This study answers the questions on which factors drive the adoption of AI and MR in the multiplex retail environment and which factors drive consumers’ behavioral responses to the multiplex retail environment.
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This article seeks to contribute to the literature on circular business model innovation in fashion retail. Our research question is which ‘model’—or combination of models—would be ideal as a business case crafting multiple value creation in small fashion retail. We focus on a qualitative, single in-depth case study—pop-up store KLEER—that we operated for a duration of three months in the Autumn of 2020. The shop served as a ‘testlab’ for action research to experiment with different business models around buying, swapping, and borrowing second-hand clothing. Adopting the Business Model Template (BMT) as a conceptual lens, we undertook a sensory ethnography which led to disclose three key strategies for circular business model innovation in fashion retail: Fashion-as-a-Service (F-a-a-S) instead of Product-as-a-Service (P-a-a-S) (1), Place-based value proposition (2) and Community as co-creator (3). Drawing on these findings, we reflect on ethnography in the context of a real pop-up store as methodological approach for business model experimentation. As a practical implication, we propose a tailor-made BMT for sustainable SME fashion retailers. Poldner K, Overdiek A, Evangelista A. Fashion-as-a-Service: Circular Business Model Innovation in Retail. Sustainability. 2022; 14(20):13273. https://doi.org/10.3390/su142013273
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Purpose: The purpose of this study is to assess the evolution of restaurant locations in the city of Hamilton over a 12-year period (1996 to 2008) using GIS techniques. Retail theories such as central place, spatial interaction and principle of minimum differentiation are applied to the restaurant setting. Design/methodology/approach: A database of restaurants was compiled using the NZ yellow pages and contained 981 entries that consisted mainly of location addresses and types of cuisine. This paper focuses on locational patterns only. Findings: A process of geo-coding and clustering enabled the identification of two clustering periods over 12 years for city restaurants, indicating locational patterns of agglomeration within a short walking distance of the CBD and spill over effects to the north of the city. Research limitations/implications: The data do not allow statistical analysis of the variables causing the clustering but offer a visual description of the evolution. Explanations are offered on the possible planning regimes, retail provision and population changes that may explain this evolution. Practical implications: The findings allow identification of land use patterns in Hamilton city and potential areas where new restaurants could be developed. Also, the usefulness of geo-coded data in identifying clustering effects is highlighted. Originality/value: Existing location studies relate mostly to site selection criteria in the retailing industry while few have considered the evolution of restaurant locations in a specific geographic area. This paper offers a case study of Hamilton city and highlights the usefulness of GIS techniques in understanding locational patterns.
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