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COVID-19 pandemisinin nüfus hareketliliği üzerine etkisi: Hareketlilik ve gelir arasındaki ilişkinin analizi

Yıl 2021, Sayı: 79, 7 - 16, 31.12.2021
https://doi.org/10.17211/tcd.971688

Öz

Bu çalışma COVID-19 pandemisinde nüfus hareketliliği ve gelir arasındaki ilişkiyi konu alır. Bu
bağlamda araştırmada gelirin pandemi sürecinde yaşanan hareketlilikte belirleyici olup olmadığı
sorusuna yanıt aranmıştır. Çalışma nicel veri toplama ve analiz araçlarından faydalanılarak
tasarlanmıştır. Hareketlilikte yaşanan değişimin analizinde Google tarafından sunulan altı farklı
kategoriye ilişkin hareketlilik verileri ile Türkiye İstatistik Kurumu (TÜİK) tarafından yayınlanan
gelir verilerinden faydalanılmıştır. Hareketlilik verileri mekânsal otokorelasyon, hareketlilik ve
gelir arasındaki ilişki ise korelasyon analizi kullanarak çözümlenmiştir. Araştırmanın temel bulguları
şu şekildedir: Perakende ve rekreasyon, park ve toplu taşıma kategorilerinde nüfusun
hareketliliği değerlendirmeye alınan dönemde azalmıştır. Buna karşın market ve eczane ile konut
kategorilerinde yaşanan hareketlilik artmıştır. Korelasyon analizi sonuçlarına göre ise perakende
ve rekreasyon, market ve eczane, işyeri ve konut kategorilerinde gelir ve hareketlilik
arasında ilişki bulunur. Gelirin fazla olduğu illerde perakende ve rekreasyon, merkez ve eczane
ile işyerinde yaşanan hareketlilik daha fazla azalmıştır. Gelirin düşük olduğu illerde ise konutta
geçirilen hareketlilik azalmaktadır. Park ve toplu taşıma kategorilerinde yaşanan hareketlilik ile
gelir arasında pozitif ilişki bulunduğu tespit edilmiştir. Bununla birlikte bu ilişki istatistiksel olarak
anlamlı değildir.

