This study presents a new risk assessment model by combining interval type-2 fuzzy best-worst method (IT2F-BWM) and perceptual reasoning for risk evaluation of digital transformation projects. Digital transformations are technology-driven change processes that transform many businesses. Digital transformations are risky and difficult undertakings so that the decision-makers should be supported with appropriate risk assessment tools. The proposed model is a step towards this direction by providing decision-makers with a practical and applicable risk assessment tool that computes with words through a transparent and interpretable reasoning mechanism. In the proposed model, the relative importance of risk factors (RFs) is derived by using IT2F-BWM. Then, IT2F rule-based model is developed by considering risk factors along with the likelihood and severity of risks. The risk magnitudes of digital transformation projects are evaluated via perceptual reasoning. Both the input and output of the reasoning model are IT2F numbers, and the resulting risk magnitudes are decoded into words such as critical, major, and minor so as to ease interpretation. A real-life digital transformation risk assessment case study is conducted in order to demonstrate the applicability of the proposed model.

本研究通过结合区间2型模糊最优方法（IT2F-BWM）和感知推理对数字化转型项目进行风险评估，提出了一种新的风险评估模型。数字化转型是技术驱动的变革过程，可改变许多企业。数字化转型是冒险且艰巨的任务，因此决策者应得到适当的风险评估工具的支持。提议的模型是朝这个方向迈出的一步，它为决策者提供了一种实用且适用的风险评估工具，该工具可通过透明且可解释的推理机制进行文字计算。在提出的模型中，使用IT2F-BWM得出了风险因素（RFs）的相对重要性。然后，通过考虑风险因素以及风险的可能性和严重性来开发基于IT2F规则的模型。数字化转型项目的风险大小通过感知推理进行评估。推理模型的输入和输出都是IT2F编号，并且将得到的风险大小解码为关键，主要和次要之类的词，以便于解释。进行了现实生活中的数字化转型风险评估案例研究，以证明所提出模型的适用性。