Information Disclosure and Pricing Policies for Sales of Network Goods

We study a two-period model in which a firm faces the problem of deciding whether to commit to sales volume disclosure under market size uncertainty, when selling a network good to forward-looking customers who time their purchases. If the first-period sales volume is disclosed, the second-period customers will base their purchase decisions on this information. If the sales volume is not disclosed, all customers will make purchase decisions based on their estimate of market size. We identify two countervailing effects of sales disclosure: (i) a pro-disclosure "Matthew" effect: the benefit of a realized large market size tends to outweigh the loss of a realized small one; and (ii) an anti-disclosure saturation effect: for a sufficiently large market, customers would make a purchase anyway even without knowing the realized market size, but might be discouraged if observing a realized small one. With exogenous prices, we show that committing to sales disclosure is a dominating (resp., dominated) policy when the expected network benefit is relatively weak (resp., strong). We also examine three endogenous pricing scenarios. First, under state-independent pricing, committing to sales disclosure is optimal if the customer valuation distribution has a high probability of reaching very high values (i.e., heavy tail). Second, if a firm can credibly preannounce a contingent pricing policy, committing to sales disclosure is always optimal. Finally, under contingent pricing without commitment, we show that committing to sales disclosure is optimal when delaying the purchase decision to the second period does not reduce the value much