SHS Web Conf.
Volume 132, 2022Innovative Economic Symposium 2021 – New Trends in Business and Corporate Finance in COVID-19 Era (IES2021)
|Number of page(s)||6|
|Section||New Trends in Business and Corporate Finance in COVID-19 Era|
|Published online||05 January 2022|
- L. Jones, D. Palumbo, D. Brown, Coronavirus: How the pandemic has changed the world economy [online], Available at: https://www.bbc.com/news/business-51706225 (2021) [Google Scholar]
- A. Nadya Septi Nur, L. Lutfi, The influence of risk perception, risk tolerance, overconfidence, and loss aversion towards investment decision making. Journal of Economics, Business, & Accountancy Ventura, 21(3), 401–413 (2019) [CrossRef] [Google Scholar]
- D. Forlani, J. W. Mullins, Perceived risks and choices in entrepreneurs’ new venture decisions. Journal of business Venturing, 15, 305–322 (2000) [CrossRef] [Google Scholar]
- P. Yue, A. Gizem Korkmaz, H. Zhou, Household financial decision making amidst the COVID-19 pandemic. Emerging Markets Finance and Trade, 56(10), 2363–2377 (2020) [CrossRef] [Google Scholar]
- J. Shachat, M. J. Walker, L. Wei, The impact of the Covid-19 pandemic on economic behaviours and preferences: Experimental evidence from Wuhan. ESI Working Paper, 20(33) (2020) [Google Scholar]
- M. Angrisani, M. Cipriani, A. Guarino, R. Kendall, J. Ortiz de Zarate, Risk preferences at the time of COVID-19: an experiment with professional traders and students. FRB of New York Staff Report, 927 (2020) [Google Scholar]
- T. M. Daly, R. Nataraajan, Swapping bricks for clicks: Crowdsourcing longitudinal data on Amazon Turk. Journal of Business Research, 68(12), 2603–2609 (2015) [CrossRef] [Google Scholar]
- M. Buhrmester, T. Kwang, S. D. Gosling, Amazon’s Mechanical Turk: A new source of inexpensive, yet high-quality data? Perspectives on Psychological Science, 6(1), 3–5 (2016) [Google Scholar]
- P. B. Lowry, J. D’Arcy, B. Hammer, G. D. Moody, “Cargo Cult” science in traditional organization and information systems survey research: A case for using nontraditional methods of data collection, including Mechanical Turk and online panels. The Journal of Strategic Information Systems, 25(3), 232–240 (2016) [CrossRef] [Google Scholar]
- S. Banerjee, A. Y. Chua, A theoretical framework to identify authentic online reviews. Online Information Review, 38(5), 634–649 (2014) [CrossRef] [Google Scholar]
- M. Licht, Multiple regression and correlation. In L.G. Grimm & P.R. Yarnold (Eds.), Reading and understanding multivariate statistics, Washington, DC, American Psychological Association, 19–64 (1995) [Google Scholar]
- M. A. Schroeder, J. Lander, S. Levine-Silverman, Diagnosing and dealing with multicollinearity. Western Journal of Nursing Research, 12(2), 75–187 (1990) [Google Scholar]
- Y. Trope, N. Liberman, Construal-level theory of psychological distance. Psychological Review, 117(2), 440–450 (2010) [CrossRef] [Google Scholar]
- T. A. Hallahan, R. W. Faff, M. D. McKenzie, An empirical investigation of personal financial risk tolerance. Financial Services Review-greenwich, 13(1), 57–78 (2004) [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.