Patterns of Innovation in UK Industry: Exploring the CIS Data to Contrast High and Low Technology Industries.

This paper is divided into two parts. The first part is an examination of the OECD classification of industries into high, medium and low technology industries, to look at the basis for this classification and to use that as a benchmark with which to classify the Community Innovation Survey (CIS) data for the UK into similar groupings. The industries are ranked according to their research intensities and the rankings between the two datasets are compared. Some features of the UK rankings are highlighted and anomalies between the two datasets pointed out. The second part of the paper goes on to use the OECD classification into high, medium and low technology industries, applied to the CIS dataset, to contrast patterns of innovation in high technology industries with those in low technology industries. We build on the three types of innovation surveyed in the CIS, namely product, process and organisational innovation and contrast those types across high and low technology sectors. The expected relationship between high technology industries and product innovation holds - that enterprises tend to do more product innovation, the higher their research intensity. But process innovation does not conform to this pattern and there is not such a clear division between high and low technology industries. However the way they do process innovations differs with high technology industries more reliant on internal resources whereas lower technology industries tend to do it using external resources in collaboration with others. Organisational innovation is more complex, with certain types of innovation done as widely by lower technology industries as by the more research intensive industries. This supports the idea that all types of innovation should be considered, with the diffusion of ICTs making an impact across the technological spectrum of industries and showing up in various forms of organisational innovation

The global financial crisis: trying to understand the global trade downturn and recovery

This paper aims to shed light on why the downturn in global trade during the intensification of the financial crisis in 2008Q4-2009Q1 was so severe and synchronized across the world, and also examines the subsequent recovery in global trade during 2009Q2-2010Q1. The paper finds that a structural imports function which captures the different and time-varying importintensities of the components of total final expenditure can explain the sharp decline in global imports of goods and services. By contrast, a specification based on aggregate total expenditure can not fully capture the global trade downturn. In particular, panel estimates for a large number of OECD countries suggest that the high import-intensity of exports at the country-level can explain a significant proportion of the decline in world imports during the crisis, while declines in the highly import-intensive expenditure category of investment also contributed to the remaining fall in global trade. At the same time, the high and rising import-intensity of exports also reflects and captures the rapid growth in “vertical specialisation”, suggesting that widespread global production chains may have amplified the downturn in world trade and partly explains its high-degree of synchronisation across the globe. In addition, the estimates find that stockbuilding, business confidence and credit conditions also played a role in the global trade downturn. Meanwhile, the global trade recovery (2009Q2-2010Q1) can only be partially explained by differential elasticities for the components of demand (although the results confirm that the upturn in OECD imports was also driven by strong export growth and the associated reactivation of global production chains, as well as the recovery in stockbuilding and the fiscal stimulus). This may be due in part to the many policy measures that were implemented to boost global trade at that time and which can not be captured by the specification. JEL Classification: E0, F01, F10, F15, F17financial crisis, forecasting, global trade downturn and recovery, Globalisation, import-intensity of components of total final expenditure, synchronisation, timevarying parameters, vertical specialisation

One More Awareness Gap? The Behaviour–Impact Gap Problem

Preceding research has made hardly any attempt to measure the ecological impacts of pro-environmental behaviour in an objective way. Those impacts were rather supposed or calculated. The research described herein scrutinized the ecological impact reductions achieved through pro-environmental behaviour and raised the question how much of a reduction in carbon footprint can be achieved through voluntary action without actually affecting the socio-economic determinants of life. A survey was carried out in order to measure the difference between the ecological footprint of “green” and “brown” consumers. No significant difference was found between the ecological footprints of the two groups—suggesting that individual pro-environmental attitudes and behaviour do not always reduce the environmental impacts of consumption. This finding resulted in the formulation of a new proposition called the BIG (behaviour–impact gap) problem, which is an interesting addition to research in the field of environmental awareness gaps

Material implication of Chile’s economic growth: combining material flow accounting (MFA) and structural decomposition analysis

