Samer Alhawari

Knowledge-Based Risk Management framework for Information Technology project

Abstract The purpose of this paper is to explore the field of Risk Management (RM) in relation with Knowledge Management (KM). It attempts to present a conceptual framework, called Knowledge-Based Risk Management (KBRM) that employs KM processes to improve its effectiveness and increase the probability of success in innovative Information Technology (IT) projects. It addresses initiatives towards employing KM processes in RM processes by reviewing, interpreting the related and relevant literature and sheds light on integration with RM in the IT project. The paper exposes some pertinent elements needed for building the KBRM framework for IT projects and also suggests some instrument about the integration of KM and RM process to improve the RRP (Risk Response Planning) process efficiency. This paper will contribute to the literature and practice by providing a clear method for employing KBRM as a framework to keep organizations competitive within the business environment.

Applying Security Policies in Small Business Utilizing Cloud Computing Technologies

Over a decade ago, cloud computing became an important topic for small and large businesses alike. The new concept promises scalability, security, cost reduction, portability, and availability. While addressing this issue over the past several years, there have been intensive discussions about the importance of cloud computing technologies. Therefore, this paper reviews the transition from traditional computing to cloud computing and the benefit for businesses, cloud computing architecture, cloud computing services classification, and deployment models. Furthermore, this paper discusses the security policies and types of internal risks that a small business might encounter implementing cloud computing technologies. It addresses initiatives towards employing certain types of security policies in small businesses implementing cloud computing technologies to encourage small business to migrate to cloud computing by portraying what is needed to secure their infrastructure using traditional security policies without the complexity used in large corporations.

The Outcome of Knowledge Process for Customer of Jordanian Companies on the Achievement of Customer Knowledge Retention

Organizations have increasingly recognized the importance of managing customer relationships, and Knowledge Management KM from the perspective of a process approaches assure positive impact on customer retention. Many organizations are turning to Customer Relationship Management CRM to better serve customers and facilitate closer relationships. This paper investigates how Knowledge Process for customers is used in practice by Jordanian companies to achieve Customer Knowledge Retention. The current practice is based on the data collected from 156, randomly drawn and reported from a survey of CRM applications and evaluation of CRM analytical functions provided by three software business solution companies working in the CRM area, and four companies that used the CRM system. Based on data collected from the companies, results from the analysis indicated that the knowledge process for customers had a positive effect on customer knowledge retention. The paper also verified the hypotheses of the effect of knowledge processes for customers on customer retention. The findings shed light on the potential relationship between the knowledge processes for customers and customer retention. It also provides guidance for the Information Technology IT industry as to how an analytical knowledge process for customers should be taken into account in developing countries to support to achieve customer knowledge retention due to cultural, social and educational differences.

An Empirical Study to Evaluation of Customer Acquisition Processes on Customer Satisfaction

In todays highly competitive environment, the organizations have been paying considerable attention to improve their customer satisfaction. For this reason, the purpose of this paper is to suggest a model defines how the combination between customer acquisition processes and knowledge about customer would improve the customer satisfaction. This paper adapts the quantitative research approach by using the survey strategy which is conducted by a questionnaire collected from 193 people working in the management position of Jordanian telecommunication organizations. The researcher uses the PLS as an analysis technique to test all hypotheses. The findings suggest that there is a positive effect of adapting the customer acquisition processes in improving the customer satisfaction mediating by the knowledge about customer. The proposed model makes a contribution on the part of the customer acquisition processes and the knowledge about customer and can be used as a structure of reference for the incorporation between them in order to attain the customer satisfaction.

A new fast associative classification algorithm for detecting phishing websites

Display Omitted A new fast Associative classification mining approach is developed.The applicability of well-known associative classification techniques on detecting phishing websites is investigated.Experimental results using different associative classification algorithms was performed. Associative classification (AC) is a new, effective supervised learning approach that aims to predict unseen instances. AC effectively integrates association rule mining and classification, and produces more accurate results than other traditional data mining classification algorithms. In this paper, we propose a new AC algorithm called the Fast Associative Classification Algorithm (FACA). We investigate our proposed algorithm against four well-known AC algorithms (CBA, CMAR, MCAR, and ECAR) on real-world phishing datasets. The bases of the investigation in our experiments are classification accuracy and the F1 evaluation measures. The results indicate that FACA is very successful with regard to the F1 evaluation measure compared with the other four well-known algorithms (CBA, CMAR, MCAR, and ECAR). The FACA also outperformed the other four AC algorithms with regard to the accuracy evaluation measure.

The Practice of Jordanian Business to Attain Customer Knowledge Acquisition

This paper examines how Jordanian companies use the knowledge process to support Customer Knowledge Acquisition CKA and how they foster it. The empirical study is based on a sample of the data collected from 156 respondents, drawn randomly from three software business solution companies working in the Customer Relationship Management CRM area, and four companies which are employing the CRM system. The results show that the three selected factors need for Customer Knowledge, Verify Customer Source, and Capture Customer Knowledge have a significant impact on customer acquisition. However, the source identification of knowledge is not significant in Jordanian business software environments. The empirical findings will help both researchers and practitioners in future Knowledge Management KM and Customer Acquisition research to gain a better understanding of the knowledge processes about customers on Customer Acquisition. This paper provides a contribution to the literature about Customer Knowledge Acquisition in one of the developing countries as a framework to keep organizations competitive within the global business environment.

