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Anjomshoa, E (2024) Key performance indicators of construction companies in branding products and construction projects for success in a competitive environment in Iran. Engineering, Construction and Architectural Management, 31(05), 2151-75.
Arora, M, Prakash, A, Mittal, A and Singh, S (2024) Examining the slow acceptance of HR analytics in the Indian engineering and construction industry: a SEM-ANN-based approach. Engineering, Construction and Architectural Management, 31(05), 1973-93.
- Type: Journal Article
- Keywords: artificial neural network (ANN); data availability; HR analytics; quantitative self-efficacy; structural equation modeling (SEM); technology adoption
- ISBN/ISSN:
- URL: https://doi.org/10.1108/ECAM-09-2021-0795
- Abstract:
Purpose: Despite the extensive benefits of human resource (HR) analytics, the intention to adopt such technology is still a matter of concern in the engineering and construction sectors. This study aims to examine the slow adoption of HR analytics among HR professionals in the engineering and construction sector. Design/methodology/approach: A cross-sectional online survey including 376 HR executives working in Indian-based engineering and construction firms was conducted. Hierarchal regression, structural equation modeling and artificial neural networks (ANN) were applied to evaluate the relative importance of HR analytics predictors. Findings: The results reveal that hedonic motivation (HM), data availability (DA) and performance expectancy (PE) influence the behavioral intention (BI) to use HR analytics, whereas effort expectancy (EE), quantitative self-efficacy (QSE), habit (HA) and social influence (SI) act as barriers to its adoption. Moreover, PE was the most influential predictor of BI. Practical implications: Based on the findings of this study, engineering and construction industry managers can formulate strategies for the implementation and promotion of HR analytics to enhance organizational performance. Originality/value: This study draws attention to evidence-based decision-making, emphasizing barriers to the adoption of HR analytics. This study also emphasizes the concept of DA and QSE to enhance adoption among HR professionals, specifically in the engineering and construction industry. © 2022, Emerald Publishing Limited.
Aslam, M, Baffoe-Twum, E and Malik, S (2024) Benchmarking lean construction conformance in Pakistan’s construction industry. Engineering, Construction and Architectural Management, 31(05), 2077-100.
Chan, I Y S and Chen, H (2024) Towards an integrative analysis of underground environment and human health: a survey and field measurement approach. Engineering, Construction and Architectural Management, 31(05), 1807-34.
Cole-Colander, C (2003) Designing the Customer Experience. Building Research & Information, 31(05), 357–66.
Cong, W, Zhang, S, Liang, H and Xiang, Q (2024) Impact of challenge and hindrance job stressors on informal safety communication of construction workers in China: the moderating role of co-worker relationship. Engineering, Construction and Architectural Management, 31(05), 2011-33.
Cooper, R, Bruce, M, Wootton, A, Hands, D and Daly, L (2003) Managing design in the extended enterprise. Building Research & Information, 31(05), 367–78.
Espinoza, D and Morris, J W F (2013) Decoupled NPV: a simple, improved method to value infrastructure investments. Construction Management and Economics, 31(05), 471-96.
Fazeli, A, Banihashemi, S, Hajirasouli, A and Mohandes, S R (2024) Automated 4D BIM development: the resource specification and optimization approach. Engineering, Construction and Architectural Management, 31(05), 1896-922.
Fellows, R and Liu, A M M (2013) Use and misuse of the concept of culture. Construction Management and Economics, 31(05), 401-22.
Gann, D M, Salter, A J and Whyte, J K (2003) Design Quality Indicator as a tool for thinking. Building Research & Information, 31(05), 318–33.
Ghansah, F A, Lu, W and Ababio, B K (2024) Modelling the critical challenges of quality assurance of cross-border construction logistics and supply chain during the COVID-19 pandemic. Engineering, Construction and Architectural Management, 31(05), 2128-50.
Gibson, E G and Gebken, R J (2003) Design quality in pre-project planning: applications of the Project Definition Rating Index. Building Research & Information, 31(05), 346–56.
Goh, Y M and Chua, D (2013) Neural network analysis of construction safety management systems: a case study in Singapore. Construction Management and Economics, 31(05), 460-70.
Guo, Y, Liu, J, Chen, C, Luo, X and Martek, I (2024) PPP project price mode typologies: a China-based comparative case study. Engineering, Construction and Architectural Management, 31(05), 2034-52.
Han, Y, Shen, J, Zhu, X, An, B and Bao, X (2024) Interaction mechanisms of interface management risks in complex systems of high-speed rail construction projects: an association rule mining-based modeling framework. Engineering, Construction and Architectural Management, 31(05), 2101-27.
Hansen, K L and Vanegas, J A (2003) Improving design quality through briefing automation. Building Research & Information, 31(05), 379–86.
Hu, Y, Song, J and Zhao, T (2024) Evolutionary game analysis of the intelligent upgrading of smart solar photovoltaic projects. Engineering, Construction and Architectural Management, 31(05), 1835-56.
Huang, W, Zhong, D and Chen, Y (2024) The relationship between construction workers’ emotional intelligence and safety performance. Engineering, Construction and Architectural Management, 31(05), 2176-201.
Li, H, Chen, Y, Zheng, J, Fang, Y, Yang, Y, Skitmore, M, Rusch, R and Jiang, T (2024) The influence of the psychological contract on the safety of performance of construction workers in China. Engineering, Construction and Architectural Management, 31(05), 1879-95.
Liao, L, Ye, Y, Wei, N, Li, H and Fan, C (2024) Exploring blockchain technology acceptance among non-managerial construction practitioners in Shenzhen, China. Engineering, Construction and Architectural Management, 31(05), 2053-76.
Odeyinka, H A, Lowe, J and Kaka, A P (2013) Artificial neural network cost flow risk assessment model. Construction Management and Economics, 31(05), 423-39.
Onubi, H O, Carpio, M and Hassan, A S (2024) Job satisfaction in green construction projects: antecedent roles of green work climate, pro-environmental construction practice and green human capital. Engineering, Construction and Architectural Management, 31(05), 1857-78.
Orr, S and Jadhav, A (2024) The effect of construction sustainability system interactions on financial performance: a sociotechnical perspective. Engineering, Construction and Architectural Management, 31(05), 1923-46.
Pinder, J, Iii, R S and Saker, J (2013) Stakeholder perspectives on developing more adaptable buildings. Construction Management and Economics, 31(05), 440-59.
Thomson, D S, Austin, S A, Devine-Wright, H and Mills, G R (2003) Managing value and quality in design. Building Research & Information, 31(05), 334–45.
Tiew, S Y (2024) Factors affecting performance of graduate architects in contract implementation management: a case study on housing projects in Malaysia. Engineering, Construction and Architectural Management, 31(05), 1789-806.
Wang, D, Luo, J and Wang, Y (2024) Multifactor uncertainty analysis of prefabricated building supply chain: qualitative comparative analysis. Engineering, Construction and Architectural Management, 31(05), 1994-2010.
Whyte, J K and Gann, D M (2003) Design Quality Indicators: work in progress. Building Research & Information, 31(05), 387–98.
Wu, X, Qian, Q and Zhang, M (2024) Impact of supervisor leadership on construction worker safety behavior in China: the moderating role of social capital. Engineering, Construction and Architectural Management, 31(05), 1947-72.