Integrated risk/cost planning models for the US Air Traffic system

A prototype network planning model for the U.S. Air Traffic control system is described. The model encompasses the dual objectives of managing collision risks and transportation costs where traffic flows can be related to these objectives. The underlying structure is a network graph with nonseparable convex costs; the model is solved efficiently by capitalizing on its intrinsic characteristics. Two specialized algorithms for solving the resulting problems are described: (1) truncated Newton, and (2) simplicial decomposition. The feasibility of the approach is demonstrated using data collected from a control center in the Midwest. Computational results with different computer systems are presented, including a vector supercomputer (CRAY-XMP). The risk/cost model has two primary uses: (1) as a strategic planning tool using aggregate flight information, and (2) as an integrated operational system for forecasting congestion and monitoring (controlling) flow throughout the U.S. In the latter case, access to a supercomputer is required due to the model's enormous size

Stochastic debt sustainability analysis for sovereigns and the scope for optimization modeling

We argue that sovereign debt sustainability analysis must be augmented by stochastic correlated risk factors and a risk measure to capture tail effects. Crisis situations can thus be adequately specified and analyzed with sufficient accuracy to warrant the relevance of policy decisions. In this context there is significant scope for optimization modeling for both strategic planning and operational management. We discuss diverse aspects of the problem of debt sustainability and highlight modeling approaches that can be brought to bear on the problem. Results with the fictitious, but nor unrealistic, Kingdom of Atlantis, which is sinking under excessive debt, illustrate the proposed models

A parsimonious model for generating arbitrage-free scenario trees

Simulation models of economic, financial and business risk factors are widely used to assess risks and support decision-making. Extensive literature on scenario generation methods aims at describing some underlying stochastic processes with the least number of scenarios to overcome the ‘curse of dimensionality’. There is, however, an important requirement that is usually overlooked when one departs from the application domain of security pricing: the no-arbitrage condition. We formulate a moment matching model to generate multi-factor scenario trees for stochastic optimization satisfying no-arbitrage restrictions with a minimal number of scenarios and without any distributional assumptions. The resulting global optimization problem is quite general. However, it is non-convex and can grow significantly with the number of risk factors, and we develop convex lower bounding techniques for its solution exploiting the special structure of the problem. Applications to some standard problems from the literature show that this is a robust approach for tree generation. We use it to price a European basket option in complete and incomplete markets

Designing and pricing guarantee options in defined contribution pension plans

The shift from defined benefit (DB) to defined contribution (DC) is pervasive among pension funds, due to demographic changes and macroeconomic pressures. In DB all risks are borne by the provider, while in plain vanilla DC all risks are borne by the beneficiary. However, for DC to provide income security some kind of guarantee is required. A minimum guarantee clause can be modeled as a put option written on some underlying reference portfolio and we develop a discrete model that selects the reference portfolio to minimise the cost of a guarantee. While the relation DB-DC is typically viewed as a binary one, the model shows how to price a wide range of guarantees creating a continuum between DB and DC. Integrating guarantee pricing with asset allocation decision is useful to both pension fund managers and regulators. The former are given a yardstick to assess if a given asset portfolio is fit-for-purpose; the latter can assess differences of specific reference funds with respect to the optimal one, signalling possible cases of moral hazard. We develop the model and report numerical results to illustrate its uses

Asset and Liability Modelling for Participating Policies with Guarantee

We study the problem of asset and liability management of participating insurance policies with guarantees. We develop a scenario optimization model for integrative asset and liability management, analyse the tradeoffs in structuring such policies, and study alternative choices in funding them. The nonlinearly constrained optimization model can be linearised through closed form solutions of the dynamic equations. Thus large-scale problems are solved with standard methods. We report on an empirical analysis of policies offered by Italian insurers. The optimized model results are in general agreement with current industry practices. However, some inefficiencies are identified and potential improvements are highlighted

Is There a Doctor in the House? Expert Product Users, Organizational Roles, and Innovation

We explore the impact on innovation that professional end-users of a product have as inventors, executives, and board members in a young organization. In contrast to prior literature, which has emphasized technology roles, we put the spotlight on executive and governance roles that many professional users take in young firms. Using an extensive custom-collected dataset of 231 surgical instrument ventures over a 25-year period combined with qualitative fieldwork, we find that professional physician-users (surgeons) strengthen innovation in some roles but block it in others. Surgeons are related with the increase in a firm’s innovation when they take a technology role as inventors, and particularly when they take a governance role on the young firm’s board. However, despite their frequent involvement in executive roles, surgeon-executives are less likely to be helpful, and especially likely to block innovation as chief executives. Our results emphasize professional users as a critical external dependency for a young firm’s innovation, but show that a mismatch with a particular organizational role may have unanticipated negative effects on innovation. A key finding is that users are more helpful in suggesting a broad variety of solutions to the firm’s innovation problems but less helpful in selecting the best ones for the organization to pursue. Our findings have implications for research on evolutionary perspective on user innovation, organizational roles in young firms, and entrepreneurial policy

The new (challenging) role of academia in biomaterial translational research and medical device development

With the ever-changing landscape of translational research, the medical device and pharmaceutical industries increasingly license technologies with the added value of clinical and/or pre-clinical data rather than those in earlier stages of development. Universities have the potential to fill the gap in product development from academic laboratories through enhanced student training and increased implementation of some development and manufacturing activities that are traditionally found only in the private sector. A development roadmap is described from initial product feasibility through commercialization in the context of efficient development practices. The specific challenges in the design and development of biomaterialbased medical devices are described in the context of this development path with an emphasis on unique challenges for academic laboratories. © The Author(s) 2012.Link_to_subscribed_fulltex