Attesting Building Defect Causality Factors of The Actual Project Data and Internet Survey: A Triangulation Method on Empirical
Data Statistical Analysis
Roslan Talib1*, Mohd Zailan Sulieman2
1School of Housing, Building & Planning, Interior Architecture Program- Universiti Sains Malaysia 11800 Pulau Pinang, Malaysia
2School of Housing, Building & Planning, Building Surveying Program- Universiti Sains Malaysia 11800 Pulau Pinang, Malaysia
*Corresponding Author: [email protected]
Accepted: 15 March 2023 | Published: 31 March 2023
DOI:https://doi.org/10.55057/ijbtm.2023.5.1.19
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Abstract: The paper aims to analyse the findings of the building or the construction defects found from the mix-method research through the triangulation technique to maximise its results consistencies. Early on, the methodology approach for the study involved the mix-method option involving the collection of the actual projects’ defect data and the structured online questionnaires survey. In this paper, a triangulation method was used to increase the credibility and validity of research findings. The findings revealed a strong correlation between actual defect variables empirical input and the descriptive statistical defect census. The results also show the Likert Scale’s Google Form (LS GF) responses on the actual defects independent and dependent variables versus statistical defect census survey; tabulates on decisive co- relation causation factor between the multiple defect categories. The paper describes, identifies, and proved the critical aspect of building defects contribution factors from actual defects data collection and online census's statistical input.
Keywords: triangulation technique, triangulation analysis, triangulation approach, building defect, defects factor
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1. Introduction
Construction or building defects are among the most common causes of disputes and litigation in the construction industry. By definition, cited by (R. Bin Talib & Sulieman, 2019), a defect is a building flaw or design mistake that reduces the value of the building and causes a threatening condition. However, a construction defect can arise due to many factors, such as poor workmanship or the use of inferior materials (Fox et al., 2016) (TR Practical Law, 2019).
Therefore, it is essential to prove the probable factors resulting in building defects and re- happen. By outlining three convergence tables and three LS GF census facts on defects originated causes statistical findings compared with the selected matching online questionnaires. The same idea has been repeated for building components cases for roof and wall affecting the internal and external leakage defects.
2. Triangulation Convergence Approach on Mix-method Defects Data Collection
The main intention of producing this paper is to analyse the findings of the building or the construction defects found from the mix-method research through the triangulation technique to maximise its results consistencies. Triangulation is a method used to increase the credibility and validity of research findings (Bergman, 2014)(Ariffin, 2014). In research, having the data with the actual project’s data and actual online survey's statistical data (LS GF) can raise the quality of the convergence results. It also can donate case studies intelligence content and affect the viability prediction theories successfully.
3. Literature Research
The term 'leak' denotes to the inadvertently loss or admission of something over a hole, crack, or some other penetrability (Defects in Construction - Designing Buildings Wiki, 2020). Water leakage causes mutilation to structures and its contents reinforcement deterioration , delamination, enhanced aging and enlarged upkeep costs (R. Talib et al., 2015).Throughout history, written by (Rasdi Mohamad, 2018), builders have always been revered for their ability to mould the natural elements into something new. Perhaps something is never seen before.
The building is, therefore, a creative act on a momentous scale. For those lucky enough to be involved in construction and building scenes, (Solehah Abdul Hamid, 2010) highlighted that it is an incredible joy to bring forth from mere drawings and ideas a structure that will stand for many lifetimes.
4. Building defects causal factor
In the construction process (pre or post-construction stage), (R. B. Talib & Sulieman, 2020) stated that the regularity of the building defects could be a nightmare to the builder or the maintenance team. The first three census parts identified the factors that typically triggered most defects and touched on its primary causal factors. The last three part of the analyses experimented on the LS GF statistical content on components of leakage defects tabulation.
Identify quality goals for the defect causal analysis team can emphasise the importance of translating recommendations into action later (on the analysis findings part).
5. Methodology -Qualitative and Quantitative Method Approach
In advance, the methodology approach for the study involved the mix-method option involving the collection of the actual projects’ defect data and the structured online questionnaires survey.
In this paper, a triangulation method was used to increase the credibility and validity of research findings. Three main census measurement categories have been identified as below: -
• Most defect attributer factors
• Main defect causal factors (building components attribution)
• Identify on minimizing defect affect factors
Qualitatively, a total of 17,995 actual defects has been accumulated from the actual construction projects; new or refurbish been table-up. The use of qualitative research can complement the actual collected defect’ project data. It is the bridge that helps to understand the parameters that drive survey replication results. On the other hand, the quantitative research method with 86 respondents (n=86) replied through e-mail correspondences has been done.
