sample study - methodology, analysis, and conclusion chapters

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CHAPTER THREE: METHODOLOGY 3.1 Introduction 3.2 Research Design 3.2.1 Research Purpose 3.2.2 Research Approach 3.2.3 Research Strategy 3.3 Population and Sampling Design 3.3.1 Population The population of a study basically refers to the total number of people in the form of a thorough headcount of all elements the findings of the study seeks to represent (Sekaran, 2003). A clearly defined population ensures that the results and findings apply to the correct category of elements in the society. Considering that the study basically assesses the factors that affect the motivation of workers in the UAE construction industry and other ways of enhancing productivity through employee motivation, the population of the study is all construction workers of UAE. In order to be able to pay closer attention to construction companies in a thorough assessment of motivation factors, the multiple case study strategy presents the construction workers of the two selected companies are main population under study. As mentioned, whereas one construction company is large and widely networked in the UAE construction industry, the other is comparably small in terms of workforce and assets. 3.3.2 Sampling method Due to limited resources, there is almost always the need to sample respondents for any investigation (Saunders et al. 2007). It may be added that it is not practical to use the whole population to conduct the survey since that process takes a lot of effort and consumes a lot of time. The term “Sample” is part picked from the whole set of data, which is called “population” to reflect the responses of the whole population (Denscomble, 2010). “Once you have decided the technique for collecting your fieldwork data and you have thought about what to ask, you should be ready to decide on the characteristics of the respondents” (Naoum, 2007) .Saunders at al. (2007) add that the size of the sample may impact on the extent of significance of relationship between variables of the study. Whereas a small sample size may not be

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Page 1: Sample study - Methodology, Analysis, and Conclusion Chapters

CHAPTER THREE: METHODOLOGY

3.1 Introduction

3.2 Research Design

3.2.1 Research Purpose

3.2.2 Research Approach

3.2.3 Research Strategy

3.3 Population and Sampling Design

3.3.1 Population

The population of a study basically refers to the total number of people in the form of a

thorough headcount of all elements the findings of the study seeks to represent (Sekaran, 2003).

A clearly defined population ensures that the results and findings apply to the correct category

of elements in the society. Considering that the study basically assesses the factors that affect

the motivation of workers in the UAE construction industry and other ways of enhancing

productivity through employee motivation, the population of the study is all construction

workers of UAE. In order to be able to pay closer attention to construction companies in a

thorough assessment of motivation factors, the multiple case study strategy presents the

construction workers of the two selected companies are main population under study. As

mentioned, whereas one construction company is large and widely networked in the UAE

construction industry, the other is comparably small in terms of workforce and assets.

3.3.2 Sampling method

Due to limited resources, there is almost always the need to sample respondents for any

investigation (Saunders et al. 2007). It may be added that it is not practical to use the whole

population to conduct the survey since that process takes a lot of effort and consumes a lot of

time. The term “Sample” is part picked from the whole set of data, which is called “population”

to reflect the responses of the whole population (Denscomble, 2010). “Once you have decided

the technique for collecting your fieldwork data and you have thought about what to ask, you

should be ready to decide on the characteristics of the respondents” (Naoum, 2007).Saunders

at al. (2007) add that the size of the sample may impact on the extent of significance of

relationship between variables of the study. Whereas a small sample size may not be

Page 2: Sample study - Methodology, Analysis, and Conclusion Chapters

representative, a sample size too large can create the perception of significance of a non-

existing relationship. Irrespective of these, it is representative to select a sample size

appropriate for the study with the use of a method that offered each other equal chance of

selection. It must be noted that the two companies were conveniently selected due to the easy

access to data by the researcher.

Company A has a total of 30000 workers, of which 3000 are professionals. Company A was

established in 1967 and it operates in 11 countries and has 14 offices throughout the Middle

East. The annual turnover of company A is worth 1.4$ billion. The study took one of the

projects of company A during working hours and a sample of 35 workers, which was picked

randomly from a total of about 200 workers. The reason of not having an exact figure of the

total present workforce is the continuous change of the number of workers present at the site

due to the changes in type of operation. The other company, company B, has a total of 1000

workers, of which 75 are professionals. It was established in 2005 and it operates in one country

(United Arab Emirates); it has two offices throughout the United Arab Emirates in Abu Dhabi

& Dubai. The study visited company B workers accommodation after working hours. A sample

of 85 workers was conveniently selected from a total present figure of 350 workers. The total

of responses that were taken in the study is 97. The other responses were not taken into

consideration because of missing data and uncompleted surveys.

