Enterprise modelling framework for dynamic and complex business environment: socio-technical systems perspective

The modern business environment is characterised by dynamism and ambiguity. The causes include global economic change, rapid change requirements, shortened development life cycles and the increasing complexity of information technology and information systems (IT/IS). However, enterprises have been seen as socio-technical systems. The dynamic complex business environment cannot be understood without intensive modelling and simulation. Nevertheless, there is no single description of reality, which has been seen as relative to its context and point of view. Human perception is considered an important determinant for the subjectivist view of reality. Many scholars working in the socio-technical systems and enterprise modelling domains have conceived the holistic sociotechnical systems analysis and design possible using a limited number of procedural and modelling approaches. For instance, the ETHICS and Human-centred design approaches of socio-technical analysis and design, goal-oriented and process-oriented modelling of enterprise modelling perspectives, and the Zachman and DoDAF enterprise architecture frameworks all have limitations that can be improved upon, which have been significantly explained in this thesis. [Continues.

The Role of IT and Knowledge Management Capabilities in Generating Innovation Knowledge in Telecom Companies

Most organisations moving their legacy systems to the cloud base their decisions on the naïve assumption that public cloud always provides cost savings, without sufficiently assessing the underlying application architecture, and the technical and financial constraints that it imposes on the chosen cloud architecture. This can lead to undesirable consequences including project delays, budget overruns, below-par performance, application instability and creation of technical debt. In this paper, we address the shortcomings of this assumption by proposing a structured yet flexible decision framework comprising models, guidelines, tools and calculators that enables IT and/or business practitioners to make the correct architectural decision between public, private and hybrid cloud, from a functional, non-functional and financial perspective, based on the application architecture. By treating the application architecture as a first-class citizen in the decision making process, our proposed framework ensures that business and technical stakeholders make the correct decision early on in the migration process, resulting in timely deployment and quality-assured provision of critical business functions, minimization of waste, and avoidance of rework. We use a sample scenario to illustrate the need and usefulness of such a decision framework

The Role of Big Data Analytics on Innovation: A Study from The Telecom Industry

Telecom companies face a fierce competition from innovation based start-up companies, particularly those that are using internet networks to offer communication services through the voice and video over internet protocol (VoIP & PVoIP) technologies. More than 10 years have passed from the time the internet and VoIP were widely used, but still, telecom companies are having a great deal of business success through offering a wide spectrum of services, products, deals, and packages to consumers using both B2C and B2B models. The future landscape of how telecom companies will evolve in the market is still not clear, particularly with the increase of aggressive competition from companies that are technology-innovative and starting to deliver new forms of ubiquitous communication technology and services. Understanding why and how telecom companies innovate in the market is very crucial in order to predict the future of this business sector. In this paper, we argue that telecom companies are utilising their capabilities that have a significantly important role in fostering innovation, namely information technology (IT) capability and knowledge management (KM) capability. IT capabilities have changed dramatically in the last few years with the introduction of intelligent systems, big data analytics, the Internet of Things and the wide use of mobile apps and sensors. It is not clear how these technologies play a role in telecom companies’ innovation and it is not clear whether IT impacts innovation directly or if KM capability has a mediation role in utilising technology to support innovation. This paper is a position paper to establish grounds for understanding how telecom companies innovate, and in particular how IT and KM capabilities influence innovation. We outline the methodology of this investigation as a qualitative study with stakeholders from multiple telecom companies and we expect at the end of the study to be able to offer a holistic view on the way these companies innovate in regard to their products and services. We aim at providing a cross case studies comparison towards a prediction of the future of the telecom business sector

Effective Remote Monitoring System for Heart Disease Patients

Despite the advancement that has been seen in all life aspects and in particular in technology, patients still struggle in receiving the care and emergent support they need due to the ever-increasing cost of healthcare services and the increasing number of chronic diseases patients. Information technology can offer promising solutions to 21`st century human, in particularly the what is called internet of things (IoTs) and remote based services. We design and develop a solution where patients can use wearable sensors that can offer a prediction and alerting in their heart disease conditions. The solution seems promising when it is combined with medical profile data, better decisions can be made and alerting of emergency can be timely which can help to save lives. We use data gathered from few number of people to build our analytics and decision model

Toward Securing Cloud-Based Data Analytics:A Discussion on Current Solutions and Open Issues

In the last few years, organizations and business professionals have realized the value of data analytics in supporting decision-making. Where several activities are performed on on-line data by different stakeholders, such as cleansing, aggregation, analysis and visualization, cloud-based data analytics has become a favored choice for business professionals due to the elasticity, availability, scalability, and pay-as-you-go features offered by cloud computing. However, large amounts of data stored on the cloud are very sensitive (e.g., innovation, financial, legal, customers’ data), and so data privacy remains one of the top concerns for many reasons;mainly those relating to legal or competition issues. In this paper, we review the security and cryptographic mechanisms which aim to make data analytics secure in a cloud environment, and discuss current research challenges

