Prediction of accessibility testing using a generalized linear model for e-government

Ahmad Althunibat, Wael Alzyadat, Siti Sarah Maidin, Adnan Hnaif, Basem Alokush

Article ID: 3520
Vol 8, Issue 7, 2024

VIEWS - 155 (Abstract) 100 (PDF)

Abstract


Using the United Nations’ Online Services Indicator (OSI) as a benchmark, the study analyzes Jordan’s e-government performance trends from 2008 to 2022, revealing temporal variations and areas of discontent. The research incorporates diverse testing strategies, considering technological, organizational, and environmental factors, and aligns with global frameworks emphasizing usability, accessibility, and security. The proposed model unfolds in three stages: data collection, performing data operations, and target selection using the Generalized Linear Model (GLM). Leveraging web crawling techniques, the data collection process extracts structured information from the Jordanian e-government portal. Results demonstrate the model’s efficacy in assessing accessibility and predicting web crawler behavior, providing valuable insights for policymakers and officials. This model serves as a practical tool for the enhancement of e-government services, addressing citizen concerns and improving overall service quality in Jordan and beyond.


Keywords


e-government; predict; accessibility; generalized linear model; accuracy; sustainable growth

Full Text:

PDF


References


Abdallah, M., Hammad, A., & AlZyadat, W. (2022). Towards a Data Collection Quality Model for Big Data Applications. Lecture Notes in Business Information Processing, 103–108. https://doi.org/10.1007/978-3-031-04216-4_11

Angelo, L., Nicola, M., Gabriele, C., & Alessandro, M. (2022). e-government in Europe. A Machine Learning Approach. Available online: https://mpra.ub.uni-muenchen.de/112242/ (accessed on 17 July 2022).

Abuaddous, H. Y. (2019). The Accessibility Diagnosis on Jordan E-Government Website. International Journal of Science and Applied Information Technology, 8(6), 45–48. https://doi.org/10.30534/ijsait/2019/05862019

Alexopoulos, C., Lachana, Z., Androutsopoulou, A., et al. (2019). How Machine Learning is Changing e-government. In: Proceedings of the 12th International Conference on Theory and Practice of Electronic Governance. https://doi.org/10.1145/3326365.3326412

Alhroob, A., Alzyadat, W., Tareq Imam, A., & M. Jaradat, G. (2020). The Genetic Algorithm and Binary Search Technique in the Program Path Coverage for Improving Software Testing Using Big Data. Intelligent Automation & Soft Computing, 26(4), 725–733. https://doi.org/10.32604/iasc.2020.010106

Alhroob, A., Alzyadat, W., Almukahel, I., & Altarawneh, H. (2020). Missing Data Prediction using Correlation Genetic Algorithm and SVM Approach. International Journal of Advanced Computer Science and Applications, 11(2). https://doi.org/10.14569/ijacsa.2020.0110288

Alhroob, A. M., Alzyadat, W. J., Almukahel, I. H., & Jaradat, G. M. (2020). Adaptive Fuzzy Map Approach for Accruing Velocity of Big Data Relies on Fireflies Algorithm for Decentralized Decision Making. IEEE Access, 8, 21401–21410. https://doi.org/10.1109/access.2020.2969204

Al-Mushayt, O. S. (2019). Automating E-Government Services With Artificial Intelligence. IEEE Access, 7, 146821–146829. https://doi.org/10.1109/access.2019.2946204

AL-Naimat, A. M. (2013). The Critical Success Factors for E-Government Implementation in Jordan. In: Proceedings of the 4th International Conference on Computing and Informatics, ICOCI 2013; Sarawak, Malaysia. pp. 391–398.

Al Olama, O. S. (2018). UAE National Strategy for Artificial Intelligence 2031. Available online: https://ai.gov.ae/wp-content/uploads/2021/07/UAE-National-Strategy-for-Artificial-Intelligence-2031.pdf (accessed on 12 December 2023).

