40 research outputs found

    Advancing digital transformation: Integrated digital transformation framework for a successful deployment

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    © 2019, IEOM Society International. In today\u27s knowledge-based digital economy, the pace of innovation is accelerating with disruptive technologies being discovered and introduced rapidly. The new global business environment has pressured many organizations to be more aggressive in adopting innovation and emerging technologies and use them as the cornerstone of their competitive strategy. Moreover, changing customer behavior, demand and requirement have led to complex changes and created an urgency to digitally transform an organization. In such an environment, rapid transformation is needed to accelerate and innovate business activities, business processes, models, and, ultimately, the workforce competencies. In such a situation, many c-suite executives are facing various challenges such as rigid processes, risk avoidance, digital disruption, interdepartmental conflict, disinterest in new ideas and complacency to move forward. These challenges require a vastly different approach to digitally transform a company\u27s business. The objective of this paper is to propose an integrated digital transformation framework by integrating the business-need space (model elements), problem space (design thinking), solution space (Waterfall, agile) and change management space methods for a successful digital transformation deployment

    A reference framework for enterprise computing curriculum

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    © Springer International Publishing AG 2017. An increasing number of universities are offering one form or another of Enterprise Computing (EC) program, while simultaneously a number of enterprises in the private and public sectors have articulated needs for graduates with knowledge in enterprise applications, analytical skills and competencies. The programs often are structured by the knowledge of their faculty and in collaboration with Enterprise Application Solutions Vendors (EASV) providing solutions in this space. Based on their perception of the educational needs of their primary stakeholders (students, parents, employers, society), both within industry and government. This perception of audience needs is often based on interviews, exchange forums, surveys, and informal assessments. As of now, there is no EC reference curriculum identified by academia or industry. Industry and academia often differ in the definition of the scope of EC curriculum. Consequently, the need for a reference framework for enterprise computing curriculum has often been articulated in a variety of meetings within the enterprise community. The aim of this paper is to propose an EC reference curriculum at the undergraduate level based on the expertise of the authors, a study of the EC program at several local, regional, and international universities, the industry needs of EC competencies and the best practices available in academia and industry

    Building An Integrated Digital Transformation System Framework: A Design Science Research, The Case Of Feduni

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    The purpose of this paper is to propose an integrated digital transformation system framework (IDTSF) to help support business leaders and teams in making their products, services, and operations more streamlined and competitive. The framework will help organizations to best meet user/customer needs with minimum waste and time and enables businesses to achieve efficiency compared with island and traditional sequential approaches. The proposed framework can also provide insights to help organizations to avoid common failures when deploying digital transformation initiatives. The paper follows the design science research (DSR) and the information systems design science research (ISDSR) methodologies to develop the IDTSF model and a practical design artifact. The main problems were the initiation, execution, and governance challenges associated with digital transformation. After identifying the problems and the objectives, a relevant IDTSF model was synthesized and tested as a design artifact. The results of the test of the proposed artifact showed its effectiveness and efficiency in facilitating the components of the model in creating a cohesive framework

    REQUIREMENT ANALYSIS FOR PROCESS-CENTRIC CONTINUOUS MONITORING

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    With the emergence of mission-critical real-time systems becoming ever more important to the competitive strategies of corporations and their e-business and supply-chain models, an increasing number of process controls are being embedded into information systems, and co-processed with business transaction thus providing for the continuous monitoring of business operations. A parallel trend in the auditing industry is towards continuous auditing, able to provide management with real-time auditing of the functioning of controls and of business transactions, thus enhancing significantly management’s ability to ensure compliance and make key business decisions. Continuous auditing requires that information systems are developed not only to fulfill business requirements but also continuous monitoring of transactions and other compliance and control requirements. This integration of business systems and their controls within a process-centric logic necessitates a likewise integration of their development processes. Subsequently existing tools and techniques for requirements analysis need to be recast within a hybrid and integrated approach dubbed requirement analysis for process-centric continuous monitoring or RA-PCCM, which consists of the concurrent analysis of operational systems, information systems, the control system, and the management system. Whilst efforts exist within the auditing community to outline a process-driven methodology for developing continuous auditing systems, this paper argues for integrating control development for continuous monitoring within the fold of information system development, hence restricting auditors to control monitoring assurance

