Factors Affecting Labor Productivity on Building Projects in Zimbabwe

Transcription

1 International Journal of Architecture, Engineering and Construction Vol 3, No 1, March 2014, Factors Affecting Labor Productivity on Building Projects in Zimbabwe Benviolent Chigara and Tirivavi Moyo Department of Landscape Architecture and Urban Design & Department of Quantity Surveying Faculty of The Built Environment, National University of Science and Technology, Bulawayo, Zimbabwe Abstract: The aim of this research was to identify and rank, according to relative importance, factors affecting labor productivity on building projects in Zimbabwe. Structured questionnaires comprising forty pre-selected factors were used for data collection. Using a five-point likert scale, consultants and building contractors expressed their views on the relative importance of pre-selected factors on labor productivity. The data was analyzed using Spearman s rank correlation, mean response and the relative importance index. The results show that unavailability of materials, late payment of salaries and wages, suitability/adequacy of plant and equipment, supervisory incompetence, and lack of manpower skills, are the top five most important factors impinging on labor productivity in Zimbabwe. Adequate work planning, efficient resources procurement systems, timeous payment of salaries and continuous professional development for workers, are amongst the recommended intervention strategies to improve on-site labor productivity. Keywords: Construction, labor productivity, building projects, productivity factors, Zimbabwe DOI: /IJAEC INTRODUCTION The construction industry is a strategic industry to the national economy providing infrastructure and shelter for other economic activities to take place. Attar et al. (2012) noted that construction is a key sector of the national economy for countries all around the world, as traditionally it takes up a big portion in the nation s total employment and its significant contribution to a nation s revenue as a whole. In Indonesia, Alwi (2003) indicated that construction projects are an important priority in national plans. According to Zimstat (2014), the Zimbabwean construction industry s contribution to Gross Domestic Product (GDP) during the last quarter of 2013 stood at 3.59%. Against this background, the national importance of construction projects could be enhanced through adopting efficient methods of managing resources to achieve increased productivity. According to Horner et al. (1989) as cited by Soham and Rajiv (2013), a 10% increase in labor productivity would yield annual savings of approximately a billion pounds to the British economy. Improving productivity is thus a major concern for any profit-oriented organization. Productivity improvements achieve high cost savings and is a key factor driving long-term economic growth and increasing living standards. Thus given the razor-thin profit margins associated with competitive building contracts, managing problems that negatively affect productivity should be a priority. Picard (2003) indicates that systemic inefficiencies in construction projects can no longer be overlooked in a competitive industry operating at low profit margins. Drucker (1980) cited by Ameh and Osegbo (2011) argue that there is nothing as dangerous to an economy as a decline in productivities because it creates inflationary pressure, social conflict and mutual suspicion. However, apart from the advantages that contractors may gain over their competitors by improving upon productivity to build projects at lower costs; most contractors do not systematically and properly address this strategic issue or evaluate its impact on the project s profit (Mojahed 2005). According to Attar et al. (2012) construction industries are still facing a number of problems regarding low productivity, poor safety and insufficient quality. In Zimbabwe, inability of workers to produce at industry set output standards is clear testimony of declining productivity. *Corresponding author. benviolent.chigara@nust.ac.zw 57

2 However, instances of declining labor productivity have not been limited to Zimbabwe. In South Africa, workforce management group Adcorp estimates that labor marginal productivity is at the lowest mark in more than 40 years (Business Day Live 2013). In Nigeria, labor productivity growth has been unsatisfactory (Umoru and Yaqub 2013). This is not a healthy situation for the labor-intensive building industry in developing countries of Africa and elsewhere. In most countries labor accounts for between 30-50% of project cost (Yates and Guhathakurta 1993; Jergeas 2009; Jarkas and Bitar 2012). Thus construction productivity largely depends on performance of construction workers and as such decline in labor productivity will substantially affect