CFP last date
22 April 2024
Call for Paper
May Edition
IJCA solicits high quality original research papers for the upcoming May edition of the journal. The last date of research paper submission is 22 April 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Online Shopping Adoption Factors in Kuwait Market based on Data Mining Rough Set Approach

by Luai A. Al-Shalabi
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 180 - Number 32
Year of Publication: 2018
Authors: Luai A. Al-Shalabi
10.5120/ijca2018916832

Luai A. Al-Shalabi . Online Shopping Adoption Factors in Kuwait Market based on Data Mining Rough Set Approach. International Journal of Computer Applications. 180, 32 ( Apr 2018), 10-17. DOI=10.5120/ijca2018916832

@article{ 10.5120/ijca2018916832,
author = { Luai A. Al-Shalabi },
title = { Online Shopping Adoption Factors in Kuwait Market based on Data Mining Rough Set Approach },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2018 },
volume = { 180 },
number = { 32 },
month = { Apr },
year = { 2018 },
issn = { 0975-8887 },
pages = { 10-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume180/number32/29249-2018916832/ },
doi = { 10.5120/ijca2018916832 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:04:29.753979+05:30
%A Luai A. Al-Shalabi
%T Online Shopping Adoption Factors in Kuwait Market based on Data Mining Rough Set Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 180
%N 32
%P 10-17
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This study applied data mining process to provide an insight about factors which led to the adoption of online shopping in medium and Large-sized shopping centers (MLShCs) in Kuwait. This research is focused on proposing the high quality environmental factors which affect the success of online shopping among (MLShCs) in Kuwait and ignoring the low impact factors that may cost a lot of money. It also researches the behavior of the customers and their desire to buy directly from the physical store, the online shopping website, or both. This was achieved by distributing a questionnaire, collecting the data in dataset, cleaning the data, minimizing the dimension of the dataset vertically by applying the rough set feature selection technique, and building a classification model. The result of the previous process is the key to examine the success of online shopping in MLShCs. This study could work as the decision maker for those new investors in Kuwait who are thinking of establishing new shopping business and advise them to go for physical store, online shopping website, or both. It also advices current online shopping business to improve their infrastructure, website’s design and availability, and security issues. The proposed approach performs effectively and generates interested results.

References
  1. WTO. 1998. Study from WTO Secretariat highlights potential trade gains from electronic commerce. http://www.wto.org/english/newse/pres98e/pr96e.htm
  2. ECLAC. 2002. Electronic Commerce, International Trade and Employment: Review of the Issues. UN, Economic commission for Latin America and the Caribbean ECLAS, Washington Office, April, pp: 1-30.
  3. Yu, Z., Jing, B., and Weixiang, Z. 2013. Trust fraud: A crucial challenge for China’s e-commerce market. Electronic Commerce Research and Applications, 12: 299-308.
  4. Ramakrishnan, R., Usha, R., and Hsieh-Ling, H. 2012. The impact of e-commerce on Taiwanese SMEs: Marketing and operations effects. International Journal of Production Economics, 140: 934-943.
  5. Panagariya, A. E-Commerce, WTO, and Developing Countries. 2000. Policy issues in international trade and commodities study Series. No.2 UN, New York and Geneva, pp: 1-33.
  6. Malkawi, B. H. 2007. E-commerce in Light of International Trade Agreements: The WTO and the United States-Jordan Free Trade Agreement. International Journal of Law and Information Technology, 15: 153-169.
  7. Nuray Terzi, 2011. The impact of e-commerce on international trade and employment. Procedia - Social and Behavioral Sciences, 24: 745-753.
  8. Dave C. 2011. E-Business and E-Commerce Management: Strategy. Implementation and Practice, 5th Edition, Prentice Hall, New York.
  9. Jarvenpaa, S. L., Tractinsky, N., and Vitale, M. 2000. Consumer Trust in an Internet Store. Information Technology and Management, 1: 45-71.
  10. Kim, J. and Moon, J. Y. 1998. Designing Emotional Usability in Customer Interfaces – Trustworthiness of Cyber-banking System Interfaces. Interacting with Computers, 10: 1-29.
  11. Egger, F. N. 2000. Trust Me, I'm an Online Vendor: Towards a Model of Trust for E-Commerce System Design. in: G. Szwillus & T. Turner (Eds.): CHI2000 Extended Abstracts: Conference on Human Factors in Computing Systems, The Hague (NL), ACM Press, April 1-6, pp: 101-102.
  12. Inc. Magazine - December 2010/January 2011 English.
  13. Parasuraman, A., Zeithaml, V. A. and Berry, L. L. 1988. SERVQUAL: a multiple item scale for measuring customer perceptions of service quality. Journal of Retailing, 64: 12-40.
  14. Kuo, Y. F. 2003. A study on service quality of virtual community web sites. Total Quality Management, 14: 461-73.
  15. Negash, S., Ryan, T. and Igbaria, M. 2003. Quality and effectiveness in web-based customer support systems. Information and Management, 40: 757-68.
  16. Al-Hudhaif, S. and Alkubeyyer, A. 2011. E-Commerce Adoption Factors in Saudi Arabia. International Journal of Business and Management, 6: 122-133
  17. Oreku, G. S., Mtenzi, F. J. and Ali, A. D. 2011. The Prospects and Barriers of E-Commerce Implementation in Tanzania. Conference Proceedings, ICIT 5th International Conference on Information Technology, Amman, Jordan, pp: 11-13.
  18. Radovilsky, Z. and Hegde, V. G. 2004. Factors influencing e-commerce implementation: Analysis of survey results. Journal of Academy of Business and Economics, 4: 29-37
  19. Zhu, K. 2004. E-Commerce Capability: A Resource-Based Assessment of Their Business Value. Journal of Management Information Systems, 21: 167–202.
  20. Al-Fadhli, S. 2011. Critical Success Factors influencing e-commerce in Kuwait. Journal of Internet Banking and Commerce, 16.
  21. Pawlak Z. and Skowron A. 2007. Rudiments of rough sets. Information Sciences, 177: 3-27.
  22. Al-Shalabi L. 2009. Improving Accuracy and Coverage of Data Mining Systems that are built from Noisy Datasets: A new Approach. Journal of Computer Science, 5: 131-135.
  23. Al-Shalabi L. 2016. Data Mining Application: Predicting Students’ performance of ITC program in the Arab Open University in Kuwait – The blended Learning. International Journal of Computer Science and Information Security (IJCSIS), ISSN 1947-5500, Pittsburgh, PA, USA, 14: 827-833.
  24. Al-Shalabi L. 2017. Perceptions of crime behavior and Relationships: Rough Set Based Approach. International Journal of Computer Science and Information Security (IJCSIS), ISSN 1947-5500, Pittsburgh, PA, USA, 15: 413-420.
  25. Pyle, D. 1999. Data Preparation for Data Mining. Morgan Kaufmann Publishers, LosAltos, California.
  26. Al-Shalabi, L., Shaaban, Z., and Kasasbeh, B., 2006. Data mining: A Preprocessing Engine. Journal of Computer Science, 2: 735-739.
  27. Quinlan J. R. 1989. Unknown Attribute Values in Induction. In Proceedings of the Sixth International Workshop on Machine Learning, pp: 164-168.
  28. Dempster, A. P., Larid, N. M., and Rubin, D. B. 1977. Maximum likelihood from incomplete data via the Em Algorithm (with discussion). Journal of Royal Statistical Society. B39: 1-38.
Index Terms

Computer Science
Information Sciences

Keywords

E-commerce Data Mining feature selection classifiers.

Powered by PhDFocusTM