Towards an integrated maturity model of asset management capabilities

Asset service organisations often recognize asset management as a core competence to deliver benefits to their business. But how do organizations know whether their asset management processes are adequate? Asset management maturity models, which combine best practices and competencies, provide a useful approach to test the capacity of organisations to manage their assets. Asset management frameworks are required to meet the dynamic challenges of managing assets in contemporary society. Although existing models are subject to wide variations in their implementation and sophistication, they also display a distinct weakness in that they tend to focus primarily on the operational and technical level and neglect the levels of strategy, policy and governance as well as the social and human resources – the people elements. Moreover, asset management maturity models have to respond to the external environmental factors, including such as climate change and sustainability, stakeholders and community demand management. Drawing on five dimensions of effective asset management – spatial, temporal, organisational, statistical, and evaluation – as identified by Amadi Echendu et al. [1], this paper carries out a comprehensive comparative analysis of six existing maturity models to identify the gaps in key process areas. Results suggest incorporating these into an integrated approach to assess the maturity of asset-intensive organizations. It is contended that the adoption of an integrated asset management maturity model will enhance effective and efficient delivery of services.

Emergency Health Services (EHS) : demand and service delivery models. monograph 3 : patients’ reasons and perceptions

Executive Summary Emergency health is a critical component of Australia’s health system and emergency departments (EDs) are increasingly congested from growing demand and blocked access to inpatient beds. The Emergency Health Services Queensland (EHSQ) study aims to identify the factors driving increased demand for emergency health and to evaluate strategies which may safely reduce the future demand growth. This monograph addresses the perspectives of users of both ambulance services and EDs. The research reported here aimed to identify the perspectives of users of emergency health services, both ambulance services and public hospital Emergency Departments and to identify the factors that they took into consideration when exercising their choice of location for acute health care. A cross-sectional survey design was used involving a survey of patients or their carers presenting to the EDs of a stratified sample of eight hospitals. A specific purpose questionnaire was developed based on a novel theoretical model which had been derived from analysis of the literature (Monograph 1). Two survey versions were developed: one for adult patients (self-complete); and one for children (to be completed by parents/guardians). The questionnaires measured perceptions of social support, health status, illness severity, self-efficacy; beliefs and attitudes towards ED and ambulance services; reasons for using these services, and actions taken prior to the service request. The survey was conducted at a stratified sample of eight hospitals representing major cities (four), inner regional (two) and outer regional and remote (two). Due to practical limitations, data were collected for ambulance and ED users within hospital EDs, while patients were waiting for or under treatment. A sample size quota was determined for each ED based on their 2009/10 presentation volumes. The data collection was conducted by four members of the research team and a group of eight interviewers between March and May 2011 (corresponding to autumn season). Of the total of 1608 patients in all eight emergency departments the interviewers were able to approach 1361 (85%) patients and seek their consent to participate in the study. In total, 911 valid surveys were available for analysis (response rate= 67%). These studies demonstrate that patients elected to attend hospital EDs in a considered fashion after weighing up alternatives and there is no evidence of deliberate or ill-informed misuse. • Patients attending ED have high levels of social support and self-efficacy that speak to the considered and purposeful nature of the exercise of choice. • About one third of patients have new conditions while two thirds have chronic illnesses • More than half the attendees (53.1%) had consulted a healthcare professional prior to making the decision. • The decision to seek urgent care at an ED was mostly constructed around the patient’s perception of the urgency and severity of their illness, reinforced by a strong perception that the hospital ED was the correct location for them (better specialised staff, better care for my condition, other options not as suitable). • 33% of the respondent held private hospital insurance but nevertheless attended a public hospital ED. Similarly patients exercised considered and rational judgements in their choice to seek help from the ambulance service. • The decision to call for ambulance assistance was based on a strong perception about the severity of the illness (too severe to use other means of transport) and that other options were not considered appropriate. • The decision also appeared influenced by a perception that the ambulance provided appropriate access to the ED which was considered most appropriate for their particular condition (too severe to go elsewhere, all facilities in one spot, better specialised and better care). • In 43.8% of cases a health care professional advised use of the ambulance. • Only a small number of people perceived that ambulance should be freely available regardless of severity or appropriateness. These findings confirm a growing understanding that the choice of professional emergency health care services is not made lightly but rather made by reasonable people exercising a judgement which is influenced by public awareness of the risks of acute health and which is most often informed by health professionals. It is also made on the basis of a rational weighing up of alternatives and a deliberate and considered choice to seek assistance from a service which the patient perceived was most appropriate to their needs at that time. These findings add weight to dispensing with public perceptions that ED and ambulance congestion is a result of inappropriate choice by patients. The challenge for health services is to better understand the patient’s needs and to design and validate services that meet those needs. The failure of our health system to do so should not be grounds for blaming the patient, claiming inappropriate patient choices.

