The Economic Model Of Productivity Construction Essay

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In the past, several studies about labor productivity in the construction were done. Some of them are related to quantifying the impact of productivity factors. Quantitative evaluations about the effects of those factors are required for many purposes, including construction estimating, planning, scheduling, and proof of damages for the construction claims. However, an extensive review of relevant literature reveals that it is difficult to quantify such an impact, and there are currently no universally accepted standards for quantifying factors affecting productivity loss in the construction industry. This lack of a means for quantifying impact highlights the need to enhance quantitative evaluations for the factors affecting productivity in building construction, which is the subject of this study.

Achieving better labor productivity requires detailed studies of the actual cost of labor. Various labors have different variables affecting their levels of productivity. For every project, productivity, cost, quality, and time have been the main concern. Better productivity can be achieved if project management includes the skills of education and training, method of work, personal health, motivational factors, type of tools, machines, equipment and materials required, personal skills, workload to be executed, expected quality of work, location of work, type of work to be done, and supervisory personnel (Rowlinson and Proctor, 1999).

Improving productivity is a significant concern for any profit-oriented organization, representing the effective and efficient conversion of resources into marketable products and determining business profitability (Wilcox et al., 2000). Consequently, considerable effort has been directed to understand the productivity concept with the different approaches taken by researchers, resulting in a wide variety of productivity definitions (Lema, Samson, 1995; Oglesby et al, 2002; Pilcher, 1997).

A survey conducted by (Bernstein and Lemer 1996) states that 10 million people are employed in the U.S. construction industry. Thus, considering drawings, designs, new construction, renovations, equipment, and material manufacturing, it can be said that the construction industry is one of the largest manufacturing industries in the USA.

1.2. Background About Productivity

Productivity is generally defined as the average direct labor hours required to install a unit of material. It is said that perfect productivity (1.0) can be achieved with a 40-hour work week, with people taking all the holidays and vacation days as planned, all of the engineering drawings would be 100% complete there would be no delays of any kind; everyone would work safely; everything would fit perfect first time; the weather would be 70 oF; and there would be no litigation at the end of the project (Rowlinson and Proctor, 1999).

Productivity, in general, represents the conscious growth of a society or an organization in its ability to improve the value or the quality of its products or services. The success of an organization can be more clearly measured by its productivity growth than by its growth in profits. However, productivity is theoretically defined as a ratio between output and input. In the context of the construction industry, the output is the structure, or facility, that is built or some component. The major inputs for the construction process include manpower, materials, equipment, management, energy, and capital (Bodek, 1985).

1.3. Definition of Productivity in the Construction Industry

The term "productivity" expresses the relationship between outputs and inputs (Borcherding and Liou, 1986). Output and input differs from one industry to another. Also, the productivity definition varies with the application to different areas of the same industry. In the construction industry, there is a need for using different models, such as the economic model, the project-specific model, and the activity-oriented model (Davies, Thomas, 1990).

Productivity = Outputs

Input

Equation 1.1

The Project-Specific Model Productivity = Square Feet Output

Dollars of Input

Equation 1.2

The Activity-Oriented Model Productivity = Output

Labor cost

Equation 1.3

The Economic Model of Productivity = Dollars of Output

Dollars of Input

Equation 1.4

Labor is one of the basic requirements in the construction industry. Labor productivity usually relates manpower in terms of non-hour or labor cost to the unit of outputs produced (Borcherding and Liou, 1986. In other words, the definition of labor productivity is the amount of goods and services produced by a productive factor (manpower) in the unit of time (Drewin, 1982).

Ouesnat (Vaggi, 1987) says the origin of the word "productivity" can be traced back to 1766. In 1883, Littre defined productivity as the "faculty to produce," that is, the desire to produce (Jarkas, 2005). In 1950, the Organization for European Economic Cooperation (OEEC) introduced the definition of productivity as a quotient obtained by dividing the output by one of the production factors (Sumanth, 1984). Depending on measurement objectives and the availability of data, several productivity definitions are encountered. The U.S. Department of Commerce defines productivity as "dollars of output per person-hour of labor input" (Adrian, 1987).

1.4. Importance of Productivity

Productivity has a great significance in construction. Labor productivity constitutes a considerable share of production input for construction. In the construction industry, there are many external and internal factors that are never constant and are difficult to anticipate. This factor leads to a continuous variation in labor productivity. It is necessary to make sure that a reduction in productivity does not affect the plan and schedule of the work and does not cause delays. The consequences of these delays could result in serious money losses. Further, considerable cost can be saved if productivity is improved because the same work can be produced with less manpower, thus reducing overall labor cost (Thomas, 1991).

1.5. Measurement of Productivity

It is difficult to measure productivity with construction work due to the uniqueness and various operations of construction projects (Sweis, 2000). Construction labor productivity is typically measured as labor hours per quantity of material installed. When a contractor, or an assigned crew, does not accomplish the anticipated or planned production rate, labor productivity loss is experienced. In other words, a loss of productivity is when it takes extra labor and equipment to do the same amount of work, thereby increasing project costs. There are many causes for labor productivity impacts on a construction project, stemming from owners, contractors, and construction managers. Common causes include, but are not limited to, mismanagement, maladministration, site-access restrictions, differing site conditions, defective plans and/or specifications, changes in the work, labor availability, turnover, rework, testing/inspections, overtime and/or shift work, interferences, changes in construction means and methods, out-of-sequence work, and differing weather conditions (Sweis, 2000).

1.6. Problem Statement

Loss of productivity is one of the most serious problems in the construction industry. Research studies confirm that productivity loss results from several causes, including excessive change orders, long periods of overtime, poor field management, and extreme weather (Alarcon and Borcherding, 1991; Leonard, 1987; Sanders and Thomas, 1991; Thomas and Oloufa, 1995).

