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International Journal of Civil Engineering and Technology (IJCIET)
Volume 8, Issue 1, January 2017, pp. 340–348, Article ID: IJCIET_08_01_038
Available online at http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=8&IType=1
ISSN Print: 0976-6308 and ISSN Online: 0976-6316
© IAEME Publication
ASSESEMENT ON FACTORS DECLINING
LABOUR PRODUCTIVTY INCONSTRUCTION
PROJECTS
Achuth Kumar N.V
M. Tech Student Civil Engineering Department,
K L University, Vaddeswaram – 522 502 (A.P)
SS.Asadi
Associate Dean-Academics, Civil Engineering Department,
K L University, Vaddeswaram - 522 502 (A.P)
ABSTRACT
Objective: Identifying the factors which are affecting the labour productivity and
leading to its decline. Defining the major causing factors which minimize 80% of maximum
damage done to decline the labour productivity. Methodology: Survey is conducted and
data collected through questionnaire followed by reliability test, ranking and Pareto
analysis, Pareto analysis is done to indicate the factors which can minimize the damage
about 80%. Findings: Results reveals that Cronbach coefficient value 0.7-0.8 which proves
that collected data is consistent, factors lack of skilled labour with RII value 0.92, improper
planning with RII value 0.83 and malfunctioning of equipment with RII value 0.78 are
major that would affect the labour productivity and Pareto analysis shows that factors from
efficiency related, management related and technical related are main in declining labour
productivity in Indian scenario construction projects. Novelty/Improvement: Decline in
labour productivity is concern for resource management which is critical in execution of
construction projects. Efficiency and technical related factors proves to be critical in
declining the productivity on job site.
Key words: Construction Management, Labour Productivity, Pareto Analysis,
Management Strategies.
Cite this Article: Achuth Kumar N.V and SS.Asadi, Assesement On Factors Declining
Labour Productivity In Construction Projects. International Journal of Civil Engineering
and Technology, 8(1), 2017, pp. 340–348.
http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=8&IType=1
1. INTRODUCTION
Construction workmen are trade men, labourer or professional employed at the execution of
construction of built environment and its concern infrastructure developlement. Basic Labour
productivity in construction is taken as work done per man hour with concern activity. The
productivity is main achieving the goals which are established in completing the project, but in
recent years the productivity which are produced by labour has been declined for so many reasons
Assesement On Factors Declining Labour Productivity In Construction Projects
http://www.iaeme.com/IJCIET/index.asp 341 editor@iaeme.com
may due size of work, resource availability, economical conditions of organization and as well as
labour who is involved with organization and some miscellaneous reasons.
Labour characteristics: To analysing the declination of production rate of labour we go to roots
of the production of labour about their characteristics, the basic characteristics of labour are age
factor which they are governed with, skills produced by labour, experiences of labour and
leadership qualities of labour1
.
Productivity can be measured by various methods by various ways through management by
objectives, measuring productivity quantitatively, 360 degree feedback, measuring sales
productivity, service productivity, time management productivity, productivity by profit2
.
To analysis the defects for low labour productivity, primarily we have to measure productivity
which was produced by labour involved in execution of construction .There can taken necessary
steps to improve the labour productivity through few maturing techniques and also reveals concept
about basic definitions and productivity improving techniques by considering two case studies and
providing information through techniques like project management index, covariance coefficient,
project performance and indentifying the factors affecting the productivity3
. states that labour
productivity declination was due to many factors which are many departments, so survey was
conducted in and around Nairobi and results reveals that lack of skilled labour 90% was top among
12 factors and also provided management strategies like training ,mentoring, work measurement,
outsourcing and supply crew size to improve the labour productivity4
. states that jobsite
productivity is mainly based on labour, they are many factors which affect the productivity among
those the factors are subdivided into project related factors, labour related factors, resource related
factors, efficiency related factors, and management related factors, survey is conducted among
industrial experience people and stated that among increase in price of materials is major factors
which affect the productivity5
. that their many categories in factors affecting the labour
productivity they are taken into analytical hierarchy process model taking psychological,
experience, physical, time and work load, supervision and leadership, external and proves that job
satisfaction, job security, lack of incentives, skill and experience and drug use and work load plays
major role in affecting the labour productivity6
. There are many factors affecting the labour
productivity and study is followed analysing the data through reliability test factor analysis,
regression analysis and few other tests gives results that planning is major factor that would affect
the productivity followed by material availability. The labour which are involved in the
construction tends to be older persons and sometimes the productivity which is produced by them
might be less as compared to the estimated due various reasons the major would be grouped into
external related factors such as socio economic factors and physical factors relating to their living
standards and policies relating to socioeconomic and living conditions of the labour7
. The
manpower relating to the construction activities is largely influenced by the labour involved and
those parameters are influenced by the migration of the labour from other countries and respective
states especially these can witnessed in the Kazakhstan which on improving the global labour
market. Large migration can affect the national labour market and leads to encouraging the illegal
migration of the labour into the nation. These can be reduced by improving the international legal
regulation of labour migrants and streamlining the export based manpower aboard and
implementation of norms of the labour relation laws and rights of labour and also by improving
the knowledge of the labour on the “Labour Relations Law of the Republic of Kazakhstan”8
.
• Labour related factors (2,3,4,6
): No job security, lack of general utilities, low wages, truancy of
work by labour, Disputes among labour.
• Technical related (2,3,4,6
): Poor planning, delay due to numerical errors, rework due to design
faults.
Achuth Kumar N.V and SS.Asadi
http://www.iaeme.com/IJCIET/index.asp 342 editor@iaeme.com
• Management related (2,3,4,6
): less crew size, economical condition, not providing incentive
scheme, poor communication between parities, work load.
• Efficiency related (2,3,4,6
): Incompetent staff, lack of experience supervisors, lack of skilled
labour, malfunction of machinery.
• External related (2,3,4,6,8
): weather conditions, safety violations, social environment .
2. METHODOLOGY
2.1. QUESTIONAIR SURVEY: A questionnaire survey was conducted with factors from
different aspects which affect the labour productivity they are labour related, technical related,
management related, efficiency related, external, and survey conducted with opinions from
industrial experience persons and rate the factor in the scale of 1-5(2,3,4,6
).
