Population ageing in a globalizing labour market : implications for older workers

This article concerns the changing nature of the relationship between age and the labour market. Global demographic, economic and technological changes potentially pose major challenges for older workers trying to maintain a secure attachment to the labour market. Recent public policy has responded by defining concepts such as 'active ageing' which encourage older workers to participate fully within society, including maintaining workforce participation. Older workers' ability to secure quality work within a volatile labour market is considered. While activation approaches are currently popular among policymakers, the notion that older workers will easily avoid a diminution of their employment prospects is challenged.

Intelligent negotiation behaviour model for an open railway access market

In an open railway access market, the provisions of railway infrastructures and train services are separated and independent. Negotiations between the track owner and train service providers are thus required for the allocation of the track capacity and the formulation of the services timetables, in which each party, i.e. a stakeholder, exhibits intelligence from the previous negotiation experience to obtain the favourable terms and conditions for the track access. In order to analyse the realistic interacting behaviour among the stakeholders in the open railway access market schedule negotiations, intelligent learning capability should be included in the behaviour modelling. This paper presents a reinforcement learning approach on modelling the intelligent negotiation behaviour. The effectiveness of incorporating learning capability in the stakeholder negotiation behaviour is then demonstrated through simulation.

Poisson, Poisson-gamma and zero-inflated regression models of motor vehicle crashes: balancing statistical fit and theory

There has been considerable research conducted over the last 20 years focused on predicting motor vehicle crashes on transportation facilities. The range of statistical models commonly applied includes binomial, Poisson, Poisson-gamma (or negative binomial), zero-inflated Poisson and negative binomial models (ZIP and ZINB), and multinomial probability models. Given the range of possible modeling approaches and the host of assumptions with each modeling approach, making an intelligent choice for modeling motor vehicle crash data is difficult. There is little discussion in the literature comparing different statistical modeling approaches, identifying which statistical models are most appropriate for modeling crash data, and providing a strong justification from basic crash principles. In the recent literature, it has been suggested that the motor vehicle crash process can successfully be modeled by assuming a dual-state data-generating process, which implies that entities (e.g., intersections, road segments, pedestrian crossings, etc.) exist in one of two states—perfectly safe and unsafe. As a result, the ZIP and ZINB are two models that have been applied to account for the preponderance of “excess” zeros frequently observed in crash count data. The objective of this study is to provide defensible guidance on how to appropriate model crash data. We first examine the motor vehicle crash process using theoretical principles and a basic understanding of the crash process. It is shown that the fundamental crash process follows a Bernoulli trial with unequal probability of independent events, also known as Poisson trials. We examine the evolution of statistical models as they apply to the motor vehicle crash process, and indicate how well they statistically approximate the crash process. We also present the theory behind dual-state process count models, and note why they have become popular for modeling crash data. A simulation experiment is then conducted to demonstrate how crash data give rise to “excess” zeros frequently observed in crash data. It is shown that the Poisson and other mixed probabilistic structures are approximations assumed for modeling the motor vehicle crash process. Furthermore, it is demonstrated that under certain (fairly common) circumstances excess zeros are observed—and that these circumstances arise from low exposure and/or inappropriate selection of time/space scales and not an underlying dual state process. In conclusion, carefully selecting the time/space scales for analysis, including an improved set of explanatory variables and/or unobserved heterogeneity effects in count regression models, or applying small-area statistical methods (observations with low exposure) represent the most defensible modeling approaches for datasets with a preponderance of zeros

