Purpose

This paper aims to identify and analyze the agtech classification and categorization systems in the Brazilian context.

Design/methodology/approach

The systematic literature review (SLR) was carried out according to the protocol of Kitchenham and Charters (2007). The classification systems found in literature were evaluated using the thinking aloud protocol, as proposed by Ericsson and Simon (1993). The responses obtained were evaluated through lexicographic analysis, described by Bécue-Bertaut (2019) and content analysis, described by Bardin (2011).

Findings

SLR identified four agtech classification systems. The model proposed by Dias, Jardim, and Sakuda (2019) was the one with the highest adherence to classify Brazilian agtechs. From the analysis of the systems found in literature, the authors proposed a new categorization model of agricultural startups (agtechs).

Research limitations/implications

The study has limitations in relation to the theoretical and empirical validation of the model proposed by the authors. This limitation can be the subject of subsequent research.

Practical implications

The SLR study considers the evolution of the classification systems of a new agribusiness reality, the agtechs. In addition, there is a practical contribution in proposing a new classification system that attempts to address some of the limitations found in previous studies.

Originality/value

Agtechs are startups focused on developing solutions for agriculture and have shown a significant increase in recent years. However, there are few studies focused on this type of company. Even rarer are the studies that seek to classify and categorize them. The present work opens the horizon for future studies focused on this new reality.

中文翻译：

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巴西农业初创公司 (Agtechs) 的分类和归类

目的

本文旨在识别和分析巴西背景下的 agtech 分类和分类系统。

设计/方法/方法

系统文献综述 (SLR) 根据 Kitchenham 和Charters (2007) 的协议进行。正如 Ericsson 和 Simon (1993) 提出的那样，文献中发现的分类系统使用大声思考协议进行评估。通过 Bécue-Bertaut (2019) 描述的词典分析和 Bardin (2011) 描述的内容分析对获得的回答进行了评估。

发现

SLR 确定了四个 agtech 分类系统。Dias、Jardim 和 Sakuda（2019 年）提出的模型是对巴西 agtechs 进行分类的依从性最高的模型。通过对文献中发现的系统的分析，作者提出了一种新的农业初创企业（agtechs）分类模型。

研究限制/影响

该研究在作者提出的模型的理论和经验验证方面存在局限性。这种限制可能是后续研究的主题。

实际影响

SLR 研究考虑了新的农业综合企业现实（即农业技术）的分类系统的演变。此外，在提出一种新的分类系统以试图解决先前研究中发现的一些局限性方面也有实际贡献。

原创性/价值

Agtechs 是专注于开发农业解决方案的初创公司，近年来增长显着。然而，很少有研究关注这种类型的公司。更罕见的是寻求对它们进行分类和分类的研究。目前的工作为未来关注这一新现实的研究打开了视野。