Measuring the effect of customer relationship management (CRM) components on the non financial performance of commercial banks: Egypt case

This paper presents customer relationship management (CRM) components as applied on the Egyptian Commercial Banks, examined from the bankers' point of view. Then, it intends to measure their effect on the level of customer satisfaction and loyalty from the customers’ point of view as examples of the non financial performance measures. The paper is quantitative in nature and consists of two different structured questionnaires using convenience/quota sampling. The first involved 180 employees in order to measure CRM applicability, and the second involved 270 customers to measure the level of customer satisfaction and loyalty and their effect on the Egyptian Commercial Banks' financial performance The findings show that the selected banks apply CRM components but the level of application differs from one bank to another. The results showed a significant positive relationship between CRM and customer satisfaction in the Egyptian Commercial Banks, when applying them together and not separately. In addition, there is a strong positive effect between customer satisfaction and loyalty which was reflected on the Commercial Banks' financial performance. The findings confirm the importance of studying and implementing CRM to achieve customer loyalty and improve the Egyptian Commercial Banks financial performance. Banks wishing to improve their relationships with customers need to focus on the CRM components to develop relevant and effective marketing strategies and tactics. The paper measures the CRM as a multidimensional construct as applied on the Egyptian Commercial Banks and relate it to the achievement of the ultimate goal of retaining customers to gaining a sustainable competitive advantage and achieve more profits

Electronic word of mouth in social media: The common characteristics of retweeted and favourited marketer-generated content posted on Twitter

Marketers desire to utilise electronic word of mouth (eWOM) marketing on social media sites. However, not all online content generated by marketers has the same effect on consumers; some of them are effective while others are not. This paper aims to examine different characteristics of marketer-generated content (MGC) that of which one lead users to eWOM. Twitter was chosen as one of the leading social media sites and a content analysis approach was employed to identify the common characteristics of retweeted and favourited tweets. 2,780 tweets from six companies (Booking, Hostelworld, Hotels, Lastminute, Laterooms and Priceline) operating in the tourism sector are analysed. Results indicate that the posts which contain pictures, hyperlinks, product or service information, direct answers to customers and brand centrality are more likely to be retweeted and favourited by users. The findings present the main eWOM drivers for MGC in social media.Abdulaziz Elwalda and Mohammed Alsagga

The dilemma of internal audit function adaptation: The impact of ERP and corporate governance pressures

© Emerald Group Publishing Limited. Purpose: The purpose of this paper is to provide a conceptual framework that helps to investigate how the internal audit function (IAF) responds to both the introduction of the control logic of Enterprise Resource Planning (ERP) systems, and corporate governance’s (CG) institutional pressures. Furthermore, the paper aims to articulate the concurrence between the external pressures of CG and internal control logic of ERP systems. Design/methodology/approach: The paper presents a review of the normative literature pertaining to the increase in significance of CG in the light of the worldwide economic crisis. The paper highlights a literature gap related to the lack of studies focusing on the impact of ERP systems implementation on the IAF practices. Findings: The authors articulate institutional theory to formulate a conceptual framework that explains the reciprocal interplay between the macro external governance pressures, micro internal institutional logics inscribed in the ERP systems and their effect on IAF practices and structure within organisations. Research limitations/implications: The paper is conceptual in nature and therefore the proposed framework will be subsequently validated using a qualitative research approach in future research. Practical implications: The conceptual framework would offer the internal auditors some strategies for enabling adaptation to the different internal and external pressures. Also the paper provides a platform for research community to investigate the influence of CG and ERP systems implementation on IAF adaptation. Originality/value: The paper provides a clearer articulation of the various constructs that affect the IAF, which has gained great attention for assuring good CG

Particle production in proton-proton collisions

Proton-proton collision is a simple system to investigate nuclear matter and it is considered to be a guide for more sophisticated processes in the proton-nucleus and the nucleus-nucleus collisions. In this article, we present a phenomological study of how the mechanism of particle production in pp interaction changes over a wide range of interaction energy. This study is done on data of charged particle produced in pp experiments at different values of energy. Some of these data give the created particles classified as hadrons, baryons and mesons, which help us compare between production of different particles. This might probe some changes in the state of nuclear matter and identify the mechanism of interaction.Comment: arXiv admin note: text overlap with arXiv:1410.715

The impact of image dynamic range on texture classification of brain white matter

<p>Abstract</p> <p>Background</p> <p>The Greylevel Cooccurrence Matrix method (COM) is one of the most promising methods used in Texture Analysis of Magnetic Resonance Images. This method provides statistical information about the spatial distribution of greylevels in the image which can be used for classification of different tissue regions. Optimizing the size and complexity of the COM has the potential to enhance the reliability of Texture Analysis results. In this paper we investigate the effect of matrix size and calculation approach on the ability of COM to discriminate between peritumoral white matter and other white matter regions.</p> <p>Method</p> <p>MR images were obtained from patients with histologically confirmed brain glioblastoma using MRI at 3-T giving isotropic resolution of 1 mm³. Three Regions of Interest (ROI) were outlined in visually normal white matter on three image slices based on relative distance from the tumor: one peritumoral white matter region and two distant white matter regions on both hemispheres. Volumes of Interest (VOI) were composed from the three slices. Two different calculation approaches for COM were used: i) Classical approach (CCOM) on each individual ROI, and ii) Three Dimensional approach (3DCOM) calculated on VOIs. For, each calculation approach five dynamic ranges (number of greylevels N) were investigated (N = 16, 32, 64, 128, and 256).</p> <p>Results</p> <p>Classification showed that peritumoral white matter always represents a homogenous class, separate from other white matter, regardless of the value of N or the calculation approach used. The best test measures (sensitivity and specificity) for average CCOM were obtained for N = 128. These measures were also optimal for 3DCOM with N = 128, which additionally showed a balanced tradeoff between the measures.</p> <p>Conclusion</p> <p>We conclude that the dynamic range used for COM calculation significantly influences the classification results for identical samples. In order to obtain more reliable classification results with COM, the dynamic range must be optimized to avoid too small or sparse matrices. Larger dynamic ranges for COM calculations do not necessarily give better texture results; they might increase the computation costs and limit the method performance.</p

