111
Evaluating Professionals’ Perception of Risk factors Influencing Green Construction Projects in Nigeria
Hassan Adaviriku Ahmadu1, Rilwan Shuaib Abdulrahman2, Abdulrasheed Madugu Abdullahi3*, Mohammed Hassan Buratai4
1Department of Quantity Surveying, Faculty of Environmental Design, Ahmadu Bello University, Zaria, Nigeria
2Department of Quantity Surveying, Ahmadu Bello University, Zaria, Nigeria
3Department of Quantity Surveying, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor Malaysia
4Department of Quantity Surveying, Ahmadu Bello University, Zaria, Nigeria
Corresponding authors email: *[email protected], 1[email protected],
ABSTRACT
Buildings bring a plethora of benefits to society. However, they have a detrimental effect on society due to their high energy consumption, which often results in resource depletion, air pollution, and the generation of wastes that are difficult for the environment to absorb. To address these issues, developed countries have advocated for green buildings (GBs), which pose a less environmental risk. While numerous efforts have been made to identify and assess risk factors affecting green buildings in developed countries, little evidence is available on assessing the perception of construction professionals on risk factors affecting green buildings in developing countries like Nigeria. In response to this knowledge gap, this study aims to evaluate the perception of construction professionals on risk factors affecting green projects, specifically green building (GB) projects in Nigeria.
Data were collected through a questionnaire purposively distributed to construction professionals (Architects, Builders, Engineers, and Quantity Surveyors). A sample size of 373 was derived using Krejcie and Morgan (1970), and a total of 137 correctly completed questionnaires were retrieved. Descriptive statistics and analysis of variance were used to analyze data from the retrieved questionnaires. The results showed that the professionals’ overall assessment of the risk factors having a high impact is: “construction accidents,” “inefficient communication and coordination,” and “labour and materials price fluctuations.”
The findings present differences in the perception of construction professionals (Architects, Builders, Engineers, and Quantity Surveyors) on risk factors affecting GBs and provide a basis for different project participants to implement appropriate risk management strategies according to their perceptions of risk importance.
Keywords: Green buildings, Energy efficient projects, Risk factors, Professionals, Nigeria.
BACKGROUND
With the increasing global concern for climate change, construction companies worldwide are moving towards green building (GB) projects to reduce the project's negative impacts (Hwang, Zhao & Lim, 2019).
According to Woolley (2000), the construction industry is the largest destroyer of the natural environment.
The sector consumes non-renewable resources, produces massive waste, and pollutes the air, water, and land (Wallabaun & Buerkin, 2003). This negativity brought about sustainable development to meet today's needs without compromising the future generation’s needs. Implementing GB initiatives provides many natural, economic, and social benefits, including reduction of the effects of global warming and climate change, energy and resource savings, and enhancing occupational health (Ahn, Pearce, Wang & Wang,
Received: 5 Mar, 2022 Reviewed 2 June, 2022 Accepted: 1 July, 2022
112
2013; Zhao, Hwang & Gao., 2016). GB practices, thus, offer an opportunity for sustainable development of the construction sector.
Recently, GBs have attracted so much attention leading to an apparent shift to green construction (Zuo
& Zhao, 2014). Most developed countries, for example, have started implementing environmental strategies and introducing new rules to shift from conventionally practiced building construction (Zhao, Hwang &
Gao, 2016). Already there are several worldwide GB rating systems which include but are not limited to:
Leadership in Energy and Environmental Design (LEED)-used in the United States, Building Research Establishment Environmental Assessment Method (BREEAM)-the oldest rating system created in 1990, Comprehensive Assessment System for Built Environmental Efficiency (CASBEE)-established in Japan (He, Kvan, & Liu, 2018; Ulubeyli and Kazanci, 2018). Overall, the global GB industry continues to multiply in a growing market, and green practices have become a requirement for project stakeholders who are environmentally conscious (Zhao et al., 2016).
