Elsevier

Applied Soft Computing

Volume 67, June 2018, Pages 756-763
Applied Soft Computing

How to select a promising enterprise for venture capitalists with prospect theory under intuitionistic fuzzy circumstance?

https://doi.org/10.1016/j.asoc.2017.04.027Get rights and content

Highlights

  • A screening approach for the venture capitalists is constructed based on IFPT to simulate the psychological state of the venture capitalists in the decision-making process.

  • The proposed approach not only provides an alternative tool for the venture capitalists in decision-making but also enriches the application of IFPT.

  • The analysis framework of constructing this approach can be extended to other uncertain decision-making problems and play the part of demonstration role for future research in other fields.

Abstract

Venture capitalists are confronted with decision-making problems under an uncertain investment circumstance, which lead them to rely heavily on intuition and psychological state to make their decisions in most cases. It has attracted more and more researches to focus on such behaviors of venture capitalists in recent years and along with the development of behavioral finance in venture capital field. Through the review of framework of venture capitalists’ decision-making and the investigation of background of venture capital market in China, we find that the decision-making framework, which is based on the traditional expected utility theory with hypothesis that the investor is completely rational, is inconsistent with reality. Moreover, the decision-making information is often depicted as crisp number with probability that couldn’t express the uncertainty which is the fundamental nature of venture capital circumstance. Therefore, a novel approach that considers both the bounded rationality of venture capitalists and the uncertain circumstance of venture capital in decision-making is urgent to select the promising enterprise in China. Fortunately, prospect theory, as one of the greatest achievement in behavioral finance, thinks that venture capitalists focus on subjective probabilities instead of objective probabilities and show the behavior characterized by risk aversion over gains and risk seeking over losses, which can depict the psychological state of venture capitalists properly. Furthermore, the intuitionistic fuzzy information can express essential uncertainty in venture capital circumstance accurately. Therefore, we adopt Intuitionistic Fuzzy Prospect Theory that integrates both the merits of prospect theory and intuitionistic fuzzy information to aid venture capitalists to make a better decision in the real world. In this paper, the detailed steps of how to select a promising enterprise has been illustrated. Then, a practical example of selecting the promising enterprise for venture capitalists in Ali Capital is provided to exhibit the process of application and exemplify the feasibility of this selecting approach. Meanwhile, from the comparison of ranking results derived by TOPSIS and this approach, we find that the approach proposed in this paper is superior to the TOPSIS in selecting the promising enterprise according to the subsequent funded results of enterprises.

Introduction

Venture capital (VC) is a kind of capital that helps New High-tech Enterprises (NHEs) get rid of strategic or capital dilemma via providing professional resources such as additional financial capital, effective management and monitoring system, or powerful social network and so on. While NHEs play a great important role in activating economy with new scientific research results and with the application of new technologies. Moreover, those NHEs often accompany with high risk, potential high profit and many uncertain factors [1] so that only VC is willing to finance them for the sake of gaining high revenue with small probability of success.

Since the market of VC began to take shape in the 1980s in China, the government takes many effective measures to promote the development of VC market, including setting up guiding funds, making rules and regulations. Benefited by those effective measures, some achievements have already been made in recent years, as shown in Table 1.1

As we can see from Table 1 that the VC market keeps good and continuous development in China. But it is still unsatisfactory by comparing it with USA in the internal rate of return (IRR), an important index for the efficiency of VC. The IRRs of VC in USA were 9.09% in 2013 and 30.5% in 20122 according to the criterion of NVCA (the National Venture Capital Association). Due to the immaturity of VC market in China and the incompleteness of data collection, there is no precise IRR. But fortunately, we have interviewed some senior venture capitalists (VCs), and all of them agree that the IRR of VC in China is far less than in USA.

Why this tremendous gap between USA and China has been widened? A very important reason is that there is lack of a complete and effective approach used by VCs to aid them to select a promising enterprise which will affect their performances. It is particularly important for VCs to select the promising enterprise before spending their limited capital to enterprise. Sometimes, they would rather consider the promising enterprise than fund an unsatisfactory one. Therefore, as the development and expansion of VC market, the VCs are always devoting themselves to selecting the promising one among the thousands of enterprises under uncertain investment circumstance. The decision-making process of VCs can be shown in Fig. 1.

Uncertainty not only includes the fundamental nature of VC circumstance but also contains the bounded perception of VC circumstance by the VCs. However, VCs are individuals who differ in educational background, gender, age, experience, belief, risk preference and so on, and they couldn’t access all the information or enterprises, or predict the tendency of future exactly. Those conditions lead VCs to conceptualize and understand uncertainty in a different way which will impact their encoding processes of decision-making information. Moreover, in most decision-making processes, the VCs express cognitive bias caused by psychological state such as overconfidence, representativeness, availability, under and over-reaction, and herding. Those psychological states of VCs are hard to be quantitative as the decision-making information in the existing decision-making approach. Based on the uncertain circumstance of VC investment and the different perception of decision-making information produced by cognitive biases of VCs and so on, an approach is necessary to exhibit it.

The primary work of this paper is to construct the steps of how to select a promising enterprise by considering both the psychological state of VCs and vague information under VC circumstance. First, we begin with the development of VC market in China. Next, the literature review about how the VCs make their decisions including the decision-making approaches and frameworks used by VCs is presented, and we find that there is no appropriate approach that can be used to demonstrate the complex process of decision-making for VCs, especially the psychological state of VCs can’t be reflected in the existing approaches. After that, a suitable approach based on Intuitionistic Fuzzy Prospect Theory (IFPT) [2] is constructed to improve the quality of the VCs’ decisions, and the specific steps of selecting a promising enterprise are proposed. Finally, a practical example is provided to exhibit the application of this approach for the VCs in Ali Capital, and the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) is used to compare with this approach to exemplify its superiority.

