The Impact of E-Recruitment on Construction Recruitment and Data-Driven AI Advancements.

The construction industry has historically relied on traditional recruitment methods, such as job advertisements and referrals, to find qualified candidates.(Eckhardt et al., 2014)

However, the rise of e-recruitment has transformed the way construction firms approach talent acquisition (Abia & Brown, 2020).

E-recruitment offers a range of benefits, including reaching a broader pool of candidates, streamlining the application process, and gathering valuable data to drive future hiring decisions.

One of the key advantages of e-recruitment in the construction industry is the ability to reach a wider audience. By leveraging online platforms, construction firms can disseminate job postings more efficiently and effectively, allowing them to connect with a larger pool of potential candidates. This can be particularly beneficial in the construction industry, where specialized skills and experience are in high demand.

E-recruitment enables construction firms to collect and analyse data on candidate behaviour, preferences, and qualifications, which can inform future recruitment strategies and enhance the overall hiring process.(Mishra & Kumar, 2019)(Abia & Brown, 2020).

E-recruitment can also improve the candidate experience, allowing job seekers to apply for positions more conveniently and receive feedback more promptly.

Adopting e-recruitment in the construction industry has yielded several benefits, including increased flexibility, reduced costs, and improved company image.(Abia & Brown, 2020)

Despite these advantages, e-recruitment is not without its challenges. (Abia & Brown, 2020)One potential drawback is the risk of information overload, as the large volume of applications received through online platforms can be overwhelming for hiring managers (Abia & Brown, 2020).

The integration of artificial intelligence (AI) into e-recruitment systems can help address some of these challenges. AI-powered technologies, such as natural language processing (NLP) and machine learning, can automate the screening and sorting of applications, enabling construction firms to efficiently identify the most suitable candidates (Hemalatha et al., 2021).

As the construction industry continues to evolve, the impact of e-recruitment is likely to grow, with the potential for data-driven enhancements that can further streamline the recruitment process and improve the quality of hires (Mishra & Kumar, 2019)(Singh et al., 2020)(Jamil & Sopiah, 2022)(Abia & Brown, 2020).

References

1. Abia, M., & Brown, I. (2020, January 1). Conceptualizations of E-recruitment: A Literature Review and Analysis. Springer Science+Business Media, 370-379. https://doi.org/10.1007/978-3-030-45002-1_32

2. Eckhardt, A., Laumer, S., Maier, C., & Weitzel, T. (2014, May 27). The transformation of people, processes, and IT in e-recruiting. Emerald Publishing Limited, 36(4), 415-431. https://doi.org/10.1108/er-07-2013-0079

3. Hemalatha, A., Kumari, P., Nawaz, N., & Gajenderan, V. (2021, March 25). Impact of Artificial Intelligence on Recruitment and Selection of Information Technology Companies. https://doi.org/10.1109/icais50930.2021.9396036

4. Jamil, N A., & Sopiah, S. (2022, November 11). Analysis of Implementation E-Recruitment on HRM: Systematic Literature Review. European Organization for Nuclear Research. https://doi.org/10.5281/zenodo.7313382

5. Mishra, S., & Kumar, S P. (2019, January 1). Prospecting the enablers for adoption of e-recruitment practices in organisations: a proposed framework. Inderscience Publishers, 5(3), 235-235. https://doi.org/10.1504/ijewe.2019.103396

6. Singh, S., Jadhav, I., Waghmare, V., & Ramesh, R. (2020, July 31). ARTIFICIAL INTELLIGENT RECRUITMENT SYSTEM. IJEAST, 5(3), 241-244. https://doi.org/10.33564/ijeast.2020.v05i03.037