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The purpose of this paper is to propose new directions for human resource management (HRM) research by drawing attention to online data as a complementary data source to traditional quantitative and qualitative data, and introducing network text analysis as a method for large quantities of textual material.

The paper first presents the added value and potential challenges of utilising online data in HRM research, and then proposes a four-step process for analysing online data with network text analysis.

Online data represent a naturally occuring source of real-time behavioural data that do not suffer from researcher intervention or hindsight bias. The authors argue that as such, this type of data provides a promising yet currently largely untapped empirical context for HRM research that is particularly suited for examining discourses and behavioural and social patterns over time.

While online data hold promise for many novel research questions, it is less appropriate for research questions that seek to establish causality between variables. When using online data, particular attention must be paid to ethical considerations, as well as the validity and representativeness of the sample.

The authors introduce online data and network text analysis as a new avenue for HRM research, with potential to address novel research questions at micro-, meso- and macro-levels of analysis.

The purpose of this study is to examine the extent to which dynamic network analysis (DNA), text mining and natural language processing (NLP) are helpful research tools in identifying the key actors in a complex international crisis. The study uses these tools to identify the key actors in the Syrian crisis as a case study to validate the proposed algorithm.

To achieve its main purpose, the study uses a collection of three methodologies, namely, DNA, text mining and NLP.

The results of the analysis show four key actors in the Syrian crisis, namely, Russia, the USA, Turkey and China. The results also reveal changes in their powerful positions from 2012 to 2016, which matches the changes that occurred in the real world. The matching between the findings of the proposed algorithm and the real world events that happened in Syria validate our proposed algorithm and proves that the algorithm can be used in identifying the key actors in complex international crises.

The importance of the study lies in two main points. It proposes a new algorithm that mixes NLP, network extraction from textual unstructured data and DNA to understand and monitor changes occurring in a complex international crisis. It applies the proposed algorithm on the Syrian crisis as a case study to identify the key actors and hence validate the proposed algorithm.

Large-scale text-based data increasingly poses methodological challenges due to its size, scope and nature, requiring sophisticated methods for managing, visualizing, analyzing and interpreting such data. This paper aims to propose semantic network analysis (SemNA) as one possible solution to these challenges, showcasing its potential for consumer and marketing researchers through three application areas in phygital contexts.

This paper outlines three general application areas for SemNA in phygital contexts and presents specific use cases, data collection methodologies, analyses, findings and discussions for each application area.

The paper uncovers three application areas and use cases where SemNA holds promise for providing valuable insights and driving further adoption of the method: (1) Investigating phygital experiences and consumption phenomena; (2) Exploring phygital consumer and market discourse, trends and practices; and (3) Capturing phygital social constructs.

The limitations section highlights the specific challenges of the qualitative, interpretivist approach to SemNA, along with general methodological constraints.

Practical implications highlight SemNA as a pragmatic tool for managers to analyze and visualize company-/brand-related data, supporting strategic decision-making in physical, digital and phygital spaces.

This paper contributes to the expanding body of computational, tool-based methods by providing an overview of application areas for the qualitative, interpretivist approach to SemNA in consumer and marketing research. It emphasizes the diversity of research contexts and data, where the boundaries between physical and digital spaces have become increasingly intertwined with physical and digital elements closely integrated – a phenomenon known as phygital.

This paper aims to map the creation and evolution of centering resonance analysis (CRA). This method was an innovative approach developed to conduct textual content analysis in a semi-automatic, theory-informed and analytically rigorous way. Nevertheless, despite its robust procedures to analyze documents and interviews, CRA is still broadly unknown and scarcely used in management research.

To track CRA’s development, the roadmapping approach was properly adapted. The traditional time-based multi-layered map format was customized to depict, graphically, the results obtained from a systematic literature review of the main CRA publications.

In total, 19 papers were reviewed, from the method’s introduction in 2002 to its last tracked methodological development. In all, 26 types of CRA analysis were identified and grouped in five categories. The most innovative procedures in each group were discussed and exemplified. Finally, a CRA methodological roadmap was presented, including a layered typology of the publications, in terms of their focus and innovativeness; the number of analysis conducted in each publication; references for further CRA development; a segmentation and description of the main publication periods; main turning points; citation-based relationships; and four possible future scenarios for CRA as a method.

This paper offers a unique and comprehensive review of CRA’s development, favoring its broader use in management research. In addition, it develops an adapted version of the roadmapping approach, customized for mapping methodological innovations over time.

This study aims to frame the authenticity–standardisation relationship in international gastronomy retailing and explores how and to what extent the food place of origin and the urban context in which the gastronomy stores are located shape customers' in-store experience.