At least two main contributions are made in this paper: firstly, we construct a selecting approach based on IFPT to simulate the VCs’ decision-making. It not only includes the vague information under uncertain investment circumstance but contains the psychological states of the VCs. Secondly, the proposed approach is the application of IFPT in the field of VC, which plays a demonstrated role for other fields.

Section snippets

Literature review: researches about the venture capitalists’ decision-making

To understand the decision-making process of VCs is not only conductive for them to make better decisions in a more rational way, but also beneficial for substantial entrepreneurs to gain the desired capital to realize their business dreams. However, to choose a proper decision-making approach is the most important issue for VCs in their decision-making processes. In order to demonstrate the superiority of the decision-making approach constructed by us, in the following, we review the

The process of selecting the promising enterprise based on the IFPT

The decision-making approaches under the PT with fuzzy information, such as interval-valued intuitionistic fuzzy information [43], triangular intuitionistic fuzzy information [44], trapezoidal fuzzy information [45], trapezoidal intuitionistic fuzzy information [46], intuitionistic random information [47] and so on, have already been studied. In addition, the TODIM is constructed based on the PT to measure the relative dominance of the alternatives [48]. But none of them takes the uncertain

Case study

In this section, an example of Ali Capital has been discussed to illustrate the advantage of the selecting approach proposed in this paper. Hundreds of enterprises have been provided by entrepreneurs to Ali Capital as alternatives. Ali Capital is the famous Chinese-fund VC institution in China. The total amount of investment of Ali Capital has already been CNY 30.53 billion during 2011–2015, capturing the top two in China and the top one among the Chinese-fund VC institution. The key challenge

Conclusions

The VCs are confronted with the decision-making problems all the time under uncertain circumstances which will produce psychological discomforts. It motivates them to take actions such as decision-making strategy or model to transfer the uncertain situations to the relative certain ones. While, in the process of decision-making, VCs make their decisions with intuition and psychological state involuntarily. So, it is important to simulate the characteristics of VCs’ decision-making. The main

Acknowledgments

This research was funded by the National Natural Science Foundation of China (Nos. 71401116, 71571123), also funded by Sichuan University (No. skqy201655), and funded by the FEDER funds under grant (TIN2013-40658-P, TIN2016-75850-P) as well.

References (59)

  • A. Parhankangas et al.

    How venture capitalists respond to unmet expectations: the role of social environment

    J. Bus. Venturing

    (2006)
  • X.H. Li et al.

    Trapezoidal intuitionistic fuzzy multiattribute decision making method based on cumulative prospect theory and Dempster-Shafer theory

    J. Appl. Math.

    (2016)
  • R. Lourenzutti et al.

    A study of TODIM in a intuitionistic fuzzy and random environment

    Expert Syst. Appl.

    (2013)
  • Z.P. Fan et al.

    Multiple attribute decision making considering aspiration-levels: a method based on prospect theory

    Comput. Ind. Eng.

    (2013)
  • P. Dolan et al.

    The measurement of preferences over the distribution of benefits: the importance of the reference point

    Eur. Econ. Rev.

    (2001)
  • R. Gonzalez et al.

    On the shape of the probability weighting function

    Cognit. Psychol.

    (1999)
  • S.M. Chen et al.

    Handling multicriteria fuzzy decision-making problems based on vague set theory

    Fuzzy Sets Syst.

    (1994)
  • D.H. Hong et al.

    Multicriteria fuzzy decision-making problems based on vague set theory

    Fuzzy Sets Syst.

    (2000)
  • Y.C. Dong et al.

    Integrating experts' weights generated dynamically into the consensus reaching process and its applications in managing non-cooperative behaviors

    Decis. Support Syst.

    (2016)
  • G.Z. Chen et al.

    Investment risk evaluation of high-tech projects based on random forests model

  • J. Gu et al.

    Decision making framework construction in prospect theory under intuitionistic fuzzy information

    Technical Report

    (2016)
  • B. Aouni et al.

    A cardinality constrained stochastic goal programming model with satisfaction functions for venture capital investment decision making

    Ann. Oper. Res.

    (2013)
  • B. Aouni et al.

    On Dynamic Multiple Criteria Decision Making Models: A Goal Programming Approach. Multiple Criteria Decision Making in Finance, Insurance and Investment

    (2015)
  • C. Colapinto et al.

    Multiple Criteria Decision Making and Goal Programming for Optimal Venture Capital Investments and Portfolio Management. Multiple Criteria Decision Making in Finance, Insurance and Investment

    (2015)
  • B. Aouni et al.

    A fuzzy goal programming model for venture capital investment decision making

    Inf. Syst. Oper. Res.

    (2014)
  • E. Afful-Dadzie et al.

    A decision making model for selecting start-up businesses in a government venture capital scheme

    Manage. Decis.

    (2016)
  • Y. Lin

    Evaluation model for venture capital with intuitionistic fuzzy information

  • J.S. Zhou

    Research on appraisal model of venture capital investing project based on high-tech outcome transformation with uncertain linguistic information

    Adv. Inf. Sci. Serv. Sci.

    (2012)
  • Y.J. Zhao et al.

    Research on evaluation of venture capital fund project based on data envelopment analysis model

    J. Comput. Theor. Nanosci.

    (2016)
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