    Screening of Murabaha business process through Quran and hadith: a text mining analysis

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    © 2020, Emerald Publishing Limited. Purpose: This paper revolves around the usage of data analytics in the Qur’an and Hadith through a new text mining technique to answer the main research question of whether the activities and the data flows of the Murabaha financing contract is compatible with Sharia law. The purpose of this paper is to provide a thorough and comprehensive database that will be used to examine existing practices in Islamic banks’ and improve compliancy with Islamic financial law (Sharia). Design/methodology/approach: To design a Sharia-compliant Murabaha business process originated on text mining, the authors start by identifying the factors deemed necessary in their text mining techniques of both texts; using a four-step strategy to analyze those text mining analytics; then, they list the three basic approaches in text mining used for new knowledge discovery in databases: the co-occurrence approach based on the recursive co-occurrence algorithm; the machine learning or statistical-based; and the knowledge-based. They identify any variation and association between the Murabaha business processes produced using text mining against the one developed through data collection. Findings: The main finding attained in this paper is to confirm the compatibility of all activities and the data flows in the Murabaha financing contract produced using data analytics of the Quran and Hadith texts against the Murabaha business process that was developed based on data collection. Another key finding is revealing some shortcomings regarding Islamic banks business process compliance with Sharia law. Practical implications: Given Murabaha as the most popular mode of Islamic financing with more than 75% in total transactions, this research has managed to touch-base on an area that is interesting to the vast majority of those dealing with Islamic finance instruments. By reaching findings that could improve the existing Islamic Murabaha business process and concluding on Sharia compliance of the existing Murabaha business process, this research is quite relevant and could be used in practice as well as in influencing public policy. In fact, Islamic Sharia law experts, Islamic finance professionals and Islamic banks may find the results of this study very useful in improving at least one aspect of the Islamic finance transactions. Originality/value: By using a novel, fresh text mining methods built on recursive occurrence of synonym words from the Qur’an and Hadith to enrich Islamic finance, this research study can claim to have been the first of its kind in using machine learning to mine the Quran, Hadith and in extracting valuable knowledge to support and consolidate the Islamic financial business processes and make them more compliant with the i

    Developing Adaptive Islamic Law Business Processes Models for Islamic Finance and Banking by Text Mining the Holy Qur\u27an and Hadith

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    © 2017 IEEE. A large number of conventional financial institutions, especially banks are moving to an Islamic financial model that\u27s comply with the Shari\u27a Law with little change to current conventional practices (reverse eningineer current business processes) to accommodate the market for Islamic finance. This study is an attempt to design and develop the business processes for the Islamic financial institutions\u27 (IFIs) products by investigating and collecting information through Islamic literature, surveys and interviews of experts in Islamic jurisprudence, regulators, academic and Islamic finance and banking practitioners. Then the findings will be assessed and evaluated using a Qur\u27anic Financial Corpus and use computational and analytical approaches to mine the Qur\u27an and the Hadith to find hidden knowledge on Islamic financial business processes. The knowledge acquired from this investigation will be translated into an Islamic financial process model to be adapted by Islamic and non-Islamic financial institutions. The outcome of this research will influence the future development, growth and diversification of Islamic financial services worldwide

    Developing Adaptive Islamic Law Business Processes Models for Islamic Finance and Banking by Text Mining the Holy Quran and Hadith.

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    Global Islamic finance assets grew from 200billionto200 billion to 1.8 trillion (IMF 2015) and is growing faster than the conventional banking sector. A large number of conventional financial institutions, especially banks are moving to an Islamic financial model that\u27s comply with the Shari\u27a Law with little change to current conventional practices (reverse eningineer current business processes) to accommodate the new situation. In this study we will design and develop the business processes for the Islamic financial institutions\u27 (IFIs) products by investigating and collecting information through Islamic literature, surveys and interviews of experts in Islamic jurisprudence, regulators, academic and Islamic finance and banking practitioners. Then we will assess and evaluate the findings by using a Qur\u27anic Financial Corpus and use computational and analytical approaches to mine the Qur\u27an (the Muslim Holy book) and the Hadith (actions and words of the prophet Muhammad peace be upon him) to uncover hidden knowledge on Islamic financial business processes. The knowledge acquired from this investigation will be translated into an Islamic financial process model to be adapted by Islamic and non-Islamic financial institutions. The outcome of this research will influence the future development, growth and diversification of Islamic Financial Services worldwid

