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Keiichi Kawai

Publications and source records attributed to Keiichi Kawai.

2 recordsLinked to original sources

Geography in Online Capital Allocation: Evidence from Equity-Based Crowdfunding

Digital investment platforms reduce search costs, yet realized investments can remain geographically concentrated. Such concentration alone cannot distinguish whether local investment reflects initial salience, proximity-related information, prior ties, or nonpecuniary motives such as support for firms in one's home prefecture. We use user-campaign records from Fundinno, Japan's dominant equity-based crowdfunding platform, which link listing exposure, campaign-page views, and investments to user residence and issuer location. For campaigns outside the Tokyo metropolitan area (non-TMA), same-prefecture users are 6.7 percentage points more likely to invest after viewing a campaign page, relative to an other-prefecture investment rate of roughly 10 percent. The corresponding adjacent-prefecture difference is only 0.9 percentage points, and the same-prefecture premium is small for campaigns inside the Tokyo metropolitan area. The premium therefore remains after observed campaign-page access, is much larger than the adjacent-prefecture difference, and is concentrated outside the metropolitan core. These findings show that online access does not make investment demand geographically neutral: for regional issuers, same-prefecture investors remain disproportionately important even after campaign-page access. The data do not identify the underlying motive, but the pattern is difficult to explain by discovery alone or by smooth proximity.

econ.GN

Robust Pricing with Refunds

Before purchase, a buyer of an experience good learns about the product's fit using various information sources, including some of which the seller may be unaware of. The buyer, however, can conclusively learn the fit only after purchasing and trying out the product. We show that the seller can use a simple mechanism to best take advantage of the buyer's post-purchase learning to maximize his guaranteed-profit. We show that this mechanism combines a generous refund, which performs well when the buyer is relatively informed, with non-refundable random discounts, which work well when the buyer is relatively uninformed.

cs.GT