The integrity of digital technologies in the evolving characteristics of real-time enterprise architecture

Advancements in interactive and responsive enterprises involve real-time access to the information and capabilities of emerging technologies. Digital technologies (DTs) are emerging technologies that provide end-to-end business processes (BPs), engage a diversified set of real-time enterprise (RTE) participants, and institutes interactive DT services. This thesis offers a selection of the author’s work over the last decade that addresses the real-time access to changing characteristics of information and integration of DTs. They are critical for RTEs to run a competitive business and respond to a dynamic marketplace. The primary contributions of this work are listed below. • Performed an intense investigation to illustrate the challenges of the RTE during the advancement of DTs and corresponding business operations. • Constituted a practical approach to continuously evolve the RTEs and measure the impact of DTs by developing, instrumenting, and inferring the standardized RTE architecture and DTs. • Established the RTE operational governance framework and instituted it to provide structure, oversight responsibilities, features, and interdependencies of business operations. • Formulated the incremental risk (IR) modeling framework to identify and correlate the evolving risks of the RTEs during the deployment of DT services. • DT service classifications scheme is derived based on BPs, BP activities, DT’s paradigms, RTE processes, and RTE policies. • Identified and assessed the evaluation paradigms of the RTEs to measure the progress of the RTE architecture based on the DT service classifications. The starting point was the author’s experience with evolving aspects of DTs that are disrupting industries and consequently impacting the sustainability of the RTE. The initial publications emphasized innovative characteristics of DTs and lack of standardization, indicating the impact and adaptation of DTs are questionable for the RTEs. The publications are focused on developing different elements of RTE architecture. Each published work concerns the creation of an RTE architecture framework fit to the purpose of business operations in association with the DT services and associated capabilities. The RTE operational governance framework and incremental risk methodology presented in subsequent publications ensure the continuous evolution of RTE in advancements of DTs. Eventually, each publication presents the evaluation paradigms based on the identified scheme of DT service classification to measure the success of RTE architecture or corresponding elements of the RTE architecture

Smart Systems:The Role of Advanced Technologies in Improving Business Quality, Performance and Supply Chain Integration

Technologies such as the Internet of Things (IoT), cloud computing, and Smart Systems (SSs) have become an important focus for industry, especially in the manufacturing and retail sectors. The aim of this paper is to analyse the importance of SSs and their related technologies in improving business performance. Through an initial systematic review of sixty-one papers, the authors identify six key determinants that lead to the effective application of SSs in business systems, namely, the application of effective managerial skills, supply chain integration, financial analysis, business performance, strategic and operational capabilities, and technologies. The work then goes on to develop an industry case study that informs thinking on the capabilities of smart technologies in collaborative working environments and then onto the development of a practice-focused framework for future research. This study identifies that the implementation of SSs within organisations not only improves business performance but also their supply chains through the effective integration of business activities and systems, and through the degree to which communication and decision-making is facilitated between humans and devices. This leads to the improvement of quality, speed of information, and information sharing. This study also finds that there is a lack of systems standards that currently govern IoT and SSs integration and data security within businesses

Smart Systems:The Role of Advanced Technologies in Improving Business Quality, Performance and Supply Chain Integration

Technologies such as the Internet of Things (IoT), cloud computing and Smart Systems (SS) have become an important focus for industry, especially in the manufacturing and retail sectors. The aim of this paper is to analyse the importance of SS and their re-lated technologies towards improving business performance. Through an initial systematic review of sixty-one papers, the authors identify six key determinants that lead to the effective application of SS in business systems namely; application of effective managerial skills, supply chain integration, financial analysis, business performance, strategic/operational capabilities and, technologies. The work then goes on to develop an industry case study that informs thinking on the capabilities of smart technologies in collaborative working environments and then onto the development of a practice focused framework for future research. This study identifies that the implementation of SS within organisations not only improves business performance but their supply chains too through the effective integration of business activities and systems and, through the degree to which communication and decision-making is being facilitated between humans and devices. This leads to the improvement of quality, speed of information and, information sharing. The study also finds that there is a lack of systems standards that currently govern IoT/SS integration and data security within businesses

