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In this paper we analyze how stock market liquidity affects the abnormal return to target firms in mergers and tender offers. We predict that target firms with poorer stock market liquidity receive larger announcement day abnormal returns based on the following considerations. First, target firms with poorer stock market liquidity receive greater liquidity improvements after a merger or tender offer. Second, deals that involve less liquid targets are less anticipated and/or more likely to be completed. Third, less liquid stocks have more diverse reservation prices across shareholders and thus require a higher takeover return. Consistent with these expectations, we show that abnormal returns to target firms’ shareholders are significantly and positively related to the difference in liquidity (measured by the bid‐ask spread) between acquirers and targets as well as the magnitude of target firms’ liquidity improvement.

In this study we test the information hypothesis of price improvement. Our results show that price improvement is negatively related to both the probability of information-based trading and the price impact of trades. We interpret these results as evidence that liquidity providers selectively offer price improvements according to the information content of trades. We also show that liquidity providers offer greater (and more frequent) price improvements when they are at the NBBO, and for stocks with wider spreads, fewer trades, or smaller trade sizes relative to the quoted depth. Buyer-initiated trades receive smaller (larger) price improvements than seller-initiated trades on the NYSE (NASDAQ). Copyright (c) 2009 The Authors Journal compilation (c) 2009 Blackwell Publishing Ltd.

This study examines the relationship between investor sentiment and stock returns in two active but different Korean stock markets. Using daily KOSPI and KOSDAQ data, we construct an investor sentiment index that includes adjusted turnover rate, buy–sell imbalance, and relative strength index. We find that investor sentiment significantly affects stock returns, more so in the KOSDAQ with high individual participation. Company characteristics, including size and stock price, affect the relationship between investor sentiment and stock returns. Moreover, we introduce the relationship between mobile trading and investor sentiment, and demonstrate that mobile trading transforms irrational investors into informed, rational investors.

This paper develops a model to analyze inter-organizational technology adoption in a supply chain. While the basic model is general, this study is motivated by several cases of inter-organizational technology adoption in supply chains. The proposed model in this study considers firms on both levels of the supply chain, namely, supplier firms and buyer firms. These individual firms' thresholds for adoption should be considered by other firms' decisions within a network, together with their own organizational attributes. The heterogeneity across the population should be allowed. That is, individual firms make a decision for adopting the technology at different times due to their different network sizes, prior beliefs, and amounts of information observed. The main finding is that this uncertainty decreases as other suppliers adopt the technology, and information about their experiences becomes available. In addition, at any given time, an estimate of the benefit to a supplier depends on the number of supplier firms and on the number of buyer firms that have already adopted the technology. Thus, we seek to capture this dependence and analyze its effect on the adoption of a new inter-organizational technology. The next step is to embed the firm-level adoption model into a population model. The model includes various types of heterogeneity in the population model to capture the factors affecting the speed of diffusion. This allows us to derive an adoption curve that is specified by the accumulated fraction of firms that have adopted the technology in or before any given period. The population model allows us to consider the effect of several strategies observed in practice and numerical experiments yielding many managerial implications in this area.