Generally, quantitative methods provide summaries of data that support generalizations about the phenomenon under study (Zein et al., 2019). The study used 5 Likert-scale (L.S.)
questionnaires developed from the cognitive research tabulation in designing the survey questionnaire related to defects causal hypotheses. (Abowitz & Toole, 2010) (Chyung et al., 2017) indicated appropriate statistical analysis could be derived from testing the hypothesis that ordinal in the format as Likert Scale does. The method is widely integrated with survey questionnaires as the Likert rating scale (LS) featured.
6. Triangulation Technique and the Convergence Exercise
Building a cause-effect Excel diagram (the first three Excels) identifies and defines causal analysis of defects crisscrossing with qualitative and quantitative collected data empirical statistics. Next, the triangulation procedure has been used as a convergence technique to increase the credibility and validity of mix-method research findings (Abowitz & Toole, 2010) (Wald, 2014). By combining theories, methods, or observers in a research study, the triangulation idea can help ensure that fundamental biases arising from the use of a single method or a single observer are overcome. The same method approach has been done for the last three SPSS tables outlying the mix-method convergence similarities factual census facts.
7. Results and Discussions -Future Defects Problem (Why it still exists?) - Tasks Inspection + Google Forms Survey - (Table 1)
As further analysis of the triangulation convergence survey, this particular census deals with the current and future building defects that may arise and still retain on in the list in the future expected and projected by the researchers. The statistic indicated that qualitatively, 1,209 total defects found from the six identified building components and eight dependent variables (see Table 1). The variables ranging from lacking design innovation, specification and detailing to unfollow the building's occupancy requirement.
As far as the quantitative part is concerned, 13 identified questionnaires have been selected having the same defects factors concerning the qualitative part to be analysed. Qualitatively, the lack of a creative method to solve defects is the highest variable found with 234 cases.
Next, with 216 cases, the problem with using unskilled foreign labour come second. In comparison, the 3rd rank with 198 cases from the variable on using non-quality material leads to potential defects.
Furthermore, 364 defect cases found on the roof related problem, next with 216 cases on defects problem found at the internal wet areas, and the 3rd in the list with 137 cases on defects originated from the internal wall shows how bad are the defects accumulated. Quantitatively, three questionnaires having among the highest respondents (ռ=86), which are SB2, Q19c, SC1, Q49 and SB2, Q27 reporting how 'YES' triangulation convergence was easily proved on the said defect’s issues. With all the 13 questionnaires matching perfectly with the eight defects factor categories, the mix-method triangulation converged strongly to prove that considering the future defects factors negatively impacted the quality of the building's construction. One way or the other, C.D.B. (Central Database) is very important to accumulate all the defect factors in one single database for the industry players to be able to look into from repeating the defect mistakes. Now, it is time to do it.
Table 1: Triangulation Convergence Table on Factor attributing to building defects existence-Qualitative from real projects versus Quantitative from Online survey.
7.1. Latent and Non-Latent Defects on Roof and Skylight (Roofing components) (1) and Door, Window, Floor & Structure (Non-roofing components) (2) – Real Projects + Google Forms - (Table 2 and Table 3)
A latent construction defect can be explained wherein construction contracting; a latent defect is defined as a defect that exists at the time of acceptance but cannot be discovered by a reasonable inspection (Assaf et al., 1996). By definition, a latent defect is a type of construction defect hidden and may even go unnoticed for years. (Ali & Wen, 2011); yet, it is still provable
in court and can cause damage to the construction business. For this section, the author had chosen the latent and non-latent defects detection tabulation from W.S.C. (Waterproofing Specialist Contractor) real projects, which had 42 dependent variables from 11 main dependent variable categories (see Table 2). Among the identified variables from the qualitative measure are the roofing component itself, roof tiles, skylight, and the walls, groundwater and wall paint defects. However, only six variables have been selected to match the 12 questionnaires identified reflecting on the same issues. Roofing defects with 318 of the total 1,055 cases is top in the list, while external and internal wall variables score 290/1,055 defect cases at no.2 position. Quantitatively, three questionnaires dominated on the issues which are SB1/ Q10 (on the roof), SB1/ Q10 (on the wall) and SB1/Q10 (on the wall again) received 61 respondents (from ռ=86) on "Strongly Agree' on all three questions.
