Selling Platforms - Boston University...Selling Platforms Hemant K. Bhargava UC Davis with Olivier Rubel Platforms Symposium, Boston, July 2016 Hemant K. Bhargava UC Davis 07/14/2016

Selling Platforms

Hemant K. Bhargava

UC Davis

with Olivier Rubel

Platforms Symposium, Boston, July 2016

Hemant K. Bhargava UC Davis 07/14/2016 Selling Platforms 1 / 13

“SELLING” PLATFORMS

I exciting part of economy and society

I some grow virally, due to network effects, many must be “sold”

I single-sided network goods: e.g., Kyruus

I two-sided goods: e.g., OpenTable, American Well, CreditKarma

I “selling” is fraught with uncertainty, moral hazard ... managed via

risk-sharing compensation plans (commission rate)

I NE alter rewards, productivity and risk exposure of selling agent

I what is the net influence on plan design?

I how should network and platform firms manage sales agents?


“SELLING” PLATFORMS

I exciting part of economy and society

I some grow virally, due to network effects, many must be “sold”

I single-sided network goods: e.g., Kyruus

I two-sided goods: e.g., OpenTable, American Well, CreditKarma

I “selling” is fraught with uncertainty, moral hazard ... managed via

risk-sharing compensation plans (commission rate)

I NE alter rewards, productivity and risk exposure of selling agent

I what is the net influence on plan design?

I how should network and platform firms manage sales agents?


BACKGROUND AND RESEARCH QUESTIONS

I platforms need to be “sold” (too)

I salesforce management literature: principal-agent model - does not

recognize role of network effects

I our research: impact of NE on

I mix of guaranteed and performance-based incentives?

I risk and reward sharing between firm and agent?

I how should firm respond to externalities created by NE


BACKGROUND AND RESEARCH QUESTIONS

I platforms need to be “sold” (too)

I salesforce management literature: principal-agent model - does not

recognize role of network effects

I our research: impact of NE on

I mix of guaranteed and performance-based incentives?

I risk and reward sharing between firm and agent?

I how should firm respond to externalities created by NE


RESULTS AND INSIGHTS

I network effects exert externalities on sales agent: increase both mean

and variance of sales (⇒ compensation risk)

I spectrum of influence, depending on nature of network effects

I one-sided (direct) vs. two-sided (indirect) NE

I which side to meter for commission

I one vs. two agents

I firm’s ability to leverage network effects depends on balance between

# externalities vs. # instruments to manage them.


CONCEPTUAL FRAMEWORK AND BENCHMARK CASE

compensation design without network effects

I agent’s influence on sales: Q = V + βw + ε

V=base sales; β=agent’s productivity; ε ≈ N(0, σ2)

I risk-averse agent, earns ω(w) = α0+α1Q, picks effort level w∗

(max. U(ω(Q), w) = −e−ρ(ω(Q)−C(w)) ≥ R

)⇒ w∗ = βα1

I firm designs (α0, α1) to max. E[Π] = E[Q]− (α0+α1E[Q])

⇒ α∗1 =

β2

β2+ρσ2; Λ0 =

α1E[Q]

α0+α1E[Q]=

2β2

β2+ρσ2β4+V (β2+ρσ2)

β4+2R(β2+ρσ2)







(max. U(ω(Q), w) = −e−ρ(ω(Q)−C(w)) ≥ R

)⇒ w∗ = βα1


⇒ α∗1 =

β2

β2+ρσ2; Λ0 =

α1E[Q]

α0+α1E[Q]=

2β2


β4+2R(β2+ρσ2)







(max. U(ω(Q), w) = −e−ρ(ω(Q)−C(w)) ≥ R

)⇒ w∗ = βα1


⇒ α∗1 =

β2

β2+ρσ2; Λ0 =

α1E[Q]

α0+α1E[Q]=

2β2


β4+2R(β2+ρσ2)


SELLING ONE-SIDED NETWORK GOODS

direct network effects, intensity η

I with Q = V + βw + ηQe + ε, and rational expectations,

q =V + βw

1− η+

ε

1− η; η increases mean AND volatility

I η makes agent more productive, puts in more work, w∗ = β α11−η

and has more compensation risk, Var(ω(q)) = α21

σ2

(1−η)2

how to adjust commission rate and reward structure?


