The effect of organizational culture on CRM success

Copyright @ 2013 EMCIS.The aim of this paper is to develop a theoretical framework exemplifying the effect of organizational culture on the success of Customer Relationship Management (CRM) systems' implementation. This is deemed significant as yet little research has investigated the role of organizational culture as a critical success factor to CRM implementation. The proposed theoretical framework is developed based on the notion that nurturing an organizational culture that promotes adaptive learning leads to better management of customer information that in turn improves the quality of customer information, which is considered a key contributor to successful implementation of CRM initiatives. The Competing Values Framework (CVF) is used to measure "Organizational Culture" since it has proven its validity in examining the effect of organizational culture on organizational effectiveness and performance

Electrochemical determination of Cd2+ in some Al-Madinah water samples and human plasma by cathodic stripping voltammetry in the presence of oxine as a chelating agent

AbstractA fast, simple, sensitive cathodic adsorptive stripping voltammetric procedure for quantitative analysis of Cd–oxine complex in al-Madinah city water samples and human plasma is described. The technique involves adsorptive accumulation of the complex on the working electrode, followed by square wave voltammetric determination of the preconcentrated analyte. In basic media, a cathodic electrochemical process involving the elimination of two protons occurs, and a mechanism for the reduction process is suggested. The optimal experimental parameters for assay of this complex are: carbonate supporting electrolyte pH 8, accumulation time 30s, accumulation potential −0.1V, scan rate 200mVs−1, pulse amplitude 80mV, frequency 40Hz, surface area of working electrode 0.6mm2 and convection rate 1000rpm. The calibration graph for determination of Cd–oxine was linear over the concentration range 5×10−8 to 4×10−7moll−1 (r=0.998), with a detection limit of 3.5×10−9moll−1. The precision of the proposed procedure was estimated by 10 successive voltammetric measurements of 2×10−6moll−1 Cd with 4×10−6moll−1 oxine, and the calculated relative standard deviation was 0.39%. The percentage recovery, indicating the accuracy of the analytical method, was 94±1.0%. Possible interference by several substances, including metals and ligands, was also evaluated. The electroanalytical method was successfully applied to assaying cadmium in water samples and biological fluids such as plasma

Evaluation of the Potential Use of Waste Tires as Supplementary Fuel in Jordan Cement Industry

Although scrap tires can cause serious environmental problems, their use as an energy source in cement industry could save considerable amounts of money. The total generated scrap tires in Jordan is estimated to be 7,862,968 per year. The elemental analysis showed that 81% of waste tires was carbon and the average of the measured lower heating value was 33845 kj/kg.  Jordan has seven cement factories that produce about 14.1 million tons of cement and consume about 987000 tons of crude oil which costs about 661 million dollars. The study analyzed the use of waste tires as supplementary fuel in cement industry in Jordan. Results showed that savings could reach 6.29 million dollars if we used 20% of the generated waste tires per year in cement industry and 31.43 if the whole generated waste tires (100%) was used in cement industry.Â

