Early identification of important patents through network centrality

One of the most challenging problems in technological forecasting is to identify as early as possible those technologies that have the potential to lead to radical changes in our society. In this paper, we use the US patent citation network (1926-2010) to test our ability to early identify a list of historically significant patents through citation network analysis. We show that in order to effectively uncover these patents shortly after they are issued, we need to go beyond raw citation counts and take into account both the citation network topology and temporal information. In particular, an age-normalized measure of patent centrality, called rescaled PageRank, allows us to identify the significant patents earlier than citation count and PageRank score. In addition, we find that while high-impact patents tend to rely on other high-impact patents in a similar way as scientific papers, the patents' citation dynamics is significantly slower than that of papers, which makes the early identification of significant patents more challenging than that of significant papers.Comment: 14 page

Technology upgrading of middle income economies: A new approach and results

We explore issues of measurement for technology upgrading of the economies moving from middle to high-income status. In exploring this issue, we apply theoretically relevant and empirically grounded middle level conceptual and statistical framework based on three dimensions: (i) Intensity (ii) breadth of technological upgrading, and (iii) technology and knowledge exchange. As an outcome, we construct a three-pronged composite indicator of technology upgrading based on 35 indicators which reflect different drivers and patterns of technology upgrading of countries at different income levels. We show that technology upgrading of middle-income economies is distinctively different from that of low and high-income economies. Our results suggest the existence of middle-income trap in technology upgrading - i.e. countries' technology upgrading activities are not reflected in their income levels. Based on the simple statistical analysis we show that the middle-income trap is present in all three aspects of technology upgrading, but their importance varies across different aspects. A trap seems to be higher for 'breadth' of technology upgrading than for 'intensity' of technology upgrading and is by far the highest for the dimension of knowledge and technology interaction with the global economy. Finally, our research shows that technology upgrading is a multidimensional process and that it would be methodologically wrong to aim for an aggregate index

Nanotechnology Publications and Patents: A Review of Social Science Studies and Search Strategies

This paper provides a comprehensive review of more than 120 social science studies in nanoscience and technology, all of which analyze publication and patent data. We conduct a comparative analysis of bibliometric search strategies that these studies use to harvest publication and patent data related to nanoscience and technology. We implement these strategies on 2006 publication data and find that Mogoutov and Kahane (2007), with their evolutionary lexical query search strategy, extract the highest number of records from the Web of Science. The strategies of Glanzel et al. (2003), Noyons et al. (2003), Porter et al. (2008) and Mogoutov and Kahane (2007) produce very similar ranking tables of the top ten nanotechnology subject areas and the top ten most prolific countries and institutions.nanotechnology, research and development, productivity, publications, patents, bibliometric analysis, search strategy

Are Prices Really Affected by Mergers?

During the 80s, several empirical studies have shown a positive correlation between concentration, prices and profits. It is well known that these estimates all suffer from simultaneity bias: market structure and prices are affected by common factors, some of which are not observable, which rules out any causal interpretation of cross-sectional correlations. Mergers are an interesting instrument to identify the (static) impact of concentration on prices, since they induce breaks in strategic interactions between actors. The few ex post studies on mergers that are currently available are difficult to generalize, because they pertain to specific markets. This study looks more systematically to selling prices in 63 sectors observed between 1989 and 2002. The approach that has been chosen is a difference in differences approach, applied to price movements around mergers. The rate of inflation in a sector where a merger has occurred is compared to a counterfactual. In a simple framework, in line with previous studies (McCabe 2002), this counterfactual would be built as the mean of inflation rates in other sectors. This paper focuses on more relevant estimates, provided by a factor model. This methodology allows tracking the profile of prices around mergers. We separate mergers between French firms and mergers between other European firms controlled by European authorities (and thus assumed to have affected the common market). We also distinguish mergers having led to an in-depth inquiry by competition authorities (« phase 2 ») and those benefiting from a shorter procedure (« phase 1 »). We observe an acceleration of price movements around the most important of French mergers, but not for the ones authorized under phase 1. We also observe a break in price movements for mergers between foreign firms examined by the European Commission, generally in the other direction.mergers, prices, factor models

Demand Forecasting: Evidence-based Methods

We looked at evidence from comparative empirical studies to identify methods that can be useful for predicting demand in various situations and to warn against methods that should not be used. In general, use structured methods and avoid intuition, unstructured meetings, focus groups, and data mining. In situations where there are sufficient data, use quantitative methods including extrapolation, quantitative analogies, rule-based forecasting, and causal methods. Otherwise, use methods that structure judgement including surveys of intentions and expectations, judgmental bootstrapping, structured analogies, and simulated interaction. Managers' domain knowledge should be incorporated into statistical forecasts. Methods for combining forecasts, including Delphi and prediction markets, improve accuracy. We provide guidelines for the effective use of forecasts, including such procedures as scenarios. Few organizations use many of the methods described in this paper. Thus, there are opportunities to improve efficiency by adopting these forecasting practices.Accuracy, expertise, forecasting, judgement, marketing.

Forecasting for Marketing

Research on forecasting is extensive and includes many studies that have tested alternative methods in order to determine which ones are most effective. We review this evidence in order to provide guidelines for forecasting for marketing. The coverage includes intentions, Delphi, role playing, conjoint analysis, judgmental bootstrapping, analogies, extrapolation, rule-based forecasting, expert systems, and econometric methods. We discuss research about which methods are most appropriate to forecast market size, actions of decision makers, market share, sales, and financial outcomes. In general, there is a need for statistical methods that incorporate the manager's domain knowledge. This includes rule-based forecasting, expert systems, and econometric methods. We describe how to choose a forecasting method and provide guidelines for the effective use of forecasts including such procedures as scenarios.forecasting, marketing