The systematic construction of information systems

Process modelling is a vital issue for communicating with experts of the application domain. Depending on the roles and responsibilities of the application domain experts involved, process models are discussed on different levels of abstraction. These may range from detailed regulation for process execution to the interrelation of basic core processes on a strategic level. To ensure consistency and to allow for a flexible integration of process information on different levels of abstraction, we introduce a transformational calculus that allows the incremental addition to and refinement of the information in a process model, while maintaining the validity of more abstract high level processes. A complete formal treatment of model and the calculus is given and is illustrated on a small banking example.Funding received from the UK Engineering and Physical Sciences Research Council (EPSRC) through the Research Grant GR/M/0258

Onshore to near-shore outsourcing transitions: unpacking tensions

This study is directed towards highlighting tensions of incoming and outgoing vendors during outsourcing in a near-shore context. Incoming-and-outgoing of vendors generate a complex form of relationship in which the participating organizations cooperate and compete simultaneously. It is of great importance to develop knowledge about this kind of relationship typically in the current GSE-related multi-sourcing environment. We carried out a longitudinal case study and utilized data from the 'Novo pay' project, which is available in the public domain. This project involved an outgoing New Zealand based vendor and incoming Australian based vendor. The results show that the demand for the same human resources, dependency upon cooperation and collaboration between vendors, reliance on each other system's configurations and utilizing similar strategies by the client, which worked for the previous vendor, generated a set of tensions which needed to be continuously managed throughout the project

BI-based Organizations: A Sensemaking Perspective

Business intelligence (BI) offers opportunities for managers to master vast data resources for operational and strategic gains, and allows BI-based organizations to generate significant business value. While several researchers emphasized the importance of BI to assist making quality decisions, no study explored the use of BI for improved understanding of business before such decisions are made and assessing the impact of the actions derived from these decisions. To fill this gap we use the theory of organizational sensemaking. The presented research uses hermeneutic phenomenology to study the experiences of decision-makers in using BI-generated insights to guide their actions while altering business processes, structures and information. The study emphasizes the necessity of using BI in the creation and maintenance of individual and organizational identity, as well as, enactment of this identity on the business and its environment, which need to be moulded in response to changing circumstances

A service oriented architecture to implement clinical guidelines for evidence-based medical practice

Health information technology (HIT) has been identified as the fundamental driver to streamline the healthcare delivery processes to improve care quality and reduce operational costs. Of the many facets of HIT is Clinical Decision Support (CDS) which provides the physician with patient-specific inferences, intelligently filtered and organized, at appropriate times. This research has been conducted to develop an agile solution to Clinical Decision Support at the point of care in a healthcare setting as a potential solution to the challenges of interoperability and the complexity of possible solutions. The capabilities of Business Process Management (BPM) and Workflow Management systems are leveraged to support a Service Oriented Architecture development approach for ensuring evidence based medical practice. The aim of this study is to present an architecture solution that is based on SOA principles and embeds clinical guidelines within a healthcare setting. Since the solution is designed to implement real life healthcare scenarios, it essentially supports evidence-based clinical guidelines that are liable to change over a period of time. The thesis is divided into four parts. The first part consists of an Introduction to the study and a background to existing approaches for development and integration of Clinical Decision Support Systems. The second part focuses on the development of a Clinical Decision Support Framework based on Service Oriented Architecture. The CDS Framework is composed of standards based open source technologies including JBoss SwitchYard (enterprise service bus), rule-based CDS enabled by JBoss Drools, process modelling using Business Process Modelling and Notation. To ensure interoperability among various components, healthcare standards by HL7 and OMG are implemented. The third part provides implementation of this CDS Framework in healthcare scenarios. Two scenarios are concerned with the medical practice for diagnosis and early intervention (Chronic Obstructive Pulmonary Disease and Lung Cancer), one case study for Genetic data enablement of CDS systems (New born screening for Cystic Fibrosis) and the last case study is about using BPM techniques for managing healthcare organizational perspectives including human interaction with automated clinical workflows. The last part concludes the research with contributions in design and architecture of CDS systems. This thesis has primarily adopted the Design Science Research Methodology for Information Systems. Additionally, Business Process Management Life Cycle, Agile Business Rules Development methodology and Pattern-Based Cycle for E-Workflow Design for individual case studies are used. Using evidence-based clinical guidelines published by UK’s National Institute of Health and Care Excellence, the integration of latest research in clinical practice has been employed in the automated workflows. The case studies implemented using the CDS Framework are evaluated against implementation requirements, conformance to SOA principles and response time using load testing strategy. For a healthcare organization to achieve its strategic goals in administrative and clinical practice, this research has provided a standards based integration solution in the field of clinical decision support. A SOA based CDS can serve as a potential solution to complexities in IT interventions as the core data and business logic functions are loosely coupled from the presentation. Additionally, the results of this this research can serve as an exemplar for other industrial domains requiring rapid response to evolving business processes

