Purpose

This paper aims to retrieve key components of blockchain applications in supply chain areas. It applies natural language processing methods to generate useful insights from academic literature.

Design/methodology/approach

It first applies a text mining method to retrieve information from scientific journal papers on the related topics. The text information is then analyzed through machine learning (ML) models to identify the important implications from the existing literature.

Findings

The research findings are three-fold. While challenges are of concern, the focus should be given to the design and implementation of blockchain in the supply chain field. Integration with internet of things is considered to be of higher importance. Blockchain plays a crucial role in food sustainability.

Research limitations/implications

The research findings offer insights for both policymakers and business managers on blockchain implementation in the supply chain.

Practical implications

This paper exemplifies the model as situated in the interface of human-based and machine-learned analysis, potentially offering an interesting and relevant avenue for blockchain and supply chain management researchers.

Originality/value

To the best of the knowledge, the research is the very first attempt to apply ML algorithms to analyzing the full contents of blockchain-related research, in the supply chain sector, thereby providing new insights and complementing existing literature.

中文翻译：

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供应链管理中的区块链技术：机器学习算法的见解

目的

本文旨在检索供应链领域中区块链应用程序的关键组件。它运用自然语言处理方法从学术文献中产生有用的见解。

设计/方法/方法

它首先应用文本挖掘方法从科学期刊论文中检索有关主题的信息。然后通过机器学习（ML）模型分析文本信息，以从现有文献中识别出重要的含义。

发现

研究结果是三方面的。尽管面临挑战，但应将重点放在供应链领域中区块链的设计和实施上。与物联网的集成被认为具有更高的重要性。区块链在食品可持续性中起着至关重要的作用。

研究局限/意义

研究结果为决策者和业务经理提供了关于供应链中区块链实施的见解。

实际影响

本文举例说明了该模型位于基于人机分析和机器学习分析的界面中，为区块链和供应链管理研究人员提供了一种有趣且相关的途径。

创意/价值

据了解，该研究是将ML算法应用于供应链领域中与区块链相关研究的全部内容进行分析的首次尝试，从而提供了新的见解并补充了现有文献。