After quantitative data collection, another sample of top management employees were selected

by purposive sampling technique. Purposive sampling of top management was necessary in

order to ensure that respondents had adequate knowledge on the area of employee motivation

and productivity, as mentioned by Creswell (2009). A total of 11 top management employees

were therefore selected for interview discussions. In summary, two samples were selected from

both case study companies. Data from interviews significantly supported and paved way for

understanding of measures that are instituted by both companies to motivate workers.

Questionnaire on the other hand helped identify the real needs of the workers and to find out

whether the current motivational measures are desirable by them.

3.4 Sources of Data Collection

Cooper and Schindler (2006) assert that two main sources of data exist. These sources of data

are primary and secondary data sources. The study implements both primary and secondary

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data in answering research questions (Table 3.2). Both data sources contribute to the objectives

and helped generate conclusions and recommendations.

3.4.1 Primary Sources

The various forms of data collection are explained: hence, the study adopts a questionnaire and

an interview guide as instruments for data collection in a joint qualitative and quantitative

approach. The survey strategy of study administration permits the collection of data from a

wide range of responses. The large mode of data collected helps gather enough evidence that

helped establish conclusions for the study. Yin (2003) argues that the survey strategy permits

the collection of a large amount of data which are later analyzed with the help of the appropriate

statistical modules towards founding of conclusions.

Primary data was gathered from management and operational level workers from 2 different

companies randomly selected through purposive sampling. Primary data basically includes the

data collected by interacting with workers and management of these companies. Zikmund

(2003) describes primary data as data gathered for the central purpose of a study. Collecting

primary data helped to enhance understanding and implementation of direct evaluation of the

subject using a survey questionnaire and an interview guide. For the purpose of this study

information was gathered from 97 construction workers in UAE using the survey questionnaire

(Appendix A-F) whereas 11 managerial workers were interviewed using the interview guide

(Appendix G & H).

The questionnaire was used in order to ensure the regularity of information on all factors that

affect the motivation of workers. The questionnaire collects data in an organized or structured

way whereas the interview collects data in a rather semi structured format. The interview

guide’s semi structured format was to make it easier to collect information on how employee

motivation is regarded and managed which the researcher thinks may not be strictly in

agreement with any of the factors discussed in the literature review of this study.

Survey Questionnaire

The survey questionnaire covered 4 main dimensions of physical, psychological, economic,

and organizational factors (Appendix A-F). All items and individual factors measured were

adequately discussed under the literature review section of the study. The various dimensions

were based on Kazaz et al. (2010) exploratory study to determine factors that influence workers

motivation in the construction sector, done with the help of 82 construction companies. A total

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of 10 items were placed under physical dimension, 12 items under psychological factors, 10

under organizational factors, and finally 6 items under economic dimension.

Interview Guide

Interview guide (Appendix G & H) was divided into two main sections with regards to mode

of answer required. Whereas the first seventeen open ended questions pertained to the

discussion of physical, psychological, economic, and organizational factors. Another 26 closed

ended questions were asked to re-enforce the various dimensions and items presented and

discussed under the questionnaire. The interview guide went a step ahead to investigate

management commitment to motivate construction workers towards enhanced performance.

3.4.2 Secondary sources of data

Secondary Data Sources may be referred to as data that is not originally gathered by the study,

and help in some way to arrive at a conclusion for the study. Secondary data sources according

to Sekaran (2003) are derived from data that is already in existence. Secondary data for this

study was acquired from a variety of online databases of journals, books, year projects by past

students of the institution, and other such sources. Secondary data was very instrumental in

gathering primary data to in the bid to find solutions to the study’sresearch questions.

Documentations on management attempts to install policies that significantly motivate

employees were requested. Other secondary data on employee satisfaction survey conducted

internally were requested.