project cost, time and quality. In spite of some notable research on labor productivity by various scholars who include, among others: Olomolaiye et al. (1987); Kaming et al. (1997); Makulsawatudom and Emsley (2001); Chan (2002); Mojahed (2005); Alinaitwe et al. (2006); Enshassi et al. (2007); Jergeas (2009); Durdyev and Mbachu (2011); Jarkas and Bitar (2012), declining labor productivity continues to torment the industry. For example, the Intergraph Corporation (2012) postulates that every year, owner operators, engineering, procurement, and construction companies are hit with billions of dollars in construction claims as a result of inefficiency factors impacting labor. In Zimbabwe, the problem is compounded by lack of research and published data on labor productivity, yet knowledge of the factors that affect productivity is important if any meaningful intervention strategies are to be put in place to improve construction productivity. Therefore, this research used pre-selected factors from literature to analyze the key factors that affect labor productivity on building projects in Zimbabwe. Specifically, the research sought to identify factors that affect labor productivity on building projects; rank the factors according to their relative importance; and proffer intervention strategies to improve labor productivity. 2 CONSTRUCTION LABOR PRODUCTIVITY Labor is a key resource on building projects. However, to realize full economic value from labor, productivity issues must be addressed in all contracting organisations. Productivity is one of the key components of every company s success and competitiveness in the market (Mojahed 2005). Declining labor productivity across nations (Jergeas 2009; Intergraph Corporation 2012; Umoru and Yaqub 2013; Soham and Rajiv 2013) is a cause for concern. 2.1 Labor Productivity In spite of the numerous researches on labor productivity there is no consensus among scholars and practitioners regarding the definition and measurement of construction labor productivity. The Organisation for Economic Co-operation and Development (OECD) defines productivity as a ratio of a volume measure of output to a volume measure of input use (OECD 2001). While there is no disagreement on this general notion, the OECD argued that a look at the productivity literature and its various applications reveals that there is neither a unique purpose for, nor a single measure of, productivity. According to Alwi (2003) measuring productivity for construction projects is a complex problem. In construction; productivity is usually taken to mean labor productivity (Attar et al. 2012). This stems from the fact that construction projects are mostly labor based with basic hand tools and e- quipment. Attar et al. (2012) asserted that productivity signifies the measurement of how well an individual entity uses available resources to produce outputs from inputs. The American Association of Cost Engineers defines productivity as a relative measure of labor efficiency, either good or bad, when compared to an established base or norm (Intergraph Corporation 2012) Labor productivity reflects how efficiently labor is combined with other factors of production, how many of these other inputs are available per worker and how rapidly embodied and disembodied technical change proceed (OECD 2001). Mojahed (2005) distinguishes between industry level and project specific productivity. Thus the definition of productivity at the industry level is utilized by an economist to determine the economy s health, trends, and growth rate. The definition of productivity at project level applies to the areas of construction planning and scheduling, cost estimating, accounting, and cost control (Proverbs et al. 1999). Project level productivity may also be equated to labor productivity. Whilst there are many factors that affect productivity; their impact may be measured relative to labor productivity. 2.2 Measures of Labor Productivity Dozzi and AbouRizk (1993) identified two most important measures of labor productivity as: the effectiveness with which labor is used in the construction process and the relative efficiency of labor doing what it is required to do at a given time and place. However, they argued that contractors are more concerned with the latter, that is, the relative efficiency of labor. Labor efficiency is the basis of most tender estimates, as well as the yardstick by which performance is measured and monitored (Dozzi and AbouRizk 1993). However to improve labor effectiveness various factors should be addressed, including motivation, job safety, environmental factors and physical limitations. On the other hand, Attar et al. (2012) indicate that productivity measures can be put into two categories: Single Factor or Partial and Multi-Factor Productivity Measures (MFP). Single factor productivity measures relate to 58

