Digital transformation (DT) has become vital for companies trying to remain competitive in the recent ever-changing technological environment. DT is the integration of digital technologies into all disciplines of business from regular activities to strategic decision making. Risk management planning requires projects to assess possible risks that may negatively or positively affect a DT project. The purpose of the study is to introduce a hybridized decision support system (DSS) by combining the distance measure, ranking comparison (RANCOM) model and additive ratio assessment (ARAS) approach in the context of a picture fuzzy set (PFS). In this framework, the decision experts’ significance values are computed using a picture fuzzy score function-based formula. With the combination of objective weight using distance measure and subjective weight through the RANCOM model, a combined weight-determining approach is developed to determine the significance values of considered DT risks under picture fuzzy environment, while a hybrid ARAS model is developed to evaluate and rank DT projects from the risks perspective. To exhibit the feasibility of the introduced framework, a case study of a DT projects assessment problem is discussed in the context of picture fuzzy sets. A sensitivity study is also discussed over different values of the strategy coefficient, which confirms the strength of the proposed model. Further, a comparison with the existing picture fuzzy information-based methods is presented to prove the robustness of the developed decision-making framework.

This research proposes a novel way to improve Process Failure Modes and Effects Analysis (PFMEA) by using the Fuzzy RAnking based on the Distances And Range (FRADAR) method to prioritize activities for mitigating or eliminating failure modes in the automotive industry. The suggested approach seeks to improve classic PFMEA by using fuzzy sets to better assess risk-related criteria and their inherent uncertainty. The criteria used to prioritize actions for mitigating failure modes include the Action Priority (AP) and Risk Priority Number (RPN) approach, as well as the cost-effectiveness of actions, the time required to resolve issues, and their impact on production, all of which are assessed by a PFMEA team using predefined linguistic terms and suggestions. Applied to a case study of a Tier-1 automotive supplier, the FRADAR method effectively ranks failure modes, providing a structured and precise approach for action prioritization. The results highlight the model’s potential to enhance decision-making processes, offering a robust framework for implementing PFMEA recommendations in the automotive industry.

When selling food products, it's important to choose the appropriate sales channel. These channels connect producers with consumers. The aim of this study was to select a channel for the sale of cabbage to end customers. In this paper, six different sales channels that are used in the Semberija region for the sale of cabbage were observed. These sales channels were evaluated using 11 different criteria. In order to choose the sales channel that best meets the set objectives, a fuzzy set approach was used. This approach was chosen because qualitative criteria were used and expert ratings were in the form of linguistic values. Based on the input of seven experts who are professors at agricultural faculties in Bijeljina, it was found that consumer habits were the most important criterion, followed by the criterion compliance with environmental standards, while the smallest weight value was given to the criterion delivery method. Using the RAWEC (Ranking of Alternatives with Weights of Criterion) method, it was shown that online sales yield the best results, after that follows Producer-sales agent-consumer, while according to experts, the sales channel is the best rated Producer-wholesaler-retailer-consumer. This is because various tools can be utilized on the Internet for selling agricultural products. Based on the conducted research, the contribution of this study lies in the selection of sales channels using the integration of the MEREC and RAWEC methods.