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The Journal of the Southern Association for Information Systems

Introduction

The Journal of the Southern AIS is pleased to announce our latest issue: Vol 11 Issue 1

In this issue we have three research papers. While all of them are interesting and important, we would like to point out the second paper: The Celebrity Factor. The lead author of this paper, Abishek Shah, is a high school student. I was privileged to hear his presentation at the Southern Association Conference and am happy to say that it was the equal of any of the other presentations at the conference. It has resulted in a fine publication. We encourage you to read this paper and the other two excellent papers in this issue.

Healthcare Value Chain and the Impact of Analytics & Business Intelligence (A&BI) Capabilities: A Case Study, Rudolph T. Bedeley (Belmont University),  Lakshmi Iyer (University of North Carolina at Greensboro)

This study aims to investigate how the existing healthcare value chain system has significantly been impacted as a result of the increasing adoption and implementation of analytics and business intelligence (A&BI) capabilities. Given the increasing interest and investment in A&BI, it is important to have a good understanding of what A&BI capabilities healthcare organizations are utilizing to enhance value. Based on extensive search of the literature and a follow-up case study of a large regional hospital, it was found that the existing healthcare value chain (HCVC) framework is outdated and no longer effective. We therefore revised and updated the existing framework to meet the current needs of modern healthcare practices. Moreover, A&BI applications currently being deployed in healthcare organizations were identified and mapped onto the revised framework. The study contributes by illustrating how healthcare organizations currently utilize or should be using A&BI capabilities to enable them to close the quality gaps.

The Celebrity Factor: Exploring the Impact of Influencers on COVID-19 Vaccine Sentiment through Bayesian Modeling of Time Series, Abhishek Shah (Green Level High School),  Shweta Shah (Green Level High School),  Bill Rand (North Carolina State University),  Xiaoxia Champon (North Carolina State University)

Online social networks allow for information to rapidly propagate throughout the world, and opinions expressed on such platforms can influence people’s decisions. During the COVID-19 pandemic, many influential public figures used these social networks to share their opinions about the vaccines developed to combat the virus. Many influencers encouraged vaccination, and a considerable number also expressed doubt and skepticism over the efficacy of the vaccines. This study modeled the impact that eleven influencers’ statements had on the overall sentiment towards COVID-19 vaccines, as expressed on Twitter. Sentiment is measured by collecting a series of publicly-available tweets made regarding the vaccine during the pandemic, and assigning each a sentiment score based on the VADER lexicon. Several models were used to analyze the impact of the influencers’ statements, including linear, sequential and tree-based models. The results were obtained by constructing a Bayesian structural time series model based on each model’s counterfactual estimate. The results found that influencers who share messages encouraging vaccination generally tend to increase the number of ”pro-vaccination” tweets over the next 20 days. Influencers sharing” anti-vaccination” messages sometimes resulted in a decrease in anti-vaccine tweets, and other times in an increase over the next 20 days. The results from this study provide an introductory look into the complex issue of vaccine hesitancy and the effect of influencers on vaccine messaging, and inform public health strategy regarding this issue.

Utilizing Social Networks to Improve Success Metrics in Social E-Commerce, Richelle Oakley DaSouza (North Carolina Agricultural and Technical State University),  E Mitchell Church (Coastal Carolina University)

Social e-commerce highlights the current trend of companies strategically using a multi-platform approach for their marketing plans and selling needs. This approach often consists of a company utilizing one or more social networks, along with social e-commerce, to create an online community around their products. However, there is limited holistic research on how companies use social networks to maximize their branding and marketing efforts. This study theorizes the strategic social network actions of a social e-commerce platform. We collected data from a random sample of 1,458 social e-commerce users and their chosen social networks, including Instagram, Pinterest, Facebook, and X (formerly known as Twitter). This unique data set and analysis assessed the impact of social network marketing from firms across a wide variety of industries and platforms. The study provides empirical evidence on follower growth and sales and identifies impactful marketing strategies in a multi-platform web environment.

Michael Cuellar, Editor

 

https://doi.org/doi:10.17705/3JSIS.19009