Kaynakça

  • Abdulai, A., Tiffere, A., Adam, F., & Kabanunye, M. M. (2021). COVID-19 information-related digital literacy among online health consumers in a low-income country. International Journal of Medical Informatics, 145, 104322. https://doi.org/10.1016/j. ijmedinf.2020.104322
  • Anselin, L. (1995). Local indicators of spatial association-LISA. Geographical Analysis, 27, 93–115
  • Arora, N., Pflumm, S., Rodriguez, L., Robinson, K., Bhargava, S., Charm, T., Tormo S. (2020) Survey: US Consumer Sentiment during the Coronavirus Crisis https://www.mckinsey.com/ business-functions/marketing-and-sales/our-insights/surveyus- consumer-sentiment-during-the-coronavirus-crisis
  • Asfaw, A. A. (2021). The effect of income support programs on job search, workplace mobility and COVID-19: International evidence. Economics & Human Biology, 41, 100997. https://doi. org/10.1016/j.ehb.2021.100997
  • Awad-Núñez, S., Julio, R., Moya-Gómez, B., Gomez, J., & Sastre González, J. (2021). Acceptability of sustainable mobility policies under a post-COVID-19 scenario. Evidence from Spain. Transport Policy, 106, 205-214. https://doi.org/10.1016/j. tranpol.2021.04.010
  • Bozkurt, A. (2020). Koronavirüs (Covid-19) pandemi süreci ve pandemi sonrası dünyada eğitime yönelik değerlendirmeler: Yeni normal ve yeni eğitim paradigması. Açıköğretim Uygulamaları ve Araştırmaları Dergisi, 6(3), 112-142.
  • Brewer, P., & Sebby, A. G. (2021). The effect of online restaurant menus on consumers’ purchase intentions during the COVID-19 pandemic. International Journal of Hospitality Management, 94, 102777. https://doi.org/10.1016/j.ijhm.2020.102777
  • Budak, F., & Korkmaz, Ş. (2020). COVID-19 pandemi sürecine yönelik genel bir değerlendirme: Türkiye örneği. Sosyal Araştırmalar ve Yönetim Dergisi, (1), 62-79.
  • Chakrabarti, S. (2017). How can public transit get people out of their cars? An analysis of transit mode choice for commute trips in Los Angeles. Transport Policy, 54, 80-89. https://doi.org/10.1016/j. tranpol.2016.11.005
  • Cheng, Y., Zhang, J., Wei, W., & Zhao, B. (2021). Effects of urban parks on residents’ expressed happiness before and during the COVID-19 pandemic. Landscape and Urban Planning, 212, 104118. https://doi.org/10.1016/j.landurbplan.2021.104118
  • Chee, W. L., & Fernandez, J. L. (2013). Factors that influence the choice of mode of transport in Penang: A preliminary analysis. Procedia - Social and Behavioral Sciences, 91, 120-127. https:// doi.org/10.1016/j.sbspro.2013.08.409
  • Collins, R. M., Spake, R., Brown, K. A., Ogutu, B. O., Smith, D., & Eigenbrod, F. (2020). A systematic map of research exploring the effect of greenspace on mental health. Landscape and Urban Planning, 201, 103823. https://doi.org/10.1016/j. landurbplan.2020.103823
  • Dalkmann, H., Obika, B., & Geronimo, L. (2020). A call for collective action for international transport stakeholders to respond to the COVID-19 pandemic. High Volume Transport applied research. https://assets.publishing.service.gov.uk/media/5f8b094be- 90e0727cc8d96b0/HVT029.001_COVID-19_Transport_Overview_ Report__1_.pdf
  • Das, S., Boruah, A., Banerjee, A., Raoniar, R., Nama, S., & Maurya, A. K. (2021). Impact of COVID-19: A radical modal shift from public to private transport mode. Transport Policy, 109, 1-11. https:// doi.org/10.1016/j.tranpol.2021.05.005
  • Davis, M., (2007) Gecekondu Gezegeni. (Planet of Slums) Çev: G.Koca. İstanbul: Metis Yayınları.
  • Döker, M.F., Ocak, F. (2020). COVID-19 salgınının Türkiye’deki coğrafi dağılışının izlenmesinde Web CBS kullanımı. Türk Coğrafya Dergisi, 76, 7-18. DOI: 10.17211/tcd.778712
  • Dzhambov, A. M., Browning, M. H., Markevych, I., Hartig, T., & Lercher, P. (2020). Analytical approaches to testing pathways linking greenspace to health: A scoping review of the empirical literature. Environmental Research, 186, 109613. https://doi. org/10.1016/j.envres.2020.109613
  • Eger, L., Komárková, L., Egerová, D., & Mičík, M. (2021). The effect of COVID-19 on consumer shopping behaviour: Generational cohort perspective. Journal of Retailing and Consumer Services, 61, 102542. https://doi.org/10.1016/j.jretconser.2021.102542
  • Ermagun, A., & Samimi, A. (2017). Mode choice and travel distance joint models in school trips. Transportation, 45(6), 1755-1781. https://doi.org/10.1007/s11116-017-9794-y
  • Flaxman, S., Mishra, S., Gandy, A., Unwin, H. J. T., Mellan, T. A., Coupland, H., ... & Bhatt, S. (2020). Estimating the effects of nonpharmaceutical interventions on COVID-19 in Europe. Nature, 584(7820), 257-261.
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Impact of COVID-19 pandemic on population mobility: Analysis of the relationship between mobility and income

Yıl 2021, Sayı: 79, 7 - 16, 31.12.2021
https://doi.org/10.17211/tcd.971688

Öz

This study seeks to explore the relationship between population mobility and income in the
COVID-19 pandemic. In this context, it was questioned in the research whether income is a determinant
in the mobility experienced during the pandemic process. The study was designed
using quantitative data collection and analysis tools. In the analysis of the change in mobility,
the mobility data for six different categories prepared by Google and the income data published
by the Turkish Statistical Institute were used. Mobility data were analyzed using spatial
autocorrelation, and the relationship between mobility and income was analyzed using correlation
analysis. The main results of the study are as follows: The mobility of the population in
the categories of retail and recreation, parks and public transport decreased during the period
that analyzed in this research. On the other hand, the activity in the market, pharmacy and
housing categories increased. According to the results of the correlation analysis, there is a relationship
between income and mobility in the categories of retail and recreation, market and
pharmacy, workplace and housing. In provinces with high income, the mobility experienced in
retail and recreation, center, pharmacy and workplace decreased more. On the other hand, in
provinces with low income, mobility in housing decreases. It has been determined that there is
a positive relationship between the mobility experienced in the park and public transportation
categories and income. However, this relationship is not statistically significant.