1=very poor, 2=poor, 3=neutral, 4=strong, 5= very strong. Factors are considered 5 from labour
related,3 from technical related,5 from management related,4 from efficiency related,3 from
external factors.
2.2. RELIABILITY METHOD
Test is conducted to prove that collected data is reliable (2,3,4,6
) for further studies and know its
degree of consistency. The Cronbach coefficient value shows that data consistency in concern
field. The coefficient values which are considered are mentioned below. If alpha value is greater
than 0.7, the data which is collected is Considered as acceptable for further analysis mentioned in
table 1
Table 1 Details of Cronbach coefficient values for reliability test
Cronbach value consideration
α >0.9 Represents Excellent
α >0.8 Represents Good
α >0.7 Represent Acceptable
α >0.6 Represent Questionable
α >0.5 Represents Poor
α<0.4 Represents Unacceptable
2.3. RANKING METHOD
The relative importance index method RII (2,3,4.5,6
) was used to determine that industrial person’s
opinion of the relative importance to the identified management factor which may affect the labour
productivity. Using this formula the major significant factors was identified. The RII was
computed as,
RII= ∑ W ∕ A* N……………………………...equation 1
Where,
RII - Relative Importance Index,
W = weighting given to each factor by the respondents (ranging from 0 to4) A = highest weight
(i.e. 4)
N = total number of respondents.
2.4. PARETO ANALYSIS
Pareto analysis is a useful technique in the area where factors are acting in as complex nature. It
estimates the benefits which are going to get on action which is to taken on factors and selects
Assesement On Factors Declining Labour
http://www.iaeme.com/IJCIET/index.
those factors which would max benefit if action is taken
maximum closely range .Pareto analysis is a better way of analyzing at root causes of problems,
because it helps in improving thinking and structuring the thoughts in getting results. However, it is
limited by its exclusion of possibly important problems which may be small initially, but will
improve with time. This technique helps to identify the top factors which are needed to be
considered to minimize the maximum of problems. Once the major causes are identified
are used to identify the root causes of the problems. Pareto says that "80/20" rule, under the
assumption that, in all situations, 20% of causes determine 80% of problems
3. RESULT AND DISCUSSIONS
3.1. DEMOGRAPHIC ANALYSIS
consisting of factors from 5 different aspects namely labour, management, and efficiency,
technical, external which will affect labour productivity. Totally 30 response was received out of
42 which are received manually and through mails
As per mentioned in figure 1 a total of 30 respondents out of which 13 are project managers
holding a 43% major in participation in the survey, and remaining4 where AEE,2 are EE,3 are
senior engineers,2 are asst project man
Figure 1 Details of respondents for demographic analysis
Assesement On Factors Declining Labour Productivity In Construction Projects
IJCIET/index.asp 343 editor@iaeme.com
those factors which would max benefit if action is taken on those factors in getting the benefit in
maximum closely range .Pareto analysis is a better way of analyzing at root causes of problems,
because it helps in improving thinking and structuring the thoughts in getting results. However, it is
exclusion of possibly important problems which may be small initially, but will
improve with time. This technique helps to identify the top factors which are needed to be
considered to minimize the maximum of problems. Once the major causes are identified
are used to identify the root causes of the problems. Pareto says that "80/20" rule, under the
assumption that, in all situations, 20% of causes determine 80% of problems7
.
SIONS
DEMOGRAPHIC ANALYSIS Survey (2,3,4,6
) was conducted with preferred
consisting of factors from 5 different aspects namely labour, management, and efficiency,
technical, external which will affect labour productivity. Totally 30 response was received out of
ived manually and through mails
As per mentioned in figure 1 a total of 30 respondents out of which 13 are project managers
holding a 43% major in participation in the survey, and remaining4 where AEE,2 are EE,3 are
senior engineers,2 are asst project manager,4 are general manager,2 are asst general managers.
Details of respondents for demographic analysis
In Construction Projects
editor@iaeme.com
on those factors in getting the benefit in
maximum closely range .Pareto analysis is a better way of analyzing at root causes of problems,
because it helps in improving thinking and structuring the thoughts in getting results. However, it is
exclusion of possibly important problems which may be small initially, but will
improve with time. This technique helps to identify the top factors which are needed to be
considered to minimize the maximum of problems. Once the major causes are identified, then tools
are used to identify the root causes of the problems. Pareto says that "80/20" rule, under the
was conducted with preferred questionnaire
consisting of factors from 5 different aspects namely labour, management, and efficiency,
technical, external which will affect labour productivity. Totally 30 response was received out of
As per mentioned in figure 1 a total of 30 respondents out of which 13 are project managers
holding a 43% major in participation in the survey, and remaining4 where AEE,2 are EE,3 are
ager,4 are general manager,2 are asst general managers.
Achuth Kumar N.V and SS.Asadi
http://www.iaeme.com/IJCIET/index.asp 344 editor@iaeme.com
Table 2 Experience of respondents in demographic analysis
Serial NO EXPERIENCE IN YEARS NO OF RESPONDENT
1 0 - 10Y 2
2 10Y - 15Y 8
3 15Y - 20Y 7
4 ≥20Y 16
TOTAL 33
Respondents who are involved in survey has a vast experience in construction sector, according
to the table 2 mentioned response who has major 13 persons out of 30 holding 43% having
experience above 20 years and 2nd having 8 out of 30 holding 27% having experience 10-15 years,
3
rd
having 7 out of 30 holding 23% having experience 15-20 years and 4
th
least 2 out of 30 holding
7% having experience 0-10 years.
3.2. REABILITY TEST: Total 20 factors are considered as variables and reliability test is
conducted in SPSS software 20 mentioned. Data from each component of questionnaire were
tested for its Cronbach α value. To ensure that the collected data are valid and reliable for analysis
(2,3,4,6
). Table 3 shows values of Cronbach α in each category of the questionnaire data. The alpha
values vary from of 0.70 to 0.80. This shows that data collected was acceptable and acknowledged
as good. Thus, the reliability of collected data is assured. Certainly, this shows that the
questionnaire data which is collected are valid and reliable.
