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Baron Diermeier (2006) - Strategic Activism And Nonmarket Strategy (view source)
Revision as of 23:29, 23 May 2010
, 23:29, 23 May 2010no edit summary
You can derive a rewards to cost ratio, which suggest that more responsive firms will be threatened with harm over rewards, and that harm will be preferred with rewards are costly. If the internet reduces <math>\beta\,</math>, then we would expect to see campaigns with higher demands that emphasize more harm after its adoption.
==Why Are Campaigns Negative?===
Campaigns are most likely to be negative because;
*There is an industry effect - rewards alone would increase the profit of the firm, whereas harm decreases them. Therefore harm acts to discourage investment in the industry, which reduces the scale of the industry and hence the objectional practises
*There is an endogenous selection effect - targets are selected by the responsiveness <math>p\,</math>, and both the demand and the harm are increasing in <math>p\,</math>, whereas <math>r\,</math> may be decreasing in <math>p\,</math>
*Rewards may be costly to provide (i.e. <math>\alpha\,</math> maybe high)
*Harm can induce proactive self-regulation (see later)
===Target Selection===
Targets are selected, all else equal, when:
*<math>v(x_0) - v(x_D)\,</math> is high - the campaign gives high utility to the activist
*Likewise if <math>\gamma\,</math> is high
*If <math>p\,</math> is high
*If there are low costs to the campaign (<math>\eta, \alpha, \beta\,</math>)
===The Market for Activists===
Activists must be supported by citizens and could adopt strategies or either rewards, harm, or both.
The expected cost to rewards (in equilibrium) are:
:<math>C^r = \frac{p \gamm^2}{4 \eta^2 \alpha}\,</math>
The gains to rewards can likewise be calculated and are <math>G^r = C^r\,</math>. In fact the ratio of gains to costs for any strategy are the same:
:<math>\frac{G^r}{C^r} = \frac{G^h}{C^h} = \frac{G^*}{C^*} = 1\,</math>
However, the demands are as follows:
:<math>x_D^* = x_D^r + \frac{1}{\eta}h^* = x_D^h + \frac{1}{\eta}r^*\,</math>
So the activist that uses both harm and rewards accomplishes more.
===Self-Regulation===
====With a Single Target===
Assume that the activist can commit not to conduct a campaign once a concession is made. Such a committment could be credible if the activist had a reputation.
The activist will not commit if:
:<math>v(\hat{x}) \ge u(x_D^*, r^*, h^*)\,</math>
Likewise the target will adopt if:
:<math>\pi(\hat{x}) \ge \pi(x_0) - h^*\,</math>
Putting these together (noting that <math>\hat{x} < x_D\,</math>) <math>\hat{x}\,</math> exists iff:
:<math>\frac{2-p}{1-p} \ge \frac{\beta}{\alpha}\,</math>
Therefore if harm is emphasized over reward then pro-active measures can be observed. Note that if the activist can not commit then there is a hold up problem that prevents pro-active measures: After the firm had implemented <math>\hat{x}\,</math> the activist would consider it the new <math>x_0\,</math> and begin the cycle again.
====With Multiple Targets====
If there are no strategic interactions between the firms then a firm has an incentive to adopt a pro-active measure to shift the activist's focus elsewhere. Thus there is a multiplier effect - the activist need only target one firm to make the entire industry shift pro-actively. However, without strategic interactions the shift is identical to that in single firm example above.
With strategic interactions, a competition in pro-active measures ensues. The result is equivalent to the activist conducting a second-price auction for the opportunity to avoid a campaign. A sufficient condition (but not necessary) for this is that harm is emphasized over rewards. The race to the top leads to greater aggregate change than targeting a single firm.
