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http://dx.doi.org/10.14400/JDC.2021.19.5.001

Determinants of Shortening Job-hunting Period in Platform Labor Market: Analysis by using Web Crawling and Survival Model  

Lee, Jongho (The Center for Economic Catch-up)
Publication Information
Journal of Digital Convergence / v.19, no.5, 2021 , pp. 1-13 More about this Journal
Abstract
The purpose of this research is to analyze how the wage level of new job seekers in the platform labor market affects the period on getting the first job. Recently, the platform gets attention as one of alternatives to solve the increase of unemployment rate. It is important to create quality jobs that we build up a trust between employers and employees in the platform. Previous studies showed that feedback from previous employers is important for solving the information asymmetry problem between those people. However, there is no feedback for new job seekers who have not get the first job. Therefore, we focus on the fact that wages are presented by job seekers rather than employers in the platform, and we will figure out that the low wages of new job seekers may affect the shortening of job-hunting period. For this reason, we use 3,704 job seekers of Freelancer.com. Survival analysis shows that low wages for new job seekers have a significant impact on shortening job-hunting period.
Keywords
Web Crawling; Survival Analysis; Platform Labor Market; Job-hunting Period; Digital;
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  • Reference
1 D. T. Mortensen. (1986). Job search and labor market analysis. In: O. Ashenfelter & R. Layard. (eds) Handbook of Labor Economics Volume 2. North Holland: Elsevier.
2 J. Horton, W. R. Kerr & C. Stanton. (2017). Digital labor markets and global talent flows. In: G. H. Hanson, W. R. Kerr & S. Turner. (eds) High-skilled migration to the United States and its economic consequences. Chicago: University of Chicago Press.
3 D. H. Autor. (2001). Wiring the labor market. The Journal of Economic Perspectives, 15(1), 25-40.   DOI
4 K. S. Choi. (2016). Effects of the Gap between Reservation and Market Wage on the Period to Get First Job. Quarterly Journal of Labor Policy, 16(2), 33-63.   DOI
5 U.S. Department of Labor. (2020). History of Federal Minimum Wage Rates Under the Fair Labor Standards Act, 1938 - 2009.
6 J. Horton, N. Leonard & J. Golden. (2015). Reputation Inflation: Evidence from an Online Labor Market. Working paper NYU.
7 B. Kim. (2016). Worker Characteristics and Search Duration: Duration Model. The Journal of Women and Economics, 13(1), 93-123.
8 S. M. Kim, (2011). Business Failure Prediction Using Survival Analysis and Survival Time Analysis. Journal of SME Finance, Summer, 78-107.
9 S. Szczypinski. (April 19, 2019). What Is the Average Annual Income for a Freelancer in the U.S.? The balance small business.
10 G. Heinze & M. Schemper. (2002). A solution to the problem of separation in logistic regression. Statistics in medicine, 21(16), 2409-241   DOI
11 W. H. Cho. (1995). Youth Unemployment Problem and The Analysis of Unemployment Probability in Korea. Korean Journal of Labor Economics, 18(1), 107-128.
12 B. Kaufman & J. Hotchkiss. (2006). The economics of labor markets. New York: Thomson/South Western.
13 J. Faberman & M. Kudlyak. (2016). What does online job search tell us about the labor market?. Economic perspectives, 40(1), 1-15.
14 C. Codagnone & B. Martens. (2016). Scoping the sharing economy: Origins, definitions, impact and regulatory issues. Institute for Prospective Technological Studies Digital Economy Working Paper 2016/01, JRC100369.
15 S. Banfi & B. Villena-Roldan. (2019). Do high-wage jobs attract more applicants? Directed search evidence from the online labor market. Journal of Labor Economics, 37(3), 715-746.   DOI
16 M. Belot, P. Kircher & P. Muller. (2019). Providing advice to jobseekers at low cost: An experimental study on online advice. The review of economic studies, 86(4), 1411-1447.   DOI
17 C. Kim & J. Jeon. (2011). Development of New Mobile Application Service Concept : Application Store DB Analysis. The Journal of Internet Electronic Commerce Research, 11(2), 257-272.
18 M. Kokkodis, P. Papadimitriou & P. G. Ipeirotis. (2015, February). Hiring behavior models for online labor markets. Proceedings of the Eighth ACM International Conference on Web Search and Data Mining. (pp. 223-232). New York : Association for Computing Machinery.
19 S. K. Rhee. (2010). The Definition of Two-sided Market and Its Conditions. International Telecommunications Policy Review, 17(4), 73-105.
