Learning difficulties: collaborative inter-organisational information system use within UK retail supply networks

Inter-organisational information systems (IOIS) have been introduced to support collaborative retail supply relationships, yet how these systems are used is not well understood. This paper presents analysis of an ideographic case study of a dynamic United Kingdom grocery sector supply network. Using Archer's (1995) social change theory we explore how changes to buyer-supplier relationship structures re-conditioned individual actors' situational logics in a way that created network learning difficulties. Our analysis shows how actors' inter-organisational information system use reinforced pre-existing bargaining positions and improved already powerful actors' relative negotiating strength. This paper demonstrates the value of multi-level analysis in furthering understanding of the complex relationships between processes of network and individual learning

Business Models and their Implications for Skills

The dominant political-economic narrative of our time is that, under conditions of global competition with low-wage economies able to undercut even efficient western firms, the only viable and sustainable route to competitiveness is to trade on high value-added goods and services and that these in turn require enhanced skills and knowledge. This kind of analysis finds echo and sustenance in the management literature concerning 'knowledge'. Drawing upon a series of case studies this monograph reveals a more varied and complex pattern of possibilities

Devolved governance systems

This article assesses the extent, nature and outcomes of the recently devolved health service governance in the four countries which comprise the United Kingdom. This four-part configuration can be seen as a natural experiment in comparative governance which could therefore carry important lessons not only for the UK but in other countries too. While remaining under the aegis of the National Health Service, each constituent devolved administration has a developed a substantially different governance system. These systems reflect fundamental issues and priorities concerning the decentring of authority, the production and deployment of authority, the suite of incentives required and the preferred role of quasi-market mechanisms. The paper makes an evaluation of the strengths and weaknesses of each governance regime

Towards a New Model of Leadership for the NHS

This paper was commissioned by the NHS Leadership Academy as a contribution to thinking about the future development of leadership in and around the NHS. It was prepared in collaboration with the Hay Group. The backdrop and one of the triggers was the launch of a new suite of professional development programmes sponsored and organised by the NHS Leadership Academy. From the research reported in this paper a new framework for leadership in the healthcare is built. This is being used to guide the construction of a new Leadership Model. To quote the NLA this 'will be a well-researched, evidence-based model that reflects the values of the NHS, what we know about effective leadership, what we have learned from the Leadership Framework and what our patients and communities are now asking from us as leaders'

Clinical leadership in action

The nature, scope and potential for clinical leadership are explored by focusing on four cases. These were cross-boundary service redesign attempts for dementia and sexual health in London and Greater Manchester. Each case contained multiple organisations, including GPs and primary care trusts, acute hospital trusts, mental health trusts, local authorities and independent sector provider

Do employee-owned firms produce more positive employee behavioural outcomes? If not why not? A British-Spanish comparative analysis

Whether ‘employee ownership’ takes the form of worker cooperatives, co-ownership or simply employee share ownership plans, there are normally high expectations that a range of positive outcomes will result. Yet many empirically-based studies tend to find a much more complex picture. An influential segment of that empirical literature has posited the need for a number of mutually-reinforcing workforce management components to be in place alongside co-ownership. Drawing on detailed case research in two large and successful co-owned retailers in Spain and Britain this paper examines the role of these wider elements supporting employee ownership. We find that employee ownership can be linked to higher productivity and lower employee turnover, while at the same time being linked to higher absenteeism and mixed effects on attitudes. Expectations held by managers and employees are higher; these expectations are not always fully met. The role of managers was also found to be crucial

Consistent Estimation of Low-Dimensional Latent Structure in High-Dimensional Data

We consider the problem of extracting a low-dimensional, linear latent variable structure from high-dimensional random variables. Specifically, we show that under mild conditions and when this structure manifests itself as a linear space that spans the conditional means, it is possible to consistently recover the structure using only information up to the second moments of these random variables. This finding, specialized to one-parameter exponential families whose variance function is quadratic in their means, allows for the derivation of an explicit estimator of such latent structure. This approach serves as a latent variable model estimator and as a tool for dimension reduction for a high-dimensional matrix of data composed of many related variables. Our theoretical results are verified by simulation studies and an application to genomic data