Kaynakça

  • Abdulai, A., Tiffere, A., Adam, F., & Kabanunye, M. M. (2021). COVID-19 information-related digital literacy among online health consumers in a low-income country. International Journal of Medical Informatics, 145, 104322. https://doi.org/10.1016/j. ijmedinf.2020.104322
  • Anselin, L. (1995). Local indicators of spatial association-LISA. Geographical Analysis, 27, 93–115
  • Arora, N., Pflumm, S., Rodriguez, L., Robinson, K., Bhargava, S., Charm, T., Tormo S. (2020) Survey: US Consumer Sentiment during the Coronavirus Crisis https://www.mckinsey.com/ business-functions/marketing-and-sales/our-insights/surveyus- consumer-sentiment-during-the-coronavirus-crisis
  • Asfaw, A. A. (2021). The effect of income support programs on job search, workplace mobility and COVID-19: International evidence. Economics & Human Biology, 41, 100997. https://doi. org/10.1016/j.ehb.2021.100997
  • Awad-Núñez, S., Julio, R., Moya-Gómez, B., Gomez, J., & Sastre González, J. (2021). Acceptability of sustainable mobility policies under a post-COVID-19 scenario. Evidence from Spain. Transport Policy, 106, 205-214. https://doi.org/10.1016/j. tranpol.2021.04.010
  • Bozkurt, A. (2020). Koronavirüs (Covid-19) pandemi süreci ve pandemi sonrası dünyada eğitime yönelik değerlendirmeler: Yeni normal ve yeni eğitim paradigması. Açıköğretim Uygulamaları ve Araştırmaları Dergisi, 6(3), 112-142.
  • Brewer, P., & Sebby, A. G. (2021). The effect of online restaurant menus on consumers’ purchase intentions during the COVID-19 pandemic. International Journal of Hospitality Management, 94, 102777. https://doi.org/10.1016/j.ijhm.2020.102777
  • Budak, F., & Korkmaz, Ş. (2020). COVID-19 pandemi sürecine yönelik genel bir değerlendirme: Türkiye örneği. Sosyal Araştırmalar ve Yönetim Dergisi, (1), 62-79.
  • Chakrabarti, S. (2017). How can public transit get people out of their cars? An analysis of transit mode choice for commute trips in Los Angeles. Transport Policy, 54, 80-89. https://doi.org/10.1016/j. tranpol.2016.11.005
  • Cheng, Y., Zhang, J., Wei, W., & Zhao, B. (2021). Effects of urban parks on residents’ expressed happiness before and during the COVID-19 pandemic. Landscape and Urban Planning, 212, 104118. https://doi.org/10.1016/j.landurbplan.2021.104118
  • Chee, W. L., & Fernandez, J. L. (2013). Factors that influence the choice of mode of transport in Penang: A preliminary analysis. Procedia - Social and Behavioral Sciences, 91, 120-127. https:// doi.org/10.1016/j.sbspro.2013.08.409
  • Collins, R. M., Spake, R., Brown, K. A., Ogutu, B. O., Smith, D., & Eigenbrod, F. (2020). A systematic map of research exploring the effect of greenspace on mental health. Landscape and Urban Planning, 201, 103823. https://doi.org/10.1016/j. landurbplan.2020.103823
  • Dalkmann, H., Obika, B., & Geronimo, L. (2020). A call for collective action for international transport stakeholders to respond to the COVID-19 pandemic. High Volume Transport applied research. https://assets.publishing.service.gov.uk/media/5f8b094be- 90e0727cc8d96b0/HVT029.001_COVID-19_Transport_Overview_ Report__1_.pdf
  • Das, S., Boruah, A., Banerjee, A., Raoniar, R., Nama, S., & Maurya, A. K. (2021). Impact of COVID-19: A radical modal shift from public to private transport mode. Transport Policy, 109, 1-11. https:// doi.org/10.1016/j.tranpol.2021.05.005
  • Davis, M., (2007) Gecekondu Gezegeni. (Planet of Slums) Çev: G.Koca. İstanbul: Metis Yayınları.
  • Döker, M.F., Ocak, F. (2020). COVID-19 salgınının Türkiye’deki coğrafi dağılışının izlenmesinde Web CBS kullanımı. Türk Coğrafya Dergisi, 76, 7-18. DOI: 10.17211/tcd.778712