Fuzzy model based multivariable predictive control design for rapid and efficient speed-sensorless maximum power extraction of renewable wind generators

Introduction. A wind energy conversion system needs a maximum power point tracking algorithm. In the literature, several works have interested in the search for a maximum power point wind energy conversion system. Generally, their goals are to optimize the mechanical rotation or the generator torque and the direct current or the duty cycle switchers. The power output of a wind energy conversion system depends on the accuracy of the maximum power tracking controller, as wind speed changes constantly throughout the day. Maximum power point tracking systems that do not require mechanical sensors to measure the wind speed offer several advantages over systems using mechanical sensors. The novelty. The proposed work introduces an intelligent maximum power point tracking technique based on a fuzzy model and multivariable predictive controller to extract the maximum energy for a small-scale wind energy conversion system coupled to the electrical network. The suggested algorithm does not need the measurement of the wind velocity or the knowledge of turbine parameters. Purpose. Building an intelligent maximum power point tracking algorithm that does not use mechanical sensors to measure the wind speed and extracts the maximum possible power from the wind generator, and is simple and easy to implement. Methods. In this control approach, a fuzzy system is mainly utilized to generate the reference DC-current corresponding to the maximum power point based on the changes in the DC-power and the rectified DC-voltage. In contrast, the fuzzy model-based multivariable predictive regulator follows the resultant reference current with minimum steady-state error. The significant issues of the suggested maximum power point tracking method, such as the detailed design process and implementation of the two controllers, have been thoroughly investigated and presented. The considered maximum power point tracking approach has been applied to a wind system driving a 5 kW permanent magnet synchronous generator in variable speed mode through the simulation tests. Practical value. A practical implementation has been executed on a 5 kW test bench consisting of a dSPACEds1104 controller board, permanent magnet synchronous generator, and DC-motor drives to confirm the simulation results. Comparative experimental results under varying wind speed have confirmed the achievable significant performance enhancements on the maximum wind energy generation and overall system response by using the suggested control method compared with a traditional proportional integral maximum power point tracking controller.Вступ. Система перетворення енергії вітру потребує алгоритму відстеження точки максимальної потужності. У літературі є кілька робіт, присвячених пошуку системи перетворення енергії вітру із точкою максимальної потужності. Як правило, їх метою є оптимізація механічного обертання або моменту, що крутить, генератора і перемикачів постійного струму або робочого циклу. Вихідна потужність системи перетворення енергії вітру залежить від точності контролера стеження за максимальною потужністю, оскільки швидкість вітру постійно змінюється протягом дня. Системи стеження за точками з максимальною потужністю, яким не потрібні механічні датчики для вимірювання швидкості вітру, мають ряд переваг у порівнянні з системами, що використовують механічні датчики. Новизна. Пропонована робота представляє інтелектуальний метод відстеження точки максимальної потужності, заснований на нечіткій моделі та багатопараметричному прогнозуючому контролері, для отримання максимальної енергії для маломасштабної системи перетворення енергії вітру, підключеної до електричної мережі. Пропонований алгоритм не вимагає вимірювання швидкості вітру або знання параметрів турбіни. Мета. Побудова інтелектуального алгоритму відстеження точки максимальної потужності, який не використовує механічні датчики для вимірювання швидкості вітру та витягує максимально можливу потужність з вітрогенератора, а також простий та зручний у реалізації. Методи. У цьому підході до управління нечітка система в основному використовується для генерування еталонного постійного струму, що відповідає точці максимальної потужності, на основі змін потужності постійного струму та постійної випрямленої напруги. Навпаки, багатопараметричний прогнозуючий регулятор на основі нечіткої моделі слідує за результуючим еталонним струмом з мінімальною помилкою, що встановилася. Істотні проблеми запропонованого методу відстеження точки максимальної потужності, такі як процес детального проектування та реалізація двох контролерів, були ретельно досліджені та представлені. Розглянутий підхід до відстеження точки максимальної потужності був застосований до вітрової системи, що приводить у дію синхронний генератор з постійними магнітами потужністю 5 кВт у режимі змінної швидкості за допомогою моделювання. Практична цінність. Для підтвердження результатів моделювання було виконано практичну реалізацію на випробувальному стенді потужністю 5 кВт, що складається з плати контролера dSPACEds1104, синхронного генератора з постійними магнітами та електроприводів з двигунами постійного струму. Порівняльні експериментальні результати при різній швидкості вітру підтвердили значні поліпшення продуктивності з максимального вироблення енергії вітру і загального відгуку системи при використанні запропонованого методу управління в порівнянні з традиційним пропорційно-інтегральним контролером спостереження за точкою максимальної потужності