A Decision Support System for Investment Evaluation in Information Systems / Information Technology in Public Administration Organisations

Mestrado em Gestão de Sistemas de Informaçãoinfo:eu-repo/semantics/publishedVersio

Critical Success Factors of Alignment between Websites and OCAs in the Manufacturing Industry

In this study, a list containing twelve organizational critical activities (OCAs) of manufacturing industry is found out by the interviews with executives and revision of two experts. The analysis on secondary data and the deeper interviews are carried out to obtain the critical success factors of the alignment between websites and OCAs in the manufacturing industry. Six common critical success factors of the three companies are: Support of Executives, Excellent and Professional Team, Full Communication, Harmonic Website Build Process, Technical Support, and Complete Information System Architecture. Finally, this study hopes that companies in the manufacturing industry can improve the competitiveness according to the result of this study

The Definition of an Assessment Framework for Information Systems Issues for Agile Manufacturing

Information systems are identified as enablers of agile manufacturing. Despite the continuous utilisation of IT/IS applications, there is growing evidence that information technology/systems do not deliver their expected benefits. In this work we investigated three main issues related to information systems: competitive bases-general goals, development and infrastructure. We tested our approach with information gathered from 14 manufacturing companies based in the UK. The results of this work make it possible to link information systems to other dimensions of agility like competitive bases and agility attributes to define an assessment framework

Application of Artificial Neural Networks to Multiple Criteria Inventory Classification

Inventory classification is a very important part of inventory control which represents the technique of operational research discipline. A systematicapproach to the inventory control and classification may have a significant influence on company competitiveness. The paper describes the results obtained by investigating the application of neural networks in multiple criteria inventory classification. Various structures of a back-propagation neural network have been analysed and the optimal one with the minimum Root Mean Square error selected. The predicted results are compared to those obtained by the multiple criteria classification using the analytical hierarchy process

Investigating enterprise resource planning adoption and implementation in service sector organisations

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel UniversityThis thesis investigates Enterprise Resource Planning (ERP) adoption and implementation in Service Sector Organisations (SSOs). ERP is a business management system that has emerged to support organisations to use a system of integrated applications to enhance their Information Technology (IT) infrastructures, enhance business processes and deliver high quality of services. Regardless of the fact that several other sector organisations have adopted and implemented ERP systems, its application in SSOs is rather inadequate. Among other reasons, two core rationales can be attributed to the latter fact – firstly, SSOs lack the sufficient knowledge, expertise and training to implement such sophisticated integrated systems and secondly, the top management lacks the ability to take appropriate decisions for ERP adoption and implementation. However, merely focusing on a number of factors influencing ERP adoption and implementation may not be suffice, as there is a need for a systematic decision-making process for adopting and implementing ERP systems in SSOs. The limited number of ERP systems’ applications in SSOs has resulted in inadequate research in this area with many issues, like its adoption and implementation requiring further exploration. Despite, the implications of ERP systems have yet to be assessed in SSOs, leaving ample scope for relevance and producing a unique piece of research work. Thus, the author demonstrates that it is of high importance to investigate this area within SSOs and contribute towards successful ERP adoption and implementation. This thesis makes a step forward and contributes to the body of knowledge as it: investigates factors influencing the decision-making process for ERP adoption and implementation in SSOs, prioritises the importance of factors influencing ERP adoption and implementation, evaluates ERP lifecycle phases and stages, maps the ERP factors on different phases and stages of the ERP lifecycle, and in doing so, to propose a model for ERP adoption and implementation in SSOs. The author claims that such an ERP adoption and implementation process in SSOs is significant and novel as: it extends established norms for ERP adoption and implementation, by including Analytical Hierarchy Process (AHP) technique for prioritising the importance of factors, thus, facilitating SSOs to produce more robust proposals for ERP adoption and implementation. The author further assess the proposed ERP adoption and implementation model by using a qualitative, interpretive, multiple case study research strategy. Findings from two case studies demonstrate that such a systematic approach contributes towards more robust decisions for ERP adoption and implementation and indicates that it is acceptable by the case study organisations. The thesis proposes, assesses and presents a novel model for ERP adoption and implementation in SSOs and contributes to the body of knowledge by extending the literature.King Abdulaziz University and Saudi Arabia Cultural Burea

Handbook of Computational Intelligence in Manufacturing and Production Management

Artificial intelligence (AI) is simply a way of providing a computer or a machine to think intelligently like human beings. Since human intelligence is a complex abstraction, scientists have only recently began to understand and make certain assumptions on how people think and to apply these assumptions in order to design AI programs. It is a vast knowledge base discipline that covers reasoning, machine learning, planning, intelligent search, and perception building. Traditional AI had the limitations to meet the increasing demand of search, optimization, and machine learning in the areas of large, biological, and commercial database information systems and management of factory automation for different industries such as power, automobile, aerospace, and chemical plants. The drawbacks of classical AI became more pronounced due to successive failures of the decade long Japanese project on fifth generation computing machines. The limitation of traditional AI gave rise to development of new computational methods in various applications of engineering and management problems. As a result, these computational techniques emerged as a new discipline called computational intelligence (CI)

Cyber-physical business systems modelling : advancing Industry 4.0

Abstract: The dynamic digital age drives contemporary multinationals to focus on delivering world-class business solutions with the use of advanced technology. Contemporary multinationals relate to a present-day business primarily engaged to generate profits. These complex multinationals offer value through the manufacture, sale, and management of products and services. Disruptive strategies in operations driven by emerging technological innovations demand continuous business improvements. These insightful opportunities are inclusive of operations, enterprise systems, engineering management, and research. Business sustainability is a strategic priority to deliver exceptional digital solutions. The Fourth Industrial Revolutions (4IR) offer significant technological advancements for total business sustainability. The underlying 4IR technologies include Cyber-Physical Systems (CPS). The collective challenges of a large global business are not easy to predict. CPS protocols deliver sustainable prospects required to integrate and model physical systems in real-time driven by the 4IR implementations. The goal of this thesis is to develop a model (CPS) suitable for self-predicting and to determine ideal operational practice driven by technologies of the 4IR. The model (CPS) seeks a novel tool effective for comprehensive business evaluation and optimisation. The competence of the anticipated tool includes suitability to collaborate current operations and predict the impact of change on a complex business. ..D.Phil. (Engineering Management