DETERMINATION OF LABOUR OUTPUTS FOR THE NIGERIAN CONSTRUCTION INDUSTRY; A CASE STUDY OF THE KADUNA CONSTRUCTION LABOUR MARKET
ABSTRACT
The sustainability and success of the construction industry depends greatly on the level of accuracy in project estimates. The consequences of adopting inaccurate estimates are quite enormous and overwhelming. This research aims at using work study approach to empirically establish labour outputs of some selected trades for the Nigerian construction industry with the view of increasing the accuracy of construction cost estimates. A total of 15 construction sites were sampled within Zaria and Kaduna town. Physical observations and measurement of work outputs on block work, plastering/rendering and excavations were conducted through work study approach, particularly work measurement. Data collected were subjected to statistical analysis using both the descriptive and inferential data analysis techniques. The inferential tools made use of T-test statistics to assess and examine the influence of the various labour productivity factors on the outputs of the workers observed. The results of the analysis carried out established general average output values per day of; 10.68m2 30.85m2 and 19.04m3 for block laying, plastering/rendering and excavating trenches i.e. 1.50m deep respectively. However, The test of difference conducted in order to analyze and investigate the extent of influence of the productivity factors discovered a consistent significant difference in output of workers as the period of observation and the level and style of payment is varied. Also age as a productivity factor affected only the outputs of trench diggers excavating trenches n.e 1.50m deep. Similarly, even though differences existed between outputs in block laying and plastering operations, the tests conducted confirmed that they were quite insignificant. The level and length of experience of tradesmen observed had a tremendous effect on their outputs in block laying and plastering operations. Nonetheless, that did not affected workers in trench excavations operations. The additional qualifications obtained by the tradesmen in addition to their apprenticeship qualifications only affected the output of plasterers and was virtually insignificant to the other tradesmen in their trades operations.
The research concluded by recommending the outputs established to Contractors so as to exploit the output figures extracted according to productivity factors in order to optimize the productivity of their workers and profitability.
TABLE OF CONTENTS
TITLE PAGE
DECLARATION
CERTIFICATION
DEDICATION
ACKNOWLEDGEMENT
ABSTRACT
TABLE OF CONTENTS
LIST OF TABLES
CHAPTER ONE
INTRODUCTION
1.1 Background to the Study
1.2 STATEMENT OF RESEARCH PROBLEM
1.3 AIM:
1.4 OBJECTIVES:
1.5 RESEARCH HYPOTHESES
1.6 SCOPE AND LIMITATIONS:
CHAPTER TWO
2.0 LITERATURE REVIEW
2.1.0 Productivity Background
2.1.1 Labour Productivity
2.1.2 Productivity Enhancement Measures
2.1.3 Productivity of Nigerian Construction Works Labour:
2.1.4 Factors Affecting Construction Labour Productivity
2.2 Introduction to Work Study
2.2.1 Background
2.2.2 Definition of Work Study
2.2.3 Aims of Work Study
2.2.4 Objectives of Work Study
2.2.5 Benefits of Work Study
2.2.6 Work Study Techniques
2.2.7 Method Study
2.2.8 Work Measurement
2.2.9 Procedure of Work Measurement
2.2.10 Analysis Stage
2.2.11 Measurement Stage
2.2.12 Synthesis Stage
2.2.13 Uses of Work Measurement
2.2.14 Work Measurement Techniques
2.2.15 Time Study
2.2.15 Time Study Equipments
2.2.16 Selection of Operator to be studied
2.3 Review of Previously Related Works on Labour Outputs Determination
2.3.1 Labour output on plastering works by Mike I. Udegbe
2.3.2 Labour Output Appraisal by Ibrahim Ajia
CHAPTER THREE
3.0 RESEARCH METHODOLOGY
3.1 INTRODUCTION:
3.2 RESEARCH DESIGN/ APPROACH
3.2 AREA OF STUDY:
3.3 STUDY POPULATION
3.4 RESEARCH SAMPLE AND SAMPLING TECHNIQUES
3.5 INSTRUMENT FOR DATA GATHERING
3.6 VALIDATION AND RELIABILITY OF THE INSTRUMENT
3.7 METHODS OF DATA COLLECTION
3.7.1 LITERATURE REVIEW
3.7.2 FIELD SURVEY
3.8 RESEARCH PROCEDURES
3.8 PILOT SURVEY:
3.9 DATA ANALYSIS:
3.9.1 Measurement of outputs
3.9.2 Test of differences in labour outputs