This paper analyses the case of Eataly, which combines specialty grocery stores and restaurants disseminating the Italian eating style, quality food and regional traditions internationally. Facebook reviews (1,018) of four Eataly stores – New York City, Rome, Munich and Istanbul were analysed, adopting a web content mining approach.

Place of origin, quality and hosting city categories frame the gastronomic in-store experience. Standardisation elements (shared across the four analysed stores) and authenticity elements (specific to a single store) are identified towards defining three archetypical authenticity–standardisation relationships, namely originated authenticity, standardised authenticity and localised authenticity.

This study proposes original modelling that disentangles the authenticity–standardisation paradox in international gastronomy retailing. It provides evidence of the intertwining of the place of origin and the city brand in customers' in-store experience.

The purpose of this paper is to review state-of-the-art literature on product/brand positioning to re-examine the positioning concept and developing a more comprehensive definition from a theoretical viewpoint.

A systematic review of positioning was conducted. The review conformed to a rigorous set of core principles: it was systematic (organized according to a method designed to address the review questions), transparent (explicitly stated), reproducible and updatable and synthesized (summarized the evidence relating to the review question).

The literature review reveals that there is lack of coherent definition for positioning, and there is no mutual agreement among marketing scholars and practitioners about the exact meaning of the concept. Therefore, comprehensive definition of positioning encompassing the five underlying positioning perspectives (competition; empty slot/mind; consumers’ perception, differentiation and competitive advantage) is suggested.

This paper will be useful for academicians to analyze the current nature of academic research in this area and will provide an added advantage to managers to design and implement positioning strategies for their product/brands that will allow their organizations to gain competitive advantage. This study acknowledges limitations with respect to its exclusive search criteria, which might affect its generalizability.

Position and positioning is of relevance in society in broad terms, e.g. in sports, politics and culture. Positioning strategy is discussed and implemented in different industries (business-to-business and consumer), for all kinds of brands (including, for instance, corporate brands) and for “brands” in the very widest sense (such as places or people).

This is the first systematic review of positioning that provides a detailed understanding of the current state of positioning research on a single platform and also draws a comprehensive positioning conceptualization.

Food companies and consumers are increasingly interested in healthy food and beverages. Coffee is one of the most commonly consumed beverages worldwide. There is increasing consensus that coffee consumption can have beneficial effects on human body. This paper aims at exploring Twitter messages' content and sentiment towards health attributes of coffee.

The research adopted a utilitarian and hedonic consumer behaviour perspective to analyse online community messages. A sample of 13,000 tweets, from around 4,800 users, that mentions keywords coffee and health was collected on a daily basis for a month in mid-2017. The tweets were categorized with a term frequency analysis, keyword-in-context analysis and sentiment analysis.

Results showed that the majority of tweets are neutral or slightly positive towards coffee’s effects on health. Media and consumers are dynamic Twitter users. Findings support that coffee consumption brings favourable emotions, wellness, energy, positive state of mind and an enjoyable and trendy lifestyle. Many tweets have a positive perception of coffee health benefits, especially relating to mental and physical well-being.

The high number of users and tweets analysed compensates the limited amount of time of data collection, Twitter messages' restricted number of characters and quantitative software analysis limitations.

The research provides valuable suggestions for food and beverage industry managers.

This work adds value to the literature by expanding scholars' research on food product attributes perception analysis by using social media as a source of information. Moreover, it provides valuable information on marketable coffee attributes.

The purpose of this paper is to investigate how previous literature has analyzed the role of augmented reality and virtual reality in the field of tourism, distinguishing between studies focused on one technology or the other as both have characteristics that profoundly differentiate them.

This study carries out a critical review to assess and synthesize the literature on augmented reality and virtual reality in tourism. Literature searches are conducted using various keywords, resulting in a selection of 84 articles (19 on augmented reality and 65 on virtual reality) from 39 indexed journals.

The research findings demonstrate an increasing scholarly focus on exploring the application of virtual reality and augmented reality within the realm of tourism. These results highlight a noticeable progression in recent years with respect to different matters, such as methodologies, used theories or considered variables, among others. Based on these results, it is proposed a future research agenda that seeks to establish a cohesive framework and drive the development of both augmented reality and virtual reality research in tourism.

By conducting an individual and comparative review of the literature on the application of augmented reality and virtual reality in tourism, this research helps elucidate the specific lines of research for each technology while providing a better understanding of how each technology can be used to generate effective tourist experiences.