3 particular measure of output to a single measure of input, such as labor or capital. MFP relates to a particular measure of output to a group of inputs, or total inputs used (Intergraph Corporation 2012). These measures are not independent of each other. For example, it is possible to identify various driving forces behind labor productivity growth, one of which is the rate of MFP change (OECD 2001). According to Dozzi and AbouRizk (1993) performance factor, production rate, unit person-hour (p-h) rate and other measures may be used to describe productivity in the construction industry. Nonetheless, the most reliable measure of productivity is the output per man-hour achieved by the workers at the construction site (i.e. labor productivity) (Mojahed 2005). 2.3 Factors affecting Labor Productivity Studies over the years have identified a myriad of factors that affect construction labor productivity in developed countries such as: Canada (Jergeas 2009), UK (Chan 2002), New Zealand (Durdyev and Mbachu 2011) and developing countries such as Nigeria (Olomolaiye et al. 1987; Ameh and Osegbo 2011; Adamu et al. 2011), Indonesia (Kaming et al. 1997; Alwi 2003), Malaysia (Kadir et al. 2005), Palestine (Enshassi et al. 2007), Kuwait (Jarkas and Bitar 2012); Thailand (Makulsawatudom and Emsley 2001), and U- ganda (Alinaitwe et al. 2007). Broadly, labor productivity is affected by external and internal factors, representing those outside the control of the firm s management and those originating within the firm respectively. In a study of 45 factors negatively affecting labor productivity in the Gaza strip, Enshassi et al. (2007) noted that the 10 most important factors negatively affecting labor productivity are: material shortages; lack of labor experience; lack of labor surveillance; misunderstanding between labor and superintendents; drawings and specification alterations during project execution; payment delay; labor disloyalty; inspection delay; working seven days per week without holiday; and tool/equipment shortages. In Thailand, Makulsawatudom and Emsley (2001) identified six key factors impinging on labor productivity as follows: lack of material; supervision delays (instruction time); lack of tools and equipment; rework; absenteeism; and interference. In a study of craftsman productivity in Indonesia, Kaming et al. (1997) identified lack of materials, rework, absenteeism, interference due to work mismanagement and lack of equipment and tools as the main productivity problems. In a comparative assessment of labor productivity problems in Indonesia, Nigeria, United Kingdom and the United States, Kaming et al. (1997) observed that lack of materials is a common problem in the four nations. In Nigeria, a study by Olomolaiye et al. (1987) identified the following problems influencing craftsmen s productivity in order of rank: lack of materials, lack of tools, duplicated efforts (repeated work), instruction delays, inspection delays, absenteeism, incompetency of supervisor, and changing crew members. A later study on factors affecting productivity in Nigeria revealed that low wages ranked top closely followed by lack of materials and unfriendly working atmosphere (Adamu et al. 2011). Late arrival of materials or labor, equipment break-downs, poor lay out of work plan, and inability to provide information will lead to non-productive or down time (Thomas and Raynar, 1997 in Mojahed 2005). In New Zealand, Durdyev and Mbachu (2011) reported on the constraints with the highest impact on productivity as reworks, level of skill and experience of the workforce, adequacy of method of construction, buildability issues, and inadequate supervision and coordination. 3 RESEARCH METHOD 3.1 Research Design The research method employed was mainly quantitative although to some extent qualitative assessments were also included. To get a balanced analysis of the factors, the research sought opinions from both consultants and contractors. Simple random sampling was used to select both consultants and contractors. Consultants were selected from active members on the register of their respective professional institutes while contractors (in categories A to D) were selected from the Construction Industry Federation of Zimbabwe (CIFOZ) register of contractors for Contractors in category A have unrestricted tender ceilings while category D contractors may tender for works not exceeding US$1,500,000. s were also used to ensure a wider geographical spread of respondents. Despite increasing geographical spread of respondents, Harare (capital city) and Bulawayo (second largest c- ity) had the majority of respondents. The two cities collectively account for over 80% of practicing consultants and registered contractors. A total of 43 responses were achieved comprising 21 contractors (representing 20% of the population) and 22 consultants (representing 22% of the population). According to Freund and Simon (1992) as cited by Proverbs et al. (1999), the achieved sample of 43 exceeds the minimum of 30 for assumed normality and homogeneity and therefore satisfies the requirements of a robust and valid statistical analysis. 3.2 Data Collection Methods Structured questionnaires were used to get the views of consultants (quantity surveyors, architects, engineers, and project managers) and contractors from the building industry in Zimbabwe on the relative importance of 40 pre-selected factors on labor productivity. The structured questionnaire was preferred because of the 59