Construction labor cost is estimated to be 33-50% of the total project cost (Hanna, et al 2005). In labor-intensive construction, the profit margins are typically 2-3% of the total project cost. As labor is more variable and unpredictable than other project-cost components, it becomes necessary to understand the effects of different factors on labor productivity. Compared to other project-cost components, such as material and equipment, labor cost has more opportunity to improve by proper management. An increase in productivity reduces the labor cost in direct proportion. It can either benefit or reduce a project's profit, making it of vital interest to the construction industry (Hanna, et al 2005).

Of the typical project-cost components (materials, equipment, and labor), labor is considered the element containing the most risk. The other cost components (materials and equipment) are predominately determined by the market price and are, consequently, beyond the influence of project management. As a result, the management of labor and its productivity becomes paramount in determining the success of a project.

1.7. Misconceptions About Construction Productivity

A study from Adrian (1990) states the following general misconceptions about labor productivity:

In the construction industry, labor is the key factor for low productivity.

Because the construction industry is controlled by the weather, productivity cannot be improved.

The construction industry will always be an unfavorable relationship process.

1.8. Facts About Construction Productivity

Following are a few facts about the construction productivity studied by Adrian (1990):

Compared to any other day of the week, labor is most productive on Tuesday.

The most productive time of the day for labor is around 10 a.m.

The least productive time frame for labor is right before the finishing time.

Laborer is capable of lifting approximately 94 pounds on his own.

If the laborer is engaged in performing the same task repeatedly, there will be a chance of low productivity after 60-70 minutes of performing the same work.

Friday has been proven to be the least productive day of the week.

1.9. Aim and Objective

Poor productivity of craftsmen is one of the causes for cost and time overruns on building projects. Productivity of labor is of great importance, especially in developing countries where most of the building work is still done manually (Alinaitwe, 2005). The objective of this study focuses on views from the construction industry about various factors affecting labor productivity, analyzes factors affecting labor productivity impact, and suggests appropriate measures that can be taken to improve labor productivity. The aim is supported by the following objectives.

To study and discuss various factors affecting labor productivity in the construction industry.

To analyze and calculate the Relative Important Index (RII) of those factors affecting labor productivity.

To make recommendations to improve labor productivity in construction.

Background of Productivity

Conclusion/Recommendation

Data Analysis

Data Preparation

Data Collection

Pilot Survey

Questionnaire Design

Literature Review/Issue Identification

Figure 1.1. Flow Chart Showing Research Structure.

CHAPTER 2. LITERATURE REVIEW

2.1. Review of Previous Study

Prior to the mid-1960s, the construction industry reflected a rise in productivity (Stall, 1983). Since then, poorer productivity has been one of the most commonly discussed topics in the construction industry. In 1968, the Construction Roundtable was established due to concern about the increased cost of construction resulting from an increase in the inflation rate and a significant decline in construction productivity (Thomas and Kramer, 1988). Also in 1965, the United Nations Committee on Housing, Building, and Planning (UNC) published a significant manual concerning the effect of repetition on building operations and processes (UNC, 1965). The study revealed that the need for an increase in productivity was probably more intense in the construction industry than in many other industries. It was necessary to adopt, as far as possible, industry-wide principles of production throughout the building process. However, it was recognized that careful adaptation would be required to implement the knowledge and experience gained in the manufacturing industry to the building construction industry (Borcherding and Alarcon, 1991).

Many researchers around the world have done different studied on various factors that affect productivity; in spite of these studies, there are many productivity problems that remain unknown and need to be further investigated, even in developed countries (Makulsawatudom and Emsley, 2002). A study by (Polat and Arditi, 2005) stated that policies for increasing productivity are not necessarily the same in every country. Their study identified factors affecting labor productivity and grouped the factors according to their characteristics: design, execution plan, material, equipment, labor, health and safety, supervision, working time, project factor, quality, financial, leadership and coordination, organization, owner/consultant, and external factors.

(Adrian, 1987) classified the factors causing low productivity as industry-related factors, labor-related factors, and management-related factors. Industry-related factors, essentially, are the characteristics of the construction industry, such as the uniqueness of construction projects, varied locations, adverse and variable weather, and seasonality. Labor-related factors include the union's influence, little potential for learning, and lack of motivation. Management-related factors usually refer to a lack of management for tools or techniques.

(Olomolaiye et al, 1998) divided the productivity factors into two categories, external factors representing those outside the control of the firm's management and internal factors on behalf of productivity factors originating within the firm. From his viewpoint, the nature of the industry, usually the separation of design and construction functions, has affected construction productivity through waiting for drawings, design changes, and subsequent rework. The construction clients have sometimes been impediments to construction productivity because of their lack of adequate knowledge about construction procedures. Moreover, being an outdoor industry, construction performance is extremely affected by the weather conditions. The level of economic development also affects productivity. In addition to the factors described above, health and safety legislation, procurement policies, and codes of practices are other external factors influencing site practice and productivity. In the internal category, management inadequacies could result in a waste of resources with consequent losses in productivity; adoption of advanced technology and training for the laborer would improve productivity.

(Thomas and Sakarcan, 1994) built a model to describe the factors affecting labor productivity. In the model, two groups of factors determine the productivity performance, work environment and work to be done. Work-environment factors refer to how well a job is organized and managed. Work to be done, or work content, relates to work that needs to be done and encompasses physical components of work, specification requirements, and design details.

