Abstract
One of the main objectives of this research is to implement and validate a new expert system for identifying the failure in the web interaction design of management information systems. This system aims at assisting the top level of management, staff and information system developers to validate IT investments through detecting the online communication tools and interaction capabilities of user interfaces. Second, this paper focuses on the employment of artificial neural network in the prediction of quality characteristics of MIS from the end-users perspectives. To validate the expert model, the authors follow a methodology of five steps including reviewing related empirical studies, extracting the core diagnosis factors, designing, implementing, testing and deploying the expert system. The final validation of the proposed expert model is performed by ten information system developers and professionals and the results pointed out that the detection framework has a reasonable effectiveness in checking the quality of Web interaction design. For predicting the quality characteristics of the MIS, a dataset of 50 subjects collected from end-users ANN learning where each subject consists of 4 features (4 quality factors as inputs and one Boolean output). 60% of the subjects are used in the training phase while the other 20 subjects are used for testing and validation purposes. According to the collected feedback of the validation team we can safely say that the proposed expert system framework is practical and can be applied in several IT areas such as software engineering and maintenance. Also, based on the accuracy percentage of the artificial network prediction, it is clearly seen that neural network can be considered as an effective AI tool in the prediction of end-users’ perceptions where the prediction accuracy of the proposed model is 90%. It is suggested to apply the proposed models in the validation and prediction in the related information system areas.
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References
Alhendawi, K.M., Al-Janabi, A.A.: An intelligent expert system for management information system failure diagnosis. In: International Conference on Intelligent Computing and Optimization, pp. 257–266. Springer, Cham (2018)
Alhendawi, K., Baharudin, A.: The impact of interaction quality factors on the effectiveness of web-based system: the mediating role of user satisfaction. J. Cogn. Technol. Work. (2013). https://doi.org/10.1007/s10111-013-0272-9
Albrecht, C.C., Dean, D.L., Hansen, J.V.: Marketplace and technology standards for B2B e-commerce: progress, challenges, and the state of the art. Inf. Manag. 42, 865875 (2005)
Allwood, R.J.: Techniques and Applications of Expert System in the Construction Industry. Ellis Horwood Series in Civil Engineering, 1st edn. England (1989)
Chung, P., Hinde, C., Moonis, A.: Developments in Applied Artificial Intelligence: 16th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2003, Laughborough, UK, 23–26 June 2003, Proceedings: Springer (2003)
Cooper, A., Reimann, R., Cronin, D.: The Essentials of Interaction Design. Wiley Press, Indianapolis (2007)
Dalkir, K.: Knowledge Management in Theory and Practice: Taylor & Francis (2013)
Edeholt, H., Löwgren, J.: Industrial design in a post-industrial society: a framework for understanding the relationship between industrial design and interaction design. In: 5th Conference on European Academy of Design (2003)
Harvey, J.J.: Expert systems: an introduction. Int. J. Comput. Appl. Technol. 1(½), 53–60 (1988)
Holmlid, S.: Interaction design and service design: expanding a comparison of design disciplines. In: Nordic Conference on Service Design and Service Innovation (2009)
Hopgood, A.A.: Intelligent Systems for Engineers and Scientists, 3rd edn. Taylor & Francis (2011)
Julier, G.: From visual culture to design culture. Design Issues 22(1) (2006)
Law, L.C., Law, E., Hvannberg, E.T., Cockton, G.: Maturing Usability: Quality in Software, Interaction and Value. Springer (2007)
Lawson-Body, A., Willoughby, L., Logossah, K.: Developing an instrument for measuring e-commerce dimensions. J. Comput. Inf. Syst. 51(2), 213 (2010)
Lawson-Body, A., Limayem, M.: The impact of customer relationship management on customer loyalty: the moderating role of web site characteristics. J. Comput.-Mediated Commun. 9(4) (2004)
Lin, H.-C.K., Chen, N.-S., Sun, R.-T., Tsai, I.-H.: Usability of affective interfaces for a digital arts tutoring system. Behaviour Information Technology (ahead-of-print) 1–12 (2012)
Moggridge, B.: Designing Interactions. MIT Press (2007)
Muylle, S., Moenert, R., Despontin, M.: The conceptualization and empirical validation of website user satisfaction. Inf. Manag. 41, 213–226 (2004)
Puntambekar, A.A.: Software Engineering and Quality Assurance: Technical Publications (2010)
Shu-Hsien, L.: Expert system methodologies and applications - a decade review from 1995 to 2004. Expert Syst. Appl. 28, 93–103 (2005)
Tyler, A.R.: Expert Systems Research Trends. Nova Science Publishers (2007)
Yoo, B., Donthu, N.: Developing a scale to measure the perceived quality of an internet shopping site (SITEQUAL). Q. J. Electron. Commer. 2(1), 31–45 (2001)
Zhang, J.-R., Zhang, J., Lok, T.-M., Lyu, M.R.: A hybrid particle swarm optimization–back-propagation algorithm for feedforward neural network training. Appl. Math. Comput. 185(2), 1026–1037 (2007)
Engelbrecht, A.P.: Computational Intelligence: An Introduction: Wiley (2007)
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Appendix A: CLIPS Code of the Developed Expert System
Appendix A: CLIPS Code of the Developed Expert System
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Alhendawi, K.M., Al-Janabi, A.A., Badwan, J. (2020). Predicting the Quality of MIS Characteristics and End-Users’ Perceptions Using Artificial Intelligence Tools: Expert Systems and Neural Network. In: Vasant, P., Zelinka, I., Weber, GW. (eds) Intelligent Computing and Optimization. ICO 2019. Advances in Intelligent Systems and Computing, vol 1072. Springer, Cham. https://doi.org/10.1007/978-3-030-33585-4_3
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