Stakeholders' perceptions of data utility in the context of ERP outcomes

A substantial body of literature exists identifying factors contributing to under-performing Enterprise Resource Planning systems (ERPs), including poor communication, lack of executive support and user dissatisfaction (Calisir et al., 2009). Of particular interest is Momoh et al.’s (2010) recent review identifying poor data quality (DQ) as one of nine critical factors associated with ERP failure. DQ is central to ERP operating processes, ERP facilitated decision-making and inter-organizational cooperation (Batini et al., 2009). Crucial in ERP contexts is that the integrated, automated, process driven nature of ERP data flows can amplify DQ issues, compounding minor errors as they flow through the system (Haug et al., 2009; Xu et al., 2002). However, the growing appreciation of the importance of DQ in determining ERP success lacks research addressing the relationship between stakeholders’ requirements and perceptions of ERP DQ, perceived data utility and the impact of users’ treatment of data on ERP outcomes.

ERP stakeholders’ perceptions of data quality and utility

While data quality has been identified as a critical factor associated with enterprise resource planning (ERP) failure, the relationship between ERP stakeholders, the information they require and its relationship to ERP outcomes continues to be poorly understood. Applying stakeholder theory to the problem of ERP performance, we put forward a framework articulating the fundamental differences in the way users differentiate between ERP data quality and utility. We argue that the failure of ERPs to produce significant organisational outcomes can be attributed to conflict between stakeholder groups over whether the data contained within an ERP is of adequate ‘quality’. The framework provides guidance as how to manage data flows between stakeholders, offering insight into each of their specific data requirements. The framework provides support for the idea that stakeholder affiliation dictates the assumptions and core values held by individuals, driving their data needs and their perceptions of data quality and utility.

Preserving utility in social network graph anonymization

To protect from privacy disclosure, the social network graph is modified in order to hide the information that potentially be used to disclose person's identity. However, when the social network graph is changed, it is a great challenge to balance between the privacy gained and the loss of data utility. In this paper, we address this problem. We propose a new graph topological-based metric to improve utility preservation in social network graph anonymization. We compare the proposed approach with the amount-of-edge-change metric that popularly used in most of previous works. Experimental evaluation shows that our approach generates anonymized social network with improved utility preservation.

Utility-aware social network graph anonymization

As the need for social network data publishing continues to increase, how to preserve the privacy of the social network data before publishing is becoming an important and challenging issue. A common approach to address this issue is through anonymization of the social network structure. The problem with altering the structure of the links relationship in social network data is how to balance between the gain of privacy and the loss of information (data utility). In this paper, we address this problem. We propose a utility-aware social network graph anonymization. The approach is based on a new metric that calculates the utility impact of social network link modification. The metric utilizes the shortest path length and the neighborhood overlap as the utility value. The value is then used as a weight factor in preserving structural integrity in the social network graph anonymization. For any modification made to the social network links, the proposed approach guarantees that the distance between vertices in the modified social network stays as close as the original social network graph prior to the modification. Experimental evaluation shows that the proposed metric improves the utility preservation as compared to the number-of-change metric.

Investment incentives and valuation of power sector infrastructure assets with increasing interconnection, intermittency and decarbonisation

This dissertation applies a variety of quantitative methods to electricity and carbon market data, utility company accounts data, capital and operating costs to analyse some of the challenges associated with investment in energy assets. In particular, three distinct research topics are analysed within this general theme: the efficiency of interconnector trading, the optimal sizing of intermittent wind facilities and the impact of carbon pricing on the cost of capital for investors are researched in successive sections.

What Transaction Costs are Acceptable in Life Insurance Products from the Policyholders' Viewpoint?

Purpose - The purpose of this paper is to analyze what transaction costs are acceptable for customers in different investments. In this study, two life insurance contracts, a mutual fund and a risk-free investment, as alternative investment forms are considered. The first two products under scrutiny are a life insurance investment with a point-to-point capital guarantee and a participating contract with an annual interest rate guarantee and participation in the insurer's surplus. The policyholder assesses the various investment opportunities using different utility measures. For selected types of risk profiles, the utility position and the investor's preference for the various investments are assessed. Based on this analysis, the authors study which cost levels can make all of the products equally rewarding for the investor. Design/methodology/approach - The paper notes the risk-neutral valuation calibration using empirical data utility and performance measurement dynamics underlying: geometric Brownian motion numerical examples via Monte Carlo simulation. Findings - In the first step, the financial performance of the various saving opportunities under different assumptions of the investor's utility measurement is studied. In the second step, the authors calculate the level of transaction costs that are allowed in the various products to make all of the investment opportunities equally rewarding from the investor's point of view. A comparison of these results with transaction costs that are common in the market shows that insurance companies must be careful with respect to the level of transaction costs that they pass on to their customers to provide attractive payoff distributions. Originality/value - To the best of the authors' knowledge, their research question - i.e. which transaction costs for life insurance products would be acceptable from the customer's point of view - has not been studied in the above described context so far.

