Assessment Attributes on Effective Construction Management for Property Developers in Malaysia

Malaysia has shown very rapid growth in property and construction since the 1970s. The competition among property developers has created major changes in the construction industries mainly in the design and infrastructure, in order to satisfy the needs of the property buyers. Eventually, the capability of property developers varies. Project management, including the tools, techniques, and knowledge-based practices applied to manage the creation of products and services, is becoming an increasingly accepted and applied discipline across industry sectors (Jugdev et al. 2007). Adoption of project management is used as ‘a method’ for solving complex organizational problems. Such a viewpoint treats project management as one of the several ways of handling organizational activity. Similar arguments and standpoints are found in numerous project management research texts (Söderlund 2004).

Malaysia has shown very rapid growth in property and construction since the 1970s.The competition among property developers has created major changes in the construction industries mainly in the design and infrastructure, in order to satisfy the needs of the property buyers.Eventually, the capability of property developers varies.Project management, including the tools, techniques, and knowledge-based practices applied to manage the creation of products and services, is becoming an increasingly accepted and applied discipline across industry sectors (Jugdev et al. 2007).Adoption of project management is used as 'a method' for solving complex organizational problems.Such a viewpoint treats project management as one of the several ways of handling organizational activity.Similar arguments and standpoints are found in numerous project management research texts (Söderlund 2004).
Research on Critical Success Factors (CSFs) in the construction industries were mainly based on theoretical rather than empirical evidences (Khosrowshahi & Howes 2005).But, what is the extent of expectation that could be obtained from CSFs?The outcome of this study is therefore to determine the measurement arrays as attributes in developing an effective costruction management (CM) assessment for property developer in Malaysia.

Assessment Attributes on Effective Construction Management for Property Developers in Malaysia Literature Review
CSFs has been defined as a tool to identify executive information needs (Rockart 1982).Rockart et al. (1979) identified four prime sources of CSFs in any industry, which are: (1) Structure of the industry: has its own set of CSFs which are dependent on its characteristics; (2) Competitive strategy, industry position and geographic allocation: each organization has its own strategies and strategic plan due to the nature of the industry in which it operates; (3) Environmental factors: the effects of the environment upon the organization behaviour are essential to understand the CSFs; (4) Temporal factors: CSFs changes with the change of the organization priorities, where the areas of activity for success changes and some activities become more critical and others become less critical (Elwakil et al. 2009).
In Managing Information Systems, CSFs examine their existing methodologies, and from time to time, CSFs has been widely used by other industries, including the construction industry.In the construction industry, CSFs are integrated with eight elements that are used as benchmarking parameters which are: structure of industry; competitive strategy; market conditions; political environment; organizational structure; technical applications; employee enhancements and process benchmarking (Rockart 1982;Sanvido et al. 1992;Abraham 2003).Success is defined by Ashley et al. (1987) as 'results much better than expected or normally observed in terms of cost, schedule, quality, safety and participant satisfaction'.The investigation of success factors in construction industries have attracted the interest of many researchers and many studies have been conducted with the aim of providing valuable insights into how to consistently achieve superior results for the projects.Although construction projects are by their nature repetitive activities, each one has its own characteristics and circumstances (Salleh 2009).Chan (2004) identified five primary CSFs from 44 identified factors, which are: projectrelated factors; project procedures; project management actions; human-related factors and external environment (Yong & Mustaffa 2011;Doloi et al. 2011) established attributes that relate to schedule and performance, listing 55 attributes that were subsequently grouped into six CSFs and seven Critical Failure Factors.Those factors are project managers' competence, supportive owners, top management monitoring, feedback, and co-ordination.Love et al. (2002) identified 55 attributes and grouped them into five CSFs for public-private partnership projects in the United Kingdom.The five categories were: effective procurement; project implementation ability; government guarantees; favourable economic conditions, and the available financial market.Abraham (2004) identified seven CSFs that influence the success of construction industries which are: competitive strategy; market analysis; political environment; economic environment; technical application; employee/ organizational enhancement and process benchmarking.Saqib (2008) listed the top five CSFs affecting the construction industries in Pakistan, developed from 77 identified factors which are: contractor-related factors; project management factors; procurement-related factors and design team-related factors.Marc Hockins (Stolton & Leverington 2006) proved that CSFs are the best methodology to develop an executive monitoring system to contain corporate-wide indicators of success (Elwakil et al. 2009).In this study, the function of CSFs is reversed by using attributes obtained from the questionnaire survey conducted.