3.5 Data Collection Administration

Pilot Study

It may be mentioned that a pilot study was conducted to find out the appropriateness and

applicability of the scales to the study. Pilot studies assist in instituting measures and

constraints, clarity of directives, and help to determine the right level of the independent

variable (Teijlingen van et al., 2001). In all, 20 employees conveniently selected from UAE

construction companies were selected. Pilot study was also conducted to investigate the

understanding of the questions by the construction workers. On the whole, participants did not

show much signs of difficulty in answering questions on the survey questionnaire. The pilot

study also helped identify which languages that must be used for main data collection. After

the pilot study, a number of questions were adjusted to make them more understandable to

respondents. Main questionnaire administration was also offered in five different languages

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including, English, Malayam, Hindi, Tamil and Urdu. Fundamentally, this preliminary

investigation was helpful in the understanding of the possible challenges to be expected during

the main data collection stage of the study

Fieldwork and data collection

In order to gain permission for data collection, a Student Identity (ID) card of Girne American

University used. To request a permission to collect data from respondents. The Student ID card

helped also to gain consent of individual workers towards contributing to data required for

answering research questions. Consent was also sought from each individual respondent

particularly before they were allowed to complete any instrument. Questionnaires were

personally administered by the researcher to selected respondents. Where needed, explanations

had to be offered to a few number of respondents who experience difficulties in completing the

questionnaire.

3.6 Data Analysis Techniques

Quantitative data analysis was done with the help of IBM SPSS Statistics (SPSS) software

version 20 and Microsoft Office Excel 2013. Quantitative data collected was first coded and

entered into IBM SPSS to pave way for easy analysis. Descriptive aspects of the findings were

presented with the help of tables and graphs alongside other descriptive statistical indicators.

Qualitative data was manually coded by the researcher (Appendix J). This significantly

reduced the amount of data available for analysis. Qualitative data was analyzed alongside

quantitative data in a concurrent triangulation approach to mixed methodologies.

Whereas coded data permitted the reduction of errors in analysis, the use of a likert scale

permitted easiness of quantitative data analysis. Likert scales present a quantitative approach

to the assessment of significance between any two or more variables of the study (Creswell,

2009). Saunders et al (2007) add that the use of likert scales for quantitative data collection

permit the expression of responses over a degree of opinion or no opinion at all.

3.7 Limitations of methodology and ethical considerations

Limitations

It may be observed first and foremost that the present study is geographically limited and

confined to the United Arab Emirates, Abu Dhabi city. An important limitation however is the

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limited amount of time offered to complete the present study by the researcher’s institution. A

time table was maintained in order to overcome such limitations pertaining to interim

submissions and maintenance of other milestones necessary to complete the study in time. It

was critical to establish a timetable with pre-determined achievable milestones in an attempt to

keep track of vial activities that are fundamental in meeting necessary deadlines of project. The

researcher’s busy work schedule also served as a major obstacle in this area. Other important

challenges such as the time allocation to each questionnaire and interview administration was

altered due to experience gained from the pilot study. Other implications of the methodology

to findings are discussed in the next chapter.

Ethical Considerations

Strict code of ethics as outlines by Girne American University was observed. Creswell (2009)

argue that ethical considerations must be an integral aspect of any particular study. Dependable

ethical principles were observed in the course of conducting the research. Saunders et al. (2009)

add that gaining permission and consent to collect data is a very important aspect of any study.

All data collection instruments were therefore made to contain an informed consent form. Prior

to data collection however, a student ID card with request latter was submitted to the two

companies for their approval as previously mentioned. In addition to this, personal data

pertaining to any of the respondents were not collected. Interview questions were as well

submitted to respondents ahead of time before face-to-face discussion.

Page 7: Sample study - Methodology, Analysis, and Conclusion Chapters

CHAPTER FOUR: RESULTS & DISCUSSIONS

4.1 Introduction

In this chapter, primary data collected is summarized. Whereas quantitative data collected with

the help of the survey questionnaire is presented with the help of tables, graphs and brief

explanations, qualitative data narrated concurrently the data and will answers the research, as

discussed in the previous chapter. Where relevant, relationships are tested for significance

between variables, with the help of statistical software and techniques, towards providing

answers to the research questions. The chapter begins with a discussion of the demographics

of primary data collection; it then proceeds to discuss findings in context of the research

questions. After the presentation of data findings, discussions and implications of findings to

theory and practice are also discussed. Other implications of the methodology and limitations

are as well discussed. Presentation and discussion of findings is critical to the achievement of

set objectives.

4.2 Demographics

Out of data collected with the help of the questionnaire, 14 were in Urdu Language, 55 in

Malayalam, and the rest in Hindi language. Most of the workers were from India (83%), a few

others were from Pakistan (8%) and Bangladesh (6%). Most workers were between the ages of

18 to 30 years (54%). This was closely followed by the age group of 30 to 40 years (29%).

Responsive rate of the study was 80.83%.