Past study show the work to be done could affect the total cumulative labor resources by as much as 15%, whereas work environment can affect labor requirements by an additional 25%. Based on this factor model, research was done in more detail. One study suggested that scheduled overtime always leads to losses of efficiency because of the inability to provide materials, tools, equipment, and information at an accelerated rate (Ginther, 993)

Surveys and interviews are standard methods that have already been adopted in many productivity studies. (Lim and Alum, 1995) conducted a survey of top civil engineering and building contractors to identify the factors affecting productivity in Singapore. The three items of greatest concern were identified as difficulty in the recruitment of supervisors, difficulty in the recruitment of labors, and a high rate of labor turnover. (Portas and AbouRizk, 1997) undertook a questionnaire of superintendents and project managers to determine all possible factors affecting productivity. An interview conducted with contractors showed that weather and material delivery were the main adverse factors for site productivity (Hassanein and Melin, 1997). A questionnaire identified rework, material problems, tools, heavy equipment availability, crew interference, overcrowded work areas, instruction, quality-control inspection, and management interventions as the main factors affecting craftsman productivity and motivation (Chang and Borcherding, 1985).

Another survey on construction personnel (Hanna and Heale, 1994) was conducted to gauge the opinion of personnel in the field of construction, specifically their knowledge about the factors that most affect construction productivity. As a result, a set of comprehensive factors was identified and classified into six groups: contract environment, planning, site management, working conditions, working hours, and motivation.

(Ng et al, 2004) found that the morale of workers at the civil engineering sites visited was relatively low, with demotivation occurring due to extensive rework, overcrowded work areas, problems in crew interfacing, availability of tools, delays in inspection, availability of materials, and incompetence of site foremen. The results indicates that the total time lost in the 7 civil engineering projects surveyed due to demotivation of workers ranged from 5.1 to 13.6 man hours/week, with the most significant time lost being caused by a lack of material availability, overcrowded work areas, and rework resulting of poor management and poor communication at the site. Should management have been sensitive to these demotivators, it was possible that their impact could have been reduced. The study also showed that project value was found to have a negative correlation with the time loss due to demotivation, indicating that, as project size increases, time loss decreases. Managers also needed to be aware that higher time losses can occur during the immediate stages of projects. As projects progress towards their peak at the site activity, more activities from workers will be involved, and coordination and communication problems will be inevitable. By paying more attention to construction employees at this stage, it may be possible for project managers to address these problems before they grow further.

2.2. Different Factors Affecting Labor Productivity from Previous Studies

Productivity is the outcome of several interrelated factors. Discussed below are various factors affecting labor productivity in construction reviewed from previous study.

Time: During construction projects, there are numerous circumstances and events which may cause a loss of productivity. It has been consistently documented over the years that productivity typically declines as overtime work continues. The most commonly stated reasons for this result include fatigue; increased absenteeism; decreased morale; reduced supervision effectiveness; poor workmanship, resulting in higher-than-average rework; increased accidents; and others On average, no matter how many hours a week one works, one will only achieve 50 hours of results. Overtime work will initially result in increased output if it is continued for a prolonged period; the output may actually decline for the reasons stated earlier. Thus, long-term overtime may lead to increased costs and decreased productivity (Hinze, 1999). The effect of continued overtime work on labor productivity is, perhaps, one of the most studied productivity loss factors in the construction industry. Time used by a construction laborer on productive activities averages about 30% of the total time available. An employee in the field only works effectively for 3.5 hours of his 8-hour shift and spends 20% of his time on direct value-adding activities (Alinaitwe et al., 2005).

Overtime is defined as the work performed over 8 hours/day or 40 hours/week. Overtime can occur in a variety of schedules, including 5 days with 10 hours worked per day [5(10) s, 7(8) s, 6(10) s or 7(10) s] (Hanna et al, 2005). Short-Term overtime is using up to 50 or 60 hours per week for 1 or 2 weeks, and it is used to meet specific project targets or to minimize downtime during a plant shutdown. There are added costs for this short-term overtime, but productivity and safety can be controlled by increased supervision and planning. When overtime is used for more than two weeks, the effects of extended overtime start to take effect. Fatigue from longer hours of physical labor, overextended supervision, material shortages, increased accidents, and other issues are all factors. Laborers start to take personal days and turnover increases. Eventually, the work completed each week approaches the level that could have been completed in 40 hours (Hanna, et al 2005). Overtime achieves schedule acceleration by increasing the number of hours worked by laborers beyond the typical 40 hours per week. Past research indicates that labor productivity can be negatively impacted by overtime, causing problems such as fatigue, reduced safety, increased absenteeism, and low morale (Horner and Talhouni, 1995).

Willingness to Work: Motivation and morale of people are extremely important factors that determine productivity. These factors are affected by wage-incentive schemes, labor participation in management, communication systems, informal group relations, promotion policy, union management relations, and quality of leadership, working hours, sanitation, ventilation, subsidized canteen, and company transport (Kumar Cited in Desai 2004).

Schedule Compression: Contractors are not legally bound to prove that contract performance was extended to recover lost productivity. When there are delays early in a project, compressions of the overall time frame for a later activity are often the way to make up for delays and to finish the project on time. From a strict scheduling perspective, schedule compression may be possible to do without accelerating individual work activities by utilizing float in the project's overall schedule. However, on many projects, schedules are not fully resource loaded. As a consequence, a properly updated schedule reflecting the delays may show the project finishing on time without shortening individual activities. Schedule compression may result in over manning of the work by the contractor due to shortening the overall duration, allowing the contractor to complete the total remaining work. Schedule compression, when associated with over manning, often results in significant productivity losses due to dilution of supervision; shortages of materials tools or equipment to support the additional labor; increased difficulty in planning and coordinating the work; and shortages of skilled labor (National Electrical Contractors Association, 1983).

Type of Project: To achieve significant productivity, each member of a crew requires sufficient working space to perform work without being interfered with/by the other laborers. When more laborers are assigned to work in a fixed amount of space, it is probable that interference may occur, thus decreasing productivity. Additionally, when multiple trades are assigned to work in the same area, the probability of interference rises and productivity may be reduced. Interference among the various crews and laborers is caused by mismanagement on construction sites. For example, steel fixtures crew will have to wait before fixing the reinforcement rods if the carpenter has not completed the formwork. Types of activities and construction methods also influence labor productivity (Thomas and Sanders, 1991).

