{"title":"How agricultural economists are using big data: a review","authors":"Liang Lu, Guang Tian, Patrick L. Hatzenbuehler","doi":"10.1108/caer-09-2021-0167","DOIUrl":null,"url":null,"abstract":"PurposeThe purpose of this paper is to describe the main ways in which large amounts of information have been integrated to provide new measures of food consumption and agricultural production, and new methods for gathering and analyzing internet-based data.Design/methodology/approachThis study reviews some of the recent developments and applications of big data, which is becoming increasingly popular in agricultural economics research. In particular, this study focuses on applications of new types of data such as text and graphics in consumers' online reviews emerging from e-commerce transactions and Normalized Difference Vegetation Index (NDVI) data as well as other producer data that are gaining popularity in precision agriculture. This study then reviews data gathering techniques such as web scraping and data analytics tools such as textual analysis and machine learning.FindingsThis study provides a comprehensive review of applications of big data in agricultural economics and discusses some potential future uses of big data.Originality/valueThis study documents some new types of data that are being utilized in agricultural economics, sources and methods to gather and store such data, existing applications of these new types of data and techniques to analyze these new data.","PeriodicalId":10095,"journal":{"name":"China Agricultural Economic Review","volume":" ","pages":""},"PeriodicalIF":4.4000,"publicationDate":"2022-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"China Agricultural Economic Review","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1108/caer-09-2021-0167","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURAL ECONOMICS & POLICY","Score":null,"Total":0}
引用次数: 2
Abstract
PurposeThe purpose of this paper is to describe the main ways in which large amounts of information have been integrated to provide new measures of food consumption and agricultural production, and new methods for gathering and analyzing internet-based data.Design/methodology/approachThis study reviews some of the recent developments and applications of big data, which is becoming increasingly popular in agricultural economics research. In particular, this study focuses on applications of new types of data such as text and graphics in consumers' online reviews emerging from e-commerce transactions and Normalized Difference Vegetation Index (NDVI) data as well as other producer data that are gaining popularity in precision agriculture. This study then reviews data gathering techniques such as web scraping and data analytics tools such as textual analysis and machine learning.FindingsThis study provides a comprehensive review of applications of big data in agricultural economics and discusses some potential future uses of big data.Originality/valueThis study documents some new types of data that are being utilized in agricultural economics, sources and methods to gather and store such data, existing applications of these new types of data and techniques to analyze these new data.
期刊介绍:
Published in association with China Agricultural University and the Chinese Association for Agricultural Economics, China Agricultural Economic Review publishes academic writings by international scholars, and particularly encourages empirical work that can be replicated and extended by others; and research articles that employ econometric and statistical hypothesis testing, optimization and simulation models. The journal aims to publish research which can be applied to China’s agricultural and rural policy-making process, the development of the agricultural economics discipline and to developing countries hoping to learn from China’s agricultural and rural development.