4 relative ease of providing standard data suitable for the research quickly and economically (Makulsawatudom and Emsley 2001; Alinaitwe et al. 2007).The questionnaire was built around the factors affecting labour productivity drawn from previous studies. Consultants and contractors expressed their opinion, by way of ranking on a likert scale (from 1 least important to 5 extremely important), the relative impact of pre-selected factors on labor productivity. The literature driven factors were further classified into seven main categories/groups according to their characteristics, namely: materials related factors, technical related factors, plant and equipment related factor, management related factors, manpower related factors, motivation related factors and other factors. In addition to structured questions, the questionnaire included some open-ended questions to collect qualitative data that could generate unexpected insights not otherwise possible from quantitative data alone (Bhattacherjee 2012). Secondary data was gathered from relevant literature including journal articles, conference proceedings, textbooks and other documents existing in the public domain. 3.3 Data Analysis Mean Response (MR), Relative Importance Index (RI- I) and Spearman s rank correlation were used to analyse the ratings given by the respondents. Based on MR values, the most significant factor in a subset is the one with the highest MR value (Durdyev et al. 2013). E- q. (1) (modified from Durdyev and Mbachu 2011), Eq. (2) (Durdyev and Mbachu 2011) and Eq. (3) (Naoum 2013) were used to compute MR, RII and Spearman correlation ranking respectively. The mean rating is defined as: 5 R pjk R jk MR j = T R k=1 (1) where, MR j = Mean Rating for constraint factor j; R pjk = Rating point k (ranging from 1-5); R jk = Responses to rating point k, for constraint factor; T R = Total responses. The relative importance index is defined as: RII = MR j n j=1 MR j The Spearman s rank correlation is defined as: ρ = 1 6 d 2 i n(n 2 1) (2) (3) where, d i = difference in paired ranks and n = number of cases. The Spearman rank collection was calculated to compare opinion ratings of consultants and contractors. The analysis aimed at establishing that the ratings had not been arrived at by chance but rather that there was true agreement in ratings (Alinaitwe et al. 2007). 4 RESULTS ANALYSIS AND DISCUSSIONS 4.1 Respondents Demographics A total of 43 questionnaires were completed and analysed. The respondents construction industry work experience ranges from 1year to 31 years and the average work experience is years. The respondents were made up of contractors (48.8%) and consultants (51.2%). Contractors in category A accounted for 50% of participating contractors whilst category B, C and D contractors accounted for 22%, 17% and 11% respectively. The demographics of respondents who participated in the study shows that they had relevant technical experience to provide valid assessments of the factors presented in the questionnaire. 4.2 Factors Affecting Labor Productivity The study noted that numerous factors impinge on construction labor productivity in Zimbabwe. Since the Spearman rank correlation computation showed a strong positive correlation of between both sets of rank-ordered mean rating values computed from consultants and contractors ratings for the factors, a combined analysis of such views is provided on Table 1. Based on Pareto rule, the highest ranked factor is as- Table 1. Contractors and consultants rating of factors affecting labour productivity Factor Overall Overall Contractor Consultants Group Mean Rank MR R MR R Unavailability of Material Material Late Payment of Salaries and Wages Motivation Suitability/Adequacy of Plant and Equipment Plant & Equipment Supervisory Incompetence Management Lack of Manpower Skills Manpower Lack of labour experience Manpower Plant Breakdown Plant & Equipment Late Deliveries of Material Material Shortage of Tools and Equipment Plant & Equipment Low remuneration Motivation 60

