Best Practices of Using Cloud-based Virtual Technologies to Improve Management in West Coast Governments

Authors

  • Dr. Harvey Zack

DOI:

https://doi.org/10.53819/81018102t2411

Abstract

Improving project management in the government sector is a priority. Government agencies on the West Coast are actively adopting various technologies that can enable them to achieve project management goals. Despite the key role of cloud-based virtual technologies in providing a basis for improving project management, there is a persistent lack of consensus among information technology experts on the best practices for using cloud-based virtual technologies to improve project management. This study explored the consensus of information technology experts on the West Coast on best practices of using cloud-based virtual technologies to improve project management in West Coast governments. A Delphi technique was used, allowing for the collection of qualitative data from a purposive sample of a panel of 20 IT experts working on the West Coast. Data was collected in three cycles, consistent with the requirements of the Delphi technique. Data collected was transcribed and coded, followed by generating two themes. The two themes were developing user skills for project management personnel and effective compliance with data security standards, indicating the two best practices for using cloud-based virtual technologies to improve project management in West Coast government agencies. Based on the study findings, it was recommended that government agencies provide training opportunities for project staff to increase their knowledge of cloud-based virtual technologies for project management and emphasize compliance with data security standards.

Keywords: Cloud-based virtual technologies, project management, data security, West Coast government agencies.

References

Abd, T., Mezaal, Y. S., Shareef, M. S., Khaleel, S. K., Madhi, H. H., & Abdulkareem, S. F. (2019). Iraqi e-government and cloud computing development based on unified citizen identification. Periodicals of Engineering and Natural Sciences (PEN), 7(4), 1776-1793. http://dx.doi.org/10.21533/pen.v7i4.840

Agrawal, S. (2021). A survey on recent applications of Cloud computing in education: Covid-19 perspective. Journal of Physics: Conference Series, 1828(1). https://iopscience.iop.org/article/10.1088/1742-6596/1828/1/012076/meta.

Ahad, M. A., Paiva, S., Tripathi, G., & Feroz, N. (2020). Enabling technologies and sustainable smart cities. Sustainable cities and society, 61, 102301. https://doi.org/10.1016/j.scs.2020.102301

Ahmad, T., & Waheed, M. (2015). Cloud computing adoption issues and applications in developing countries: A Qualitative approach. Int. Arab. J. e Technol., 4(2), 84-93. https://www.researchgate.net/profile/Mehwish-Waheed/publication/283908626

Alashhab, Z. R., Anbar, M., Singh, M. M., Leau, Y. B., Al-Sai, Z. A., & Alhayja’a, S. A. (2021). Impact of coronavirus pandemic crisis on technologies and cloud computing applications. Journal of Electronic Science and Technology, 19(1), 100059. https://doi.org/10.1016/j.jnlest.2020.100059

Alassafi, M. O., Alharthi, A., Walters, R. J., & Wills, G. B. (2016). Security risk factors that influence cloud computing adoption in Saudi Arabia government agencies. In 2016 International Conference on Information Society (i-Society) (pp. 28-31). IEEE. 10.1109/i-Society.2016.7854165

Alcivar, I., & Abad, A. G. (2016). Design and evaluation of a gamified system for ERP training. Computers in Human Behavior, 58, 109-118. https://doi.org/10.1016/j.chb.2015.12.018

Allan, G. (2020). Qualitative research: Handbook for research students in the social sciences. Routledge.

Alsaffar, A. A., Pham, H. P., Hong, C. S., Huh, E. N., & Aazam, M. (2016). An architecture of IoT service delegation and resource allocation based on collaboration between fog and cloud computing. Mobile Information Systems, 1-15. https://doi.org/10.1155/2016/6123234

Angeles, R. (2014). A decision support system-driven system uses the technology-organization-environment framework to analyze Nike's Considered Index green initiative. J. Mgmt. & Sustainability, 4, 96. DOI: 10.5539/jms.v4n1p96.

