The Impact of the Social Media Influencer Power on Consumer Attitudes toward the Brand: The Mediating/Moderating Role of Social Media Influencer Source Credibility

This paper presents a conceptual model of the impact of social media influencer power on consumer attitudes toward a brand. The research uses naïve theories of social influence, consumer socialization theory and market signaling theory to support the contention that social media influencer power will impact consumer brand attitudes. However, the impact of the social media influencer power on consumer brand attitudes is posited to be mediated and/or moderated by the social media influencer source credibility. In turn, the social media influencer source credibility is modeled as being positively related to the social media influencer’s expertise/competence with respect to the product, the social media influencer’s goodwill toward the consumer, and the social media influencer’s trustworthiness

All-Payer Claims Database Development Manual: Establishing a Foundation for Health Care Transparency and Informed Decision Making

With support from the Gary and Mary West Health Policy Center, the APCD Council has developed a manual for states to develop all-payer claims databases. Titled All-Payer Claims Database Development Manual: Establishing a Foundation for Health Care Transparency and Informed Decision Making, the manual is a first-of its-kind resource that provides states with detailed guidance on common data standards, collection, aggregation and analysis involved with establishing these databases

Hazardous Drug Administration in the Home Setting: Reducing Exposure Risks

Hazardous drug (HD) administration used to be contained in controlled-healthcare settings, however, the introduction of HDs for home administration has become a growing area of concern for home health agencies. The objectives of the Clinical Nurse Leader (CNL) project aims to improve homecare nurses\u27 knowledge of HDs and improve competency with personal protective equipment (PPE). The microsystem provides short-term homecare services for acute and chronically-ill patients. One team leader, two home infusion coordinators, and twelve registered infusion nurses participated in learning about exposure risks and PPE use with HD administration. Kotter\u27s 8-step change theory was used to develop behavior change strategies necessary to create a connection between emotion and the need for change. Education materials and PPE kits were developed specifically to address the needs of home care nurses and their patients. Teaching aids were developed with a health literacy team that included reviews by nurses, patients, and education experts. A literature review in the CINAHL, Cochrane Library, and PubMed databases provided articles rich with content about safe-handling practices withHD administration and exposure protection strategies. Themes that emerged from the project for future consideration included tracking exposed workers through a national database and improving data collection via electronic health records (EHR) used by homecare nurses at the point of care. While the goal of the project was to improve and sustain nurses\u27 knowledge and competency with PPE use to 95%, more education and hands-on practice will be required to achieve this worthy goal

Hadoop Based Data Intensive Computation on IAAS Cloud Platforms

Cloud computing is a relatively new form of computing which uses virtualized resources. It is dynamically scalable and is often provided as pay for use service over the Internet or Intranet or both. With increasing demand for data storage in the cloud, the study of data-intensive applications is becoming a primary focus. Data intensive applications are those which involve high CPU usage, processing large volumes of data typically in size of hundreds of gigabytes, terabytes or petabytes. The research in this thesis is focused on the Amazon’s Elastic Cloud Compute (EC2) and Amazon Elastic Map Reduce (EMR) using HiBench Hadoop Benchmark suite. HiBench is a Hadoop benchmark suite and is used for performing and evaluating Hadoop based data intensive computation on both these cloud platforms. Both quantitative and qualitative comparisons of Amazon EC2 and Amazon EMR are presented. Also presented are their pricing models and suggestions for future research