Factors affecting the productivity of building craftsmen--studies of Uganda.
Keywords: labour, productivity, factors, developing countries, building sector, craftsmen.
VEIKSNIAI, LEMIANTYS STATYBOS DARBININKU DARBO NASUMA (UGANDOS PAVYZDYS)
Menkas statybos imoniu darbininku darbo nasumas yra viena is priezaseiu, lemianeiu statybos projektu pinigu ir laiko nuostolius. Darbo jegos nasumas yra ypae svarbus besivystaneiose salyse, kur dauguma statybos darbu atliekama rankomis. Siame straipsnyje pateikiama pastatu projektu darbu vadovu apklausa Ugandoje, kur ypae siekiama didinti darbininku nasuma. Respondentu buvo prasoma, naudojantis savo patirtimi, pateikti 36 veiksnius, kurie lemia nasuma atsizvelgiant i laika, islaidas bei kokybe. Si apklausa buvo daroma anketomis, ir visi atsakymai buvo gauti per 3 menesius. Buvo isskirta desimt pagrindiniu veiksniu, lemianeiu darbo jegos nasuma, t. y. nekompetentingas vadovavimas, darbininku igudziu stoka, klaidu taisymas, irankiu (irangos) trukumas, pasene statybos metodai, bloga informacijos perdavimo sistema, netikslus breziniai, darbu stabdymas del konsultantu, politinis nesaugumas, irankiu (irangos) gedimas, prastos oro salygos. Nors mediagu stoka yra vienas is labiausiai gaisati lemianeiu veiksniu, taeiau, naudojant reiksmingumo indeksa, i kuri ieina laikas, islaidos bei darbo kokybe, tarp desimties isvardytu veiksniu nepateko. Politikai ir mokslininkai turetu daugiau demesio skirti nustatytiems veiksniams, kad geretu statyboje dirbaneiu darbininku darbo nasumas.
Reiksminiai zodziai: darbo jega, nasumas, veiksniai, besivystaneios salys, statybos sektorius, darbininkas.
Construction industries in many countries are greatly concerned about a low level of productivity [1, 2]. Poor productivity of craftsmen is one of the most daunting problems that construction industries, especially those in developing countries, face . Although some research has been carried out on productivity of construction craftsmen in developing countries [3, 4], there are still gaps to be filled.
The construction industry in Uganda constitutes over 12% of the gross domestic product and has witnessed a steady growth for the last 20 years . In developing countries, building construction consumes about 70% of the construction investment [6, 7]. The situation in Uganda is not different. The majority of construction workers are employed on building sites as civil engineering works are to a large extent mechanised. Hence the emphasis of this research is on labour productivity on building sites. It is assumed that any effort directed to improving productivity will greatly enhance the country's chances to realise its development goals.
The building industry in Sub-Sahara Africa has unique characteristics. To mention only a few, building is labour intensive as it is largely in situ; the workers are exposed to extremes of hot and wet weather conditions; the pay incentive structures are poor; the working environment is hazardous. The major task currently being addressed by the Uganda National Association of Building and Civil Engineering Contractors (UNABCEC) is how to increase construction productivity , hence the need for this research.
The construction industry in Uganda suffers from cost and time overruns . Overruns in the construction industry are indicators of productivity problems. Improving construction productivity will go a long way towards eliminating time and cost overruns . Identifying and evaluating the factors that influence productivity are critical issues faced by construction managers . Some research on factors that affect productivity in developed countries has been carried out [12-14]. Strategies for performance improvement in those industries have been identified and implemented mainly basing on the identified key factors. The critical factors in developed countries are different from those in developing countries. For instance, while addressing the problem of supply of materials, Polat and Arditi  have found out that contractors in developing countries stock excess materials just-incase, while the trend in developed countries is for materials to deliver just-in-time. It is therefore important that factors affecting productivity in Uganda's building industry are well identified so that efforts can be made to improve the situation. However, the results from earlier research were based on perceived effect with regard to time only. For example, the Importance Index used by Lim and Alum  is based on the frequency of encountering the factors. The three common indicators of performance in construction projects are time, cost and quality  and all these factors should be included in assessing productivity in order to get a better picture. Having different indicators of productivity is in line with the paradigm of Key Performance Indicators .