Table 3 Cronbach coefficient values of reliability test
Component of data collected Cronbach α value
Labour related 0.73
Management related 0.76
Efficiency related 0.75
Technical related 0.72
External related 0.76
3.3. RANKING METHOD
Management factors as shown in table 4 which are driven from 5 category related factors, totally
holding with 20 factors and to rank these factors RII was used and computed in Microsoft excel
which are considered to be critical in ranking the factors which are causes for declination of labour
productivity (2,3,4,6
).
As mentioned in table 4 the “lack of skilled labour” is major factor in declination 0f labour
productivity with RII value 0.92 which are driven from efficiency related factors , reason is time
completion of concern activity is increased due to less skill and knowledge and may lead repetitive
corrections and wastage of resources,2
nd
position was improper work schedule with RII value
0.833 from technical related factors because of which completion time of previous is not done and
resource allocation to concern activity is not provided at time due to which productivity can
reduced,3
rd
position was malfunctioning of machinery with RII value 0.786 which to which time
consumption of required activity get delayed or even postponed due to sudden breakdown of
machine involved in activity and resource allocated to concern activity can be wasted and
scheduled work gets disturbed which lead to critical path of activities and rest are shown in table 4
Assesement On Factors Declining Labour Productivity In Construction Projects
http://www.iaeme.com/IJCIET/index.asp 345 editor@iaeme.com
Table 4 Ranking to factors affecting labour productivity
Rank Factors affecting labour productivity Weight RII
1 lack of skilled labour 138 0.92
2 Improper work schedule 125 0.833
3 Malfunctioning of equipment 118 0.786
4 lack of experienced supervisors 116 0.773
5 Economical conditions 116 0.773
6 Poor communication between sub contractor and contractor 116 0.773
7 Incompetent technical staff 110 0.773
8 Truancy of work from labour 110 0.773
9 Negligence in providing general utilities 108 0.72
10 Repetitive works due to design faults 108 0.72
11 Delay due to numerical errors in design drawings 106 0.706
12 Unsuitable weather conditions 100 0.666
13 less crew size compared to estimated manpower 98 0.653
14 low wages compared with living standards 92 0.613
15 Safety violations 92 0.613
16 Negligence in incentive scheme providing to them 83 0.553
17 No job security 73 0.486
18 Work load 62 0.266
19 Disputes among labour 40 0.26
20 Social environment 39 0.413
3.4. PARETO ANALYSIS
In order to regroup the disintegrated pattern of the factors obtained, Pareto analysis was applied.
The data collected through survey and ranking is provided to them earlier which was shown in
table 4 by taking those score in to consideration score percentage and cumulative percentage of
data are calculated which was shown in table 5.Pareto Analysis are shown in Table 5 and
illustrated in Figure 2 . The results of Pareto Analysis show that the first 14 factors contribute to
about 80% of the weight of all the factors7
. These 14 factors can be considered as the most
important factors affecting labour productivity. Lack of skilled labour would be major about 7% ,
improper work schedule with 6%,malfunctioning of equipment in total contribution of 100% as
shown in figure 2.so to minimize the 80% of declination of labour productivity the primarily the 14
factors should be considered important and they should be nullified first to improve productivity .
Table 5 Details regarding to Pareto analysis for factors affecting productivity
Factors affecting labour productivity Weight Weight %
Cumulative weight
%
lack of skilled labour 138 7.07 7.07
Improper work schedule 125 6.41 13.48
Malfunctioning of equipment 118 6.05 19.53
lack of experienced supervisors 116 5.948 25.478
Economical conditions 116 5.948 31.426
Poor communication between sub contractor and contractor 116 5.948 37.374
Incompetent technical staff 110 5.641 43.015
Truancy of work from labour 110 5.641 48.656
Negligence in providing general utilities 108 5.538 54.194
Repetitive works due to design faults 108 5.538 59.732
Delay due to numerical errors in design drawings 106 5.435 65.167
Unsuitable weather conditions 100 5.128 70.295
less crew size compared to estimated manpower 98 5.025 75.32
Achuth Kumar N.V and SS.Asadi
http://www.iaeme.com/IJCIET/index.
Factors affecting labour productivity
low wages compared with living standards
Safety violations
Negligence in incentive scheme providing to them
No job security
Work load
Disputes among labour
Social environment
Figure 2 Details of Pareto analysis for factors affecting productivity
4. CASE STUDY
Case study was considered to show the declination of labour productivity in execution at job site.
The case study deals with housing complex with 5 construction buildings each building comprises
of 5 floors with completion period about 2 years and about 280 labour was utilised to both skilled
and unskilled per day.
4.1. COMPARISSION BETWEEN ACTUAL PRODU
THERIOTICAL PRODUCTIVITY
Basic definition of productivity is that work output for man
labour productivity is calculated at job site conditionAs shown in figure 3 there are small variation
in the activities for brick work and 12 mm plastering done at construction due skilled workers are
utilised and also the transportation of
and there are no objections from technical client depar
more variation in productivity in the pouring of concrete activity regarding to activity concern with
above foundation, pouring done manually because of less efficient labourer where utilised and
Achuth Kumar N.V and SS.Asadi
IJCIET/index.asp 346 editor@i
actors affecting labour productivity Weight Weight %
low wages compared with living standards 92 4.717
92 4.717
egligence in incentive scheme providing to them 83 4.256
73 3.743
62 3.179
40 2.051
39 2.017
Details of Pareto analysis for factors affecting productivity
Case study was considered to show the declination of labour productivity in execution at job site.
The case study deals with housing complex with 5 construction buildings each building comprises
of 5 floors with completion period about 2 years and about 280 labour was utilised to both skilled
COMPARISSION BETWEEN ACTUAL PRODUCTIVITY AND
HERIOTICAL PRODUCTIVITY
Basic definition of productivity is that work output for man-hour to concern activity, general the
labour productivity is calculated at job site conditionAs shown in figure 3 there are small variation
for brick work and 12 mm plastering done at construction due skilled workers are
utilised and also the transportation ofrequired material are given without any delay by any source
and there are no objections from technical client department regarding to drawings, but there is
more variation in productivity in the pouring of concrete activity regarding to activity concern with
above foundation, pouring done manually because of less efficient labourer where utilised and
editor@iaeme.com
Cumulative weight
%
80.037
84.754
89.01
92.753
95.932
97.983
100
Details of Pareto analysis for factors affecting productivity
Case study was considered to show the declination of labour productivity in execution at job site.