Regardless of the size, nature, complexity, and place of execution, risks and uncertainties are inherent in all construction projects from initiation to completion and even during the constructed facility operation phase (Siraj & Fayek, 2016). However, GB projects are faced with even more challenges in terms of risks and uncertainties than conventional building projects as a result of achieving sustainability in addition to the traditional project objective of cost, time, quality, safety, and satisfaction (Zhao et al., 2016; Hwang, Shan, Phua and Chi, 2017a). In a bid to achieve sustainability, GBs adopts new approaches, techniques, complicated designs, technologies, and innovative materials (such materials may lack adequate testing or may have sustainability issues) that can cause significant confusion and unpredictable risks (Hwang et al., 2017a; Yang and Zou, 2014). These risks need to be managed appropriately. Otherwise, they will continue to serve as barriers hindering the implementation of green buildings (Qin et al., 2016). Researchers (Alamdari, Jabarzadeh, Samaon and Sanoubar, 2021; Hwang Shan and Supa’at, 2017b; Zhao et al., 2016;
Qin et al., 2016; Jinghui, Xuan, & Xin, 2012) have identified and assessed many risk factors that are known to affect GB projects with varied findings all over the world. Studies by Jinghui, Xuan, & Xin (2012) went further to use system dynamics to establish a risk identification feedback model for green building projects from the contractor's perspective to help the contractor identify key risk factors for green buildings. Also, Nguyen and Macchion (2022) developed a comprehensive risk assessment model for green building projects. In Nigeria, however, while efforts (Ebekozien, Ayo-odifiri, Nwaole, Ibeabuchi and Uwadia 2021;
Dalibi, Feng, Shuangqin, Sadiq, Bello and Danja, 2017; Komolafe, Oyewole and Kolawole, 2016) exist to assess GB attributes, factors hindering its adoption, as well as barriers to its implementation initiative, no evidence is available on assessing the perception of construction professionals on risk factors affecting GBs. Moreover, studies covering this subject matter were all conducted in developed countries (Nguyen and Macchion, 2022; Alamdari, Jabarzadeh, Samaon and Sanoubar, 2021; Hwang et al., 2017a; Zhao et al., 2016; Qin et al., 2016; Jinghui, Xuan, & Xin, 2012). Hence, this study seeks to identify and assess the critical risk factors affecting the GB project’s success in Nigeria.
113
RESEARCH METHODS Data collection
The study adopted a quantitative research approach wherein questionnaires were administered to construction professionals to obtain their quantitative insights regarding risk factors influencing green construction projects. Construction professionals whose insights/perceptions were elicited encompassed Architects, Builders, Engineers, and Quantity Surveyors. Green projects fall into several categories, including; renewable energy, energy efficiency, pollution prevention and control, environmentally sustainable management of living natural resources and land use, terrestrial and aquatic biodiversity, clean transportation, sustainable water, and wastewater management, green buildings, eco-efficient production technologies, and processes, etc. For this study, however, green building was the scope of green projects considered as it is the most common in Nigeria.
Essentially, the questionnaire doled out to obtain insights/perceptions of construction professionals was organized into two sections. The first section sought demographic information of respondents, which could picture how genuine and reliable a respondent’s response was. This information includes: the respondents’
profession, years of practice experience, professional registration status as well as academic qualifications of respondents. On the other hand, the second section of the questionnaire required respondents’ perceptions of the risk factors influencing the success of green construction projects. It comprised a synthesized list of risk factors shown in previous literature to influence construction projects, alongside a 0 to 5 Likert-type scoring scale. The synthesized list was based on a literature review shown in Table 2. Respondents were required to provide their perception with respect to the influence/impact each risk factor have on a green construction project’s success, using the 0 to 5 Likert type scoring scale provided (where: 0 = not applicable;
1 = very low; 2 = low; 3 = medium; 4 = high; and 5 = very high).