5 sumed to have the greatest influence (Alinaitwe et al. 2007). The results show the factors with significant impact on labor productivity in descending order of importance are as follows: unavailability of material, late payment of salaries and wages, suitability of plant and equipment, supervisory incompetence, lack of manpower skills, lack of labour experience, plant breakdown, late delivery of material, shortage of tools and equipment, and low remuneration. Those factors with the greatest influence on construction labor productivity are drawn from five group categories, i.e. materials related factors (unavailability of materials, late delivery of materials); manpower related factors (lack of manpower skills, labour inexperience); motivation related factors (late payment of salaries and wages, low remuneration), plant and equipment related factors (suitability/adequacy of plant and equipment, plant breakdown, shortage of tools and equipment); and management related factors (supervisory incompetence). The analysis was extended to look at the impact of group factors on labor productivity and their effect was ranked in descending order as follows: plant and equipment related factors, materials related factors, management related factors, manpower related factors, motivation related factors, technical related factors and other factors. Table 2 provides details of the breakdown of the ratings for individual and group factors. Plant and Equipment Related Factors Plant and equipment related factors are the top rated group factor affecting labor productivity. Of the 40 factors affecting labor productivity, suitability/adequacy of plant and equipment; plant breakdown; and shortage of tools and equipment were ranked 2nd, 7th and 9th respectively. Lack of suitable plant and equipment affects labor productivity since labor relies on plant, equipment and tools to aid the production process. These results reaffirm the observation by the former President of CIFOZ, that most of the plant and equipment owned by construction companies is antiquated such that they cannot perform tasks efficiently (Nyakazeya 2012). In addition, available plant is expensive to purchase and is therefore beyond the reach of many indigenous contractors. Thus, apart from the efforts by made by CIFOZ in 2011 to negotiate for mechanisation finance from financial institutions for its members, more interventions are still required. In an earlier study by Kim et al. (2005) it was observed that technological application is the most effective way of improving site labor productivity. In Zimbabwe, the problem is further compounded by plant breakdown as a result of old age and/or unavailability of spares. In USA, UK, Indonesia and Palestine, shortage of tools and equipment was also noted to have a strong effect on labor productivity. For example, in the Gaza strip results of a study done by Enshassi et al. (2007) showed that shortage of tools and equipment had a high effect on labor productivity ranking 10th out of the 45 factors studied. These observations serve to show that labor productivity is complemented by availability of a certain level of plant, tools or equipment. Materials Related Factors The results of the study show that unavailability of materials on the local market and on site is a factor with the greatest influence on labor productivity on building projects in Zimbabwe. Without materials, labor will be idle since a greater part of building production involves use of materials. Previous studies in Zimbabwe showed that the building materials manufacturing industry had not been fully capacitated to supply the building industry with all the material demands (Chigara and Mangore 2012). The problem is further compounded by the internationalization of designs where most designers are incorporating materials that are not locally manufactured. Against this background, CIFOZ has been advocating for laws that compel designers to incorporate locally manufactured materials in their designs (Nyakazeya 2012). In addition, late delivery of materials on projects also affects labor productive time. Further exacerbating the problem is poor material supply chain management which subsequently delays delivery of materials. A study by Chigara et al. (2013) observed that material related challenges were amongst significant factors negatively impacting on cost management efforts by building contractors in Zimbabwe. These findings in Zimbabwe concur with findings from other countries like Nigeria, Indonesia, USA, UK, Thailand and Palestine where shortage of materials was rated as a top factor affecting labor productivity (Olomolaiye et al. 1987; Kaming et al. 1997; Makulsawatudom and Emsley 2001; Enshassi et al. 2007). Management Related Factors Management related factors are rated 3rd amongst group factors affecting labor productivity. Specifically, supervisory incompetence was rated 4th out of 40 factors that affect labor productivity. Poor planning, coordination and control of construction activities affects the overall organization of construction process, increasing waiting and idle times, duplication of effort, double handling of materials all of which contribute to reduction in productivity. In a study on masonry productivity, Popescu et al. (2003) noted that the ability of the foreman with regard to planning, scheduling, and laying out of work also extensively affects masonry productivity. However, in the Zimbabwean building industry, a foremen/supervisor who is normally tasked with supervision of site works is a tradesman who is normally lacking human resources and project management skills. 61