A feed forward neural network approach for matrix computations

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.A new neural network approach for performing matrix computations is presented. The idea of this approach is to construct a feed-forward neural network (FNN) and then train it by matching a desired set of patterns. The solution of the problem is the converged weight of the FNN. Accordingly, unlike the conventional FNN research that concentrates on external properties (mappings) of the networks, this study concentrates on the internal properties (weights) of the network. The present network is linear and its weights are usually strongly constrained; hence, complicated overlapped network needs to be construct. It should be noticed, however, that the present approach depends highly on the training algorithm of the FNN. Unfortunately, the available training methods; such as, the original Back-propagation (BP) algorithm, encounter many deficiencies when applied to matrix algebra problems; e. g., slow convergence due to improper choice of learning rates (LR). Thus, this study will focus on the development of new efficient and accurate FNN training methods. One improvement suggested to alleviate the problem of LR choice is the use of a line search with steepest descent method; namely, bracketing with golden section method. This provides an optimal LR as training progresses. Another improvement proposed in this study is the use of conjugate gradient (CG) methods to speed up the training process of the neural network. The computational feasibility of these methods is assessed on two matrix problems; namely, the LU-decomposition of both band and square ill-conditioned unsymmetric matrices and the inversion of square ill-conditioned unsymmetric matrices. In this study, two performance indexes have been considered; namely, learning speed and convergence accuracy. Extensive computer simulations have been carried out using the following training methods: steepest descent with line search (SDLS) method, conventional back propagation (BP) algorithm, and conjugate gradient (CG) methods; specifically, Fletcher Reeves conjugate gradient (CGFR) method and Polak Ribiere conjugate gradient (CGPR) method. The performance comparisons between these minimization methods have demonstrated that the CG training methods give better convergence accuracy and are by far the superior with respect to learning time; they offer speed-ups of anything between 3 and 4 over SDLS depending on the severity of the error goal chosen and the size of the problem. Furthermore, when using Powell's restart criteria with the CG methods, the problem of wrong convergence directions usually encountered in pure CG learning methods is alleviated. In general, CG methods with restarts have shown the best performance among all other methods in training the FNN for LU-decomposition and matrix inversion. Consequently, it is concluded that CG methods are good candidates for training FNN of matrix computations, in particular, Polak-Ribidre conjugate gradient method with Powell's restart criteria

Middle Cretaceous (Cenomanian Ostracoda from the Wasia Formation of Saudi Arabia

6 p., 1 pl., 1 fig.http://paleo.ku.edu/contributions.htm

3-Ammonio­pyridinium tetra­bromido­mercurate(II) monohydrate

The asymmetric unit of the title compound, (C5H8N2)[HgBr4]·H2O, consists of one cation, one anion and one water mol­ecule. The anion exhibits a distorted tetra­hedral arrangement about the Hg atom. The crystal structure contains alternating sheets of cations (in the ac plane) and stacks of anions. Several strong hydrogen-bonding inter­actions (pyN—H⋯Br and C—H⋯Br; py is pyridine), along with O—H⋯Br inter­actions, connect the sheets of cations to the stacks of anions. Cation–cation π–π stacking is also present (C⋯C distances in the range 3.424–3.865 Å). The shortest Br⋯Br distance is 3.9527 (9) Å

Service level agreement framework for differentiated survivability in GMPLS-based IP-over-optical networks

In the next generation optical internet, GMPLS based IP-over-optical networks, ISPs will be required to support a wide variety of applications each having their own requirements. These requirements are contracted by means of the SLA. This paper describes a recovery framework that may be included in the SLA contract between ISP and customers in order to provide the required level of survivability. A key concern with such a recovery framework is how to present the different survivability alternatives including recovery techniques, failure scenario and layered integration into a transparent manner for customers. In this paper, two issues are investigated. First, the performance of the recovery framework when applying a proposed mapping procedure as an admission control mechanism in the edge router considering a smart-edge simple-core GMPLS-based IP/WDM network is considered. The second issue pertains to the performance of a pre-allocated restoration and its ability to provide protected connections under different failure scenarios

Electrochemical determination of rosiglitazone by square-wave adsorptive stripping voltammetry method

AbstractSquare-wave adsorptive stripping voltammetry technique was used to determine rosiglitazone (ROS) on the hanging mercury dropping electrode (HMDE) surface, in Britton Robinson buffer, pH=5. The voltammetric cathodic peak was observed at −1520mV vs. Ag/AgCl reference electrode. The voltammetric peak response was characterized with respect to pH, supporting electrolyte, accumulation potential, preconcentration time, scan rate, frequency, pulse amplitude, surface area of the working electrode and the convection rate. Under optimal conditions, the voltammetric current is proportional to the concentration of ROS over the concentration range of 5×10−8–8×10−7moll−1 (r=0.9899) with a detection limit of 3.2×10−11moll−1 using 120s accumulation time. The developed SW-AdSV procedure showed a good reproducibility, the relative standard deviation RSD% (n=10) at a concentration level of 5×10−7moll−1 was 0.33%, whereas the accuracy was 101%±1.0. The proposed method was successfully applied to assay the drug in the human urine and plasma samples with mean recoveries of 90±0.71% and 86±1.0%, respectively