This research aims to know and the role of the marketing recovery dimensions in improving the organization's reputation through an exploratory study of private banks in the city of Baghdad. The aim of the research is to define the role of the marketing recovery through its dimensions (compensation, apology, speed of response, assistance and problem solving), in improving the organization's reputation, as the research will attempt to provide a theoretical framework for the dimensions studied through the most important of what researchers presented and then conduct the applied aspect of the research. Data were collected using a questionnaire-based survey consisting of 35 questions and distributed to 110 managers of private banks in the city of Baghdad. Therefore, the research attempts to answer a set of questions that embody the research problem (is there a role to exclude the marketing recovery on the dimensions of the organization's reputation), and in order to analyze the data obtained from the questionnaire, statistical methods such as the arithmetic mean, standard deviation, coefficient of variation, and the simple correlation coefficient were used, The results showed that there is an effect of the marketing recovery dimensions on improving the organization's reputation. Therefore, the research recommends that the bank's administration should work to improve the bank's reputation by focusing on and increasing attention to the dimensions of recovery in banks to obtain customer satisfaction. The researcher has faced the difficulty of obtaining data and the unwillingness of banks to cooperate with him, so it is not possible to generalize the results of the research to the research community for the privacy of banks compared to other service institutions. The research banks should use the marketing recovery dimensions to contribute to achieving customer satisfaction. Therefore, the research will contribute to knowing the mechanisms that help the bank to recover, improve its reputation and increase customer satisfaction.
This study proposed using color components as artificial intelligence (AI) input to predict milk moisture and fat contents. In this sense, an adaptive neuro‐fuzzy inference system (ANFIS) was applied to milk processed by moderate electrical field‐based non‐thermal (NP) and conventional pasteurization (CP). The differences between predicted and experimental data were not significant (
In this study, a low-cost biosorbent, dead mushroom biomass (DMB) granules, was used for investigating the optimum conditions of Pb(II), Cu(II), and Ni(II) biosorption from aqueous solutions. Various physicochemical parameters, such as initial metal ion concentration, equilibrium time, pH value, agitation speed, particles diameter, and adsorbent dosage, were studied. Five mathematical models describing the biosorption equilibrium and isotherm constants were tested to find the maximum uptake capacities: Langmuir, Freundlich, Redlich-Peterson, Sips, and Khan models. The best fit to the Pb(II) and Ni(II) biosorption results was obtained by Langmuir model with maximum uptake capacities of 44.67 and 29.17 mg/g for these two ions, respectively, w
... Show MoreAccurate pore and fracture pressure detection is a major step in successful drilling operations design. The overestimation of these parameters absolutely leads to serious problems throughout and after well drilling. This study is concerned with the characterization and analysis of the most significant diagenetic processes that degrade or improve the reservoir characteristics of the Mauddud Formation in the Badra oil field. The primary goal of this research is to estimate the pore pressure and fracture pressure using well logging data by Techlog 2015 software in order to assess the impact on the estimation of the mud weight window (MWW). The estimated values of formation pressures are then analyzed according to different diagenetic p
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