Purpose

This work consists of a critical reflection on the extent to which hospitality and tourism management scholars have accurately used the term “analytics” and its five types (i.e. descriptive, exploratory, predictive, prescriptive and cognitive analytics) in their research. Only cognitive analytics, the latest and most advanced type, is based on artificial intelligence (AI) and requires machine learning (ML). As cognitive analytics constitutes the cutting edge in industry application, this study aims to examine in depth the extent cognitive analytics has been covered in the literature.

Design/methodology/approach

This study is based on a systematic literature review (SLR) of the hospitality and tourism literature on the topic of “analytics”. The SLR findings were complemented by the results of an additional search query based on “machine learning” and “deep learning” that was used as a robustness check. Moreover, the SLR findings were triangulated with recent literature reviews on related topics (e.g. big data and AI) to generate additional insights.

Findings

The findings of this study show that: there is a growing and accelerating body of research on analytics; the literature lacks a consistent use of terminology and definitions related to analytics. Specifically, publications rarely use scientific definitions of analytics and their different types; although AI and ML are key enabling technologies for cognitive analytics, hospitality and tourism management research did not explicitly link these terms to analytics and did not distinguish cognitive analytics from other forms of analytics that do not rely on ML. In fact, the term “cognitive analytics” is apparently missing in the hospitality and tourism management literature.

Research limitations/implications

This study generates a set of eight theoretical and three practical implications and advance theoretical and methodological recommendations for further research.

Originality/value

To the best of the authors’ knowledge, this is the first study that explicitly and critically examines the use of analytics in general, and cognitive analytics in particular, in the hospitality and tourism management literature.

中文翻译：

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对酒店和旅游管理研究中分析和基于人工智能的分析的批判性反思

目的

这项工作包括对酒店和旅游管理学者在其研究中准确使用“分析”一词及其五种类型（即描述性分析、探索性分析、预测性分析、规范性分析和认知分析）的程度进行批判性反思。只有最新、最先进的认知分析基于人工智能 (AI)，并且需要机器学习 (ML)。由于认知分析构成了行业应用的前沿，本研究旨在深入研究认知分析在文献中的涵盖程度。

设计/方法论/途径

本研究基于对“分析”主题的酒店和旅游文献的系统文献综述（SLR）。SLR 的发现得到了基于“机器学习”和“深度学习”的额外搜索查询结果的补充，该搜索查询被用作稳健性检查。此外，SLR 的研究结果与最近相关主题（例如大数据和人工智能）的文献综述进行了三角测量，以产生更多的见解。

发现

这项研究的结果表明： 关于分析的研究正在不断增长和加速；文献中缺乏与分析相关的术语和定义的一致使用。具体来说，出版物很少使用分析及其不同类型的科学定义；尽管人工智能和机器学习是认知分析的关键支持技术，但酒店和旅游管理研究并未明确将这些术语与分析联系起来，也没有将认知分析与不依赖机器学习的其他形式的分析区分开来。事实上，酒店和旅游管理文献中显然缺少“认知分析”一词。

研究局限性/影响

这项研究产生了八项理论意义和三项实践意义，并为进一步研究提出了理论和方法论建议。

原创性/价值

据作者所知，这是第一项明确且批判性地研究一般分析，特别是认知分析在酒店和旅游管理文献中的使用的研究。