Based on a sample size of 373 professionals computed (from an aggregated sample population of 5655 construction professionals) using Krejcie and Morgan's (1970) sample size computation formula, the questionnaire was purposively administered to professionals in Kaduna, Abuja, and Lagos states of Nigeria via mails and distribution on construction sites. The purposive selection of the construction professionals was based on the assumption that not all construction professionals may have participated in/experienced a green construction project. Out of the 373 questionnaires distributed, a total of 137 correctly completed questionnaires were retrieved. The retrieved questionnaires represented a response rate of 37%. They were considered adequate for analysis, following the accepted norm of a 20 to 30 percent response rate in most construction industry postal questionnaire surveys (Akintoye and Fitzgerald, 2000; Odeyinka, Lowe, and Kaka, 2008). Of the retrieved sample, 36 (38.7%) were Architects, 39 (41.9%) were Quantity Surveyors, 29 (31.1%) were builders, and the remaining 33 (35.4%) were Engineers.
Data Analysis
Using Statistical Package for Social Sciences (SPSS), descriptive statistics, precisely, means, was used to rank the influence/impact of the risk factors. This was followed by testing for a significant difference in the perceptions of different categories of professionals considered in the study, using analysis of variance (ANOVA).
114
RESULTS AND DISCUSSION
Demographic Information of Respondents
Table 1 highlights demographic information of professionals that responded to the study’s questionnaire. It sheds light on how genuine and reliable the respondents’ responses were.
Table 1: Demographic Information of respondents Demographic information Frequency Percentage
Practice experience
0 to 5 14 10.22
6 to 10 21 15.33
11 to 15 60 43.80
16 to 20 29 21.17
Over 20 13 9.49
Academic qualification
HND 13 9.49
B.Sc./B.Eng./B.Tech. 76 55.47
M.Sc./M.Tech. 39 28.47
PhD 9 6.57
Professional qualification
Fellow membership 46 33.58
Full membership 77 56.20
Probational membership 14 10.22
As presented in Table 1, with regards to the practice experience of the professionals/respondents, only 9.49% of the professionals/respondents had over 20 years of practice experience. However, the majority (43.80%) had practice experience of 11 to 15 years, while 21.17% had practice experience of 16 to 20 years.
Approximately 25% had practice experience below ten years (6 to 10 years - 15.33% and 0 to 5 years – 10.22% majority (90.51%) of the professionals had an academic qualification ranging from a degree, an M.Sc. to a Ph.D. Likewise, the majority (89.78) of the professionals had professional qualifications that ranged from fellow membership to full membership of their respective professional bodies. Essentially, the large proportion of the professionals with several years of practice experience and high academic and professional qualifications indicates that knowledgeable/well-informed respondents responded to the study’s questionnaire; hence, the information provided in the questionnaire can be considered reliable.
115
Table 2: Identified Risk Factors influencing Green Construction Projects
S/N Risk Factors Source(s)
1 Construction accidents Loo et al. (2013); Hwang et al. (2013); El-Sayegh and Mansour (2015)
2 Inefficient communication and coordination
Hwang et al. (2013); El-Sayegh and Mansour (2015); Hwang et al. (2015); Nguyen et al. (2022)
3 Labour and materials price fluctuations
Hwang et al. (2013); Zhao, Hwang, and Yu (2013); Al-Sabah et al. (2014)
4 Delayed payments from clients Rafindadi et al. (2014); Zhao et al. (2016); Li et al. (2017) 5 Inaccurate cost estimation Qin et al. (2016).
