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This study investigates the relationships between perceived scarcity, fear of missing out (FOMO) and impulse-buying tendencies (IBT) in the fast fashion context in both scarcity and non-scarcity conditions. Additionally, this study examines whether these relationships vary depending on the type of scarcity messages: limited-quantity scarcity (LQS) and limited-time scarcity (LTS).

We used written scenarios, and each participant was assigned to one of the experimental or control groups for LQS and LTS conditions. Using a structural modeling approach, we tested the conceptual model and analyzed the data through SmartPLS version 4. We conducted mediating and multigroup (MGA) analysis.

We found that perceived scarcity directly increases IBT and that FOMO partially mediates this relationship across all samples. The MGA findings also revealed that hypothesized relationships were not significantly different across LQS and LTS groups, suggesting that the effect of scarcity messages may be context specific.

Previous studies have yielded mixed results on the effects of different scarcity messages on consumer behavior. This study contributes to the literature by providing evidence of the direct relationship between perceived scarcity, FOMO and impulse buying in the fast fashion context. The study supports the idea that the effect of different types of scarcity messages is context specific, suggesting that the relationship between scarcity perceptions and consumer behavior may vary depending on the product category and cultural context.

The purpose of this paper is to review the literature on Central Bank Digital Currencies (CBDCs) in light of the increasing demand for digital payments globally. It aims to assess the global research landscape, methodologies and data utilized in CBDC studies as their popularity grows.

The paper employs a systematic literature review (SLR) framework, utilizing the Scopus database to identify 323 studies related to Central Bank Digital Currency or CBDC. Through a thorough manual screening process, 169 studies were selected for inclusion. The research employs R, Biblioshiny and Excel for data evaluation, classifying the studies into three methodological categories: quantitative, qualitative and mixed approaches. This classification allows for a detailed assessment of the research techniques and data used in the literature on CBDCs.

The findings include a diverse range of research methodologies and data employed in CBDCs literature, highlighting the growing interest and depth of academic investigation into this area. By categorizing papers according to research technique, the study provides a comprehensive evaluation of the academic landscape regarding CBDC research. It offers valuable insights for researchers, policymakers and stakeholders, contributing to an enhanced understanding of the complexities and opportunities presented by the development and implementation of CBDCs.

This study’s originality lies in its rigorous and transparent methodology for data from CBDC studies, offering a solid framework for future research. By evaluating global research growth within an SLR framework and categorizing studies by research technique, it contributes uniquely to the academic discourse on digital currencies. The paper provides a critical resource for researchers, lawmakers and stakeholders, enriching the knowledge base on CBDCs and supporting informed decision-making in the context of digital financial innovation.