Artificial intelligence and knowledge sharing: Contributing factors to organizational performance

The evolution of organizational processes and performance over the past decade has been largely enabled by cutting-edge technologies such as data analytics, artificial intelligence (AI), and business intelligence applications. The increasing use of cutting-edge technologies has boosted effectiveness, efficiency and productivity, as existing and new knowledge within an organization continues to improve AI abilities. Consequently, AI can identify redundancies within business processes and offer optimal resource utilization for improved performance. However, the lack of integration of existing and new knowledge makes it problematic to ascertain the required nature of knowledge needed for AI’s ability to optimally improve organizational performance. Hence, organizations continue to face reoccurring challenges in their business processes, competition, technological advancement and finding new solutions in a fast-changing society. To address this knowledge gap, this study applies a fuzzy set-theoretic approach underpinned by the conceptualization of AI, knowledge sharing (KS) and organizational performance (OP). Our result suggests that the implementation of AI technologies alone is not sufficient in improving organizational performance. Rather, a complementary system that combines AI and KS provides a more sustainable organizational performance strategy for business operations in a constantly changing digitized society

Artificial intelligence and knowledge sharing: Contributing factors to organizational performance

The evolution of organizational processes and performance over the past decade has been largely enabled by cutting-edge technologies such as data analytics, artificial intelligence (AI), and business intelligence applications. The increasing use of cutting-edge technologies has boosted effectiveness, efficiency and productivity, as existing and new knowledge within an organization continues to improve AI abilities. Consequently, AI can identify redundancies within business processes and offer optimal resource utilization for improved performance. However, the lack of integration of existing and new knowledge makes it problematic to ascertain the required nature of knowledge needed for AI’s ability to optimally improve organizational performance. Hence, organizations continue to face reoccurring challenges in their business processes, competition, technological advancement and finding new solutions in a fast-changing society. To address this knowledge gap, this study applies a fuzzy set-theoretic approach underpinned by the conceptualization of AI, knowledge sharing (KS) and organizational performance (OP). Our result suggests that the implementation of AI technologies alone is not sufficient in improving organizational performance. Rather, a complementary system that combines AI and KS provides a more sustainable organizational performance strategy for business operations in a constantly changing digitized society

Artificial intelligence and knowledge sharing: Contributing factors to organizational performance

The evolution of organizational processes and performance over the past decade has been largely enabled by cutting-edge technologies such as data analytics, artificial intelligence (AI), and business intelligence applications. The increasing use of cutting-edge technologies has boosted effectiveness, efficiency and productivity, as existing and new knowledge within an organization continues to improve AI abilities. Consequently, AI can identify redundancies within business processes and offer optimal resource utilization for improved performance. However, the lack of integration of existing and new knowledge makes it problematic to ascertain the required nature of knowledge needed for AI’s ability to optimally improve organizational performance. Hence, organizations continue to face reoccurring challenges in their business processes, competition, technological advancement and finding new solutions in a fast-changing society. To address this knowledge gap, this study applies a fuzzy set-theoretic approach underpinned by the conceptualization of AI, knowledge sharing (KS) and organizational performance (OP). Our result suggests that the implementation of AI technologies alone is not sufficient in improving organizational performance. Rather, a complementary system that combines AI and KS provides a more sustainable organizational performance strategy for business operations in a constantly changing digitized society