6 Use of new construction methods and technology
Al-Sabah et al. (2014); Chien, Wu, & Huang (2014); El-Sayegh and Mansour (2015)
7 Unclear detailed design or specifications
Marques and Berg (2011); Al-Sabah et al. (2014); El-Sayegh and Mansour (2015); Nguyen et al. (2022)
8 Availability of equipment and materials
Aktas and Ozorhon (2015); Hwang et al. (2017a); El-Sayegh et al. (2018)
9 Technical complexity Al-Sabah et al. (2014); Chien, Wu, & Huang (2014); El-Sayegh and Mansour (2015)
10 Project teams without the
relevant knowledge El-Sayegh et al. (2018); Nguyen et al. (2022) 11 Variation in design Rebeiz (2012); Al-Sabah et al. (2014) 12 Constraint on labourer
employment El-Sayegh and Mansour (2015); Hwang et al. (2015) 13 Lack of management staff El-Sayegh et al. (2018)
14 Inadequate safety measures Afshari et al. (2013); Karakhan and Gambatese (2017) 15 Material and equipment
problems
Aktas and Ozorhon (2015); Hwang et al. (2017a); El-Sayegh et al. (2018)
16 Inexperienced sub-contractors El-Sayegh et al. (2018) 17 Intervention of clients El-Sayegh et al. (2018)
18 Poor design Marques and Berg (2011); Al-Sabah et al. (2014); El-Sayegh and Mansour (2015); Nguyen et al. (2022)
19 Currency exchange rate fluctuation
Hwang et al. (2017a); Hwang et al. (2017b); El-Sayegh et al.
(2018)
20 Increasing inflation rate Hwang et al. (2013); Zhao, Hwang, and Yu (2013); Al-Sabah et al. (2014)
21 Increasing tax rate Menassa (2011); Zhao et al. (2015); Zhao et al. (2016) 22 Unclear requirements of clients Hwang et al. (2017a); Nguyen et al. (2017); El-Sayegh et al.
(2018) 23 Delay in the issuance of
documents Hwang et al. (2013); El-Sayegh and Mansour (2015) 24 Poorly trained labourers El-Sayegh et al. (2018)
25 Complex planning approval and permit procedures
Hwang and Ng (2013); Darko and Chan (2017); El-Sayegh et al. (2018);
26 Unclear contract conditions for dispute resolution
Al-Sabah et al. (2014); El-Sayegh and Mansour (2015);
Nguyen et al. (2022) 27 Default in the supply of
materials, equipment, and plants
Aktas and Ozorhon (2015); Hwang et al. (2017a); El-Sayegh et al. (2018); Nguyen et al. (2022)
28 Unclear contract conditions for claims and litigations
Loo et al. (2013); Al-Sabah et al. (2014); El-Sayegh and Mansour (2015); Nguyen et al. (2022)
116
The Extent of Risk Occurrence in Green Construction Projects
Table 3 presents professionals’ perceptions of risk factors influencing green construction projects in Nigeria. It highlights thoughtful assessment by four categories of construction professionals (namely:
Architects, Quantity Surveyors, Builders, and Engineers) regarding the risk factors impacting the success of green construction projects in Nigeria.
Table 3: Professionals’ assessment of Risk factors influencing Green Construction Projects Risk Factors
Professionals’
overall assessment
Architect's assessment
Quantity Surveyor's assessment
Builder's assessment
Engineer's assessment Mean Rank Mean Rank Mean Rank Mean Rank Mean Rank Construction accidents 4.23 1 3.67 2 4.21 1 3.84 1 4.34 1 Inefficient communication and
coordination 4.23 1 3.51 8 3.43 11 3.56 7 3.44 8
Labour and materials price
fluctuations 4.02 3 3.64 5 3.64 6 3.53 8 3.98 5
Delayed payments from clients 3.67 4 3.64 5 3.82 4 3.6 4 4.25 2 Inaccurate cost estimation 3.67 4 3.67 2 3.76 5 3.46 11 3.71 6 Use of new construction
methods and technology 3.63 6 3.04 13 3.59 7 3.46 11 3.31 10 Unclear detailed design or
specifications 3.62 7 3.04 13 4.17 2 3.73 2 4.12 3
Availability of equipment and
materials 3.62 7 3.64 5 4.17 2 3.53 8 3.31 10
Technical complexity 3.45 9 3.46 9 3.46 10 3.63 3 3.31 10 Project teams without the
relevant knowledge 3.29 10 3.67 2 3.59 7 3.6 4 3.23 14
Variation in design 3.29 11 3.85 1 3.51 9 3.46 11 3.31 10 Constraint on labourer
