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 presents, for the first time, an innovative Jet Plasma-assisted technique for the green synthesis of TiO₂@Ag core–shell nanoparticles using chard leaf extract as a natural reducing and stabilizing agent. The Jet Plasma provides a highly energetic environment that accelerates nucleation and core–shell formation at low temperatures without toxic precursors. The synthesized nanoparticles exhibited uniform and stable structures, as confirmed by comprehensive characterization techniques including X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), ultraviolet–visible (UV–Vis) spectroscopy, transmission electron microscopy (TEM), and zeta potential analysis. XRD patterns confirmed the crystalline anatase
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Objective: To self-evaluate the effect of SBAR (Situation, Background, Assessment, and Recommendation) educational program on nurse and midwives practices in maternal health report documentation accuracy.
Methods: A quasi- experimental design was carried with the application of pre- post test for nurses and midwives’ knowledge and practices regarding SBAR communication tool. The study was held in Al-Elwia maternity teaching hospital, Al –Karckh maternity hospital and Al-Yarmouk teaching Hospital. purposive sample as it was convenient with inclusion criteria consisted of (84) nurse and midwives. The questionnaire comprised of demographic data, nurses- midwives practices of SBAR using (5) level Likert scale for assessme
An experiment was conducted in pots under field conditions during fall seasons of 2017 and 2018. This study aimed to improve a weak growth of seedlings under salt stress in sorghum. Three factors were studied. 1st factor was three cultivars (Inqath, Rabeh, and Buhoth70). 2nd factor was seed priming (primed and unprimed seed). Seed were primed by soaking for 12 hours in a solution containing 300 + 70 mg L−1 of gibberellic (GA3) and salicylic (SA) acids, respectively. 3rd factor was irrigation with saline water (6, 9 and 12 dS m−1) resulting from dissolving sodium chloride in distilled water in addition to control treatment (distilled water). Randomized complete block design was used with four replications. In both seasons: the results sh
... Show MoreSoftware-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
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