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http://dx.doi.org/10.5762/KAIS.2017.18.10.215

A Trend Analysis of Agricultural and Food Marketing Studies Using Text-mining Technique  

Yoo, Li-Na (Center for Food, Agricultural & Rural Policy)
Hwang, Su-Chul (Center for Food, Agricultural & Rural Policy)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.18, no.10, 2017 , pp. 215-226 More about this Journal
Abstract
This study analyzed trends in agricultural and food marketing studies from 1984 to 2015 using text-mining techniques. Text-mining is a part of Big-data analysis, which is an effective tool to objectively process large amounts of information based on categorization and trend analysis. In the present study, frequency analysis, topic analysis and association rules were conducted. Titles of agricultural and food marketing studies in four journals and reports were used for placing the analysis. The results showed that 1,126 total theses related to agricultural and food marketing could be categorized into six subjects. There were significant changes in research trends before and after the 2000s. While research before 2000s focused on farm and wholesale level marketing, research after the 2000s mainly covered consumption, (processed)food, exports and imports. Local food and school meals are new subjects that are increasingly being studied. Issues regarding agricultural supply and demand were the only subjects investigated in policy research studies. Interest in agricultural supply and demand was lost after the 2000s. A number of studies after the 2010s analyzed consumption, primarily consumption trends and consumer behavior.
Keywords
Agricultural and Food Marketing; Big-Data; Marketing and Distribution; Text-mining; Trend Analysis;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
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