20 T. Eisenmann, G. Parker & M. W. Van Alstyne. (2006). Strategies for two-sided markets. Harvard business review, 84(10), 92.
21 B. C. Greenwald. (1986). Adverse selection in the labour market. The Review of Economic Studies, 53(3), 325-347.   DOI
22 C. Park, H. Kim & J. Han. (2011). Business Strategy for Scenarios in Mobile Application Market : Focusing on the Responding Strategies of Mobile Operators. The Journal of Internet Electronic Commerce Research, 11(2), 75-107.   DOI
23 O. Kassi & V. Lehdonvirta. (2018). Online labour index: Measuring the online gig economy for policy and research. Technological forecasting and social change, 137, 241-248.   DOI
24 S. C. Kuek, C. Paradi-Guilford, T. Fayomi, S. Imaizumi, P. Ipeirotis, P. Pina & M. Singh. (2015). The Global Opportunity in Online Outsourcing. Washington, DC. : ©World Bank.
25 C. Krieger-Boden & A. Sorgner. (2018). Labor market opportunities for women in the digital age. Economics Discussion Papers, No 2018-18, Kiel Institute for the World Economy.
26 M. Mamertino & T. Sinclair. (2019). Migration and Online Job Search: A Gravity Model Approach. Economics Letters, 181, 5-53.
27 A. Benson, A. Sojourner & A. Umyarov. (2020). Can reputation discipline the gig economy? Experimental evidence from an online labor market. Management Science, 66(5), 1802-1825.   DOI
28 E. Brynjolfsson, Y. J. Hu & M. D. Smith. (2006). From niches to riches: Anatomy of the long tail. Sloan Management Review, 47(4), 67-71.
29 E. Brynjolfsson & A. McAfee. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. New York : W.W. Norton & Company.
30 C. Anderson. (2006). The long tail: Why the future of business is selling less of more. London : Hachette Books.
31 H. Ko, D. H. Park & H. B. Jeong. (2019). Deployment of Artificial Intelligence Technology and Law and Economics of Employment Discrimination. Korean Journal of Law and Economics, 16(1), 39-70.   DOI
32 H. S. Farber & R. Gibbons. (1996). Learning and wage dynamics. The Quarterly Journal of Economics, 111(4), 1007-1047.   DOI
33 J. G. Altonji & C. R Pierret. (2001). Employer learning and statistical discrimination. The quarterly journal of economics, 116(1), 313-350.   DOI
34 F. Lange. (2007). The speed of employer learning. Journal of Labor Economics, 25(1), 1-35.   DOI
35 A. Pallais. (2014). Inefficient hiring in entry-level labor markets. American Economic Review, 104(11), 3565-99.   DOI
36 Z. Li, Y. Hong & Z. Zhang. (2018, January). An empirical analysis of the impacts of the sharing economy platforms on the US labor market. Proceedings of the 51st Hawaii International Conference on System Sciences. (pp.1-9).
37 J. Lim. (2017). The Government's Supporting Strategies to the Productive Prosumer Economy for the Successful Transition to the Fourth Industrial Revolution Era: Human Resource Development Perspectives for Solving Job problems. Informatization Policy, 24(2), 87-104.   DOI
38 G. Lazaroiu & D. Rommer. (2017). Digital technologies, labor markets, and economic reputation. Ekonomicko-manazerske spektrum, 11(2), 13-21.
39 F. Bogliacino, V. Cirillo, C. Codagnone & D. Guarascio. (2020). Quantity and Quality of Work in the Platform Economy. In: Zimmermann K. (eds) Handbook of Labor, Human Resources and Population Economics. Springer, Cham.
40 C. O. Bae & J. W. Kim. (2016, May). The Study for Performance Analysis of Ability-based Employment based on NCS. Proceedings of the Korean Academic Association of Business Administration 2016 Summer Conference. (pp. 31-40). Seoul : Korean Academic Association of Business Administration.
41 S. Tadelis. (2016). Reputation and feedback systems in online platform markets. Annual Review of Economics, 8, 321-340.   DOI
42 C. T. Stanton & C. Thomas. (2016). Landing the first job: The value of intermediaries in online hiring. The Review of Economic Studies, 83(2), 810-854.   DOI
43 S. Suri, D. G. Goldstein & W. A. Mason. (2011, August). Honesty in an online labor market. Proceedings of Workshops at the Twenty-Fifth AAAI Conference on Artificial Intelligence. Menlo Park : The AAAI Press.