A comprehensive approach for assessing the causes of low productivity in the construction sector: a systematic categorization and ranking using Pareto and Fuzzy analysis

Figures & data

Figure 1. Origin and distribution of analyzed studies over the globe—130 studies (1991–2022)—heat map.

Table 1. Factors affecting construction productivity in different countries worldwide.

Studied country	Identified factors affecting the construction productivity in the country
Australia	(1) Lack of pre-planning, (2) inadequate incentives (financial bonuses), (3) poor site conditions, (4) insufficient pre-programming, and (5) poor management. (Doloi 2008)
New Zealand	(1) Poor investments, (2) poor management, (3) fewer competitions, (4) low economic scales, (5) lack of innovation and its problems in utilization (Durdyev and Mbachu 2011, Carson and Abbott 2012)
United States of America	(1) Inadequate experience and skill level of the workers, (2) poor job planning procedures, (3) incompetent management methods, (4) low motivation of the workforce, and (5) availability of material (inadequate) (Mojahed and Aghazadeh 2008)
Canada	(1) Quality of the structural and architectural drawings (inadequate), (2) readiness of working (shop) drawings (inadequate), (3) poor management on overtime (OT) and scheduling, (4) quality of supervisors being low, (5) poor operational sequence, (6) less competent management policies, and (7) change of orders (detrimental) (Hanna and Heale 1994)
Japan	(1) Safety protocols and aspects followed in working environments, adapting to workers’ ability over age, (2) labor quality (low), (3) capital input (insufficient), and (4) working hours (extended work) (Abdel-Wahab and Vogl 2011, Hashiguchi et al. 2020)
China	(1) Low quality in work and materials, (2) increased repetitive works, (3) higher community and construction densities, (4) lower scales in constructions (specifically apartment constructions resulting due to limited availability of land) (Charnes et al. 1978, Coelli et al. 2005, Xue et al. 2008)
United Arab Emirates	(1) Problems in drawings, (2) insufficient planning, (3) lack of management, (4) longer time on documentation and approvals, (5) lack of workforce, (6) less financial stability during the projects, (7) unavailability of resources and materials, (8) delays by authorities and government officials, (9) lack of skill level, (10) changes to the initial design (Faridi and El-Sayegh 2006, Jarkas and Radosavljevic 2013)
United Kingdom	(1) Methods of design (improper), (2) outdated methods of procurement, (3) improper methods of construction, (4) inadequate pre-planning, (5) poor site management, (6) poor resource management, (7) change of orders, (8) low number of workers, (9) skill level of workers (low), (10) lack of leadership, (11) lack of supervision, (12) insufficient job satisfaction levels, (13) lack of investments, (14) lack of innovation, (15) lack of technological utilization, (16) low wages, (17) safety issues, (18) nature of work (diverse), (19) problems in overtime, (20) environmental factors (restrictions) (Naoum 2016)
Singapore	(1) Information transfer delays, (2) lack of skills of laborers, (3) insufficient pre-planning, (4) delays by the authorities in following guidelines, (5) design changes, (6) the complexity of the design and project, (7) improper methods on work, (8) strict regulations, (9) lack of motivations by workers, (10) problems in communication (Tan 2000, Ofori et al. 2020)
Malaysia	(1) Shortage of material, (2) payment problems, (3) change of orders, (4) delays in construction drawings, (5) site management (poor), (6) lack of labor, (7) shortage of equipment, (8) problems in coordination, (9) reworks, (10) strict policies. (Abdul Kadir et al. 2005)
India	(1) Resource availability (inadequate), (2) problems in procurements, (3) inadequate clarity, (4) regular changes in design, (5) lack of coordination, (6) exclusive financial competence of managers, (7) labor strikes, (8) site clearance problems, (9) delay in payments, (10) capacity to handle unforeseen events by managers (poor). (Soham and Rajiv 2013, Dixit et al. 2019)

Figure 2. The proposed adaptive assessment approach for assessing and ranking factors leading to low construction productivity mitigating subjective biases.

Figure 3. Main research interest clusters using a co-occurrence network of keywords from the selected studies (130 studies).

Figure 4. Number of assessed factors in each region with cross-percentage comparison (915 factors, 130 studies) [205 (25)—Number of factors (Number of studies)].

Table 2. Summary of Pareto analysis carried over the introduced regions and benchmarks (number of identified factors—915).

