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首页> 外文期刊>Journal of service management >From words to pixels: text and image mining methods for service research
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From words to pixels: text and image mining methods for service research

机译：从单词到像素：用于服务研究的文本和图像挖掘方法

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Purpose The purpose of this paper is to describe and position the state-of-the-art of text and image mining methods in business research. By providing a detailed conceptual and technical review of both methods, it aims to increase their utilization in service research. Design/methodology/approach On a first stage, the authors review business literature in marketing, operations and management concerning the use of text and image mining methods. On a second stage, the authors identify and analyze empirical papers that used text and image mining methods in services journals and premier business. Finally, avenues for further research in services are provided. Findings The manuscript identifies seven text mining methods and describes their approaches, processes, techniques and algorithms, involved in their implementation. Four of these methods are positioned similarly for image mining. There are 39 papers using text mining in service research, with a focus on measuring consumer sentiment, experiences, and service quality. Due to the nonexistent use of image mining service journals, the authors review their application in marketing and management, and suggest ideas for further research in services. Research limitations/implications - This manuscript focuses on the different methods and their implementation in service research, but it does not offer a complete review of business literature using text and image mining methods. Practical implications - The results have a number of implications for the discipline that are presented and discussed. The authors provide research directions using text and image mining methods in service priority areas such as artificial intelligence, frontline employees, transformative consumer research and customer experience. Originality/value The manuscript provides an introduction to text and image mining methods to service researchers and practitioners interested in the analysis of unstructured data. This paper provides several suggestions concerning the use of new sources of data (e.g. customer reviews, social media images, employee reviews and emails), measurement of new constructs (beyond sentiment and valence) and the use of more recent methods (e.g. deep learning).
机译：目的本文的目的是描述和定位商务研究中最新的文本和图像挖掘方法。通过对这两种方法进行详细的概念和技术审查，它旨在提高其在服务研究中的利用率。设计/方法/方法在第一阶段，作者回顾了有关文本和图像挖掘方法使用的市场营销，运营和管理方面的商业文献。在第二阶段，作者确定并分析了在服务期刊和主要业务中使用文本和图像挖掘方法的经验论文。最后，提供了进一步研究服务的途径。调查结果该手稿确定了七种文本挖掘方法，并描述了它们的实现所涉及的方法，过程，技术和算法。这些方法中的四种被相似地定位用于图像挖掘。在服务研究中，有39篇使用文本挖掘的论文，着重于衡量消费者的情感，体验和服务质量。由于不存在图像挖掘服务期刊，因此作者回顾了它们在市场营销和管理中的应用，并提出了进一步研究服务的想法。研究局限性/含义-该手稿着重于服务研究中的不同方法及其实现，但未提供使用文本和图像挖掘方法的商业文献的完整综述。实际意义-结果对所介绍和讨论的学科有许多启示。作者在人工智能，一线员工，变革型消费者研究和客户体验等服务优先领域中使用文本和图像挖掘方法提供了研究方向。独创性/价值该手稿为服务于对非结构化数据分析感兴趣的研究人员和从业人员介绍了文本和图像挖掘方法。本文提供了有关使用新数据源（例如，客户评论，社交媒体图像，员工评论和电子邮件），衡量新结构（超出情感和价值）以及使用最新方法（例如，深度学习）的一些建议。 。

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