Bayesian multinomial logit: Theory and route choice example

Statisticians along with other scientists have made significant computational advances that enable the estimation of formerly complex statistical models. The Bayesian inference framework combined with Markov chain Monte Carlo estimation methods such as the Gibbs sampler enable the estimation of discrete choice models such as the multinomial logit (MNL) model. MNL models are frequently applied in transportation research to model choice outcomes such as mode, destination, or route choices or to model categorical outcomes such as crash outcomes. Recent developments allow for the modification of the potentially limiting assumptions of MNL such as the independence from irrelevant alternatives (IIA) property. However, relatively little transportation-related research has focused on Bayesian MNL models, the tractability of which is of great value to researchers and practitioners alike. This paper addresses MNL model specification issues in the Bayesian framework, such as the value of including prior information on parameters, allowing for nonlinear covariate effects, and extensions to random parameter models, so changing the usual limiting IIA assumption. This paper also provides an example that demonstrates, using route-choice data, the considerable potential of the Bayesian MNL approach with many transportation applications. This paper then concludes with a discussion of the pros and cons of this Bayesian approach and identifies when its application is worthwhile

Conflict resolution through negotiation in a railway open access market : a multi-agent system approach

Open access reforms to railway regulations allow multiple train operators to provide rail services on a common infrastructure. As railway operations are now independently managed by different stakeholders, conflicts in operations may arise, and there have been attempts to derive an effective access charge regime so that these conflicts may be resolved. One approach is by direct negotiation between the infrastructure manager and the train service providers. Despite the substantial literature on the topic, few consider the benefits of employing computer simulation as an evaluation tool for railway operational activities such as access pricing. This article proposes a multi-agent system (MAS) framework for the railway open market and demonstrates its feasibility by modelling the negotiation between an infrastructure provider and a train service operator. Empirical results show that the model is capable of resolving operational conflicts according to market demand.

Efficient algorithm for achieving GWPMM fairness in ATM ABR services

A new explicit rate allocation algorithm is proposed for achieving generic weight-proportional max-min (GWPMM) fairness in asynchronous transfer mode (ATM) available bit rate services. This algorithm scales well with a fixed computational complexity of O(1) and can realise GWPMM fair rate allocation in an ATM network accurately.

Application of reinforcement learning in an open railway access market price negotiation

In an open railway access market price negotiation, it is feasible to achieve higher cost recovery by applying the principles of price discrimination. The price negotiation can be modeled as an optimization problem of revenue intake. In this paper, we present the pricing negotiation based on reinforcement learning model. A negotiated-price setting technique based on agent learning is introduced, and the feasible applications of the proposed method for open railway access market simulation are discussed.

Scheduling coordination through negotiation between train service providers in an open railway access market

A schedule coordination problem involving two train services provided by different operators is modeled as an optimization of revenue intake. The coordination is achieved through the adjustment of commencement times of the train services by negotiation. The problem is subject to constraints regarding to passenger demands and idle costs of rolling-stocks from both operators. This paper models the operators as software agents having the flexibility to incorporate one of the two (and potentially more) proposed negotiation strategies. Empirical results show that agents employing different combination of strategies have significant impact on the quality of solution and negotiation time.

Political theory and theoretical physics

This paper argues, somewhat along a Simmelian line, that political theory may produce practical and universal theories like those developed in theoretical physics. The reasoning behind this paper is to show that the theory of ‘basic democracy’ may be true by way of comparing it to Einstein’s Special Relativity – specifically concerning the parameters of symmetry, unification, simplicity, and utility. These parameters are what make a theory in physics as meeting them not only fits with current knowledge, but also produces paths towards testing (application). As the theory of ‘basic democracy’ may meet these same parameters, it could settle the debate concerning the definition of democracy. This will be argued firstly by discussing what the theory of ‘basic democracy’ is and why it differs from previous work; secondly by explaining the parameters chosen (as in why these and not others confirm or scuttle theories); and thirdly by comparing how Special Relativity and the theory of ‘basic democracy’ may match the parameters.

