Abstract
PurposeDespite 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/approachA 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.FindingsThe 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 implicationsBased 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/valueThis 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.
Subject
General Business, Management and Accounting,Building and Construction,Architecture,Civil and Structural Engineering
Reference68 articles.
1. Challenges and drivers for data mining in the AEC sector;Engineering, Construction and Architectural Management,2018
2. Attitudes and the attitude-behavior relation: reasoned and automatic processes;European Review of Social Psychology,2000
3. Determinants of user acceptance of electronic-HRM through the extension of UTAUT model via the structural equation modelling approach;Journal of Information and Knowledge Management (JIKM),2020
4. Factors affecting intention to use e-banking in Jordan;International Journal of Bank Marketing,2019
5. AIS in Australia: UTAUT application and cultural implication,2010
Cited by
7 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献