Perceptions of organ donors and willingness to donate organs upon death : a test of the prototype/willingness model

Understanding people's organ donation decisions may narrow the gap between organ supply and demand. In two studies, participants who had not recorded their posthumous organ donation decision (Study 1, N = 210; Study 2, N = 307) completed items assessing prototype/willingness model (PWM; attitude, subjective norm, donor prototype favorability and similarity, willingness) constructs. Attitude, subjective norm, and prototype similarity predicted willingness to donate. Prototype favorability and a Prototype Favorability × Similarity interaction predicted willingness (Study 2). These findings provide support for the PWM in altruistic health contexts, highlighting the importance of people's perceptions about organ donors in their donation decisions.

A demand-responsive decision support system for coal transportation

In this paper, a demand-responsive decision support system is proposed by integrating the operations of coal shipment, coal stockpiles and coal railing within a whole system. A generic and flexible scheduling optimisation methodology is developed to identify, represent, model, solve and analyse the coal transport problem in a standard and convenient way. As a result, the integrated train-stockpile-ship timetable is created and optimised for improving overall efficiency of coal transport system. A comprehensive sensitivity analysis based on extensive computational experiments is conducted to validate the proposed methodology. The mathematical proposition and proof are concluded as technical and insightful advices for industry practice. The proposed methodology provides better decision making on how to assign rail rolling-stocks and upgrade infrastructure in order to significantly improve capacity utilisation with the best resource-effectiveness ratio. The proposed decision support system with train-stockpile-ship scheduling optimisation techniques is promising to be applied in railway or mining industry, especially as a useful quantitative decision making tool on how to use more current rolling-stocks or whether to buy additional rolling-stocks for mining transportation.

Demand response for residential appliances via Customer Reward Scheme

This paper proposes a reward based demand response algorithm for residential customers to shave network peaks. Customer survey information is used to calculate various criteria indices reflecting their priority and flexibility. Criteria indices and sensitivity based house ranking is used for appropriate load selection in the feeder for demand response. Customer Rewards (CR) are paid based on load shift and voltage improvement due to load adjustment. The proposed algorithm can be deployed in residential distribution networks using a two-level hierarchical control scheme. Realistic residential load model consisting of non-controllable and controllable appliances is considered in this study. The effectiveness of the proposed demand response scheme on the annual load growth of the feeder is also investigated. Simulation results show that reduced peak demand, improved network voltage performance, and customer satisfaction can be achieved.

Defining expected cost for the air conditioning to avoid a price spike of electricity market under DSR model

This work presents a demand side response model (DSR) which assists small electricity consumers, through an aggregator, exposed to the market price to proactively mitigate price and peak impact on the electrical system. The proposed model allows consumers to manage air-conditioning when as a function of possible price spikes. The main contribution of this research is to demonstrate how consumers can minimise the total expected cost by optimising air-conditioning to account for occurrences of a price spike in the electricity market. This model investigates how pre-cooling method can be used to minimise energy costs when there is a substantial risk of an electricity price spike. The model was tested with Queensland electricity market data from the Australian Energy Market Operator and Brisbane temperature data from the Bureau of Statistics during hot days on weekdays in the period 2011 to 2012.

The impact of a congestion charging exemption on the demand for new low‐emission vehicles