The case study deals with housing complex with 5 construction buildings each building comprises
of 5 floors with completion period about 2 years and about 280 labour was utilised to both skilled
CTIVITY AND
hour to concern activity, general the
labour productivity is calculated at job site conditionAs shown in figure 3 there are small variation
for brick work and 12 mm plastering done at construction due skilled workers are
required material are given without any delay by any source
tment regarding to drawings, but there is
more variation in productivity in the pouring of concrete activity regarding to activity concern with
above foundation, pouring done manually because of less efficient labourer where utilised and
Assesement On Factors Declining Labour
http://www.iaeme.com/IJCIET/index.
vertical lifting is major affect in decline in productivity as compared concrete pouring below
foundation level and mentioned in table 6.
Table 5 Details regarding to Pareto analysis for factors affecting productivity
Factors affecting labour productivity
lack of skilled labour
Improper work schedule
Malfunctioning of equipment
lack of experienced supervisors
Economical conditions
Poor communication between sub contractor and
contractor
Incompetent technical staff
Truancy of work from labour
Negligence in providing general utilities
Repetitive works due to design faults
Delay due to numerical errors in design drawings
Unsuitable weather conditions
less crew size compared to estimated manpower
low wages compared with living standards
Safety violations
Negligence in incentive scheme providing to them
No job security
Work load
Disputes among labour
Social environment
Figure 3 Comparison for labour productivity at site through case study
Assesement On Factors Declining Labour Productivity In Construction Projects
IJCIET/index.asp 347 editor@iaeme.com
s major affect in decline in productivity as compared concrete pouring below
foundation level and mentioned in table 6.
Details regarding to Pareto analysis for factors affecting productivity
actors affecting labour productivity Weight Weight %
138 7.07
125 6.41
118 6.05
116 5.948
116 5.948
oor communication between sub contractor and
116 5.948
110 5.641
110 5.641
egligence in providing general utilities 108 5.538
epetitive works due to design faults 108 5.538
elay due to numerical errors in design drawings 106 5.435
100 5.128
size compared to estimated manpower 98 5.025
low wages compared with living standards 92 4.717
92 4.717
egligence in incentive scheme providing to them 83 4.256
73 3.743
62 3.179
40 2.051
39 2.017
Comparison for labour productivity at site through case study
In Construction Projects
editor@iaeme.com
s major affect in decline in productivity as compared concrete pouring below
Details regarding to Pareto analysis for factors affecting productivity
Cumulative
weight %
7.07
13.48
19.53
25.478
31.426
37.374
43.015
48.656
54.194
59.732
65.167
70.295
75.32
80.037
84.754
89.01
92.753
95.932
97.983
100
Comparison for labour productivity at site through case study
Achuth Kumar N.V and SS.Asadi
http://www.iaeme.com/IJCIET/index.asp 348 editor@iaeme.com
5. CONCULSIONS
• A questionnaire survey is conducted with 20 factors from 5 different categories and 78 % is
achieved in return of 30 from 45 persons who had completed projects in overall country
• The data which is collected had got reliability value from range 0.7 to 0.8 which is preferred as
highly reliable source and allowed for further analysis
• Lack of skilled labour is major factor which would affect the labour productivity with 0.92 RII
value from technical related category
• Improper work schedule is second among major factors affecting productivity with RII value
0.833 from technical related factors
• Malfunctioning of equipment is 3rd
position with RII value 0.786 which affecting Labour
productivity considered from efficiency related factors
• Efficiency related, technical related and management related are critical in reducing the damage
about 80% in affecting the labour productivity
• Pareto analysis is done among the 20 factors from 5 categories and results reveals that 14
factors shown in figure 2 are critical in minimizing the damage of labour Productivity about
80%
REFERENCES
[1] Mostafa E S, Khaled M E. Towards improving construction labour productivity and projects
performance. Alexandria Engineering Journal. 2012 December; 50(4), 321–330.
[2] Nithya k, Saravanan M M. Evaluation of factors improving jobsite productivity. Advanced
Engineering and Applied Sciences: An International Journal. 2015 May; 5(2), 28-31.
[3] Shashank K, Sutapa H, Kabindra NP. Analysis on key factors affecting the variation of labour
productivity in construction projects. International Journal of Emerging Technology and
Advanced Engineering. 2014 May; 4(5), 152-161.
[4] Prakash Rao B , Ambika S, Prasad Babu N V. Labour productivity-analysis and ranking.
International Research Journal of Engineering and Technology. 2015 June; 2(3), 151-155.
[5] Absalom H V L. Factors Influencing Effective Productivity on Construction Sites in Nairobi
County. International Journal of Soft Computing and Engineering. 2014 November; 4(5), 24-
30.
[6] Hasan H, Nadine A. Enhancing Labour Productivity within Construction Industry through
Analytical Hierarchy Process, the Case of Gaza Strip. Universal Journal of Management 2015;
3(8), 329-336.
[7] Nikolayevich P I. Labor Activity Dynamics of Older Persons in the Far East of Russia. Indian
Journal of Science and Technology. 2015 December; 8(10), 1-6.
[8] D. Satish Chandra, SS. Asadi and M.V.S. Raju, Design of Web Based Decision Support System
- Model Study of Vijayawada, A.P. International Journal of Civil Engineering and Technology,
7(6), 2016, pp.514–522.
[9] G.S. Sarma, SS. Asadi and S. Lakshmi Narayana, Creation of Web Based Decision Support
Information System for Evaluation of Topographic Characteristics Using Remote Sensing &
GIS and Visual Basic Programe. International Journal of Civil Engineering and Technology,
7(6), 2016, pp. 621–634.
