000			02776cam a2200337 a 4500
003			EG-GiCUC
005			20250223031907.0
008			171231s2017 ua d f m 000 0 eng d
040			_aEG-GiCUC _beng _cEG-GiCUC
041	0		_aeng
049			_aDeposite
097			_aM.Sc
099			_aCai01.20.02.M.Sc.2017.Ya.M
100	0		_aYassmin Kamal Aly Ahmed Elsharkawy
245	1	2	_aA modeling framework for enhancing customer satisfaction / _cYassmin Kamal Aly Ahmed Elsharkawy ; Supervised Moataz Mohamed Khorshid , Mohamed Mostafa Saleh
246	1	5	_aإطار للنمذجة من اجل تحسين رضاء العميل
260			_aCairo : _bYassmin Kamal Aly Ahmed Elsharkawy , _c2017
300			_a74 Leaves : _bcharts ; _c30cm
502			_aThesis (M.Sc.) - Cairo University - Faculty of Computer and Information - Department of Operations Research and Decision Support
520			_aIn a very rapid, competitive environment, characterized by stochasticity, randomness, non-linearity and complexity, organizations who fall to stand strong in front of changes will definitely die. Every organization{u2019}s objective is to maximize its profit. Customers are the main assist of any running business. In order to maximize the for any organization, customer{u2019}s satisfaction becomes one of the most important performance Indicator (KPI) to guarantee the organization{u2019}s success. Increasing customer{u2019}s satisfaction will increase the probability of purchasing of the product service which directly affects the profit. This thesis proposes a simulation framework that can enhance an organization{u2019}s product to increase the customer{u2019}s satisfaction via integrating conjoint analysis, system dynamics and stochastic optimization. There are two main types of decisions (that decision-maker can control). Either to set the price, or to enhance the quality of the important attributes in the product or service studied taking into considerations the process and costs. These attributes are selected based on their relative utility conjoint analysis. In order to apply the model, the required data was collected through survey questionnaire sent to the different customers. The proposed framework aims to identify robust and near optimal values for decisions, taking into consideration the uncertain variables in the environment like the rate of growth of competitor`s utilities
530			_aIssued also as CD
653		4	_aConjoint analysis
653		4	_aDynamic models
653		4	_aLancaster analysis
700	0		_aMoataz Mohamed Khorshid , _eSupervisor
700	0		_aMohamed Mostafa Saleh , _eSupervisor
856			_uhttp://172.23.153.220/th.pdf
905			_aNazla _eRevisor
905			_aSamia _eCataloger
942			_2ddc _cTH
999			_c64331 _d64331