Numerous initiatives have been employed around the world in order to address rising greenhouse gas (GHG) emissions originating from the transport sector. These measures include: travel demand management (congestion‐charging), increased fuel taxes, alternative fuel subsidies and low‐emission vehicle (LEV) rebates. Incentivizing the purchase of LEVs has been one of the more prevalent approaches in attempting to tackle this global issue. LEVs, whilst having the advantage of lower emissions and, in some cases, more efficient fuel consumption, also bring the downsides of increased purchase cost, reduced convenience of vehicle fuelling, and operational uncertainty. To stimulate demand in the face of these challenges, various incentive‐based policies, such as toll exemptions, have been used by national and local governments to encourage the purchase of these types of vehicles. In order to address rising GHG emissions in Stockholm, and in line with the Swedish Government’s ambition to operate a fossil free fleet by 2030, a number of policies were implemented targeting the transport sector. Foremost amongst these was the combination of a congestion charge – initiated to discourage emissions‐intensive travel – and an exemption from this charge for some LEVs, established to encourage a transition towards a ‘green’ vehicle fleet. Although both policies shared the aim of reducing GHG emissions, the exemption for LEVs carried the risk of diminishing the effectiveness of the congestion charging scheme. As the number of vehicle owners choosing to transition to an eligible LEV increased, the congestion‐reduction effectiveness of the charging scheme weakened. In fact, policy makers quickly recognized this potential issue and consequently phased out the LEV exemption less than 18 months after its introduction (1). Several studies have investigated the demand for LEVs through stated‐preference (SP) surveys across multiple countries, including: Denmark (2), Germany (3, 4), UK (5), Canada (6), USA (7, 8) and Australia (9). Although each of these studies differed in approach, all involved SP surveys where differing characteristics between various types of vehicles, including LEVs, were presented to respondents and these respondents in turn made hypothetical decisions about which vehicle they would be most likely to purchase. Although these studies revealed a number of interesting findings in regards to the potential demand for LEVs, they relied on SP data. In contrast, this paper employs an approach where LEV choice is modelled by taking a retrospective view and by using revealed preference (RP) data. By examining the revealed preferences of vehicle owners in Stockholm, this study overcomes one of the principal limitations of SP data, namely that stated preferences may not in fact reflect individuals’ actual choices, such as when cost, time, and inconvenience factors are real rather than hypothetical. This paper’s RP approach involves modelling the characteristics of individuals who purchased new LEVs, whilst estimating the effect of the congestion charging exemption upon choice probabilities and subsequent aggregate demand. The paper contributes to the current literature by examining the effectiveness of a toll exemption under revealed preference conditions, and by assessing the total effect of the policy based on key indicators for policy makers, including: vehicle owner home location, commuting patterns, number of children, age, gender and income. Extended Abstract Submission for Kuhmo Nectar Conference 2014 2 The two main research questions motivating this study were:  Which individuals chose to purchase a new LEV in Stockholm in 2008?; and,  How did the congestion charging exemption affect the aggregate demand for new LEVs in Stockholm in 2008? In order to answer these research questions the analysis was split into two stages. Firstly, a multinomial logit (MNL) model was used to identify which demographic characteristics were most significantly related to the purchase of an LEV over a conventional vehicle. The three most significant variables were found to be: intra‐cordon residency (positive); commuting across the cordon (positive); and distance of residence from the cordon (negative). In order to estimate the effect of the exemption policy on vehicle purchase choice, the model included variables to control for geographic differences in preferences, based on the location of the vehicle owners’ homes and workplaces in relation to the congestion‐charging cordon boundary. These variables included one indicator representing commutes across the cordon and another indicator representing intra‐cordon residency. The effect of the exemption policy on the probability of purchasing LEVs was estimated in the second stage of the analysis by focusing on the groups of vehicle owners that were most likely to have been affected by the policy i.e. those commuting across the cordon boundary (in both directions). Given the inclusion of the indicator variable representing commutes across the cordon, it is assumed that the estimated coefficient of this variable captures the effect of the exemption policy on the utility of choosing to purchase an exempt LEV for these two groups of vehicle owners. The intra‐cordon residency indicator variable also controls for differences between the two groups, based upon direction of travel across the cordon boundary. A counter‐hypothesis to this assumption is that the coefficient of the variable representing commuting across the cordon boundary instead only captures geo‐demographic differences that lead to variations in LEV ownership across the different groups of vehicle owners in relation to the cordon boundary. In order to address this counter‐hypothesis, an additional analysis was performed on data from a city with a similar geodemographic pattern to Stockholm, Gothenburg ‐ Sweden’s second largest city. The results of this analysis provided evidence to support the argument that the coefficient of the variable representing commutes across the cordon was capturing the effect of the exemption policy. Based upon this framework, the predicted vehicle type shares were calculated using the estimated coefficients of the MNL model and compared with predicted vehicle type shares from a simulated scenario where the exemption policy was inactive. This simulated scenario was constructed by setting the coefficient for the variable representing commutes across the cordon boundary to zero for all observations to remove the utility benefit of the exemption policy. Overall, the procedure of this second stage of the analysis led to results showing that the exemption had a substantial effect upon the probability of purchasing and aggregate demand for exempt LEVs in Stockholm during 2008. By making use of unique evidence of revealed preferences of LEV owners, this study identifies the common characteristics of new LEV owners and estimates the effect of Stockholm's congestion charging exemption upon the demand for new LEVs during 2008. It was found that the variables that had the greatest effect upon the choice of purchasing an exempt LEV included intra‐cordon residency (positive), distance of home from the cordon (negative), and commuting across the cordon (positive). It was also determined that owners under the age of 30 years preferred non‐exempt LEVs (low CO2 LEVs), whilst those over the age of 30 years preferred electric vehicles. In terms of electric vehicles, it was apparent that those individuals living within the city had the highest propensity towards purchasing this vehicle type. A negative relationship between choosing an electric vehicle and the distance of an individuals’ residency from the cordon was also evident. Overall, the congestion charging exemption was found to have increased the share of exempt LEVs in Stockholm by 1.9%, with, as expected, a much stronger effect on those commuting across the boundary, with those living inside the cordon having a 13.1% increase, and those owners living outside the cordon having a 5.0% increase. This increase in demand corresponded to an additional 538 (+/‐ 93; 95% C.I.) new exempt LEVs purchased in Stockholm during 2008 (out of a total of 5 427; 9.9%). Policy makers can take note that an incentive‐based policy can increase the demand for LEVs and appears to be an appropriate approach to adopt when attempting to reduce transport emissions through encouraging a transition towards a ‘green’ vehicle fleet.

