makers as it will allow them to better
understand whom the laws and regulations that shape the gig-economy
The effect of gig-economy participation on long-term career outcomes
is particularly unclear. A defining attribute of gig-economy jobs is that opportunities for “advancement” within
the firm are limited. These jobs might
therefore stagnate workers’ career
progressions, particularly if the gig-economy job requires the worker to
make capital investments, such as the
purchase of an automobile, which may
require debt-based financing. At the
same time, job flexibility may allow
the worker to pursue other opportunities outside the gig-economy, such as
education, which would allow her to
improve career outcomes over the long
term. Which of these effects dominates, and for whom, is an important
opportunity for future research.
The volume of open questions in this
space implies the presence of a substantial blind-spot for practitioners
and policymakers alike. It is not yet
clear how the gig-economy influences
social welfare, or how much total surplus is generated by these platforms.
Although consumers appear to benefit
from reduced prices, 5 media accounts
have repeatedly pointed out that working in these markets can have important drawbacks.c Understanding the
implications of this new form of organizing is critical for scholars from
many academic traditions. We therefore strongly urge researchers to consider these and other research questions at the confluence of business,
technology, and society.
1. Abhishek, V., Guajardo, J. A., and Zhang, Z. Business
models in the sharing economy: Manufacturing
durable goods in the presence of peer-to-peer rental
markets. 2016; http://bit.ly/2pGF4nv.
2. Brazil, N. and Kirk, D.S. Uber and metropolitan traffic
fatalities in the United States. American Journal of
3. Burtch, G., Carnahan, S., and Greenwood, B.N. Can you
gig it? An empirical examination of the gig-economy
and entrepreneurial activity. (2017); http://bit.
4. Chen, M. K. and Sheldon, M. Dynamic pricing in a labor
market: Surge pricing and flexible work on the Uber
platform. (Mimeo, UCLA), 2015.
5. Cohen, P. Using Big Data to Estimate Consumer
Surplus: The Case of Uber. National Bureau of
Economic Research, 2016.
6. Cohen, M. and Sundararajan, A. Self-regulation and
innovation in the peer-to-peer sharing economy.
U. Chi. L. Rev. Dialogue 82 (2015), 116.
7. Cusumano, M.A. How traditional firms must compete
in the sharing economy. Commun. ACM 58, 1 (Jan.
8. Cusumano, M.A. Platform wars come to social media.
Commun. ACM 54, 4 (Apr. 2011), 31–33.
9. Edelman, B. and Luca, M. Digital discrimination: The
case of Airbnb.com. Harvard Business School NOM
Unit Working Paper (14-054), (2014)
10. Edelman B.G., Luca, M., and Svirsky, D. Racial
discrimination in the sharing economy: Evidence from
a field experiment. Harvard Business School NOM Unit
Working Paper, (16-069), 2015.
11. Greengard, S. Smart transportation networks drive
gains. Commun. ACM 58, 1 (Jan. 2015), 25–27.
12. Greenwood, B.N. and Wattal, S. Show me the way to
go home: An empirical investigation of ride sharing and
alcohol-related motor vehicle fatalities. MIS Quarterly
41, 1 (Jan. 2017), 163–187.
13. Hagiu, A. Strategic decisions for multisided platforms.
MI T Sloan Management Review 55, 2 (2014), 71.
14. Hall, J.V. and Krueger, A. B. An analysis of the labor
market for Uber’s driver-partners in the United States.
15. Ipeirotis, P.G. Demographics of mechanical turk. 2010;
16. Katz, L. F. and Krueger, A. B. The rise and nature of
alternative work arrangements in the United States,
1995–2015 (2016); http://bit.ly/2pSZUuX
17. Malhotra A. and Van Alstyne, M. The dark side of the
sharing economy… and how to lighten it. Commun.
ACM 57, 11 (Nov. 2014), 24–27.
18. Scheiber, N. How Uber uses psychological tricks to
push its drivers’ buttons. The New York Times (Apr.
19. Telles, R. Digital matching firms: A new definition in
the “sharing economy” space. U.S. Department of
Commerce Economics and Statistics Administration,
20. Zervas, G., Proserpio, D., and Byers, J. The rise of the
sharing economy: Estimating the impact of Airbnb
on the hotel industry. Boston University School of
Management Research Paper (2013–16), 2015.
21. Zhang, S., et al. Professional versus amateur images:
Investigating differential impact on Airbnb property
demand. In Proceedings of the Conference on
Information Systems and Technology, 2016.
22. Zhu, F. and Furr, N. Products to platforms: Making the
leap. Harvard Business Review 94, 4 (2016), 18.
Seth Carnahan ( email@example.com) is the Sanford R.
Robertson Assistant Professor in Business Administration
in the Ross School of Business at the University of
Gordon Burtch ( firstname.lastname@example.org) is an assistant
professor of Information and Decision Sciences at the
University of Minnesota Carlson School of Management.
Brad N. Greenwood ( email@example.com) is
an assistant professor of Management Information
Systems and the Richard J. Fox Faculty Fellow at Temple
University’s Fox School of Business.
Copyright held by author.
Which of these
and for whom,
is an important
I3D ‘17: Symposium on
Interactive 3D Graphics
San Francisco, CA,
Contact: Kenny Mitchell,
HRI ‘17: ACM/IEEE
International Conference on
Contact: Bilge Dincer Mutlu,
CHIIR ‘17: Conference on
Human Information Interaction
Contact: Ragnar Nordlie,
IUI’17: 22nd International
Conference on Intelligent User
Contact: George Angelos
TAU ‘17: ACM International
Workshop on Timing Issues in
the Specification and Synthesis
of Digital Systems,
Bay Area, CA,
Contact: Qiuyang Wu,
ISPD ‘17: International
on Physical Design,
Contact: Mustafa Ozdal,
TEI ‘17: 10th International
Conference on Tangible,
Embedded, and Embodied
Contact Phone: 81-467-32-7941