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This study aims to explore the application of emojis to mood descriptions of fiction. The three goals are investigating whether Cho et al.'s model (2023) is a sound conceptual framework for implementing emojis and mood categories in information systems, mapping 30 mood categories to 115 face emojis and exploring and visualizing the relationships between mood categories based on emojis mapping.

An online survey was distributed to a US public university to recruit adult fiction readers. In total, 64 participants completed the survey.

The results show that the participants distinguished between the three families of fiction mood categories. The three families model is a promising option to improve mood descriptions for fiction. Through mapping emojis to 30 mood categories, the authors identified the most popular emojis for each category, analyzed the relationships between mood categories and examined participants' consensus on mapping.

This study focuses on applying emojis to fiction reading. Emojis were mapped to mood categories by fiction readers. Emoji mapping contributes to the understanding of the relationships between mood categories. Emojis, as graphic mood descriptors, have the potential to complement textual descriptors and enrich mood metadata for fiction.

Using bibliometric techniques, the author analyzes a dataset of 276 articles on cross-border mergers and acquisitions (CBMAs) published in 13 management and international business journals. The author assesses the scientific impact and visualizes the intellectual landscape of research on CBMAs by analyzing publication and citation data and interconnections between publications. First, the author assesses annual publication trends and identifies highly cited articles and productive journals in the dataset that have significantly contributed to our understanding of CBMAs. Second, the author identifies main themes in recent research on CBMAs by focusing on frequently used keywords in publications. Third, the author identifies clusters of related research and explores their interrelationships to outline emerging trends, new perspectives, and directions for future research on CBMAs. Overall, this chapter contributes to the understanding of CBMAs by documenting the progress made to date and providing important insights for future research.

This study broadens the understanding of how omnichannel service convenience, shopping value and channel congruence affect customer perceived trust and satisfaction and, in turn, affect selection intention after an omnichannel shopping experience.

Target participants were recruited based on previous purchases from the Japanese clothing brand Uniqlo. A questionnaire was distributed via social media. In total, 341 valid responses were collected for structural equation modelling (SEM).

The results revealed that in omnichannel shopping context, perceived trust and satisfaction are positively affected by service convenience and shopping value and are especially affected by channel congruence. Further analysis showed that perceived trust and satisfaction have a positive effect on omnichannel selection intention, with satisfaction playing a mediating role in the relationships of omnichannel service convenience, shopping value and channel congruence with omnichannel selection intention.

This study contributes to the literature on omnichannel customer behaviour by shedding light on the antecedents of intention to select omnichannel retailers from the customer’s perspective.