Browsing by Author "Hamdy, Hosny"

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    The Impact of CRM on Customer Satisfaction and Customer Loyalty: Mediation Effect of Customer Perceived Value (Evidence from Hospitality Industry)
    (Alexandria Univesity, 2020-09) El Sheikh, Samia; Halim, Yasser Tawfik; Hamdy, Hosny; Hamdy, Mohamed Adel
    Many businesses and service providers including hotels realize the significance of Customer Relationship Management (CRM) and its potential to help them gain new customers, retain existing customers, and maximize their lifetime value. This study aims to explore the relationship between CRM and customer perceived value (CPV), and their impact on customer perceived satisfaction and loyalty towards hotels in Egypt. The study clarifies the need for hotels to strengthen their business relationship with their customers as it is considered a strategic step for the growth and competitiveness of hotels. The contribution of this research is to help managers of hotels to better understand the real value of CRM and if it is really worth the large amounts of money that are put in it. Moreover, the study further added the investigation of whether CPV mediates the relationship between CRM and customer satisfaction/loyalty or not. The researchers adopted a quantitative approach that started with a comprehensive literature review of the main marketing concept of CRM and its alleged outcomes of customer perceived value (CPV), satisfaction and loyalty. This was followed by designing a conceptual model to answer the research questions. Next, primary data was gathered using self- administered questionnaires to collect quantitative data from several branches of one 5-star hotel in Egypt based
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    Triple Sampling Inference Procedures for the Mean of the Normal Distribution When the Population Coefficient of Variation Is Known
    (Multidisciplinary Digital Publishing Institute (MDPI), 2023-03) Alhajraf, Ali; Yousef, Ali; Hamdy, Hosny
    This paper discusses the triple sampling inference procedures for the mean of a symmetric distribution—the normal distribution when the coefficient of variation is known. We use the Searls’ estimator as an initial estimate for the unknown population mean rather than the classical sample mean. In statistics literature, the normal distribution under investigation underlines almost all the natural phenomena with applications in many fields. First, we discuss the minimum risk point estimation problem under a squared error loss function with linear sampling cost. We obtained all asymptotic results that enhanced finding the second-order asymptotic risk and regret. Second, we construct a fixed-width confidence interval for the mean that satisfies at least a predetermined nominal value and find the second-order asymptotic coverage probability. Both estimation problems are performed under a unified optimal framework. The theoretical results reveal that the performance of the triple sampling procedure depends on the numerical value of the coefficient of variation—the smaller the coefficient of variation, the better the performance of the procedure.