Un modèle rétroactif de réconciliation utilité-confidentialité sur les données d’assurance

Le partage des données de façon confidentielle préoccupe un bon nombre d’acteurs, peu importe le domaine. La recherche évolue rapidement, mais le manque de solutions adaptées à la réalité d’une entreprise freine l’adoption de bonnes pratiques d’affaires quant à la protection des renseignements sensibles. Nous proposons dans ce mémoire une solution modulaire, évolutive et complète nommée PEPS, paramétrée pour une utilisation dans le domaine de l’assurance. Nous évaluons le cycle entier d’un partage confidentiel, de la gestion des données à la divulgation, en passant par la gestion des forces externes et l’anonymisation. PEPS se démarque du fait qu’il utilise la contextualisation du problème rencontré et l’information propre au domaine afin de s’ajuster et de maximiser l’utilisation de l’ensemble anonymisé. À cette fin, nous présentons un algorithme d’anonymat fortement contextualisé ainsi que des mesures de performances ajustées aux analyses d’expérience.

Un modèle rétroactif de réconciliation utilité-confidentialité sur les données d’assurance

Le partage des données de façon confidentielle préoccupe un bon nombre d’acteurs, peu importe le domaine. La recherche évolue rapidement, mais le manque de solutions adaptées à la réalité d’une entreprise freine l’adoption de bonnes pratiques d’affaires quant à la protection des renseignements sensibles. Nous proposons dans ce mémoire une solution modulaire, évolutive et complète nommée PEPS, paramétrée pour une utilisation dans le domaine de l’assurance. Nous évaluons le cycle entier d’un partage confidentiel, de la gestion des données à la divulgation, en passant par la gestion des forces externes et l’anonymisation. PEPS se démarque du fait qu’il utilise la contextualisation du problème rencontré et l’information propre au domaine afin de s’ajuster et de maximiser l’utilisation de l’ensemble anonymisé. À cette fin, nous présentons un algorithme d’anonymat fortement contextualisé ainsi que des mesures de performances ajustées aux analyses d’expérience.

Utility of routine data sources for feedback on the quality of cancer care: an assessment based on clinical practice guidelines

Background Not all cancer patients receive state-of-the-art care and providing regular feedback to clinicians might reduce this problem. The purpose of this study was to assess the utility of various data sources in providing feedback on the quality of cancer care. Methods Published clinical practice guidelines were used to obtain a list of processes-of-care of interest to clinicians. These were assigned to one of four data categories according to their availability and the marginal cost of using them for feedback. Results Only 8 (3%) of 243 processes-of-care could be measured using population-based registry or administrative inpatient data (lowest cost). A further 119 (49%) could be measured using a core clinical registry, which contains information on important prognostic factors (e.g., clinical stage, physiological reserve, hormone-receptor status). Another 88 (36%) required an expanded clinical registry or medical record review; mainly because they concerned long-term management of disease progression (recurrences and metastases) and 28 (11.5%) required patient interview or audio-taping of consultations because they involved information sharing between clinician and patient. Conclusion The advantages of population-based cancer registries and administrative inpatient data are wide coverage and low cost. The disadvantage is that they currently contain information on only a few processes-of-care. In most jurisdictions, clinical cancer registries, which can be used to report on many more processes-of-care, do not cover smaller hospitals. If we are to provide feedback about all patients, not just those in larger academic hospitals with the most developed data systems, then we need to develop sustainable population-based data systems that capture information on prognostic factors at the time of initial diagnosis and information on management of disease progression.

Utility of COI, CAD and morphological data for resolving relationships within the genus Sarcophaga (sensu lato) (Diptera: Sarcophagidae) : a preliminary study

Currently there are ~3000 known species of Sarcophagidae (Diptera), which are classified into 173 genera in three subfamilies. Almost 25% of sarcophagids belong to the genus Sarcophaga (sensu lato) however little is known about the validity of, and relationships between the ~150 (or more) subgenera of Sarcophaga s.l. In this preliminary study, we evaluated the usefulness of three sources of data for resolving relationships between 35 species from 14 Sarcophaga s.l. subgenera: the mitochondrial COI barcode region, ~800. bp of the nuclear gene CAD, and 110 morphological characters. Bayesian, maximum likelihood (ML) and maximum parsimony (MP) analyses were performed on the combined dataset. Much of the tree was only supported by the Bayesian and ML analyses, with the MP tree poorly resolved. The genus Sarcophaga s.l. was resolved as monophyletic in both the Bayesian and ML analyses and strong support was obtained at the species-level. Notably, the only subgenus consistently resolved as monophyletic was Liopygia. The monophyly of and relationships between the remaining Sarcophaga s.l. subgenera sampled remain questionable. We suggest that future phylogenetic studies on the genus Sarcophaga s.l. use combined datasets for analyses. We also advocate the use of additional data and a range of inference strategies to assist with resolving relationships within Sarcophaga s.l.

