Grading attribute selection of China's grading system for agricultural products: What attributes benefit consumers more?

Wenjing Nie, David Abler, Taiping Li

Research output: Contribution to journalArticlepeer-review

Abstract

The grading system for agricultural products is an effective and widely adopted way to meet increasing consumer demand for food quality. China has a huge and fast-growing market for food consumption, the effectiveness of grading system, however, is still low even after almost a decade of implementation. This study provides an empirical and statistically significant evidence that the improper grading attribute selection based solely on sensory attributes is inferred to be the main reason for the low effectiveness of grading system. The real choice experiment is applied to reveal consumer preferences and willingness to pay for prescribed grading attributes using Fuji apples as a representative example. A welfare economics analysis is performed to estimate potential consumer demand for graded food within an optimized grading system. Results indicate that consumers have stronger preferences for intrinsic quality attributes comparing to external sensory attributes. For Fuji apples, crispness and sweetness are the two most preferred quality attributes associated with the relative importance values of 47% and 40%, respectively, while the color only accounts 13%. Furthermore, the optimized grading system with a more emphasis on quality attributes is found to contribute to a greater welfare improvement and leave high-income consumers better off.

Original languageEnglish (US)
Article number101707
JournalJournal of Behavioral and Experimental Economics
Volume93
DOIs
StatePublished - Aug 2021

All Science Journal Classification (ASJC) codes

  • Applied Psychology
  • Economics and Econometrics
  • Social Sciences(all)

Fingerprint Dive into the research topics of 'Grading attribute selection of China's grading system for agricultural products: What attributes benefit consumers more?'. Together they form a unique fingerprint.

Cite this