employment 3.17 12 3.40 10 3.43 11 3.46 11 4.05 4
Lack of management staff 3.17 12 3.31 11 3.43 11 3.6 4 3.71 6 Inadequate safety measures 3.1 14 3.31 11 3.43 11 3.49 10 3.44 8 Material and equipment
problems 3.1 14 2.29 19 2.88 21 1.57 27 2.73 20
Inexperienced sub-contractors 3.1 14 1.67 27 2.88 21 3.46 11 2.57 22 Intervention of clients 3.04 17 2.29 19 2.98 16 1.73 24 2.97 18
Poor design 3.02 18 2.05 23 2.93 18 3.22 16 2.73 20
Currency exchange rate
fluctuation 3 19 1.67 28 2.58 25 1.13 28 1.55 27
Increasing inflation rate 2.92 20 2.29 19 2.58 25 2.67 21 1.78 26 Increasing tax rate 2.87 21 2.05 23 2.67 24 1.73 24 3.23 14 Unclear requirements of clients 2.55 22 2.92 16 2.88 21 3.22 16 3.16 16 Delay in the issuance of
documents 2.55 22 3.04 13 3.36 15 3.22 16 2.01 25
Poorly trained labourers 2.16 24 2.29 19 2 28 1.73 24 3.16 16
117 Complex planning approval and
permit procedures 2.01 25 1.93 26 2.35 27 2.67 21 2.97 18 Unclear contract conditions for
dispute resolution 1.95 26 2.05 23 2.93 18 2.67 21 2.57 22 Default in the supply of
materials, equipment, and plants 1.63 27 2.92 16 2.98 16 3.22 16 2.57 22 Unclear contract conditions for
claims and litigations 1.41 28 2.75 18 2.93 18 3.22 16 1.55 27
As shown in Table 3, based on risk factors with a mean score of 3 and above, the professionals’ overall assessment reveals that 19 out of 28 risk factors considered in the study rank moderate to high in their impact on green construction projects’ success in Nigeria. Specifically, construction accidents, inefficient communication, coordination, and labour and materials price fluctuations are high-risk factors. Those with moderate impact include delayed payments from clients, inaccurate cost estimation, use of new construction method and technology, unclear detailed design or specifications, availability of equipment and materials, technical complexity, project teams without relevant knowledge, variation in design, constraints on labourer employment, lack of management staff, and inadequate safety measures, material and equipment problems, inexperienced sub-contractors, intervention of clients, poor design and currency exchange rate fluctuation.
Construction accidents, inefficient communication and coordination, and labour and materials price fluctuations, emerging as risk factors with a high impact on green construction projects in Nigeria, are not surprising as the Nigerian construction industry has widely been reported to be prone to construction accidents. In addition, as rightly observed by (Oladapo, Aladegbaiye, and Aibinu, 2008), Nigeria's large size and geographical diversity are expected to provoke labour and material price fluctuations as well as inefficient communication and coordination.
Regarding the respective professionals’ perception, Architects consider variation in design to be the only risk factor with a high impact on green construction projects’ success in Nigeria. In contrast, construction accidents, inaccurate cost estimation, and project teams without relevant knowledge are the main risk factors that they consider to have a moderate impact on the success of green construction projects.
Quantity surveyors consider construction accidents, unclear detailed design or specifications, and availability of equipment and materials as risk factors that significantly impact a green construction project’s success. At the same time, delayed payments from clients and inaccurate cost estimation are the main risk factors that they consider to have a moderate impact. Similar to Quantity surveyors, Builders consider construction accidents and unclear detailed design or specifications to be risk factors with a high impact on the success of green construction projects.