Innovation in construction : a case study of the Australian context

The dominant economic paradigm currently guiding industry policy making in Australia and much of the rest of the world is the neoclassical approach. Although neoclassical theories acknowledge that growth is driven by innovation, such innovation is exogenous to their standard models and hence often not explored. Instead the focus is on the allocation of scarce resources, where innovation is perceived as an external shock to the system. Indeed, analysis of innovation is largely undertaken by other disciplines, such as evolutionary economics and institutional economics. As more has become known about innovation processes, linear models, based on research and development or market demand, have been replaced by more complex interactive models which emphasise the existence of feedback loops between the actors and activities involved in the commercialisation of ideas (Manley 2003). Currently dominant among these approaches is the national or sectoral innovation system model (Breschi and Malerba 2000; Nelson 1993), which is based on the notion of increasingly open innovation systems (Chesbrough, Vanhaverbeke, and West 2008). This chapter reports on the ‘BRITE Survey’ funded by the Cooperative Research Centre for Construction Innovation which investigated the open sectoral innovation system operating in the Australian construction industry. The BRITE Survey was undertaken in 2004 and it is the largest construction innovation survey ever conducted in Australia. The results reported here give an indication of how construction innovation processes operate, as an example that should be of interest to international audiences interested in construction economics. The questionnaire was based on a broad range of indicators recommended in the OECD’s Community Innovation Survey guidelines (OECD/Eurostat 2005). Although the ABS has recently begun to undertake regular innovation surveys that include the construction industry (2006), they employ a very narrow definition of the industry and only collect very basic data compared to that provided by the BRITE Survey, which is presented in this chapter. The term ‘innovation’ is defined here as a new or significantly improved technology or organisational practice, based broadly on OECD definitions (OECD/Eurostat 2005). Innovation may be technological or organisational in nature and it may be new to the world, or just new to the industry or the business concerned. The definition thus includes the simple adoption of existing technological and organisational advancements. The survey collected information about respondents’ perceptions of innovation determinants in the industry, comprising various aspects of business strategy and business environment. It builds on a pilot innovation survey undertaken by PricewaterhouseCoopers (PWC) for the Australian Construction Industry Forum on behalf of the Australian Commonwealth Department of Industry Tourism and Resources, in 2001 (PWC 2002). The survey responds to an identified need within the Australian construction industry to have accurate and timely innovation data upon which to base effective management strategies and public policies (Focus Group 2004).

Highly efficient, stoichiometric radical exchange reactions using isoindoline profluorescent nitroxides

Exchange reactions between the isoindoline profluorescent nitroxide 1,1,3,3-tetramethyldibenzo[e,g]isoindolin-2-yloxyl (TMDBIO) and a TEMPO capped polystyrene were carried out. High conversions to the desired products were achieved using only stoichiometric ratios of nitroxide relative to polymer. The scope of this study was expanded by exploiting a di-nitroxide 9,10-bis(5-[1,1,3,3-tetramethylisoindolin-2-yloxy])anthracene (BTMIOA) as a connector between two polymer chains forming PS–nitroxide–PS systems.

Rayleigh theory of ultrasound scattering applied to liquid-filled contrast nanoparticles

We present a novel modified theory based upon Rayleigh scattering of ultrasound from composite nanoparticles with a liquid core and solid shell. We derive closed form solutions to the scattering cross-section and have applied this model to an ultrasound contrast agent consisting of a liquid-filled core (perfluorooctyl bromide, PFOB) encapsulated by a polymer shell (poly-caprolactone, PCL). Sensitivity analysis was performed to predict the dependence of the scattering cross-section upon material and dimensional parameters. A rapid increase in the scattering cross-section was achieved by increasing the compressibility of the core, validating the incorporation of high compressibility PFOB; the compressibility of the shell had little impact on the overall scattering cross-section although a more compressible shell is desirable. Changes in the density of the shell and the core result in predicted local minima in the scattering cross-section, approximately corresponding to the PFOB-PCL contrast agent considered; hence, incorporation of a lower shell density could potentially significantly improve the scattering cross-section. A 50% reduction in shell thickness relative to external radius increased the predicted scattering cross-section by 50%. Although it has often been considered that the shell has a negative effect on the echogeneity due to its low compressibility, we have shown that it can potentially play an important role in the echogeneity of the contrast agent. The challenge for the future is to identify suitable shell and core materials that meet the predicted characteristics in order to achieve optimal echogenity.

