Estimating Facility Size for Variable or Uncertain Activity Levels

In this article, we propose a model and methodology for valuing the option to delay network investment decisions and calculating cost-based access prices. We model the value of the option to invest in each network element as a function of two stochastic variables: the flow of total variable profit from the service provided by the network element and the cost of new investment in that network element. We calculate the option value multiple to be applied to the investment cost component of three main network elements, conduct sensitivity analyses, and highlight key findings.     

Bounds for Ratios of Posterior Expectations: Applications in the Collective Risk Model

This paper considers the collective risk model for the insurance claims process. We will adopt a Bayesian point of view, where uncertainty concerning the specification of the prior distribution is a common question. The robust Bayesian approach uses a class of prior distributions which model uncertainty about the prior, instead of a single distribution. Relatively little research has dealt with robustness with respect to ratios of posterior expectations as occurs with the Esscher and Variance premium principles. Appropriate techniques are developed in this paper to solve this problem using the k -contamination class in the collective risk model.     

Issues in the Drive to Measure Liabilities at Fair Value

This paper compares the discussion on liability measurement in Accounting The0y Monograph 10 with the liability measurement requirements in recent international proposals on accounting for financial instruments. Rather than conducting a detailed review of the Monograph, the paper examines three major issues which wawant amplifjing, extending or criticising: What is “fair value”? Why fair value liabilities? Should fair value include an entity's own credit risk? The focus is on financial liabilities such as “plain vanilla” debt; other financial liabilities, such as insurance obligations, pensions, wawanties and environmental damage restoration involve additional considerations and are therefore not considered.     

Development of an inclined plate jet reactor system

A new design combines reaction or extraction and separation in one unit. Here are practical working details.     

Making visions visible for long-term landscape management

Results generated by planning and futures studies are often too abstract to provide a clear vision of the future to non-specialists. In this study the role of 3D visualization and the challenges in developing and communicating visible visions for our future landscapes is explored. While traditional visualization techniques have been well-known for several hundreds of years digital 3D visualizations are still not yet taken advantage of in long-term planning or in futures studies in general to their full potential. As part of an iterative consultation and participation process a long-term vision for the landscape and land management of the Alport Valley in the Peak District National Park, UK is developed in order to improve the valley's special landscape character, to enhance the valley's visual and recreational attractiveness, to regenerate the woodlands in ways that maximize the long-term benefit of ecology, wildlife and landscape and to get a good balance between wooded areas and open moorland.An early integration of 3D visualization in the planning process offers a wide range of opportunities for exploring alternative futures but it also poses challenges to the expert planners such as being able to react timely, with a high degree of realism and interactively to incorporate new inputs from participating stakeholders. Furthermore, the planner is forced to translate a vision into concrete geographically referenced data. Only then the vision can be visualized. The full potential of 3D visualizations in the planning disciplines and in futures studies is still to be explored. The visualizations could be the basis to communicate the vision - the views of the future - and to share the vision with others in order to influence future change.     

Improving retirement adequacy through asset class prioritization

Highly risk-averse retirees are generally advised to adopt a fixed spending strategy such as the 4% withdrawal rule. To prevent the premature depletion of a retirement portfolio, the rule attempts to proxy as the ‘safe withdrawal rate’. But a constant withdrawal rate means that retirees accumulate unspent surpluses when markets outperform and face spending shortfalls when markets underperform. While a safe withdrawal rate can prevent spending shortfalls, the opportunity cost of unspent surpluses associated with this strategy can be extreme. We apply a range of basic investment decision rules to a retirement portfolio applying various withdrawal rates and examine the probability of shortfalls over a retirement horizon. Using a block bootstrap simulation technique, we examine decision rules relating to stock and bond investments. Our results show that retirement portfolios with a bias towards stocks coupled with a decision rule that sources withdrawals from bonds and cash before stocks significantly outperforms alternative withdrawal strategies, despite the inherent increase in volatility. This finding is in direct contrast to the safe withdrawal rate conventions used in contemporary financial advice models.     

Improving the effectiveness of nondisclosure agreements by strengthening concept learning

Intellectual property infringements rank among the top economic crimes, even though there are mechanisms in place to prevent their occurrence. One such mechanism are nondisclosure agreements, which, however, have been reported to fail in practice. This article argues that this may be overcome by strengthening employees’ concept learning. In an experiment, we investigated whether extended nondisclosure agreements, which provide the employee with detailed explanations and examples, lead to better recognition of trade secrets as compared to a standard nondisclosure agreement or no agreement at all. It was found that the extended nondisclosure agreement indeed increased participants’ ability to judge what falls under the trade secret law, whereas the standard nondisclosure agreement showed no such effect. Furthermore, the effects of the factors ‘Involvement’, ‘Specificity’, ‘Publicity’, and ‘Purpose’ on the identification of trade secrets could be proven experimentally. Employees’ judgments of whether an information represents a trade secret seem to rely on general cognitive processes. From this follows that concept learning could be integrated into systematic approaches for protecting intellectual property.