Table 4.1 Worker Centred Demographics

Frequency Percent Valid

Percent Cumulative

Percent

Country of Origin

Pakistan 8 8.2 8.2 8.2

Bangladesh 6 6.2 6.2 14.4

India 83 85.6 85.6 100

Age Range

18-30 54 55.7 55.7 55.7

31-40 29 29.9 29.9 85.6

41-50 14 14.4 14.4 100

Total 97 100 100

Other demographics collected and pertaining to occupational related demographics are

presented in Table 4.2 below. Considering the fact that ETA is comparably larger than ACC,

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73% of the respondents came from ETA. This is in light of representativeness of data to the 2

corporations selected for the study and the fact that limited respondents were available in ACC

whereas more were available and accessible in ETA.

Table 4.2 Company Related demographic

Frequency Percent Valid

Percent Cumulative

Percent

Company ACC 26 26.8 26.8 26.8

ETA 71 73.2 73.2 100

Type of Work

Steel fixer 4 4.1 4.1 4.1

Mason 37 38.1 38.1 42.3

Foreman 12 12.4 12.4 54.6

Safety Assistant

1 1 1 55.7

Office Worker

9 9.3 9.3 64.9

Electrician 27 27.8 27.8 92.8

Driver 4 4.1 4.1 96.9

Carpenter 3 3.1 3.1 100

0-3 years 26 26.8 26.8 26.8

3-5 years 17 17.5 17.5 44.3

Years working in this field 5-8 years 19 19.6 19.6 63.9

8-12 years 13 13.4 13.4 77.3

over 12 years

22 22.7 22.7 100

Years working with this company

0-3 years 34 35.1 35.1 35.1

3-5 years 23 23.7 23.7 58.8

5-8 years 19 19.6 19.6 78.4

8-12 years 12 12.4 12.4 90.7

over 12 years

9 9.3 9.3 100

Total 97 100 100

Many of the respondents interviewed were of the mason profession, other professions such as

labor, filler, and helper were categorized under the broader mason category of work which

made up to 37 respondents (38.1%). The next dominated profession was electrician, this

accounted for close to 28% of total respondents. To add to that, a high number of respondents

had worked in the same field for the past three years (26.8%), others had worked more than 12

years in the same field (22.7%). Analyzing the years spent in the same category of work and

the years spent working with the company reveals that even though many had worked in the

same work category for a long time, these people had more likely not worked for the company

in question (22 workers in the same kind of work for more than 12 years but only 9 workers

had been with that particular company for the same period).

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4.3 Descriptive data: Main factors influencing construction workers’ motivation

Key areas of investigation in the quest for factors that affect workers motivation include

psychological, physical, organizational, and economic factors. Data presented is therefore

presented under these sub headings. There was the need to investigate the level of internal

consistency between items under the same dimensions.

Table 4.3 Reliability tests for dimensions

Dimension Cronbach's Alpha N of Items

Physical .288 12

Psychological .622 14

Organizational .538 13

Economic .075 10

It may therefore be noted that responses pertaining to psychological items followed by the

organizational dimension. Economic items/dimension were least reliable.

Physical Factors

As elaborated in the methodology, 9 items were investigated under physical dimension. It may

be noted at this point that more than one question may pertain to any single item as a factor

under any of the dimensions discussed. Many workers agreed that keeping them in their

designated position important to their motivation; a total of 79.4% rates this statement as

important. The second dimension tested project design; a total of 85 respondents against 12

respondent who thought project design is not important.

Figure 4.1 Keep working in similar activity Figure 4.2 Project design is important

Majority of them also agreed that project complexity is very important (Figure 4.3); a total of

71% rated it as important – the third item under physical factors. Pertaining to the fourth item

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on the questionnaire, respondents believed that minor mistakes should be pardoned (65%),

others believed that minor mistakes must be pardoned depending on the type of mistake (34%).

The fifth physical dimension pertained to the availability of rules about weather work

conditions; 98% were positive of the existence of weather work conditions. Out of the total,

76% further agreed that rules on weather conditions did contribute to motivation. Productivity

disruptions and pressures are other issues that affect worker motivation.

Figure 4.3 Project Design Complexity Figure 4.4 Minor mistakes be forgiven

Figure 4.5 Weather work conditions (WWC) exist Figure 4.6 WWC add to productivity

Figure 4.7 Productivity disruptions Figure 4.8 Productivity Pressures

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Dimension six (disruptions) and seven (pressure) presented in Figure 4.7 and 4.8. The last

three items under the physical dimension is overtime, shift, and crowded site and its impact on

worker motivation.

