George Mason University February 2009

Transcription

1 Cheryl Druehl George Mason University February 2009

2 Open Innovation Chesborough's (2003) book Open Innovation identifies open innovation as distinct from closed innovation. Closed takes place entirely within the firm. Open recognizes that others may have specialized expertise in particular areas. a paradigm that assumes that firms can and should use external ideas as well as internal ideas, and internal and external paths to market... (p. xxiv)

3 R&D

4 Benefits of Brokered Innovation Contests Contest Competition induced among solvers Reduces risk to seeker Open Access to broad network of solvers Increases capacity of idea generation/testing Broker Independent 3 rd party provides trust

5 Research Questions Part 1: Why do people participate in InnoCentive? Part 2: Knowing this, how can innovation brokers better design their processes and services?

6 Related Literature OSS Motivation for participation (e.g., Lerner and Tirole, 2002; Shah, 2006; Roberts et al., 2006) Largely empirical a notable exception is a DP model by Sauer (2007) Economics Contest design (Gradstein, 1995; Che and Gale, 2003) Prize literature (e.g., Lazear and Rosen 1981) Economics and Psychology the quest for status and how that motivates individuals Frank, 1985, Choosing the Right Pond Loch and Wu, 2005 Loch et al., 2000 Basu, 1989 Congleton, 1989

7 Related Literature (continued) Open Innovation Terwiesch and Xu, 2008 Erat and Krishnan, 2008 Lakhani et al., 2007

8 Motivations from InnoCentiveBios of Recent Winners InnoCentiveoffers an attractive platform for Indian scientists to solve scientific challenges from world-class companies and to be recognized for their expertise. InnoCentiveoffers an exciting opportunity to the industry and researchers. Publicity for other work/consulting /startups Looking for job Suggesting solutions is a great service. When it is rewarded, it is a great GIFT. InnoCentiveprovides an excellent opportunity to channelize your knowledge & experience to the targeted receiver. I have designed products for 43 years and have concurrently taught industrial design for 33 years. I spend my time designing and developing products that are of interest to me and that serve people with special needs such as the aged and individuals with physical and/or cognitive impairments. I no longer seek clients. I do continue to observe our culture and world for opportunities where design can make a significant difference.

9 Brokered innovation contests (BIC) differ from OSS, Lead User (LU) innovation OSS 1. Business need is often a motivator 2. No direct financial incentives 3. Reciprocity LU 1. User need is the motivator 2. No direct financial incentives 3. Reciprocity 4. Status and career concerns although a theoretical reason, not found in empirical results 5. Output is privately 5. Output is a public good owned by company BIC 1. Solver motivations differ 2. Direct financial incentives 3. Arms-length 4. Status and career concerns matter Lakhani et al. (2007) 5. Output is privately owned by seeker

10 Utility from participation Lerner and Tirole(2002) identify reasons for OSS participation: Immediate cost opportunity cost of time/effort Immediate benefit improvement in work product (need argument) or fun (hobbyist) Future benefit Signaling incentive consisting of career concerns and ego gratification BIC case: Immediate cost opportunity cost of time/effort Immediate benefit Reward (if win) and fun (hobbyist) Future benefit Signaling incentive consisting of career concerns and ego gratification. Interpreted as Status.

11 Status Extrinsic motivations, e.g., winning a reward, increase status motives (Roberts et al., 2006) Status motives decrease intrinsic motivations, e.g., fun, pride (Roberts et al., 2006) Huberman et al. (2004) showed that recognition such as applause was a better motivator than money. And in fact, money tends to decrease motivation (not supported in Roberts et al., 2006). Status is similar to the career concerns signaling motivation (Lerner and Tirole, 2002)

12 Status/Signals in BIC Win Participation Do research Enter No research Do not enter Non- Verifiable Activity Signal Strong + Weak + Weak + None Status + Weak + Weak + None Verifiable Activity Signal Strong + + None None Status + + None None

13 Models of Status Status is often modeled as rank in a peer group and depends on how much effort the individual puts into status seeking activities compared to the others in the group Loch and Wu (2005), Basu (1989) Status also comes from association with certain people/activities Basu (1989) If too many people (or the wrong people) join, status gained declines.

