This article extends signaling theory to research on acquisition premiums and investigates the value that newly public targets capture in post-IPO acquisitions. We complement previous research on acquisition premiums by suggesting that signals about targets can enhance sellers' gains by reducing acquirers' offer price discounting that is due to information asymmetries. Specifically, we argue that target firms can engage in interorganizational relationships (e.g., associations with prominent investment banks, venture capitalists, and alliance partners) that function as signals and enhance sellers' gains. Empirical evidence shows that the benefits of such signals apply to domestic and cross-border deals alike and that these benefits are even greater for IPO targets selling their companies to acquirers based in different industries.

Specific ethnic genetic backgrounds are associated with the risk of Stevens-Johnson syndrome / toxic epidermal necrolysis (SJS/TEN) especially in Asians. However, there have been no large cohort, multiple-country epidemiological studies of medication risk related to SJS/TEN in Asian populations. Thus, we analyzed the registration databases from multiple Asian countries who were treated during 1998-2017. A total 1,028 SJS/TEN cases were identified with the algorithm of drug causality for epidermal necrolysis. Furthermore, those medications labeled by the US Food and Drug Administration (FDA) as carrying a risk of SJS/TEN were also compared with the common causes of SJS/TEN in Asian countries. Oxcarbazepine, sulfasalazine, COX-II inhibitors, and strontium ranelate were identified as new potential causes. In addition to sulfa drugs and beta-lactam antibiotics, quinolones were also a common cause. Only one acetaminophen-induced SJS was identified, while several medications (e.g., oseltamivir, terbinafine, isotretinoin, and sorafenib) labeled as carrying a risk of SJS/TEN by the FDA were not found to have caused any of the cases in the Asian countries investigated in this study.

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Research summary: This article shows that there is a positive association between the changes in the number of prior acquisitions or the changes in the prominence of prior acquirers within the focal venture's subfield and the venture's likelihood to be acquired. Results are in line with the existence of frequency‐ and trait‐based imitation in acquisitions targeting tech ventures. More importantly, these positive associations are more pronounced when (a) exogenous technological uncertainty within the venture's subfield increases and (b) there are significant differences between the focal venture's and acquirer's technological resources. Our findings are in accord with the suggestion that uncertainty in the technology domain is an important boundary condition in moderating the extent of imitation in technology acquisitions. We also discuss alternative explanations and implications. Managerial summary: The findings of this article suggest that when deciding whether or not to acquire a technology venture (i.e., startup company in a high‐tech industry), managers infer information by observing other acquisitions in the venture's subfield to make assessments about the underlying value of the potential targets. We also find that receiving some informational cues from previous acquisitions would be more useful when there is high technological uncertainty in the potential target's subfield about which technologies will be dominant, and when the potential acquirer and the tech venture operate in dissimilar technological areas. This article shows that imitation can be one way to deal with decision‐making under uncertainty when making acquisition decisions in high‐tech environments. Copyright © 2017 John Wiley & Sons, Ltd.

A key challenge facing acquirers is how to judge the technological and other resources of high‐tech ventures. While it is well known that acquirers can benefit from signals about targets to reduce acquirers’ uncertainty in the selection of acquisition targets, this leaves open the question of the degree to which certain acquirers would rely on a target’s signals. We argue that different levels and types of experience can shape an acquirer’s attention to high‐tech ventures’ signals. On the one hand, general acquisition experience can lead an acquirer to pay more attention to and act on signals. On the other hand, target‐specific experience developed from prior collaborations can reduce the value of signals by directly mitigating an acquirer’s risk of adverse selection. Based on a sample of over a thousand technology ventures in the US biotechnology industry, our empirical evidence demonstrates that the combination of acquirers’ experiences and targets’ signals explains who buys whom in a high‐tech industry.