CHAPTER FOUR
DATA PRESENTATION, ANALYSIS AND DISCUSSION OF RESULTS
4.1 INTRODUCTION
4.2 Nature of the Research Data
4.3 Block Work
4.3.1 Data Presentation
4.3.2 Background Information
4.3.3 Age
4.3.4 Sex
4.3.5 Qualification
4.3.6 Experience
4.3.7 Payment
4.3.9 Data Analysis
4.3.10 Descriptive Analysis
4.3.11 The Inferential Statistics Analysis
4.3.12 The t-test
4.4 Plaster/Rendering
4.4.1 Data Presentations
4.4.2 Descriptive Analysis
4.4.3 Output Levels and Productivity Factors
4.4.4 Inferential Analysis
4.5 Excavation Works
4.5.1 The Descriptive nature of the Data
4.5.2 Inferential Analysis
CHAPTER FIVE
5.1 INTRODUCTION
5.2 Conclusion
5.3 Recommendations
5.4 Areas for further study
LIST OF TABLES
Table 1: labour outputs (m2) for rendering in selected locations in Edo State ………………….36
Table 2: Outputs of Firms based on Records ……………………………………………………37
Table 3: Output Results from Work Measurement ……………………………………………...38
Table 4: age distribution of workers …………………………………………………………….50
Table 5: Labour Quality …………………………………………………………………………51
Table 6: workers experience distribution ………………………………………………………..51
Table 7: Payment level …………………………………………………………………………..52
Table 8: Working Conditions ……………………………………………………………………52
Table 9: The output values for blockwork ………………………………………………………53
Table 10: Descriptive Analysis of the workers outputs:blockwork……………………………...54
Table 11: Descriptive analysis results of age factor …………………………………………….56
Table 12: Payment descriptive analysis result …………………………………………………..57
Table 13: Experience factor descriptive analysis results ………………………………………..58
Table 14: Labour Quality/Qualification: descriptive analysis results …………………………...58
Table 15: Test Statistics 18-35 years Vs Above 35 years ……………………………………….60
Table 16: Test Statistic – Morning Output Vs Afternoon Output ………………………………61
Table 17: Daily Paid Vs Negotiated payment …………………………………………………..62
Table 18: Highly experienced Vs Low Experience Group ……………………………………...62
Table 19: SSCE certificate Group Vs Primary Certificate Group ………………………………63
Table 20: No qualification Vs SSCE Certificate ………………………………………………..64
Table 21: Descriptive Analysis of the General Data ……………………………………………69
Table 22: Descriptive Analysis Result: Age factor ……………………………………………..70
Table 23: Descriptive Statistics results: Payment ………………………………………………71
Table 24: Descriptive Statistics results: Experience ……………………………………………71
Table 25: Descriptive Statistics Results; qualification ………………………………………….72
Table 26: 18-35 years Age group Vs Above 35 years age group ……………………………….73
Table 27: Test statistics – Morning output Vs Afternoon output ……………………………….73
Table 28: Daily paid Vs Negotiated payment ……………………………………………………74
Table 29: Highly experienced Vs low experience ………………………………………………75
Table 30: SSCE group Vs Primary certificate group ……………………………………………75
Table 31: No qualification Group Vs SSCE certificate group …………………………………..76
Table 32: Descriptive analysis results of the general data (excavation works) ………..………..80
Table 33: Descriptive statistics results for output and productivity factors ……………………..81
Table 34: 18-35 years Age Group Vs Above 35 years Age Group ……………………………..83
Table 35: Test statistics results – Morning output Vs Afternoon output ………………………..83
Table 36: Highly experienced VS low experience group t-statistics:
Two samples assuming unequal variances average output/day …………………………………84
Table 37: No Qualification group Vs Primary certificate group ………………………………..84
Table 38: General Outputs ………………………………………………………………………85
Table 39: Outputs According to Productivity Factors …………………………………………..85
Table 40: Results of null hypothesis …………………………………………………………….86
Table 41: Results summary of research hypothesis ……………………………………………..86
CHAPTER ONE
INTRODUCTION
1.1 Background to the Study
Estimating is one of the key fundamental functions of the Quantity Surveyor. Estimates are very vital to clients when making decisions and therefore, client expect from estimator’s useful and objective information from estimators. These estimates according to Morledge (2006), should have clear indications of the level of information reliability and not subsequent explanations of inaccuracy (Morledge, 2006).