Statistical significance of variables driving systematic variation

There are a number of well-established methods such as principal components analysis (PCA) for automatically capturing systematic variation due to latent variables in large-scale genomic data. PCA and related methods may directly provide a quantitative characterization of a complex biological variable that is otherwise difficult to precisely define or model. An unsolved problem in this context is how to systematically identify the genomic variables that are drivers of systematic variation captured by PCA. Principal components (and other estimates of systematic variation) are directly constructed from the genomic variables themselves, making measures of statistical significance artificially inflated when using conventional methods due to over-fitting. We introduce a new approach called the jackstraw that allows one to accurately identify genomic variables that are statistically significantly associated with any subset or linear combination of principal components (PCs). The proposed method can greatly simplify complex significance testing problems encountered in genomics and can be utilized to identify the genomic variables significantly associated with latent variables. Using simulation, we demonstrate that our method attains accurate measures of statistical significance over a range of relevant scenarios. We consider yeast cell-cycle gene expression data, and show that the proposed method can be used to straightforwardly identify statistically significant genes that are cell-cycle regulated. We also analyze gene expression data from post-trauma patients, allowing the gene expression data to provide a molecularly-driven phenotype. We find a greater enrichment for inflammatory-related gene sets compared to using a clinically defined phenotype. The proposed method provides a useful bridge between large-scale quantifications of systematic variation and gene-level significance analyses.Comment: 35 pages, 1 table, 6 main figures, 7 supplementary figure

Multiple locus linkage analysis of genomewide expression in yeast.

With the ability to measure thousands of related phenotypes from a single biological sample, it is now feasible to genetically dissect systems-level biological phenomena. The genetics of transcriptional regulation and protein abundance are likely to be complex, meaning that genetic variation at multiple loci will influence these phenotypes. Several recent studies have investigated the role of genetic variation in transcription by applying traditional linkage analysis methods to genomewide expression data, where each gene expression level was treated as a quantitative trait and analyzed separately from one another. Here, we develop a new, computationally efficient method for simultaneously mapping multiple gene expression quantitative trait loci that directly uses all of the available data. Information shared across gene expression traits is captured in a way that makes minimal assumptions about the statistical properties of the data. The method produces easy-to-interpret measures of statistical significance for both individual loci and the overall joint significance of multiple loci selected for a given expression trait. We apply the new method to a cross between two strains of the budding yeast Saccharomyces cerevisiae, and estimate that at least 37% of all gene expression traits show two simultaneous linkages, where we have allowed for epistatic interactions. Pairs of jointly linking quantitative trait loci are identified with high confidence for 170 gene expression traits, where it is expected that both loci are true positives for at least 153 traits. In addition, we are able to show that epistatic interactions contribute to gene expression variation for at least 14% of all traits. We compare the proposed approach to an exhaustive two-dimensional scan over all pairs of loci. Surprisingly, we demonstrate that an exhaustive two-dimensional scan is less powerful than the sequential search used here. In addition, we show that a two-dimensional scan does not truly allow one to test for simultaneous linkage, and the statistical significance measured from this existing method cannot be interpreted among many traits

Factors affecting the adoption of quality assurance technologies in healthcare

Purpose – In the light of public concern and of strong policy emphasis on quality and safety in the nursing care of patients in hospital settings, this paper focuses on the factors affecting the adoption of innovative quality assurance technologies. Design/methodology/approach – Two sets of complementary literatures were mined for key themes. Next, new empirical insights were sought. Data gathering was conducted in three phases. The first involved contact with NHS Technology Hubs and other institutions which had insights into leading centres in quality assurance technologies. The second phase was a series of telephone interviews with lead nurses in those hospitals which were identified in the first phase as comprising the leading centres. The third phase comprised a series of face to face interviews with innovators and adopters of healthcare quality assurance technologies in five hospital trusts. Findings – There were three main sets of findings. First, despite the strong policy push and the templates established at national level, there were significant variations in the nature and robustness of the quality assurance toolkits that were developed, adapted and adopted. Second, in most of the adopting cases there were important obstacles to the full adoption of the toolkits that were designed. Third, the extent and nature of the ambition of the developers varied dramatically – some wished to see their work impacting widely across the health service; others had a number of different reasons for wanting to restrict the impact of their work. Originality/value – The general concerns about front-line care and the various inquiries into care quality failures emphasise the need for improved and consistent care quality assurance methodologies and practice. The technology adoption literature gives only partial insight into the nature of the challenges; this paper offers specific insights into the factors inhibiting the full adoption of quality assurance technologies in ward-based care