The impact of corporate volunteering on CSR image: a consumer perspective

Received: 29 June 2013 / Accepted: 15 January 2014Abstract Corporate volunteering (CV) is known to be an effective employee engagement initiative. However, despite the prominence of corporate social responsibility (CSR) in academia and practice, research is yet to investigate whether and how CV may influence consumer perceptions of CSR image and subsequent consumer behaviour. Data collected using an online survey in Australia show perceived familiarity with a company’s CV programme to positively impact CSR image and firm image, partially mediated by others-centred attributions. CSR image, in turn, strengthens affective and cognitive loyalty as well as word-of-mouth. Further analysis reveals the moderating effect of perceived leveraging of the corporate volunteering programme, customer status and the value individuals place on CSR. The paper concludes with theoretical and managerial implications, as well as an agenda for future research.Carolin Plewa, Jodie Conduit, Pascale G. Quester, Claire Johnso

The Use of EST Expression Matrixes for the Quality Control of Gene Expression Data

EST expression profiling provides an attractive tool for studying differential gene expression, but cDNA libraries' origins and EST data quality are not always known or reported. Libraries may originate from pooled or mixed tissues; EST clustering, EST counts, library annotations and analysis algorithms may contain errors. Traditional data analysis methods, including research into tissue-specific gene expression, assume EST counts to be correct and libraries to be correctly annotated, which is not always the case. Therefore, a method capable of assessing the quality of expression data based on that data alone would be invaluable for assessing the quality of EST data and determining their suitability for mRNA expression analysis. Here we report an approach to the selection of a small generic subset of 244 UniGene clusters suitable for identification of the tissue of origin for EST libraries and quality control of the expression data using EST expression information alone. We created a small expression matrix of UniGene IDs using two rounds of selection followed by two rounds of optimisation. Our selection procedures differ from traditional approaches to finding "tissue-specific" genes and our matrix yields consistency high positive correlation values for libraries with confirmed tissues of origin and can be applied for tissue typing and quality control of libraries as small as just a few hundred total ESTs. Furthermore, we can pick up tissue correlations between related tissues e.g. brain and peripheral nervous tissue, heart and muscle tissues and identify tissue origins for a few libraries of uncharacterised tissue identity. It was possible to confirm tissue identity for some libraries which have been derived from cancer tissues or have been normalised. Tissue matching is affected strongly by cancer progression or library normalisation and our approach may potentially be applied for elucidating the stage of normalisation in normalised libraries or for cancer staging