Araral, E. (2020). Why do cities adopt smart technologies? Contingency theory and evidence from the United States. Cities, 106, 102873. https://doi.org/10.1016/j.cities.2020.102873

Artem, K., Holoshchuk, R., Kunanets, N., Shestakevysh, T., & Rzheuskyi, A. (2018, September). Information support of scientific research of virtual communities on the Platform of Cloud Services. In Conference on Computer Science and Information Technologies (pp. 301-311). Springer, Cham. https://link.springer.com/chapter/10.1007/978-3-030-01069-0_22

Baker, J. (2012). The technology–organization–environment framework. Information Systems Theory, 231-245. https://doi.org/10.1007/978-1-4419-6108-2_12

Bello, S. A., Oyedele, L. O., Akinade, O. O., Bilal, M., Delgado, J. M. D., Akanbi, L. A., ... & Owolabi, H. A. (2021). Cloud computing in construction industry: Use cases, benefits and challenges. Automation in Construction, 122, 103441. https://doi.org/10.1016/j.autcon.2020.103441

Bur, J. (2018). These tech problems could hurt the government for years. Federal Times. https://www.federaltimes.com/it-networks/2018/05/24/why-the-government-is-playingtechnology-catch-up/

Busetto, L., Wick, W., & Gumbinger, C. (2020). How to use and assess qualitative research methods. Neurological Research and practice, 2(1), 1-10. https://doi.org/10.1186/s42466-020-00059-z

Campbell, S., Greenwood, M., Prior, S., Shearer, T., Walkem, K., Young, S., & Walker, K. (2020). Purposive sampling: Complex or simple? Research case examples. Journal of Research in Nursing, 25(8), 652-661. https://doi.org/10.1177/1744987120927206

Cao, Q., & Jones, D. R., & Sheng, H. (2014). Contained nomadic information environments: technology, organization, and environmental influences on the adoption of hospital RFID patient tracking. Information & Management, 51(2), 225-239. https://doi.org/10.1016/j.im.2013.11.007

Caprolu, M., Di Pietro, R., Lombardi, F., & Raponi, S. (2019). Edge computing perspectives: architectures, technologies, and open security issues. In 2019 IEEE International Conference on Edge Computing (EDGE) (pp. 116-123). IEEE. https://ieeexplore.ieee.org/abstract/document/8473104

Chopdar, P. K., Korfiatis, N., Sivakumar, V. J., & Lytras, M. D. (2018). Mobile shopping apps adoption and perceived risks: A cross-country perspective utilizing the unified theory of acceptance and use of technology. Computers in Human Behavior, 86, 109-128. https://doi.org/10.1016/j.chb.2018.04.017

Chuttur, M. (2009). Overview of the technology acceptance model: Origins, developments, and future directions. https://aisel.aisnet.org/sprouts_all/290/

Clark, K. R., & Vealé, B. L. (2018). Strategies to enhance data collection and analysis in qualitative research. Radiologic technology, 89(5), 482CT-485CT. http://www.radiologictechnology.org/content/89/5/482CT.extract

Colander, D. C. (2014). Some government skin in the game: How to encourage new technology. Eastern Economic Journal, 40(2), 143-145. https://doi.org/10.1057/eej.2014.10

Correia, S. R. V., & Martens, C. D. P. (2023). Cloud computing projects: critical success factors. RAUSP Management Journal, 58, 5-21. https://doi.org/10.1108/RAUSP-06-2021-0107

Creswell, J.W. (2013). Educational research: Planning, conducting, and evaluating qualitative and quantitative research. Pearson Higher Education.

Ćwiklicki, M., & Pilch, K. (2021). Multiple case study design: The example of place marketing research. Place Branding and Public Diplomacy, 17(1), 50-62. https://doi.org/10.1057/s41254-020-00159-2

Daly, J. (2021). Why modernizing government technology was a necessity even before COVID-19. https://www.ibm.com/blog/federal-government-it-modernization-post-covid/

Daniel, B. K. (2019). Student experience of the maximum variation framework for determining sample size in qualitative research. In Proceedings of the European Conference on Research Methods for Business & Management Studies (pp. 92-100). https://doi.org/10.34190/rm.19.075

Deshko, I. P., Kryazhenkov, K. G., & Cheharin, E. E. (2016). Virtual technologies. modeling of artificial intelligence, 7(1), 33-43. https://doi.org/10.13187/mai.2016.9.33

Doelitzscher, F., Sulistio, A., Reich, C., Kuijs, H., & Wolf, D. (2011). Private cloud for collaboration and e-Learning services: from IaaS to SaaS. Computing, 91(1), 23-42. https://link.springer.com/article/10.1007/s00607-010-0106-z.