[10] Yermek A B, Gulzhazira B M, Aliya K, Aigerim Z.Z, Elmira M M. Legal Regulation of Labor
Migration in the Republic of Kazakhstan. Indian Journal of Science and Technology. 2016 Apr,
9(16), pp.1-5.

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ASSESEMENT ON FACTORS DECLINING LABOUR PRODUCTIVTY IN CONSTRUCTION PROJECTS

  • 1. http://www.iaeme.com/IJCIET/index.asp 340 editor@iaeme.com International Journal of Civil Engineering and Technology (IJCIET) Volume 8, Issue 1, January 2017, pp. 340–348, Article ID: IJCIET_08_01_038 Available online at http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=8&IType=1 ISSN Print: 0976-6308 and ISSN Online: 0976-6316 © IAEME Publication ASSESEMENT ON FACTORS DECLINING LABOUR PRODUCTIVTY INCONSTRUCTION PROJECTS Achuth Kumar N.V M. Tech Student Civil Engineering Department, K L University, Vaddeswaram – 522 502 (A.P) SS.Asadi Associate Dean-Academics, Civil Engineering Department, K L University, Vaddeswaram - 522 502 (A.P) ABSTRACT Objective: Identifying the factors which are affecting the labour productivity and leading to its decline. Defining the major causing factors which minimize 80% of maximum damage done to decline the labour productivity. Methodology: Survey is conducted and data collected through questionnaire followed by reliability test, ranking and Pareto analysis, Pareto analysis is done to indicate the factors which can minimize the damage about 80%. Findings: Results reveals that Cronbach coefficient value 0.7-0.8 which proves that collected data is consistent, factors lack of skilled labour with RII value 0.92, improper planning with RII value 0.83 and malfunctioning of equipment with RII value 0.78 are major that would affect the labour productivity and Pareto analysis shows that factors from efficiency related, management related and technical related are main in declining labour productivity in Indian scenario construction projects. Novelty/Improvement: Decline in labour productivity is concern for resource management which is critical in execution of construction projects. Efficiency and technical related factors proves to be critical in declining the productivity on job site. Key words: Construction Management, Labour Productivity, Pareto Analysis, Management Strategies. Cite this Article: Achuth Kumar N.V and SS.Asadi, Assesement On Factors Declining Labour Productivity In Construction Projects. International Journal of Civil Engineering and Technology, 8(1), 2017, pp. 340–348. http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=8&IType=1 1. INTRODUCTION Construction workmen are trade men, labourer or professional employed at the execution of construction of built environment and its concern infrastructure developlement. Basic Labour productivity in construction is taken as work done per man hour with concern activity. The productivity is main achieving the goals which are established in completing the project, but in recent years the productivity which are produced by labour has been declined for so many reasons
  • 2. Assesement On Factors Declining Labour Productivity In Construction Projects http://www.iaeme.com/IJCIET/index.asp 341 editor@iaeme.com may due size of work, resource availability, economical conditions of organization and as well as labour who is involved with organization and some miscellaneous reasons. Labour characteristics: To analysing the declination of production rate of labour we go to roots of the production of labour about their characteristics, the basic characteristics of labour are age factor which they are governed with, skills produced by labour, experiences of labour and leadership qualities of labour1 . Productivity can be measured by various methods by various ways through management by objectives, measuring productivity quantitatively, 360 degree feedback, measuring sales productivity, service productivity, time management productivity, productivity by profit2 . To analysis the defects for low labour productivity, primarily we have to measure productivity which was produced by labour involved in execution of construction .There can taken necessary steps to improve the labour productivity through few maturing techniques and also reveals concept about basic definitions and productivity improving techniques by considering two case studies and providing information through techniques like project management index, covariance coefficient, project performance and indentifying the factors affecting the productivity3 . states that labour productivity declination was due to many factors which are many departments, so survey was conducted in and around Nairobi and results reveals that lack of skilled labour 90% was top among 12 factors and also provided management strategies like training ,mentoring, work measurement, outsourcing and supply crew size to improve the labour productivity4 . states that jobsite productivity is mainly based on labour, they are many factors which affect the productivity among those the factors are subdivided into project related factors, labour related factors, resource related factors, efficiency related factors, and management related factors, survey is conducted among industrial experience people and stated that among increase in price of materials is major factors which affect the productivity5 . that their many categories in factors affecting the labour productivity they are taken into analytical hierarchy process model taking psychological, experience, physical, time and work load, supervision and leadership, external and proves that job satisfaction, job security, lack of incentives, skill and experience and drug use and work load plays major role in affecting the labour productivity6 . There are many factors affecting the labour productivity and study is followed analysing the data through reliability test factor analysis, regression analysis and few other tests gives results that planning is major factor that would affect the productivity followed by material availability. The labour which are involved in the construction tends to be older persons and sometimes the productivity which is produced by them might be less as compared to the estimated due various reasons the major would be grouped into external related factors such as socio economic factors and physical factors relating to their living standards and policies relating to socioeconomic and living conditions of the labour7 . The manpower relating to the construction activities is largely influenced by the labour involved and those parameters are influenced by the migration of the labour from other countries and respective states especially these can witnessed in the Kazakhstan which on improving the global labour market. Large migration can affect the national labour market and leads to encouraging the illegal migration of the labour into the nation. These can be reduced by improving the international legal regulation of labour migrants and streamlining the export based manpower aboard and implementation of norms of the labour relation laws and rights of labour and also by improving the knowledge of the labour on the “Labour Relations Law of the Republic of Kazakhstan”8 . • Labour related factors (2,3,4,6 ): No job security, lack of general utilities, low wages, truancy of work by labour, Disputes among labour. • Technical related (2,3,4,6 ): Poor planning, delay due to numerical errors, rework due to design faults.