Conceptual framework for understanding the demand for emergency health services

Background & Objectives Emergency health services (EHS) throughout the world are increasingly congested. As more people use EHS, factors such as population growth and aging cannot fully explain this increase. Also, focus on patients’ clinical characteristics ignores the role that attitudinal and perceptual factors and motivations play in directing their decisions and actions. The aim of this study is to review and synthesize an integrated conceptual framework for understanding social psychological factors underpinning demand for EHS. Methodology A comprehensive search and review of empirical and theoretical studies about the utilization of EHS was conducted using major medical, health, social and behavioral sciences databases. Results A small number of studies used a relevant conceptual framework (e.g. Health Services Utilization Model or Health Belief Model) or their components to analyze patients’ decision to use EHS. The studies evidenced that demand was affected by perceived severity of the condition; perceived costs and benefits (e.g. availability, accessibility and affordability of alternative services); experience, preference and knowledge; perceived and actual social support; and demographic characteristics (e.g. age, sex, socioeconomic status, ethnicity, marital and living circumstances, place of residence). Conclusions Conceptual models that are commonly used in areas like social and behavioral sciences have rarely been applied in the EHS utilization field. Understanding patients’ decision-making and associated factors will lay the groundwork for identification of the evidence to inform improved policy responses and the development of demand management strategies. An integrated conceptual framework will be introduced as part of this study.

Paratransit demand of disabled people

This paper estimates the demand for transportation systems that are used primarily by disabled individuals. These systems are known as paratransit systems and have experienced large increases in number and average size over the past 15 years. We first use a national database and standard time series techniques to model aggregate demand. We then use a unique data set of administrative records from a paratransit system in central Virginia to estimate standard and nonstandard count models of individual demand. We conclude that most of the demand growth is from new passengers, but that predicting the growth of new passengers is very difficult. Our results also highlight the importance of incorporating autocorrelation and possible sample attrition into standard count models.

Enhancing paramedics procedural skills using a cadaveric model

Background Paramedic education has evolved in recent times from vocational post-employment to tertiary pre-employment supplemented by clinical placement. Simulation is advocated as a means of transferring learned skills to clinical practice. Sole reliance of simulation learning using mannequin-based models may not be sufficient to prepare students for variance in human anatomy. In 2012, we trialled the use of fresh frozen human cadavers to supplement undergraduate paramedic procedural skill training. The purpose of this study is to evaluate whether cadaveric training is an effective adjunct to mannequin simulation and clinical placement. Methods A multi-method approach was adopted. The first step involved a Delphi methodology to formulate and validate the evaluation instrument. The instrument comprised of knowledge-based MCQs, Likert for self-evaluation of procedural skills and behaviours, and open answer. The second step involved a pre-post evaluation of the 2013 cadaveric training. Results One hundred and fourteen students attended the workshop and 96 evaluations were included in the analysis, representing a return rate of 84%. There was statistically significant improved anatomical knowledge after the workshop. Students' self-rated confidence in performing procedural skills on real patients improved significantly after the workshop: inserting laryngeal mask (MD 0.667), oropharyngeal (MD 0.198) and nasopharyngeal (MD 0.600) airways, performing Bag-Valve-Mask (MD 0.379), double (MD 0.344) and triple (MD 0.326,) airway manoeuvre, doing 12-lead electrocardiography (MD 0.729), using McGrath(R) laryngoscope (MD 0.726), using McGrath(R) forceps to remove foreign body (MD 0.632), attempting thoracocentesis (MD 1.240), and putting on a traction splint (MD 0.865). The students commented that the workshop provided context to their theoretical knowledge and that they gained an appreciation of the differences in normal tissue variation. Following engagement in/ completion of the workshop, students were more aware of their own clinical and non-clinical competencies. Conclusions The paramedic profession has evolved beyond patient transport with minimal intervention to providing comprehensive both emergency and non-emergency medical care. With limited availability of clinical placements for undergraduate paramedic training, there is an increasing demand on universities to provide suitable alternatives. Our findings suggested that cadaveric training using fresh frozen cadavers provides an effective adjunct to simulated learning and clinical placements.

