institutional overlap: platform rules and government ... wesley.pdf · institutional overlap •...
TRANSCRIPT
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Institutional Overlap:
Platform Rules and Government Regulation
Wesley Wu-Yi Koo
June 2019
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Institutions & Institutional Constituents
Institutions: structures that govern the behavior of individuals & organizations; rules that constrain opportunism and facilitate exchange (Scott 1987).
An institutional constituent supports an institution and exerts conformity pressures on market actors (Oliver 1991, 1992).
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Institution
Constituent
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Theoretical Puzzle
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Theoretical Puzzle
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Theoretical Puzzle
Institutional
Overlap
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Theoretical Puzzle
Institutional
Overlap
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Theoretical Puzzle
vs.Institutional
Overlap
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Research Question
How do market actors respond to institutional overlap?
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BACKGROUND
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Government Regulation & Digital Platforms
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Government Regulation & Digital Platforms
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Government Regulation & Digital Platforms
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Institutional Overlap
• Both the private constituent (the platform) and the public constituent (the government) can regulate seller behavior.
• Institutional overlap: both constituents exert a similar institutional demand on sellers (e.g., “protect data privacy”, “don’t sell counterfeits”).
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Chinese Government & Digital Platforms: Censorship
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Chinese Government & Digital Platforms:Censorship
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Chinese Government & Digital Platforms:Consumer Rights Protection
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Chinese Government & Digital Platforms:Consumer Rights Protection
• Worked with Alibaba & JD to crack down on counterfeit products.
• Incentive differences between local and central governments.
• 13th Five Year Plan: to develop standardized regulations for digital platforms and the “new economy”.
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Research Question
How do market actors respond to institutional overlap?
institutional overlap = platform regulation X government regulation
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HYPOTHESES
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Research on private regulation
• Private constituents can provide and enforce private regulations, e.g. platform rules, to constrain opportunistic behaviors by market actors (Büthe 2010; King &
Lenox 2000).
• A legal/government presence in private regulations generally creates more coercive power (Oliver 1991).
• Example: INPO and NRC’s monitoring of nuclear power plants (Rees 1997; Reid & Toffel 2009).
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H1. Relative to platform-only rules, platform rules with government regulation will be associated with a lower transgression tendency among sellers.
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seller
transgression_
government
regulation in
platform rule
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Rule details
• When facing a detailed issue, actors are likely to use simplified mental models to guide thinking (Gary & Wood 2011;
Gavetti & Levinthal 2000).
• Popular mental models associated with the government: incompetence and technological inadequacy to work with technology (Malesky & Taussig 2017; Nye 1997; Pasquale 2015).
—> For complex platform rules, the negative perceptions of the government will be accentuated in the minds of sellers.
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H2. The mitigating effect of government regulation on seller transgression will be less pronounced for highly detailed rules.
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seller
transgression_
government
regulation in
platform rule
rule details
_
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METHODS
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Survey Experiment
Online questionnaire answered by 3,000 Chinese e-commerce sellers in December, 2017.
Six different vignettes (500 seller respondents per vignette) systematically vary the description of the platform rule to elicit sellers’ responses.
Advantages of a survey experiment (Atzmüller & Steiner 2010; Finch
1987): • embed respondents in a realistic context;• high internal validity;• manipulation of multiple layers of treatments, e.g.
government regulation & rule complexity.
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Survey Experiment
low
complexity
moderate
complexity
high
complexity
with gov.
regulationVignette A Vignette B Vignette C
without gov.
regulationVignette D Vignette E Vignette F
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Survey Experiment
with government regulation
without government regulation
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Survey Experiment
high details
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Survey Experiment
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Measures: Outcome Variable
A seller’s transgression tendency:
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Measures: Predictors
Treatments/manipulations:
• GovReg: Read platform rule mentioning government regulation
• Rule Complexity: low, moderate, high complexity.
Control Variables:
• Seller Age, Seller Gender (1=male, 2=female), Seller Education.
• Store Monthly Sales (ordinal), Store Age.
