| Literature DB >> 32526939 |
Elijah Frimpong Boadu1, Cynthia Changxin Wang1, Riza Yosia Sunindijo1.
Abstract
From both practical and theoretical perspectives, understanding the health and safety (H&S) implications of the characteristics and foundation upon which the construction industry in developing countries is built and operates is essential for H&S management within the industry. While many studies have provided evidence of factors affecting construction H&S in developing countries, none has fully considered the H&S implications of the industry's characteristics. The current study thus examined how the peculiar characteristics of the construction industry in developing countries impact on the industry's H&S management. Data were collected using questionnaire surveys from construction industry professionals in Ghana. Nine distinct characteristics were identified and ranked, as well as their relationships and statistical significance determined through correlation and analysis of variance (ANOVA), respectively. The findings showed that these characteristics of the construction industry in developing countries, particularly the lack of skilled and educated workforce, reliance on labour intensive methods and lack of single regulatory authority, present huge challenges to the management of H&S. Accordingly, this research recommended strategic interventions which are tailored towards the context of the industry's characteristics. With the construction industry in developing countries exhibiting similar characteristics, the findings of this research can serve as a framework for country-specific study. The study contributes to the broader H&S performance improvement research in developing countries by throwing light on the characteristics of the industry that pose challenges to H&S performance.Entities:
Keywords: characteristics; construction industry; developing countries; health and safety
Year: 2020 PMID: 32526939 PMCID: PMC7311985 DOI: 10.3390/ijerph17114110
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Occupational accident fatality rate for different countries.
| Country | AFRO * Region Such as Ghana | Australia | UK | France | Germany | USA |
|---|---|---|---|---|---|---|
| Accident fatality rate per 100,000 workers | 21.1 | 1.5 | 0.55 | 3.14 | 0.81 | 3.6 |
* Low- and middle-income countries of the African Region (AFRO). Sources: For AFRO regions such as Ghana [9], for Australia [14], for UK, France and Germany [15] and for the USA [16].
Profile of respondents.
| Quantity | Percentage (%) | |||
|---|---|---|---|---|
| 1 | Professional background | Engineering | 11 | 23.9 |
| Quantity Surveying | 7 | 15.2 | ||
| Architecture | 6 | 13.0 | ||
| Project Management | 7 | 15.2 | ||
| Occupational health and safety | 7 | 15.2 | ||
| Building Technology | 3 | 6.5 | ||
| Other | 5 | 10.9 | ||
| 2 | Years of work experience | 1–5 years | 2 | 4.4 |
| 6–10 years | 6 | 13.0 | ||
| 11–15 years | 18 | 39.1 | ||
| 16–20 years | 15 | 32.6 | ||
| Over 20 years | 5 | 10.9 | ||
| 3 | Type of organisation | Consultant | 13 | 28.3 |
| Contractor | 17 | 37.0 | ||
| Government institution | 11 | 23.9 | ||
| Supplier | 1 | 2.2 | ||
| Trade union/association | 3 | 6.5 | ||
| Others | 1 | 2.2 |
Total number of respondents = 46.
The extent to which characteristics of the construction industry in Ghana influence OHS management within the industry.
| S/n | Characteristics | Consultants | Contractors | Government Inst. | Overall | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Mean | Rank | Mean | Rank | Mean | Rank | Mean | Standard Deviation | Variance | Rank | Skewness | Kurtosis | ||
| 1 | Colonial Influence | 3.23 | 8 | 3.41 | 8 | 3.45 | 5 | 3.37 | 0.73 | 0.54 | 8 | −0.38 | −0.53 |
| 2 | Procurement system | 3.69 | 6 | 3.82 | 4 | 3.45 | 5 | 3.65 | 0.76 | 0.57 | 6 | 0.08 | −0.40 |
| 3 | Huge number of informal sector participation | 3.85 | 4 | 3.53 | 6 | 3.64 | 4 | 3.70 | 0.66 | 0.43 | 4 | 0.43 | −0.69 |
| 4 | Large number of small contractors | 3.77 | 5 | 3.71 | 5 | 3.45 | 5 | 3.70 | 0.58 | 0.34 | 4 | 0.19 | −0.54 |
| 5 | Fragmented industry | 2.54 | 9 | 3.29 | 9 | 3.00 | 9 | 2.98 | 0.77 | 0.59 | 9 | −0.26 | −0.49 |
| 6 | Lack of single regulatory authority | 3.92 | 3 | 3.94 | 3 | 4.09 | 2 | 4.00 | 0.63 | 0.39 | 3 | 0.00 | −0.35 |
| 7 | Reliance on labour intensive methods | 4.31 | 2 | 4.41 | 2 | 4.09 | 2 | 4.24 | 0.52 | 0.27 | 2 | 0.24 | −0.13 |
| 8 | Lack of skilled and educated workforce | 4.62 | 1 | 4.76 | 1 | 4.36 | 1 | 4.59 | 0.57 | 0.33 | 1 | −1.07 | 0.22 |
| 9 | Reliance on temporary labour force | 3.69 | 6 | 3.47 | 7 | 3.36 | 8 | 3.50 | 0.77 | 0.6 | 7 | 0.29 | −0.30 |
Number of respondents: Consultants = 13, Contractors = 17, Government institutions = 11, Overall = 46 (including Trade unions = 3, Suppliers = 1 and Others = 1); Note: 1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree and 5 = strongly agree.
