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Sievers and C. F. Mokwa, <i>The Relevance of Biases in Management Forecasts for Failure Prediction in Venture Capital Investments</i>. 2012.","apa":"Sievers, S., &#38; Mokwa, C. F. (2012). <i>The Relevance of Biases in Management Forecasts for Failure Prediction in Venture Capital Investments</i>. <a href=\"https://doi.org/10.2139/ssrn.2100501\">https://doi.org/10.2139/ssrn.2100501</a>","short":"S. Sievers, C.F. Mokwa, The Relevance of Biases in Management Forecasts for Failure Prediction in Venture Capital Investments, 2012.","chicago":"Sievers, Sönke, and Christopher Frederik Mokwa. <i>The Relevance of Biases in Management Forecasts for Failure Prediction in Venture Capital Investments</i>, 2012. <a href=\"https://doi.org/10.2139/ssrn.2100501\">https://doi.org/10.2139/ssrn.2100501</a>."},"extern":"1","abstract":[{"text":"This study shows how venture capital investors can identify potential biases in multi-year management forecasts before an investment decision and derive significantly more accurate failure predictions. By advancing a cross-sectional projection method developed by prior research and using firm-specific information in financial statements and business plans, we derive benchmarks for management revenue forecasts. With these benchmarks, we estimate forecast errors as an a priori measure of biased expectations. Using this measure for our proprietary dataset on venture-backed start-ups in Germany, we find evidence of substantial upward forecast biases. We uncover that firms with large forecast errors fail significantly more often than do less biased entrepreneurs in years following the investment. Overall, our results highlight the implications of excessive optimism and overconfidence in entrepreneurial environments and emphasize the relevance of accounting information and business plans for venture capital investment decisions.","lang":"eng"}],"date_created":"2021-01-05T11:59:50Z","department":[{"_id":"275"}],"type":"working_paper","keyword":["Management forecast biases","cross-sectional projection models","venture-backed start-ups","failure prediction","overoptimism","overconfidence"]},{"author":[{"full_name":"Hoyer, Britta","first_name":"Britta","last_name":"Hoyer","id":"42447"},{"last_name":"De Jaegher","first_name":"Kris","full_name":"De Jaegher, Kris"}],"title":"Network Disruption and the Common Enemy Effect","year":"2012","status":"public","date_updated":"2022-01-06T06:55:34Z","series_title":"TKI Working Paper Series","_id":"2249","main_file_link":[{"url":"https://www.uu.nl/en/files/rebousedp201212062pdf","open_access":"1"}],"volume":"12-06","user_id":"42447","citation":{"short":"B. Hoyer, K. De Jaegher, Network Disruption and the Common Enemy Effect, 2012.","chicago":"Hoyer, Britta, and Kris De Jaegher. <i>Network Disruption and the Common Enemy Effect</i>. Vol. 12–06. TKI Working Paper Series, 2012.","ieee":"B. Hoyer and K. De Jaegher, <i>Network Disruption and the Common Enemy Effect</i>, vol. 12–06. 2012.","apa":"Hoyer, B., &#38; De Jaegher, K. (2012). <i>Network Disruption and the Common Enemy Effect</i> (Vol. 12–06).","bibtex":"@book{Hoyer_De Jaegher_2012, series={TKI Working Paper Series}, title={Network Disruption and the Common Enemy Effect}, volume={12–06}, author={Hoyer, Britta and De Jaegher, Kris}, year={2012}, collection={TKI Working Paper Series} }","ama":"Hoyer B, De Jaegher K. <i>Network Disruption and the Common Enemy Effect</i>. Vol 12-06.; 2012.","mla":"Hoyer, Britta, and Kris De Jaegher. <i>Network Disruption and the Common Enemy Effect</i>. Vol. 12–06, 2012."},"abstract":[{"lang":"eng","text":"The phenomenon that groups or people work together when they face an opponent,\r\nalthough they have little in common otherwise, has been termed the \"common enemy\r\neffect\". We study a model of network formation, where players can use links to build\r\na network, knowing that they are facing a common enemy who can disrupt the links\r\nwithin the network, and whose goal it is to minimize the sum of the benefits of the\r\nnetwork. We find that introducing a common enemy can lead to the formation of\r\nstable and efficient networks as well as fragmented networks and the empty network."}],"date_created":"2018-04-06T07:44:14Z","department":[{"_id":"280"},{"_id":"475"}],"oa":"1","type":"working_paper"}]