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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.

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.