Some researchers have voiced their concerns about continued declining performance of the construction industry and the increasing challenges [18-20]. To deal with the situation, many companies have adopted different philosophies to reverse the trend such as lean construction that should have some significant effect on performance, productivity and profitability . However, some researchers believe that the payback of these improvement approaches in the construction industry has been small compared to the investment . This leaves the construction companies in the developing world at a loss. The objective of this study is to identify and rank the major factors that affect the productivity of craftsmen in Uganda. The goal is to have an appropriate strategy for building contractors to improve the productivity of craftsmen.
Responses were solicited from project managers of building contractors in Uganda through a questionnaire survey. All building contractors registered with the national contractors' association were targeted to provide one project manager who would participate in filling in the questionnaire. A response rate of 53% was achieved. The survey found out that incompetent supervisors, lack of skills, rework and lack/breakdown of tools and equipment are the main factors that lead to a low productivity of the craftsmen within the building industry in Uganda when time, cost and quality are factored in. Lack of materials is the main factor that leads to a low productivity from the perspective of lost time and frequency of occurrence.
The arrangement of this article is that after this introduction, there is a section on literature review of productivity, then a section on methods is provided. There follows a section on results and discussion and lastly conclusion.
2. Productivity problems
Although some research has been carried out on factors influencing productivity, there is still a lot to be done even in developed countries . To improve productivity, the impact of each factor can be assessed by statistical methods and attention given to those particular parameters that adversely affect productivity . Previous studies looked at the construction industry as a whole, yet the majority of the workers are employed on building sites. Most civil engineering projects are mechanised.
Various factors have been identified by different researchers from the time aspect in different construction industries. Lack of materials, incomplete drawings, incompetent supervisors, lack of tools and equipment, absenteeism, poor communication, instruction time, poor site layout, inspection delay and rework were found to be the ten most significant problems affecting construction productivity in Thailand . Kaming et al  found out that lack of materials, rework, worker interference, absenteeism, and lack of equipment were the most significant problems affecting workers in Indonesia. Olomolaiye et al  found that the five most significant factors in Nigeria are lack of materials, rework, lack of equipment, supervision delays, absenteeism, and interference. Lack of materials, weather and physical site conditions, lack of proper tools and equipment, design, drawing and change orders, inspection delays, absenteeism, safety, improper plan of work, repeating work, changing crew size and labour turnover were found out to be the most critical factors in Iran . Lim and Alum  found that the major problems with labour productivity in Singapore are recruitment of supervisors, recruitment of workers, high rate of labour turnover, absenteeism at the workplace, communication with foreign workers, and inclement weather. Yet Lema  through a survey of contractors in Tanzania found out that the major factors that influence productivity are leadership, level of skill, wages, level of mechanisation, and monetary incentives. Motwani et al  found out through a survey in USA that five major problems that impede productivity are adverse site conditions; poor sequencing of works; drawing conflict/ lack of information; searching for tools, materials, and poor weather. By the literature cited above, there are various factors that affect productivity to different levels in different industries. However, lack of materials comes out as a common problem among the critical ones. The experience of the authors is that most building sites in Uganda normally have stocks of different materials on site and as such may be not the most critical problem.
It is important to note that the questionnaires and ranking used in the studies before were based on time aspect of frequency of occurrence. However, quality and cost are equally important in assessing the factors that affect productivity. Craftsmen can deliver varying quantities of work but the quality and cost should be acceptable. Rosefielde and Mills  argued that any measure of construction productivity that does not account for the changes in design and quality would lead to low, if not negative, measures of construction productivity. Hence there was need for this research to capture effects of time, cost and quality, since contractors in Uganda are trying to address the problems of low productivity.
3.1. Research method
Fellows and Liu  highlight five research styles: experiment, survey, action research, ethnographic research and case study. Research in construction is usually carried out through experiments, surveys or case studies . Experiments on factors that affect labour productivity in the building industry would take a long time to yield results and they are difficult to control and would therefore be expensive. Case studies would not provide results that are easy to generalise as different companies face different problems. Surveys through questionnaires were found appropriate because of the relative ease of obtaining standard data appropriate for achieving the objectives of this study.
Surveys are one of the most frequently used methods of data gathering in social research. The survey protocol of random sampling procedures allows a relatively small number of people to represent a much larger population . The opinions and characteristics of a population can be explained by a representative sample. Surveys are an effective means to gain a lot of data on attitudes, on issues and causal relationships and they are inexpensive to administer. However, they can only show the strength of statistical association between variables and they provide no basis to expect that the respondents correctly interpret the questions.