14 Previous Status Models γ + ε i, where ε i is a stochastic error term to account for heterogeneity (Sauer, 2007) Status in a workgroup: S(t+1) α γ γ α α = α(γ*politicking + (1- γ)*working)+(1-α)s(t), where α is a decay rate. Utility is a function of rank based on this status (and wages). (Loch et al., 2000)

15 Status in BIC Comes from awareness by group for Winning Participating The group here may be the BIC community, coworkers, friends/family. Awareness comes from Web site Word of mouth

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19 Terwiesch and Xu (2008) Ideation Challenge All solvers have same expertise β Seeker s taste parameter is essentially noise, ξ i, iid Gumbel RV with mean 0and scale parameter µ The value of solution i: v i = β+ θln(e i ) + ξ i Solver s Expected Utility = max U = δ ( A Pr( win) c e c ) + (1 δ )0 e 1 i f i Where δ= 1 if solver iparticipates, e i is effort Pr(win) = Pr (your solution is better than the max of everyone else s) θ ln ei exp µ = θ ln ei θ ln e exp + ( n 1) exp µ µ

20 Adding Status to the Utility Model Assuming participation Utility for solver i= P(win) * (A + Status) + α *P(lose)*Status c 1 e i c f α 1 i f where 0 α 1

21 Adding Status to Terwieschand Xu If effort does not affect resulting status, any status benefit reduces the fixed cost of participation and increases the award. If status increases linearly in effort, say Se, then it If status increases linearly in effort, say Se 1, then it reduces the variable cost of effort and is like an effort dependent award a fixed award + effort dependent portion

22 Status Model S = S 0 em/nwhere S 0 is a base level of status, m is the visibility, n the number of participants. Lerner and Tirole (2002) note that the value of the signal increases with visibility. However, the more people that participate the less valuable the signal. Effort increases status, thus effort/participation is assumed visible.

23 Solver s Problem 0 i 0 i max ( i ) Pr( ) ( ) e i S e m S e m U e = + A win + α P lose c1e i cf n n θ ln ei exp S e m µ S e m α A α c e cf exp + ( n 1) exp µ µ 0 i 0 i = i n θ ln ei θ ln e n Assume other players all choose e and find the symmetric Nash equilibrium. e * = A( n 1) nθ c µ n S m ( n 1) αθ + nµ ( α + nα ) ( )

24 Seeker s Problem Seeker may want either the best solution (weight ρ) or may care about the average performance of all the solutions (weight (1-ρ)). 0 ρ 1 A, m ( 1 ρ ) β θ ln ( (, )) ( ( * ) ) max π ( A, m) = ρ β + θ ln e ( A, m) + µ ln( n) ( ) + + e A m A cm ( ) * 2 = β + θ ln e ( A, m) + ρµ ln( n) A cm * 2

25 Seeker s Solution A* = θ m * = ( 2 2 (( 1) ( )) ) c S ( n ) αθ + n µ ( α + n α ) c c n µ c c c n µ + S n αθ + nµ α + nα v v 1 v 0 ( ) 2 1 v 0

26 Insights Status benefits induce more effort in equilibrium as compared to Terwiesch and Xu In numerical examples, extra effort drops off quickly as n grows. Currently BIC do not take advantage of social networking to increase status. Recognition (in the solver community) only comes by winning. However, the number of solvers on a challenge is visible. This may reduce the likelihood of another solver joining.

27 Effort and Seeker Profit Increase Effort Improvement Seeker Profit Improvement β = 1, c =.1, µ = 2, θ = 1, ρ = S =.1, c =.4, c = 0, α =.3 v f

28 Limitations Have only looked at ideation contests Assumes symmetric players so it is solvable. People are not likely to be symmetric, especially in motivations. Lakhani et al. (2007) found free time was important. The amount of effort or cost of effort should depend on this.

29 Future Directions Marketing models for visibility eyeballs Social networking models for status Other status models, e.g., depends on size of reward Empirical validation How should the firm design the system based on these motivations? Can firms copy this mechanism for internal use? Success of contests versus brokered contracts InnoCentive vs. IdeaConnection vs. NineSigma

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