Duygan, M., Fischer, M., Pärli, R., & Ingold, K. (2022). Where do smart cities grow? The spatial and socio-economic configurations of smart city development. Sustainable Cities and Society, 77, 103578. https://doi.org/10.1016/j.scs.2021.103578

Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of convenience sampling and purposive sampling. American journal of theoretical and applied statistics, 5(1), 1-4. https://doi.org/10.11648/j.ajtas.20160501.11

Evans, M., & Farrell, P. (2021). Barriers to integrating building information modelling (BIM) and lean construction practices on construction mega-projects: A Delphi study. Benchmarking: An International Journal, 28(2), 652-669. https://doi.org/10.1108/BIJ-04-2020-0169

Gao, J. (2021). Level-based E-government cloud cross-domain access control technology. In 2021 20th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES) (pp. 53-56). IEEE. https://ieeexplore.ieee.org/abstract/document/9680393

Gill, S. H., Razzaq, M. A., Ahmad, M., Almansour, F. M., Ul Haq, I., Jhanjhi, N. Z., ... & Masud, M. (2022). Security and privacy aspects of cloud computing: a smart campus case study. Intelligent Automation and Soft Computing, 31(1), 117-128. https://doi.org/10.32604/iasc.2022.016597.

Habibi, A., Sarafrazi, A., & Izadyar, S. (2014). Delphi technique theoretical framework in qualitative research. The International Journal of Engineering and Science, 3(4), 8-13. https://parsmodir.com/wp-content/uploads/2018/11/Delphi2014-En.pdf

Hakizimana, G. W., & Muhe, M. (2019). Investigating challenges in the implementation of e-government services: A case of Rwanda. Umea University.

Irion, K. (2012). Government cloud computing and national data sovereignty. Policy & Internet, 4(3-4), 40-71. https://doi.org/10.1002/poi3.10

Kamal, S. A., Shafiq, M., & Kakria, P. (2020). Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM). Technology in Society, 60, 101212. https://doi.org/10.1016/j.techsoc.2019.101212

Khan, S., Al-Dmour, A., Bali, V., Rabbani, M. R., & Thirunavukkarasu, K. (2021). Cloud computing based futuristic educational model for virtual learning. Journal of Statistics and Management Systems, 24(2), 357-385. https://doi.org/10.1080/09720510.2021.1879468

Liang, Y., Wang, W., Dong, K., Zhang, G., & Qi, G. (2021). Adoption of mobile government cloud from the perspective of public sector. Mobile Information Systems, 2021, 1-20. https://www.hindawi.com/journals/misy/2021/8884594/

Mabry, P. L., Yan, X., Pentchev, V., Van Rennes, R., McGavin, S. H., & Wittenberg, J. V. (2020). CADRE: a collaborative, cloud-based solution for big bibliographic data research in academic libraries. Frontiers in big Data, 3, 556282. https://doi.org/10.3389/fdata.2020.556282

Meng, S., & Zhang, X. (2022). The Use of internet of things and cloud computing technology in the performance appraisal management of innovation capability of university scientific research team. Computational Intelligence and Neuroscience, 2022. https://doi.org/10.1155/2022/9423718

Miller, R. (2009). Obama tech team envisions federal cloud data center knowledge. https://www.datacenterknowledge.com/archives/2009/01/20/obama-tech-team-envisions-federal-cloud

Mohajan, H. K. (2018). Qualitative research methodology in social sciences and related subjects. Journal of Economic Development, Environment and People, 7(1), 23-48. https://doi.org/10.26458/jedep.v7i1.571

Nanos, I., Manthou, V., & Androutsou, E. (2019). Cloud computing adoption decision in E-government. In Operational Research in the Digital Era–ICT Challenges (pp. 125-145). Springer, Cham. https://link.springer.com/chapter/10.1007/978-3-319-95666-4_9.

Paquette, S., Jaeger, P. T., & Wilson, S. C. (2010). Identifying the security risks associated with governmental use of cloud computing. Government information quarterly, 27(3), 245-253. https://doi.org/10.1016/j.giq.2010.01.002

Pearson, S. (2013). Privacy, security and trust in cloud computing. Springer, London.

