Businesses derive more revenue from building and maintaining long-term relationships with their customers. Therefore, it is essential to build refined strategies based on customer relationship management, with the purpose of increasing their turnover and profits while retaining their customers. In this context, customer segmentation, which is at the heart of marketing strategy, makes it possible to determine the answers to questions relating to the number of investments to be released, the marketing campaigns to be organized, and the development strategy to be implemented. This paper develops an extended RFMT (Recency, Frequency, Monetary, and Interpurchase Time) model, namely the RFMTS model, by introducing a new dimension as satisfaction 'S'. The aim of this model is to analyze online consumer satisfaction over time and discern changes to implement customer segmentation. This article proposes an approach to a segmentation, by client clustering along the unsupervised machine learning method kmeans based on data generated using the proposed RFMTS model, in order to improve the customer relationship and develop more effective personalized marketing strategies. The study shows that including satisfaction to the existing RFM model for customer clustering has a major impact and helps identify customers who are satisfied and those who are not, unlike previous attempts to develop new RFM models. By ignoring the "satisfaction" indicator, what went well and what didn't went well cannot be understood. Consequently, the business loses its unsatisfied, loyal, and profitable customers and either fails or relies only on the satisfied ones to continue making profits for an indefinite period of time.
IT master plan, which allows planning and managing the development of the computer systems, derives its importance in the central role of the computer systems in the functioning of organizations. This article focuses on the use of FAHP method for analysis and evaluation of tenders during the awarding of contracts of IT master plan's realization. For those purposes, a painstaking work was realized for making an inventory of criteria and sub-criteria involved in the evaluation of tenders and for specifying the degrees of preference for each pair of criteria and sub-criteria. To find a provider for the IT master plan's realization, organizations are increasingly using tendering as the mode of awarding contracts. This paper is an improvement of a previous published paper in which AHP method was used. The goals of this work are to make available to members of tenders committee a decision support tool for evaluating tenders of IT master plan's realization and endow the organizations with effective IT master plans in order to increase their information systems' performance. Keyword:Artificial intelligence Fuzzy AHP IT master plan Multi-criteria decision making Tendering Copyright © 2017 Institute of Advanced Engineering and Science.All rights reserved. Corresponding Author:Amadou Diabagaté, Department of Computer Science, University Abdel Malek Essaadi, Ziaten, Tangier 413, Morocco. Email: ahmadou.diabagate@gmail.com INTRODUCTIONOrganizations increasingly use IT master plan for leading the development of the computer system which is an essential element for their operations [1]. Thus, public and private procurement of IT master plan's realization are becoming more frequent.The IT master plan is a strategic plan intended for piloting the development of IT in an organization. It allows having a computer system that meets the strategic options of the Directorate General. Its starting point is the strategy of an organization to reach the definition of a target in terms of IT and information system. The realization of an IT master plan aims at many objectives such as the urbanization of the computer system, the modernization of IT infrastructures (hardware and software), the reduction of IT costs, the accompaniment of the launch of strategic projects, the creation of monitoring indicators, the multi-sites deployment of the computer system.Organizations, in order to ensure their tasks, need to purchase goods or services or to execute work. These purchases designated by the term "procurement" play a considerable economic role and have a significant economic weight [2] estimated at about 20% of global GDP [3]. The award of contracts is a sensitive area as the economic interests at stake are huge [3], [4]. There are several modes for awarding contracts including tendering [5] which can be defined as a process that allows to emit a request for works, services and goods to businesses and then choose the provider after analysis of proposals according to predetermined criteria without negotiation [6].
This paper proposes improvements concerning the analysis and the evaluation of tenders in the tendering process. At first, a new method of analysis and evaluation of tenders using the rule of proportion is proposed. Secondly, the principles of fuzzy logic are introduced in order to reconsider limits from the classical logic in the analysis and evaluation of tenders.This work is a step towards the modeling of an IT solution integrating the concepts of artificial intelligence and decision support in the context of e-government (e-tendering).
Abstract-This work focuses on the use of mult i-criteria decision-making method AHP for using in educational and vocational guidance. Analytical Hierarchy Process (AHP), proposed by the mathematician Thomas Saaty in 1980, is a method of analysis greatly used in the context of a mult i-criteria analysis; it allows the comparison and the choice between the preset options. To achieve this goal, a vital work, preceded the use of the AHP method, which consists in doing a prototyping of trades according to the guidance criteria and sub-criteria. The IT system based on this method allo ws the student to find, firstly, the activities' sectors which are the most appropriate to his/her profile, to choose subsequently the trades and finally, to identify, the potential training paths.
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