Marcello M. Mariani, R. Baggio, M. Fuchs, Wolfram Hoepken
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引用次数: 224
Abstract
Purpose
This paper aims to examine the extent to which Business Intelligence and Big Data feature within academic research in hospitality and tourism published until 2016, by identifying research gaps and future developments and designing an agenda for future research.
Design/methodology/approach
The study consists of a systematic quantitative literature review of academic articles indexed on the Scopus and Web of Science databases. The articles were reviewed based on the following features: research topic; conceptual and theoretical characterization; sources of data; type of data and size; data collection methods; data analysis techniques; and data reporting and visualization.
Findings
Findings indicate an increase in hospitality and tourism management literature applying analytical techniques to large quantities of data. However, this research field is fairly fragmented in scope and limited in methodologies and displays several gaps. A conceptual framework that helps to identify critical business problems and links the domains of business intelligence and big data to tourism and hospitality management and development is missing. Moreover, epistemological dilemmas and consequences for theory development of big data-driven knowledge are still a terra incognita. Last, despite calls for more integration of management and data science, cross-disciplinary collaborations with computer and data scientists are rather episodic and related to specific types of work and research.
Research limitations/implications
This work is based on academic articles published before 2017; hence, scientific outputs published after the moment of writing have not been included. A rich research agenda is designed.
Originality/value
This study contributes to explore in depth and systematically to what extent hospitality and tourism scholars are aware of and working intendedly on business intelligence and big data. To the best of the authors’ knowledge, it is the first systematic literature review within hospitality and tourism research dealing with business intelligence and big data.
目的本文旨在通过确定研究差距和未来发展,并设计未来研究议程,来检验商业智能和大数据在2016年之前发表的酒店和旅游学术研究中的作用。设计/方法/方法该研究包括对Scopus和Web of Science数据库上的学术文章进行系统的定量文献综述。文章从以下几个方面进行了综述:研究主题;概念和理论特征;数据来源;数据类型和大小;数据收集方法;数据分析技术;以及数据报告和可视化。调查结果表明,将分析技术应用于大量数据的酒店和旅游管理文献有所增加。然而,这一研究领域在范围上相当分散,在方法上也很有限,并显示出一些差距。缺少一个概念框架,该框架有助于识别关键的商业问题,并将商业智能和大数据领域与旅游和酒店管理和发展联系起来。此外,大数据驱动知识理论发展的认识论困境和后果仍然是一块未知的领域。最后,尽管有人呼吁将管理和数据科学更多地融合在一起,但与计算机和数据科学家的跨学科合作是偶然的,与特定类型的工作和研究有关。研究局限性/含义本文基于2017年之前发表的学术文章;因此,在撰写本文之后发表的科学成果没有被包括在内。设计了丰富的研究议程。独创性/价值本研究有助于深入系统地探索酒店和旅游学者对商业智能和大数据的了解程度。据作者所知,这是酒店和旅游研究中首次涉及商业智能和大数据的系统文献综述。
期刊介绍:
The International Journal of Contemporary Hospitality Management serves as a conduit for disseminating the latest developments and innovative insights into the management of hospitality and tourism businesses globally. The journal publishes peer-reviewed papers that comprehensively address issues pertinent to strategic management, operations, marketing, finance, and HR management in the field of hospitality and tourism.