Abstract
Nowadays, one of the biggest concerns of industries all over the world is situations regarding absenteeism, since it has a great impact on the productivity and economy of companies, as well as on the health of their employees. The major causes of absenteeism appear to be work accidents and sickness leaves, which lead to the attempt by companies of understanding how the workload is related to the health of their collaborators and, consequently, to absenteeism. Thus, this paper proposes the design and development of a Web Application based on Business Intelligence indicators in order to help the health and human resources professionals of a Portuguese company analyse the relation between absenteeism and the health and lifestyle of employees, with the intention of concluding whether the work executed on the company is harming workers’ health. Furthermore, it is intended to discover the principal motives for the numerous and more frequent absences in this company, so that it is possible to decrease the absenteeism rate and, hence, improve the decision-making process. This platform will also provide higher quality healthcare and the possibility to find patterns in the absence of collaborators, as well as reduce time-waste and errors.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Aldana, S.G., Pronk, N.P.: Health promotion programs, modifiable health risks, and employee absenteeism. J. Occup. Environ. Med. 43(1), 36–46 (2001). https://doi.org/10.1097/00043764-200101000-00009
Blau, G.J., Boal, K.B.: Conceptualizing how job involvement and organizational commitment affect turnover and absenteeism. Acad. Manag. Rev. 12(2), 288–300 (1987). https://doi.org/10.5465/amr.1987.4307844
Gagnon, M.P., Desmartis, M., Labrecque, M., et al.: Systematic review of factors influencing the adoption of information and communication technologies by healthcare professionals. J. Med. Syst. 36(1), 241–277 (2012). https://doi.org/10.1007/s10916-010-9473-4
Esteves, M., Abelha, A., Machado, J.: The development of a pervasive web application to alert patients based on business intelligence clinical indicators: a case study in a health institution. J. Wirel. Netw., 1–7 (2019). https://doi.org/10.1007/s11276-018-01911-6. Springer
Alpuim, A., Esteves, M., Pereira, S., Santos, M.F.: Monitoring time consumption in complementary diagnostic and therapeutic procedure requests. In: Health Care Delivery and Clinical Science: Concepts, Methodologies, Tools, and Applications, pp. 1553–1579. IGI Global (2018). https://doi.org/10.4018/978-1-5225-3926-1.ch078
Negash, S., Gray, P.: Business intelligence. In: Handbook on Decision Support Systems 2. International Handbooks Information System, pp. 175–193. Springer, Berlin (2008). https://doi.org/10.1007/978-3-540-48716-6_9
Foshay, N., Kuziemsky, C.: Towards an implementation framework for business intelligence in healthcare. Int. J. Inf. Manag. 34(1), 20–27 (2014). https://doi.org/10.1016/j.ijinfomgt.2013.09.003
Reis, R., Mendonça, A., Ferreira, D.L.A., Peixoto, H., Machado, J.: Business intelligence for nutrition therapy. In: Healthcare Policy and Reform: Concepts, Methodologies, Tools, and Applications, pp. 459–474. IGI Global (2019). https://doi.org/10.4018/978-1-5225-6915-2.ch022
Esteves, M., Miranda, F., Machado, J., Abelha, A.: Mobile collaborative augmented reality and business intelligence: A system to support elderly people’s self-care. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S. (eds.) Trends and Advances in Information Systems and Technologies, WorldCIST 2018, vol. 747, pp. 195–204. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-77700-9_20
Mach, M.A., Abdel-Badeeh, M.S.: Intelligent techniques for business intelligence in healthcare. In: 2010 10th International Conference on Intelligent Systems Design and Applications, pp. 545–550. IEEE, Cairo (2010). https://doi.org/10.1109/isda.2010.5687209
Mettler, T., Vimarlund, V.: Understanding business intelligence in the context of healthcare. Health Inf. J. 15(3), 254–264 (2009). https://doi.org/10.1177/1460458209337446
Bansal, S.K.: Towards a semantic extract-transform-load (ETL) framework for big data integration. In: 2014 IEEE International Congress on Big Data, pp. 522–529. IEEE, Anchorage (2014). https://doi.org/10.1109/bigdata.congress.2014.82
Esteves, M., Miranda, F., Abelha, A.: Pervasive business intelligence platform to support the decision-making process in waiting lists. In: Next-Generation Mobile and Pervasive Healthcare Solutions, pp. 186–202. IGI Global (2018). https://doi.org/10.4018/978-1-5225-2851-7.ch012
Golfarelli, M., Maio, D., Rizzi, S.: Conceptual design of data warehouses from E/R schemes. In: Proceedings of the Thirty-First Hawaii International Conference on System Sciences, vol. 7, no. 1, pp. 334–343. IEEE, Kohala Coast (1998). https://doi.org/10.1109/hicss.1998.649228
Brandão, A., Pereira, E., Esteves, M., Portela, F., Santos, M., Abelha, A., Machado, J.: A benchmarking analysis of open-source business intelligence tools in healthcare environments. Information 7(4), 57 (2016). https://doi.org/10.3390/info7040057
Chaudhuri, S., Dayal, U., Narasayya, V.: An overview of business intelligence technology. Commun. ACM 54(8), 88–98 (2011). https://doi.org/10.1145/1978542.1978562
Olszak, C.M., Batko, K.: The use of business intelligence systems in healthcare organizations in Poland. In: 2012 Federated Conference on Computer Science and Information Systems (FedCSIS), pp. 969–976. IEEE, Wroclaw (2012)
Bonney, W.: Applicability of business intelligence in electronic health record. Procedia-Soc. Behav. Sci. 73, 257–262 (2013). https://doi.org/10.1016/j.sbspro.2013.02.050
Peffers, K., Tuunanen, T., Rothenberger, M.A., Chatterjee, S.: A design science research methodology for information systems research. J. Manag. Inf. Syst. 24(3), 45–77 (2007). https://doi.org/10.2753/mis0742-1222240302
Hevner, A., Chatterjee, S.: Design science research in information systems. In: Design Research in Information Systems. Integrated Series in Information Systems, vol. 22, pp. 9–22. Springer, Boston (2010). https://doi.org/10.1007/978-1-4419-5653-8_2
Facebook Inc. React – a JavaScript library for building user interfaces. https://reactjs.org/. Accessed 17 Aug 2019
Node.js. Introduction to Node.js. https://nodejs.dev/. Accessed 17 Aug 2019
Chart.js. Chart.js – simple yet flexible JavaScript charting for designers & developers. https://www.chartjs.org/. Accessed 18 Aug 2019
Express.js. Express.js – the fast, unopinionated, minimalist web framework for node. https://github.com/expressjs. Accessed 18 Aug 2019
Acknowledgements
This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2019.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Oliveira, S., Esteves, M., Cernadas, R., Abelha, A., Machado, J. (2020). The Development of a Business Intelligence Web Application to Support the Decision-Making Process Regarding Absenteeism in the Workplace. In: Rocha, Á., Ferrás, C., Montenegro Marin, C., Medina García, V. (eds) Information Technology and Systems. ICITS 2020. Advances in Intelligent Systems and Computing, vol 1137. Springer, Cham. https://doi.org/10.1007/978-3-030-40690-5_11
Download citation
DOI: https://doi.org/10.1007/978-3-030-40690-5_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-40689-9
Online ISBN: 978-3-030-40690-5
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)