Althunibat, A., Abdallah, M., Amin Almaiah, M., et al. (2022). An Acceptance Model of Using Mobile-government Services (AMGS). Computer Modeling in Engineering & Sciences, 131(2), 865–880. https://doi.org/10.32604/cmes.2022.019075

Althunibat, A., Alrawashdeh, T. A., & Muhairat, M. (2014). The Acceptance of Using M-government Services in Jordan. In: Proceedings of the 2014 11th International Conference on Information Technology: New Generations. https://doi.org/10.1109/itng.2014.65

Althunibat, A., Binsawad, M., Almaiah, M. A., et al. (2021). Sustainable Applications of Smart-Government Services: A Model to Understand Smart-Government Adoption. Sustainability, 13(6), 3028. https://doi.org/10.3390/su13063028

Althunibat, A., AlNuhait, H., Almanasra, S., et al. (2024). Culture and law enforcement influence on m-government adoption: An exploratory study. Journal of Infrastructure, Policy and Development, 8(5), 3353.

Althunibat, A., Alokush, B., Tarabieh, S. M., & Dawood, R. (2021). Mobile Government and Digital Economy Relationship and Challenges. International Journal of Advances in Soft Computing & Its Applications, 13(1).

Al Thunibat, A., Zin, N. A. M., & Sahari, N. (2011). Mobile government user requirements model. Journal of E-governance, 34(2), 104–111.

Almarashde, I., Althunibat, A., & Fazidah El, N. (2014). Developing a Mobile Portal Prototype for E-government Services. Journal of Applied Sciences, 14(8), 791–797.

Alrawashdeh, T., ElQirem, F., Althunibat, A., & Alsoub, R. (2021). A prioritization approach for regression test cases based on a revised genetic algorithm. Information Technology and Control, 50(3), 443–457.

Alrawashed, T. A., Almomani, A., Althunibat, A., & Tamimi, A. (2019). An automated approach to generate test cases from use case description model. Computer Modeling in Engineering & Sciences, 119(3), 409–425.

Almaiah, M., Al-Khasawneh, A., Althunibat, A., & Khawatreh, S. (2020). Mobile government adoption model based on combining GAM and UTAUT to explain factors according to adoption of mobile government services. International Journal of Interactive Mobile Technologies (iJIM), 14(03), 199–225. https://doi.org/10.3991/ijim.v14i03.11264

Alzyadat, W., Muhairat, M., Alhroob, A., & Rawashdeh, T. (2022). A Recruitment Big Data Approach to interplay of the Target Drugs. International Journal of Advances in Soft Computing and Its Applications, 14(1), 02–13. https://doi.org/10.15849/zujijasaca.220328.01

Assiri, H., Nanda, P., & Mohanty, M. (2021). A novel e-government Framework using Blockchain. Journal of Information Assurance & Cybersecurity, 1–14. https://doi.org/10.5171/2021.164568

Awwad, M. S., & Omoush, K. S. A. (2012). Governance of information technology-business relationship quality and performance outcomes. Electronic Government, an International Journal, 9(4), 350. https://doi.org/10.1504/eg.2012.049724

Bigdeli, A. Z., & de Cesare, S. (2011). Barriers to e-government Service Delivery in Developing Countries: The Case of Iran. Emerging Themes in Information Systems and Organization Studies, 307–320. https://doi.org/10.1007/978-3-7908-2739-2_24

Cabrera-Moya, D. R. R., Vasudevan, H., & Prieto-Rodriguez, G. (2023). Kash training models: increasing levels of commitment and organizational effectiveness. Business: Theory and Practice, 24(1), 239–249. https://doi.org/10.3846/btp.2023.17480

Charalabidis, Y., Lampathaki, F., Sarantis, D., et al. (2008). The Greek Electronic Government Interoperability Framework: Standards and Infrastructures for One-Stop Service Provision. In: Proceedings of the 2008 Panhellenic Conference on Informatics. https://doi.org/10.1109/pci.2008.37

Falco, E., Kleinhans, R. (2018). Beyond Information Sharing. A Typology of Government Challenges and Requirements for Two-Way Social Media Communication with Citizen. The Electronic Journal of e-government, 19(1), 32–45.

Forum, J. S. (2019). E-Government in Jordan a Guide for Policy Maker, 2019. Available online: https://jsf.org/sites/default/files/EN%20E-Government%20Report%20.pdf (accessed on 7 October 2022).