    Modelling customers credit card behaviour using bidirectional LSTM neural networks

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    With the rapid growth of consumer credit and the huge amount of financial data developing effective credit scoring models is very crucial. Researchers have developed complex credit scoring models using statistical and artificial intelligence (AI) techniques to help banks and financial institutions to support their financial decisions. Neural networks are considered as a mostly wide used technique in finance and business applications. Thus, the main aim of this paper is to help bank management in scoring credit card clients using machine learning by modelling and predicting the consumer behaviour with respect to two aspects: the probability of single and consecutive missed payments for credit card customers. The proposed model is based on the bidirectional Long-Short Term Memory (LSTM) model to give the probability of a missed payment during the next month for each customer. The model was trained on a real credit card dataset and the customer behavioural scores are analysed using classical measures such as accuracy, Area Under the Curve, Brier score, Kolmogorov–Smirnov test, and H-measure. Calibration analysis of the LSTM model scores showed that they can be considered as probabilities of missed payments. The LSTM model was compared to four traditional machine learning algorithms: support vector machine, random forest, multi-layer perceptron neural network, and logistic regression. Experimental results show that, compared with traditional methods, the consumer credit scoring method based on the LSTM neural network has significantly improved consumer credit scoring

    Using Deep Learning Model to Identify Iron Chlorosis in Plants

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    Iron deficiency in plants causes iron chlorosis which frequently occurs in soils that are alkaline (pH greater than 7.0) and that contain lime. This deficiency turns affected plant leaves to yellow, or with brown edges in advanced stages. The goal of this research is to use the deep learning model to identify a nutrient deficiency in plant leaves and perform soil analysis to identify the cause of the deficiency. Two pre-trained deep learning models, Single Shot Detector (SSD) MobileNet v2 and EfficientDet D0, are used to complete this task via transfer learning. This research also contrasts the architecture and performance of the models at each stage and freezes the models for future use. Classification accuracy ranged from 93% to 98% for the SSD Mobilenet v2 model. Although this model took less time to process, its accuracy level was lower. While the EfficientDet D0 model required more processing time, it provided very high classification accuracy for the photos, ranging from 87% to 98.4%. These findings lead to the conclusion that both models are useful for real-time classifications, however, the EfficientDet D0 model may perform significantly better

    Assessing IT disaster recovery plans the case of publicly listed firms on Abu Dhabi/UAE security exchange

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    © 2016 Emerald Group Publishing Limited. Purpose - This purpose of this paper is to assess information technology (IT) disaster recovery plans (DRPs) in publicly listed companies on Abu Dhabi securities exchange (ADX) in the United Arab Emirates. The authors assessed, among other things, DRP preparedness, documentation, employees\u27 preparedness and awareness and the most significant physical and logical risks that pose the most threads to drive the development of the DRP, etc. Design/methodology/approach - The authors surveyed publicly listed companies on the ADX using a questionnaire adapted from past research papers as well as from audit programs published by the Information Systems Audit and Control Association. The surveys were completed through interviews with middle and senior management familiar with their firm\u27s IT practices. Findings - The majority of the respondents reported having a DRP, and a significant number of the respondents reported that their top management were extremely committed to their DRP. Employees were generally aware of their role and the existence of the DRP. The greatest risk/threat to their organization\u27s IT system was logical risk followed closely by power and network connectivity loss as the second highest physical risk. The most highly ranked consequence of an IT disaster was loss of confidence in the organization. Research limitations/implications - Because this paper only examined publicly listed companies on ADX, the research results may lack generality. Therefore, further research is needed in this area for determining the extent of the deployment of the DRP in the region. Practical implications - Results of this paper could be used for IT DRP planning bench-marking purposes. Originality/value - This paper adds value to research by investigating the current IT DRP practices by public companies listed on ADX
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