Garret (2006) reported that the sustainability and success of the construction industry depends greatly on the level of accuracy in project estimates. This is strongly supported by the fact that the construction industry statistics indicates that more than 50% of the construction projects exceed their initial cost and time estimates (Garret, 2006). The consequences of adopting inaccurate estimates are quite enormous and overwhelming. Garret (2006) ascertained that it is a straight forward equation that if the price for the project is wrong then financial pressures, hardship, supply chain conflict and quality problems will result. In addition, the client’s vulnerability as the ultimate risk holder of the finished building can be horribly exposed and no one may possibly gain (Morledge, 2006).
According to Ashworth (2002), the common method of estimating the costs of construction works involves the multiplication of unit rates and the measured quantities in the Bills of Quantities (BOQ) .The calculation of the unit rates for the individual measured items in a BOQ requires the collation of current cost information for labour, plant and materials, as well as overhead and profit (Ayeni, 1999)
The estimation of the cost figures of materials, plant and overhead and profit has never been a point of discourse and contention. This is because they involve the quantitative estimation of the cost values for plants and overheads while market survey research for materials prices are the basis for the material cost estimation (Ashwort, 1999). The aspect of labour pricing is usually done on the basis of the output constants collected on each trade (Ayeni, 1999).The high degree of inaccuracy found in our BOQ estimates is mostly attributed in the uncertainty of the accuracy of the labour constants used in pricing labour costs. Ajia (2002) concluded that while most of the outputs used by estimators are the British originated constants, some contractors adopt outputs gotten from their realm of experience and hence non-uniform outputs are widely in use. However, Yates and Swagata (1993) argued that the productivity of workers is being influenced by factors which vary according to geographical locations. Therefore, if these factors vary acutely with location then how feasible realistic and accurate are the currently adopted British originated outputs within the Nigerian context? Hence, this research work intends to employ work study approach to empirically establish labour outputs of some selected trades with the view of improving the accuracy of construction cost estimates.
1.2 STATEMENT OF RESEARCH PROBLEM
While it is very clear that the materials, plants, overheads and profits ingredients of a unit rate of construction work can be calculated on the basis of quantitative estimations, the accuracy of the labour constants commonly used for estimating labour costs still remain unclear and uncertain. Similarly, the dynamics of the factors that affect the productivity of construction workers in Nigeria are not well understood.
1.3 AIM:
This research aims at using work study approach to empirically establish labour outputs of some selected trades for the Nigerian construction industry with the view of increasing the accuracy of construction cost estimates. 1.4 OBJECTIVES:
1. To investigate and review some of the current labour outputs currently in use in Nigeria, their basis and originations.
2. To empirically establish the output of some selected trades.
3. To statistically examine the influence of labour productivity factors on the established labour outputs. 1.5 RESEARCH HYPOTHESES
In order to conduct inferential test to determine the influence of the labour productivity factors on the labour outputs established, both null and alternative hypothesis were found deemly necessary.
Hence, the following research hypotheses are posited in terms of workers output and productivity level:
· Hypothesis(H1):The ages of workers have a significant impact over their outputs on site
⦁ Null hypothesis (H1o): There is no output difference between the various age groups observed.
⦁ Hypothesis (H2): The outputs of workers vary progressively with changes in the period of work.
⦁ Null hypothesis (H2o): there is no output difference in all the different periods of observations.
⦁ Hypothesis (H3): The level of outputs of workers depends on the type and level of payment made to them.
⦁ Null hypothesis (H3o): there is no output difference in respect of the type and level of Payment to workers under observation.
⦁ Hypothesis (H4): The group of highly experienced workers has higher outputs than those with low work experience.
⦁ Null hypothesis (H4o): There is no output difference between the highly experienced groups of workers and workers with low experience level.
⦁ Null hypothesis (H5): The well educated and highly qualified group of workers has higher output than those with little or no qualification.
· Null hypothesis (H5o): There is no output difference between the well educated and highly qualified group of workers and workers with little or no qualification. 1.6 SCOPE AND LIMITATIONS:
SCOPE:
This research work will cover the following selected trades:
· Block work
· Excavations
· Plaster/Rendering .
All the construction sites considered are within the Kaduna metropolis and Zaria town. LIMITATIONS:
The following were the foreseeable limitations of the study, which should affect the accuracy of the results:
1. The Hawthorne effect: a phenomenon whereby workers tend to improve upon their natural productivity level when being directly observed.
2. The difficulty in assessing whether a worker is operating in full and natural capacity or not during the period of observations.
3. A non random probability sampling technique was used for selecting the workers considered in the research. Therefore, members of the population observed were selected with some little element of bias.
.