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A Proposed Road Map To Enhance E-Government Services: Kuwait Case Study

Volume 3 - Issue 12, December 2019 Edition
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Author(s)
Sayed Abdel Gaber, Bader Kazim
Keywords
KPI, Road map, e-government, Kuwait, data mining, sentiment analysis, statistical methods.
Abstract
Nowadays; key performance indicators (KPI) is considered to be an important factor to evaluate the organizational maturity level. Information and Communication Technology ICT is used as the backbone of the modern countries infrastructure. Kuwait aims to enhance the ICT services for citizens in order to increase citizen satisfaction. This couldn’t be reached without evaluating the existing services throughout defining KPIs. The main objective is to provide a solution to the e-government in Kuwait especially in the educational sector in order to facilitate and enhance the decision making process. This paper proposes a road map introduce KPIs measurements for the services in e-government. The proposed road map uses mission, vision, and objectives to define and measure KPIs. We used five key indicators which are loyalty, participation, productivity, communication, and satisfaction. A case study is implemented for the Ministry of Education (MOE) throughout using questionnaire with population with 291 participants. Data mining (DM), Sentiment Analysis (SA), and statistical methods used to analyze the results of the questionnaire which is near similar. The results show that; the clustering process indicates the degree of agreement regarding the predefined Key Result Indicators (KRIs) and based on three clusters reach 63.7% in participation, 64.2% for satisfaction, 65.2% for loyalty, 66.3% communication, and 63.7% for productivity. The sentiment analysis model shows the ability to predict correctly 86 positive reviews with 67.7% and 41 and 32.3% negative reviews. Regarding the statistical methods; after identifying mean, standard deviation and percent shows near values compared to the data mining (clustering) results 64% in participation, 64.8% for satisfaction, 66% for loyalty, 64.4% communication, and 65% for productivity. The results indicate that the output of the three methods of evaluation is near equivalent. This leads to an important implication which is although the excellent infrastructure of Information and Communication Technology (ICT), the proposed road map highlighted that the e-government services need to be enhanced. Enhancements may go through increasing training for teachers and students, developing modern schools, and developing long run educational policies and plans to the Kuwaiti citizens to cope with the tremendous advancements in the ICT sector.
References
[1] United Nations E-Government Survey 2016: E-Government in Support of Sustainable Development. https://publicadministration.un.org/egovkb/en-us/#.WVXTg9JEnZ4. Last visit: Dec. 2018

[2] https://publicadministration.un.org/egovkb/en-us/Data/Country-Information/id/90-Kuwait/dataYear/2016. Last visit: June 2017

[3] Jacques Warren. 2011. Key Performance Indicators – Definition and Action. White Paper. http://kwantyx.com/wp-content/uploads/AT_WP_KPI_EN.pdf. Last visit: Nov 2018

[4] Central Agency for Information Technology. 2016. Consolidated Kuwait National ICT Indicators Report. https://www.e.gov.kw/sites/kgoarabic/Forms/FinalConsolidatedEnglishReportSinglePages.pdf. Last visit: Jun 2018

[5] Parmenter, D. 2010. Key Performance Indicators (KPI): Developing, Implementing, and Using Winning KPIs, 2nd ed. John Wiley

[6] Tanković, Ana Čuić. "Defining strategy using vision and mission statements of croatian organizations in times of crisis. "Economic Research-Ekonomska Istraživanja 26.sup1 (2013): 331-342.

[7] Harshman, Carl L. "Mission-vision-values: Toward common definitions." viewed 2 (2006): 2018.

[8] Ilango Sivaraman, Dr, Ahmed Al Balushi, and D. H. Rao. "Developing Key Performance Indicators from Mission and Vision Statements of an Engineering College in Oman." Global Journal of Management And Business Research (2014).

[9] Hanover Research Council. 2010. Key Performance Indicators for Administrative Support Units (http://www.hanoverresearch.com). Last visit Dec. 2017

[10] Abdulazeez Boujarwah. 2006. E-Government in Kuwait: From Vision to Reality. Proceedings of iiWAS2006. http://unpan1.un.org/intradoc/groups/public/documents/unpan/unpan033591.pdf. Last visit: July 2018

[11] David Parmenter. 2007. Key Performance Indicators Developing, Implementing, and Using Winning KPIs. ISBN-13: 978-0-470-09588-1. John Wiley & Sons, Inc

[12] Folan, Paul, Jim Browne, and Harinder Jagdev. "Performance: Its meaning and content for today's business research." Computers in industry 58.7 (2007): 605-620.

[13] Saeidi, S.P., Sofian, S., Saeidi, P., Saeidi, S.P., and Saaeidi, S.A. (2015). How does corporate social responsibility contribute to firm financial performance? The mediating role of competitive advantage, reputation, and customer satisfaction. Journal of Business Research, 68(2), 341-350

[14] Majumdar, A. (2005). A model for customer loyalty for retail stores inside shopping malls - An Indian perspective. Journal of Services Research - Special Issue, December, 47-64.

[15] Le Roux, Abraham Albertus. Integrated customer experience management at the North–West University. Diss. North-West University, 2011.

[16] Oliver, R. L. (1999). Whence customer loyalty? Journal of Marketing. 63. 33–44.

[17] Le Feuvre, Meryl. Understanding stakeholder relationships in marketing the urban village. Diss. University of Manchester, 2011.

