ARCOM

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Almashaqbeh, M and El-Rayes, K (2022) Minimizing transportation cost of prefabricated modules in modular construction projects. Engineering, Construction and Architectural Management, 29(10), 3847-67.

Alshboul, O, Shehadeh, A, Al-Kasasbeh, M, Al Mamlook, R E, Halalsheh, N and Alkasasbeh, M (2022) Deep and machine learning approaches for forecasting the residual value of heavy construction equipment: a management decision support model. Engineering, Construction and Architectural Management, 29(10), 4153-76.

Durdyev, S, Mohandes, S R, Mahdiyar, A and Ismail, S (2022) What drives clients to purchase green building?: The cybernetic fuzzy analytic hierarchy process approach. Engineering, Construction and Architectural Management, 29(10), 4015-39.

Egbelakin, T, Wilkinson, S, Potangaroa, R and Ingham, J (2011) Enhancing seismic risk mitigation decisions: a motivational approach. Construction Management and Economics, 29(10), 1003–16.

Ekanayake, E M A C, Shen, G, Kumaraswamy, M, Owusu, E K and Xue, J (2022) Capabilities to withstand vulnerabilities and boost resilience in industrialized construction supply chains: a Hong Kong study. Engineering, Construction and Architectural Management, 29(10), 3809-29.

Hee, C H S and Ling, F Y Y (2011) Strategies for reducing employee turnover and increasing retention rates of quantity surveyors. Construction Management and Economics, 29(10), 1059–72.

Hu, X, Hu, X, Cui, Q, Li, Y, Lemckert, C and Wei, A (2022) Spatial-temporal analysis for the business performance of construction consultancy services in China. Engineering, Construction and Architectural Management, 29(10), 3997-4014.

Igwe, C, Nasiri, F and Hammad, A (2022) An empirical study on non-physical waste factors in the construction industry. Engineering, Construction and Architectural Management, 29(10), 4088-106.

Khan, N A, Hui, Z, Khan, A N and Soomro, M A (2022) Impact of women authentic leadership on their own mental wellbeing through ego depletion: moderating role of leader's sense of belongingness. Engineering, Construction and Architectural Management, 29(10), 4191-214.

Larsen, G D (2011) Understanding the early stages of the innovation diffusion process: awareness, influence and communication networks. Construction Management and Economics, 29(10), 987–1002.

Ma, G, Jiang, S and Jia, J (2022) Investigating the adoption of social media in the construction industry: empirical evidence from project teams in China. Engineering, Construction and Architectural Management, 29(10), 3948-69.

Marzouk, M, Elsaay, H and Othman, A A E (2022) Analysing BIM implementation in the Egyptian construction industry. Engineering, Construction and Architectural Management, 29(10), 4177-90.

Mbachu, J (2011) Sources of contractor’s payment risks and cash flow problems in the New Zealand construction industry: project team’s perceptions of the risks and mitigation measures. Construction Management and Economics, 29(10), 1027–41.

Oladinrin, O T and Ojo, L D (2022) Characterisation of the drivers of environmental management system implementation. Engineering, Construction and Architectural Management, 29(10), 3868-92.

Olbina, S, Hinze, J and Arduengo, C (2011) Drug testing practices in the US construction industry in 2008. Construction Management and Economics, 29(10), 1043–57.

Rezaei Nasab, S S, Tayefi Nasrabadi, A, Asadi, S and Haj Seiyed Taghia, S A (2022) Investigating the probability of designing net-zero energy buildings with consideration of electric vehicles and renewable energy. Engineering, Construction and Architectural Management, 29(10), 4061-87.

• Type: Journal Article
• Keywords: electric vehicle; monte carlo simulation; net-zero energy buildings; reliability analysis; stochastic models
• ISBN/ISSN:
• URL: https://doi.org/10.1108/ECAM-05-2021-0448
• Abstract:
  Purpose: Due to technological improvement and development of the vehicle-to-home (V2H) concept, electric vehicle (EV) can be considered as an active component of net-zero energy buildings (NZEBs). However, to achieve more dependable results, proper energy analysis is needed to take into consideration the stochastic behavior of renewable energy, energy consumption in the building and vehicle use pattern. This study aims to stochastically model a building integrating photovoltaic panels as a microgeneration technology and EVs to meet NZEB requirements. Design/methodology/approach: First, a multiobjective nondominated sorting genetic algorithm (NSGA-II) was developed to optimize the building energy performance considering panels installed on the façade. Next, a dynamic solution is implemented in MATLAB to stochastically model electricity generation using solar panels as well as building and EV energy consumption. Besides, the Monte Carlo simulation method is used for quantifying the uncertainty of NZEB performance. To investigate the impact of weather on both energy consumption and generation, the model is tested in five different climatic zones in Iran. Findings: The results show that the stochastic simulation provides building designers with a variety of convenient options to select the best design based on level of confidence and desired budget. Furthermore, economic evaluation signifies that investing in all studied cities is profitable. Originality/value: Considering the uncertainty in building energy demand and PV power generation as well as EV mobility and the charging–discharging power profile for evaluating building energy performance is the main contribution of this study.

Saad, S, Alaloul, W S, Ammad, S and Qureshi, A H (2022) A qualitative conceptual framework to tackle skill shortages in offsite construction industry: a scientometric approach. Engineering, Construction and Architectural Management, 29(10), 3917-47.

Shooshtarian, S, Caldera, S, Maqsood, T, Ryley, T and Khalfan, M (2022) An investigation into challenges and opportunities in the Australian construction and demolition waste management system. Engineering, Construction and Architectural Management, 29(10), 4313-30.

Singla, H K and Sridharan, S (2022) Factors influencing the level of accuracy and compromise in overhead estimation for construction projects in India: an exploratory investigation. Engineering, Construction and Architectural Management, 29(10), 4040-60.

Tandon, U, Mittal, A, Bhandari, H and Bansal, K (2022) E-learning adoption by undergraduate architecture students: facilitators and inhibitors. Engineering, Construction and Architectural Management, 29(10), 4287-312.

Wan, X, Zhang, Y, Mao, P, Li, H, Wang, R, Yi, X and Zhao, X (2022) How perceived corporate social responsibility and public knowledge affect public participation intention: evidence from Chinese waste incineration power projects. Engineering, Construction and Architectural Management, 29(10), 4107-31.

Wang, Z, Liu, J and Guan, X (2022) Investigating the causal complexity of corruption in project-based organizations: a scenario analysis of bidding activity in the Chinese construction sector. Engineering, Construction and Architectural Management, 29(10), 3893-916.

Wilkins, J R (2011) Construction workers’ perceptions of health and safety training programmes. Construction Management and Economics, 29(10), 1017–26.

Yi, H (2022) 4D-printed parametric façade in architecture: prototyping a self-shaping skin using programmable two-way shape memory composite (TWSMC). Engineering, Construction and Architectural Management, 29(10), 4132-52.

Zhang, L, Yuan, J, Ning, Y, Xia, N and Zhang, G (2022) Enhancing the impacts of absorptive capacity on interorganizational collaboration in BIM-enabled construction projects – an SLT perspective. Engineering, Construction and Architectural Management, 29(10), 4215-40.

Zhang, Y, Wang, J, Ahmad, R and Li, X (2022) Integrating lean production strategies, virtual reality technique and building information modeling method for mass customization in cabinet manufacturing. Engineering, Construction and Architectural Management, 29(10), 3970-96.

Zhao, X and Pan, W (2022) The characteristics and evolution of business model for green buildings: a bibliometric approach. Engineering, Construction and Architectural Management, 29(10), 4241-66.