An Ethical Basis for Relationship Marketing: A Virtue Ethics Perspective

Purpose – The purpose of this paper is to provide an ethical foundation for relationship marketing using a virtue ethics approach. Design/methodology/approach – The approach is a conceptual one providing a background on relationship marketing from both American and European perspectives. Earlier studies published in EJM on relationship marketing are featured in a table. Findings – The proposed ethical relationship marketing approach has three stages (establishing, sustaining and reinforcing) that are paired with specific virtues (trust, commitment and diligence). These and other facilitating virtues are shown in a figure. Research limitations/implications – The model and its components have yet to be tested empirically. Some strategies for undertaking such research are discussed. Practical implications – Several European and American companies that currently practice ethical relationship marketing are discussed. Originality/value – Although relationship marketing has been studied for a number of years by many scholars, the ethical basis of it has not been thoroughly examined in any previous work

Field Studies of the Co-Occlusion Strategy with a Genetically Altered Isolate of the Autographa californica Nuclear Polyhedrosis Virus

The first field study of a genetically altered virus in the United States was performed with an isolate of the Autographa californica nuclear polyhedrosis virus (AcMNPV), which lacks a polyhedrin gene. In the first year of the study, three applications of 7.4 × 1011 AcMNPV polyhedra containing 48% genetically altered and 52% wild-type virus particles (co-occluded) were made on a O.1-ha circular plot of cabbage plants. The application area was surrounded by a 0.7-ha circular buffer zone. Before each application, the plants in the application area were infested with 4,500 third-ins tar Trichoplusia ni (Hübner) larvae. After each application, 100% of the T. ni test larvae sampled 5 d after infection were infected with AcMNPV and produced progeny polyhedra containing an average of 42 ± 17.6% genetically altered virus particles. At the end of the 1st yr, the progeny polyhedra population in the application area was estimated at 1.6 × 1013 polyhedra. In the 2nd yr, the application and buffer sites were replanted with cabbage plants. At four times during the growing season, the plants were seeded with T. ni larvae or eggs. Less than 2% of the test larvae became infected with AcMNPV. Polyhedra were extracted from soil samples collected in the application and buffer areas. Using neonate larval bioassays with the soil extracts, it was estimated that the soil in the application and buffer areas contained an average of 1,652 ± 3,370 and 832 ± 2,539 biologically active polyhedra per gram dry weight, respectively. Seventy-five larvae infected with polyhedra extracted from application area soil samples produced progeny polyhedra containing a mean of 9 ± 19% genetically altered virus particles. In the 3rd yr, the application area soil samples contained an average of 1,671 ± 3,274 biologically active polyhedra per gram dry weight. Eighty-four progeny polyhedral samples contained a mean of 6 ± 14% genetically altered virus particles. The co-occlusion strategy did not alter the environmental persistence of the polyhedra containing both wild-type and polyhedrin-minus virus particles. However, the data show a decline in the percent of polyhedrin-minus particles in the polyhedra and demonstrate that the persistence of a polyhedrin-minus virus in a cycling virus population is limited by the co-occlusion process. The environmentally desirable attributes of using the co-occlusion process for genetically enhanced baculovirus pesticides and possible problems are discusse

The estimation and use of predictions for the assessment of model performance using large samples with multiply imputed data.

Multiple imputation can be used as a tool in the process of constructing prediction models in medical and epidemiological studies with missing covariate values. Such models can be used to make predictions for model performance assessment, but the task is made more complicated by the multiple imputation structure. We summarize various predictions constructed from covariates, including multiply imputed covariates, and either the set of imputation-specific prediction model coefficients or the pooled prediction model coefficients. We further describe approaches for using the predictions to assess model performance. We distinguish between ideal model performance and pragmatic model performance, where the former refers to the model's performance in an ideal clinical setting where all individuals have fully observed predictors and the latter refers to the model's performance in a real-world clinical setting where some individuals have missing predictors. The approaches are compared through an extensive simulation study based on the UK700 trial. We determine that measures of ideal model performance can be estimated within imputed datasets and subsequently pooled to give an overall measure of model performance. Alternative methods to evaluate pragmatic model performance are required and we propose constructing predictions either from a second set of covariate imputations which make no use of observed outcomes, or from a set of partial prediction models constructed for each potential observed pattern of covariate. Pragmatic model performance is generally lower than ideal model performance. We focus on model performance within the derivation data, but describe how to extend all the methods to a validation dataset.Angela Wood part supported by MRC grant G0701619. Ian White from MRC _Biostatistics Unit with unit programme number U105260558This is the final version. It was first published by Wiley at http://onlinelibrary.wiley.com/doi/10.1002/bimj.201400004/abstract;jsessionid=144424FA52D50041821329D8A7741BFD.f02t0

Further characterization of glycine-containing microcystins from the McMurdo Dry Valleys of Antarctica

Microcystins are hepatotoxic cyclic peptides produced by several cyanobacterial genera worldwide. In 2008, our research group identified eight new glycine-containing microcystin congeners in two hydro-terrestrial mat samples from the McMurdo Dry Valleys of Eastern Antarctica. During the present study, high-resolution mass spectrometry, amino acid analysis and micro-scale thiol derivatization were used to further elucidate their structures. The Antarctic microcystin congeners contained the rare substitution of the position-1 D-alanine for glycine, as well as the acetyl desmethyl modification of the position-5 Adda moiety (3S-amino-9S-methoxy-2S,6,8S-trimethyl-10-phenyldeca-4E,6E-dienoic acid). Amino acid analysis was used to determine the stereochemistry of several of the amino acids and conclusively demonstrated the presence of glycine in the microcystins. A recently developed thiol derivatization technique showed that each microcystin contained dehydrobutyrine in position-7 instead of the commonly observed N-methyl dehydroalanine

Correcting for optimistic prediction in small data sets.

