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dc.contributor.authorDhochak, Monika-
dc.contributor.authorSharma, Anil K.-
dc.date.accessioned2017-11-03T07:06:34Z-
dc.date.available2017-11-03T07:06:34Z-
dc.date.issued2016-
dc.identifier.urihttp://hdl.handle.net/123456789/6481-
dc.description.abstractIn the last few years, researchers viewed that venture capitalists do not always follow the same criteria suggested by theory, but use a multi-criteria decision analysis for screening a new proposal. The first objective of this study is to identify the criteria used by Indian venture capitalists in investment decision-making process. Second, it analyses the relationship among predetermined decision-making factors. Selecting a new venture is a tedious job for venture capitalists due to the direct and indirect effect of certain factors. For this purpose, exploratory factor analysis was used to extract the determinants of investment decision-making process, and interpretive structural modelling was conducted to establish a hierarchal relationship among key decision-making enablers. Afterwards, a diagraph facilitates to accomplish the logical framework as per their relative dependence and driving powers. It is found that financial consideration is the most important factor that depends on other driving powers. The findings of the relationship-based approach may help to mitigate the adverse selection process. The insights of this model would assist the investors, entrepreneurs and researchers to understand the complex relationship among significant decision-making factors.en_US
dc.language.isoenen_US
dc.publisherInternational Journal of Management and Decision Makingen_US
dc.relation.ispartofseriesVol. 15, No. 1;-
dc.subjectExploratory Factor Analysisen_US
dc.subjectInterpretive Structural Modellingen_US
dc.subjectInvestment Decision-Makingen_US
dc.subjectISMen_US
dc.subjectMicmac Analysisen_US
dc.subjectVenture Capitalen_US
dc.titleIntegration of Factors Affecting Venture Capitalists’ Investment Decision: An Interpretive Structural Modelling Approachen_US
dc.typeArticleen_US
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