3.2. Questionnaire design
Factors affecting the productivity of craftsmen were identified through the literature based on previous research [2-4, 10, 16, 23-25]. A total of 36 factors were identified. The project managers were required to rate the factors in the way they affect productivity in relation to time, cost and quality using their own experiences on building sites. The questionnaire required the respondents to rank their answers on a Likert Scale  with the rating of "0" representing no effect; "2" slightly significant effect; and "5" very big effect on labour productivity for each of time, cost and quality separately. The survey package comprised a covering letter, the questionnaire and a pre-stamped self-addressed envelope.
3.3. Pilot studies
Pilot studies were carried out to ensure the clarity and relevance of the questionnaire to contractors. The questionnaire was shown to two researchers in the same field. Based on their feedback, amendments were made and the second phase of the pilot study was conducted on four building project managers among those who were not going to participate in the final survey. Based on the feedback, minor amendments were again made to remove any ambiguities and discrepancies. This pilot study was conducted to validate and improve the questionnaire, in terms of its format and layout, the wording of statements and the overall content. The draft questionnaire was revised to include the suggestions of these participants. In short, the questionnaire was validated through this process and provided the authors with improvement opportunities before launching the main survey.
3.4. Sample selection
The survey gathered data from project managers of building contractors from as broad a geographic area within Uganda as possible. For this purpose, it was determined that all contractors who registered with the contractor's association participate. The target population of contractors was 167, those registered with the contractors' association, UNABCEC, and engaged in formal building work. At the national level, one recognised way of categorising construction companies is by the UNABCEC grade. The classification from A to E takes into account the financial strength, size and ability to carry out jobs. Those in class A are the biggest and undertake works of the biggest magnitude and include some multinational companies. At the time of the survey, UNABCEC had a membership of 189 including civil engineering contractors. For the purposes of this survey, the mailing lists of all those who were engaged in building construction during the year 2005 were used. The chief executive officers were asked to provide one project manager to make a response. A total of 159 questionnaires were sent out. For varied reasons, 22 could not participate. The sample size therefore reduced to 137. The survey was carried within a period of 3 months from mid-July to October 2005.
3.5. Survey response
As a result of mailing and follow up, a total of 73 usable questionnaires were completed and returned. The distribution in the various grades of the 137 who were contacted and the 73 who responded is given in Table 1. A review of the responses from the national surveys indicated no measurable differences in the respondents' answers. All the questionnaires were therefore combined for the survey analysis.
The respondent project managers have been in the construction industry for a period with both mean and median of 6 years. The total time the respondents have spent in the construction industry has a mean of 11 years and a median of 9 years. 95% have either degrees or diplomas in engineering, architecture or quantity surveying. This means that they are generally well educated and have ample experience in the construction industry. The mean number of craftsmen employed on salary terms at the respondents' sites is 31. The mean number of casual workers was 96 but this varies with the amount of work at hand. At the time of the survey, the ratio was about 1:3 of salaried craftsmen to casual ones. All the tradesmen on permanent terms have some training, through either technical vocational schools or on-the-job.
Of the companies that provided responses, 74,6% have local majority share capital while 4,2% have all foreign share capital and 12,7% have majority local share capital and 8,5% have majority foreign capital. It can be concluded that the companies have got a range of ownership status and also possibly different management styles. 67,1% of them keep data on productivity while the rest do not. 85,7% of the respondents replied that they develop the data in-house. 12,2% share data on labour productivity with other companies and only 1,2% share data with companies outside the country. 85% of the companies replied that they monitor and control labour productivity. The majority of the project managers at 57,6% have the perception that labour productivity is low. Those who believe that productivity is satisfactory make 37% and only about 6% believe that labour productivity is good.
4. Results and discussion
4.1. Data analysis and results
The average rankings were calculated basing on 4 different criteria: mean ratings for effect on time; effect on cost; effect on quality and combined importance index. The means for time, cost and quality were calculated using the formula
[R.sub.m] = [SIGMA][R.sub.x]/I; x = time, cost or quality, (1)
where [R.sub.m] is the mean rating with respect to time, cost, or quality from the "I" number of raters. [R.sub.x] is the rating given by the respondents.
The mean combined importance index from the rankings was calculated using the formula
I = [SIGMA][R.sub.t]x[R.sub.t]x[R.sub.q]/[Nx[M.sup.3], (2)
where [R.sub.t] is the rating basing on time, [R.sub.c] is the rating on cost and [R.sub.q] is the rating on quality. Table 2 gives the summary of the calculated mean values for the different factors and also their ranking within the groups.
