Business Commons^™

Transforming Business Using Digital Innovations: The Application Of Ai, Blockchain, Cloud And Data Analytics, Shahriar Akter, Katina Michael, Muhammad Rajib Uddin, Grace Mccarthy, Mahfuzur Rahman

Sydney Business School - Papers

This study explores digital business transformation through the lens of four emerging technology fields: artificial intelligence, blockchain, cloud and data analytics (i.e., ABCD). Specifically, the study investigates the operations and value propositions of these distinct but increasingly converging technologies. Due to the dynamic nature of innovation, the potential of this ABCD hybridization, integration, recombination and convergence has yet to be considered. Using a multidisciplinary approach, the findings of the study show wide-reaching and diverse applications among a variety of vertical sectors, presenting exploratory research avenues for future investigation. The study also highlights the practical implications of these new technologies.

Improving National Hospice/Palliative Care Service Symptom Outcomes Systematically Through Point-Of-Care Data Collection, Structured Feedback And Benchmarking, David Currow, Samuel Allingham, Patsy Yates, Claire Johnson, Katherine Clark, Kathy Eagar

Sydney Business School - Papers

Purpose Every health care sector including hospice/palliative care needs to systematically improve services using patient-defined outcomes. Data from the national Australian Palliative Care Outcomes Collaboration aims to define whether hospice/palliative care patients' outcomes and the consistency of these outcomes have improved in the last 3 years.

Methods Data were analysed by clinical phase (stable, unstable, deteriorating, terminal). Patient-level data included the Symptom Assessment Scale and the Palliative Care Problem Severity Score. Nationally collected point-of-care data were anchored for the period July-December 2008 and subsequently compared to this baseline in six 6-month reporting cycles for all services that submitted data in …

A New Approach For Considering A Dual-Role Factor In Data Envelopment Analysis, Abdollah Noorizadeh, Mahdi Mahdiloo, Reza Farzipoor Saen

Sydney Business School - Papers

The conventional data envelopment analysis models deal with dualrole factor as non-discretionary (uncontrollable) factor. However, there might be dual-role factor which is under control of decision-maker. In addition, despite the fact that there are several publications addressing dual-role factors, it seems that their idea of classifying a factor as an input or an output within a single model has a limitation. They also do not consider non-zero input and output slacks and cannot fully measure the inefficiency of decision-making units. To resolve these limitations and to consider dual-role factor as well, this paper proposes a slacks-based measure model which does …

A Novel Data Envelopment Analysis Model For Solving Supplier Selection Problems With Undesirable Outputs And Lack Of Inputs, Mahdi Mahdiloo, Reza Farzipoor Saen, Madjid Tavana

Sydney Business School - Papers

Supplier evaluation and selection problems are inherently multi-criteria decision problems. Numerous analytical techniques ranging from simple weighted scoring to complex mathematical programming approaches have been proposed to solve these problems. Data Envelopment Analysis (DEA) has been used to evaluate suppliers' performance when there are multiple inputs and outputs in the supplier selection problem. The DEA determines the relative efficiencies of multiple suppliers. These relative efficiencies are then used to provide benchmarking data for reducing the number of suppliers. The DEA models used for supplier selection require numerical data for all the inputs and outputs for all the suppliers. However, this …

A Data Envelopment Analysis Model For Selecting Suppliers In The Presence Of Both Dual-Role Factors And Non-Discretionary Inputs, Abdollah Noorizadeh, Mahdi Mahdiloo, Reza Farzipoor Saen

Sydney Business School - Papers

Supplier selection is the strategy adopted by the manufacturer, to evaluate and select suppliers, which can fulfil the requirements of the manufacturer. To this end, data envelopment analysis (DEA), as a multiple criteria decision-making tool, has been applied for several times. However, conventional DEA models cannot simultaneously consider dual-role and non-discretionary factors. The objective of this paper is to propose a DEA model for ranking suppliers in the presence of both dual-role factors and non-discretionary inputs. A numerical example demonstrates the application of the proposed model. 2012 Inderscience Enterprises Ltd.

Designing A Faecal Incontinence Instrument Using Survey Data, Janet E. Sansoni, Nicholas Marosszeky, Emily Sansoni, Graeme Hawthorne

Sydney Business School - Papers

The development of instruments for the measurement of faecal incontinence symptoms and quality of life impact is at an early stage in psychometric terms (Thomas et al., 2006). The absence of large scale studies and clinical data makes the selection of reliable and valid measures difficult. Issues surrounding the actual content of questionnaires and scoring systems are also hotly debated. Some of these issues include: What do you mean by the severity of symptoms (Flatus, Liquid, or Solid Stool)? How do you measure the frequency of symptoms? Do you include questions about the use of pads? Do you ask questions …

Stroke Outcomes In Australia - Five Years Of Aroc Data, Tara L. Stevermuer

Sydney Business School - Papers

Introduction: Many stroke patients, although initially managed in an acute care setting, are admitted to a designated rehabilitation facility. This facility could be a ward in the same acute hospital as their initial treatment, or a ward in a sub-acute hospital. Where the patient receives treatment that meets the AN-SNAP definition of rehabilitation (refer “Definition of Rehabilitation” box) and the facility providing that treatment is a member of the Australasian Rehabilitation Outcomes Centre (AROC), information on their episode of care is reported to the national rehabilitation database held by AROC.

The Time Controlled Clustering Algorithm For Optimised Data Dissemination In Wireless Sensor Networks, S. Selvakennedy, Sukunesan Sinnappan

Sydney Business School - Papers

As the communication task is a significant power consumer, there are many attempts to improve energy efficiency. Node clustering, to reduce direct transmission to the base station, is one such attempt to control data dissemination. Here, we derived the optimal number of clusters for TCCA clustering algorithm based on a realistic energy model using results in stochastic geometry.