The utility of survey and administrative data to generate information for research and outcomes-based oral health services development

The aim of this research, which focused on the Irish adult population, was to generate information for policymakers by applying statistical analyses and current technologies to oral health administrative and survey databases. Objectives included identifying socio-demographic influences on oral health and utilisation of dental services, comparing epidemiologically-estimated dental treatment need with treatment provided, and investigating the potential of a dental administrative database to provide information on utilisation of services and the volume and types of treatment provided over time. Information was extracted from the claims databases for the Dental Treatment Benefit Scheme (DTBS) for employed adults and the Dental Treatment Services Scheme (DTSS) for less-well-off adults, the National Surveys of Adult Oral Health, and the 2007 Survey of Lifestyle Attitudes and Nutrition in Ireland. Factors associated with utilisation and retention of natural teeth were analysed using count data models and logistic regression. The chi-square test and the student’s t-test were used to compare epidemiologically-estimated need in a representative sample of adults with treatment provided. Differences were found in dental care utilisation and tooth retention by Socio-Economic Status. An analysis of the five-year utilisation behaviour of a 2003 cohort of DTBS dental attendees revealed that age and being female were positively associated with visiting annually and number of treatments. Number of adults using the DTBS increased, and mean number of treatments per patient decreased, between 1997 and 2008. As a percentage of overall treatments, restorations, dentures, and extractions decreased, while prophylaxis increased. Differences were found between epidemiologically-estimated treatment need and treatment provided for those using the DTBS and DTSS. This research confirms the utility of survey and administrative data to generate knowledge for policymakers. Public administrative databases have not been designed for research purposes, but they have the potential to provide a wealth of knowledge on treatments provided and utilisation patterns.

Use of the child health utility and strengths and difficulties outcome measures in economic evaluations of school-based interventions: data from a cluster-randomised controlled trial in Northern Ireland

Background There is growing evidence linking early social and emotional wellbeing to later academic performance and various health outcomes including mental health. An economic evaluation was designed alongside the Roots of Empathy cluster-randomised trial evaluation, which is a school-based intervention for improving pupils’ social and emotional wellbeing. Exploration of the relevance of the Strengths and Diffi culties Questionnaire (SDQ) and Child Health Utility 9D (CHU9D) in school-based health economic evaluations is warranted. The SDQ is a behavioural screening questionnaire for 4–17-year-old children, consisting of a total diffi culties score, and also prosocial behaviour,
which aims to identify positive aspects of behaviour. The CHU9D is a generic preference-based health-related quality of life instrument for 7–17-year-old children.

The potential utility of age, triage score, and disposition data contained in emergency department electronic records for influenza-like illness surveillance in Montreal

La surveillance de l’influenza s’appuie sur un large spectre de données, dont les données de surveillance syndromique provenant des salles d’urgences. De plus en plus de variables sont enregistrées dans les dossiers électroniques des urgences et mises à la disposition des équipes de surveillance. L’objectif principal de ce mémoire est d’évaluer l’utilité potentielle de l’âge, de la catégorie de triage et de l’orientation au départ de l’urgence pour améliorer la surveillance de la morbidité liée aux cas sévères d’influenza. Les données d’un sous-ensemble des hôpitaux de Montréal ont été utilisées, d’avril 2006 à janvier 2011. Les hospitalisations avec diagnostic de pneumonie ou influenza ont été utilisées comme mesure de la morbidité liée aux cas sévères d’influenza, et ont été modélisées par régression binomiale négative, en tenant compte des tendances séculaires et saisonnières. En comparaison avec les visites avec syndrome d’allure grippale (SAG) totales, les visites avec SAG stratifiées par âge, par catégorie de triage et par orientation de départ ont amélioré le modèle prédictif des hospitalisations avec pneumonie ou influenza. Avant d’intégrer ces variables dans le système de surveillance de Montréal, des étapes additionnelles sont suggérées, incluant l’optimisation de la définition du syndrome d’allure grippale à utiliser, la confirmation de la valeur de ces prédicteurs avec de nouvelles données et l’évaluation de leur utilité pratique.

Utility of real-time decision-making in commercial data stream mining domains

The objective is to measure utility of real-time commercial decision making. It is important due to a higher possibility of mistakes in real-time decisions, problems with recording actual occurrences, and significant costs associated with predictions produced by algorithms. The first contribution is to use overall utility and represent individual utility with a monetary value instead of a prediction. The second is to calculate the benefit from predictions using the utility-based decision threshold. The third is to incorporate cost of predictions. For experiments, overall utility is used to evaluate communal and spike detection, and their adaptive versions. The overall utility results show that with fewer alerts, communal detection is better than spike detection. With more alerts, adaptive communal and spike detection are better than their static versions. To maximise overall utility with all algorithms, only 1% to 4% in the highest predictions should be alerts.