Purpose

This study aims to investigate the relationship between consumer awareness of Zespri International Limited (Zespri™) and its sales promotion in Japan and the recent expansion of New Zealand (NZ) kiwifruit imported into Japan.

Design/methodology/approach

Tweets mentioning Zespri™ were utilised as a proxy of such awareness. They were first summarised using two text-mining techniques: tf-idf scoring and a co-occurrence network graph. Afterwards, the authors estimated a tri-variate vector autoregression (VAR) model consisting of the net imports of NZ kiwifruit in Japan, unit import price and number of tweets. Additionally, the occurrence frequency of tweets with “Kiwi Brothers”, promotional characters for Zespri™’s sales, was added to the model, and a tetra-variate VAR model was estimated. Finally, Granger-causality tests, an estimation of the impulse response function and forecast error variance decomposition was conducted.

Findings

All these variables were found to Granger-cause each other. Furthermore, a shock in the document frequency of “Kiwi Brothers” significantly affected Japan’s kiwifruit imports from NZ, explaining approximately 20% of future imports. Zespri™’s distinctive sales promotion was, thus, found to contribute in part to the recent increase in NZ’s kiwifruit export to Japan.

Originality/value

This paper is the first to apply text-regression methodology to food consumption research; it contributes to food consumption research by proposing a practical way to combine tweets with outcome variables using a time-series analysis.

中文翻译：

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推文在农产品出口中的作用：文本挖掘和时间序列分析的方法

目的

本研究旨在调查佳沛国际有限公司 (Zespri™) 的消费者认知度及其在日本的促销活动与新西兰 (NZ) 奇异果进口到日本的近期扩张之间的关系。

设计/方法论/途径

提及 Zespri™ 的推文被用作这种意识的代表。首先使用两种文本挖掘技术对它们进行总结：tf-idf 评分和共现网络图。随后，作者估计了一个三变量向量自回归（VAR）模型，该模型由日本新西兰奇异果的净进口量、进口单位价格和推文数量组成。此外，模型中还添加了“Kiwi Brothers”（佳沛™销售促销角色）推文的出现频率，并估计了四变量 VAR 模型。最后进行格兰杰因果检验、脉冲响应函数估计和预测误差方差分解。

发现

所有这些变量都被发现相互存在格兰杰因果关系。此外，“奇异果兄弟”文件频率的冲击显着影响了日本从新西兰的奇异果进口，解释了未来进口量的约20%。因此，人们发现佳沛™独特的促销活动在一定程度上促进了最近新西兰向日本出口奇异果的增长。

原创性/价值

本文首次将文本回归方法应用于食品消费研究；它提出了一种使用时间序列分析将推文与结果变量结合起来的实用方法，为食品消费研究做出了贡献。