Green consumer segmentation: managerial and environmental implications from the perspective of business strategies and practices

With the new millennium, environmental concern entered a new phase, with stricter governmental regulations and incentives. Currently, within environmental issues, there is a broader challenge to commitment with economic and social goals. This is motivating companies and organizations to participate in transformation processes with the aim of minimizing the negative impacts of their activities. Within this context, new business philosophies, emerged empowering organizations to consider sustainability issues that have come to be viewed as an innovative and differentiating factor, providing competitive advantages (Fraj-Andres, MartinezSalinas, & Matute-Vallejo. Journal of Business Ethics, 88,263-286, 2009; Leipziger. The corporate responsibility code book. Greenleaf Publishing Limited, 2016; Leipziger. The corporate responsibility code book. Greenleaf Publishing Limited, 2016). Therefore, organizations have begun incorporating these concerns in their processes, adopting green management policies, and including green marketing strategies in order to remain competitive (Straughan & Roberts. Journal of Consumer Marketing, 16(6), 558-575, 1999; Rivera-Camino. European Journal of Marketing, 41, 1328-1358, 2007). From the marketing perspective, the importance of understanding green consumer behaviour in order to develop better segmentation and targeting strategies is highlighted. Green consumers are changing significantly. Consumers, although with some reluctance, are moving to greener products. The Mintel organization reported that the number of consumers buying green has tripled in recent years. Furthermore, it found that the number of consumers that never bought green products have decreased. These results show that widespread environmental awareness had an important role in purchasing behaviour, with more consumers considering the environmental impact of their buying decisions and looking for a greener alternative to their conventional purchasing options. The existing literature suggests that previous research regarding the green consumer profile has different perspectives. The first group of researchers attempted to characterize green consumer profile using sociodemographic variables such as age, gender, education, income and occupation. In tum, the second group of researchers used psychographic variables instead of sociodemographic ones (Mainieri, Barnett, Valdero, Unipan, & Oskamp. Journal of Social Psychology, 137(2), 189-204, 1997). This chapter aims to better explore the importance of green consumer segmentation and its implications from a management point of view. More specifically, the aim is to analyze which variables better characterize green consumers (sociodemographic and psychographic). At the end, a theoretical framework is proposed to enable and support organizations to better understand green consumer profile. It also enables managers and marketers to target and develop better marketing strategies for these segments.info:eu-repo/semantics/publishedVersio

The role of genetic factors in predisposition to squamous cell cancer of the head and neck

© 1999 Cancer Research Campaig

Developing a National Alfalfa Information System

Using state-of-the-art telecommunication technologies, this project is developing a comprehensive knowledge resource for alfalfa (Medicago sativa L.); the National Alfalfa Information System (NAIS). This project will serve as an improved model for Extension educational programs. Alfalfa is the most important forage crop in the USA and grown worldwide for feeding millions of livestock and in many cropping systems. As a legume, it is important in sustaining the environment and the productivity of agriculture. Information needs are present in every state and internationally. The NAIS is being developed through national and international cooperation, putting the best science-based alfalfa information and expertise at the fingertips of producers, consultants, extension workers, instructors, researchers, and users. Collaboratively developed materials will reduce duplication of effort. To make the knowledge easy-to-use, educational design, communication, and information science professionals are working with alfalfa experts in creating a WWW system and Web-aware CD-ROM. To ensure content quality, peer-review by members of multiple professional societies is included. A significant result will be around-the-clock availability of up-to-date, easy-to-use, and peerreviewed information. Shared workload and the peer-review process can influence faculty morale, efficiency, and effectiveness, an adjunct to maximizing the utilization of alfalfa worldwide by making the best information readily available