Results of Welch ANOVA (robust tests of equality of means).
| Welch | Statistic * | df1 | df2 | Significance |
|---|---|---|---|---|
| CHA1 | 0.336 | 2 | 24.118 | 0.718 |
| CHA2 | 1.054 | 2 | 24.691 | 0.364 |
| CHA3 | 0.949 | 2 | 23.655 | 0.401 |
| CHA4 | 1.072 | 2 | 23.907 | 0.358 |
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| CHA6 | 0.227 | 2 | 23.250 | 0.799 |
| CHA7 | 2.368 | 2 | 24.763 | 0.115 |
| CHA8 | 1.889 | 2 | 23.970 | 0.173 |
| CHA9 | 0.674 | 2 | 23.583 | 0.519 |
* Asymptotically F distributed. Bold: Significantly different at 0.05 level.
Test for homogeneity of variances (based on means).
| CHA1 | CHA2 | CHA3 | CHA4 | CHA5 | CHA6 | CHA7 | CHA8 | CHA9 | |
|---|---|---|---|---|---|---|---|---|---|
| Levene Statistic | 0.825 | 5.351 | 1.908 | 0.036 | 1.311 | 1.371 | 11.933 | 0.438 | 0.921 |
| df1 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 2 |
| df2 | 38 | 38 | 38 | 38 | 38 | 38 | 38 | 38 | 38 |
| Sig. | 0.446 | 0.009 | 0.162 | 0.965 | 0.281 | 0.266 | 0.000 | 0.648 | 0.407 |
Games–Howell HSD multiple comparisons.
| Dependent Variable | (I) Type of Organisation | (J) Type of Organisation | Mean Difference (I–J) | Std. Error | Significance | 95% Confidence Interval | |
|---|---|---|---|---|---|---|---|
| Lower Bound | Upper Bound | ||||||
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| −1.469 | −0.042 |
| Gov’t Inst. | −0.462 | 0.337 | 0.374 | −1.309 | 0.386 | ||
| Contractors | Consultants |
| 0.282 |
| 0.042 | 1.469 | |
| Gov’t Inst. | 0.294 | 0.274 | 0.542 | −0.407 | 0.995 | ||
| Gov’t Inst. | Consultants | 0.462 | 0.337 | 0.374 | −0.386 | 1.309 | |
| Contractors | −0.294 | 0.274 | 0.542 | −0.995 | 0.407 | ||
*: Significantly different at 0.05 level.
Correlation results.
| Pearson’s Correlation | Experience | CHA1 | CHA2 | CHA3 | CHA4 | CHA5 | CHA6 | CHA7 | CHA8 | CHA9 | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Experience | Correlation | 1 | |||||||||
| Significance | |||||||||||
| CHA1 | Correlation | 0.105 | 1 | ||||||||
| Significance | 0.489 | ||||||||||
| CHA2 | Correlation | 0.036 | 0.192 | 1 | |||||||
| Significance | 0.814 | 0.201 | |||||||||
| CHA3 | Correlation | 0.222 | −0.037 | 0.093 | 1 | ||||||
| Significance | 0.137 | 0.805 | 0.538 | ||||||||
| CHA 4 | Correlation | −0.017 | 0.110 | 0.055 | −0.015 | 1 | |||||
| Significance | 0.913 | 0.466 | 0.715 | 0.922 | |||||||
| CHA5 | Correlation | −0.512 a | 0.247 | 0.024 | −0.187 | 0.228 | 1 | ||||
| Significance | 0.000 | 0.098 | 0.872 | 0.215 | 0.128 | ||||||
| CHA6 | Correlation | 0.213 | 0.427 a | 0.092 | 0.106 | 0.119 | 0.000 | 1 | |||
| Significance | 0.155 | 0.003 | 0.545 | 0.483 | 0.432 | 1.000 | |||||
| CHA7 | Correlation | −0.282 | 0.282 | 0.156 | −0.234 | 0.168 | 0.232 | −0.134 | 1 | ||
| Significance | 0.058 | 0.057 | 0.300 | 0.118 | 0.264 | 0.121 | 0.375 | ||||
| CHA8 | Correlation | 0.085 | 0.053 | −0.08 | 0.013 | 0.079 | −0.020 | 0.182 | 0.113 | 1 | |
| Significance | 0.575 | 0.727 | 0.595 | 0.934 | 0.603 | 0.893 | 0.227 | 0.456 | |||
| CHA9 | Correlation | −0.072 | −0.364 b | 0.037 | −0.215 | 0.048 | −0.202 | −0.180 | 0.136 | 0.171 | 1 |
| Significance | 0.635 | 0.013 | 0.807 | 0.152 | 0.751 | 0.178 | 0.232 | 0.369 | 0.255 | ||
a Correlation is significant at the 0.01 level (2-tailed); b Correlation is significant at the 0.05 level (2-tailed). CHA—Characteristics, for instance CHA1 = Colonial influence.