This section contains the results from the ratings as given in Table 2 and a discussion about the factors. There follows a section on analysis of the reliability of the ratings obtained from the survey. Discussion is made on the ten highest ranked within the category of overall ranking and five highest ranking in terms of time, cost and quality where they are not yet dealt with. The assumption is made that the highest ranked have the greatest influence in line with Pareto rule. The highest ranked according to the Overall Importance Index are: incompetence of supervisors; lack of skills of the workers originating from inexperienced poorly trained workers; rework eg from poor work done; lack of tools/equipment; poor construction methods including poor sequencing of work items; poor communication which includes inaccurate instructions; inaccurate drawings; stoppages because of work rejected by consultants; political insecurity, for example, insurgency, wars, and risk; tools/equipment breakdown; harsh weather conditions.
The factor of materials shortages and delays is ranked first in terms of time only. This is similar to what was found out in earlier research [3, 4, 24]. However, basing on the overall Importance Index, it is ranked seventeenth. Material shortages consume a lot of the contractors' time but the effect of cost and quality is relatively lower. The main cost incurred due to shortages is for the idle time that craftsmen have to wait for materials. But since a good number are employed on short contracts and casual terms, it implies that when there are no materials, they can also afford to wait without transmitting extra costs to the contractor. The factor of Incompetent supervisors is rated highest on the overall Importance index. This could be partly because supervisors do not attend refresher courses. Most of the supervisors are trained but their formal training stops when they leave school. There are also a good number of supervisors who have only attained on-the-job training. Those may not be well versed with many requirements of supervision. There is therefore need for continuous training of the supervisors. The other issue is that they may not be well facilitated to do their work. Incompetence of supervisors affects many other factors.
Lack of skills is a major problem and seriously affects the time to accomplish tasks, the cost of labour and the quality of products achieved. The hope is that since the government of Uganda is promising to introduce technical schools at all sub-counties, the right skills will be developed in future but this will take some time to have impact on the industry. As the government introduces universal secondary and technical training, it is necessary to make needs assessment and to identify the key trades and right numbers to train if the situation is to change. On-the-job training through which the majority of skilled workers pass should be studied with a view to improving it and possibly formalising it so that those that have been trained obtain certificates. Rework is rated third overall on Importance Index. It is ranked second, first and seventh against time, cost and quality respectively. It is mainly caused by failure to follow specifications. Specifications should be made clear and explained to the executing team to avoid rework. Repetition of instructions everyday with visual management aids could possibly make it easier for the workers to access them. At the moment, the specifications are usually kept in office and relayed only when they are needed.
Lack of tools and equipment is ranked fourth overall. Tools are mainly provided to the craftsmen engaged on full time basis. Casual workers are expected to bring their own partly because these workers end up taking the very tools they are provided with. Some equipment is not readily available in some places even for hiring. There is a need to improve the availability of tools to make the workers more productive. The factor of poor construction methods is ranked fifth on the overall importance index. Poor construction methods are mainly due to poor planning of the work. Poor planning may partly be attributed to the incompetence of the supervisors. The other problem is that of designs that are not easily buildable. Lack of buildability is due to designs that do not take into account the available resources for construction purposes and inadequate appreciation of construction techniques. Supervisors should be encouraged to develop work statements before the work starts.
Poor communication due, for instance, to inaccurate instructions and inaccurate drawings is ranked sixth on the overall importance index. This is largely attributed to the low levels of literacy of the workers and the level of technical training. The most common form of communication is verbal and, moreover, face-to-face. The other reason is that most of the contracts are traditional. The frequency of meetings between contractors, clients, and designers may not be as often as it should and this brings in communication gaps.
Stoppages because of work being rejected by consultants is rated seventh overall. This is linked to the overall quality management process. A number of contractors do not follow the quality management procedures and many are not Total Quality Management certified. Specifications are at times kept in the offices and only used when there is a need for reference. Political insecurity, for example, due to insurgency, wars is rated eighth on the overall importance. The factor of risk and insecurity has not been rated high before. This might have come up because Uganda has not been at peace for a long time. Currently a big portion of the country faces insecurity from rebels and this affects execution of building contracts.
