AN ASSESSMENT OF LABOR OUTPUT DETERMINATION ON WINDOWS AND DOORS FIXING
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- 1-5 Chapters
- Quantitative
- T-test
- Abstract : Available
- Table of Content: Available
- Reference Style: APA
- Recommended for : Student Researchers
- NGN 3000
BACKGROUND OF THE STUDY
The construction industry's productivity is extremely important to its efficiency. According to Adnan et al (2007), the nation's economy would continue to face setbacks unless the productivity level of building operations is enhanced. As a result, increasing productivity has become a top priority for any profit-driven company (Adnan et al, 2007). Labor is a key part of the construction industry's productivity. Labor expenditures make for a significant component of the ultimate cost of a structure, typically accounting for 40 to 60% of the total cost (Butchan et al, 1993). Furthermore, labor is widely regarded as the most significant element in production since it is the sole factor that produces value and determines overall productivity (Ameh and Odusami, 2002). Labor productivity, defined by Yates and Guhathakurta (1993), is the value of gross production per worker, also known as man-hour or work-hour. It might alternatively be defined as the methodical measurement of labor's physical output while taking into consideration the other elements that influence construction productivity.
Several studies have focused on the elements that determine labor productivity, recognizing its relevance (Oloko, 1983; Lema, 1995; Yagba and Ayandele, 1999; Ameh and Odusami, 2002; Adnan et al, 2007; Kane et al, 2007). However, none of these studies give an actual assessment of the magnitude and scope of these factors' impact on Nigerian construction labor productivity. Given the significance of this topic, this study aims to investigate the impact of specific productivity determinants on labor outputs that the authors empirically established for a few selected trades and published elsewhere.
The usual technique of estimating the costs of building works, according to Ashworth (2002), includes multiplying unit rates and measured quantities in the Bills of Quantities (BOQ). In order to calculate the unit rates for the different measured items in a BOQ, current cost information for labor, plant, and materials, as well as overhead and profit, must be gathered (Ayeni, 1999). The calculation of material, plant, and administrative costs, as well as profit, has never been a topic of debate. This is because they entail the quantitative calculation of plant and overhead cost values, whereas market survey research for material prices serves as the foundation for material cost estimation (Ashwort, 1999). The output constants obtained on each exchange are frequently used to price labor (Ayeni, 1999).
STATEMENT OF RESEARCH PROBLEM
Collecting current information on the cost of materials, labor, plants, overheads, and profit is required to establish a unit rate for construction activity. Materials, plant, overhead, and profit components can all be calculated numerically. However, due to a number of factors that influence the calculation of labor output, the labor component cannot be exactly quantified. Because BESMM3 and geographical location were not taken into account, the correctness of the labor constants routinely employed in the Nigerian construction industry is imprecise and dubious.
Sani (2011) found that the task items in BESMM3 took precedence over those in a previous study on determining labor output for doors and window repair. To comply with the Building and Engineering Standard Method of Measurement, it has become important to experimentally establish the labor output constant for the Nigerian Construction Industry (BESMM3).
JUSTIFICATION FOR THE STUDY
The significant level of error in our BOQ estimations is mostly due to the uncertainty around the correctness of the labor constants utilized in labor cost pricing. Most output constants utilized by estimators in Nigeria, for example, are either generated from experience or are vestiges of British colonial legacy Abdulrazaq et al, 2010. As a result, non-uniform outputs are common in the construction business. The BESMM3 and geographical locations of Nigeria are not taken into consideration in these results.
Furthermore, the study will allow Construction Managers to: determine how effectively his or her projects are being managed; detect adverse trends quickly so that corrective action can be taken; determine the effects of changed methods and conditions; identify both high and low areas of productivity and reasons for these differences; and compare performance between sites.
The hazards of making an incorrect estimate cannot be overstated. According to Garret (2006), the accuracy of project cost estimates is critical to the construction industry's long-term viability and profitability. This is due to the large financial commitments necessary for a normal construction project, and erroneous cost estimates can harm all parties involved (Onukwube, 2002). Financial difficulties, hardship, supply chain disputes, and quality problems will arise if a project's cost estimate is incorrect, according to Garret (2006). Furthermore, the client's vulnerability as the ultimate risk bearer of the completed structure might be severely exposed, with no one benefiting (Morledge, 2006). All stakeholders are concerned about the accuracy of project cost estimates.
RESEARCH AIM
The aim of this research is to determine the labour outputs for fixing selected windows and doors in Kano and Jigawa states Nigeria.
RESEARCH OBJECTIVES
- To examine the influence of labour factors on productivity.
- To establish the labour output of some selected windows and doors fixing.
- To investigate through literature, the sources and origin of some of the labor outputs currently in use in Nigeria.
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 (Abdullahi, 2009).
These hypotheses are:
- Hypothesis (H1): The ages of workers have a significant difference 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 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.
- 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.
SCOPE
The research work covers selected sizes of windows and doors for bungalow buildings.
LIMITATIONS
The following foreseeable limitations could affect the accuracy of the results:
- Workers will tend to improve upon their natural productivity level when being directly observed.
- The difficulty in assessing whether a worker is operating in full and natural capacity or not during the period of observations.
- This research focused on only doors and windows on bungalow buildings.
- The research focuses only on Aluminum windows and steel doors.
- Windows of sizes 1500x1200, 1299x1200mm and 600x600mm high only are considered.
- Doors of sizes 1200x2100mm, 900x2100mm and 750x2100mm high only are considered.
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