## 2 Literature Review
### New Product Development (NPD), Technology Selection and Supplier Selection
An interval type 2 fuzzy AHP was used to calculate the supplier evaluation criteria, and then the Complex Proportional Assessment method with Gray interval numbers (COPRAS-G) method was applied to rank the suppliers. [PERSON] et al. [36] constructed a model that integrated MCDM and data mining techniques for evaluating green suppliers. The Support Vector Machine (SVM) was applied to extract the core criteria from a firm's historical supplier performance data, then the Fuzzy Best Worst Method (FBWM) was used to calculate the weights of the criteria, and the fuzzy TOPSIS was finally adopted to select the most suitable green suppliers. [PERSON] et al. [37] reviewed past works regarding the evaluation and selection of suppliers for materials using MADM. Some commonly used methodologies include DEA, AHP, Simple Multi-Attribute Rating Technique (SMART). Mathematical programming such as linear programming, integer linear programming, integer non-linear programming, goal programming, multi-objective programming, and SMART are often adopted. Some preliminary AI methods, including Genetic Algorithms (GAs), Neural Networks (NNs), Rough Set Theory (RST), Particle Swarm Optimization (PSO), Grey System Theory (GST), and Ant Colony Algorithms (ACAs), have been applied. [PERSON] and [PERSON] [38] developed a strategy for a smart and sustainable supplier selection process. The importance weights of smart and sustainable criteria were determined by different MCDM methods, including AHP, best worst method, and TOPSIS in triangular and Pythagorean fuzzy environments, and supplier rankings were calculated and compared. Solely considering environmental criteria, [PERSON] [39] proposed a green supplier selection model based on the AHP under the interval type-2 fuzzy environment model. The interval type-2 fuzzy sets were found to handle uncertainty well because their membership functions were also fuzzy numbers. [PERSON] and [PERSON] [40] considered ethics as a dimension of sustainability in purchasing activity and supplier selection and proposed an AHP-TOPSIS approach to tackle uncertainty and both quantitative and qualitative data. The AHP was applied to find the importance weights of the criteria and sub-criteria, and the TOPSIS was used to determine the ranking of the suppliers. [PERSON] et al. [41] proposed a fuzzy MCDM approach for selecting the most sustainable supplier. The sustainable supplier selection was decomposed hierarchically into dimensions and criteria, and the criteria weights and the alternative performance with respect to each criterion were evaluated by using linguistic terms and were further transformed into triangular interval-valued fuzzy sets. To consider the decision makers' risk preferences, cumulative prospect theory was applied to rank the suppliers. Identifying suitable materials is an important issue in the conception and improvement of new products. Material selection is regarded as an important MCDM problem because multiple criteria need to be considered from different dimensions [42]. A poor choice of materials can negatively impact a company's success. [PERSON] and [PERSON] [42] proposed a fuzzy multi-criteria group decision-making approach for material selection. QFD was used to incorporate customer requirements in the evaluation process, and 2-tuple fuzzy linguistic representation and linguistic hierarchies were used to unify the data provided by experts. The most suitable alternative could be selected using the fuzzy complex proportional assessment method. [PERSON] et al. [43] studied the design partner selection in green product collaboration design, and a two-stage MADM framework was proposed. In stage one, the evaluation indices were determined by using a Fuzzy Decision-Making Trial and Evaluation Laboratory (fuzzy DEMATEL) approach.