Engineers consider construction accidents, delayed payments from clients, and unclear detailed design or specifications as risk factors that highly impact the success of green construction projects. In contrast, technical complexity, project teams without relevant knowledge, and delayed payments from clients are the main risk factors that they deem to have a moderate impact. At the same time, the constraint on labourer employment and labour and material price fluctuations are the main risk factors with moderate impact.
The foregoing difference in mean scoring of the respective professionals regarding their perception of the impact of risk factors on the success of green construction projects in Nigeria clearly illustrates the difference in mindset between the professionals. Even though ANOVA conducted at a 5% significance level shows that the supposed difference in mindset is insignificant. This is not surprising as researchers (Kishan, Bhatt, and Bhavsar, 2014; Agyakwa-Baah and Chileshe, 2010) have noted that at an individual level, a collection of psychological, social, institutional, and cultural factors such as safety climate, peer/community pressure, demographic and occupational characteristics influence risk perception.
118
Table 4: ANOVA of Professionals’ assessment of risk factors influencing in Green Construction Project
Sum of Squares df Mean Square F Sig.
Between Groups 1.65 3 0.55 1.169 0.325
Within Groups 50.783 108 0.47
Total 52.433 111
As shown in Table 4, the ANOVA results revealed that no statistically significant difference exists in the perception of the different categories of professionals (P>0.05) (0.325), suggesting a consensus in their scoring of the extent of risk factor influence/impact on green construction project’s success in Nigeria.
CONCLUSION
Green building projects have gained popularity in recent years due to the enormous benefits associated with energy conservation. However, little evidence is available on assessing the perception of construction professionals on risk factors affecting GBs. This study aimed to address this knowledge gap by conducting an empirical questionnaire survey to ascertain professionals' perceptions of the various risk factors affecting green building projects in Nigeria. The results showed that the professionals’ overall assessment of the risk factors having a high impact is: “construction accidents,” “inefficient communication and coordination,”
and “labour and materials price fluctuations.” This study is essential as it sheds light on professionals’
perception of risk factors affecting green buildings in Nigeria's construction industry and helps equip different project participants with better knowledge and understanding of potential risk factors regarding green buildings. The findings present the differences in perception of the influence of risk factors among professionals that would help them to implement appropriate risk management strategies according to their perceptions of risk impact.
It is hoped that by doing so, a concerted effort may be made to increase group cooperation and ultimately create a win-win situation for the project. As such, this study adds to the body of knowledge, and its findings benefit industry practitioners. The study's limitations include that the conclusions reached are indicative rather than definitive, as only 137 completed survey questionnaires were received and analyzed, and the study's scope was limited to Nigeria. It is recommended that additional research be conducted to compare the findings in Nigeria to those in developed countries where green building development is mature and refined.
REFERENCES
Afshari, H., Issa, M. H., & Peng, Q. (2013). Barriers to the design, construction, operation, and maintenance of green buildings: A state-of-the-art review. In Proceedings of CSCE Annual General Meeting and Conference.
Agyakwa-Baah, A., and Chileshe, N. (2010). Construction professionals’ perception of risk assessment and management practices: does length of service in the construction industry matter. In: Egbu, C. (Ed) Procs 26th Annual ARCOM Conference, 6-8 September 2010, Leeds, UK, Association of Researchers in Construction Management, 1219-1228.
Ahn, Y. H., Pearce, A. R., Wang, Y & Wang, G. (2013). Drivers and barriers of sustainable design and construction: The perception of green building experience. International Journal of Sustainable Building Technology and Urban Development. Vol. 4, pp. 35–45.
Akintoye, A., Fitzgerald, E. (2000). A survey of current cost estimating practices in the UK. Construction Management and Economics. 18(2), 161-172.
Aktas, B., & Ozorhon, B. (2015). Green building certification process of existing buildings in developing countries: cases from Turkey. Journal of Management in Engineering, 31(6), 05015002.
