Cloud Inspired Human Resource Management Empowered with Fuzzy Inference System

Authors

  • Shama Sadaqat Lecturer, Management Sciences Department, University of South Asia, Raiwind Campus, Lahore, Punjab, Pakistan.
  • Safiullah Junejo MA Scholar, Faculty of Economics and Business, Universitas Islam International Indonesia, Indonesia.
  • Saba Anwar MA Scholar, International Business and Management, University of Bradford, UK.

DOI:

https://doi.org/10.56976/rjsi.v5i3.65

Keywords:

Human Resources Management, Cloud Inspired Human Resources Management, Information System, Cloud Computing, Fuzzy Logic

Abstract

Traditional Human Resource Management (HRM) systems face complications in managing various issues related to personnel, organization, salary, attendance, etc. Cloud Computing (CC) provides help in these business applications. This research proposes a Cloud-Inspired Human Resource Management Information System (CIHRMIS) employing a fuzzy logic system. The proposed CIHRMIS, in view of Fuzzy Logic, may help companies accomplish their HRM tasks proficiently, which in turn reduces the cost and increases managerial efficiency. Further, the Fuzzy Logic System performs adaptive activities, which can be used with multiterminal platforms operation, which supplements the application value of the system as well.

Author Biography

Saba Anwar, MA Scholar, International Business and Management, University of Bradford, UK.

 

 

References

Ahmad, N. (2015). MSc Project Title : Advancing HRMS with Cloud Computing (December).

Ajith, A. (2009). Rule-Based Expert Systems. Handbook for Measurement System Design. John Wiley and Sons.

Alshamaila, Y., Papagiannidis, S., & Li, F. (2013). Cloud computing adoption by SMEs in the northeast of England: A multi-perspective framework. Journal of Enterprise Information Management, 26(3), 250–275. https://doi.org/10.1108/17410391311325225

Asghar, A. (2018). Key role of multinational companies in Pakistan. Pakistan & Gulf Economist.

Avram, M. G. (2014). Advantages and Challenges of Adopting Cloud Computing from an Enterprise Perspective. Procedia Technology, 12, 529–534. https://doi.org/10.1016/j.protcy.2013.12.525

Berman, S. J., Kesterson-Townes, L., Marshall, A., & Srivathsa, R. (2012). How cloud computing enables process and business model innovation. Strategy and Leadership, 40(4), 27–35. https://doi.org/10.1108/10878571211242920

Brekis, E., Rozite, K., & Zuka, R. (2014). Meta-Analysis of Advantages And Concerns of Cloud Computing in Small Companies. the 8th International Days of Statistics and Economics. Prague.

Canos, L., & Liern, V. (2004). Some Fuzzy Models for Human Resource Management. International journal of Technology, Policy and Management, 291-308.

Domun, V., & Bheemul, H. (2019). Information Systems Design and Intelligent Applications (Vol. 862). Springer Singapore. https://doi.org/10.1007/978-981-13-3329-3

Erbes, J., Motahari Nezhad, H. R., & Graupner, S. (2012). The future of enterprise IT in the cloud. Computer, 45(5), 66–72. https://doi.org/10.1109/MC.2012.73

Garg, S. K., Versteeg, S., & Buyya, R. (2013). A framework for ranking of cloud computing services. Future Generation Computer Systems, 29(4), 1012–1023. https://doi.org/10.1016/j.future.2012.06.006

Heiser, J., & Nicolett, M. (2008). Assessing the Security Risks of Cloud Computing. Gartner Research, (June), 1–6. Retrieved from http://www.gartner.com/DisplayDocument?id=685308

Hoberg, P., Wollersheim, J., & Krcmar, H. (2012). The business perspective on cloud computing - A literature review of research on cloud computing. AMCIS 2012 Proceedings, 1–12. Retrieved from https://aisel.aisnet.org/amcis2012/proceedings/EnterpriseSystems/5

Iqbal, N. (2015). Oracle HRMS E-Business Migration to the Cloud Environment.

Leimeister, S., Böhm, M., Riedl, C., & Krcmar, H. (2010). The Business Perspective of Cloud Computing: Actors, Roles and Value Networks. 18th European Conference on Information Systems, 1–12. Retrieved from http://aisel.aisnet.org/ecis2010/56/

Li, L., & Pahlevanzadeh, B. (2021). Evaluation of the trust values among human resources in the enterprise cloud using an optimization algorithm and fuzzy logic. Kybernetes, 51(6), 2008–2029. https://doi.org/10.1108/k-04-2021-0280

Lima-Junior, F. R., & Carpinetti, L. C. R. (2020). An adaptive network-based fuzzy inference system to supply chain performance evaluation based on SCOR® metrics. Computers &Amp; Industrial Engineering, 139, 106191. https://doi.org/10.1016/j.cie.2019.106191

Lv, Z., Wang, Q., & Yang, Y. (2018). cloud computing management platform of Human Resource Based on Mobile Communication Technology.

