Computer Assisted Alerts Using Mental Model Approach for Customer Service Improvement

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DOI: 10.4236/jsea.2013.65B005    3,673 Downloads   5,258 Views  Citations

ABSTRACT

Warning alerts are specially designed to protect user rights and safety to avoid serious damage caused by overlooking the essence of warning alerts. Today’s world of Information Communication Technology (ICT) needs improvement and to review the decisions of security experts in terms of improving warning designs and dialogues, and timely inform the authorities to take quick action at the right time and choice. Human behaviour is deeply involved in most of the security failures and its poor response. If we are able to check and monitor human behaviour in any organisation, we can achieve quality assurance and provide best services to our customers. We have arranged a study in the Center of Post Graduate Studies, International Islamic University, Malaysia (CPS-IIUM), department of Hajj Services-Makkah, and Hospital Management System-Makkah comprised of Observation, Interviews, Questionnaire and discussion based on organizational structure and job activities of people involved in different scenarios and positions under one umbrella of organizational objectives in order to trap the human error in order to take rapid action and response from the management team. Human behaviour is deeply observed and checked while performing different job activities in order to identify the serious errors at the right time during job performance at various levels. We have applied the concept of Brahm’s Language for the simulation of human behaviour which proves an opportunity to simulate human behaviour while performing job activities. Customer service can be improved easily if necessary measures and decisions are taken at the right time and place in any organisation.

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A. Ghaffar, M. Wahiddin and A. Shaikh, "Computer Assisted Alerts Using Mental Model Approach for Customer Service Improvement," Journal of Software Engineering and Applications, Vol. 6 No. 5B, 2013, pp. 21-25. doi: 10.4236/jsea.2013.65B005.

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