The triangulation convergence test results in only two scenarios with 'NO' result, which is on the skylight and under-floor moisture defects (see Table 2), while the other ten triangulation figures (in Yes result) all match. The triangulation result in Table 3 on the window, door, floor and structural components revealed the same result as in Table 2. Overall, the test revealed that regardless of the many defects found on the real projects tabulation, either they are latent or non-latent; when the triangulation was done with the matching, particular online survey questionnaires, 83.3% of the result agreed that the defects problem is in a dire state. 42 detail building components can let the defects can be produced and this condition is supported by the online survey with related questionnaires (ռ=86) that has been done.
For information, Section 6A (3) of the Limitation (Amendment) Act 2018 provides that no action can be commenced 15 years after the occurrence of the latent defect even if knowledge of the latent defect was obtained during or after the 15 years. However, contractors often believe that the latent defects are no longer their responsibility after the job is handed over to the employer or subsequent owner. Consequently, the construction players are better reminded that it is easier to stop something happening in the first place than to repair the damage after it has happened. It is similar to the Dutch Northern Renaissance philosopher's Desiderius Erasmus quote say "prevention is better than cure”.
Table 2: Triangulation Convergence Table on Factor affected Roof & Skylight (latent and non) defects- Qualitative from real projects versus Quantitative from Online
Table 3: Triangulation Convergence Table on factor affected Door, Window, Floor etc. defects - Qualitative from real projects versus Quantitative from Online survey
7.2 Construction Minimizing Building Failures – Real Data + Google Forms - (Table 4) Additionally, again, (Boton & Forgues, 2017) figured triangulation is the route of confirming the results of a study through two or more methods to crisscross its reliability and validity. The triangulation approach can be relevant to both qualitative and quantitative research studies. For the cases as in Table 4, eight out of 13 goals agreed with the defect’s improvement variable percentage goals, representing 61.53% (8/13) of the survey. This showed a firm agreement
with the factor hypotheses in reducing building defects. A further of 5 respondents vote for a Neutral stand for the matter. Remember that it is never too late to change the attitude (in alerting building defect effect) (no matter what age the players are) and live differently. Yes, everyone can!
Table 4: Triangulation on Setting-up goals to minimise building defects in L.S. survey ranking.
Not really mentioned (or Neutral) of
response in L.S. survey
Agree or Strongly Agree response in L.S.
survey Need to have a fast track and shorter
construction period
0.0% 100.0%
Target on defects free buildings syndrome
0.0% 100.0%
Preventing regular and irregular flooding.
100.0% 0.0%
Minimise and avoid buildings vandalism 0.0% 100.0%
Avoid misguided application of waterproofing/sealant materials
0.0% 100.0%
Fulfil unexpected user requirement 0.0% 100.0%
Simplify complex framework on the construction industry
100.0% 0.0%
Avoid the cheapest bid to win the tender may lower work quality.
100.0% 0.0%
Improved feedback from industry players.
100.0% 0.0%
Improved construction drawing details. 0.0% 100.0%
Regular job training on a defects maintenance program.
0.0% 100.0%
Produce and make available a proper defects avoidance guidance checklist.
0.0% 100.0%
Introduce more sophisticated building systems (i.e. I.B.S.) to avoid defects.
100.0% 0.0%
7.3 Exterior-Leaking to Blistering – Real project Data + Google Forms -(Table 5)
Table 5: Triangulation Convergence Table on Building External Components list -Qualitative from real projects versus Quantitative from Online L.S. survey
RESPONDED IN DISAGREE AND STRONGLY DISAGREE SCALE IN
LS SURVEY
RESPONDED IN NEUTRAL SCALE IN LS
SURVEY
RESPONDED IN AGREE AND
STRONGLY AGREE ON SCALE IN LS
SURVEY
EXT 1-Foundation 0.0% 0.0% 100.0%
EXT2-Landscaping - tree, weed 0.0% 0.0% 100.0%
EXT3-Roof 0.0% 0.0% 100.0%
EXT4- Gutter and downspouts 0.0% 0.0% 100.0%
EXT5-External brick wall 0.0% 0.0% 100.0%
EXT6- External concrete wall 0.0% 0.0% 100.0%
EXT7-External timber siding 100.0% 0.0% 0.0%
EXT8-External water tank 100.0% 0.0% 0.0%
EXT79-Air-Cond.itioning piping
0.0% 0.0% 100.0%
EXT10-Door 0.0% 0.0% 100.0%
EXT11-Window 0.0% 0.0% 100.0%
EXT12-Balcony/deck 100.0% 0.0% 0.0%
EXT13-Planter box 0.0% 0.0% 100.0%
EXT14- Roof top swimming pool
0.0% 100.0% 0.0%
Table 5 resulted in having 8 out of 14 external variables factor agreeing or Strongly Agree on the building component variables letting most of the building defects. The analysis revealed further with 1 clicked on Neutral result while three went for Strongly Disagree and disagree mode upon the task. The idea is that more building components still giving and having a problem with the defects matter and require further devotion to limit them.