Exploring fine-grained sentiment values in online product reviews

We hypothesise that it is possible to determine a fine-grained set of sentiment values over and above the simple three-way positive/neutral/negative or binary Like/Dislike distinctions by examining textual formatting features. We show that this is possible for online comments about ten different categories of products. In the context of online shopping and reviews, one of the ways to analyse consumers' feedback is by analysing comments. The rating of the ???like??? button on a product or a comment is not sufficient to understand the level of expression. The expression of opinion is not only identified by the meaning of the words used in the comments, nor by simply counting the number of ???thumbs up???, but it also includes the usage of capital letters, the use of repeated words, and the usage of emoticons. In this paper, we investigate whether it is possible to expand up to seven levels of sentiment by extracting such features. Five hundred questionnaires were collected and analysed to verify the level of ???like??? and ???dislike??? value. Our results show significant values on each of the hypotheses. For consumers, reading reviews helps them make better purchase decisions but we show there is also value to be gained in a finer-grained sentiment analysis for future commercial website platforms

A hybrid recommendation approach for a tourism system

Many current e-commerce systems provide personalization when their content is shown to users. In this sense, recommender systems make personalized suggestions and provide information of items available in the system. Nowadays, there is a vast amount of methods, including data mining techniques that can be employed for personalization in recommender systems. However, these methods are still quite vulnerable to some limitations and shortcomings related to recommender environment. In order to deal with some of them, in this work we implement a recommendation methodology in a recommender system for tourism, where classification based on association is applied. Classification based on association methods, also named associative classification methods, consist of an alternative data mining technique, which combines concepts from classification and association in order to allow association rules to be employed in a prediction context. The proposed methodology was evaluated in some case studies, where we could verify that it is able to shorten limitations presented in recommender systems and to enhance recommendation quality

Cloud-computing strategies for sustainable ICT utilization : a decision-making framework for non-expert Smart Building managers

Virtualization of processing power, storage, and networking applications via cloud-computing allows Smart Buildings to operate heavy demand computing resources off-premises. While this approach reduces in-house costs and energy use, recent case-studies have highlighted complexities in decision-making processes associated with implementing the concept of cloud-computing. This complexity is due to the rapid evolution of these technologies without standardization of approach by those organizations offering cloud-computing provision as a commercial concern. This study defines the term Smart Building as an ICT environment where a degree of system integration is accomplished. Non-expert managers are highlighted as key users of the outcomes from this project given the diverse nature of Smart Buildings’ operational objectives. This research evaluates different ICT management methods to effectively support decisions made by non-expert clients to deploy different models of cloud-computing services in their Smart Buildings ICT environments. The objective of this study is to reduce the need for costly 3rd party ICT consultancy providers, so non-experts can focus more on their Smart Buildings’ core competencies rather than the complex, expensive, and energy consuming processes of ICT management. The gap identified by this research represents vulnerability for non-expert managers to make effective decisions regarding cloud-computing cost estimation, deployment assessment, associated power consumption, and management flexibility in their Smart Buildings ICT environments. The project analyses cloud-computing decision-making concepts with reference to different Smart Building ICT attributes. In particular, it focuses on a structured programme of data collection which is achieved through semi-structured interviews, cost simulations and risk-analysis surveys. The main output is a theoretical management framework for non-expert decision-makers across variously-operated Smart Buildings. Furthermore, a decision-support tool is designed to enable non-expert managers to identify the extent of virtualization potential by evaluating different implementation options. This is presented to correlate with contract limitations, security challenges, system integration levels, sustainability, and long-term costs. These requirements are explored in contrast to cloud demand changes observed across specified periods. Dependencies were identified to greatly vary depending on numerous organizational aspects such as performance, size, and workload. The study argues that constructing long-term, sustainable, and cost-efficient strategies for any cloud deployment, depends on the thorough identification of required services off and on-premises. It points out that most of today’s heavy-burdened Smart Buildings are outsourcing these services to costly independent suppliers, which causes unnecessary management complexities, additional cost, and system incompatibility. The main conclusions argue that cloud-computing cost can differ depending on the Smart Building attributes and ICT requirements, and although in most cases cloud services are more convenient and cost effective at the early stages of the deployment and migration process, it can become costly in the future if not planned carefully using cost estimation service patterns. The results of the study can be exploited to enhance core competencies within Smart Buildings in order to maximize growth and attract new business opportunities