119
Alamdari, A.M., Jabarzadeh, Y., Samson, D. and Sanoubar, N. (2021), "Supply chain risk factors in green construction of residential mega projects – interactions and categorization," Engineering, Construction and Architectural Management, Vol. ahead-of-print No. Ahead-of-print.
https://doi.org/10.1108/ECAM-07-2021-0663
Al-Sabah, R., Menassa, C. C., & Hanna, A. (2014). Evaluating impact of construction risks in the Arabian Gulf Region from perspective of multinational architecture, engineering and construction firms.
Construction management and economics, 32(4), 382-402.
Chien, K. F., Wu, Z. H., & Huang, S. C. (2014). Identifying and assessing critical risk factors for BIM projects: Empirical study. Automation in construction, 45, 1-15.I
Dalibi, S.G., Feng, J.C., Shuangqin, L., Sadiq, A., Bello, B.S., and Danja, I.I. (2017). Hindrances to Green Building Developments in Nigeria’s Built Environment: “The Project Professionals’ Perspectives.” IOP Conference Series: Earth and Environmental Science, 2017, DOI:10.1088/1755-1315/63/1/012033.
Darko, A., & Chan, A. P. (2017). Review of barriers to green building adoption. Sustainable Development, 25(3), 167-179.
Ebekozien, A., Ayo-odifiri, S. O., Nwaole, A. N. C., Ibeabuchi, A. L., and Uwadia, F. E. (2021). Barriers in Nigeria’s public hospital green buildings implementation initiatives. Journal of Facilities Management, https://doi.org/10.1108.
El-Sayegh, S. M., & Mansour, M. H. (2015). Risk assessment and allocation in highway construction projects in the UAE. Journal of Management in Engineering, 31(6), 04015004.
El-Sayegh, S. M., Manjikian, S., Ibrahim, A., Abouelyousr, A., & Jabbour, R. (2018). Risk identification and assessment in sustainable construction projects in the UAE. International Journal of Construction Management, 21(4), 327-336.
He, Y., Kvan, T., Liu, M. (2018). How green building rating systems affect designing green. Build.
Environ. Vol. 133, pp. 19-31.
Hwang, B, Zhao, X., Lim, J. (2019). Job satisfaction of project managers in green construction projects Influencing factors and improvement strategies. Engineering, Construction, and Architectural management. Vol. 27, pp. 205-226.
Hwang, B. G., Shan, M., & Supa’at, N. N. B. (2017b). Green commercial building projects in Singapore:
Critical risk factors and mitigation measures. Sustainable cities and society, 30, 237-247.
Hwang, B. G., Shan, M., Phua, H., & Chi, S. (2017a). An exploratory analysis of risks in green residential building construction projects: The case of Singapore. Sustainability, 9(7), 1116.
Hwang, B. G., Zhao, X., & Gay, M. J. S. (2013). Public p, private partnership projects in Singapore: Factors, critical risks and preferred risk allocation from contractors' perspective. International journal of project management, 31(3), 424-433.
Hwang, B. G., Zhao, X., See, Y. L., & Zhong, Y. (2015). Addressing risks in green retrofit projects: The case of Singapore. Project Management Journal, 46(4), 76-89.
Jinghui, Q., Xuan, Q. & Xin, W. (2012). Risk Factor Identification and Risk Path Analysis of Green Building Projects. Construction Technology. Vol. 41, pp. 30-34.
Karakhan, A. A., & Gambatese, J. A. (2017). Integrating worker health and safety into sustainable design and construction: designer and constructor perspectives. Journal of Construction Engineering and Management, 143(9), 04017069.
Kishan, P., Bhatt, R., and Bhavsar, J., J. (2014). A Study of Risk Factors Affecting Building Construction Projects. International Journal of Engineering Research & Technology. 3(12), 831-835.
Komolafe, M.O., Oyewole, M.O. and Kolawole, J.T. (2016). “Extent of incorporation of green features in office properties in Lagos, Nigeria.” Smart and Sustainable Built Environment, Vol. 5 No. 3. Pp. 232- 260. https://doi.org/10.1108/SASBE-08-2015-0019.