Mutual Information for Testing Gene-Environment Interaction

Despite current enthusiasm for investigation of gene-gene interactions and gene-environment interactions, the essential issue of how to define and detect gene-environment interactions remains unresolved. In this report, we define gene-environment interactions as a stochastic dependence in the context of the effects of the genetic and environmental risk factors on the cause of phenotypic variation among individuals. We use mutual information that is widely used in communication and complex system analysis to measure gene-environment interactions. We investigate how gene-environment interactions generate the large difference in the information measure of gene-environment interactions between the general population and a diseased population, which motives us to develop mutual information-based statistics for testing gene-environment interactions. We validated the null distribution and calculated the type 1 error rates for the mutual information-based statistics to test gene-environment interactions using extensive simulation studies. We found that the new test statistics were more powerful than the traditional logistic regression under several disease models. Finally, in order to further evaluate the performance of our new method, we applied the mutual information-based statistics to three real examples. Our results showed that P-values for the mutual information-based statistics were much smaller than that obtained by other approaches including logistic regression models

A Novel Statistic for Genome-Wide Interaction Analysis

Although great progress in genome-wide association studies (GWAS) has been made, the significant SNP associations identified by GWAS account for only a few percent of the genetic variance, leading many to question where and how we can find the missing heritability. There is increasing interest in genome-wide interaction analysis as a possible source of finding heritability unexplained by current GWAS. However, the existing statistics for testing interaction have low power for genome-wide interaction analysis. To meet challenges raised by genome-wide interactional analysis, we have developed a novel statistic for testing interaction between two loci (either linked or unlinked). The null distribution and the type I error rates of the new statistic for testing interaction are validated using simulations. Extensive power studies show that the developed statistic has much higher power to detect interaction than classical logistic regression. The results identified 44 and 211 pairs of SNPs showing significant evidence of interactions with FDR<0.001 and 0.001<FDR<0.003, respectively, which were seen in two independent studies of psoriasis. These included five interacting pairs of SNPs in genes LST1/NCR3, CXCR5/BCL9L, and GLS2, some of which were located in the target sites of miR-324-3p, miR-433, and miR-382, as well as 15 pairs of interacting SNPs that had nonsynonymous substitutions. Our results demonstrated that genome-wide interaction analysis is a valuable tool for finding remaining missing heritability unexplained by the current GWAS, and the developed novel statistic is able to search significant interaction between SNPs across the genome. Real data analysis showed that the results of genome-wide interaction analysis can be replicated in two independent studies

О перспективе извлечения йода из продукта утилизации окислителя ракетного топлива

Crop models are essential tools for assessing the threat of climate change to local and global food production. Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature. Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 degrees C to 32 degrees C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each degree C of further temperature increase and become more variable over space and time

Common genetic variation and susceptibility to partial epilepsies: a genome-wide association study

Partial epilepsies have a substantial heritability. However, the actual genetic causes are largely unknown. In contrast to many other common diseases for which genetic association-studies have successfully revealed common variants associated with disease risk, the role of common variation in partial epilepsies has not yet been explored in a well-powered study. We undertook a genome-wide association-study to identify common variants which influence risk for epilepsy shared amongst partial epilepsy syndromes, in 3445 patients and 6935 controls of European ancestry. We did not identify any genome-wide significant association. A few single nucleotide polymorphisms may warrant further investigation. We exclude common genetic variants with effect sizes above a modest 1.3 odds ratio for a single variant as contributors to genetic susceptibility shared across the partial epilepsies. We show that, at best, common genetic variation can only have a modest role in predisposition to the partial epilepsies when considered across syndromes in Europeans. The genetic architecture of the partial epilepsies is likely to be very complex, reflecting genotypic and phenotypic heterogeneity. Larger meta-analyses are required to identify variants of smaller effect sizes (odds ratio <1.3) or syndrome-specific variants. Further, our results suggest research efforts should also be directed towards identifying the multiple rare variants likely to account for at least part of the heritability of the partial epilepsies. Data emerging from genome-wide association-studies will be valuable during the next serious challenge of interpreting all the genetic variation emerging from whole-genome sequencing studies