Tools/equipment breakdown is ranked ninth according to the overall Importance Index. This is in relation to breakdown of equipment including vibrators, water pumps, and powered machinery. These breakdowns due to poor maintenance and lack of regular service. Many of them are also not in the best condition as they lack spares. There is a need for good garages and workshops to take care of the repairs and maintenance and for contractors to understand that there is optimal age for replacing such tools and equipment.
The factor of harsh weather conditions is ranked tenth from the overall importance index. Uganda, being in the equatorial region, experiences wet and dry conditions. The rains are heavy but in many cases last for a short time. They cause damage to unprotected building components under construction that are mainly carried out in situ. The afternoons are generally hot at average maximum of about 28 - 35[degrees]C.
4.3. Reliability of ratings
To test the consistence of the ratings, a null hypothesis [H.sub.o] was set that: "there was no significant agreement among the respondents on the rating of the factors". The alternative H1 was that "there was significant agreement among the respondents on the rating of the factors". The analysis aimed at establishing that the ratings had not been arrived at by chance but rather that there was true agreement in the ratings and therefore the results are reliable.
To test the hypotheses, non-parametric tests using the Kappa Coefficient of Agreement (K) were used . These tests do not rely on the distribution of data, unlike most other parametric tests. The statistics is used in a typical situation where a group of N objects, each of which is to be assigned m categories by a group of I raters. There were N = 73 factors to be rated, evaluated by I = 73 raters each assigning factor on time, cost and quality on M = 6 rating scales. The value of K is the ratio of the proportion of times that the raters agree (corrected for chance agreement) to the maximum proportion of the times the raters could agree .
K = P(A) - P(E)/1 - P(E), (3)
where P(A) is the proportion of time that the raters agree; P(E) is the proportion of time that the raters would be expected to agree by chance. If there was a complete agreement among the raters, then K = 1; and if there is no agreement, other than that which would be expected to occur by chance, then K = 0.
P(E) = [m.summation over (j=1)] [p.sup.2.sub.j], where [p.sub.j] = [C.sub.j]/NI, (4)
[C.sub.j]--number of times a factor is assigned to category j. It is the sum of the column frequencies under the ratings.
P(A) = [1/NI(I - 1) [N.summation over (i=1)] [M.summation over (j=1)] [n.sup.2.sub.ij]) - 1/I - 1, (5)
N--number of factors being rated = 36; M--number of rating scales = 6; I - number of raters = 73; [n.sub.ij]--scores in the rating matrix.
According to Siegel and Castellan, K is normally distributed with zero mean and variance, var(K), given by equation (6).
Hence, z = K/[square root of var(K)], (6)
Var(K) [approximately equal to] 2/NI(I - 1) P(E)-(21 - 3)P[(E).sup.2] + 2(I - 2)[SIGMA][p.sup.3.sub.j]/[[1 - P(E)].sup.2] (7)
The z statistic was used to test the null hypothesis, [H.sub.o]: K = 0 against the alternative hypothesis, [H.sub.1]: K [not equal to] 0. From equations (1), (2) and (3) above, the values of P(A), P(E) and K were computed as indicated in Table 3.
The computed values of var(K) and z are given in Table 3. At 5% level of significance, z = 1,645. Since the computed values are greater than [z.sub.0,05], it can be concluded that there was a significant agreement in rating the factors and the degree of agreement is beyond that which could have occurred by chance. The null hypothesis is therefore rejected and the ranking given represents consensus among the respondents.
The objective of this study was to identify and rank the major factors that affect the productivity of craftsmen in Uganda. The goal is to find an appropriate strategy for improving the productivity of craftsmen in this country, with emphasis on the most critical factors taking into account the effects on time, cost and quality. From the survey, five highest ranked factors that affect labour productivity are incompetent supervisors, lack of skills; rework; lack of tools/equipment; and poor construction methods. Since contractors in Uganda are trying to find ways of improving productivity, UNABCEC, researchers and policy makers should mainly dwell on the identified critical factors. The level of supervision and level of skills of craftsmen particularly have to be improved. Contractors should focus on improving these areas by giving refresher courses, rewarding on the basis of skill and output, and participating in structured training on workers in the construction industry. Research geared at improving productivity should focus on the identified factors preferably those on top of the list by importance index that has taken into account time, cost and quality of the building products.
The authors would like to acknowledge the support given by sida/SAREC, Lund University and Makerere University that made this research possible. The authors also thank the anonymous referees for the comments that have led to an improvement in the paper quality.