El objetivo de este artículo es investigar cómo la literatura previa ha analizado el papel de la realidad aumentada y la realidad virtual en el ámbito del turismo, distinguiendo entre estudios centrados en una u otra tecnología ya que ambas tienen características que las diferencian profundamente.

Este estudio realiza una revisión crítica para evaluar y sintetizar la literatura sobre realidad aumentada y realidad virtual en turismo. Se realizan búsquedas de literatura utilizando diversas palabras clave, que dan como resultado la selección de 84 artículos (19 sobre realidad aumentada y 65 sobre realidad virtual) procedentes de 39 revistas indexadas.

Los resultados de la investigación demuestran que existe un interés creciente en explorar la aplicación de la realidad virtual y la realidad aumentada en el ámbito del turismo. Asimismo, se pone de manifiesto una notable progresión en los últimos años con respecto a diferentes cuestiones, como las metodologías aplicadas, las teorías empleadas o las variables consideradas, entre otras. A partir de estos resultados, se propone una agenda de investigación futura que pretende establecer un marco cohesionado e impulsar el desarrollo de la investigación en el ámbito tanto de la realidad aumentada como de la realidad virtual en turismo.

Al realizar una revisión individual y comparativa de la literatura sobre la aplicación de la realidad aumentada y la realidad virtual en el turismo, esta investigación ayuda a esclarecer las líneas de investigación específicas de cada tecnología a la vez que proporciona una mejor comprensión de cómo cada tecnología puede ser utilizada para generar experiencias turísticas efectivas.

本文旨在研究以往的文献是如何分析增强现实和虚拟现实在旅游领域的作用的, 并对侧重于其中一种技术或另一种技术的研究加以区分, 因为这两种技术都有深刻区别于其他技术的特点。

本研究通过批判性综述来评估和归纳有关旅游业中增强现实和虚拟现实技术的文献。通过使用各种关键词进行文献检索, 从 39 种索引期刊中筛选出 84 篇文章（19 篇关于增强现实技术, 65 篇关于虚拟现实技术）。

研究结果表明, 学术界越来越重视探索虚拟现实和增强现实在旅游业中的应用。这些结果突显了近年来在方法论、采用的理论或考虑的变量等不同方面的明显进步。在这些成果的基础上, 提出了未来的研究议程, 旨在建立一个具有凝聚力的框架, 推动旅游业中增强现实和虚拟现实研究的发展。

本研究通过对增强现实和虚拟现实技术在旅游业中应用的文献进行单独和比较审查, 有助于阐明每种技术的具体研究方向, 同时让人们更好地了解如何使用每种技术来产生有效的旅游体验。

Using the methodologies of text mining, this paper examines the implications of US and Chinese policies on bilateral trade. Official speeches by political leaders of the U.S. and China on the issues of trade were collected and analytically examined for US-China gaps in major foreign policies, such as bilateral trade and the Belt and Road Initiative. In this paper, a term frequency-inverse document frequency word cloud, a network similarities index, machine learning-processed latent Dirichlet allocation (LDA), and structural equivalence are applied to examine the meanings of the speeches. The main arguments in this paper are as follows. First, the document similarity between the speeches of Chinese and US leaders appears to be completely different. Also, while the documents from Chinese leaders are considerably similar, the documents from US leaders differ by far. Secondly, LDA topic analysis indicates that China concentrates more on international and collaborative relationships, while the U.S. has more focus on domestic and economic interests. Third, from a word hierarchy analysis, the basic words used by American and Chinese leaders are also completely different. Agriculture, farmers, automobiles, and negotiations are the basic words for American leaders, but for Chinese leaders, the basic words are planning, markets, and education.

Following Hovland’s persuasion theory, this paper aims to develop a conceptual model and analyzes characteristics of online political deliberation behavior from three aspects (i.e. information, situation and manager). Based on the whole interactive process of online political deliberation, this paper aims to reveal the key points that affect the response effect of the government from the persuasive perspective of online political consultation.

Based on more than 40,000 netizens’ posts and government responses from 2011 to the first half of 2019 of the Chinese political platform, this paper used the text analysis and machine learning methods to extract measurement variables of online political deliberation characteristics and the econometrics analysis method to conduct empirical research.

The results showed that the textual information, political environment and identity of the political objects affect the effectiveness of government response. Furthermore, for different position categories of political officials, the length of political texts, topic categories and emotional tendencies have different effects on the response effectiveness. Additionally, the effect of political time on the effectiveness of response differs.

The findings will help ascertain the characteristics of online political deliberation behavior that affect how effective government response is and provide a theoretical basis for why the public should express their political concerns.