Figure 4.9 Availability of overtime Figure 4.10 Importance of overtime

Figure 4.11 Shift Affect productivity Figure 4.12 Crowdedness affect productivity

It may be noted that aside the impact of crowdedness on productivity, respondents generally

agreed that the other factors such as overtime and shift does affect motivation and productivity

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of construction workers. Respondents were basically neutral whether crowdedness affect

productivity.

Psychological Factors

A total of 11 items were investigated under the psychological dimension. The first item had to

do with discipline whereas the second item had to do with safety guidelines. About 80% had

safety guidelines installed, out of this 75% claimed that such guidelines are very important.

Another 56.7% mentioned that discipline is important to productivity.

Figure 4.13 Discipline & productivity Figure 4.14 Safety guidelines & productivity

Figure 4.15 Satisfaction & productivity Figure 4.16 Relationship with other workers

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Figure 4.17 Competition & productivity Figure 4.18 Increased responsibility

Figure 4.19 Company share problems Figure 4.20 Social activities & Motivation

Figure 4.21 Culture Differences & motivation Figure 4.22 Participation & motivation

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Figure 4.23 Living close to work place Figure 4.24 Living close & motivation

A total of 71% of respondents lived near to the work place, close to 80% as well agreed that

living close to the work place affect productivity (Figure 4.23 and 4.24). Culture differences

(Figure 4.19) and work participation (Figure 4.20) as well had positive responses but were not

as having much impact on motivation as the previous dimensions presented in Figures 4.15 to

4.20.

Organizational factors

A total of 10 items were measured under organizational dimensions. Quality of site

management, materials management, organized work and good supervision are important items

that impact on productivity; these are presented in Figure 4.25 to 4.28. Layout was seen as

very important to productivity (Figure 4.29). To add to this 97% had attended training

programs and close to 71% agreed training programs is good for productivity (Figure 4.30).

Even though 86% agreed that off days are available in their organizations, only 44.3% agreed

that off-days increases motivation (Figure 4.34). Crew size, company name and camping

conditions are some other factors which have significant impact on motivation according to

workers (Figure4.31 – 4.33).

Figure 4.25 Quality of site management Figure 4.26 Materials management

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Figure 4.27 Organized work Figure 4.28 Supervision and Productivity

Figure 4.29 Layout Figure 4.30 Training program and

productivity

Figure 4.31 Crew size & motivation Figure 4.32 Company name & motivation

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Figure 4.33 Camping conditions & motivation Figure 4.34 Off days & motivation

Economic Factors

Under this dimension, six main items were investigated. Workers believed that on time

payment does enhance their productivity levels (Figure 4.35). Whereas 76.3% agreed that

salary is not enough for them, 68% further agreed that salary is important for motivation

(Figure 4.36). A total of 68% of respondents had social insurance and close to 90% rated social

security as important (Figure 4.37). Out of 61% who agreed there are rewards in their

companies, around 73% rated rewards as being very important to productivity (Figure 4.38).

The last two items under this dimension was work stoppages (Figure 4.39) and union

membership (Figure 4.40).

Figure 4.35 On-time payment and productivity Figure 4.36 Salary & motivation

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Figure 4.37 Social Security Figure 4.38 Rewards and Productivity

Qualitative Data Analysis

A total of 9 respondents were interviewed. Basically, demographics of interview respondents

are presented in Table 4.4.

Table 4.4 Interview demographics

Interview Experience in years Company

1- Safety officer 5 to 10 years ACC

2- Project engineer more than 10 years ACC

3- Forman more than 10 years ACC

4- Site engineer Less than 5 years ETA

5- Project manager more than 10 years ACC

6- Forman Less than 5 years ETA

7- Forman 5 to 10 years ETA

8- Mechanic engineer Less than 5 years ETA

9- Site engineer Less than 5 years ETA

Generally, all interview respondents acknowledged workers motivation are very important,

they all agreed that workers motivation is important and gave reasons including the need to

ensure a systematic flow of work and also ensure that workers are satisfied. Others stated that

there is the need to motivate workers in order to ensure health and safety of workers and

alleviate interruptions in the production processed. Key factors of workers’ motivation

therefore fall into the categories of organizational and psychological factors.

Respondents went further to explain how workers are motivated citing that they are educated

through training and development programs to other strategies that include incentives and

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financial rewards. In motivating employees, quality of site, materials flow, and systematic flow

is fundamental. It is important to ensure satisfaction at all times through others strategies that

include sharing of both organizational problems and workers’ problems. In light of these, the

companies had installed human resource policies which primarily covered areas of training and

development programs, as well as incentives payments and financial rewards.