RESEARCH METHODOLOGY
In order to achieve the objective of this study, a questionnaire survey was distributed among the practitioners in the construction industry which included government sectors, consultants, property developers, contractors and others (suppliers, manufacturers, planners and others.).The questionnaire contained 37 nominated success factors for property developers.It was developed from an extensive literature review and was consolidated by a series of pilot studies conducted in several states of Malaysia.
Five hundred sets of questionnaires were distributed within Malaysia.The distribution was categorized into few regions which consisted of the central region (Selangor and Kuala Lumpur), northern region ((Pulau Pinang, Kedah, Perak and Perlis), eastern region (Kelantan, Terengganu and Pahang), southern region (Negeri Sembilan, Melaka and Johor) and East Malaysia (Sabah and Sarawak).Data were collected and analyzed using Factor Analysis in statistics via SPSS (V.20).The Factor Analysis technique used was Principal Component Analysis (PCA) where effective variables are used to identify the principal factors.This techniques enables a more in-depth understanding of factor grouping techniques to underpin the success measures (Robinson et al. 2005).PCA can also be used for hypothesis testing or in searching for constructs within a group of variables (Sommerville et al. 2004).It is a series of methods for finding clusters of related variables and hence an ideal technique for reducing a large number of items into a more easily understood framework (Norusis 2008).Since the numbers of variables for CSFs for pre-determined attributes were about 37 numbers, Factor Analysis was used in this study, to converge these numbers to make it more reliable.
In order to determine the validity of the questionnaire developed in this study, Cronbach's alpha was tested to provide an accurate estimate of internal consistency and indicates how well the items in the set were correlated to one another (Brown & Adams 2000).The internal consistency ranges between zero and one.A commonly-accepted rule of thumb is that scores of above 0.70 are considered acceptable (Nunnally 2010).In this study, Cronbach's alpha was computed at 0.791 which indicated that the items were in the form of a scale with reasonable internal consistency reliability.

Response Rate
A total of 344 questionnaires were satisfactorily completed, resulting to a total response rate of 68.8%.This is acceptable as according to Takim et al. (2004) and Peansupap et al. (2005); they stated normal response rate in the construction industries for postal questionnaires is approximately between 20% to 30%.The General Respondent Demographic showed that the majority of the respondents (48.3%) were from property developers as shown in Table 1.
The questionnaires were distributed to all practitioners in the construction industries in Malaysia.Based on Table 1, it was found that the highest respondents were property developers (48.4%), followed by contractors (20.6%), consultants (14.2%), the government sector (12.5%) and others (4.4%).

Ranking of Critical Success Factors
The first analysis was performed to rank the nominated factors based on the mean values of the responses.In this study, it was assumed that if two or more factors happen to have the same mean values, then the one with the lowest standard deviation would be assigned as the highest important rank among the nominated factors.In addition, factors with means exceeding or equal to the value of four are recognized as CSFs based on the consensus of the respondents.In this study, 15 factors were identified as CSFs having significant influence on the success of this study.Table 2 shows the ranking of these factors according to the value of their statistical means.
The CSFs identified in this study were largely in line with the findings of other researchers in the field of CSFs.Nevertheless, unlike other studies on CSFs, this study led to the refinement of the assessment attributes that would ensure affective construction management in Malaysia.

Factor Analysis
In this study, Factor Analysis is used to explore and detect the underlying relationships among the identified CSFs.This statistical technique identifies a relatively small number of factors that can be used to represent relationships among sets of many interrelated variables.Various tests are required for the appropriateness of this method for factor extraction.
In this study, 37 numbers of CSFs were obtained as shown in Table 3 subjected to Factor Analysis using PCA and varimax rotation.PCA is a common method in Factor Analysis.It involves the generation of linear combinations of variables in Factor Analysis so that the variance present in the collected data are considered.This analysis summarizes the variability in the observed data by means of a series of linear combination of 'factors'.Each factor can be viewed as a 'supervariable' comprising a specific combination of the actual variables examined in the survey.
The advantage of this method over other factor analytical approaches is that the mathematical representation of the derived linear combinations avoids the need for the use of questionable causal models (Johnson & Carter 1993;Shen & Liu 2003).

Interpretations of the Components Group
In this study, eight numbers of group components were extracted using varimax rotation Factor Analysis.In accordance to Burgees (2006), based on Factor Analysis output for factor loading the results on all attributes could be defined as very high (0.6), high (0.3), and ignored (less than 0.3) (Kozak-Holland & Procter 2013).In this study, Factors Analysis was used to converge the 37 numbers of identified CSFs into eight groups.Out of the 37 attributes established in this study, 13 were eliminated due to the result obtained from Factor Analysis which was below 0.3 (less impact).It was found that CIM was the highest group component.For future work, the correlation rank at each element of the group components will be further investigated and defined using the Structural Equation Method.

Date of submission: August 2014
Date of acceptance: November 2014

Table 1 .
Respondent to questionnaire based on General Respondent Demographics.

Table 2 .
Ranking of success factors based on 'Mean' value.

Table 3 .
Factor analysis at each group component

Table 3 (
Cont.).Factor analysis at each group component

Table 3 (
Cont.).Factor analysis at each group component CONCLUSION This study identified and analyzed the possible assessment attributes on effective CM for property developers in Malaysia.Identification of CSFs were used as measurement tools to determine its effectiveness.The findings of this study were generally in line with the earlier studies performed on CSFs which have been established by other articles in journals.Nevertheless, the findings of this study further enforced the results obtained from CSFs analysis and established the assessment attributes.