The Role of Big Data Analytics in Innovation: A Study from The Telecom Industry

Organisations are looking for new definitions and guidelines for innovation direction due to the changing nature of technology, user behaviour, competition and market trends. Data sources, types and analysis mechanisms have changed dramatically in the last few years, and there are pieces of evidence that these are influencing the level of innovation in a firm. We found that it is very important to explore how telecom companies capture, analyse and make innovation insights from big data. Our review shows a clear scarcity of research on this topic. The study aims to use qualitative methods of both interviews and documents review in three telecom companies in Jordan, with an opportunity to extend the study to different regions and countries. The understanding of how big data and its analysis are carried out by companies will support our effort in building more systematic procedures and guidelines for companies who wish to utilise big data for different types of innovation with different levels of maturity indicators

Towards a Unified Meta-Model for Goal Oriented Modelling

Goal oriented modelling (GOM) is one of the most prominent and widely accepted techniques in information systems research. Since the early 1990’s, a large number of GOM approaches have been proposed aiming to a better alignment between business strategy and the behaviour of supporting systems. Different GOM approaches focus on different activities in the early stages of system development and propose a variety of strategies for reasoning about goals. A number of researchers have stressed the advantages of integrating different GOM techniques, especially in the context of modern global business environments. This is evidenced in the increasing number of publications in this area. However as each GOM language (even versions of the same language) comes with its own syntactic and semantic singularities, such integration requires a number of complicated transformations which is a major obstacle to model and tool interoperability, and prevent wider adoption by practitioners. In order to provide a unified view of GOM, one needs a common understanding of GOM concepts, their semantics and deployment. To this end, this paper proposes a language independent meta-model based on the analysis of eight GOM languages. Generic concepts were identified and a robust semantic definition among these concepts was built in a unified meta-model. We claim that the unified GOM meta-model could help in a) analysing existing goal models in order to provide insights regarding different goal modelling perspectives b) identify semantic similarities / overlaps between existing GOM techniques c) provide the basis for a reference model for GOM

Understanding Online Customer Touchpoints:A Deep Learning Approach to Enhancing Customer Experience in Digital Retail

This study investigates the main touchpoints that customers value most when shopping online and their attitudes towards them, using Ocado's customer reviews as a case study. Employing machine learning and deep learning methods, such as word2vec, CNN-based sentiment models, and embedding-based topic models, the analysis identified seven critical touchpoints across pre-purchase and post-purchase stages. Recommendations were provided regarding promotional opportunities, technology utilization, and customer experience creation, highlighting the need for different strategies based on customer stages in their journey. The findings offer valuable insights for retail companies transitioning to digital platforms, emphasizing the importance of understanding customer needs and prioritizing touchpoints. Future research could explore additional retail companies with various channels and incorporate different types of customer views to provide a broader perspective on touchpoints

Conceptual modeling for the design of intelligent and emergent information systems

A key requirement to today's fast changing economic environment is the ability of organizations to adapt dynamically in an effective and efficient manner. Information and Communication Technologies play a crucially important role in addressing such adaptation requirements. The notion of `intelligent software' has emerged as a means by which enterprises can respond to changes in a reactive manner but also to explore, in a pro-active manner, possibilities for new business models. The development of such software systems demands analysis, design and implementation paradigms that recognize the need for ‘co-development’ of these systems with enterprise goals, processes and capabilities. The work presented in this paper is motivated by this need and to this end it proposes a paradigm that recognizes co-development as a knowledge-based activity. The proposed solution is based on a multi-perspective modeling approach that involves (i) modeling key aspects of the enterprise, (ii) reasoning about design choices and (iii) supporting strategic decision-making through simulations. The utility of the approach is demonstrated though a case study in the field of marketing for a start-up company

Ecosystem-inspired enterprise modelling framework for collaborative and networked manufacturing systems

Rapid changes in the open manufacturing environment are imminent due to the increase of customer demand, global competition, and digital fusion. This has exponentially increased both complexity and uncertainty in the manufacturing landscape, creating serious challenges for competitive enterprises. For enterprises to remain competitive, analysing manufacturing activities and designing systems to address emergent needs, in a timely and efficient manner, is understood to be crucial. However, existing analysis and design approaches adopt a narrow diagnostic focus on either managerial or engineering aspects and neglect to consider the holistic complex behaviour of enterprises in a collaborative manufacturing network (CMN). It has been suggested that reflecting upon ecosystem theory may bring a better understanding of how to analyse the CMN. The research presented in this paper draws on a theoretical discussion with aim to demonstrate a facilitating approach to those analysis and design tasks. This approach was later operationalised using enterprise modelling (EM) techniques in a novel, developed framework that enhanced systematic analysis, design, and business-IT alignment. It is expected that this research view is opening a new field of investigation