As part of the responsibilities of interviewed managers and pertaining to workers’ motivation

and their productivity, responses include responsibilities to keep workers safe whereas others

ensured that all workers’ physical needs required to correctly execute their work activities are

provided. All other responses fell into these major categories include the need to ensure their

ultimate satisfaction. Major challenges in managing workers include the need to manage

cultural and language differences. Other top-management respondents had problems with

ensuring discipline in the organization. Health and safety issues also remain one of the main

factors which posed challenges to construction site managers.

In order to increase motivation, management again suggested training and development,

financial incentives, payment for overtime, and worker participation in decision making. In

cases where an accident or an error occurs, management attempts to understand the scope of

the problem and do not issue punishment at the scene. In the case of accidents however, the

site nurse is called to attend to the injured before any other enquiries are made. Where the nurse

is incapable of addressing the injuries or where the injuries are severe, workers are sent to the

nearest medical facility for attendance. Severe matters are usually reported to the head office

of the companies.

All managers agreed that bad weather conditions have adverse impact on workers motivation

and productivity. Many of them also commented that crowded site does reduce workers’

productivity. Interview respondents however had mixed respondents on whether competition

does or does not influence workers’ productivity, some of them nonetheless mentioned that it

is important to tie payment and other financial rewards with competition and performance.

Culture differences significantly impacts negatively on workers motivation even though a few

respondents would not clearly associate culture differences as deterrent of motivation. All

respondents however agreed that it is important for workers to work from home in order to

relax, attend to family, and save time.

Other data sought from respondents pertained to worker supervision, whereas all respondents

agreed that close supervision is important, primarily as an organizational element, a single

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response was in the opposite direction that supervision is not a critical factor. Days off are

mostly available in the organizations and are very important to workers motivation. An increase

in salaries and other financial compensations are observed as important factors that can increase

motivation and productivity in the construction industry.

In order to arrive at more succinct results, other closed ended questions were considered. Data

collected from the later aspects of the interview guide are presented in Figure 4.39.

Figure 4.39 Workers motivation factors (management perspective)

Management also commented that they do not usually work in shifts (6 respondents), whereas

others mentioned that they do work in shift and it does not really motivate workers. A total of

8 managers thought discipline is important for productivity, they also agrees that safety rules

are installed on site and this does contributes to workers’ productivity. Other factors pertaining

to management perspective of what factors motivate workers and increase productivity are

presented in Figure 4.40 and Figure 4.41. In Figure 4.42, respondents were asked to rate site

management, equipment management, and materials management out of a total of 10, as key

determinants of productivity.

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Figure 4.40 Managers’ perspective of workers motivation

Figure 4.41 Rating of site, materials, and equipment management

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Other statistics showing top management perception of motivation and workers’ productivity

are presented in Appendix J.

4.4 Orientation of employee motivation and performance in the construction sector

Since the investigation was conducted in a single group in a single cross-sectional, one

important manner through which the results showed above and pertaining to the sample

collected form the study can be assessed as representative of the larger population is the one-

sample t-test statistical analysis approach. The population mean for all responses were

maintained at the center of responses based on the assumption that no particular differences

exist between variables of the study. Four statements were selected from each dimension; two

on motivation and other two on productivity.

Physical Factors

Table 4.5 assesses the level of significance based on the assumption of no particular impact on

motivation and productivity by any of the items examined in the survey.

Table 4.5 Test for significance (Physical factors)

Dimension Test Value Mean t Sig (2-tailed) Mean difference

Project design on motivation 2.5 1.12 -40.956 .000 -1.376

Productivity disruptions on motivation 2.5 1.76 -7.975 .000 -0.737

Working in shift and productivity 2.0 1.62 -3.804 .000 -0.3711

Crowdedness and productivity 2.0 2.28 2.666 .009 0.278

Concerning Physical factors, it may be established that considering a population mean of no

particular effect of these factors on motivation and productivity, such assertions may be

rejected. In order words, the findings significantly differ from the population assumption that

one or more of these items does not impact on motivation and productivity. It may as well be

observed that the mean values are lower that the population mean values, since the responses

were coded as ‘1’= ‘very important/yes’ and ‘4/5’ = ‘Not important at all/No’, it may be

interpreted that the actual results of the study shows that these variables are important

determinants of motivation and productivity.

Psychological Factors

Presented in Table 4.6 pertain to the establishment of relationship that no relationship exists

between psychological variables and motivation/productivity. Key variables here include

responsibility, social activity, discipline, and overall satisfaction.

