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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.

• Type: Journal Article
• Keywords: business performance; China; construction consultancy services; data envelopment analysis; spatial-temporal analysis
• ISBN/ISSN:
• URL: https://doi.org/10.1108/ECAM-03-2021-0273
• Abstract:
  Purpose: This paper presents a developed spatial-temporal analysis framework for the case of investigating the business performance of construction consultancy services (CCS) in China. Design/methodology/approach: The spatial-temporal analysis is based on the data envelopment analysis (DEA) technique. The spatial analysis follows the DEA results under a contemporaneous benchmark technology and a virtual decision-making unit, consisting of ranking analysis, cluster analysis and variation analysis. The temporal analysis is reliant on the DEA results under a global benchmark technology and the time value of money, including trend analysis and driving force analysis containing pure technical and scale efficiency factors. Findings: Three CCS types in China are investigated, including engineering survey and design, construction supervision and procurement agency. The performance rank order and cluster classifications are mainly related to economic development levels. Engineering survey and design demonstrates the best performance and higher imbalances; however, construction supervision and procurement agency illustrate lower performance and imbalances. Scale efficiency significantly promotes business performance, whereas pure technical efficiency plays an inconspicuous role. Practical implications: The CCS promote technical efficiency by developing their service and innovation levels. The service of engineering survey and design registered in Beijing, Shanghai and Guangdong is recommended for entering the service market in China. Originality/value: The spatial-temporal analysis framework was developed, which is generic and provides a pathway to measure, compare and assess performance comprehensively. The CCS business performance is firstly measured.

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.

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.