6 Table 2. Composite analysis Item Factors Level of Importance TR MR RII Rank Grp Grp Grp MR RII Rank Maximum Value 43 1 A. Plant and equipment related factors Suitability or adequacy of Plant and equipment 2 Plant breakdown Shortage of tools and equipment Inefficiency of equipment B. Material related factors Unavailability of material Late deliveries of material Insufficient or poor material handling C. Management related factors Supervisory incompetence Instruction delays Inspection delays Lack of coordination Poor communication Poor management practice Poor relations between management and workers 15 Increasing labourers in order to accelerate works 16 Compliance to statutory regulations (NSSA, NEC) D. Manpower related factors Absenteeism Working for long periods without holiday 19 Lack of manpower skills Lack of labour experience Inappropriate use of skills E. Motivational related factors Low remuneration Lack of incentive schemes Availability of site facilities Worker retention schemes Lack of worker respect or recognition Health and safety provisions Lack of training sessions Late payment of salaries and wages F. Technical related factors Alterations of design during project execution 31 Poor site layout and organization Incomplete drawings Poor site conditions project complexity Construction methods Crew size inefficiency Alterations of schedule Reworks G. Other factors Inclement weather On-site accidents

7 Manpower Related Factors Lack of manpower skills and labor inexperience negatively affects labor productivity. The Zimbabwean building industry suffered from mass exodus of skilled personnel to greener pastures in neighboring countries and across continents during the year 2000 through to 2008 (Chigara and Mangore 2012). This period marks the great economic depression in Zimbabwe. Due to lack of skill, the remaining craftsmen are producing at far less than industry gazetted standard output. A study by Chigara et al. (2013) showed that labor inexperience and lack of appropriate skills significantly constrained contractors efforts to manage costs on building projects in Zimbabwe. Enshassi et al. (2007) indicate that experience improves both the intellectual and physical abilities of labor force, which directly increase labor productivity. In Turkey, lack of local experienced labour ranked 1st among the 24 factors identified, thus making it the most significant factor affecting labor productivity of Turkish contractors (Durdyev et al. 2013). However, other manpower related factors such as absenteeism and working for long periods have minimal effect on labor productivity in Zimbabwe as witnessed by their lower ranking. The foregoing observations are at contrast with findings in Nigeria, Indonesia, and Thailand, where absenteeism was rated among the top ten factors affecting productivity (Olomolaiye et al. 1987; Kaming et al. 1997; Makulsawatudom and Emsley 2001). Motivation Related Factors Although motivational factors are collectively ranked 5th, sub-factors like late payment of salaries and wages, and low remuneration are highly rated at 2nd and 10th amongst the 40 selected factors impinging on labor productivity. Workers perform better if they are well motivated. According to Stoner et al. (2009) motivating is the management process of influencing people s behaviour based on this knowledge of what makes people tick. However, late payment of salaries and low remuneration lowers worker morale and thus reduces productivity. In the Gaza strip, Enshassi et al. (2007) noted that payment delay has a high impact on productivity rating 6th out of 45 factors. Apart from late payment and low remuneration, other motivation related factors such as health and safety provisions, lack of incentive schemes, lack of worker retention schemes, were found to have less effect on labor productivity. Technical Related Factors Technical related factors are rated 6th among group factors. In spite of the fact that technical related factors are highly rated in some countries, they are not among those found in the top ten factors affecting labor productivity on building projects in Zimbabwe. The highest