2 research outputs found

    How To Predict A Pop-Up Store – Developing A Data Based Framework For Digitizing The Location Choice Process And Prototyping At The Case Of St. Gallen (Ch)

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    We target identifying the needs for the fulfillment of location factors of pop-up retailers being determined by their core motivations and retail sector affiliation. We undertake to do both, to qualify, and to quantify their needs to gain at end of the day a profound description of various pop-up retail patterns. Through the use of a mixed-methods approach containing qualitative research through conducting interviews and qualitative content analysis as well as quantitative fulfillment of location factors through data analysis of multiple location data sources like Open Street Map, we try to gain first indications towards a deeper understanding of pop-up location decisions as well as to validate our hypothesis of the existence of pop-up retail patterns. We were able to validate three retail patterns through our qualitative research. Furthermore, we saw differences reflecting the particular motivations of running the ephemeral retail project. Despite our small shown sample of quantitative data for St. Gallen, we figured out the first indications that store density is a suitable indicator to understand pop-up retailers’ locations’ decisions. Nevertheless, there is a need to continue research in both terms, more quantitative data like footfall and financial transactions (turnovers) as well as bigger, more representative samples. Within the undertaken literature review we saw a lack of research in gaining a deeper understanding of the nature of pop-up retail in terms of location needs and how location decisions are made. We present results that may deal as a foundation for upcoming research. Moreover, we contribute to the state of research in patterns of retail location choice through a data-driven approach, which presents reasonable insights into the field of location intelligence of temporary retail

    Carbon Footprint und Carbon Management am Beispiel eines Biomasse-Heizkraftwerkes

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