Please use this identifier to cite or link to this item: http://idr.iimranchi.ac.in:8080/xmlui/handle/123456789/1505
Title: Information signals and bias in investment decisions: a meta-analytic comparison of prediction and actual performance of new ventures
Authors: Vazirani, Ashish.
Sarkar, Subhro.
Bhattacharjee, Titas.
Dwivedi, Yogesh K.
Jack, Sarah.
Keywords: New-venture Financing
New-venture Performance
Decision Bias
ELM
Meta-analysis
IIM Ranchi
Issue Date: 2023
Publisher: Journal of Business Research
Citation: Ashish Vazirani, Subhro Sarkar, Titas Bhattacharjee, Yogesh K. Dwivedi, and Sarah Jack (2023). Information signals and bias in investment decisions: A meta-analytic comparison of prediction and actual performance of new ventures. Journal of Business Research, 155(Part B), 113424. https://doi.org/10.1016/j.jbusres.2022.113424
Abstract: This study investigates the presence, direction, and scale of bias in investors’ consideration of qualitative information signals while appraising new venture proposals through a meta-analysis of 75 empirical studies published between 2000 and 2020. Our results suggest that investors evaluate different information signals differently owing to their varying abilities and motivations. High levels of ability and motivation stimulate elaboration, resulting in positive bias, whereas low levels of both ability and motivation reduce the likelihood of elaboration, resulting in negative bias. However, for lower levels of either ability or motivation, we found a mix of both positive and negative biases determined by the dominance of information cues. While considering the prospects of investment decisions, our results show that signals suggesting growth potential are preferred over those suggesting financial risk coverage. This study has substantial implications for investors to optimize their decision-making processes and enable entrepreneurs to understand investors’ appraisal processes.
URI: https://doi.org/10.1016/j.jbusres.2022.113424
http://idr.iimranchi.ac.in:8080/xmlui/handle/123456789/1505
ISSN: 1873-7978 (Online)
Appears in Collections:Journal Articles

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