Murali S. Shanker

Prof. Murali S. Shanker

Department of Management & Information Systems, Kent State University, Kent, OH 44242, USA
orcid

Research Focus & Metrics

Academic Career Length

27Years (2000-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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2 September 2021 in Journal of Medical Internet Research
Verified
Journal Article
Open access
Ikpe Justice AkpanIkpe Justice Akpan
Ikpe Justice Akpan
OAObianuju Genevieve Aguolu
Obianuju Genevieve Aguolu
YKYawo Kobara
Yawo Kobara
RRRouzbeh Razavi
Rouzbeh Razavi
AAAsuama A Akpan
Asuama A Akpan
Murali S. ShankerMurali S. Shanker
Murali S. Shanker
Background: The use of the internet and web-based platforms to obtain public health information and manage health-related issues has become widespread in this digital age. The practice is so pervasive that the first reaction to obtaining health information is to “Google it.” As SARS-CoV-2 broke out in Wuhan, China, in December 2019 and quickly spread worldwide, people flocked to the internet to learn about the novel coronavirus and the disease, COVID-19. Lagging responses by governments and public health agencies to prioritize the dissemination of information about the coronavirus outbreak through the internet and the World Wide Web and to build trust gave room for others to quickly populate social media, online blogs, news outlets, and websites with misinformation and conspiracy theories about the COVID-19 pandemic, resulting in people’s deviant behaviors toward public health safety measures. Objective: The goals of this study were to determine what people learned about the COVID-19 pandemic through web searches, examine any association between what people learned about COVID-19 and behavior toward public health guidelines, and analyze the impact of misinformation and conspiracy theories about the COVID-19 pandemic on people’s behavior toward public health measures. Methods: This infodemiology study used Google Trends’ worldwide search index, covering the first 6 months after the SARS-CoV-2 outbreak (January 1 to June 30, 2020) when the public scrambled for information about the pandemic. Data analysis employed statistical trends, correlation and regression, principal component analysis (PCA), and predictive models. Results: The PCA identified two latent variables comprising past coronavirus epidemics (pastCoVepidemics: keywords that address previous epidemics) and the ongoing COVID-19 pandemic (presCoVpandemic: keywords that explain the ongoing pandemic). Both principal components were used significantly to learn about SARS-CoV-2 and COVID-19 and explained 88.78% of the variability. Three principal components fuelled misinformation about COVID-19: misinformation (keywords “biological weapon,” “virus hoax,” “common cold,” “COVID-19 hoax,” and “China virus”), conspiracy theory 1 (ConspTheory1; keyword “5G” or “@5G”), and conspiracy theory 2 (ConspTheory2; keyword “ingest bleach”). These principal components explained 84.85% of the variability. The principal components represent two measurements of public health safety guidelines—public health measures 1 (PubHealthMes1; keywords “social distancing,” “wash hands,” “isolation,” and “quarantine”) and public health measures 2 (PubHealthMes2; keyword “wear mask”)—which explained 84.7% of the variability. Based on the PCA results and the log-linear and predictive models, ConspTheory1 (keyword “@5G”) was identified as a predictor of people’s behavior toward public health measures (PubHealthMes2). Although correlations of misinformation (keywords “COVID-19,” “hoax,” “virus hoax,” “common cold,” and more) and ConspTheory2 (keyword “ingest bleach”) with PubHealthMes1 (keywords “social distancing,” “hand wash,” “isolation,” and more) were r=0.83 and r=–0.11, respectively, neither was statistically significant (P=.27 and P=.13, respectively). Conclusions: Several studies focused on the impacts of social media and related platforms on the spreading of misinformation and conspiracy theories. This study provides the first empirical evidence to the mainly anecdotal discourse on the use of web searches to learn about SARS-CoV-2 and COVID-19.

1 July 2012 in Journal of Business Research
Verified
Journal Article
Closed access
JWJing Wang
Jing Wang
MHMichael Y. Hu
Michael Y. Hu
Murali S. ShankerMurali S. Shanker
Murali S. Shanker

31 March 2008 in Decision Support Systems
Verified
Journal Article
Closed access
MHMichael Y. Hu
Michael Y. Hu
Murali S. ShankerMurali S. Shanker
Murali S. Shanker
Peter ZhangPeter Zhang
Peter Zhang
MHMing S. Hung
Ming S. Hung

1 December 2000 in Decision Sciences
Verified
Journal Article
Closed access
PDF file
MTMarvin D. Troutt
Marvin D. Troutt
DGDonald W. Gribbin
Donald W. Gribbin
Murali S. ShankerMurali S. Shanker
Murali S. Shanker
AZAimao Zhang
Aimao Zhang

1 October 2013 in Information Resources Management Journal
Verified
Journal Article
Closed access
PDF file
Joseph K. NwankpaJoseph K. Nwankpa
Joseph K. Nwankpa
YRYaman Roumani
Yaman Roumani
ABAlan Brandyberry
Alan Brandyberry
AGAlfred Guiffrida
Alfred Guiffrida
MHMichael Hu
Michael Hu
Murali S. ShankerMurali S. Shanker
Murali S. Shanker
Understanding the Link Between Initial ERP Systems and ERP-Enabled Adoption: 10.4018/irmj.2013100102: ERP systems have been identified as platform technologies that permit the adoption of subsequent technologies that leverage the information integration

1 March 2018 in Information & Management
Verified
Journal Article
Closed access
VGVenugopal Gopalakrishna-Remani
Venugopal Gopalakrishna-Remani
JBJay R. Brown
Jay R. Brown
Murali S. ShankerMurali S. Shanker
Murali S. Shanker
MHMicheal Hu
Micheal Hu