  • 3. Achuth Kumar N.V and SS.Asadi http://www.iaeme.com/IJCIET/index.asp 342 editor@iaeme.com • Management related (2,3,4,6 ): less crew size, economical condition, not providing incentive scheme, poor communication between parities, work load. • Efficiency related (2,3,4,6 ): Incompetent staff, lack of experience supervisors, lack of skilled labour, malfunction of machinery. • External related (2,3,4,6,8 ): weather conditions, safety violations, social environment . 2. METHODOLOGY 2.1. QUESTIONAIR SURVEY: A questionnaire survey was conducted with factors from different aspects which affect the labour productivity they are labour related, technical related, management related, efficiency related, external, and survey conducted with opinions from industrial experience persons and rate the factor in the scale of 1-5(2,3,4,6 ). 1=very poor, 2=poor, 3=neutral, 4=strong, 5= very strong. Factors are considered 5 from labour related,3 from technical related,5 from management related,4 from efficiency related,3 from external factors. 2.2. RELIABILITY METHOD Test is conducted to prove that collected data is reliable (2,3,4,6 ) for further studies and know its degree of consistency. The Cronbach coefficient value shows that data consistency in concern field. The coefficient values which are considered are mentioned below. If alpha value is greater than 0.7, the data which is collected is Considered as acceptable for further analysis mentioned in table 1 Table 1 Details of Cronbach coefficient values for reliability test Cronbach value consideration α >0.9 Represents Excellent α >0.8 Represents Good α >0.7 Represent Acceptable α >0.6 Represent Questionable α >0.5 Represents Poor α<0.4 Represents Unacceptable 2.3. RANKING METHOD The relative importance index method RII (2,3,4.5,6 ) was used to determine that industrial person’s opinion of the relative importance to the identified management factor which may affect the labour productivity. Using this formula the major significant factors was identified. The RII was computed as, RII= ∑ W ∕ A* N……………………………...equation 1 Where, RII - Relative Importance Index, W = weighting given to each factor by the respondents (ranging from 0 to4) A = highest weight (i.e. 4) N = total number of respondents. 2.4. PARETO ANALYSIS Pareto analysis is a useful technique in the area where factors are acting in as complex nature. It estimates the benefits which are going to get on action which is to taken on factors and selects
  • 4. Assesement On Factors Declining Labour http://www.iaeme.com/IJCIET/index. those factors which would max benefit if action is taken maximum closely range .Pareto analysis is a better way of analyzing at root causes of problems, because it helps in improving thinking and structuring the thoughts in getting results. However, it is limited by its exclusion of possibly important problems which may be small initially, but will improve with time. This technique helps to identify the top factors which are needed to be considered to minimize the maximum of problems. Once the major causes are identified are used to identify the root causes of the problems. Pareto says that "80/20" rule, under the assumption that, in all situations, 20% of causes determine 80% of problems 3. RESULT AND DISCUSSIONS 3.1. DEMOGRAPHIC ANALYSIS consisting of factors from 5 different aspects namely labour, management, and efficiency, technical, external which will affect labour productivity. Totally 30 response was received out of 42 which are received manually and through mails As per mentioned in figure 1 a total of 30 respondents out of which 13 are project managers holding a 43% major in participation in the survey, and remaining4 where AEE,2 are EE,3 are senior engineers,2 are asst project man Figure 1 Details of respondents for demographic analysis Assesement On Factors Declining Labour Productivity In Construction Projects IJCIET/index.asp 343 editor@iaeme.com those factors which would max benefit if action is taken on those factors in getting the benefit in maximum closely range .Pareto analysis is a better way of analyzing at root causes of problems, because it helps in improving thinking and structuring the thoughts in getting results. However, it is exclusion of possibly important problems which may be small initially, but will improve with time. This technique helps to identify the top factors which are needed to be considered to minimize the maximum of problems. Once the major causes are identified are used to identify the root causes of the problems. Pareto says that "80/20" rule, under the assumption that, in all situations, 20% of causes determine 80% of problems7 . SIONS DEMOGRAPHIC ANALYSIS Survey (2,3,4,6 ) was conducted with preferred consisting of factors from 5 different aspects namely labour, management, and efficiency, technical, external which will affect labour productivity. Totally 30 response was received out of ived manually and through mails As per mentioned in figure 1 a total of 30 respondents out of which 13 are project managers holding a 43% major in participation in the survey, and remaining4 where AEE,2 are EE,3 are senior engineers,2 are asst project manager,4 are general manager,2 are asst general managers. Details of respondents for demographic analysis In Construction Projects editor@iaeme.com on those factors in getting the benefit in maximum closely range .Pareto analysis is a better way of analyzing at root causes of problems, because it helps in improving thinking and structuring the thoughts in getting results. However, it is exclusion of possibly important problems which may be small initially, but will improve with time. This technique helps to identify the top factors which are needed to be considered to minimize the maximum of problems. Once the major causes are identified, then tools are used to identify the root causes of the problems. Pareto says that "80/20" rule, under the was conducted with preferred questionnaire consisting of factors from 5 different aspects namely labour, management, and efficiency, technical, external which will affect labour productivity. Totally 30 response was received out of As per mentioned in figure 1 a total of 30 respondents out of which 13 are project managers holding a 43% major in participation in the survey, and remaining4 where AEE,2 are EE,3 are ager,4 are general manager,2 are asst general managers.