Safety: Accidents have high impacts on labor productivity. Various types of accidents occur on the site, such as an accident causing death and resulting in a total work stoppage for a number of days. An accident that causes an injured to be hospitalized results in a decrease in work of the crew for which the injured worked. Small accidents resulting from nails and steel wires can stop work and, thus, decrease productivity (Thomas and Sanders, 1991). Even insufficient lighting shows decreased productivity because sufficient lighting is required to work effectively and because insufficient lighting has negative effects. Employment of a safety officer helps laborers to understand the required safety regulations and to follow them, which can prevent and reduce the number of accidents, thus increasing productivity.

Quality: Inefficiency of equipment and poor quality of the raw material are the factors which cause low productivity. Because the productivity rate of inefficient equipment is low, old equipment is subjected to a large number of breakdowns, and it takes a long time for the laborers to complete the work, thus reducing productivity. Poor-quality material used for work is the other factor because poor materials lead to poor work which can be rejected by the supervisors, thus reducing the productivity.

Managerial Factors: The competence and attitudes of managers have a crucial bearing on productivity. In many organizations, productivity is low despite the latest technology and trained manpower. Low productivity is due to inefficient and indifferent management. Competent and dedicated managers can obtain extraordinary results from ordinary people. Employees' job performance depends on their ability and willingness to work. Management is the catalyst to create both. Advanced technology requires knowledgeable laborers who, in turn, work productively under professionally qualified managers. It is only through sound management that optimum utilization of human and technical resources can be secured.

Manpower group: Literature shows that a lack of labor experience is the factor which negatively affects labor productivity and proves that, to achieve good productivity, labor plays a significant role. Contractors should have sufficiently skilled laborers employed to be productive. If skilled labor is unavailable and a contractor is required to construct a project with less-skilled labor, it is probable that productivity will be impacted. The absence of any member of the crew may impact the crew's production rate because workers will, typically, be unable to accomplish the same production rate with fewer resources or, perhaps, a different mix of skill and experience levels. Misunderstanding among laborers creates disagreements about responsibilities and the work bounds of each labor, which leads to a lot of work mistakes and decreases labor productivity. Lack of compensation and increased laborer age negatively affect labor productivity because labor speed, agility, and strength decline over time and reduce productivity (Heizer and Render, 1990).

Motivation: Motivation plays a part in enhancing construction labor productivity. Motivation can best be accomplished when laborers are able to merge their personal ambitions with those of the company. Thus, motivation can be defined as the willingness to exert a high level of effort to reach organizational goals, conditioned by the efforts' ability to satisfy some individual need. Factors such as payment delays, lack of a financial motivation system, non-provision of proper transportation, and a lack of training sessions are grouped in this topic (Decenzo, Holoviak, 1990).

Supervisions: All projects encounter some change during construction. When drawings or specifications are erroneous, ambiguous, unclear, etc., productivity is likely to decline because laborers in the field are uncertain about what needs to be done. As a consequence, they may slow down or pace their work, or have to stop all together while they wait for clear instruction. There is a 30% loss of efficiency when work changes are being performed (Thomas, et al 1999). Work inspection by the supervisor is an essential process to proceed. For example, the contractor cannot cast concrete before an inspection of the formwork and steel work, thus affecting labor productivity (Zakeri, et al 1996). With non-completion of the required work according to the specifications and drawings, supervisors may ask for the rework of a specific task. Supervisors' absenteeism stops the work totally for activities that require their attendance, such as casting concrete and backfilling, further delaying inspection of the ready work which, in turn, leads to delays in starting new work.

Material/Tools: Material management is a key element in project planning and control. If materials, tools, or construction equipment are not available to a crew at the correct location and time, then the crew's productivity will probably suffer because workers may be unable to proceed in an orderly, consistent manner. Selection of the appropriate type and size of construction equipment often affects the required amount of time and effort and, thus, the job-site productivity for a project. It is, therefore, essential for site managers and construction planners to be familiar with the characteristics of the major types of equipment most commonly used in construction. In order to increase job-site productivity, it is beneficial to select equipment with the proper characteristics and a size most suitable for the work conditions at a construction site. Laborers require a minimum number of tools and equipment to work effectively. If the wrong tools or improperly sized equipment is provided, productivity may also suffer (Alum and Lim, 1995; Guhathakurta and Yates, 1993). The size of the construction site and the material storage location have a significant impact on productivity because laborers require extra time to move required materials from inappropriate storage locations, thus resulting in productivity loss (Thomas and Sanders, 1991).

Project management factors: Work that is not properly scheduled, shortage of critical construction equipment or labor, and the incorrect mix of labor crews may result in decreased productivity because crews may not be able to work as efficiently as they would otherwise do. Improperly planned and implemented project initiation procedures may also lead to lost labor productivity. Labor productivity can be impacted by mobilizing labor prior to having access to site electrical power or prior to having adequate site parking. Additionally, poor site layout can contribute to loss of productivity. Labors have to walk a long way to lunch rooms, tool cribs, lay down areas, washrooms, entrances and exits affecting overall productivity.(Cited in AACE IRP 2004 International Recommended Practice No. 25R-03 Estimating Lost Labor Productivity in Construction Claims)

Natural Factors: Natural factors, such as physical, geographical, and climate conditions, exert considerable influence on productivity, particularly in extreme climates (too cold or too hot). Natural resources, such as water, fuel, and minerals, influence productivity.

External Factor: Some severe weather is to be expected on almost every project. Pushing weather-sensitive work from good weather periods to periods of extreme weather, or encountering unusually extreme weather, may impact productivity (e.g., earth backfill and compaction operations pushed into wet-weather periods). Adverse winter weather, such as winds and rains, reduces productivity, particularly for external work such as formwork, tee work, concrete casting, external plastering, external painting, and external tiling. Adverse weather sometimes stops the work totally (Thomas and Sanders, 1991).

