Patent and publishing activity sequence over a technology's life cycle

The use of multiple indicators in analyzing technological developments and exploiting the increasing availability of information has been recommended widely in order to decrease systematic biases between single measures. One of the few frameworks that take multiple sources into account is the Technology Life Cycle indicators that provide a measure for the totality of sources available for analysis and take their timeliness into account, although the linear model that the framework represents is often questioned. The aim of this paper is to provide bibliometric studies with insight into the timely relevance of using different databases. To assess the reporting sequence between different databases, this paper measures the reporting activity of three case technologies in different databases and analyzes the yearly reporting volumes of a number of items that mention the technology in the databases as suggested by the TLC indicators. The results of this paper suggest that, when science is the source of new ideas and the driver for technological development and innovations, communication can happen in the order suggested by the TLC indicators. However, this model does not seem to be a general model for detecting and forecasting a technological life cycle. In addition, the results of the paper point to the possibility of studying non-linear models of innovation and contexts where this type of dynamics might take place.     

Overconfidence and consumption over the life cycle

Overconfidence is a widely documented phenomenon. In this paper, we study the implications of consumer overconfidence in a life-cycle consumption/saving model. Our main analytical result is a necessary and sufficient condition under which any degree of overconfidence concerning the mean return on savings can produce a hump in the work-life consumption profile. This condition is almost always met in the data. We show by simulations that overconfidence concerning the variance of the return can have little effect on the long-run average behavior of consumption over the life cycle, and that our basic conclusion is fairly robust with various realistic modifications to the baseline model. We interpret the general applicability of our analytical framework and discuss our numerical results in the light of aggregate consumption data.     

Generic innovation dynamics across the industrial technology life cycle: Platform equation modeling of invention and innovation activity

We describe here a generic approach to innovation dynamics based on an integrated framework for inventions and innovations applied via a platform equation and model across the industrial technology life cycle. We test the model for metals and other materials, and demonstrate that this model correctly describes the production activity for several materials and energy conversion technologies.Innovation activity patterns are shown for several oxides, metals, oil and wind energy and its derivatives. The metals Cu, Al, W, Mo and Pb are particularly studied for the amount produced over time. The total activity for the metals encompasses both the invention and innovation stage for a particular metal. Four major stages and two sub stages are identified for the discovery (invention) and subsequent growth regimes (i.e. the innovation stage). The pattern equation appears to clearly capture all these stages for the metals studied — work is ongoing for similar analyses of energy and other materials. Although the metals studied existed over differing periods (e.g. copper greater than 200 years whereas aluminum, just over 100 years), one single pattern equation appears to capture all the major trends. The use of the model is also shown for productivity analysis, especially for the condition of radical innovation (very rapid growth). For sustained radical innovation, namely, when the output of the produced material per unit time, keeps on increasing with time, there are various factors which may influence growth. For the conditions where thermal activation and plant size are the dominant variables, their impact on the growth may be examined in the context of the pattern equation. A preliminary analysis of oxide production activity also appears to follow this same innovation model.The results suggest a fertile field of future research extending the initial platform equation model to include R&D, Patents, and Performance, as well as Sales, as innovation activity. Further, the model shows promise in combination with the ARI methodology model for analysis and assessment of existing and future industrial technology life cycles involving material, process, product, software and service innovations.