Learning from openness:the dynamics of breadth in external innovation linkages

We explore how openness in terms of external linkages generates learning effects, which enable firms to generate more innovation outputs from any given breadth of external linkages. Openness to external knowledge sources, whether through search activity or linkages to external partners in new product development, involves a process of interaction and information processing. Such activities are likely to be subject to a learning process, as firms learn which knowledge sources and collaborative linkages are most useful to their particular needs, and which partnerships are most effective in delivering innovation performance. Using panel data from Irish manufacturing plants, we find evidence of such learning effects: establishments with substantial experience of external collaborations in previous periods derive more innovation output from openness in the current period. © 2013 The Authors. Strategic Management Journal published by John Wiley & Sons Ltd.

Effective forms of market orientation across the business cycle:a longitudinal analysis of business-to-business firms

Macroeconomic developments, such as the business cycle, have a remarkable influence on firms and their performance. In business-to-business (B-to-B) markets characterized by a strong emphasis on long-term customer relationships, market orientation (MO) provides a particularly important safeguard for firms against fluctuating market forces. Using panel data from an economic upturn and downturn, we examine the effectiveness of different forms of MO (i.e., customer orientation, competitor orientation, interfunctional coordination, and their combinations) on firm performance in B-to-B firms. Our findings suggest that the impact of MO increases especially during a downturn, with interfunctional coordination clearly boosting firm performance and, conversely, competitor orientation becoming even detrimental. The findings further indicate that both the role of MO and its most effective forms vary across industry sectors, MO having a particularly strong impact on performance among B-to-B service firms. The findings of our study provide guidelines for executives to better manage performance across the business cycle and tailor their investments in MO more effectively, according to the firm's specific industry sector.

Industrial policy, FDI and employment:Still 'missing a strategy'

This paper contrasts the effects of trade, inward FDI and technological development upon the demand for skilled and unskilled workers in the UK. By focussing on industry level data panel data on smaller firms, the paper also contrasts these effects with those generated by large scale domestic investment. The analysis is placed within the broader context of shifts in British industrial policy, which has seen significant shifts from sectoral to horizontal measures and towards stressing the importance of SMEs, clusters and new technology, all delivered at the regional scale. This, however, is contrasted with continued elements of British and EU regional policy which have emphasised the attraction of inward investment in order to alleviate regional unemployment. The results suggest that such policies are not naturally compatible; that while both trade and FDI benefit skilled workers, they have adverse effects on the demand for unskilled labour in the UK. At the very least this suggests the need for a range of policies to tackle various targets (including in this case unemployment and social inclusion) and the need to integrate these into a coherent industrial strategy at various levels of governance, whether regional and/or national. This has important implications for the form of any 'new' industrial policy.

Discretion in accounting for pensions under IAS 19:using the ‘magic telescope’?

We use a panel data set of UK-listed companies over the period 2005–2009 to analyse the actuarial assumptions used to value pension plan liabilities under IAS 19. The valuation process requires companies to make assumptions about financial and demographic variables, notably discount rate, price inflation, salary inflation and mortality/life expectancy of plan members/beneficiaries. We use regression analysis to analyse the relationships between these key assumptions (except mortality, where disclosures are limited) and company-specific factors such as the pension plan funding position and duration of pension liabilities. We find evidence of selective ‘management’ of the three assumptions investigated, although the nature of this appears to differ from the findings of US authors. We conclude that IAS 19 does not prevent the use of managerial discretion, particularly by companies whose pension plan funding positions are weak, thereby reducing the representational faithfulness of the reported pension figures. We also highlight that the degree of discretion used reflects the extent to which IAS 19 defines how the assumptions are to be determined. We therefore suggest that companies should be encouraged to justify more explicitly their choice of assumptions.

An allocation Malmquist index with an application in the China securities industry

This paper proposes an allocation Malmquist index which is inspired by the work on the non-parametric cost Malmquist index. We first show that how to decompose the cost Malmquist index into the input-oriented Malmquist index and the allocation Malmquist index. An application in corporate management of the China securities industry with the panel data set of 40 securities companies during the period 2005–2011 shows the practicality of the propose model.

DVMS 1.5: A user manual (the data visualization and modeling system)

The data available during the drug discovery process is vast in amount and diverse in nature. To gain useful information from such data, an effective visualisation tool is required. To provide better visualisation facilities to the domain experts (screening scientist, biologist, chemist, etc.),we developed a software which is based on recently developed principled visualisation algorithms such as Generative Topographic Mapping (GTM) and Hierarchical Generative Topographic Mapping (HGTM). The software also supports conventional visualisation techniques such as Principal Component Analysis, NeuroScale, PhiVis, and Locally Linear Embedding (LLE). The software also provides global and local regression facilities . It supports regression algorithms such as Multilayer Perceptron (MLP), Radial Basis Functions network (RBF), Generalised Linear Models (GLM), Mixture of Experts (MoE), and newly developed Guided Mixture of Experts (GME). This user manual gives an overview of the purpose of the software tool, highlights some of the issues to be taken care while creating a new model, and provides information about how to install & use the tool. The user manual does not require the readers to have familiarity with the algorithms it implements. Basic computing skills are enough to operate the software.

miniDVMS v1.8 : A user manual(The data visualization and modeling system)

Today, the data available to tackle many scientific challenges is vast in quantity and diverse in nature. The exploration of heterogeneous information spaces requires suitable mining algorithms as well as effective visual interfaces. miniDVMS v1.8 provides a flexible visual data mining framework which combines advanced projection algorithms developed in the machine learning domain and visual techniques developed in the information visualisation domain. The advantage of this interface is that the user is directly involved in the data mining process. Principled projection methods, such as generative topographic mapping (GTM) and hierarchical GTM (HGTM), are integrated with powerful visual techniques, such as magnification factors, directional curvatures, parallel coordinates, and user interaction facilities, to provide this integrated visual data mining framework. The software also supports conventional visualisation techniques such as principal component analysis (PCA), Neuroscale, and PhiVis. This user manual gives an overview of the purpose of the software tool, highlights some of the issues to be taken care while creating a new model, and provides information about how to install and use the tool. The user manual does not require the readers to have familiarity with the algorithms it implements. Basic computing skills are enough to operate the software.