Employment comovements at the sectoral level over the business cycle

This paper extends the technique suggested by den Haan (2000) to investigate contemporaneous as well as lead and lag correlations among economic data for a range of forecast horizons. The technique provides a richer picture of the economic dynamics generating the data and allows one to investigate which variables lead or lag others and whether the lead or lag pattern is short term or long term in nature. The technique is applied to monthly sectoral level employment data for the U.S. and shows that among the ten industrial sectors followed by the U.S. Bureau of Labor Statistics, six tend to lead the other four. These six have high correlations indicating that the structural shocks generating the data movements are mostly in common. Among the four lagging industries, some lag by longer intervals than others and some have low correlations with the leading industries indicating that these industries are partially influenced by structural shocks beyond those generating the six leading industries.sectoral employment comovement, leading and lagging sectors, forecast errors, business cycles

A New Consumerism: The influence of social technologies on product design

Social media has enabled a new style of consumerism. Consumers are no longer passive recipients; instead they are assuming active and participatory roles in product design and production, facilitated by interaction and collaboration in virtual communities. This new participatory culture is blurring the boundaries between the specific roles of designer, consumer and producer, creating entrepreneurial opportunities for designers, and empowering consumers to influence product strategies. Evolving designer-consumer interactions are enabling an enhanced model of co-production, through a value-adding social exchange that is driving changes in consumer behaviour and influencing both product strategies and design practice. The consumer is now a knowledgeable participant, or prosumer, who can contribute to user–centered research through crowd sourcing, collaborate and co-create through open-source or open-innovation platforms, assist creative endeavors by pledging venture capital through crowd funding and advocate the product in blogs and forums. Social media- enabled product implementation strategies working in conjunction with digital production technologies (e.g. additive manufacture), enable consumer-directed adaptive customisation, product personalisation, and self-production, with once passive consumers becoming product produsers. Not only is social media driving unprecedented consumer engagement and significant behavioural change, it is emerging as a major enabler of design entrepreneurship, creating new collaborative opportunities. Innovative processes in design practice are emerging, such as the provision of digital artifacts and customisable product frameworks, rather than standardised manufactured solutions. This paper examines the influence of social media-enabled product strategies on the methodology of the next generation of product designers, and discusses the need for an educational response

Virtual Astronomy, Information Technology, and the New Scientific Methodology

All sciences, including astronomy, are now entering the era of information abundance. The exponentially increasing volume and complexity of modern data sets promises to transform the scientific practice, but also poses a number of common technological challenges. The Virtual Observatory concept is the astronomical community's response to these challenges: it aims to harness the progress in information technology in the service of astronomy, and at the same time provide a valuable testbed for information technology and applied computer science. Challenges broadly fall into two categories: data handling (or "data farming"), including issues such as archives, intelligent storage, databases, interoperability, fast networks, etc., and data mining, data understanding, and knowledge discovery, which include issues such as automated clustering and classification, multivariate correlation searches, pattern recognition, visualization in highly hyperdimensional parameter spaces, etc., as well as various applications of machine learning in these contexts. Such techniques are forming a methodological foundation for science with massive and complex data sets in general, and are likely to have a much broather impact on the modern society, commerce, information economy, security, etc. There is a powerful emerging synergy between the computationally enabled science and the science-driven computing, which will drive the progress in science, scholarship, and many other venues in the 21st century