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Table 4.6 Test for significance (Psychological factors)

Dimension Test Value Mean t Sig (2-tailed) Mean difference

Responsibility on motivation 2.5 1.63 -10.688 .000 -0.8696

Social activity on motivation 2.5 1.77 -8.699 .000 -0.7268

Discipline and productivity 2.5 1.47 -17.448 .000 -1.0257

Satisfaction and productivity 2.5 1.35 -19.584 .000 -1.1495

Findings pertaining to psychological factors and their impact on workers motivation and

productivity presented in Table 4.6, imply that significant differences exist between the test

values and the study findings. The test value that the various elements have a neutral impact

on motivation and productivity may therefore be rejected.

Organizational Factors

Organizational factors examined as having any impact on motivation include crew size and

company name. Other factors examined in context of productivity include supervision and

training, as presented in Table 4.7.

Table 4.7 Test for significance (Organizational factors)

Dimension Test Value Mean t Sig (2-tailed) Mean difference

Crew size on motivation 2.0 1.495 -4.918 .000 -0.505

Company name on motivation 2.5 1.454 -13.736 .000 -1.0464

Supervision and productivity 2.0 1.6598 -3.77 .000 -0.340

Training and productivity 2.0 1.536 -4.664 .000 -0.6614

Organizational factors as well are significantly different from the population mean that these

factors have no impact on motivation and productivity. Thea mean values under this dimension

are as well lower than the population mean, implying results points into a favorable direction

where these factors are considered to have positive influence on motivation and productivity.

Economic Factors

This represents the last dimension investigated from the perspective of the construction

workers.

Table 4.8 Test for significance (Economic factors)

Dimension Test Value Mean t Sig (2-tailed) Mean difference

Salary on motivation 2.5 1.4021 -16.482 .000 -1.0979

Social Insurance on motivation 2.5 1.4124 -15.912 .000 -1.0876

Rewards & bonuses and productivity 2.0 1.3918 -8.210 .000 -0.6083

Union membership and productivity 2.5 1.5155 -10.742 .000 -0.98454

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Key items tested under this dimension include salary and social insurance as important

determinants of workers motivation, and rewards & bonuses and union membership as key

determinants of productivity, as presented in Table 4.8. Mean comparisons with population

mean shows that significant differences exist. It may therefore be held that the assumption that

the economic factors have no impact on motivation and productivity may be rejected.

4.5 Discussions and Improvement of motivation towards enhanced performance

Generally, responses from construction workers were favorable. Both quantitative and

qualitative data findings indicate that salaries and other financial awards are key determinants

of construction worker motivation. In order to improve motivation of workers, the four areas

pertaining to the physical, psychological, organizational, and economic dimensions must be

attended to. It is important that close attention is paid to weather conditions. In the UAE,

geographical and other climatic conditions are mostly unfavorable, especially for outdoor

activities like that construction labor activities. Even though the UAE government has

established rules and regulations in order to control workers activities in times when climatic

conditions are harshest, there is also the need to put measures in place to take care of workers

throughout the year in order to ensure that workers are in the best of conditions.

Workers must as well be made to interact with themselves more often in addition to other

contributions to overall organizational decision making. Such factors, according to the

investigation, would primarily increase motivation and productivity. Interaction must be made

possible however not at the expense of discipline as management stressed that discipline is a

critical element to ensuring that tasks are successfully executed in the work place. Interaction

must be ensured within the companies to ensure that workers would have a sense of

contribution towards organizational development. In addition to interactions among workers

and with management, proximity of home to work place would significantly improve

performance by ensuring that workers interact with family and reach the work place with ease.

Concerning organizational factors, even though workers did not value materials management

and other elements within this category as opposed to other items in the other dimensions, top

management stressed that such factors are very important to productivity. These factors are

therefore observed as within the jurisdiction of management. Management must implement

organizational elements which include training and development, site layout, materials

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management, equipment management, crew size, and other factors towards ensuring optimum

motivation and productivity.

The final dimension of economic factors are as well equally important in ensuring motivated

employees. Salaries is a very important factor here, agrees by both management and operational

employees. From the results, salaries were observed as not enough for the construction

workers. Since workers’ salaries are very important to motivation, there is the need to increase

workers salary and other financial benefits. There is the need to increase rewards and bonuses

even for overtime work done. It was observed that workers unions are largely unavailable. To

add to that, construction workers do acknowledge union membership as a motivating factor.