Considered region/ benchmarked aspects	Labor- related factors	Material- related factors	Motivation- related factors	Equipment- related factors	Weather- related factors	Technology- related factors	Design- related factors	Management- related factors	Procurement process- related factors	Financial- related factors	Site condition- related factors	Safety- related factors	Project- related factors	Other	Total number of assessed parameters (without repetition)
Australia and New Zealand region	11	4	7	3	1	5	15	32	6	2	4	3	0	2	95
North American region	20	13	3	11	4	2	8	46	0	3	8	3	2	2	125
Eastern Asian/Russian region	10	3	0	1	0	1	3	16	0	2	0	4	1	2	43
Middle East region	57	14	5	8	12	4	14	59	2	7	2	2	8	11	205
European region	18	3	5	3	1	2	3	15	3	3	1	2	1	4	64
Southeast Asian region	29	12	6	8	1	1	10	37	6	21	3	1	2	3	140
South American region	0	1	1	2	0	0	0	1	0	1	0	0	0	0	06
African region	21	6	6	13	3	1	6	39	1	1	0	1	2	2	102
South Asian region	26	12	5	15	3	6	10	34	3	1	5	8	3	4	135
Number of times analyzed (without repetition)	192	68	38	64	25	22	69	279	21	41	23	24	19	30	915

Figure 5. Cross percentage comparison of assessed factors against introduced benchmarks (total—964 with repetition).

Table 4. Composition of the survey sent to evaluate the criticality and frequency of the identified factors leading to low construction productivity.

Primary benchmark of construction productivity (ID)	Number of subfactors	Primary benchmark of construction productivity (ID)	Number of subfactors
Management-related factors (M)	5	Financial-related factors (F)	5
Design-related factors (D)	5	Technology-related factors (T)	5
Material-related factors (M2)	5	Equipment-related factors (E)	5
Motivation-related factors (M3)	5	Safety-related factors (S)	5
Labor-related factors (L)	5	Site condition-related factors (S2)	5
Other (O)	3	Inputs by responders (R)	5
Total sub factors—58

Table 3. Composition of the respondents to the survey.

Respondents to the criticality and frequency assessment
Response group	Number of responses
Project managers	10
Engineers (senior and resident engineers)	41
Technical officers	33
Draughtmen	13
Laborers	20
Total responses	117
Respondents to the interdependence assessment
Response group	Number of responses
Project managers	10
Engineers (senior and resident engineers)	41
Total responses	51

Table 5. Analogy of the criticality and frequency of the employed survey.

Criticality assessment		Frequency assessment
Criticality grade	Rating	Frequency grade	Rating
Very critical	1	Very frequent	80–100%
Critical	2	Frequent	60–80%
Moderate	3	Moderate	40–60%
Less critical	4	Less frequent	20–40%
Not critical	5	Not frequent	00–20%

Table 6. Assigned numerical values for linguistic variables.

Criticality assessment		Frequency assessment
Criticality grade	Numerical value	Frequency grade	Numerical value
Very critical	6, 7	Very frequent	6, 7
Critical	5	Frequent	5
Moderate	4	Moderate	4
Less critical	2, 3	Less frequent	2, 3
Not critical	1	Not frequent	1

Figure 6. (a) Centroid (criticality assessment)—incompetent management team subfactor, (b) criticality fuzzy set—membership functions utilized in the analysis, (c) frequency fuzzy set—membership functions utilized in the analysis, (d) risk fuzzy set with results for incompetent management team sub factor [Risk Fuzzy value = (0,0,0.5,0.5,0), Crisp value—4.85)].

Table 7. Inference engine to map with fuzzy risk set.

Criticality inference		Frequency inference
Criticality grade	Risk grade	Frequency grade	Risk grade
Very critical	Extreme	Very frequent	Extreme
Critical	High	Frequent	High
Moderate	Moderate	Moderate	Moderate
Less critical	Less	Less frequent	Less
Not critical	Minor	Not frequent	Minor

Table 8. Ranking of the resulting factors through Fuzzy analysis (refer to Table 4 for ID).