rated technical factors, that is, incomplete drawings and alterations of drawing during construction, are rated 17th and 22nd respectively. Apart from the massive loss of skilled and experienced personnel, and supervisory deficiencies, rework (rated 29th) is not considered as a strong factor influencing labour productivity. These findings are justified by the fact that not all the experienced labour was lost and that continued training and improvement in the national economy is re-attracting (although at a slow pace) previously migrated skills back home. Whilst not contrasting from findings obtaining from some African countries, the results are at variance with observations in Indonesia and New Zealand where rework is considered a critical factor on labour productivity. 5 CONCLUSIONS AND RECOMMENDATIONS Labor is a key resource on building projects and effective management of the resource to achieve optimal productivity cannot be overemphasised. In Zimbabwe, the building industry is mostly labor intensive and therefore this study sought to identify the key factors that affect labor productivity on building projects. Structured questionnaires were used to get opinion of contractors and consultants on the relative impact of 40 pre-selected factors on labor productivity on building projects. Simple random sampling was used to select consultants and contractors from registration database of their respective professional institutes and the Construction Industry Federation of Z- imbabwe database respectively. The Spearman s rank correlation was used to ascertain correlation of opinion of consultants and contractors, whilst mean response and relative importance index were used to analyze the results. A total of 43 questionnaires were completed and analyzed and the computed Spearman s rank correlation showed strong positive correlation between the views of consultants and contractors. The results identified and ranked (according to importance) the factors that affect labor productivity on building projects in Zimbabwe. Numerous factors were noted to have an impact on labor productivity. However, unavailability of materials, late payment of salaries and wages, suitability/adequacy of plant and equipment, supervisory incompetence, lack of manpower skills, lack of labor experience, plant breakdown, late delivery of materials, shortage of tools and equipment, and low remuneration, in that order, are the 10 most important factors affecting labour productivity on building projects in Zimbabwe. The analysis was extended to look at the relative importance of group factors on labour productivity and they were ranked in descending order as follows: plant and equipment related factors; materials related factors, management related factors; manpower related factors; motivation related factors; technical related factors and other factors. Whilst these results 63

8 are a reflection of the situation obtaining in Zimbabwe at the time of the study, they also relate to findings from other countries as discussed under results analysis and discussions. The research therefore recommends: i contractors and other building industry practitioners to dedicate their efforts to managing those factors that significantly impact on labor productivity. This can be achieved through adequate work planning, coordination and management of the construction process with more emphasis on implementation of efficient systems for procuring materials, tools and equipment; worker motivation; continuous professional development schemes for workers; ii performance appraisal of workers and rewards for achieving or exceeding targets; and iii timeous payment of market based salaries and wages to attract and retain skilled and experienced workmen. REFERENCES Adamu, K. J., Dzasu, W. E., Haruna, A., and Balla, S. K. (2011). Labor productivity constraints in the Nigerian construction industry. Continental Journal of Environmental Design and Management, 1(2), Alinaitwe, H. M., Mwakali, J. A., and Hansson, B. (2006). Assessment of the degree of industrialization in construction - case of Uganda. Journal of Civil Engineering and Management, 12(3), Alinaitwe, H. M., Mwakali, J. A., and Hansson, B. (2007). Factors affecting productivity of building craftsmen - studies of Uganda. Journal of Civil Engineering and Management, 13(3), Alwi, S. (2003). Factors influencing construction productivity in the indonesian context. Proceedings of the Eastern Asia Society for Transportation Studies, 4, Ameh, O. J. and Osegbo, E. E. (2011). Study relationship between time overrun and productivity of construction sites. International Journal of Construction Supply Chain Management, 1(1), Attar, A. A., Gupta, A. K., and Desai, D. B. (2012). A study of various factors affecting labor productivity and methods to improve it. IOSR Journal of Mechanical