TY - JOUR
T1 - How do technology ventures signal IPO quality? A configurational approach
AU - Wang, Taiyuan
AU - Qureshi, Israr
AU - Deeds, David
AU - Ren, Yi
N1 - Publisher Copyright:
© 2019
PY - 2019/6
Y1 - 2019/6
N2 - This study examines how quality signals sent by technology ventures jointly affect investors' decisions under information asymmetry. We categorize signal contents as concerning technology development, venture officers, or early investors. Because similar information may not much reduce information asymmetry, different signals of the same content substitute for one another in enabling ventures to raise capital in their initial public offerings (IPOs). In contrast, signals of different contents collectively reduce information asymmetry, and thus complement each other. Furthermore, public investors may be more capable of assessing, and therefore give more weight to, signals based on the abilities and commitment of venture officers and early investors than to signals based on the viability and appropriability of technology development. We employ fuzzy set qualitative comparative analysis (fsQCA) and find evidence for these mechanisms from data on 268 IPOs of biotechnology ventures in the United States.
AB - This study examines how quality signals sent by technology ventures jointly affect investors' decisions under information asymmetry. We categorize signal contents as concerning technology development, venture officers, or early investors. Because similar information may not much reduce information asymmetry, different signals of the same content substitute for one another in enabling ventures to raise capital in their initial public offerings (IPOs). In contrast, signals of different contents collectively reduce information asymmetry, and thus complement each other. Furthermore, public investors may be more capable of assessing, and therefore give more weight to, signals based on the abilities and commitment of venture officers and early investors than to signals based on the viability and appropriability of technology development. We employ fuzzy set qualitative comparative analysis (fsQCA) and find evidence for these mechanisms from data on 268 IPOs of biotechnology ventures in the United States.
KW - Initial public offerings
KW - Quality signals
KW - Signal configurations
KW - Technology ventures
UR - http://www.scopus.com/inward/record.url?scp=85062005122&partnerID=8YFLogxK
U2 - 10.1016/j.jbusres.2019.01.039
DO - 10.1016/j.jbusres.2019.01.039
M3 - Article
SN - 0148-2963
VL - 99
SP - 105
EP - 114
JO - Journal of Business Research
JF - Journal of Business Research
ER -