Sociological Factors: Social customs, traditions, and institutions influence attitudes towards work and job. For instance, bias on the basis of caste, religion, etc. inhibited the growth of modern industry in some countries. The joint family system affected the incentive to work hard in India. Close ties with the land and native places hampered stability and discipline among industrial laborers (A. Kumar Cited in Desai 2004)

Political Factor: Law and order, stability of government, harmony between states, etc. are essential for high productivity in industries. The government's taxation policies influence willingness to work, capital formation, modernization and expansion of plants, etc. Industrial policy affects the size and capacity of plants. Tariff policies influence competition. Elimination of inefficient units helps to improve productivity (Kumar Cited in Desai 2004)

Economic Factors: The size of the market, banking and credit facilities, transport and communication systems, and other are important factors influencing productivity.

2.3. Identification of Possible Factors Affecting Productivity in Building Construction

Based upon the Lliterature Rreview, this study extracts various factors affecting labor productivity in construction from all previous research studies. Some similar factors were merged together, and some new factors were added. Table 2.1 below shows various factors affecting labor productivity in construction extracted from previous study.

Table 2.1. Factors Affecting Labor Productivity in Construction (from Previous Study).

Factors Affecting Labor Productivity in Construction

A

B

C

D

E

F

G

H

I

J

A

Management Characteristic

the level of management control

√

√

Professionalism of design team

√

√

√

√

Difficulties in employing site supervisor

√

√

√

Work planning and scheduling

√

√

√

√

√

√

Incompetence of site supervisor

√

√

√

√

√

√

√

√

Late inspection of completed work

√

B

SITE AND RESOURCE-MANAGEMENT CHARACTERISTICS

Coordination of subcontractor

√

√

√

Quality control

√

Unsecured construction site

√

√

√

√

Communication breakdown

√

√

√

√

Information

√

√

Rework (wrong information given by supervisor)

√

√

√

√

√

√

Congestion

√

√

√

√

√

√

√

√

Sequence of work

√

√

√

√

√

√

√

Difficulty in recruitment or availability of workforce

√

√

√

√

√

Financial problems (late payment by client)

√

Financial problems (payment to suppliers)

√

√

Availability of materials

√

√

√

√

√

√

√

√

√

Availability of tools and machinery

√

√

√

√

√

√

√

Method and machinery (including impairment)

√

√

√

√

√

√

C

PROJECT CHARACTERISTICS

Location

Inclement weather (temperature and humidity)

√

√

√

√

√

√

√

Project characteristics

√

√

√

Specification

√

Structure size

√

Design requirement

Project size

√

Site access

√

Site characteristics (including health)

√

√

Table 2.1 (continued)……

Factors Affecting Labor Productivity in Construction

A

B

C

D

E

F

G

H

I

J

D

WORKFORCE CHARACTERISTICS

Quality: Experience, training, and education level

√

√

Disturbance

√

√

√

√

√

Morality (e.g., alcohol influence or social problems)

√

Frequent changes in labors

√

Communication problems between laborers

√

√

Turnover

√

√

√

√

Absenteeism

√

√

E

EXTERNAL CHARACTERISTIC

Acceleration: Overtime schedule

√

√

√

√

Variation order

√

√

√

√

Current economic condition

√

√

Research and development

√

References: A. Abdul Kadir et al. (2005) B. Rojas and Aramvareekul (2003)

C. Park (2002) D. Ovararin and Popescu, C. M. (2001)

E. Kaming et al. (1998) F. Kaming et al. (1997)

G. Zakeri et al. (1996) H. Lim and Alum (1995)

I. Thomas and Sakarcan (1994) J. Halligan et al. (1994).

Table 2.2. Possible Factors Affecting Labor Productivity (in Alphabetical Order)

Sr. No.

Factors affecting labor productivity in building construction

1

Accidents

2

Bad ventilation

3

Construction method

4

Drawings and specifications alternated during execution

5

Government regulation

6

High quality of required work

7

Increasing number of labors

8

Inefficiency of equipment

9

Inspection delay

10

Insufficient transportation mean

11

Insufficient lighting

12

Interference

13

Labor absenteeism

14

Labor disloyalty

15

Labor dissatisfaction

16

Lack of competition

17

Lack of financial motivation system

18

Lack of labor experience

19

Lack of labor recognition programs

20

Lack of labor surveillance

21

Lack of periodic meeting with labor

22

Labor personal problems

23

Lack of place for eating and relaxation

24

Lack of the training session

25

Low quality of raw materials

26

Material shortage

27

Misunderstanding among laborers

28

Misunderstanding between laborers and superintendents

29

Misuse of time schedule

30

Noise

31

Payment delays

32

Rework

33

Supervisors' absenteeism

34

Tool and equipment shortages

35

Type of activities in the project

36

Unsuitability of materials storage location

37

Violation of safety precautions

38

Weather change

39

Working at high places

40

Working overtime

41

Working within a confined space

CHAPTER 3. RESEARCH METHODOLOGY

Survey research is defined as a method of observation that involves the collection of data through asking people questions (Fowler, 1993). For this research study, the data collection had the option from two basic methods: the questionnaires and personal interviews. A questionnaire was chosen as the most efficient and appropriate data-collection technique for the study. The questionnaire was described as a self-administered instrument with web-design questions, an appropriate respondent. It was seen that a questionnaire in a web-survey format is cost and time efficient for the researcher while permitting the respondent to answer the questionnaire at personal convenience. However, the method is inflexible, and the response rate is generally lower than for other methods such as interviews. Data's were collected from literature reviews on books, journals, articles, seminar conferences, and websites which emphasize the building construction's labor productivity. A survey was given to the employees from different trades involved with the construction project.