The C statistic is a commonly reported measure of screening test performance. Optimistic estimation of the C statistic is a frequent problem because of overfitting of statistical models in small data sets, and methods exist to correct for this issue. However, many studies do not use such methods, and those that do correct for optimism use diverse methods, some of which are known to be biased. We used clinical data sets (United Kingdom Down syndrome screening data from Glasgow (1991-2003), Edinburgh (1999-2003), and Cambridge (1990-2006), as well as Scottish national pregnancy discharge data (2004-2007)) to evaluate different approaches to adjustment for optimism. We found that sample splitting, cross-validation without replication, and leave-1-out cross-validation produced optimism-adjusted estimates of the C statistic that were biased and/or associated with greater absolute error than other available methods. Cross-validation with replication, bootstrapping, and a new method (leave-pair-out cross-validation) all generated unbiased optimism-adjusted estimates of the C statistic and had similar absolute errors in the clinical data set. Larger simulation studies confirmed that all 3 methods performed similarly with 10 or more events per variable, or when the C statistic was 0.9 or greater. However, with lower events per variable or lower C statistics, bootstrapping tended to be optimistic but with lower absolute and mean squared errors than both methods of cross-validation

Multiple imputation for an incomplete covariate that is a ratio.

We are concerned with multiple imputation of the ratio of two variables, which is to be used as a covariate in a regression analysis. If the numerator and denominator are not missing simultaneously, it seems sensible to make use of the observed variable in the imputation model. One such strategy is to impute missing values for the numerator and denominator, or the log-transformed numerator and denominator, and then calculate the ratio of interest; we call this 'passive' imputation. Alternatively, missing ratio values might be imputed directly, with or without the numerator and/or the denominator in the imputation model; we call this 'active' imputation. In two motivating datasets, one involving body mass index as a covariate and the other involving the ratio of total to high-density lipoprotein cholesterol, we assess the sensitivity of results to the choice of imputation model and, as an alternative, explore fully Bayesian joint models for the outcome and incomplete ratio. Fully Bayesian approaches using Winbugs were unusable in both datasets because of computational problems. In our first dataset, multiple imputation results are similar regardless of the imputation model; in the second, results are sensitive to the choice of imputation model. Sensitivity depends strongly on the coefficient of variation of the ratio's denominator. A simulation study demonstrates that passive imputation without transformation is risky because it can lead to downward bias when the coefficient of variation of the ratio's denominator is larger than about 0.1. Active imputation or passive imputation after log-transformation is preferable

Precise cooperative sulfur placement leads to semi-crystallinity and selective depolymerisability in CS2/oxetane copolymers

CS2 promises easy access to degradable sulfur-rich polymers and insights into how main-group derivatisation affects polymer formation and properties, though its ring-opening copolymerisation is plagued by low linkage selectivity and small-molecule by-products. We demonstrate that a cooperative Cr(III)/K catalyst selectively delivers poly(dithiocarbonates) from CS2 and oxetanes while state-of-the-art strategies produce linkage scrambled polymers and heterocyclic by-products. The formal introduction of sulfur centres into the parent polycarbonates results in a net shift of the polymerisation equilibrium towards, and therefore facilitating, depolymerisation. During copolymerisation however, the catalyst enables near quantitative generation of the metastable polymers in high sequence selectivity by limiting the lifetime of alkoxide intermediates. Furthermore, linkage selectivity is key to obtain semi-crystalline materials that can be moulded into self-standing objects as well as to enable chemoselective depolymerisation into cyclic dithiocarbonates which can themselves serve as monomers in ring-opening polymerisation. Our report demonstrates the potential of cooperative catalysis to produce previously inaccessible main-group rich materials with beneficial chemical and physical properties

Quality of life in Type 1 (insulin-dependent) diabetic patients prior to and after pancreas and kidney transplantation in relation to organ function

Improvement of the quality of life in Type 1 (insulin-dependent) diabetic patients with severe late complications is one of the main goals of pancreas and/or kidney grafting. To assess the influences of these treatment modalities on the different aspects of the quality of life a cross-sectional study in 157 patients was conducted. They were categorized into patients pre-transplant without dialysis (n=29; Group A), pre-transplant under dialysis (n=44; Group B), post-transplant with pancreas and kidney functioning (n=31; Group C), post-transplant with functioning kidney, but insulin therapy (n=29; Group D), post-transplant under dialysis and insulin therapy again (n=15; Group E) and patients after single pancreas transplantation and rejection, with good renal function, but insulin therapy (n=9; Group F). All patients answered a mailed, self-administered questionnaire (217 questions) consisting of a broad spectrum of rehabilitation criteria. The results indicate a better quality of life in Groups C and D as compared to the other groups. In general the scores are highest in C, but without any significant difference to D. Impressive significant differences between C or D and the other groups were found especially in their satisfaction with physical capacity, leisure-time activities or the overall quality of life. The satisfaction with the latter is highest in C (mean±SEM: 4.0±0.2 on a 1 to 5-rating scale; significantly different from A: 3.1±0.1, B: 2.7±0.2 and E: 2.6±0.3; p<0.01), followed by D (3.8±0.2; significantly different from B and E; p<0.01). Group F shows a mean of 3.1±0.4, which is not significantly different from C. The percentages of patients in each group, who are not working: A: 38 %, B: 64 %, C: 74 %, D: 66 %, E: 87 % and F: 78 % indicate that there is no marked improvement in the vocational situation after successful grafting