Celebrity entrepreneurship and celebrity endorsement : similarities, differences and the effect of deeper engagement

Increasingly, celebrities appear not only as endorsers for products but are apparently engaged in entrepreneurial roles as initiators, owners and perhaps even managers in the ventures that market the products they promote. Despite being extensively referred to in popular media, scholars have been slow to recognise the importance of this new phenomenon. This thesis argues theoretically and shows empirically that celebrity entrepreneurs are more effective communicators than typical celebrity endorsers because of their increased engagement with ventures. I theorise that greater engagement increases the celebrity‘s emotional involvement as perceived by consumers. This is an endorser quality thus far neglected in the marketing communications literature. In turn, emotional involvement, much like the empirically established dimensions trustworthiness, expertise and attractiveness, should affect traditional outcome variables such as attitude towards the advertisement and brand. On the downside, increases in celebrity engagement may lead to relatively stronger and worsening changes in attitudes towards the brand if and when negative information about the celebrity is revealed. A series of eight experiments was conducted on 781 Swedish and Baltic students and 151 Swedish retirees. Though there were nuanced differences and additional complexities in each experiment, participants‘ reactions to advertisements containing a celebrity portrayed as a typical endorser or entrepreneur were recorded. The overall results of these experiments suggest that emotional involvement can be successfully operationalised as distinct from variables previously known to influence communication effectiveness. In addition, emotional involvement has positive effects on attitudes toward the advertisement and brand that are as strong as the predictors traditionally applied in the marketing communications literature. Moreover, the celebrity entrepreneur condition in the experimental manipulation consistently led to an increase in emotional involvement and to a lesser extent trustworthiness, but not expertise and attractiveness. Finally, negative celebrity information led to a change in participants‘ attitudes towards the brand which were more strongly negative for celebrity entrepreneurs than celebrity endorsers. In addition, the effect of negative celebrity information on a company‘s brand is worse when they support the celebrity rather than fire them. However, this effect did not appear to interact with the celebrity‘s purported engagement.

Using decision trees in economizer repair decision making

The economiser is a critical component for efficient operation of coal-fired power stations. It consists of a large system of water-filled tubes which extract heat from the exhaust gases. When it fails, usually due to erosion causing a leak, the entire power station must be shut down to effect repairs. Not only are such repairs highly expensive, but the overall repair costs are significantly affected by fluctuations in electricity market prices, due to revenue lost during the outage. As a result, decisions about when to repair an economiser can alter the repair costs by millions of dollars. Therefore, economiser repair decisions are critical and must be optimised. However, making optimal repair decisions is difficult because economiser leaks are a type of interactive failure. If left unfixed, a leak in a tube can cause additional leaks in adjacent tubes which will need more time to repair. In addition, when choosing repair times, one also needs to consider a number of other uncertain inputs such as future electricity market prices and demands. Although many different decision models and methodologies have been developed, an effective decision-making method specifically for economiser repairs has yet to be defined. In this paper, we describe a Decision Tree based method to meet this need. An industrial case study is presented to demonstrate the application of our method.

Efficient querying of large process model repositories

Recent years have seen an increased uptake of business process management technology in industries. This has resulted in organizations trying to manage large collections of business process models. One of the challenges facing these organizations concerns the retrieval of models from large business process model repositories. For example, in some cases new process models may be derived from existing models, thus finding these models and adapting them may be more effective and less error-prone than developing them from scratch. Since process model repositories may be large, query evaluation may be time consuming. Hence, we investigate the use of indexes to speed up this evaluation process. To make our approach more applicable, we consider the semantic similarity between labels. Experiments are conducted to demonstrate that our approach is efficient.