Received 10 Nov 2006; accepted 06 March 2007
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Henry Mwanaki Alinaitwe (1), Jackson A. Mwakali (2), Bengt Hansson (3)
(1) Dept of Civil Engineering, Makerere University, P. O. Box 7062, Kampala, Uganda. E-mail: firstname.lastname@example.org
(2) Dept of Civil Engineering, Makerere University, P. O. Box 7062, Kampala, Uganda. E-mail: email@example.com
(3) Division of Construction Management, Lund University, P. O. Box 118, Lund, 221 00, Sweden. E-mail: firstname.lastname@example.org
Henry Mwanaki ALINAITWE. PhD student at Lund University and Makerere University on a sandwich programme. His research is on productivity and performance improvement in the construction industry. Member of the Uganda Institution of Professional Engineers. MSc in construction management from Loughborough University in the UK, a Master's degree in civil engineering from the University of Sydney (Australia) and a Licentiate degree from Lund University in Sweden.
Jackson A. MWAKALI. Head of Dept of Civil Engineering at Makerere University in Uganda. Assoc Prof of Civil Engineering, his main areas of interest are structures, facilities maintenance, construction techniques and management. A practicing engineer and a member of the Uganda Institution of Professional Engineers. He has published several papers in academic journals, conference proceedings and authored textbooks.
Bengt HANSSON. Head of the Construction Management Division at Lund University (Sweden). Professor of Construction Management. His main areas of interest are industrialisation, modularisation, innovation, construction techniques, knowledge management, performance in the construction industry. He has published several papers in conferences, academic journals and authored textbooks.
Table 1. UNABCEC Grades for building contractors who responded UNABCEC No No Percentage Grade Contacted Responded (%) A 38 23 60 B 16 9 56 C 31 19 61 D 27 9 33 E 27 13 48 Total 139 73 53 Table 2. Ranking of factors according to time, cost, quality and combined importance index Average Average rating, Rank, rating, according according according to time to time to cost Maximum values 5 36 5 Incompetent supervisors 3,973 4 3,795 Lack of skills of the workers 3,945 5 3,753 (eg inexperienced, poorly trained) Rework, eg poor work done 4,000 2 4,082 Lack of tools/equipment 4,000 3 3,658 Poor construction method 3,658 14 3,397 (eg poor sequencing of work items) Poor communication (eg 3,726 12 3,603 inaccurate instructions, inaccurate drawings) Stoppages because of work 3,932 6 3,616 being rejected by consultants Political insecurity 3,836 10 3,630 (eg insurgency, wars) Tools/equipment breakdown 3,671 13 3,753 Harsh weather conditions 3,658 15 3,397 Stoppages because of 3,890 7 3,534 insolvency Poor recruitment and changing 3,479 17 3,315 of foremen Stoppages because of disputes 3,849 8 3,562 with owners/consultants Incomplete drawings and 3,808 11 3,027 design changes Alcoholism and drug abuse 3,301 20 2,726 Poor economic conditions 3,247 23 2,986 of workers (eg poor pay) Material shortages/delays 4,192 1 3,411 Poor labour composition 3,288 21 3,137 (eg poor ratio of tradesmen to labourers) Absenteeism of workers 3,836 9 3,082 Disruption of power/water 3,548 16 3,315 services (eg power load shedding) Labour disputes (eg 2,986 28 3,137 industrial action) Poor site conditions 3,123 25 3,219 (eg height, shape, etc) Poor health of workers 3,205 24 2,945 (eg sickness, general weakness) Workers turnover, recruitment 2,877 30 2,603 and changing crews Design complexity 3,000 27 3,315 Poor access (eg poor 3,260 22 2,904 scaffolds) Design changes 3,466 18 3,603 Inspection delay 3,342 19 3,055 Accidents at work sites 3,014 26 3,315 Overcrowding on the site 2,452 34 2,918 Interference from other 2,575 32 2,767 trades or other crew members Too much instruction time 2,904 29 2,425 (eg to workers) Working overtime 2,836 31 2,425 Adherence to regulatory 1,986 35 2,274 requirements Attendance to social factors 2,534 33 2,384 (eg deaths of relatives, parties, etc) Small construction volume 1,959 36 2,466 Average Rank, rating, Rank, according