construction; Life-cycle analysis of construction methods
and structure.
Evaluation criteria for building programming:
Identify materials: Identify material items with lead times that
will impact the design for receipt of vendor information or impact the
construction schedule with long delivery times.
Indoor rooms: Identify indoor rooms.
Open space requirements: Service dock areas and access; Passenger
drop-off areas; Pedestrian walkways; Courtyards, plazas, or parks;
Landscape buffer areas; Lobbies and entries; Postal and newspaper
delivery; Waste removal; Interior aisle ways and corridors.
Windows and doors: Blocking of natural light; Glare reducing
windows; Exterior louvers; Interior blinds; Doors.
Compartment requirements: Identify compartment requirements.
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Li-Ren YANG (a), Jieh-Haur CHEN (b), Chung-Fah HUANG (c)
(a) Tamkang University, 151 Ying-chuan Rd., Tamsui, Taipei 251,
Taiwan
(b) Construction Engineering and Management, National Central
University, No. 300, Jhongda Rd, Jhongli 32001, Taiwan
(c) National Kaohsiung University of Applied Sciences, 415
Chien-Kung Rd., Kaohsiung 807, Taiwan
Received 03 Aug 2011; accepted 26 Jan 2012
Corresponding author: Li-Ren Yang
E-mail: iry@mail.tku.edu.tw
Li-Ren YANG. A Professor of Business Administration at Tamkang
University. He received his doctoral degree from the University of Texas
at Austin. Research interest includes project management.
Jieh-Haur CHEN. A Professor of Graduate Institute of Construction
Engineering and Management at National Central University. He received
his doctoral degree from the University of Wisconsin-Madison. Research
interest includes information technology in construction.
Chung-Fah HUANG. An Associate Professor of Civil Engineering at
National Kaohsiung University of Applied Sciences. He received his
doctoral degree from National Central University, Taiwan. Research
interests include human resource management in construction, engineering
ethics, and outsourcing management.
Table 1. Characteristics of sampled projects
Characteristic Class Number Percent of
projects
Initial site Greenfield (or new) 176 84.6
Initial site Renovation 12 5.8
Initial site Expansion 20 9.6
Project size < $5 Million 87 41.8
Project size $5-20 Million 67 32.2
Project size > $20 Million 46 22.1
Project size Not available 8 3.8
Project duration Short 69 33.2
Project duration Medium 73 35.1
Project duration Long 58 27.9
Project duration Not available 8 3.8
Number of core < 10 130 62.5
team member
Number of core 10-20 28 13.5
team member
Number of core 32 15.4
team member
Number of core Not available 18 8.7
team member
Project typicality Traditional 167 80.3
Project typicality Advanced 37 17.8
Project typicality Not available 4 1.9
Owner regulation Private 125 60.1
Owner regulation Public 79 38.0
Owner regulation Not available 4 1.9
Complexity Low 46 22.1
Complexity Medium 127 61.1
Complexity High 33 15.9
Complexity Not available 2 1.0
Table 2. Relative importance of project requirements for the
categories
Factor Project requirement Mean
1 Structural requirements 6.19
1 Structural design 5.94
1 Architectural design 5.90
1 Site survey 5.83
1 Electrical and mechanical design 5.82
1 Piping system requirements 5.82
1 Construction process 5.77
1 Civil design 5.74
1 Utility sources with supply conditions 5.71
1 Site layout 5.67
1 Geotechnical information 5.59
1 Civil information 5.50
1 Evaluation of existing facilities 5.50
1 Plot plan 5.29
2 Owner approval requirements 5.93
2 Design plan and approval 5.80
2 Project design criteria 5.77
2 Evaluation of adjacent building 5.76
2 Purpose of building use 5.74
2 Construction plan and approval 5.60
2 Building use planning 5.59
2 Site location 5.58
2 Space evaluation 5.53
2 Facility requirements 5.52
2 Project objective statement 5.29
2 Future expansion considerations 5.24
3 Fire protection 5.94
3 Site life safety considerations 5.82
3 Safety management 5.77
3 Safety procedures 5.63
3 Reliability philosophy 5.57
3 Maintenance philosophy 5.47
3 Training requirements 5.47
3 Operating philosophy 5.46
3 Waste treatment requirements 5.44
3 Water treatment requirements 5.34
3 Soil tests 5.32
3 Transportation requirements 5.21
4 Project schedule control 6.20
4 Project cost control 6.19
4 Project cost estimate 6.07
4 Overview of work scope 6.03
4 Project control requirements 6.01
4 Project schedule estimate 5.89
4 Project management strategy 5.58
5 Human resource management 5.53
5 Economic analysis 5.45
5 Project strategy 5.30
5 Alternatives considerations 5.27
5 Value-analysis process 5.13
5 Marketing strategy 5.01
6 Identify materials 5.89
6 Indoor rooms 5.40
6 Open space requirements 5.35
6 Windows and doors 5.34
6 Compartment requirements 5.29
6 Painting requirements 5.01
6 Storage space 4.94
Note: Responses are given on 7-point scale, from 1 (not at all
important) to 7 (very important)
Table 3. Criteria in the ANP model
Category Weight Item
Project design parameter 0.073 Structural requirements and design
Project design parameter 0.073 Architectural design
Project design parameter 0.073 Site survey
Project design parameter 0.073 Electrical and mechanical design
Project design parameter 0.073 Piping system requirements
Project plan 0.116 Owner approval requirements
Project plan 0.116 Design plan and approval
Project plan 0.116 Project design criteria
Project plan 0.116 Evaluation of adjacent building
Project plan 0.116 Purpose of building use
Site information 0.227 Fire protection
Site information 0.227 Site life safety considerations
Site information 0.227 Safety management
Site information 0.227 Safety procedures
Site information 0.227 Reliability philosophy
Project control 0.157 Project schedule control
Project control 0.157 Project cost control
Project control 0.157 Project cost estimate
Project control 0.157 Overview of work scope
Project control 0.157 Project control requirements
Project strategy 0.158 Human resource management
Project strategy 0.158 Economic analysis
Project strategy 0.158 Project strategy
Project strategy 0.158 Alternatives considerations
Project strategy 0.158 Value-analysis process
Building programming 0.268 Identify materials
Building programming 0.268 Indoor rooms
Building programming 0.268 Open space requirements
Building programming 0.268 Windows and doors
Building programming 0.268 Compartment requirements
Category Weight Ranking
Project design parameter 0.020 23
Project design parameter 0.013 28
Project design parameter 0.012 30
Project design parameter 0.018 26
Project design parameter 0.017 27
Project plan 0.020 25
Project plan 0.032 15
Project plan 0.041 8
Project plan 0.037 10
Project plan 0.041 7
Site information 0.026 21
Site information 0.035 12
Site information 0.012 29
Site information 0.024 22
Site information 0.061 2
Project control 0.033 14
Project control 0.041 9
Project control 0.027 20
Project control 0.020 24
Project control 0.029 17
Project strategy 0.054 5
Project strategy 0.034 13
Project strategy 0.032 16
Project strategy 0.029 18
Project strategy 0.036 11
Building programming 0.028 19
Building programming 0.054 4
Building programming 0.061 3
Building programming 0.050 6
Building programming 0.062 1
Table 4. Properties of the main constructs
Metric Composite GFI AGFI
reliability (>0.90 desired) (>0.80 desired)
Requirement 0.898 0.902 0.858
completeness
Project 0.924 0.904 0.850
performance
Metric CFI NFI RMSEA
(>0.90 desired) (>0.90 desired) (<0.08 desired)
Requirement 0.973 0.923 0.050
completeness
Project 0.967 0.943 0.078
performance
