35 research outputs found

    Airline Brands on Twitter: Discovering What Consumers Value to Create a Stronger Social CRM Strategy

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    Abstract Title: Airline Brands on Twitter: Discovering What Consumers Value to Create a Stronger Social CRM Strategy Date of the Seminar: June 2nd, 2015 Course: BUSN39. Degree project in global marketing Authors: Jane Macfarlane-Grieve Emily Widen Advisors: Christian Koch, PhD Keywords: Social Customer Relationship Management, Communication, Twitter, Airline, Customer Satisfaction Thesis purpose: The objective of this research paper is to gain a clear understanding of consumer attitudes and expectations whilst engaging in conversation with airline brands on the social media platform Twitter. This paper seeks to understand what manner of interactions consumers find valuable, and if there is a method of ensuring a satisfying response from the airline. This will examine how airline brands can strengthen social CRM strategies on a theoretical level to offer consumers what they most value. Furthermore, this paper will identify and create a model in which to use to utilize for future interactions with consumers on Twitter in the airline industry. This thesis will address the specific question; how can airline brands satisfy consumer expectations with their social CRM strategy to best interact with consumers on Twitter? Additionally, the sub-question will be addressed; can traditional communication and customer satisfaction theories enhance airline brands social CRM strategies? Methodology: In order to explore these questions in depth; first a comprehensive literature review of all relevant theories was completed. Next, a netnography study of 600 Twitter conversations were collected and coded in an attempt to gain insight and understanding of what consumers want and need from airlines on Twitter. This code was developed based on the data. Also, a self-completion web survey was used as a way to speak directly with consumers about airlines and Twitter. Theoretical perspective: This paper examines the theories of; communication, customer satisfaction, empowered consumer, social CRM, as social media theories. Empirical data: This mixed method study combines a netnography study of 600 Twitter conversations with a supplemental consumer self-completion web survey. Conclusion: The most notable theoretical findings are that present social customer relationship management theories do not fully encompass the ever-changing and culturally significant social media platforms. Customer satisfaction theories and communication theories were considered as subset elements of customer relationship management theory, and while these could align with a basic understanding of the principles of CRM social media, they could not fully grasp unique culture of Twitter and the significance of the empowered consumer. Elements such as the reduced character count on Twitter and the expectations of immediate response need to be adapted to a more specific theory, which better understands this vast communication platform. We propose that while this theory begins to emerge, brands can utilize standard theories on communication and customer satisfaction to create a comprehensive social CRM strategy to build relationships with the empowered consumer. Knowing consumer expectations, and what the consumer values, will lead to a successful implementation of these concepts in social CRM. Additionally, many practical consumer wants and needs were discovered and a model was created. This model is to be used as a guideline for airline brand managers in order to best interact with consumers via Twitter

    Developmental changes in the critical information used for facial expression processing

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    Facial expression recognition skills are known to improve across childhood and adolescence, but the mechanisms driving the development of these important social abilities remain unclear. This study investigates directly whether there are qualitative differences in child and adult processing strategies for these emotional stimuli. With a novel adaptation of the Bubbles reverse-correlation paradigm (Gosselin & Schyns, 2001), we added noise to expressive face stimuli and presented sub-sets of randomly sampled information from each image at different locations and spatial frequency bands across experimental trials. Results from our large developmental sample: 71 young children (6 -9 years), 69 older children (10-13 years) and 54 adults, uniquely reveal flexible profiles of strategic information-use for categorisations of fear, sadness, happiness and anger at all ages. All three groups relied upon a distinct set of key facial features for each of these expressions, with fine-tuning of this diagnostic information (features and spatial frequency) observed across developmental time. Reported variability in the developmental trajectories for different emotional expressions is consistent with the notion of functional links between the refinement of information-use and processing ability

    Pleiotropic meta-analysis of cognition, education, and schizophrenia differentiates roles of early neurodevelopmental and adult synaptic pathways