  • 5. Achuth Kumar N.V and SS.Asadi http://www.iaeme.com/IJCIET/index.asp 344 editor@iaeme.com Table 2 Experience of respondents in demographic analysis Serial NO EXPERIENCE IN YEARS NO OF RESPONDENT 1 0 - 10Y 2 2 10Y - 15Y 8 3 15Y - 20Y 7 4 ≥20Y 16 TOTAL 33 Respondents who are involved in survey has a vast experience in construction sector, according to the table 2 mentioned response who has major 13 persons out of 30 holding 43% having experience above 20 years and 2nd having 8 out of 30 holding 27% having experience 10-15 years, 3 rd having 7 out of 30 holding 23% having experience 15-20 years and 4 th least 2 out of 30 holding 7% having experience 0-10 years. 3.2. REABILITY TEST: Total 20 factors are considered as variables and reliability test is conducted in SPSS software 20 mentioned. Data from each component of questionnaire were tested for its Cronbach α value. To ensure that the collected data are valid and reliable for analysis (2,3,4,6 ). Table 3 shows values of Cronbach α in each category of the questionnaire data. The alpha values vary from of 0.70 to 0.80. This shows that data collected was acceptable and acknowledged as good. Thus, the reliability of collected data is assured. Certainly, this shows that the questionnaire data which is collected are valid and reliable. Table 3 Cronbach coefficient values of reliability test Component of data collected Cronbach α value Labour related 0.73 Management related 0.76 Efficiency related 0.75 Technical related 0.72 External related 0.76 3.3. RANKING METHOD Management factors as shown in table 4 which are driven from 5 category related factors, totally holding with 20 factors and to rank these factors RII was used and computed in Microsoft excel which are considered to be critical in ranking the factors which are causes for declination of labour productivity (2,3,4,6 ). As mentioned in table 4 the “lack of skilled labour” is major factor in declination 0f labour productivity with RII value 0.92 which are driven from efficiency related factors , reason is time completion of concern activity is increased due to less skill and knowledge and may lead repetitive corrections and wastage of resources,2 nd position was improper work schedule with RII value 0.833 from technical related factors because of which completion time of previous is not done and resource allocation to concern activity is not provided at time due to which productivity can reduced,3 rd position was malfunctioning of machinery with RII value 0.786 which to which time consumption of required activity get delayed or even postponed due to sudden breakdown of machine involved in activity and resource allocated to concern activity can be wasted and scheduled work gets disturbed which lead to critical path of activities and rest are shown in table 4
  • 6. Assesement On Factors Declining Labour Productivity In Construction Projects http://www.iaeme.com/IJCIET/index.asp 345 editor@iaeme.com Table 4 Ranking to factors affecting labour productivity Rank Factors affecting labour productivity Weight RII 1 lack of skilled labour 138 0.92 2 Improper work schedule 125 0.833 3 Malfunctioning of equipment 118 0.786 4 lack of experienced supervisors 116 0.773 5 Economical conditions 116 0.773 6 Poor communication between sub contractor and contractor 116 0.773 7 Incompetent technical staff 110 0.773 8 Truancy of work from labour 110 0.773 9 Negligence in providing general utilities 108 0.72 10 Repetitive works due to design faults 108 0.72 11 Delay due to numerical errors in design drawings 106 0.706 12 Unsuitable weather conditions 100 0.666 13 less crew size compared to estimated manpower 98 0.653 14 low wages compared with living standards 92 0.613 15 Safety violations 92 0.613 16 Negligence in incentive scheme providing to them 83 0.553 17 No job security 73 0.486 18 Work load 62 0.266 19 Disputes among labour 40 0.26 20 Social environment 39 0.413 3.4. PARETO ANALYSIS In order to regroup the disintegrated pattern of the factors obtained, Pareto analysis was applied. The data collected through survey and ranking is provided to them earlier which was shown in table 4 by taking those score in to consideration score percentage and cumulative percentage of data are calculated which was shown in table 5.Pareto Analysis are shown in Table 5 and illustrated in Figure 2 . The results of Pareto Analysis show that the first 14 factors contribute to about 80% of the weight of all the factors7 . These 14 factors can be considered as the most important factors affecting labour productivity. Lack of skilled labour would be major about 7% , improper work schedule with 6%,malfunctioning of equipment in total contribution of 100% as shown in figure 2.so to minimize the 80% of declination of labour productivity the primarily the 14 factors should be considered important and they should be nullified first to improve productivity . Table 5 Details regarding to Pareto analysis for factors affecting productivity Factors affecting labour productivity Weight Weight % Cumulative weight % lack of skilled labour 138 7.07 7.07 Improper work schedule 125 6.41 13.48 Malfunctioning of equipment 118 6.05 19.53 lack of experienced supervisors 116 5.948 25.478 Economical conditions 116 5.948 31.426 Poor communication between sub contractor and contractor 116 5.948 37.374 Incompetent technical staff 110 5.641 43.015 Truancy of work from labour 110 5.641 48.656 Negligence in providing general utilities 108 5.538 54.194 Repetitive works due to design faults 108 5.538 59.732 Delay due to numerical errors in design drawings 106 5.435 65.167 Unsuitable weather conditions 100 5.128 70.295 less crew size compared to estimated manpower 98 5.025 75.32
  • 7. Achuth Kumar N.V and SS.Asadi http://www.iaeme.com/IJCIET/index. Factors affecting labour productivity low wages compared with living standards Safety violations Negligence in incentive scheme providing to them No job security Work load Disputes among labour Social environment Figure 2 Details of Pareto analysis for factors affecting productivity 4. CASE STUDY Case study was considered to show the declination of labour productivity in execution at job site. The case study deals with housing complex with 5 construction buildings each building comprises of 5 floors with completion period about 2 years and about 280 labour was utilised to both skilled and unskilled per day. 4.1. COMPARISSION BETWEEN ACTUAL PRODU THERIOTICAL PRODUCTIVITY Basic definition of productivity is that work output for man labour productivity is calculated at job site conditionAs shown in figure 3 there are small variation in the activities for brick work and 12 mm plastering done at construction due skilled workers are utilised and also the transportation of and there are no objections from technical client depar more variation in productivity in the pouring of concrete activity regarding to activity concern with above foundation, pouring done manually because of less efficient labourer where utilised and Achuth Kumar N.V and SS.Asadi IJCIET/index.asp 346 editor@i actors affecting labour productivity Weight Weight % low wages compared with living standards 92 4.717 92 4.717 egligence in incentive scheme providing to them 83 4.256 73 3.743 62 3.179 40 2.051 39 2.017 Details of Pareto analysis for factors affecting productivity Case study was considered to show the declination of labour productivity in execution at job site. The