Krejcie, R. V. & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological measurement.
Loo, S. C., Abdul-Rahman, H., & Wang, C. (2013). Managing external risks for international architectural, engineering, and construction (AEC) firms operating in Gulf Cooperation Council (GCC) states. Project Management Journal, 44(5), 70-88.
120
Marques, R. C., & Berg, S. (2011). Risks, contracts, and private-sector participation in infrastructure.
Journal of construction engineering and management, 137(11), 925-932.
Menassa, C. C. (2011). Evaluating sustainable retrofits in existing buildings under uncertainty. Energy and Buildings, 43(12), 3576-3583
Nguyen, H.D., and Macchion, L. (2022), "A comprehensive risk assessment model based on a fuzzy synthetic evaluation approach for green building projects: the case of Vietnam," Engineering, Construction, and Architectural Management, Vol. ahead-of-print No. Ahead-of-print.
https://doi.org/10.1108/ECAM-09-2021-0824
Nguyen, H. T., Skitmore, M., Gray, M., Zhang, X., & Olanipekun, A. O. (2017). Will green building development take off? An exploratory study of barriers to green building in Vietnam. Resources, Conservation and Recycling, 127, 8-20.
Odeyinka, H., Lowe, J., and Kaka, A. (2008). An evaluation of risk factors impacting construction cash flow forecast. Journal of Financial Management of Property and Construction. 13(1), 5-17.
Oladapo, A., Aladegbaiye, O., and Aibinu, A. (2008). The development of location adjustment factors for construction price estimating in Nigeria. Acta Structilia: Journal for the Physical and Development Sciences. Vol. 15, pp. 118-132.
Qin, X., Y., Mo & Jing, L. (2016). Risk perceptions of the life-cycle of green buildings in China. Journal of Cleaner Production, Vol. 126, pp 148-158.
Rafindadi, A. D. U., Mikić, M., Kovačić, I., & Cekić, Z. (2014). Global perception of sustainable construction project risks. Procedia-Social and Behavioral Sciences, 119, 456-465.
Rebeiz, K. S. (2012). Public-private partnership risk factors in emerging countries: BOOT illustrative case study. Journal of Management in Engineering, 28(4), 421-428.
Siraj, N. B. & Fayek, A. R. (2016). Fuzzy System Dynamics for Modeling Construction Risk Management.
Construction Research Congress, (1990), 2411–2421.
Ulubeyli, S., Kazanci, O. (2018). Holistic sustainability assessment of green building industry in Turkey.
J. Clean. Prod. Vol. 202, pp. 197-212
Wallbaum, H, and Buerkin, C. (2003). Concepts and Instruments for a Sustainable Construction Sector.
Industry and Environment: Sustainable Building and Construction. United Nations Environment Programme. Vol. 26, pp. 53-57.
Woolley, T. (Ed). (2000). Green Building: Establishing Principles. Ethics and the Built Environment.
Warwick Fox. Rutledge, London: pp. 44-56.
Yang, R.J., Zou, P.X.W. (2014). Stakeholder-associated risks and their interactions in complex green building projects: a social network model. Build. Environ. Vol. 73, pp. 208-222.
Zhao, X., Hwang, B. G., & Gao, Y. (2016). A fuzzy synthetic evaluation approach for risk assessment: a case of Singapore's green projects. Journal of Cleaner Production, 115, 203-213.
Zhao, X., Hwang, B. G., & See, Y. L. (2015). Green retrofit projects: risk assessment and mitigation. In Thirty-First Annual Conference 2015 September 7-9 (p. 125).
Zhao, X., Hwang, B. G., & Yu, G. S. (2013). Identifying the critical risks in underground rail international construction joint ventures: A case study of Singapore. International Journal of Project Management, 31(4), 554-566.
Zuo, J., Zhao, Z.Y., 2014. Green building research-current status and future agenda: a review. Renew.
Sustain. Energy Rev. Vol. 30, pp. 271-281.