3.1. Survey Planning

For this study, the questionnaire was distributed by e-mail. The purpose of the survey was to gather information about the factors affecting labor productivity in the building construction industry. The purpose and approach used in the survey was fully explained to the respondents. Guidelines were provided to the respondents to ensure that the procedure was followed properly to reduce errors. During the survey period, some periodical oversights were provided to help ensure the process was going smoothly and consistently. The data were stored in order to maintain confidentiality, and the output was received from the Group Discussion Center GDC in the form of electronic mail, which included raw data sheets, summary sheets, and computer databases. Results included the overall statistics as well as individual statistics

3.2. Considerations for the Survey

The main consideration for a survey was that it should be easy for respondents. If questions are too complicated, it would lead to a high "drop-out" rate. Care was taken so that the questions did not negatively influence the results of subsequent questions. Sometimes, by providing too much information or by disclosing the purpose of the study, results may become biased. Preliminary text was introduced for explaining the survey project to the respondents. Page breaks on the webpages were introduced to improve the readability of the text. Logic-based questions were avoided because they could cause respondent frustration and increase the drop-out rate. Study was done to find any serious loopholes and if questions were truly answerable.

3.3. Organization of the Questionnaire

The completeness of the questionnaire and the number of responses were of greatest concern. Equally important, the recognition of respondents regarding the benefits and uses of this research study was also of interest. In response to these concerns, the questionnaire design process began with identification of the following criteria:

Questionnaire Response Rate

Accuracy Time

Relevant Ease of Completion

Completeness

Understanding

Thoroughness and efficiency were achieved with an examination for accuracy and completeness of the relevant questions, taking into consideration previous studies and Table 2.1. The efficiency of the questionnaire, however, did not guarantee a high response rate. It was of equal importance, then, to ensure that the questionnaire allowed the appropriate time frame for respondents to answer and return it to the researcher. Based on the researcher's experience and the pilot survey, the response time was set at 15 minutes, and the respondents had 6 weeks to complete the questionnaire. Simple but effective questions were asked, and different sections of the web-survey questionnaire were created with distinct colors to assist the respondents in correctly answering and efficiently attempting the questionnaire.

3.4. Questionnaire

The questionnaire design process proceeded on an interactive basis with questions being classified into two main sections: respondent profile and estimated loss of productivity due to various field disruptions. Questions in the respondent profile were created to collect information such as job position, work and supervisory experience, typical work locations, and contact information. While not directly addressing productivity loss issues, these questions were of value to the research by permitting an analysis of productivity loss issues across a variety of different profiles in different regions. It was reasonable to expect that a locality can have an impact on the loss of productivity due to various field disruptions, especially weather or environment.

The final set of questions (Appendix B), concerning a loss of productivity, directly targeted the factors affecting labor productivity in the five different groups. The questionnaire included the list of productivity factors. Respondents simply furnished factors affecting productivity for each given standard condition. Therefore, each respondent was expected to select only one option for each factor. The responses were based on the general knowledge and experience of the respondents and were not related to any specific project. This simple and direct approach was chosen to establish a means of developing a list of factors affecting labor productivity in building construction.

3.5. Pilot Survey and Questionnaire Revision

To improve the questionnaire development process, a pilot survey was conducted. This stage consisted of several steps, including identification of sources for data, collection of data, and conclusions. The implementation of lessons learned from this section significantly benefited the questionnaire development.

The 155 questionnaires shown in Table 2.2 were sent by e-mail to laborers, contractors, architectures, owners, project managers, and project engineers from various building construction organizations. Respondents were expected to complete the questionnaire within 2 weeks. A total of 25 questionnaires were finally gathered from pilot survey, 5 of which were incomplete or outliers. The incomplete responses and outliers were removed from the data set, leaving a total of 20 respondents in the database. Lessons learned from conducting this pilot survey are stated below, and they improved the final questionnaire.

The first part of the questionnaire should be general information about the organization.

There are some questions which are not practical or realistic with respect to construction-project situations. Such questions should be removed or modified to represent realistic and practical situations.

Some factors should be rearranged in order to give more suitable and consistent meaning.

Some factors and sentences should be modified or represented with more details.

Some factors are repeated with same meaning. The redundant factors should be eliminated.

Some factors and sentences should be modified in order to give clearer meaning and understanding.

Findings from the pilot study strengthened the questionnaire package. The improvements related to the, organization of the questionnaire and the response time. In terms of organization, the web survey was created using a light appearance and pleasant-looking font colors. It also included a percentage bar for the completed survey and had an option to navigate to any question at any given time. All the information entered via the web had an auto-save option and the respondents had the luxury to return to the survey within the allotted time period. Respondents were informed about the confidentiality of the responses. The list of questions used for the web survey can be found in Appendix B.

3.6. Questionnaire Distributions

n= n'/ [1+ (n'/N)]

= n' / [1+ (n'/N)]The target groups in this study were professionals from the construction industry. According to Kish (1965), the sample size can be calculated with the following equation for a 94% confidence level (Assaf et al., 2001; Israel, 2003; Moore et al., 2003):

Equation 3.1

Where, N = Total number of population

N = Sample size from a finite population

n' = Sample size from an infinite population = S²/V²;

S2 is the variance of the population elements and

V is a standard error of the sampling population. (Usually, S= 0.5, and V = 0.06.)

A list of 255 building cconstruction organizations was obtained from the Engineering News-Record:

n= n'/ [1+ (n'/N)],

n'=S2/V2= (0.5)2+(0.06)2= 69.44 For N=255

n= 69.44/ [1+ (69.44/255)] = 55

It was calculated, the questionnaire should be distributed to 55 organizations in order to achieve a 94% confidence level.