• Whether seller has Worked in Government before.
• Urban-ness of store location.
• Product Category fixed effects, Prefecture fixed effects.
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Model Specification
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RESULTS
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Government regulation ~ less transgression
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Government regulation ~ less transgression
DV =
Switch Products
DV =
Switch Part of
Products
DV =
Subpar
Quality
DV =
Non-existent
Product
DV =
All OK
DV =
None OK
log(Age) 0.439
(0.397)
0.394
(0.363)
1.011**
(0.409)
0.847**
(0.399)
1.381***
(0.392)
-1.186***
(0.245)
Gender -0.747***
(0.158)
-0.518***
(0.142)
-0.485***
(0.161)
-0.702***
(0.158)
0.578***
(0.163)
0.254***
(0.098)
Sales 0.075
(0.061)
0.169***
(0.057)
0.209***
(0.064)
0.247***
(0.061)
-0.299***
(0.066)
0.010
(0.039)
Store Age -0.035
(0.032)
-0.033
(0.029)
-0.074**
(0.034)
-0.089***
(0.033)
0.023
(0.029)
0.028
(0.019)
Worked in
Government0.670***
(0.232)
0.534**
(0.221)
0.907***
(0.227)
0.666***
(0.227)
0.710***
(0.248)
-0.685***
(0.163)
GovReg-0.341**
(0.146)
-0.305**
(0.135)
-0.260*
(0.151)
-0.384**
(0.146)
0.066
(0.152)
0.224**
(0.093)
Logistic regressions. Two tailed tests: *p<0.1; **p<0.05; ***p<0.01. Standard errors in parentheses.
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Rule details dampen the benefit of government regulation
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Rule details dampen the benefit of government regulation
DV =
Switch
Products
DV =
Switch Part
of Products
DV =
Subpar
Quality
DV =
Non-existent
Product
DV =
All OK
DV =
None OK
All controls Yes Yes Yes Yes Yes Yes
GovReg -0.341**
(0.146)
-0.305**
(0.135)
-0.260*
(0.151)
-0.384**
(0.146)
0.066
(0.152)
0.224**
(0.093)
High Details -0.271
(0.251)
-0.317
(0.224)
-0.543**
(0.257)
-0.562**
(0.246)
0.072
(0.267)
0.208
(0.159)
High Details X
GovReg
0.490
(0.369)
0.749**
(0.325)
0.966***
(0.364)
0.835**
(0.362)
-0.012
(0.372)
-0.507**
(0.227)
Logistic regressions. Two tailed tests: *p<0.1; **p<0.05; ***p<0.01. Standard errors in parentheses.
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IMPLICATIONS
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Theoretical & Policy Implications
Institutional overlap:
• Having the support of multiple constituents has nuanced effects; additional support could hamper an institution.
A new approach toward platform regulation:
• Depending on the circumstance, a platform should purposively highlight/hide the role of government regulation.
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AsiaEurope Middle East| |
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Appendix
• Mechanism: general incompetence vs. technological inadequacy
• Evidence from panel data: police-Taobao joint operation.
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Mechanism: general incompetence vs.technological inadequacy
Coefficients on High Details X
GovReg
Switch
ProductsSwitch Part
Subpar
Quality
Non-existent
Products
Sellers who were
entrepreneurs offline
(N = 658)
-0.494
(1.144)
1.822**
(0.891)
1.113
(1.004)
1.944**
(0.974)
Sellers who were not
entrepreneurs offline
(N = 2,342)
0.424
(0.415)
0.668*
(0.383)
0.899**
(0.416)
0.631
(0.428)
Sellers who worked in IT
(N = 1,016)
0.633
(0.725)
1.751***
(0.597)
0.907
(0.671)
1.148*
(0.617)
Sellers who did not work
in IT
(N = 1,984)
0.319
(0.485)
0.334
(0.451)
0.910*
(0.472)
1.038**
(0.515)
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When there is real enforcement threat:police-Taobao joint operation in 2014
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