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.

Estimation of functional connectivity from electromagnetic signals and the amount of empirical data required

An increasing number of neuroimaging studies are concerned with the identification of interactions or statistical dependencies between brain areas. Dependencies between the activities of different brain regions can be quantified with functional connectivity measures such as the cross-correlation coefficient. An important factor limiting the accuracy of such measures is the amount of empirical data available. For event-related protocols, the amount of data also affects the temporal resolution of the analysis. We use analytical expressions to calculate the amount of empirical data needed to establish whether a certain level of dependency is significant when the time series are autocorrelated, as is the case for biological signals. These analytical results are then contrasted with estimates from simulations based on real data recorded with magnetoencephalography during a resting-state paradigm and during the presentation of visual stimuli. Results indicate that, for broadband signals, 50-100 s of data is required to detect a true underlying cross-correlations coefficient of 0.05. This corresponds to a resolution of a few hundred milliseconds for typical event-related recordings. The required time window increases for narrow band signals as frequency decreases. For instance, approximately 3 times as much data is necessary for signals in the alpha band. Important implications can be derived for the design and interpretation of experiments to characterize weak interactions, which are potentially important for brain processing.

The accuracy of parameter estimation from noisy data, with application to resonance peak estimation in distributed Brillouin sensing

Distributed Brillouin sensing of strain and temperature works by making spatially resolved measurements of the position of the measurand-dependent extremum of the resonance curve associated with the scattering process in the weakly nonlinear regime. Typically, measurements of backscattered Stokes intensity (the dependent variable) are made at a number of predetermined fixed frequencies covering the design measurand range of the apparatus and combined to yield an estimate of the position of the extremum. The measurand can then be found because its relationship to the position of the extremum is assumed known. We present analytical expressions relating the relative error in the extremum position to experimental errors in the dependent variable. This is done for two cases: (i) a simple non-parametric estimate of the mean based on moments and (ii) the case in which a least squares technique is used to fit a Lorentzian to the data. The question of statistical bias in the estimates is discussed and in the second case we go further and present for the first time a general method by which the probability density function (PDF) of errors in the fitted parameters can be obtained in closed form in terms of the PDFs of the errors in the noisy data.

The accuracy of parameter estimation from noisy data, with application to resonance peak estimation in distributed Brillouin sensing

Distributed Brillouin sensing of strain and temperature works by making spatially resolved measurements of the position of the measurand-dependent extremum of the resonance curve associated with the scattering process in the weakly nonlinear regime. Typically, measurements of backscattered Stokes intensity (the dependent variable) are made at a number of predetermined fixed frequencies covering the design measurand range of the apparatus and combined to yield an estimate of the position of the extremum. The measurand can then be found because its relationship to the position of the extremum is assumed known. We present analytical expressions relating the relative error in the extremum position to experimental errors in the dependent variable. This is done for two cases: (i) a simple non-parametric estimate of the mean based on moments and (ii) the case in which a least squares technique is used to fit a Lorentzian to the data. The question of statistical bias in the estimates is discussed and in the second case we go further and present for the first time a general method by which the probability density function (PDF) of errors in the fitted parameters can be obtained in closed form in terms of the PDFs of the errors in the noisy data.

Experimental demonstration of data-dependent pilot-aided phase noise estimation for CO-OFDM

We demonstrate a novel phase noise estimation scheme for CO-OFDM, in which pilot subcarriers are deliberately correlated to the data subcarriers. This technique reduces the overhead by a factor of 2. © OSA 2014.