Predominant causes for low construction productivity (results)	ID	Criticality fuzzy value (after inference)	Frequency fuzzy value (after inference)	Risk index	Rank within the benchmark	Overall rank
Incompetent management team	(M)	0, 0, 0.5, 0.5, 0	0, 0, 1, 0.3, 0	21.34	2	23
Number of rework and alterations	(M)	0, 0.41, 0.58, 0, 0	0, 0, 0.64, 0.63, 0	16.63	4	42
Poor site and resource management	(M)	0, 0, 0.4, 0.6, 0	0, 0, 1, 0.15, 0	21.56	1	22
Poor communications	(M)	0, 0.45, 0.45, 0, 0	0, 0, 0.42, 0.88, 0.22	16.32	5	44
Improper work delegations	(M)	0, 0, 0.46, 0.52, 0	0, 0.62, 0.70, 0, 0	17.70	3	37
Lack of skills	(L)	0, 0, 0.43, 0.58, 0	0, 0, 0.69, 0.66, 0	20.21	3	29
Poor labor management	(L)	0, 0.03, 0.97, 0, 0	0, 0, 1.0, 0.25, 0	17.55	4	38
Wages and incentives	(L)	0, 0, 0.37, 0.65, 0	0, 0, 0.19, 0.83, 0.50	27.73	2	10
Low labor morality	(L)	0, 0.02, 0.98, 0, 0	0, 0.22, 1.00, 0, 0	13.65	5	48
Lack of experience	(L)	0, 0, 0, 1, 0.37	0, 0, 0.2, 0.88, 0.5	35.99	1	04
Poor drawing management	(D)	0, 0, 0.83, 0.17, 0	0, 0.1, 1, 0, 0	16.43	4	43
Changes to design	(D)	0, 0.06, 0.94, 0	0, 0, 1, 0.2, 0	16.96	3	41
Design complexity	(D)	0, 0.37, 0.64, 0, 0	0, 0.78, 0.58, 0, 0	11.22	5	55
Communication delays between involved stakeholders	(D)	0, 0, 0.83, 0.185, 0	0, 0, 0.42, 0.92, 0.24	23.32	1	17
Incomplete and erroneous drawings	(D)	0, 0, 0.47, 0.55, 0	0, 0.18, 1.0, 0, 0	17.02	2	40
Lack of material (general)	(M2)	0, 0, 0.4, 0.6, 0	0, 0, 0.33, 1.0, 0.38	26.24	1	12
Inadequate material availability at the site	(M2)	0, 0, 0.22, 0.77, 0.08	0, 0.17, 1, 0, 0	19.61	3	30
Improper scheduling and delivery	(M2)	0, 0, 1, 0, 0	0, 0, 0.95, 0.42, 0	18.80	4	33
Poor material management	(M2)	0, 0, 0.81, 0.19, 0	0, 0, 0.82, 0.52, 0	23.50	2	15
Lack of storage facilities	(M2)	0, 0.18, 0.82, 0, 0	0, 0.51, 0.82, 0, 0	12.95	5	50
Lack of tools and equipment	(E)	0, 0, 0.24, 0.77, 0.08	0, 0, 0.72, 0.6, 0	22.36	1	20
Inadequate mechanization	(E)	0, 0.02, 0.98, 0, 0	0, 0, 0.86, 0.49, 0	18.24	4	34
Number of breakdowns	(E)	0, 0, 0.78, 0.21, 0	0, 0, 0.96, 0.42, 0	20.24	3	28
Lack of operators	(E)	0, 0, 0.36, 0.66, 0	0, 0, 1, 0.28, 0	21.15	2	25
Low suitability at the site	(E)	0, 0.6, 0.96, 0, 0	0, 0, 0.37, 1, 0.37	18.02	5	36
Lack of financial management of the project	(F)	0, 0, 0.72, 0.3, 0	0, 0, 0.77, 0.6, 0	22.56	3	19
Payment delays	(F)	0, 0, 0, 0.77, 0.57	0, 0, 0.1, 0.78, 0.58	34.22	1	05
External detrimental financial conditions (inflations, interest changes)	(F)	0, 0, 0.6, 0.41, 0	0, 0, 0.21, 0.87, 0.48	26.79	2	11
Financial status of owner/client	(F)	0, 0, 0.59, 0.41, 0	0, 0, 0.98, 0.38, 0	21.16	4	24
Capital input	(F)	0, 0, 0.71, 0.3, 0	0, 0.2, 1, 0, 0	17.16	5	39
Lack of motivation	(M3)	0, 0, 0.47, 0.43, 0	0, 0, 0.6, 0.76, 0.08	24.48	3	13
Incentives, turnover, rewards, overtime, and timeliness	(M3)	0, 0, 0, 0.6, 0.74,	0, 0, 0, 0.49, 0.83	37.51	1	03
