Predicting Corporate Venture Capital Investment

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review

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Detail(s)

Original languageEnglish
Title of host publication38th International Conference on Information Systems (ICIS 2017)
Subtitle of host publicationTransforming Society with Digital Innovation
PublisherAssociation for Information Systems
Pages5841-5849
Volume8
ISBN (Print)9781510853690
StatePublished - 12 Dec 2017

Conference

Title38th International Conference on Information Systems, ICIS 2017
LocationCOEX, Convention and Exhibition Center
PlaceKorea, Republic of
CitySeoul
Period10 - 13 December 2017

Abstract

Corporate venture capital (CVC) has been growing rapidly in the past decades. As a critical first step for effective CVC investment, the selection of appropriate portfolio companies is challenging and difficult due to the large number of potential targets and the high uncertainty arising from an investment deal. In this study, we adopt the design science approach and develop a prediction model to support CVC investment decisions by identifying a list of potential investees from a large pool of portfolio companies for a CVC investor. We develop five key features using data science techniques including business proximity, wisdom of crowds in CVC investments, strategic alignment, status differential, and geographic proximity. To evaluate the performance of the proposed model, we plan to conduct experiments on the CrunchBase dataset.

Research Area(s)

  • Corporate venture capital (CVC), CVC investment network, Data science, Prediction model

Citation Format(s)

Predicting Corporate Venture Capital Investment. / Xu, Ruiyun; Chen, Hailiang; Zhao, J. Leon.

38th International Conference on Information Systems (ICIS 2017): Transforming Society with Digital Innovation. Vol. 8 Association for Information Systems, 2017. p. 5841-5849.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review