Over the last three decades, the economic integration of the Chilean economy into global markets has been taking place at a rapid pace. For example, in 1986, exports represented 29% of GDP while in 1996 they had increased to 38% of GDP. This period of time was characterized by strong economic growth with an average annual growth rate of about 10%. From a physical perspective, material requirements more than doubled from 220 to 500 million tons of direct material inputs (DMI) during the same decade (the rate of material growth requirements was around 13% per year). The main objective of this study is to explain the changes in DMI by using a structural decomposition analysis (SDA). The changes in material flow accounting (MFA) were broken down into the effects caused by changes in resource use per unit of output (material intensity effect), changes between and within sectors (structural change effect), changes in the composition of final demand (mix effect), changes due to shifting shares of domestic final demand and export categories (category effect) and finally changes in the overall level of economic activities (level effects). The results, as a percentage of the total level of DMI used in 1986, indicate that economic growth was the major source of material changes (109%). The material intensity and category effects explained 31% and 14% of the increase, respectively. The increase in the material intensity is mainly due to a declining quality of ores in copper production. However, these components were partly compensated by the structure (− 14%) and mix (− 13%) effects. Therefore, for a Southern American country such as Chile, the main causes of these changes in material consumption have been a combination of the nature of economic growth along with an increase in export production and material intensity of production

Technology sourcing by large incumbents through acquisition of small firms

Innovation activities in high technology industries provide considerable challenges for technology and innovation management. In particular, since these industries have a long history of radical innovations taking place through distinct industry cycles of higher and lower demand, firms frequently consider the option to use acquisitions as a means for technology sourcing. The paper investigates this behaviour for three high technology industries, namely semiconductor manufacturing, biotechnology and electronic design automation which is a specific sub-segment of the semiconductor industry. It analyses the association of firm characteristics with different aspects of acquisition behaviour with a particular focus being put on innovation-related firm characteristics. The paper confirms a substitutive relationship between acquisitions and own research activities as well as between own and acquired firm patenting, but also finds that firm size, financial conditions and geographical origin of the firm matter for acquisition behaviour.Acquisition, innovation, high technology, quantitative methods, research, R&D

An Evaluation of Popular Copy-Move Forgery Detection Approaches

A copy-move forgery is created by copying and pasting content within the same image, and potentially post-processing it. In recent years, the detection of copy-move forgeries has become one of the most actively researched topics in blind image forensics. A considerable number of different algorithms have been proposed focusing on different types of postprocessed copies. In this paper, we aim to answer which copy-move forgery detection algorithms and processing steps (e.g., matching, filtering, outlier detection, affine transformation estimation) perform best in various postprocessing scenarios. The focus of our analysis is to evaluate the performance of previously proposed feature sets. We achieve this by casting existing algorithms in a common pipeline. In this paper, we examined the 15 most prominent feature sets. We analyzed the detection performance on a per-image basis and on a per-pixel basis. We created a challenging real-world copy-move dataset, and a software framework for systematic image manipulation. Experiments show, that the keypoint-based features SIFT and SURF, as well as the block-based DCT, DWT, KPCA, PCA and Zernike features perform very well. These feature sets exhibit the best robustness against various noise sources and downsampling, while reliably identifying the copied regions.Comment: Main paper: 14 pages, supplemental material: 12 pages, main paper appeared in IEEE Transaction on Information Forensics and Securit

Peak residential electricity demand and social practices: deriving flexibility and greenhouse gas intensities from time use and locational data

Peak residential electricity demand takes place when people conduct simultaneous activities at specific times of the day. Social practices generate patterns of demand and can help understand why, where, with whom and when energy services are used at peak time. The aim of this work is to make use of recent UK time use and locational data to better understand: (i) how a set of component indices on synchronisation, variation, sharing and mobility indicate flexibility to shift demand; and (ii) the links between people’s activities and peaks in greenhouse gases’ intensities. The analysis is based on a recent UK time use dataset, providing 1 minute interval data from GPS devices and 10 minute data from diaries and questionnaires for 175 data days comprising 153 respondents. Findings show how greenhouse gases’ intensities and flexibility to shift activities vary throughout the day. Morning peaks are characterised by high levels of synchronisation, shared activities and occupancy, with low variation of activities. Evening peaks feature low synchronisation, and high spatial mobility variation of activities. From a network operator perspective, the results indicate that periods with lower flexibility may be prone to more significant local network loads due to the synchronization of electricity-demanding activities