CHAPTER 4. ANALYSIS AND DISCUSSION OF RESULTS

4.1. Data Collected from the Web Survey

Data collection is considered the important stage in gathering all required information from the fundamental in achieving the main objectives of the study. Data collection can be defined as a process of assembling primary data records for a certain sample or population of observations (Bohrnstedt and Knoke, 1994). A total of 255 questionnaires were sent to construction professional through e-mail in early October 2009. By the return deadline, a total of 54 questionnaires were received, resulting in an approximately 21.11% response rate (Table 3.1). Missing data commonly occur when a respondent decides not to answer a question or when the answer given by the respondent has been discarded (Kim, 1993). The most serious concern presented in the responses was some missing data. Follow-up contact was conducted over the phone to clarify some ambiguous responses. A total of 26 (i.e., 10.19%) invalid data were found and consequently discarded from the analysis. The reason to discard the data was incompleteness and invalid responses.

4.2. Measurement of Data collected from the Web Survey

In the construction industry, it is universally accepted that field disruptions can be present at any time with different degrees of adversity. In an effort to deal with these different degrees, it was decided that four condition levels would be established: not applicable, does not affect it, somewhat affects it, and directly affects it. These qualitative condition levels then necessitated the development of standard conditions. A clear specification of the standard conditions was necessary to enable respondents to clearly distinguish the degree of each adverse condition level. Standard conditions referring to four different degrees of severity for each field disruption were initially established by Dr. Eric Asa, Dr. Y. K. Yates, and the researcher. The concept of different degrees of severity for productivity factors was previously used in other studies, including Mechanical Contractor of America (1976) and Neil and Knack (1984). Minor changes were made to the standard conditions after they were reviewed by the group of construction participants. Straightforward and simple guidelines for each group were then identified. A questionnaire to assess the loss of productivity was developed next.

In order to be able to select the appropriate method of analysis, the level of measurement must be understood. For each type of measurement, there is (are) (an) appropriate method(s) that can be applied. In this research, ordinal scales were used. An ordinal scale, as shown in Table 3.2, is a ranking or a rating of data that normally uses integers in ascending or descending order. The numbers assigned (1, 2, 3, 4) neither indicate that the intervals between scales are equal nor do they indicate absolute quantities. They are merely numerical labels. Based on a Likert scale, we have Table 3.2 (Cheung et al., 2004; Iyer and Jha, 2005; Ugwu and Haupt, 2007).

Table 3.2. Ordinal Scale Used for Data Measurement

Item

Not applicable

Does not affect it

Somewhat affects it

Directly affects it

Scale

1

2

3

4

4.3. Analysis Method Used

In order to facilitate the study, after the literature review and the focus interviews, a plan was formulated for collecting field information and creating an evaluation process and numerical values. It was necessary to provide straightforward communication to respondents to ensure a clear understanding of all the applicable definitions, procedures, and guidelines that were used in collecting data. Because the data collection process included individuals, the study was conducted in accordance with the regulations of the Department of Health and Human Services, the Food and Drug Administration, and North Dakota State University (NDSU) Policy #345 under the supervision of the NDSU Institutional Review Board (IRB).

A structured survey approach was considered to study the impact of various tributes and factors affecting performance. In addition, the questionnaire can assist with studying the attitude of owners, consultants, and contractors about the factors that affect performance in the construction industry. The RII index method (RII) was used to determine various professionals' perceptions of the RII in construction projects. The RII index is computed as follows (Cheung et al., 2004); (Iyer and Jha, 2005); (Ugwu and Haupt, 2007):

, Equation 4.1

W is the weight given to each factor by the respondents and ranges from 1 to 4

W ranges 1 Not applicable. 3 Some what affect it

2 Does not affect it. 4 Directly affect it. Ã- Number of respondents for each degree

A Highest weight = 4

N is the total number of responses collected for the ordinal scale

It indicates that a lack of labor experience has an extremely high effect on productivity. This result is supported by (Paulson 1975), who found that the craftsmen's experience affects labor productivity. This result is also supported by (Heizer and Render 1990), who confirmed that the experience of the workforce affects job-site productivity. This result is justified because experience improves both the intellectual and physical abilities of laborers which, consequently, increase labor productivity. Labor disloyalty had a high effect on labor productivity and ranked in the 7th position for the manpower group, with an importance index of 373.75, and 39th among all 40 factors in terms of negatively affecting labor productivity (Table 4.9).

Misunderstanding among laborers was ranked fourth in Manpower group, with an RII of 419.75 and 32nd among all 40 factors that affected labor productivity (Table 4.9). This result is justified because misunderstanding among laborers creates disagreement among them about the responsibilities and work bounds for each laborer, which leads to a lot of mistakes in work and, consequently, decreases labor productivity. A lack of competition among laborers ranked 6th with an RII of 379.50 and ranked 38th among all 40 factors for negatively affecting labor productivity (Table 4.9.).

Laborers age was ranked fifth in Manpower group, with an RII of 408.25, and 34th among all 40 factors for negatively affecting labor productivity (Table 4.9). (Heizer and Render 1990) supported this result, citing that the age of the workforce affects job-site productivity. This result is justified because labor speed, agility, and strength decline over time and contribute to reduced productivity Labor absenteeism was ranked second in Manpower group, with RII of 477.25, and in 18th position among all 40 factors that affect labor productivity (Table 4.9). This result is justified given the transient nature of the local workforce and the ease with which construction contractors could hire additional laborers to cover absenteeism.

Personal problems were ranked eighth in Manpower group, with an RII of 368.00, and 40th among all 40 factors that affect labor productivity (Table 4.9). This result might be justified because personal problems cause mental distraction for laborers, and mental distraction affects labor safety more than labor productivity.

Alcoholism ranked third in Manpower group, with an RII of 425.50, and 30th among all 40 factors that affect labor productivity (Table 4.9). It can be justified because consuming alcohol at the construction site may lead to various negative effects on other laborers who are working. Alcohol consumption may lead to rework, misplacing the job work, and accidents, thus completely or partially stopping the construction work and affecting the labor productivity.

