Terrorism and its impact on economic growth and technological innovation

Recent terrorist acts, in particular the 9-11 attacks in 2001, have created disruptions in the global economy. The short-term impact had been felt in the global tourism, airline industries, as well as the financial markets. While the global economy has recovered and is adjusting to the new global realities, the longer-term impact of heightened security risk across the world can be felt in the form of higher risk premiums in asset markets, as well as a shift of resources towards dealing with terrorism. Just as World War II had accelerated the development of nuclear energy as well as a major contributing factor in the genesis of Silicon Valley, the current war against terrorism will affect both the pace and trajectory of technology trends, as efforts are focused on developing technologies to combat terrorism. In this paper, we review the effects of the current war on terrorism in terms of its impact on the economy, the allocation of resources to R&D, and the trajectory of future R&D.     

Governance structures in R&D networks: An analysis in the European context

This paper analyses governance structures used to organize partnerships in R&D networks using two approaches: transaction costs theory and social capital theory. We argue that these theories are complementary; this explains forms of governance through the degrees of administrative (structural and safeguard mechanism) and social factors (cohesion and openness) they embody. Data was obtained from European R&D networks created through Framework Programmes which include a great number of universities, non profit institutions and firms. Findings show the variables that characterize and explain the governance forms based on the applicability of R&D networks. This study not only provides a theoretical model for analysing governance structures of these networks, but is also useful for both improving the management of networks and for fostering collaboration at an international level.     

Dynamic risk management in petroleum project investment based on a variable precision rough set model

In this paper, an adaptive algorithm is designed for dynamic risk management in petroleum project investment based on a variable precision rough set (VPRS) model. In risk management, at each stage of decision-making, experts are invited to identify risk indices and support the decision-maker in evaluating the risk exposure (RE) of individual projects. The VPRS model is used to mine risk rules and determine the significance of risk indices from RE decision tables. Considering that there are multiple risks involved in any petroleum project investment, we use multi-objective programming to obtain the optimal selection of projects with minimum RE, where the significance of risk indices is assigned to each of the corresponding multi-objective functions as a weight. Moreover, we develop a risk ranking model to measure the degree of risk for individual projects in a portfolio. Finally, a numerical example based on a Chinese petroleum company's investments in overseas projects is presented to illustrate the proposed approach, and then conclusions are drawn.     

Comparing debt characteristics and LGD models for different collections policies

This paper discusses the similarities and differences in the collection process between in-house and 3rd party collection. The objective is to show that, although the same type of modelling approach to estimating the Loss Given Default (LGD) can be used in both cases, the details will be significantly different. In particular, the form of the LGD distribution suggests that one needs to split the distribution in different ways in the two cases, as well as using different variables. The comparisons are made using two data sets of the collection outcomes from two sets of unsecured consumer defaulters.     

Health effects on labour market exits and entries

This paper analyses the role of health on exits out of and entries into employment using data from the first twelve waves of the British Household Panel Survey (1991–2002). We use discrete-time duration models to estimate the effect of health on the hazard of becoming non-employed and on the hazard of becoming employed. The results show that general health, measured by a variable that captures health limitations and by a constructed latent health index, affects entries into and exits out of employment; the effects being higher for men than for women. The results are robust to different definitions of employment, and to the exclusion of older workers from the analysis.     

A note on the Robust Trend and ARARMA methodologies used in the M3 Competition

This brief note describes two of the forecasting methods used in the M3 Competition, Robust Trend and ARARMA. The origins of these methods are very different. Robust Trend was introduced to model the special features of some telecommunications time series. It was subsequently found to be competitive with Holt’s linear model for the more varied set of time series used in the M1 Competition. The ARARMA methodology was proposed by Parzen as a general time series modelling procedure, and can be thought of as an alternative to the ARIMA methodology of Box and Jenkins. This method was used in the M1 Competition and achieved the lowest mean absolute percentage error for longer forecasting horizons. These methods will be described in more detail and some comments on their use in the M3 Competition conclude this note.     

Technology commercialization intelligence: Organizational antecedents and performance consequences

External technology commercialization, e.g., by means of technology licensing, has recently gained in importance. Despite imperfections in technology markets, out-licensing constitutes a major technology commercialization channel. Although the identification of licensing opportunities represents a significant managerial challenge, prior research has relatively neglected these activities. Therefore, we develop the concept of ‘technology commercialization intelligence’ (TCI), which refers to the observation of a firm's environment with particular focus on identifying technology licensing opportunities. Grounded in a dynamic capabilities perspective, we test five hypotheses regarding organizational antecedents and performance consequences of TCI, drawing on data from a survey of 152 companies. The empirical findings provide strong support for the importance of the TCI concept. The findings deepen our understanding of the discrepancies between successful pioneering firms active in technology licensing and many others being less successful. The results have major implications for technology exploitation in open innovation processes.     

The co-evolution of business incubation and national innovation systems in Taiwan

Incubation has already proven to be of great value in promoting small and medium enterprise (SME) entrepreneurship activities and technological development in developed and developing countries. Incubation not only provides a diversified and integrated service for entrepreneurial ventures but also contributes upward to regional and national innovation and economic growth. Building upon the logic of co-evolution theory, this paper argues that incubation acts at the meso-level as a critical interface between macro-innovation systems and micro-business ventures. These multi-directional coupling elements in innovation ecology co-evolve to achieve collective interests and excellence, which in turn may stimulate technological development and social change. Important processes/mechanisms, including a policy kit and action, strategic networking, supportive associations, knowledge and intellectual capital management, among others, are discussed. Drawing on the national innovation system (NIS) and business incubation (BI) experience in Taiwan, we discuss the future prospects of incubation and innovation policies, including industrializing and globalizing incubation activities and virtual business incubation.     

Integrating future-oriented technology analysis and risk assessment methodologies

This paper examines the potential of integrating future-oriented technology analysis (FTA) with risk assessment methodologies and tools, with the aim of developing more proactive risk assessments and also systematically including risk assessment in future-oriented technology analysis. The similarities and development challenges of foresight, Technology Analysis (TA) and risk assessment methodologies are discussed in the light of the empirical material gathered from projects performed at VTT. Among the projects are IRRIIS project focusing on risk assessment of critical infrastructures, INNORISK project aiming at managing opportunities, risk and uncertainties in new business creation and a project related to the climate change (CES). The case projects are positioned according to their important design dimensions (informative vs. instrumental outcomes; consensual vs. diverse future perspectives, extensive vs. exclusive stakeholder involvement, and autonomous vs. fixed management). The common and complementary features of FTA and risk assessment are discussed, suggesting new ways to evolve the modular design when integrating FTA and risk assessment methodologies and tools.