Learning and information transmission within multinational corporations
研究了跨国公司如何利用在邻近市场的表现来预测新市场的盈利能力并做出进入决策，这种跨市场学习在新市场经验不足或不确定性高时尤为重要。
Firms face substantial uncertainty when doing business in new markets. We propose that multinational firms use “cross-market learning” to resolve such uncertainties. We develop a model of firm-level expectations formation with noisy signals from multiple markets and derive predictions on market entries and expectations formation over the firm’s life cycle. Using a novel dataset of Japanese multinational corporations that includes sales expectations of each affiliate, we provide supportive evidence for the model’s predictions. We find that firms rely on their performance in nearby markets to predict their profitability in a new market and make entry decisions. Such “cross-market” learning is less important after the firm has accumulated experience in the new market, but becomes more important if the uncertainty of the focal market is high or the firm has received more signals from the nearby markets.