7.4 Interior –Leaking to Blistering - Google Forms - (Table 6)
Table 6: Triangulation Convergence Table on Building Internal Components list -Qualitative from real projects versus Quantitative from Online L.S. survey
RESPONDED IN DISAGREE AND
STRONGLY DISAGREE SCALE
IN LS SURVEY
RESPONDED IN NEUTRAL SCALE
IN LS SURVEY
RESPONDED IN AGREE AND STRONGLY AGREE
ON SCALE IN LS SURVEY INT 1-Wet areas, i.e. Toilet, shower,
wuduk., kitchen 0.0% 0.0% 100.0%
INT2-Floor/Concrete/Timber,
Linoleum/ Tiled 0.0% 0.0% 100.0%
INT3-Internal brick wall 0.0% 0.0% 100.0%
INT4-Internal concrete wall 0.0% 0.0% 100.0%
INT5-Internal timber, gypsum etc. wall 0.0% 100.0% 0.0%
INT6-Ceiling 0.0% 0.0% 100.0%
INT7-Fire protection system - sprinklers, alarms, fire distinguishers, smoke detector, etc.
0.0% 0.0% 100.0%
INT8-Lift-pit 0.0% 0.0% 100.0%
INT9-Boiler's room 100.0% 0.0% 0.0%
INT10-Pump-sum 100.0% 0.0% 0.0%
INT 11- Internal water tank 100.0% 0.0% 0.0%
As far as the building's interior is a concern within the concerning perimeter of this research, as tabled in Table 6, again, the highest response received with seven votes on 100% agreeing and Strongly Agree the said interior building components variable allowing defect leakage.
One result for Neutral response while three votes 100% disagree or Strongly Disagree with the said variables permitting defects can happen. Thus, converging this qualitative interior data and merging it with the online quantitative survey analysis end up that construction players must pay further thoughtfulness to the 'interior' building component to reduce the defects problem.
8. Conclusion
In summary, the triangulation approach analysis highlighted that the six analytic census findings on building defects dependent variables hypotheses were approved to be correct.
Furthermore, the convergence analysis resulted in eighteen census tabulations of the same
variables (on defect originated) only two record on the un-converged outcome (on skylight and underfloor moisture). Next, the triangulation convergence analysis reported that all thirty-eight qualitative data on actual defects causal factors converged accordingly with the five variables LR) on repeat defect causal factors (on the quantitative side data). This first part measured 91.66% (22 of 24 variables) readings on YES variables to the census. Lastly but not the least, the second part of convergence analysis revealed that the internal and external defects data empirically as collected data tabulation duplicate nicely with the quantitative L.S. online correspondents' questionnaires on the same defect categories (which on to minimize defect causal factors). For this case, only six part (out of thirty-eight sample test lists) are not well converged, which is on water-tank and timber siding leakage issues. Statistically, however;
68.42% of LS respondence records on the YES factor with 26 out of 38 positive outcomes.
Overall, the triangulation convergence analysis carried out the use of multiple methods or data sources in qualitative and quantitative research developed a comprehensive understanding. It allows one to identify the defects causal aspects of defects originated phenomenon more accurately by approaching it from different vantage points using different methods and techniques. Building defect is a few of the main elements of building difficulties that demands considerable attention. Triangulation technique analysing the factual data on its causal upon the building identified components is substantial evidence from statistical measurement reading point of view.
The study hopes for the industry players to develop a zero-defect culture of reducing and preventing defects throughout the building construction process. Defect prevention is much more efficient and effective in reducing the number of defects and also is very cost-effective to fix the defects.
Acknowledgement
This is to acknowledge on own author financial contribution to cover the paper publication fee in ensuring the paper can be published successfully.
Ethical approval
This research content received ethical approval from UNIVERSITY RESEARCH ETHICAL (HUMAN) COMMITTEE through approval letter no.: U.S.M./JEPeM/20010066 dated 27 May 2020.
Disclosure statement
The authors reported no potential conflict of interest.
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