Integration between Cloud Computing Benefits and Customer Relationship Management (CRM) Processes to Improve Organization's Performance

Due to the rapid growth in the electronic business, information technology has become very necessary for building up efficiency and effective transactions among organizations. Consequently, Cloud Computing (CC) becomes a very important area to achieve the organizations performance. The process of integration between Cloud Computing (CC) and the Customer Relationship Management (CRM) is a new research area. Therefore, scientific research and literature review related to Cloud Computing and CRM processes are limited. Yet, the impact of Cloud Computing on CRM processes remains under exploration and investigation. To this effect, this paper takes on a holistic approach that examines the combined effects of Cloud Computing Benefits (cost and ease of use) and CRM processes (customer acquisition, customer retention and customer expansion) on organizations performance. It also presents a conceptual framework for Cloud Computing and CRM processes, based on the analysis of various models presented in Cloud Computing and CRM processes. The main emphasis is focused on the concept of Cloud Computing Benefits (cost and ease of use) and CRM processes (customer acquisition, customer retention and customer expansion) by examining some reasons that make the organization interested in using this modern technology from one hand and how Cloud Computing can encourage organizations to implement CRM to improve their performance on the other. Therefore, this paper contributes to develop three models: Cloud Computing Benefits, CRM process, and integration between the Cloud Computing and CRM process to improve organization performance model. Also, it describes more valid factors to identify how an organization deals with its performance in the future by providing an advice for the Information Technology (IT) industry as how an analytical integration between Cloud Computing Benefits and CRM process improves organizations performance-something that should be taken into account in developing countries to attain a competitive advantage. This study is divided in three sections: Literature Review, Research Model, and Conclusion.

The Support of Knowledge Process to Enhance Risk Analysis in Jordanian Telecommunication Companies

The purpose of this paper is to study how Jordanian companies use the knowledge process to support risk analysis and how they deal with and foster it. The present empirical study is based on a sample of the data collected from 180 respondents, drawn randomly from Jordanian Telecommunication Companies. It provides a contribution to the literature about knowledge-based risk analysis in one of the developing countries as a framework to keep organisations competitive within the global business environment.This paper makes the following contributions. First, it demonstrates that according to project stakeholders, individual risk management activities, like for instance risk identification, are able to contribute to project success.Second, this paper provides insight in how knowledge process to support risk analysis and how they deal with and foster risk management activities to contribute in IT project success.And third, based on this new perspective, this paper provides new directions for further research into the mechanisms on how knowledge process support risk analysis in risk management to contribute in IT project success.The results of the survey show that the four selected factors (knowledge-based risk rationalise, knowledge-based risk comprehension, knowledge-based risk examination, and knowledge-based risk validation) have a significant impact on risk analysis.Due to the literature limitation about the KM model in developing countries, the current study will contribute to this field by addressing the knowledge-based risk. The findings will certainly help both researchers and practitioners in future knowledge management (KM) process, and risk analysis research. In order to get a better understanding of the knowledge processes on risk analysis, future research endeavours should focus on several other countries for comparative purposes.

Integrating associative rule-based classification with Naïve Bayes for text classification

Abstract Associative classification (AC) integrates the task of mining association rules with the classification task to increase the efficiency of the classification process. AC algorithms produce accurate classification and generate easy to understand rules. However, AC algorithms suffer from two drawbacks: the large number of classification rules, and using different pruning methods that may remove vital information to achieve the right decision. In this paper, a new hybrid AC algorithm (HAC) is proposed. HAC applies the power of the Naive Bayes (NB) algorithm to reduce the number of classification rules and to produce several rules that represent each attribute value. Two experiments are conducted on an Arabic textual dataset and the standard Reuters-21578 datasets using six different algorithms, namely J48, NB, classification based on associations (CBA), multi-class classification based on association rules (MCAR), expert multi-class classification based on association rules (EMCAR), and fast associative classification algorithm (FACA). The results of the experiments showed that the HAC approach produced higher classification accuracy than MCAR, CBA, EMCAR, FACA, J48 and NB with gains of 3.95%, 6.58%, 3.48%, 1.18%, 5.37% and 8.05% respectively. Furthermore, on Reuters-21578 datasets, the results indicated that the HAC algorithm has an excellent and stable performance in terms of classification accuracy and F measure.

Implementing Risk Management Processes into a Cloud Computing Environment

With the significant advances in Information and Communications Technology ICT over the last half a century, the Cloud computing paradigm is one of the most discussed topics in the field of ICT today. Additionally, Cloud computing has a critical role in todays business world. Without risk management processes embedded into innovative technology that supports Cloud computing, businesses are setting themselves up for a fall. Hence, in this paper, the authors propose a conceptual model of implementing risk management processes into a Cloud computing environment. It highlights the different processes of risk management risk identification, risk analysis, risk planning, risk execution, and risk monitoring and how their existence can affect the Cloud environment to ensure proper protection of data and information in order to ensure Cloud networks and connections are secure.