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    Susceptibility to schizophrenia is inversely correlated with general cognitive ability at both the phenotypic and the genetic level. Paradoxically, a modest but consistent positive genetic correlation has been reported between schizophrenia and educational attainment, despite the strong positive genetic correlation between cognitive ability and educational attainment. Here we leverage published genome-wide association studies (GWASs) in cognitive ability, education, and schizophrenia to parse biological mechanisms underlying these results. Association analysis based on subsets (ASSET), a pleiotropic meta-analytic technique, allowed jointly associated loci to be identified and characterized. Specifically, we identified subsets of variants associated in the expected (“concordant”) direction across all three phenotypes (i.e., greater risk for schizophrenia, lower cognitive ability, and lower educational attainment); these were contrasted with variants that demonstrated the counterintuitive (“discordant”) relationship between education and schizophrenia (i.e., greater risk for schizophrenia and higher educational attainment). ASSET analysis revealed 235 independent loci associated with cognitive ability, education, and/or schizophrenia at p < 5 × 10−8. Pleiotropic analysis successfully identified more than 100 loci that were not significant in the input GWASs. Many of these have been validated by larger, more recent single-phenotype GWASs. Leveraging the joint genetic correlations of cognitive ability, education, and schizophrenia, we were able to dissociate two distinct biological mechanisms—early neurodevelopmental pathways that characterize concordant allelic variation and adulthood synaptic pruning pathways—that were linked to the paradoxical positive genetic association between education and schizophrenia. Furthermore, genetic correlation analyses revealed that these mechanisms contribute not only to the etiopathogenesis of schizophrenia but also to the broader biological dimensions implicated in both general health outcomes and psychiatric illness

    Identifying nootropic drug targets via large-scale cognitive GWAS and transcriptomics

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    Broad-based cognitive deficits are an enduring and disabling symptom for many patients with severe mental illness, and these impairments are inadequately addressed by current medications. While novel drug targets for schizophrenia and depression have emerged from recent large-scale genome-wide association studies (GWAS) of these psychiatric disorders, GWAS of general cognitive ability can suggest potential targets for nootropic drug repurposing. Here, we (1) meta-analyze results from two recent cognitive GWAS to further enhance power for locus discovery; (2) employ several complementary transcriptomic methods to identify genes in these loci that are credibly associated with cognition; and (3) further annotate the resulting genes using multiple chemoinformatic databases to identify "druggable" targets. Using our meta-analytic data set (N = 373,617), we identified 241 independent cognition-associated loci (29 novel), and 76 genes were identified by 2 or more methods of gene identification. Actin and chromatin binding gene sets were identified as novel pathways that could be targeted via drug repurposing. Leveraging our transcriptomic and chemoinformatic databases, we identified 16 putative genes targeted by existing drugs potentially available for cognitive repurposing.Peer reviewe

    Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence

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    Intelligence is highly heritable(1) and a major determinant of human health and well-being(2). Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence3-7, but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer's disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders.Peer reviewe

    Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk

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    The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project-imputed genotype data in up to similar to 370,000 women, we identify 389 independent signals (P <5 x 10(-8)) for age at menarche, a milestone in female pubertal development. In Icelandic data, these signals explain similar to 7.4% of the population variance in age at menarche, corresponding to similar to 25% of the estimated heritability. We implicate similar to 250 genes via coding variation or associated expression, demonstrating significant enrichment in neural tissues. Rare variants near the imprinted genes MKRN3 and DLK1 were identified, exhibiting large effects when paternally inherited. Mendelian randomization analyses suggest causal inverse associations, independent of body mass index (BMI), between puberty timing and risks for breast and endometrial cancers in women and prostate cancer in men. In aggregate, our findings highlight the complexity of the genetic regulation of puberty timing and support causal links with cancer susceptibility

    The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia : design, results and future prospects

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    The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites.Peer reviewe

    The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia:design, results and future prospects

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    Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

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    Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe

    Effect of cytomegalovirus infection on breastfeeding transmission of HIV and on the health of infants born to HIV-infected mothers

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    Cytomegalovirus (CMV) infection can be acquired in utero or postnatally through horizontal transmission and breastfeeding. The effect of postnatal CMV infection on postnatal HIV transmission is unknown
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