In Internet venture capital (VC), it is very important to fully analyze and evaluate the influential factors. Because this activity usually involves amounts of experts, it makes sense to incorporate it into large-scale group decision-making (LSGDM). In this process, how to deal with the noncooperative behaviors and express the preference information are two important issues that need to be addressed. Given this, this paper is committed to evaluating the influential factors of Internet VC by managing noncooperative behaviors in LSGDM. Firstly, the preference information can be expressed by linguistic preference orderings (LPOs) which can be used to express unbalanced relationship between any two adjacent alternatives. Then, three kinds of noncooperative behaviors are taken into consideration, and we can identify the group who belongs to one of the three noncooperative behaviors, and then develop methods to manage them respectively. Furthermore, a consensus reaching model is established to manage these noncooperative behaviors. Moreover, we apply the proposed model to solve a practical LSGDM problem involving the evaluations of the influential factors in Internet VC. Finally, comparative analyses between the proposed model and some existing methods are made to show the validity and applicability of the proposed consensus reaching model.

在互联网风险投资（VC）中，充分分析和评估影响因素非常重要。由于此活动通常涉及大量专家，因此有必要将其纳入大规模的团体决策（LSGDM）。在这个过程中，如何应对不合作行为和表达偏好信息是需要解决的两个重要问题。鉴于此，本文致力于通过管理LSGDM中的非合作行为来评估Internet VC的影响因素。首先，偏好信息可以通过语言偏好排序（LPO）来表达，该语言偏好排序可以用来表达任何两个相邻替代方案之间的不平衡关系。然后，考虑了三种非合作行为 然后我们可以确定属于三种非合作行为之一的群体，然后分别开发出应对方法。此外，建立了共识达成模型来管理这些非合作行为。此外，我们将提出的模型用于解决实际的LSGDM问题，该问题涉及对Internet VC中影响因素的评估。最后，通过对所提模型与现有方法的比较分析，证明了所提共识模型的有效性和适用性。我们将提出的模型用于解决实际的LSGDM问题，该问题涉及对Internet VC中影响因素的评估。最后，通过对所提模型与现有方法的比较分析，证明了所提共识模型的有效性和适用性。我们将提出的模型用于解决实际的LSGDM问题，该问题涉及对Internet VC中影响因素的评估。最后，通过对所提模型与现有方法的比较分析，证明了所提共识模型的有效性和适用性。