[18] Lee, J., Kim, H. J., & Ahn, M. J. (2011). The willingness of e-Government service adoption by business users: The role of offline service quality and trust in technology. Government Information Quarterly, 28(2), 222-230. doi: http://dx.doi.org/10.1016/j.giq.2010.07.007

[19] Alawneh, A., Al-Refai, H., & Batiha, K. (2013). Measuring user satisfaction from e-Government services: Lessons from Jordan. Government Information Quarterly, 30(3), 277-288. doi: http://dx.doi.org/10.1016/j.giq.2013.03.001

[20] Horst, M., Kuttschreuter, M., & Gutteling, J. M. (2007). Perceived usefulness, personal experiences, risk perception and trust as determinants of adoption of e-government services in The Netherlands. Computers in Human Behavior, 23(4), 1838-1852. doi: http://dx.doi.org/10.1016/j.chb.2005.11.003

[21] Panda, Bibhu Prasad, and Dillip K. Swain. "Effective Communications through e-Governance and e-Learning." Chinese Librarianship: an International Electronic Journal 27 (2009)

[22] Gauld, R., Goldfinch, S. and Horsburgh, S (2010). Do They Want It? Do They Use It? The “Demand-Side” of e-Government in Australia and New Zealand. Government Information Quarterly, 27, 177-186

[23] Mukumbareza, Caroline. Evaluating citizen satisfaction with the quality of e-government information services provided by Southern African Development Community governments. Diss. 2015.

[24] Malik, Babur Hayat, et al. "Evaluating Citizen e-Satisfaction from e-Government Services: A Case of Pakistan." European Scientific Journal, ESJ 12.5 (2016).

[25] Seifert, Jeffrey W., and Jongpil Chung. "Using E-Government to Reinforce Government—Citizen Relationships: Comparing Government Reform in the United States and China." Social Science Computer Review 27.1 (2009): 3-23.

[26] Cheng, Yu-Tien, Han-Hsin Chou, and Ching-Hsue Cheng. "Extracting key performance indicators (KPIs) new product development using mind map and Decision-Making Trial and Evaluation Laboratory (DEMATEL) methods." African Journal of Business Management 5.26 (2011): 10734.

[27] Zaki, Nesma M., Ahmed Awad, and Ehab Ezat. "Extracting accurate performance indicators from execution logs using process models." Computer Systems and Applications (AICCSA), 2015 IEEE/ACS 12th International Conference of. IEEE, 2015.

[28] Sumrit, Detcharat, and Pongpun Anuntavoranich. "Using DEMATEL method to analyze the causal relations on technological innovation capability evaluation factors in Thai technology-based firms." International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies 4.2 (2013): 81-103.

[29] Unilytics. 2016. 5 Steps to Actionable Key Performance Indicators. http://unilytics.com/wp-content/uploads/2016/07/5-Steps-to-Actionable-KPIs_.pdf. Last visit: May 2018

[30] Mical Maganda Agina. 2013. Adoption and Implementation Of Key Performance Indicators By Auditing Firms In Kenya In Their International Operations. A Research Project. University Of Nairobi

[31] Kaplan, Robert S., and David P. Norton. The balanced scorecard: translating strategy into action. Harvard Business Press, 1996.

[32] Intrafocus; 2014. Key Performance Indicators: Developing Meaningful KPIs. https://www.intrafocus.com/wp-content/uploads/2014/09/Developing-Meaningful-Key-Performance-Indicators-V7.pdf. Last visit: May 2018

[33] Dragana, Milan Velimirović, and Rade Stanković.. 2011. "Role and importance of key performance indicators measurement." Serbian Journal of Management 6.1: 63-72.

[34] Shahin, Arash, and M. Ali Mahbod. "Prioritization of key performance indicators: An integration of analytical hierarchy process and goal setting." International Journal of Productivity and Performance Management 56.3 (2007): 226-240.

[35] KPI Karta. 2015. KPIs and the Logic of Decision Making. White Paper. https://unilytics.com/wp-content/uploads/2016/06/White-Paper-KPIs-and-the-Logic-of-Decision-Making-Unilytics-website2.pdf Last visit: July 2018

[36] Ibrahim, Abdullah B., Wu Jing, and Da Wenge. "Key performance indicators supporting decision-making affecting Malaysian enterprise’ project performance in China." American Journal of Applied Sciences 7.2 (2010): 241.

[37] Sharma, B. & Dyer, P. (2009). An Investigation of Differences in Residents' Perceptions on the Sunshine Coast: Tourism Impacts and Demographic Variables. Tourism Geographies, Vol.11, No.2, pp.187-213.

[38] Veal, A.J. (2011). Research Methods for Leisure and Tourism: A practical guide. 4th edition. Harlow: Pearson Education.

[39] Carlo, V. 2009. Business Intelligence: Data Mining and Optimization for Decision Making, John Wiley & Sons, Ltd. ISBN: 978-0-470-51138-1

[40] Ibrahim, F., Abu Osman, N., Usman, J. Kadri, N. 2007. Comparison of Different Classification Techniques Using WEKA for Breast Cancer. IFMBE Proceedings vol.15. pp. 520-523.

[41] Grabmeier, J., Rudolph, A. 2002, Techniques of Cluster Algorithms in Data Mining, Data Mining and Knowledge Discovery, vol.6. Pp.303–360. Netherlands.

[42] Minka, T.P., 2012. Algorithms for maximum-likelihood logistic regression.

[43] W. Hu, Y. Qian, and F. K. Soong, “A new Neural Network based logistic regression classifier for improving mispronunciation detection of L2 language learners,” Proc. 9th Int. Symp. Chinese Spok. Lang. Process. ISCSLP 2014, pp. 245–249, 2014.