Synthesis report with pro-poor trade research findings and policy recommandations

The purpose of the project was to investigate international trade in fisheries products and its relationship to poverty alleviation and livelihoods of poor aquatic resource users in developing countries in Asia, and to identify options to improve the effectiveness of poverty reduction through international seafood trade. The project directly addressed the EC-PREP priority area of trade and development, and indirectly provided valuable insight to two other priority areas: food security and sustainable rural development; and institutional capacity building. [PDF contains 60 pages.

Design as a driver of innovation in the East Midlands

This study reports on research and consultation with local stakeholders to discuss the role of design as part of the innovation agenda in the East Midlands. A key finding of this research iss that the East Midlands has a very strong design industry and that businesses in the region use design to a much greater extent than in most other regions

Semantic data mining and linked data for a recommender system in the AEC industry

Even though it can provide design teams with valuable performance insights and enhance decision-making, monitored building data is rarely reused in an effective feedback loop from operation to design. Data mining allows users to obtain such insights from the large datasets generated throughout the building life cycle. Furthermore, semantic web technologies allow to formally represent the built environment and retrieve knowledge in response to domain-specific requirements. Both approaches have independently established themselves as powerful aids in decision-making. Combining them can enrich data mining processes with domain knowledge and facilitate knowledge discovery, representation and reuse. In this article, we look into the available data mining techniques and investigate to what extent they can be fused with semantic web technologies to provide recommendations to the end user in performance-oriented design. We demonstrate an initial implementation of a linked data-based system for generation of recommendations

Manufacturing advisory service in the East Midlands – historical evaluation

A report on the longitudinal evaluation of the Manufacturing Advisory Service (MAS) covering the period from its establishment in 2005. The evaluation looks at net economic impact and the appropriateness of the design and delivery of the service, in addition to identifying any areas for improvement

Recommendation Networks and the Long Tail of Electronic Commerce

It has been conjectured that the peer-based recommendations associated with electronic commerce lead to a redistribution of demand from popular products or 'blockbusters' to less popular or 'niche' products, and that electronic markets will therefore be characterized by a 'long tail' of demand and revenue. In this paper, we develop a novel method to test this conjecture and we report on results contrasting the demand distributions of books in over 200 distinct categories on Amazon.com. Viewing each product as having a unique position in a hyperlinked network of recommendations between products that is analogous to shelf position in traditional commerce, we quantify the extent to which a product is in uenced by its recommendation network position by using a variant of Google's PageRank measure of centrality. We then associate the average level of network influence on each category with the inequality in the distribution of its demand and revenue, quantifying this inequality using the Gini coefficient derived from the category's Lorenz curve. We establish that categories whose products are influenced more by recommendations have significantly flatter demand distributions, even after controlling for variations in average category demand, the category's size and measures of price dispersion. Our empirical findings indicate that doubling the average influence of recommendations on a category is associated with an average increase in the relative demand for the least popular 20% of products by about 50%, and a average reduction in the relative demand for the most popular 20% by about 12%. We also show that this e¤ect is enhanced when there is assortative mixing in the recommendation network, and in categories whose products are more evenly influenced by recommendations. The direction of these results persist across time, across both demand and revenue distributions, and across both daily and weekly demand aggregations. Our work offers new ideas for assessing the influence of networks on demand and revenue patterns in electronic commerce, and provides new empirical evidence supporting the impact of visible recommendations on the long tail of electronic commerce

Social Media’s impact on Intellectual Property Rights

This is a draft chapter. The final version is available in Handbook of Research on Counterfeiting and Illicit Trade, edited by Peggy E. Chaudhry, published in 2017 by Edward Elgar Publishing Ltd, https://doi.org/10.4337/9781785366451. This material is for private use only, and cannot be used for any other purpose without further permission of the publisher.Peer reviewe