S
Syed Imran Ali Meerza Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Researcher
faculty
9 h-index
45 pubs
186 cited
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
Syed Imran Ali Meerza investigates consumer behavior, particularly in relation to food choices and information consumption. His work includes examining how consumers value products, such as biofortified crops, through experimental auctions. Meerza also studies information avoidance behaviors, exploring factors that influence why individuals may choose to remain uninformed about critical health issues like antimicrobial resistance, and how stressors, such as those related to COVID-19, can exacerbate this tendency. His research also applies machine learning techniques to predict outcomes like student retention and identify vulnerable households experiencing food insecurity. Meerza has published 44 papers, with a total of 182 citations, and holds an h-index of 9. He has collaborated with Mohammad Sajidul Islam on shared publications.
Metrics
- h-index: 9
- Publications: 45
- Citations: 186
Selected Publications
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Good News or Bad News First? The Impact of Sequential Information and Recency Bias on Consumers’ Valuations of Zinc Rice (2025)
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Exploring Public Perception Towards Gene‐Edited and Genetically Modified Foods in the United States: An Application of the Spiral of Silence Theory (2025)
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The Effects of Information Interventions and Social Interactions on the Valuations of Zinc Rice Seeds: Evidence From a Field Experiment With Rice Farmers (2025)
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The role of hopelessness in mediating the relationship between income loss and delaying and foregoing healthcare: Evidence from repeated cross-sectional waves of the Household Pulse Survey (2025)
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Risk Propensity and Acceptance of Gene-edited and Genetically Modified Food among US Consumers: A Comparison between Plants and Animal Products (2024)
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Emotional responses to COVID-19 stressors increase information avoidance about an important unrelated health threat (2023)
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Consumers’ valuation of a biofortified crop: Evidence from a laboratory experiment (2023)
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Understanding the Prediction of Student Retention Behavior during covid-19 Using Effective Data Mining Techniques (2023)
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Prediction of Diabetes at Early Stage using Interpretable Machine Learning (2023)
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The Impact of Information on Valuation in Experimental Auctions: A Comparison of Between and Within Subject Designs (2023)
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Who Thinks COVID-19 is not a Crisis? Need for Cognition and Political Ideology Influence Perceptions of the Severity of COVID-19 (2023)
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Emotional responses to COVID-19 stressors increase avoidance of health information and access to care (2023)
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U.S. Consumer Attitudes toward Antibiotic Use in Livestock Production (2022)
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Information avoidance behavior: Does ignorance keep us uninformed about antimicrobial resistance? (2021)
Collaboration Network
Top Collaborators
Christopher R. Gustafson
University of Nebraska–Lincoln (US)
9 shared publications
- Information avoidance behavior: Does ignorance keep us uninformed about antimicrobial resistance?
- U.S. Consumer Attitudes toward Antibiotic Use in Livestock Production
- The Impact of Information on Valuation in Experimental Auctions: A Comparison of Between and Within Subject Designs
- Emotional responses to COVID-19 stressors increase information avoidance about an important unrelated health threat
- Emotional responses to COVID-19 stressors increase avoidance of health information and access to care
Showing 5 of 9 shared publications
Kathleen R. Brooks
University of Nebraska–Lincoln (US)
8 shared publications
- Information avoidance behavior: Does ignorance keep us uninformed about antimicrobial resistance?
- U.S. Consumer Attitudes toward Antibiotic Use in Livestock Production
- Emotional responses to COVID-19 stressors increase information avoidance about an important unrelated health threat
- Emotional responses to COVID-19 stressors increase avoidance of health information and access to care
- Predicting Information Avoidance Behavior using Machine Learning
Showing 5 of 8 shared publications
Amalia Yiannaka
University of Nebraska–Lincoln (US)
8 shared publications
- Information avoidance behavior: Does ignorance keep us uninformed about antimicrobial resistance?
- U.S. Consumer Attitudes toward Antibiotic Use in Livestock Production
- Emotional responses to COVID-19 stressors increase information avoidance about an important unrelated health threat
- Emotional responses to COVID-19 stressors increase avoidance of health information and access to care
- Predicting Information Avoidance Behavior using Machine Learning
Showing 5 of 8 shared publications
Afsana Ahamed
Arkansas Tech University (US)
4 shared publications
- Prediction of Diabetes at Early Stage using Interpretable Machine Learning
- Food Insecurity Through Machine Learning Lens: Identifying Vulnerable Households
- Risk Propensity and Acceptance of Gene-edited and Genetically Modified Food among US Consumers: A Comparison between Plants and Animal Products
- Exploring Public Perception Towards Gene‐Edited and Genetically Modified Foods in the United States: An Application of the Spiral of Silence Theory
Khondoker Abdul Mottaleb
Texas Tech University (US)
4 shared publications
- Consumers’ valuation of a biofortified crop: Evidence from a laboratory experiment
- Risk Propensity and Acceptance of Gene-edited and Genetically Modified Food among US Consumers: A Comparison between Plants and Animal Products
- The Effects of Information Interventions and Social Interactions on the Valuations of Zinc Rice Seeds: Evidence From a Field Experiment With Rice Farmers
- Good News or Bad News First? The Impact of Sequential Information and Recency Bias on Consumers’ Valuations of Zinc Rice
Alwin Dsouza
Agricultural & Applied Economics Association (US)
4 shared publications
- Consumers’ valuation of a biofortified crop: Evidence from a laboratory experiment
- Risk Propensity and Acceptance of Gene-edited and Genetically Modified Food among US Consumers: A Comparison between Plants and Animal Products
- Exploring Public Perception Towards Gene‐Edited and Genetically Modified Foods in the United States: An Application of the Spiral of Silence Theory
- Good News or Bad News First? The Impact of Sequential Information and Recency Bias on Consumers’ Valuations of Zinc Rice
Rezwanul Parvez
Colorado State University (US)
2 shared publications
- Understanding the Prediction of Student Retention Behavior during covid-19 Using Effective Data Mining Techniques
- Forecasting student enrollment using time series models and recurrent neural networks
Nazea Hasan Khan Chowdhury
1 shared publication
- Forecasting student enrollment using time series models and recurrent neural networks
Syed Irfan Ali Meerza
1 shared publication
- Food Insecurity Through Machine Learning Lens: Identifying Vulnerable Households
Sabrina Gulab
University of Nebraska–Lincoln (US)
1 shared publication
- U.S. Consumer Attitudes toward Antibiotic Use in Livestock Production
Mohammad Sajidul Islam
Arkansas Tech University
1 shared publication
In database
- Prediction of Diabetes at Early Stage using Interpretable Machine Learning
Md Minul Alam
Arkansas Tech University (US)
1 shared publication
- Prediction of Diabetes at Early Stage using Interpretable Machine Learning
A. Tarantino
Colorado State University (US)
1 shared publication
- Understanding the Prediction of Student Retention Behavior during covid-19 Using Effective Data Mining Techniques
Md. Shajedur Rahaman
Bangladesh Rice Research Institute (BD)
1 shared publication
- Consumers’ valuation of a biofortified crop: Evidence from a laboratory experiment
Md Abdur Rouf Sarkar
Bangladesh Rice Research Institute (BD)
1 shared publication
- Consumers’ valuation of a biofortified crop: Evidence from a laboratory experiment
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