  • Dzhambov, A. M., Browning, M. H., Markevych, I., Hartig, T., & Lercher, P. (2020). Analytical approaches to testing pathways linking greenspace to health: A scoping review of the empirical literature. Environmental Research, 186, 109613. https://doi. org/10.1016/j.envres.2020.109613
  • Eger, L., Komárková, L., Egerová, D., & Mičík, M. (2021). The effect of COVID-19 on consumer shopping behaviour: Generational cohort perspective. Journal of Retailing and Consumer Services, 61, 102542. https://doi.org/10.1016/j.jretconser.2021.102542
  • Ermagun, A., & Samimi, A. (2017). Mode choice and travel distance joint models in school trips. Transportation, 45(6), 1755-1781. https://doi.org/10.1007/s11116-017-9794-y
  • Flaxman, S., Mishra, S., Gandy, A., Unwin, H. J. T., Mellan, T. A., Coupland, H., ... & Bhatt, S. (2020). Estimating the effects of nonpharmaceutical interventions on COVID-19 in Europe. Nature, 584(7820), 257-261.
  • Forster, P., & Ya Tang. (2005). The role of online shopping and fulfillment in the Hong Kong SARS crisis. Proceedings of the 38th Annual Hawaii International Conference on System Sciences. https://doi.org/10.1109/hicss.2005.615
  • Frumkin, H., Bratman, G. N., Breslow, S. J., Cochran, B., Kahn Jr, P. H., Lawler, J. J., Levin, P. S., Tandon, P. S., Varanasi, U., Wolf, K. L., & Wood, S. A. (2017). Nature contact and human health: A research agenda. Environmental Health Perspectives, 125(7), 075001. https://doi.org/10.1289/ehp1663
  • Gargoum, S. A., & Gargoum, A. S. (2021). Limiting mobility during COVID-19, when and to what level? An international comparative study using change point analysis. Journal of Transport & Health, 20, 101019. https://doi.org/10.1016/j.jth.2021.101019
  • Glodeanu, A., Bilal, U., & Tosio, P. G. (2021). Social inequalities in mobility during and following the COVID-19 associated lockdown of the Madrid metropolitan area in Spain. https://doi. org/10.31235/osf.io/apz4e
  • Google (2020) Mobility Reports. https://www.google.com/covid19/ mobility/ (Erişim Tarihi: 03.30.2021)
  • Guthrie, C., Fosso-Wamba, S., & Arnaud, J. B. (2021). Online consumer resilience during a pandemic: An exploratory study of e-Commerce behavior before, during and after a COVID-19 lockdown. Journal of Retailing and Consumer Services, 61, 102570. https://doi.org/10.1016/j.jretconser.2021.102570
  • Günay Aktaş, S. (2020). Küresel sağlıktan sağlık turizmine COVID-19. Türk Coğrafya Dergisi, 76, 107-114. DOI: 10.17211/tcd.816615
  • Günay Aktas, S. Kumtepe, E. G., Kantar, Y. M., Ulukan, I. C., Aydin, S., Aksoy, T., & Er, F. (2019). Improving gender equality in higher education in Turkey. Applied Spatial Analysis and Policy, 12(1), 167-189.
  • Hakim, A., Victory, K., Chevinsky, J., Hast, M., Weikum, D., Kazazian, L., Mirza, S., Bhatkoti, R., Schmitz, M., Lynch, M., & Marston, B. (2021). Mitigation policies, community mobility, and COVID-19 case counts in Australia, Japan, Hong Kong, and Singapore. Public Health, 194, 238-244. https://doi.org/10.1016/j. puhe.2021.02.001
  • Hunter, M. R., Gillespie, B. W., & Chen, S. Y. (2019). Urban nature experiences reduce stress in the context of daily life based on salivary biomarkers. Frontiers in Psychology, 10. https://doi. org/10.3389/fpsyg.2019.00722
  • Iio, K., Guo, X., Kong, X., Rees, K., & Bruce Wang, X. (2021). COVID- 19 and social distancing: Disparities in mobility adaptation between income groups. Transportation Research Interdisciplinary Perspectives, 10, 100333. https://doi.org/10.1016/j. trip.2021.100333
  • Kanda, W., & Kivimaa, P. (2020). What opportunities could the COVID- 19 outbreak offer for sustainability transitions research on electricity and mobility? Energy Research & Social Science, 68, 101666. https://doi.org/10.1016/j.erss.2020.101666