4.10. External Factors Affecting Labor Productivity

Table 4.5. and Figure 4.2. Illustrates the ranking of the factors for the External group. Supervision delays were ranked first in External group, with an RII of 488, and 13th among all 40 factors that negatively affect labor productivity (Table 4.9). Inspection delays from the authorities were ranked sixth in External group, with an RII of 448.50, and 22nd among all 40 factors that affect labor productivity (Table 4.9).

Past study (Guhathakurta and Yates., 1993; Olomolaiye et al., 1996) proves that inspection delays are an essential process in work; for example, because contractors cannot cast concrete before inspection of formwork and steel work, the inspection delay contributes to delays in work activities. It stops work totally for activities that require the attendance of supervisors, such as casting concrete and backfilling. Additionally, it delays the inspection of ready work which, in turn, leads to a delay in the commencement of new work.

Variations in the drawings were ranked second in External group, with an RII of 488.75, and 14th among all 40 factors that affect labor productivity (Table 4.9). Incomplete drawings were ranked third in External group, with an RII of 483.00, and 16th among all 40 factors that affect labor productivity (Table 4.9). Design changes were ranked fifth in External group, with an RII of 465, and 21st among all 40 factors that affect labor productivity (Table 4.9). A complex design in drawings ranked eighth in External group, with an RII of 437.00, and twenty seventh among all 40 factors that affect labor productivity (Table 4.9). (Thomas et al 1999) stated that there is a 30% loss of efficiency when work changes are being performed. This result can be interpreted as changes to specifications and drawings that require additional time for adjustments of resources and manpower so that the change can be met. Also known as designer errors and omissions, these changes relate to plans that are incomplete or contain errors that are difficult to find until the construction contractor finds them well after the construction phase of the project has started. With most construction contracts, where the contractor bids on designs that are completed prior to contract award, the owner is liable for the designer's errors and omissions.

Payment delays were ranked seventh in External group, with an RII of 442.75, and 24th among all 40 factors that affect labor productivity (Table 4.9). Payment delays in the construction industry are adversarial and disastrous. Late payment affects a company's cash flow and may eventually lead to a company's insolvency. Timeliness of payment is important to circumvent the risk of the late-payment problem. A study by (Zou et. al.2007) pointed out that project-funding problems have been identified as cost-related risks, time-related risks, and quality-related risks which can significantly influence the delivery of a construction project. The risk of delayed payment from the owner will impact the duration and cost of the project. These risks cause the project's cost to increase abnormally and, subsequently, to delay the progress of the project

Rework ranked fourth in External group, with an RII of 471.50, and 19th among all 40 factors that affect labor productivity (Table 4.9). Past study from (Makulsawatudom, Sinthawanarong, 2004) confirms that rework is one of the major factors in the construction industry to affect labor productivity in building construction. It also lists rework as one of the critical factors effecting productivity; and states that Rework is due to incompetent craftsmen and supervisors.

Implementation of government laws was ranked ninth in External group, with an RII of 419.79, and 31st among all 40 factors that affect labor productivity (Table 4.9). For most projects, government authorities refer to specific versions and construction standards of their design. Sometimes, however, government authorities, who have well-established written standards for design and construction, choose to revise those standards after the construction has been awarded based on a previous version, thus affecting the overall labor productivity of the building construction.

Training sessions were ranked tenth in External group, with an RII of 414.00, and 33th among all 40 factors that affect labor productivity (Table 4.9). A past study from (Samson and Lema 2002), (Cheung et al 2004) and (Iyer and Jha 2005) states that persons entering the construction industry directly from high school usually start as inexperienced or as laborers. They can learn from their job quickly, by closely working with the experienced people. Whereas, skilled laborers, such as carpenters, bricklayers, plumbers, and other construction trade specialists, most often get their formal instruction by attending a local technical or trade school or through an employer-provided training program.

4.11. Communication Factors Affecting Labor Productivity

Table 4.6. and Figure 4.3.Shows the ranking of the factors for the Communication group. Change order from the DE ranked first in Communication group with an RII of 465.75, and 20th among 40 factors affecting labor productivity (Table 4.9). Disputes with the DE were ranked fourth in Communication factors with an RII of 396.75, and 35th among 40 factors affect labor productivity (Table 4.9)

. Misunderstanding among the OW, CO, and DE ranked third in Communication group with an RII of 431.25 and 29th among 40 factors affecting labor productivity (Table 4.9).

This result can be justified because DE deficiencies are changes that result from faulty or confusing aspects of construction designs and specifications which are not discovered until the contractor begins working towards building what is shown on paper. As opposed to other types of change, design deficiencies are often the result of poor quality control in the design process, and they are controllable. The owner is also liable for the contractor's costs due to designer errors, such as unreasonable delays in reviewing shop drawings, failure to provide drawings or design information in a timely fashion, failure to prove timely inspections, and other delays due to the designer's contract-administration problems (Bramble and Callahan, 2000 ). According to studies by the U.S. Army Corps of Engineers and the U.S. Navy, design deficiencies account for nearly 40% of all construction changes on a design-bid-build project, more than any other category of change.

4.12. Resource Factors Affecting Labor Productivity

Table 4.7 and Figure 4.3. Shows the ranking for the factors of the Resource group. Lack of required construction material was ranked first in Resource group, with an RII of 558.00, and 1st among all 40 factors affecting labor productivity (Table 4.9). Inadequate construction material was ranked eleventh in Resource group, with an RII of 437.00, and 28th among all 40 factors affecting (Table 4.9). An increase in the price of material was ranked seventh in Resource group, with an RII of 396.00, and 36th among all 40 factors affecting labor productivity (Table 4.9).

The material resource constitutes 40-60% of the project's total cost (Damodara K. P. E, 1999), which makes materials an important and attractive subject to control. In spite of their weight in const

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