Priyadarshinee, P., Jha, M. K., Raut, R. D., & Kharat, M. G. (2018). To measure the business performance through cloud computing adoption in Indian scenario: structural equation modelling. International Journal of Business Information Systems, 28(4), 468-503. https://doi.org/10.1504/IJBIS.2018.093658

Rashid, Y., Rashid, A., Warraich, M. A., Sabir, S. S., & Waseem, A. (2019). Case study method: A step-by-step guide for business researchers. International journal of qualitative methods, 18, 1-13. https://journals.sagepub.com/doi/pdf/10.1177/1609406919862424

Schank, H. (2021). The government has a rare chance to modernize its outdated tech systems. they can’t afford to waste it. https://www.newamerica.org/the-thread/the-government-has-a-rare-chance-to-modernize-its-outdated-tech-systems-they-cant-afford-to-waste-it/

Sekaran, K., Khan, M. S., Patan, R., Gandomi, A. H., Krishna, P. V., & Kallam, S. (2019). Improving the response time of m-learning and cloud computing environments using a dominant firefly approach. IEEE Access, 7, 30203-30212. https://ieeexplore.ieee.org/abstract/document/8640814

Shafiq, N. M., & Shakor, M. Y. (2021). Cloud computing technologies adoption in higher education institutes during COVID-19 pandemic: Case study. Passer Journal of Basic and Applied Sciences, 3(2), 187-193. http://passer.garmian.edu.krd/

Shah, M. U., & Guild, P. D. (2022). Stakeholder engagement strategy of technology firms: A review and applied view of stakeholder theory. Technovation, 114, 102460. https://doi.org/10.1016/j.technovation.2022.102460

Shuib, L., Yadegaridehkordi, E., & Ainin, S. (2019). Malaysian urban poor adoption of e-government applications and their satisfaction. Cogent Social Sciences, 5(1), 1-18. https://doi.org/10.1080/23311886.2019.1565293

Silva, P. (2015). Davis' technology acceptance model (TAM)(1989). Information seeking behavior and technology adoption: Theories and trends, 205-219. https://www.igi-global.com/chapter/davis-technology-acceptance-model-tam-1989/127133

Takabi, H., Joshi, J. B., & Ahn, G. J. (2010). Security and privacy challenges in cloud computing environments. IEEE Security & Privacy, 8(6), 24-31. DOI: 10.1109/MSP.2010.186

Tang, N., Hu, H., Xu, F., & Zhu, F. (2019). Personalized safety instruction system for construction site based on internet technology. Safety science, 116, 161-169. https://doi.org/10.1016/j.ssci.2019.03.001

U.S. Government Accountability Office (2023). Outdated and old IT systems slow government and put taxpayers at risk. https://www.gao.gov/blog/outdated-and-old-it-systems-slow-government-and-put-taxpayers-risk

Utami, I. Q., Fahmiyah, I., Ningrum, R. A., Fakhruzzaman, M. N., Pratama, A. I., & Triangga, Y. M. (2022). Teacher's acceptance toward cloud-based learning technology in Covid-19 pandemic era. Journal of Computers in Education, 1-16. https://link.springer.com/article/10.1007/s40692-021-00214-8

Venkatesh, V., Davis, F., & Morris, M. G. (2007). Dead or alive? The development, trajectory and future of technology adoption research. Journal of the Association for Information Systems, 8(4), 267-286. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3681776

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 425-478. https://doi.org/10.2307/30036540

Wu, C., & Thompson, M. E. (2020). Sampling theory and practice. Cham: Springer.

Wyld, D. C. (2010). The cloudy future of government IT: Cloud computing and the public sector around the world. International Journal of Web & Semantic Technology, 1(1), 1-20. https://cloud.report/Resources/Whitepapers/4418a939-b318-4a75-85f9-c051a55a21d8_0101w1.pdf

Zhang, Y., & Sun, J., & Yang, Z., & Wang, Y. (2020). Critical success factors of green innovation: Technology, organization and environment readiness. Journal of Cleaner Production, 17(1-2), 30-58. https://doi.org/10.1016/j.jclepro.2020.121701

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Published

2024-06-06

How to Cite

Harvey, Z. (2024). Best Practices of Using Cloud-based Virtual Technologies to Improve Management in West Coast Governments. Journal of Information and Technology, 8(1), 98–120. https://doi.org/10.53819/81018102t2411

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