Morality problems	(M3)	0, 0, 0.87, 0.14, 0	0, 0, 0.73, 0.62, 0	21.07	4	27
Inadequate welfare condition	(M3)	0, 0, 0.1, 0.89, 0.23	0, 0, 0.21, 0.88, 0.49	32.49	2	06
Changes of orders	(M3)	0.08, 0.77, 0.24, 0, 0	0, 0.6, 0.76, 0, 0	09.88	5	58
Technical literacy gap	(T)	0, 0.07, 0.96, 0, 0	0, 0, 0.58, 0.77, 0.09	19.57	3	31
Lack of technical utilizations	(T)	0, 0, 0.78, 0.22, 0	0, 0, 0.68, 0.71, 0.03	21.62	2	21
Lack of technology available	(T)	0, 0, 0.67, 0.35, 0	0, 0, 0.79, 0.58, 0	23.28	1	18
Lack of innovation	(T)	0, 0, 0.62, 0.4, 0	0.16, 0.8, 0.54, 0, 0	15.74	4	47
Inadequate investments in technology	(T)	0, 0.51, 0.5, 0, 0	0, 0.64, 0.68, 0, 0	11.90	5	53
Frequency of accidents	(S)	0, 0, 0.56, 0.48, 0	0, 0, 0.96, 0.4, 0	21.12	2	26
Poor safety plan and protocols	(S)	0, 0, 0.54, 0.29, 0	0, 0, 1, 0.26, 0	18.92	3	32
Poor health of workers	(S)	0, 0, 0, 0.52, 0.82	0, 0.2, 1, 0, 0,	23.89	1	14
Availability of safety training programs	(S)	0, 0, 0.51, 0.29, 0	0, 0.42, 0.91, 0, 0	11.55	5	54
Workers’ low commitment to safety	(S)	0, 0, 0.43, 0.58, 0	0, 0.3, 1, 0, 0	18.19	4	35
Poor site conditions	(S2)	0, 0.17, 0.84, 0, 0	0, 0, 1, 0.02, 0	15.77	2	46
Unforeseen ground conditions	(S2)	0, 0.16, 0.87, 0, 0	0, 0.62, 0.72, 0, 0	12.21	4	52
Environmental and surrounding factors	(S2)	0, 0.38, 0.62, 0, 0	0, 0, 0.57, 0.77, 0.1	16.00	1	45
Geographic location	(S2)	0, 0.4, 0.96, 0, 0	0, 0.2, 1, 0, 0	13.32	3	49
Project characteristics	(S2)	0, 0.605, 0.4, 0, 0	0.02, 0.72, 0.6, 0, 0	10.73	5	56
Weather (detrimental)	(O)	0, 0, 0, 0.84, 0.51	0, 0, 0, 0.4, 0.93	37.82	1	02
Procurement process	(O)	0, 0.68, 0.32, 0, 0	0, 0.49, 0.86, 0, 0	10.54	3	57
Project related factors	(O)	0.21, 0.89, 0.14, 0, 0	0, 0, 0.84, 0.51, 0	12.34	2	51
Political scenario	(R)	0, 0, 0, 0.4, 0.92	0, 0, 0, 0, 0.0.68	41.21	1	01
Priority of production in the industry	(R)	0, 0, 0.33, 0.68, 0	0, 0, 1, 0.36, 0	23.42	5	16
Traffic congestions	(R)	0, 0, 0, 0.82, 0.51	0, 0, 0.32, 0.98, 0.37	32.06	2	07
The contractor handles too many projects at the same time	(R)	0, 0, 0.36, 0.67, 0	0, 0, 0.22, 0.89, 0.45	27.84	4	09
Slow decision-making by owners	(R)	0, 0, 0, 0.57, 0.79	0, 0, 0.68, 0.68, 0	28.12	3	08

Figure 7. The introduced interdependence assessment approach.

Table 9. Positive results of the interdependence assessment (P—positive, N—negative).

Benchmark 1	Benchmark 2	Result (ATI, OD, TI)	Intervention
Labor	Management	P, N, P	Raise OD
Material	Motivation	N, N, P	Raise OD
Material	Project	P, N, N	Raise TI
Motivation	Management	P, N, N	Raise TI
Site Condition	Safety	P, N, N	Raise TI
Procurement	Project	P, N, P	Raise OD

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Data availability statement

The data supporting this study’s findings are available on request from the corresponding author, [Amila Premakumara].