  • Kervankıran, İ., Bağmancı, M.F. (2020). Bildiğimiz turizmin sonu mu? COVID-19’un Türkiye’deki turizm hareketliliğine etkisi. Türk Coğrafya Dergisi, 76, 19-32. DOI: 10.17211/tcd.811302
  • Ko, J., Lee, S., & Byun, M. (2019). Exploring factors associated with commute mode choice: An application of city-level general social survey data. Transport Policy, 75, 36-46. https://doi.org/ 10.1016/j.tranpol.2018.12.007
  • Kim, R. Y. (2020). The impact of COVID-19 on consumers: Preparing for digital sales. IEEE Engineering Management Review, 48(3), 212-218. https://doi.org/10.1109/emr.2020.2990115
  • Kim, J., & Kwan, M. (2021). The impact of the COVID-19 pandemic on people’s mobility: A longitudinal study of the U.S. from march to September of 2020. Journal of Transport Geography, 93, 103039. https://doi.org/10.1016/j.jtrangeo.2021.103039
  • Kim, S., Lee, S., Ko, E., Jang, K., & Yeo, J. (2021). Changes in car and bus usage amid the COVID-19 pandemic: Relationship with land use and land price. Journal of Transport Geography, 96, 103168. doi:10.1016/j.jtrangeo.2021.103168
  • Kirk, C. P., & Rifkin, L. S. (2020). I’ll trade you diamonds for toilet paper: Consumer reacting, coping and adapting behaviors in the COVID-19 pandemic. Journal of Business Research, 117, 124- 131. https://doi.org/10.1016/j.jbusres.2020.05.028
  • Lee, W. D., Qian, M., & Schwanen, T. (2021). The association between socioeconomic status and mobility reductions in the early stage of England’s COVID-19 epidemic. Health & Place, 69, 102563. https://doi.org/10.1016/j.healthplace.2021.102563
  • Liu, Y., Hong, Z., & Liu, Y. (2016). Do driving restriction policies effectively motivate commuters to use public transportation? Energy Policy, 90, 253-261. https://doi.org/10.1016/j. enpol.2015.12.038
  • Orak, N. H., & Ozdemir, O. (2021). The impacts of COVID-19 lockdown on PM10 and SO2 concentrations and association with human mobility across Turkey. Environmental Research, 197, 111018. https://doi.org/10.1016/j.envres.2021.111018
  • Porter, G., Murphy, E., Adamu, F., Dayil, P., De Lannoy, A., Han, S., Mansour, H., Dungey, C., Ahmad, H., Maskiti, B., S, C., & Van der Weidje, K. (2021). Women’s mobility and transport in the peripheries of three African cities: Reflecting on early impacts of COVID-19. Transport Policy, 110, 181-190. https://doi.org/ 10.1016/j.tranpol.2021.05.025
  • Predmore, C. E., Rovenpor, J., Manduley, A. R., & Radin, T. (2007). Shopping in an age of terrorism. Competitiveness Review, 17(3), 170-180. https://doi.org/10.1108/10595420710833570
  • Rice, W. L., & Pan, B. (2021). Understanding changes in park visitation during the COVID-19 pandemic: A spatial application of big data. Wellbeing, Space and Society, 100037. https://doi. org/10.1016/j.wss.2021.100037
  • Rung, A. L., Broyles, S. T., Mowen, A. J., Gustat, J., & Sothern, M. S. (2010). Escaping to and being active in neighbourhood parks: Park use in a post-disaster setting. Disasters, 35(2), 383-403. https://doi.org/10.1111/j.1467-7717.2010.01217.x
  • Saha, J., Mondal, S., & Chouhan, P. (2021). Spatial-temporal variations in community mobility during lockdown, unlock, and the second wave of COVID-19 in India: A data-based analysis using Google’s community mobility reports. Spatial and Spatio-temporal Epidemiology, 100442. doi:10.1016/j.sste.2021.100442
  • Seargeant, P., & Tagg, C. (2018). Critical digital literacy education in the ‘Fake news’ era. Digital Literacy Unpacked, 179-190. https:// doi.org/10.29085/9781783301997.015