Fragkou, P., Galiotou, E., & Matsakas, M. (2014). Enriching the e-GIF Ontology for an Improved Application of Linking Data Technologies to Greek Open Government Data. Procedia—Social and Behavioral Sciences, 147, 167–174. https://doi.org/10.1016/j.sbspro.2014.07.141

Guberović, E., Alexopoulos, C., Bosnić, I., & Čavrak, I. (2022). Framework for Federated Learning Open Models in e-government Applications. Interdisciplinary Description of Complex Systems, 20(2), 162–178. https://doi.org/10.7906/indecs.20.2.8

Ismailova, R. (2015). Web site accessibility, usability and security: a survey of government web sites in Kyrgyz Republic. Universal Access in the Information Society, 16(1), 257–264. https://doi.org/10.1007/s10209-015-0446-8

Leogrande, A., Magaletti, N., Cosoli, G., & Massaro, A. (2022). E-Government in Europe. A Machine Learning Approach. Preprints, 2022, 2022020359. https://doi.org/10.20944/preprints202202.0359.v1

Linders, D., Liao, C. Z. P., & Wang, C. M. (2018). Proactive e-Governance: Flipping the service delivery model from pull to push in Taiwan. Government Information Quarterly, 35(4), S68–S76. https://doi.org/10.1016/j.giq.2015.08.004

Manoharan, A. P., & Ingrams, A. (2018). Conceptualizing E-Government from Local Government Perspectives. State and Local Government Review, 50(1), 56–66. https://doi.org/10.1177/0160323x18763964

Meiyanti, R., Utomo, B., Sensuse, D. I., & Wahyuni, R. (2018). e-government Challenges in Developing Countries: A Literature Review. In: Proceedings of the 2018 6th International Conference on Cyber and IT Service Management (CITSM). https://doi.org/10.1109/citsm.2018.8674245

Ministry of Digital Economy and Entrepreneurship, Amman (2019). Available online: https://www.modee.gov.jo/ebv4.0/root_storage/ar/eb_list_page/gws_2019-modee-v16_0-en.pdf (accessed on 25 May 2022).

Mujali Al-rawahna, A. S., Chen, S. C., & Hung, C. W. (2018). The Barriers of E-Government Success : An Empirical Study from Jordan. International Journal of Managing Public Sector Information and Communication Technologies, 9(2), 01–18. https://doi.org/10.5121/ijmpict.2018.9201

Norris, D. F., & Reddick, C. G. (2012). Local E‐Government in the United States: Transformation or Incremental Change? Public Administration Review, 73(1), 165–175. https://doi.org/10.1111/j.1540-6210.2012.02647.x

Osman, I. H., Anouze, A. L., Irani, Z., et al. (2014). COBRA framework to evaluate e-government services: A citizen-centric perspective. Government Information Quarterly, 31(2), 243–256. https://doi.org/10.1016/j.giq.2013.10.009

Robles, G., Gamalielsson, J., & Lundell, B. (2019). Setting Up Government 3.0 Solutions Based on Open Source Software: The Case of X-Road. Electronic Government, 69–81. https://doi.org/10.1007/978-3-030-27325-5_6

Twizeyimana, J. D., & Andersson, A. (2019). The public value of E-Government—A literature review. Government Information Quarterly, 36(2), 167–178. https://doi.org/10.1016/j.giq.2019.01.001

Zhang, H., Xu, X., & Xiao, J. (2014). Diffusion of e-government: A literature review and directions for future directions. Government Information Quarterly, 31(4), 631–636. https://doi.org/10.1016/j.giq.2013.10.013

Zuniga, F., Kozubowski, T. J., & Panorska, A. K. (2021). A generalized linear model for multivariate events. Journal of Computational and Applied Mathematics, 398, 113655. https://doi.org/10.1016/j.cam.2021.11365




DOI: https://doi.org/10.24294/jipd.v8i7.3520

Refbacks

  • There are currently no refbacks.


Copyright (c) 2024 Ahmad Althunibat, Wael Alzyadat, Siti Sarah Maidin, Adnan Hnaif, Basem Alokush

License URL: https://creativecommons.org/licenses/by/4.0/

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