Marston, S., Li, Z., Bandyopadhyay, S., Zhang, J., & Ghalsasi, A. (2011). Cloud computing - The business perspective. Decision Support Systems, 51(1), 176–189. https://doi.org/10.1016/j.dss.2010.12.006

Mell, P., & Grance, T. (2011). Certificate of registration - dried milk, why & whey protein. National Institute of Standard AndTechnology. https://doi.org/10.1136/emj.2010.096966

Misra, S. C., & Mondal, A. (2011). Identification of a company's suitability for the adoption of cloud computing and modelling its corresponding Return on Investment. Mathematical and Computer Modelling, 53(3–4), 504–521. https://doi.org/10.1016/j.mcm.2010.03.037

Moomal, A., & Masrom, M. (2015). ICT Development and Its Impact on e-Business and HRM Strategies in the Organizations of Pakistan. Journal of Advanced Management Science, 3(4), 344–349. https://doi.org/10.12720/joams.3.4.344-349

Núñez, D., Ferrada, X., Neyem, A., Serpell, A., & Sepúlveda, M. (2018). A User-Centered Mobile Cloud Computing Platform for Improving Knowledge Management in Small-to-Medium Enterprises in the Chilean Construction Industry. Applied Sciences, 8(4), 516. https://doi.org/10.3390/app8040516

Oliveira, T., Thomas, M., & Espadanal, M. (2014). Assessing the determinants of cloud computing adoption: An analysis of the manufacturing and services sectors. Information and Management, 51(5), 497–510. https://doi.org/10.1016/j.im.2014.03.006

Park, J. H., & Jeong, H. Y. (2013). Cloud computing-based jam management for a manufacturing system in a Green IT environment. Journal of Supercomputing, 69(3), 1054–1067. https://doi.org/10.1007/s11227-013-1007-7

Prasad, R. S. R., & Atukuri, V. R. (2012). Cloud Computing Technology for Effective e-Governance. International Journal of Computer Science and Information Technologies, 3(1), 3241–3244. Retrieved from http://www.ijcsit.com/docs/Volume 3/Vol3Issue1/ijcsit2012030159.pdf

Purohit, G. N., Jaiswal, M. P., & Pandey, S. (2012). Challenges Involved in Implementation of ERP on Demand Solution: Cloud Computing. International Journal of Computer Science Issues, 9(4), 481–489.

Ross, P., & Blumenstein, M. (2013). Cloud computing: The nexus of strategy and technology. Journal of Business Strategy, 34(4), 39–47. https://doi.org/10.1108/JBS-10-2012-0061

Samuel, O. W., Omisore, M. O., & Ojokoh, B. A. (2013). A Web Based Decision Support System Driven by Fuzzy Logic for the Diagnosis of Typhoid Fever, Expert System with Applications (ESWA). 40, pp. 4164-1-4171. Elsevier.

Sandu, R., & Gide, E. (2018). Technological, Organisational and Environmental (TOE) Factors that Influence the Adoption of Cloud Based Service SMEs in India. IEEE International Conference on Cloud Computing, CLOUD, 2018–July, 866–870. https://doi.org/10.1109/CLOUD.2018.00123

Singh , M., Kuldeep , T. S., & Srivastava, V. M. (2018). Cloud Computing Adoption Challenges in the Banking Industry. 2018 International Conference on Advances in Big Data, Computing and Data Communication Systems, icABCD 2018, (pp. 1-5).

Subashini, S., & Kavitha, V. (2011). A survey on security issues in service delivery models of cloud computing. Journal of Network and Computer Applications, 34(1), 1–11. https://doi.org/10.1016/j.jnca.2010.07.006

T, T., & M., S. (1985). Fuzzy Identification of Systems and its IApplication to Modeling and Control. IEEE Transaction System Man Cyber, 116-132.

Tabassam, S. (2017). Security and Privacy Issues in Cloud Computing Environment. Journal of Information Technology & Software Engineering, 7(5), 216.

Vinay, P. (2018). The Impact of Cloud Computing in Human Resource Management. Retrieved from https://www.techprevue.com

Wang, X. L., Wang, L., Bi, Z., Li, Y. Y., & Xu, Y. (2016). Cloud computing in human resource management (HRM) systems for small and medium enterprises (SMEs). International Journal of Advanced Manufacturing Technology, 84(1–4), 485–496. https://doi.org/10.1007/s00170-016-8493-8

Zhao, C., Xue, Y., & Niu, T. (2021). Enterprise human resource management index based on fuzzy system. Journal of Intelligent &Amp; Fuzzy Systems, 40(2), 3137–3146. https://doi.org/10.3233/jifs-189352

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Published

2023-06-30

How to Cite

Sadaqat, S., Junejo, S., & Anwar, S. (2023). Cloud Inspired Human Resource Management Empowered with Fuzzy Inference System. Research Journal for Societal Issues, 5(2), 409–427. https://doi.org/10.56976/rjsi.v5i3.65

Issue

Vol. 5 No. 2 (2023): RJSI

Section

Articles

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Copyright (c) 2023 Shama Sadaqat, Safiullah Junejo, Saba Anwar

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This work is licensed under a Creative Commons Attribution 4.0 International License.