case study deals with housing complex with 5 construction buildings each building comprises of 5 floors with completion period about 2 years and about 280 labour was utilised to both skilled COMPARISSION BETWEEN ACTUAL PRODUCTIVITY AND HERIOTICAL PRODUCTIVITY Basic definition of productivity is that work output for man-hour to concern activity, general the labour productivity is calculated at job site conditionAs shown in figure 3 there are small variation for brick work and 12 mm plastering done at construction due skilled workers are utilised and also the transportation ofrequired material are given without any delay by any source and there are no objections from technical client department regarding to drawings, but there is more variation in productivity in the pouring of concrete activity regarding to activity concern with above foundation, pouring done manually because of less efficient labourer where utilised and editor@iaeme.com Cumulative weight % 80.037 84.754 89.01 92.753 95.932 97.983 100 Details of Pareto analysis for factors affecting productivity Case study was considered to show the declination of labour productivity in execution at job site. The case study deals with housing complex with 5 construction buildings each building comprises of 5 floors with completion period about 2 years and about 280 labour was utilised to both skilled CTIVITY AND hour to concern activity, general the labour productivity is calculated at job site conditionAs shown in figure 3 there are small variation for brick work and 12 mm plastering done at construction due skilled workers are required material are given without any delay by any source tment regarding to drawings, but there is more variation in productivity in the pouring of concrete activity regarding to activity concern with above foundation, pouring done manually because of less efficient labourer where utilised and
  • 8. Assesement On Factors Declining Labour http://www.iaeme.com/IJCIET/index. vertical lifting is major affect in decline in productivity as compared concrete pouring below foundation level and mentioned in table 6. Table 5 Details regarding to Pareto analysis for factors affecting productivity Factors affecting labour productivity lack of skilled labour Improper work schedule Malfunctioning of equipment lack of experienced supervisors Economical conditions Poor communication between sub contractor and contractor Incompetent technical staff Truancy of work from labour Negligence in providing general utilities Repetitive works due to design faults Delay due to numerical errors in design drawings Unsuitable weather conditions less crew size compared to estimated manpower low wages compared with living standards Safety violations Negligence in incentive scheme providing to them No job security Work load Disputes among labour Social environment Figure 3 Comparison for labour productivity at site through case study Assesement On Factors Declining Labour Productivity In Construction Projects IJCIET/index.asp 347 editor@iaeme.com s major affect in decline in productivity as compared concrete pouring below foundation level and mentioned in table 6. Details regarding to Pareto analysis for factors affecting productivity actors affecting labour productivity Weight Weight % 138 7.07 125 6.41 118 6.05 116 5.948 116 5.948 oor communication between sub contractor and 116 5.948 110 5.641 110 5.641 egligence in providing general utilities 108 5.538 epetitive works due to design faults 108 5.538 elay due to numerical errors in design drawings 106 5.435 100 5.128 size compared to estimated manpower 98 5.025 low wages compared with living standards 92 4.717 92 4.717 egligence in incentive scheme providing to them 83 4.256 73 3.743 62 3.179 40 2.051 39 2.017 Comparison for labour productivity at site through case study In Construction Projects editor@iaeme.com s major affect in decline in productivity as compared concrete pouring below Details regarding to Pareto analysis for factors affecting productivity Cumulative weight % 7.07 13.48 19.53 25.478 31.426 37.374 43.015 48.656 54.194 59.732 65.167 70.295 75.32 80.037 84.754 89.01 92.753 95.932 97.983 100 Comparison for labour productivity at site through case study
  • 9. Achuth Kumar N.V and SS.Asadi http://www.iaeme.com/IJCIET/index.asp 348 editor@iaeme.com 5. CONCULSIONS • A questionnaire survey is conducted with 20 factors from 5 different categories and 78 % is achieved in return of 30 from 45 persons who had completed projects in overall country • The data which is collected had got reliability value from range 0.7 to 0.8 which is preferred as highly reliable source and allowed for further analysis • Lack of skilled labour is major factor which would affect the labour productivity with 0.92 RII value from technical related category • Improper work schedule is second among major factors affecting productivity with RII value 0.833 from technical related factors • Malfunctioning of equipment is 3rd position with RII value 0.786 which affecting Labour productivity considered from efficiency related factors • Efficiency related, technical related and management related are critical in reducing the damage about 80% in affecting the labour productivity • Pareto analysis is done among the 20 factors from 5 categories and results reveals that 14 factors shown in figure 2 are critical in minimizing the damage of labour Productivity about 80% REFERENCES [1] Mostafa E S, Khaled M E. Towards improving construction labour productivity and projects performance. Alexandria Engineering Journal. 2012 December; 50(4), 321–330. [2] Nithya k, Saravanan M M. Evaluation of factors improving jobsite productivity. Advanced Engineering and Applied Sciences: An International Journal. 2015 May; 5(2), 28-31. [3] Shashank K, Sutapa H, Kabindra NP. Analysis on key factors affecting the variation of labour productivity in construction projects. International Journal of Emerging Technology and Advanced Engineering. 2014 May; 4(5), 152-161. [4] Prakash Rao B , Ambika S, Prasad Babu N V. Labour productivity-analysis and ranking. International Research Journal of Engineering and Technology. 2015 June; 2(3), 151-155. [5] Absalom H V L. Factors Influencing Effective Productivity on Construction Sites in Nairobi County. International Journal of Soft Computing and Engineering. 2014 November; 4(5), 24- 30. [6] Hasan H, Nadine A. Enhancing Labour Productivity within Construction Industry through Analytical Hierarchy Process, the Case of Gaza Strip. Universal Journal of Management 2015; 3(8), 329-336. [7] Nikolayevich P I. Labor Activity Dynamics of Older Persons in the Far East of Russia. Indian Journal of Science and Technology. 2015 December; 8(10), 1-6. [8] D. Satish Chandra, SS. Asadi and M.V.S. Raju, Design of Web Based Decision Support System - Model Study of Vijayawada, A.P. International Journal of Civil Engineering and Technology, 7(6), 2016, pp.514–522. [9] G.S. Sarma, SS. Asadi and S. Lakshmi Narayana, Creation of Web Based Decision Support Information System for Evaluation of Topographic Characteristics Using Remote Sensing & GIS and Visual Basic Programe. International Journal of Civil Engineering and Technology, 7(6), 2016, pp. 621–634. [10] Yermek A B, Gulzhazira B M, Aliya K, Aigerim Z.Z, Elmira M M. Legal Regulation of Labor Migration in the Republic of Kazakhstan. Indian Journal of Science and Technology. 2016 Apr, 9(16), pp.1-5.