Abstract
The application of innovative technologies for advancing mobile workforce management often represents a considerable financial barrier, especially for small and medium enterprises. In this paper, we propose an on-demand and multi-tenancy cloud-based workforce management system utilizing state-of-the-art mobile and non-mobile technologies and vehicle routing methodologies. The prototype includes functionality to manage customer data, track and communicate with mobile workers, and to efficiently plan routes by solving vehicle routing problems with different metaheuristics in a highly scalable cloud environment using the Google App Engine. The cloud-based solution can be flexibly used “as a service” by different organizations and thus enables smaller enterprises to utilize innovative technologies for low variable expenses in order to improve their competitiveness. To the best of our knowledge, the proposed prototype is the first integrative approach to support the management of mobile workforces in the cloud. The generic architecture builds a foundation for implementing cloud-based real-time decision support and communication in other appropriate application areas.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Calheiros, R.N., Ranjan, R., Beloglazov, A., De Rose, C.A.F., Buyya, R.: CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Software: Practice and Experience 41(1), 23–50 (2011)
Caserta, M., Voß, S.: Workgroups diversity maximization: A metaheuristic approach. In: Blesa, M.J., Blum, C., Festa, P., Roli, A., Sampels, M. (eds.) HM 2013. LNCS, vol. 7919, pp. 118–129. Springer, Heidelberg (2013)
Golden, B., Raghavan, S., Wasil, E. (eds.): The Vehicle Routing Problem: Latest Advances and New Challenges, Operations Research/Computer Science Interfaces, vol. 43. Springer, New York (2008)
Heilig, L., Voß, S.: Decision analytics for cloud computing: a classification and literature review. In: Newman, A., Leung, J. (eds.) Tutorials in Operations Research – Bridging Data and Decisions, pp. 1–26. INFORMS, Catonsville (2014)
Heilig, L., Voß, S.: A scientometric analysis of cloud computing literature. IEEE Transactions on Cloud Computing 2(3), 266–278 (2014)
Heilig, L., Voß, S., Wulfken, L.: Building clouds: An integrative approach for an automated deployment of elastic cloud services. In: Chang, V., Walters, R., Wills, G. (eds.) Delivery and Adoption of Cloud Computing Services in Contemporary Organizations, IGI Global (to appear, 2015), doi:10.4018/978-1-4666-8210-8
Hevner, A.R., Chatterjee, S. (eds.): Design Research in Information Systems, Integrated Series in Information Systems, vol. 22. Springer, New York (2010)
Hevner, A.R., March, S.T., Ram, S.: Design science research in information systems research. MIS Quarterly 28(1), 75–105 (2004)
Lehmann, H., Kuhn, J., Lehner, F.: The future of mobile technology: Findings from a European Delphi study. In: Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS 2004), pp. 1–10 (2004)
Marston, S., Li, Z., Bandyopadhyay, S., Zhang, J., Ghalsasi, A.: Cloud computing – the business perspective. Decision Support Systems 51(1), 176–189 (2011)
Viehland, D., Yang, C.: Bringing the mobile workforce to business: A case study in a field service organization. In: International Conference on the Management of Mobile Business (ICMB 2007), pp. 39–44 (2007)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Heilig, L., Voß, S. (2015). A Mobile Cloud Workforce Management System for SMEs. In: Donnellan, B., Helfert, M., Kenneally, J., VanderMeer, D., Rothenberger, M., Winter, R. (eds) New Horizons in Design Science: Broadening the Research Agenda. DESRIST 2015. Lecture Notes in Computer Science(), vol 9073. Springer, Cham. https://doi.org/10.1007/978-3-319-18714-3_29
Download citation
DOI: https://doi.org/10.1007/978-3-319-18714-3_29
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-18713-6
Online ISBN: 978-3-319-18714-3
eBook Packages: Computer ScienceComputer Science (R0)