and Civil Engineering - Second International Conference on emerging trends in engineering, Bhattacherjee, A. (2012). Social Science Research: Principles, Methods and Practices. University of South Florida, Florida, United States. Business Day Live (2013). Employers Warn of Job Cuts unless Productivity Rises. Available at < (accessed on 03/09/2013). Chan, P. (2002). Factors affecting labor productivity in the construction industry. Proceedings of the Eighteenth Annual ARCOM Conference, University of Northumbira, Association of Researchers in Construction Management, Chigara, B. and Mangore, E. (2012). An analysis of the implications of resources management on building projects performance in Harare and Bulawayo. International Journal of Marketing and Technology, 2(9), Chigara, B., Moyo, T., and Mudzengerere, F. H. (2013). An analysis of cost management strategies employed by building contractors on projects in Z- imbabwe. International Journal of Sustainable Construction Engineering & Technology, 4(2). Dozzi, S. P. and AbouRizk, S. M. (1993). Productivity in Construction. National Research Council, Canada. Durdyev, S., Ismail, S., and Bakar, N. A. (2013). Construction productivity in Turkmenistan: Survey of constraining factors. International Journal of e- Education, e-business, e-management, e-learning, 3(1), Durdyev, S. and Mbachu, J. (2011). On-site labor productivity of New Zealand construction industry: Key constraints and improvement measures. Australasian Journal of Construction Economics and Building, 11(3), Enshassi, A., Mohamed, S., Mustafa, Z. A., and Mayer, P. E. (2007). Factors affecting labor productivity in building projects in the Gaza strip. Journal of Civil Engineering and Management, 13(4), Intergraph Corporation (2012). Factors Affecting Construction Labor Productivity: Managing Efficiency in Work Planning. Intergraph, United States. Jarkas, A. M. and Bitar, C. G. (2012). Factors affecting construction labor productivity in Kuwait. Journal of Construction Engineering and Management, 138(7), Jergeas, G. (2009). Improving Construction Productivity on Alberta Oil and Gas Capital Projects. A report submitted to Alberta Finance and Enterprise, University of Calgary, Alberta, Canada. Kadir, M. R. A., Jaafar, M. S., Sapuan, S. M., and Ali, A. A. A. (2005). Factors affecting construction labor productivity for Malaysian residential projects. Structural Survey, 23(1), Kaming, P. F., Olomolaiye, O., Holt, G. D., and Harris, F. C. (1997). Factors influencing craftsmen productivity in Indonesia. International Journal of Project Management, 15(1), Kim, G., An, S., Cho, H., Seo, D., and Kang, K. (2005). Improved productivity using modified table formwork system for high-rise building in Korea. Building and Environment, 40, Makulsawatudom, A. and Emsley, M. (2001). Factors affecting the productivity of the construction industry in Thailand: The project managers perception. 64

9 17th Annual ARCOM Conference, University of Salford, United Kingdom, Mojahed, M. (2005). A Project Improvement System for Effective Management of Construction Projects. PhD Thesis, Agricultural and Mechanical College, Louisiana State University, United States. Naoum, S. G. (2013). Dissertation Research and Writing for Construction Students. Elsevier, Oxford, U- nited Kingdom. Nyakazeya, P. (2012). Zimbabwe: Construction sector to grow. Financial Gazette, 26th June. OECD (2001). Measuring productivity - OECD Manual - Measurement of Aggregate and Industry-level Growth. Organisation for Economic Co-operation and Development, France. Olomolaiye, P. O., Wahab, K. A., and Price, A. D. F. (1987). Problems influencing craftsmen s productivity in Nigeria. Building and Environment, 22(4), Picard, H. E. (2003). Driving down construction project labor cost. The Second International Conference on Structural and Construction Engineering, Rome, Italy. Popescu, C. M., Phaobunjong, K., and Ovararin, N. (2003). Estimating Building Costs. CRC Press. Proverbs, D. G., Holt, G. D., and Olomolaiye, P. O. (1999). Construction resource/method factors influencing productivity for high rise concrete construction. Construction Management and Economics, 17, Soham, M. and Rajiv, B. (2013). Critical factors affecting labor productivity in construction projects: Case study of Gujarat region of India. International Journal of Engineering and Advanced Technology, 2(4), Stoner, A. F., Freeman, R. E., and Gilbert, J. D. (2009). Management. Pearson Prentice Hall, India. Umoru, D. and Yaqub, O. (2013). Labour productivity and health capital in Nigeria: The empirical evidence. International Journal of Humanities and Social Science, 3(4), Yates, J. K. and Guhathakurta, S. (1993). International labour productivity. Cost Engineering, 35(1), Zimstat (2014). Quarterly Digest of Statistics: Quarter Zimstat, Harare, Zimbabwe. 4th 65