Usage analytics: a process to extract and analyse usage data to understand user behaviour in cloud

Usage in the software field deals with knowledge about how end-users use the application and how the application responds to the users’ action. Understanding usage data can help developers optimise the application development process by prioritising the resources such as time, cost and man power on features of the application which are critical for the user. However, in a complex cloud computing environment, the process of extracting and analysing usage data is difficult since the usage data is spread across various front-end interfaces and back-end underlying infrastructural components of the cloud that host the application and are of different types and formats. In this paper, we propose usage analytics, a process to extract and analyse usage to understand the behavioural usage patterns of the user with the aim to identify features critical to user. We demonstrate how to identify the features in a cloud based application, how to extract and analyse the usage data to understand the user behaviour

Exclusivity and exclusion on platform markets

We examine conditions under which an exclusive license granted by the upstream producer of a component that some consumers regard as essential to one of two potential suppliers of a downstream platform market can make the unlicensed supplier unprofitable, although both firms would be profitable if both were licensed. If downstream varieties are close substitutes, an exclusive license need not be exclusionary. If downstream varieties are highly differentiated, an exclusive license is exclusionary, but it is not in the interest of the upstream firm to grant an exclusive license. For intermediate levels of product differentiation, an exclusive license is exclusionary and maximizes the upstream firm’s payoff

Ocean acidification reduces demersal zooplankton that reside in tropical coral reefs

The in situ effects of ocean acidification on zooplankton communities remain largely unexplored. Using natural volcanic CO2 seep sites around tropical coral communities, we show a threefold reduction in the biomass of demersal zooplankton in high-CO2 sites compared with sites with ambient CO2. Differences were consistent across two reefs and three expeditions. Abundances were reduced in most taxonomic groups. There were no regime shifts in zooplankton community composition and no differences in fatty acid composition between CO2 levels, suggesting that ocean acidification affects the food quantity but not the quality for nocturnal plankton feeders. Emergence trap data show that the observed reduction in demersal plankton may be partly attributable to altered habitat. Ocean acidification changes coral community composition from branching to massive bouldering coral species, and our data suggest that bouldering corals represent inferior daytime shelter for demersal zooplankton. Since zooplankton represent a major source of nutrients for corals, fish and other planktivores, this ecological feedback may represent an additional mechanism of how coral reefs will be affected by ocean acidification

Reconciling Deep Calibration and Demographic History: Bayesian Inference of Post Glacial Colonization Patterns in Carcinus aestuarii (Nardo, 1847) and C. maenas (Linnaeus, 1758)

A precise inference of past demographic histories including dating of demographic events using Bayesian methods can only be achieved with the use of appropriate molecular rates and evolutionary models. Using a set of 596 mitochondrial cytochrome c oxidase I (COI) sequences of two sister species of European green crabs of the genus Carcinus (C. maenas and C. aestuarii), our study shows how chronologies of past evolutionary events change significantly with the application of revised molecular rates that incorporate biogeographic events for calibration and appropriate demographic priors. A clear signal of demographic expansion was found for both species, dated between 10,000 and 20,000 years ago, which places the expansions events in a time frame following the Last Glacial Maximum (LGM). In the case of C. aestuarii, a population expansion was only inferred for the Adriatic-Ionian, suggestive of a colonization event following the flooding of the Adriatic Sea (18,000 years ago). For C. maenas, the demographic expansion inferred for the continental populations of West and North Europe might result from a northward recolonization from a southern refugium when the ice sheet retreated after the LGM. Collectively, our results highlight the importance of using adequate calibrations and demographic priors in order to avoid considerable overestimates of evolutionary time scales

A BRANDS EYE VIEW OF RESPONSE SEGMENTATION IN CONSUMER BRAND CHOICE BEHAVIOR

The authors develop an approach to reveal segmentation in response to marketing variables at a brand-level perspective. In the proposed procedure, response segmentation is analyzed separately for each brand instead of jointly across all brands. This yields a segmentation picture oriented toward the potential targeting objectives of the brand manager. Using the multinomial logit and probabilistic mixture models, the procedure first calibrates consumer response in the brand choice decision. Individual-level measures of response for a given marketing variable (e.g., price) are then computed, and brand-level segments are obtained by clustering brand-specific response. Using scanner panel data, the approach is applied to price response segmentation for brands that compete in the ground coffee category. The results illustrate a series of implications for brand strategy, particularly the potential for targeting marketing activity to different response segments