according according to cost to quality to quality Maximum values 36 5 36 Incompetent supervisors 2 3,904 2 Lack of skills of the workers 3 4,192 1 (eg inexperienced, poorly trained) Rework, eg poor work done 1 3,260 7 Lack of tools/equipment 5 3,548 4 Poor construction method 13 3,726 3 (eg poor sequencing of work items) Poor communication (eg 8 3,356 5 inaccurate instructions, inaccurate drawings) Stoppages because of work 7 2,890 15 being rejected by consultants Political insecurity 6 2,918 14 (eg insurgency, wars) Tools/equipment breakdown 4 3,027 13 Harsh weather conditions 14 3,055 12 Stoppages because of 11 2,753 18 insolvency Poor recruitment and changing 16 3,123 10 of foremen Stoppages because of disputes 10 2,589 20 with owners/consultants Incomplete drawings and 24 3,164 9 design changes Alcoholism and drug abuse 30 3,233 8 Poor economic conditions 25 3,301 6 of workers (eg poor pay) Material shortages/delays 12 2,301 30 Poor labour composition 20 3,055 11 (eg poor ratio of tradesmen to labourers) Absenteeism of workers 22 2,534 22 Disruption of power/water 15 2,370 29 services (eg power load shedding) Labour disputes (eg 21 2,479 24 industrial action) Poor site conditions 19 2,795 17 (eg height, shape, etc) Poor health of workers 26 2,521 23 (eg sickness, general weakness) Workers turnover, recruitment 31 2,863 16 and changing crews Design complexity 18 2,452 26 Poor access (eg poor 28 2,644 19 scaffolds) Design changes 9 2,055 34 Inspection delay 23 2,452 25 Accidents at work sites 17 2,164 33 Overcrowding on the site 27 2,562 21 Interference from other 29 2,397 28 trades or other crew members Too much instruction time 33 2,411 27 (eg to workers) Working overtime 34 2,192 32 Adherence to regulatory 36 2,260 31 requirements Attendance to social factors 35 1,534 36 (eg deaths of relatives, parties, etc) Small construction volume 32 1,781 35 Rank, according to Importance importance index index Maximum values 1 36 Incompetent supervisors 0,577 1 Lack of skills of the workers 0,574 2 (eg inexperienced, poorly trained) Rework, eg poor work done 0,502 3 Lack of tools/equipment 0,486 4 Poor construction method 0,475 5 (eg poor sequencing of work items) Poor communication (eg 0,446 6 inaccurate instructions, inaccurate drawings) Stoppages because of work 0,441 7 being rejected by consultants Political insecurity 0,438 8 (eg insurgency, wars) Tools/equipment breakdown 0,397 9 Harsh weather conditions 0,390 10 Stoppages because of 0,385 11 insolvency Poor recruitment and changing 0,365 12 of foremen Stoppages because of disputes 0,361 13 with owners/consultants Incomplete drawings and 0,355 14 design changes Alcoholism and drug abuse 0,349 15 Poor economic conditions 0,328 16 of workers (eg poor pay) Material shortages/delays 0,314 17 Poor labour composition 0,313 18 (eg poor ratio of tradesmen to labourers) Absenteeism of workers 0,292 19 Disruption of power/water 0,289 20 services (eg power load shedding) Labour disputes (eg 0,283 21 industrial action) Poor site conditions 0,278 22 (eg height, shape, etc) Poor health of workers 0,268 23 (eg sickness, general weakness) Workers turnover, recruitment 0,256 24 and changing crews Design complexity 0,254 25 Poor access (eg poor 0,254 26 scaffolds) Design changes 0,252 27 Inspection delay 0,249 28 Accidents at work sites 0,230 29 Overcrowding on the site 0,207 30 Interference from other 0,202 31 trades or other crew members Too much instruction time 0,186 32 (eg to workers) Working overtime 0,150 33 Adherence to regulatory 0,141 34 requirements Attendance to social factors 0,135 35 (eg deaths of relatives, parties, etc) Small construction volume 0,122 36 Table 3. Calculation of Z values Factors rated against P(A) (PE) K Var(K) Z Time 0,249 635 0,216 655 0,042 102 1,28E-05 11,789 Cost 0,218 021 0,201 863 0,020 244 9,96E-06 7,173 Quality 0,195 068 0,176 393 0,022 674 3,22E-06 12,639
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|Author:||Alinaitwe, Henry Mwanaki; Mwakali, Jackson A.; Hansson, Bengt|
|Publication:||Journal of Civil Engineering and Management|
|Date:||Sep 1, 2007|
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