The impact of a congestion pricing exemption on the demand for new energy efficient vehicles in Stockholm

As governments seek to transition to more efficient vehicle fleets, one strategy has been to incentivize ‘green’ vehicle choice by exempting some of these vehicles from road user charges. As an example, to stimulate sales of Energy-Efficient Vehicles (EEVs) in Sweden, some of these automobiles were exempted from Stockholm’s congestion tax. In this paper the effect this policy had on the demand for new, privately-owned, exempt EEVs is assessed by first estimating a model of vehicle choice and then by applying this model to simulate vehicle alternative market shares under different policy scenarios. The database used to calibrate the model includes owner-specific demographics merged with vehicle registry data for all new private vehicles registered in Stockholm County during 2008. Characteristics of individuals with a higher propensity to purchase an exempt EEV were identified. The most significant factors included intra-cordon residency (positive), distance from home to the CBD (negative), and commuting across the cordon (positive). By calculating vehicle shares from the vehicle choice model and then comparing these estimates to a simulated scenario where the congestion tax exemption was inactive, the exemption was estimated to have substantially increased the share of newly purchased, private, exempt EEVs in Stockholm by 1.8% (+/- 0.3%; 95% C.I.) to a total share of 18.8%. This amounts to an estimated 10.7% increase in private, exempt EEV purchases during 2008 i.e. 519 privately owned, exempt EEVs.

Aggregating energy supply and demand

Energy usage in general, and electricity usage in particular, are major concerns internationally due to the increased cost of providing energy supplies and the environmental impacts of electricity generation using carbon-based fuels. If a "systems" approach is taken to understanding energy issues then both supply and demand need to be considered holistically. This paper examines two research projects in the energy area with IT tools as key deliverables, one examining supply issues and the other studying demand side issues. The supply side project used hard engineering methods to build the models and software, while the demand side project used a social science approach. While the projects are distinct, there was an overlap in personnel. Comparing the knowledge extraction, model building, implementation and interface issues of these two deliverables identifies both interesting contrasts and commonalities.

Emotional intelligence and job-demands resources model

Occupational stress research has consistently demonstrated negative effects for employees. Research also describes potential moderators of this relationship. While research has revealed some positive effects of emotional intelligence (EI) on employee adjustment, it has neglected investigation of their potential stress buffering effects. Based on the Job-Demand Resources model, it was predicted that higher trait emotional intelligence would act as a buffer to the potential negative effects of stressors on employee adjustment. Hierarchical multiple regression analyses with a sample of 306 nurses found no main effects of EI but revealed eight moderating effects. While some interactions support the buffering hypothesis, others revealed buffering for those with low EI. Findings are discussed in terms of theoretical and practical implications.

A framework for understanding and generating integrated solutions for residential peak energy demand

Supplying peak energy demand in a cost effective, reliable manner is a critical focus for utilities internationally. Successfully addressing peak energy concerns requires understanding of all the factors that affect electricity demand especially at peak times. This paper is based on past attempts of proposing models designed to aid our understanding of the influences on residential peak energy demand in a systematic and comprehensive way. Our model has been developed through a group model building process as a systems framework of the problem situation to model the complexity within and between systems and indicate how changes in one element might flow on to others. It is comprised of themes (social, technical and change management options) networked together in a way that captures their influence and association with each other and also their influence, association and impact on appliance usage and residential peak energy demand. The real value of the model is in creating awareness, understanding and insight into the complexity of residential peak energy demand and in working with this complexity to identify and integrate the social, technical and change management option themes and their impact on appliance usage and residential energy demand at peak times.

Improved residential electricity demand management through analysis of the customer perspective

Peak electricity demand requires substantial investment to update transmission, distribution and generation infrastructure. A successful community peak demand reduction project was examined to identify residential consumer motivational and contextual factors involved in their decision to adopt/not adopt interventions. Energy professionals actively worked to achieve community 'peer' membership and by becoming a trusted information source, facilitated voluntary home energy assessment requests from over 80% of the residential community. By combining and tailoring interventions to the specific needs and motivations of individual householders and the community, interventions promoting energy conservation and efficiency can be effective in achieving sustained reduction in peak demand.