Browsing by Author "TÜRK, Umut"

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City love and neighbourhood resilience in the urban fabric: A microcosmic urbanometric analysis of Rotterdam
(ELSEVIER, 2022) Kourtit, Karima; Nijkamp, Peter; Wahlstrom, Mia; Türk, Umut; 0000-0002-8440-7048; AGÜ, Yönetim Bilimleri Fakültesi, Ekonomi Bölümü; TÜRK, Umut
Ups and downs in city life are dependent on the citizens' appreciation for their urban ‘home’, in particular the neighbourhood liveability. Taking modern research on urban wellbeing and happiness as a point of departure, this study presents and tests a new methodology for assessing the residents' affection for their local neighbourhood. This approach is inspired by the ‘city love’ concept and seeks to examine and decompose city love through an analytical distinction into the ‘body and soul’ of the city. Using a rich multi-period and geographically detailed database on neighbourhoods in the city of Rotterdam, including distinct social capital indicators for analysing social resilience in urban areas, a microcosmic decomposition of objective and subjective socioeconomic information is carried out. On the basis of geo-science visualisation methods and advanced spatial-econometric techniques for handling neighbourhood autocorrelation effects (‘urbanometrics’), a series of explanatory regression analyses is executed in order to identify and explain the determinants of city love at neighbourhood level in Rotterdam. We find that bonding and bridging social capital are prominent in shaping neighbourhood love and social resilience.
The effect of the COVID-19 on sharing economy: survival analysis of Airbnb listings
(2021) Umut TÜRK; Serap SAP; AGÜ, Yönetim Bilimleri Fakültesi, Ekonomi Bölümü; TÜRK, Umut; SAP, Serap
This research investigates the survival probability of listings in the Airbnb platform during theCOVID-19 period between January-October 2020 in Istanbul. In line with the research aim, Cox'sProportional Hazard Model is adopted to conduct survival analysis, where the physical and spatialattributes of Airbnb listings are used as predictors. Our findings show that while physical attributesshow similarity to previous findings, spatial attributes show substantial differences in the Pre-COVIDand Post-COVID comparison. The contributions of the study have two facets. Theoretically, thisresearch's findings contribute to the current literature by understanding the changing consumerpreferences and identifying the factors that affect Airbnb listings' survival rates during the COVID-19pandemic. The findings may also help practitioners understand changing customers' preferencesduring COVID, especially in terms of locational choices. Moreover, customer feedback's quality andquantity might help the Airbnb hosts to improve their service quality, attract more customers, and bemore resilient under the changing conditions.