Rebates and Reward Programs: Conflicting Drivers

Rebate programs and customer reward programs have evolved almost side by side within the hospitality, tourism, services and retailing sectors. Interestingly, they both share a common theme of delaying rewards for consumers. In each case consumers are motivated to purchase a good or service contingent upon a reward that is delayed until a later time. At present there has been little research that examines how these programs function together and whether when implemented in tandem that they might actually be in conflict. An online survey was completed by 68 members of a shopping blog that asked about their participation and satisfaction with various rebate and reward programs. Data revealed a strong positive relationship between rebate proneness and various deal-seeking shopping behaviors, while a negative relationship was found between rebate usage and loyalty variables. We suggest that these parallel programs may actually be in conflict with each other and that practitioners must carefully manage these programs to avoid converting their loyal customers into deal seekers

Is EC class predictable from reaction mechanism?

We thank the Scottish Universities Life Sciences Alliance (SULSA) and the Scottish Overseas Research Student Awards Scheme of the Scottish Funding Council (SFC) for financial support.Background: We investigate the relationships between the EC (Enzyme Commission) class, the associated chemical reaction, and the reaction mechanism by building predictive models using Support Vector Machine (SVM), Random Forest (RF) and k-Nearest Neighbours (kNN). We consider two ways of encoding the reaction mechanism in descriptors, and also three approaches that encode only the overall chemical reaction. Both cross-validation and also an external test set are used. Results: The three descriptor sets encoding overall chemical transformation perform better than the two descriptions of mechanism. SVM and RF models perform comparably well; kNN is less successful. Oxidoreductases and hydrolases are relatively well predicted by all types of descriptor; isomerases are well predicted by overall reaction descriptors but not by mechanistic ones. Conclusions: Our results suggest that pairs of similar enzyme reactions tend to proceed by different mechanisms. Oxidoreductases, hydrolases, and to some extent isomerases and ligases, have clear chemical signatures, making them easier to predict than transferases and lyases. We find evidence that isomerases as a class are notably mechanistically diverse and that their one shared property, of substrate and product being isomers, can arise in various unrelated ways. The performance of the different machine learning algorithms is in line with many cheminformatics applications, with SVM and RF being roughly equally effective. kNN is less successful, given the role that non-local information plays in successful classification. We note also that, despite a lack of clarity in the literature, EC number prediction is not a single problem; the challenge of predicting protein function from available sequence data is quite different from assigning an EC classification from a cheminformatics representation of a reaction.Publisher PDFPeer reviewe

Entrepreneurship and Creative Professions – A Micro-Level Analysis

It has widely been recognized that creativity plays an immense role not only for arts, sciences, and technology, but also for entrepreneurship, innovation, and thus, economic growth. We analyze the level and the determinants of self-employment in creative professions at the level of individuals. The analysis is based on the representative micro data of the German Socio-Economic Panel (SOEP). The findings suggest that people in creative professions appear more likely to be self-employed and that a high regional share of people in the creative class increases an individual's likelihood of being an entrepreneur. Investigating the determinants of entrepreneurship within the creative class as compared to non-creative professions reveals only some few differences

The use of urea for the treatment of onychomycosis: a systematic review

Abstract Background Onychomycosis, a fungal infection affecting the nail plate, is a common condition often requiring prolonged treatment regimens, with low success rates. Urea is one treatment option, which is thought to improve the efficacy of topical and oral antifungal agents. Despite a theoretical basis for the use of urea for the treatment of onychomycosis, the evidence-base for this treatment has not been systematically reviewed. Aim The purpose of this study was to conduct a systematic literature review to determine the efficacy and safety of urea as a monotherapy and as adjunct therapy, compared to other treatment regimens for onychomycosis. Method A systematic literature search of ten electronic databases was conducted. Only studies that used microscopy and culture or other validated laboratory-based testing method to confirm the presence of a fungal infection before treatment were included. The outcome measures assessed were efficacy (defined in terms of mycological, clinical and complete cure) and safety (defined as self-reported adverse events). Results The systematic search yielded 560 unique studies for review. Of these, only six were eligible for inclusion. All studies were observed to have methodological concerns, most studies consisted of small sample sizes and were difficult to compare given heterogeneity in outcome measures and follow-up time. Despite this, a trend was observed to suggest that urea, when added to topical or oral antifungal treatment regimens, improved efficacy of the treatment. Conclusion This review suggests that topical urea, as an adjunct to topical and oral antifungal treatment regimens, may improve the efficacy of treatment. However, further research is needed

Quantitative comparison of catalytic mechanisms and overall reactions in convergently evolved enzymes : implications for classification of enzyme function

The authors thank the National Institutes of Health (NIH R01 GM60595 to PCB) and the Scottish Universities Life Sciences Alliance (SULSA to JBOM) for funding.Functionally analogous enzymes are those that catalyze similar reactions on similar substrates but do not share common ancestry, providing a window on the different structural strategies nature has used to evolve required catalysts. Identification and use of this information to improve reaction classification and computational annotation of enzymes newly discovered in the genome projects would benefit from systematic determination of reaction similarities. Here, we quantified similarity in bond changes for overall reactions and catalytic mechanisms for 95 pairs of functionally analogous enzymes (non-homologous enzymes with identical first three numbers of their EC codes) from the MACiE database. Similarity of overall reactions was computed by comparing the sets of bond changes in the transformations from substrates to products. For similarity of mechanisms, sets of bond changes occurring in each mechanistic step were compared; these similarities were then used to guide global and local alignments of mechanistic steps. Using this metric, only 44% of pairs of functionally analogous enzymes in the dataset had significantly similar overall reactions. For these enzymes, convergence to the same mechanism occurred in 33% of cases, with most pairs having at least one identical mechanistic step. Using our metric, overall reaction similarity serves as an upper bound for mechanistic similarity in functional analogs. For example, the four carbon-oxygen lyases acting on phosphates (EC 4.2.3) show neither significant overall reaction similarity nor significant mechanistic similarity. By contrast, the three carboxylic-ester hydrolases (EC 3.1.1) catalyze overall reactions with identical bond changes and have converged to almost identical mechanisms. The large proportion of enzyme pairs that do not show significant overall reaction similarity (56%) suggests that at least for the functionally analogous enzymes studied here, more stringent criteria could be used to refine definitions of EC sub-subclasses for improved discrimination in their classification of enzyme reactions. The results also indicate that mechanistic convergence of reaction steps is widespread, suggesting that quantitative measurement of mechanistic similarity can inform approaches for functional annotation.Publisher PDFPeer reviewe