SELLING NETWORK GOODS: RESULTS

I η has no effect on commission rate, α∗1 = β2

β2+ρσ2

∵ costs (risk-disutility) and gains (compensation) both ≈ α21

(1−η)2

I firm takes more risk; more of agent’s compensation as fixed salary

0.3 0.4 0.5 0.6 0.7

0.0

0.4

0.8

η

total compensation

revenues

performance based incentives

total cash compensation

I yet gives agent a greater share of earnings (... net profit increases)


SELLING NETWORK GOODS: RESULTS

I η has no effect on commission rate, α∗1 = β2

β2+ρσ2

∵ costs (risk-disutility) and gains (compensation) both ≈ α21

(1−η)2

I firm takes more risk; more of agent’s compensation as fixed salary

0.3 0.4 0.5 0.6 0.7

0.0

0.4

0.8

η

total compensation

revenues

performance based incentives

total cash compensation

I yet gives agent a greater share of earnings (... net profit increases)


SELLING TWO-SIDED NETWORK GOODS (B,S)

cross-market network effects, intensity ηb, ηsI agent hired to recruit side S participants, paid based on S sales

Qb = Vb + ηbQs + εb

Qs = Vs + ηsQb + εs .

I similar to network goods, agent works more, w∗ = β α11−ηbηs

and has more compensation risk, = f (ηb, ηs)

how to adjust commission rate and reward structure?


SELLING TWO-SIDED NETWORK GOODS: RESULTS

α∗1 =

β2

β2+ρ(σ2s +σ2bη

2s

) ; Λ∗2 = 2

(Vs+Vbηs)(1−ηbηs)

β2+

2β2

β2+ρ(σ2s +σ2bη2s )

I ηb behaves like η ! (no impact on α∗1) but α∗

1 varies with ηs

to internalize externality (agent not rewarded for Qb which ηs affects)

I high ηb is good for firm (like η), but high ηs may not be!

∵ ηs affects Qb, not accounted for in agent’s compensation

too many externalities, too few ways to manage the effects



α∗1 =

β2

β2+ρ(σ2s +σ2bη

2s

) ; Λ∗2 = 2


β2+

2β2



1 varies with ηs







α∗1 =

β2

β2+ρ(σ2s +σ2bη

2s

) ; Λ∗2 = 2


β2+

2β2



1 varies with ηs






TWO-SIDED INCENTIVES FOR TWO-SIDED GOODS?

I hire agent to recruit side S , but pay him also for B sales!

ω(qs , qb) = α0 + α1qs + α2qb; w∗ = βα1 + α2ηb1− ηbηs

I higher ηb, ηs ⇒ higher commission rate; α∗1 = 1

(1−ηsηb)(1+ρσ2s )

I “pay to play” ... α∗2 = −α∗

1ηs

I firm is better off with stronger network effects (both ηb and ηs)

second metric ⇒ better tuning for multiple externalities








1ηs










1ηs




MUTLIPLE AGENTS FOR MULTIPLE TERRITORIES ?

I agents (i = 1, 2) exert indirect externality on each other, because

participation is fueled by overall network size

Qi = V + βiwi + η (Qe1 + Qe

2 ) + εi

Qsi = Vs + ηsQb + βiwi + εsi .

I one-sided network goods: η does impact optimal commission rate

(firm must use α∗1 to manage externalities across agents)

I two-sided goods: ηb now impacts α∗1


SUMMARY: IMPACT OF NETWORK EFFECTS ON DESIGN

One Agent Two Agents

Traditional Good β2

β2+ρσ2β2

β2+ρσ2

Network Good β2

β2+ρσ2β2(1−η)

β2(1−η)2+ρ(1−2(1−η)η)σ2

Platform Good β2

β2+ρ(σ2s+σ

2bη

2s )

β2(1−ηbηs)β2(1−ηbηs)2+ρ(σ2

s (1−ηbηs)2+η2s (σ2s η

2b+σ

2b))

optimal commission rate α∗1


CONCLUSION AND GENERAL INSIGHTS

I network effects create externalities on selling outcomes and risks

I compensation plan design must account for network effects,

in spectrum of ways depending on type of network good

I firm must deploy suitable number of incentives, and in suitable ways,

to manage multiple externalities


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Selling Platforms - Boston University...Selling Platforms Hemant K. Bhargava UC Davis with Olivier Rubel Platforms Symposium, Boston, July 2016 Hemant K. Bhargava UC Davis 07/14/2016