Multiple generation product life cycle predictions using a novel two-stage fuzzy piecewise regression analysis method

Product life cycle (PLC) prediction plays a crucial role in strategic planning and policy definition for high-technology products. Forecast methodologies which can predict PLCs accurately can help to achieve successful strategic decision-making, forecasting, and foresight activities in high-technology firms, research institutes, governments, and universities. Over the past few decades, even though analytic framework strategies have been proposed for production, marketing, R&D (research and development), and finance, aiming at each stage of PLCs, forecast methodologies with which to predict PLCs are few. The purpose of this research is to develop a novel forecast methodology to allow for predictions of product life time (PLT) and the annual shipment of products during the entire PLC of multiple generation products. A novel two-stage fuzzy piecewise regression analysis method is proposed in this paper. In the first stage, the product life-time of the specific generation to be analyzed will be predicted by the fuzzy piecewise regression line that is derived based upon the product life-time of earlier generations. In the second stage of the forecast methodology, the annual shipment of products of the specified generation will be predicted by deriving annual fuzzy regression lines for each generation, based upon the historical data on the earlier generations' products. An empirical study predicting the life-time and the annual shipment of the 16 Mb (Mega bit) DRAM (Dynamic Random Access Memory) PLC is illustrated to validate the analytical process. The results demonstrate that two-stage fuzzy piecewise regression analysis can predict multiple generation PLT and PLC precisely, thereby serving as a foundation for future strategic planning, policy definitions and foresights.     

A multi-level analysis of sustainable mobility transitions: Niche development in the UK and Sweden

A wide range of intractable problems such as polluting emissions, noise, accidents, resource depletion, and inaccessibility of amenities are associated with the current transport regime. Given the slow movement towards a more sustainable mobility system, more radical, systemic innovation - a ‘transition’ - is required. Broadly speaking, this may be achieved via three routes: technological change, modal shift, and reduced travel demand. Drawing on concepts from the transitions literature (e.g., [Geels, F.W.: Technological Transitions and System Innovations: A Co-evolutionary and Socio-Technical Analysis, Edward Elgar, Cheltenham, 2005.]), we conceptualise each of these routes as a bundle of niche activities within an Area of Innovation, deviating to differing degrees from the current mobility ‘regime’. We present empirical evidence and indications of ongoing development of niches in these three areas within the UK and Sweden, and explore processes of co-evolution, divergence and tension within and between niches. Findings indicate recent market penetration of novel transport technologies, more advanced than modal shift or demand management activities; however, different transport technologies are more successful in each country. We also identify examples of a close relationship between development of radical vehicle/fuel technologies and provision of mobility services; and information technology as a driver in all three areas of innovation. We conclude that future innovation in transport depends on diversity, hybridisation, and co-evolution of niches. Finally, policy implications are discussed.     

A theory of innovation for process-based innovations such as nanotechnology

Many see Nanotechnology as the technology that will underlie the next Schumpeterian wave creating new opportunities for wealth and job creation. Further it is a process based or materials technology. Yet all currently used models of innovation are based on assembled products or service products and these simply do not recognize the differences in materials products nor the “enabling” nature of Nanotechnologies. If nanotechnology is poised to become the economic engine of this millennium and if current models of innovation, which are utilized, by policy makers and firm based strategist alike are based on technology product paradigms that are dissimilar to the realities of nanotechnology and other process-based technologies then there is cause for concern.Here the authors provide a model and supporting cases demonstrating a new process or materials based innovation model that is based on the tight coupling between product and process innovation of not only Nanotechnology-based products but other process-based products. This is an important finding, because it identifies and remedies a gap in the literature associated with earlier process and product innovation models. For process-based products like materials, food, chemicals and nanotechnologies any change to the manufacturing processes results in significant changes in end product features. The implications of this model to practice are considered.     

ZP-Stichwort: Offshoring

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Futures hedging using dynamic models of the variance/covariance structure

Dynamic futures‐hedging ratios are estimated across seven markets using generalized models of the variance/covariance structure. The hedging performances of the resultant dynamic strategies are then compared with static and naïve strategies, both in‐ and out‐of‐sample. Bayesian‐adjusted hedge ratios also are employed as error purgers. The empirical results indicate that the generalized dynamic models are well specified and that their use in determining optimal hedge ratios can lead to improvements in hedging performance as measured by the volatilities of the returns on the optimally hedged position. © 2003 Wiley Periodicals, Inc. Jrl Fut Mark 23:241–260, 2003     

Directly measuring early exercise premiums using American and European S&P 500 Index options

The Chicago Board Options Exchange concurrently listed European‐style and American‐style options on the Standard and Poor's 500 Index from April 2, 1986 through June 20, 1986. This unique time period allows for a direct measurement of the early exercise premium in American‐style index options. In this study, using ask quotes, we find average early exercise premiums ranging from 5.04 to 5.90% for calls, and from 7.97 to 10.86% for puts. Additionally, we are able to depict a potentially useful functional form of the early exercise premium. As in previous studies, we find some instances of negative early exercise premiums. However, a trading simulation shows that traders must be able to trade within the bid–ask spread to profit from these apparent arbitrage opportunities. © 2003 Wiley Periodicals, Inc. Jrl Fut Mark 23:287–313, 2003