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Chapter Five: Conclusions & Recommendations

5.1 Introduction

This section establishes conclusions based on findings of the study and in accordance with the

research objectives established in chapter one. It may be noted that conclusions are established

in consideration of findings and other literature discussed earlier in the study. The agreement

or disagreement of findings to reviewed literature on the area of study is also discussed. Aside

from conclusions, recommendations are also established. Recommendations are proposed on

future researches on motivation among construction workers. Other recommendations are

proposed on enhancement of employee motivation towards improved performance in the case

study firms. Finally, recommendations are offered to industry stakeholders, with particular

regards to construction organizations in the GCC construction sector.

5.2 Conclusions

Conclusions are established in context of the three main objectives set in the primary chapter

of the study.

Factors influencing motivation of workers in the construction industry

Categorized into four main factors, physical factors are an important aspect of construction

workers’ motivation. Basically workers wish to be kept in the same or similar work activity.

They as well believed that minor mistakes should be forgiven and weather conditions

acknowledged. Climatic condition are a very important area for productivity. Other factors that

significantly affect productivity include production disruptions and production pressures.

Workers had mixed feeling that crowdedness does impact on productivity. This may be due to

the believe by some workers that a larger work force would reduce individual stress load and

ensure that work activities are successfully executed.

Pertaining to psychological factors, disciple and productivity significantly impacts on

productivity and workers motivation. Management as well agrees that these together with

adequate relationship with co-workers would enhance motivation. Even though workers

believed that competition affects productivity to some extent, some management employees

believed that this was quite debatable. Company inclusion of workers in the decision making

process is observed as another important psychological variable which contributes to

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construction workers’ motivation. Social activities nonetheless contributed greatly to

motivation. It must be mentioned here however, that cultural difference presents one of the

highest forms of psychological challenges to both management and operational workers

towards motivation and productivity.

The third area of discussion of factors affection construction workers’ motivation and

productivity was attributable to organizational factors. It may be concluded that management

are the largest stakeholders with regards to these factors and their ability to ensure optimum

performance. Even though some of the items identified under this dimension may influence

motivation of operational workers, such factors are not dominant. It is important to ensure that

sire, materials, and equipment are effectively and efficiently managed by management towards

increased productivity. There is the need to ensure that work is organized and supervised,

training and development installed, and a good layout implemented. In addition to these, crew

size must be controlled at all timed in order to ensure that optimum performance per group is

achieved. Camping conditions and off days must as well be offered.

The last dimension pertaining to economic factors revealed that on-time payment is critical to

motivation. Other factors include salary and motivation, social security, rewards and

productivity. Such economic factors are among some of the most significant factors that impact

on motivation and performance, and must be duly noted.

Relationship between motivation and productivity of construction workers & Improvement

Based on an assessment of the sample mean with the population assumed mean, significant

results were arrived at. Due to the non-existence of comparable means to use as test valued, the

midpoint of each item was assumed as the population mean, assuming responses form the

population are neutral. Findings revealed that such assumption be rejected; significant

difference of means exist between the population and sample mean values all the dimensions

under investigation.

Based on discussion, key areas that must be attended to in order to improve performance and

productivity are in areas of financial rewards and other such compensations. Basically, salaries

must be increased to an acceptable level. Other bonuses and financial rewards must be offered

to workers, especially when they work for longer that contracted durations. Weather conditions

must as well be improved. Management might want to pay close attention to organizational

factors towards the larger organizational performance.

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5.3 Recommendations

Based oni findings, it is recommended that workers conditions be improved, important areas

that is recommended for improvement pertains to financial benefits awarded to construction

workers. Workers showed concern for lower financial benefits even though they as well agreed

that such financial benefiots are fundamental to motivation and productivity. It is recommended

that the instruments for conducting the investigation be improved and made more reliable. The

fact that the dimensions, particularly the physical and economic dimensions, failed the

Chronbach alpha reliability test, the overall results pertaining to these areas may be

questionable. There is the need to ensure that the various items in the dimensions are re-visited

and re-tested for relaibility.

A framework that considers a ratio/interval asessment of factors and their contribution to

motivation and production should be established. This would belp investigate correlation and

regression analysis between important causes of motivation and its result in terms of

productivity. Further attempt should be made to separate motivation and productivity on two

different platforms. As done in the present study, the distinction between motivation and

productivity is not very clear. The relationship between workers motivation and productivity

must as well be investigated. It must be established whether construction workers motivation

leads to any level of productivity.