  • Shao, W., Xie, J., & Zhu, Y. (2021). Mediation by human mobility of the association between temperature and COVID-19 transmission rate. Environmental Research, 194, 110608. https://doi.org/ 10.1016/j.envres.2020.110608
  • Sharma, G. D., Thomas, A., & Paul, J. (2021). Reviving tourism industry post-COVID-19: A resilience-based framework. Tourism Management Perspectives, 37, 100786. https://doi. org/10.1016/j.tmp.2020.100786
  • Shokouhyar, S., Shokoohyar, S., Sobhani, A., & Gorizi, A. J. (2021). Shared mobility in post-COVID era: New challenges and opportunities. Sustainable Cities and Society, 67, 102714. https://doi. org/10.1016/j.scs.2021.102714
  • Tepanosyan, G., Sahakyan, L., Zhang, C., & Saghatelyan, A. (2019). The application of local Morans “I” to identify spatial clusters and hot spots of PB, Mo and ti in urban soils of Yerevan. Applied Geochemistry, 104, 116-123. doi:10.1016/j. apgeochem.2019.03.022
  • Tong, Z., Xie, Y., & Xiao, H. (2021). Effect of CSR contribution timing during COVID-19 pandemic on consumers’ prepayment purchase intentions: Evidence from hospitality industry in China. International Journal of Hospitality Management, 97, 102997. https://doi.org/10.1016/j.ijhm.2021.102997
  • Trias-Llimós, S., Riffe, T., & Bilal, U. (2020). Monitoring life expectancy levels during the COVID-19 pandemic: Example of the unequal impact of the first wave on Spanish regions. PLOS ONE, 15(11), e0241952. https://doi.org/10.1371/journal.pone.0241952
  • TÜİK. (2020). İstihdam Edilenlerin Yıllar ve Cinsiyete Göre İktisadi Faaliyet Kolları (https://data.tuik.gov.tr/Kategori/GetKategori? p=istihdam-issizlik-ve-ucret-108&dil=1)
  • Valentino-DeVries, L. ve Dance, G.J.X. (2020). Location data says it all: staying at home during Coronavirus is a luxury. The New York Times. https://www.nytimes.com/interactive/2020/04/03/ us/coronavirus-stay
  • WHO. (2021). WHO Coronavirus (COVID-19) Dashboard. https://covid19. who.int/
  • Yabe, T., Tsubouchi, K., Fujiwara, N., Wada, T., Sekimoto, Y., & Ukkusuri, S. V. (2020). Non-compulsory measures sufficiently reduced human mobility in Tokyo during the COVID-19 epidemic. Scientific Reports, 10(1). https://doi.org/10.1038/s41598-020-75033-5
  • Yacchirema, D., & Chura, A. (2021). SafeMobility: An iot- based system for safer mobility using machine learning in the age of COVID- 19. Procedia Computer Science, 184, 524-531. https://doi. org/10.1016/j.procs.2021.03.066
  • Zhang, C., Luo, L., Xu, W., & Ledwith, V. (2008). Use of local Moran’s I and GIS to identify pollution hotspots of PB in urban soils of Galway, Ireland. Science of The Total Environment, 398(1-3), 212-221. doi:10.1016/j.scitotenv.2008.03.011
  • Zhou, Y., Xu, R., Hu, D., Yue, Y., Li, Q., & Xia, J. (2020). Effects of human mobility restrictions on the spread of COVID-19 in Shenzhen, China: A modelling study using mobile phone data. The Lancet Digital Health, 2(8), e417-e424. https://doi.org/10.1016/ s2589-7500(20)30165-5
  • Zoğal, V., Domènech, A., & Emekli, G. (2020). Stay at (which) home: Second homes during and after the COVID-19 pandemic. Journal of Tourism Futures. https://doi.org/10.1108/jtf-06-2020-0090
Toplam 61 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Beşeri Coğrafya
Bölüm Araştırma Makalesi
Yazarlar

Öznur Akgiş İlhan 0000-0001-7224-8353

Yayımlanma Tarihi 31 Aralık 2021
Kabul Tarihi 13 Ekim 2021
Yayımlandığı Sayı Yıl 2021 Sayı: 79

Kaynak Göster

APA Akgiş İlhan, Ö. (2021). COVID-19 pandemisinin nüfus hareketliliği üzerine etkisi: Hareketlilik ve gelir arasındaki ilişkinin analizi. Türk Coğrafya Dergisi(79), 7-16. https://doi.org/10.17211/tcd.971688

Yayıncı: Türk Coğrafya Kurumu