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New channels/old channels: Customer management and multi-channels: European Journal of Marketing, Vol. 40, No. 1-2. (2006), pp. 113-129.

Source: European Journal of Marketing, Vol. 40, No. 1-2. (2006), pp. 113-129.
Carotenoids in a food chain along a pollution gradient: Science of The Total Environment, Vol. 406, No. 1-2. (15 November 2008), pp. 247-255.Carote noids are synthesized by plants, therefore insects and birds must obtain them from their diet. They function in pigmentation and as antioxidants. We studied the carotenoid profiles in a model food chain (plant?insect? bird) in an air pollution gradient to find out whether heavy metal pollution affects the transfer of carotenoids across the trophic levels. Birch leaves showed higher ?-carotene and, one of the birch species (Betula pendula), higher total carotenoids levels in the polluted area. There was no difference in the lutein concentration of caterpillars? food source, birch leaves, between the study areas. Autumnal moth larvae accumulated lutein more efficiently than ?-carotene while sawfly larvae accumulated ?-carotene over lutein. Because of different antioxidant profiles in different leaf chewing insects their sensitivity to pollution stress may differ. The lutein concentration of plasma and feathers of Great tit nestlings did not differ along the pollution gradient. The lack of difference in lutein concentration of autumnal moth larvae along pollution gradient may partly explain the lutein concentrations of Great tit nestlings, since the abundance of autumnal moth larvae peak during the nestling phase of Great tit. The lutein concentration of autumnal moth larvae was positively associated to circulating plasma lutein level of Great tit indicating the importance of carotenoid rich diet during the nestling phase. In addition, the higher the plasma lutein concentration the more lutein was deposited to feathers, irrespective of the other possible functions of lutein in nestlings. We found that carotenoid levels differed between the polluted and the unpolluted area especially at lower levels of food chain: in birches and in caterpillars.

Source: Science of The Total Environment, Vol. 406, No. 1-2. (15 November 2008), pp. 247-255.
Knowledge and Communication: Essays on the Information Chain: (28 February 1991)

Source: (28 February 1991)
Some post-war models of the information chain: Journal of Librarianship and Information Science, Vol. 29, No. 4. (1 December 1997), pp. 179-187.Review s the literature of the information chain, analogous to ecology's food chain, taking the Royal Society Scientific Information Conference, 1948, as the seminal point. Describes eight successive models of the information chain each incorporating contemporary thoughts and experiences. Each model is labelled with the year to which it may be said to refer: Distribution of Scientific Information 1948; Document Network 1967; Dissemination of Scientific and Technical Information 1978; Structure of Scientific Literature 1979; Ecosystem of Scientific Communication 1980; Information Chain 1988; Information Chain 1989; Pathways of Information Flow 1993. Although of wide applicability, the focus of interest for information scientists tends to be the communication of learned information.

Source: Journal of Librarianship and Information Science, Vol. 29, No. 4. (1 December 1997), pp. 179-187.
Algorithms for scoring coreference chains: (1998), pp. 563-566.Scorin g the performance of a system is an extremely important aspect of coreference algorithm performance. The score for a particular run is the single strongest measure of how well the system is performing and it can strongly determine directions for further improvements. In this paper, we present several different scoring algorithms and detail their respective strengths and weaknesses for varying classes of processing. We also demonstrate that tasks like information extraction have very different needs from information retrieval in terms of how to score the performance of coreference annotation.

Source: (1998), pp. 563-566.
An introduction to MCMC for machine learning: (2003)This purpose of this introductory paper is threefold. First, it introduces the Monte Carlo method with emphasis on probabilistic machine learning. Second, it reviews the main building blocks of modern Markov chain Monte Carlo simulation, thereby providing and introduction to the remaining papers of this special issue. Lastly, it discusses new interesting research horizons.

Source: (2003)
Markov Chain Sampling Methods for Dirichlet Process Mixture Models: Journal of Computational and Graphical Statistics, Vol. 9, No. 2. (2000), pp. 249-265.This article reviews Markov chain methods for sampling from the posterior distribution of a Dirichlet process mixture model and presents two new classes of methods. One new approach is to make Metropolis-Has tings updates of the indicators specifying which mixture component is associated with each observation, perhaps supplemented with a partial form of Gibbs sampling. The other new approach extends Gibbs sampling for these indicators by using a set of auxiliary parameters. These methods are simple to implement and are more efficient than previous ways of handling general Dirichlet process mixture models with non-conjugate priors.

Source: Journal of Computational and Graphical Statistics, Vol. 9, No. 2. (2000), pp. 249-265.
A Split-Merge Markov Chain Monte Carlo Procedure for the Dirichlet Process Mixture Model: Journal of Computational & Graphical Statistics, Vol. 13, No. 1. (March 2004), pp. 158-182.This article proposes a split-merge Markov chain algorithm to address the problem of inefficient sampling for conjugate Dirichlet process mixture models. Traditional Markov chain Monte Carlo methods for Bayesian mixture models, such as Gibbs sampling, can become trapped in isolated modes corresponding to an inappropriate clustering of data points. This article describes a Metropolis-Has tings procedure that can escape such local modes by splitting or merging mixture components. Our algorithm employs a new technique in which an appropriate proposal for splitting or merging components is obtained by using a restricted Gibbs sampling scan. We demonstrate empirically that our method outperforms the Gibbs sampler in situations where two or more components are similar in structure.

Source: Journal of Computational & Graphical Statistics, Vol. 13, No. 1. (March 2004), pp. 158-182.
Small business and supply chain management: is there a fit?: Journal of Business Venturing, Vol. 20, No. 3. (May 2005), pp. 403-436.Confli ct exists over how supply chain management (SCM) affects small- and medium-sized enterprises (SMEs). On one hand, SCM can provide quality, cost, customer service, leverage and even risk reduction benefits for the SME. On the other hand, SCM exposes the SME to greater management and control hazards while reducing its private differentiatio n advantages. We test hypotheses relevant to the performance effects of SCM on SMEs using data collected from a recent survey of senior production managers. We find that SCM is negatively associated with SME performance after controlling for self-selection bias. We discuss several explanations for the result.

Source: Journal of Business Venturing, Vol. 20, No. 3. (May 2005), pp. 403-436.
Just in time, total quality management, and supply chain management: understanding their linkages and impact on business performance: Omega, Vol. 33, No. 2. (April 2005), pp. 153-162.In recent years, numerous approaches have been proposed to improve operations performance. Three in particular, just in time, supply chain management, and quality management, have received considerable attention. While the three are sometimes viewed and implemented as if they were independent and distinct, they can also be used as three prongs of an integrated operations strategy. This study empirically examines the extent to which just in time, supply chain management, and quality management are correlated, and how they impact business performance. Results demonstrate that at both strategic and operational levels, linkages exist between how just in time, total quality management, and supply chain management are viewed by organizations as part of their operations strategy. Results also indicate that a commitment to quality and an understanding of supply chain dynamics have the greatest effect on performance.

Source: Omega, Vol. 33, No. 2. (April 2005), pp. 153-162.

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