The most critical decisions usually involve several decision makers with different roles and opportunities to commit key resources. Several group decision-making (GDM) approaches can support the identification of a joint or compromise decision in less conflicting settings, where there is a group of subjects (e.g’, partners) who pursue a common overall objective. However, considering the uncertainty in future events and complexity of modern-day systems, decision processes do not always produce beneficial results or give the participants a positive perception of their role in the process. Group decision-making should then take into consideration some aspects that might insure future resilience and sustainability, particularly the achievement of the objectives in view of future risks and the transparency and participation that are needed to limit problems in the implementation phase of the decision. The literature survey presented in this study identified a research gap regarding GDM. Differently from traditional GDM, which was first discussed in the early 1980s and whose body of knowledge is pretty defined, resilient and sustainable GDM (R&S GDM) is fairly new. The main objective of this study is then identifying the main attributes for supporting sustainable and resilient group decisions. To this aim, a preliminary focused systematic review was conducted to study the existing group decision-making methods in the literature and how the concepts of sustainability and resilience have been employed. After defining the search keywords and exclusion criteria for the individuation of the articles, the first screening process was carried out and the most relevant articles were selected. The last steps of the systematic review were the classification of the articles and the full paper examination to extract the main factors of R&S GDM. Seven attributes were listed as the key factors of R&S GDM. In light of those factors, a group decision process concerning an injection moulding line in Tajikistan was investigated. The case study highlighted that over self-confidence, information flow and transparency were the main reasons for faulty decisions, thus suggesting that information system and information fluidity play an important role in R&S GDM. Finally, the most important managerial implications of R&S GDM are reported.

The mobility referred to the University is a significant part of the urban mobility in Trieste. Therefore a specific project was performed to analyze the main problems, to understand the preference structure of the users and to define some possible solutions to improve the accessibility of the University and to reduce urban congestion, mainly through sustainable transport modes. The survey pointed out features and preferences of different user groups, which were explicitly considered in the AHP assessment framework, and allowed to define criteria and to fix the weights. Also the presence of more than one decision maker was explicitly included in the hierarchy, to model the different impact of different user groups on the decision makers. As a result, the ranking of the alternatives has been defined, which has been taken into account by the decision makers for their planning choices. From a methodological point of view, the specific structure of the AHP hierarchy allowed to model the decisional problem even if a more complex ANP approach would be perhaps more suitable to consider interactions between nodes in this group decision problem

Purpose: Industry 4.0 technologies influence how production is planned, scheduled, and controlled. In literature, different classifications of the tasks and functions of production planning and control (PPC) exist, of which one is the German Aachen PPC model. This research aims to identify and classify current Industry 4.0 approaches for planning and controlling production processes and to reveal researched and unexplored areas of the model.Design/methodology/approach: In an exploratory literature review, we review and classify 48 publications on a full-text basis with the Aachen PPC model's tasks and functions. Two cluster analyses reveal researched and unexplored tasks and functions of the Aachen PPC model. Additionally, we give a summary of each reviewed publication.Findings: We propose a cyber-physical PPC architecture, which incorporates current Industry 4.0 technologies, current optimization methods, optimization objectives, and disturbances relevant for realizing a PPC system in a smart factory. Current approaches focus on the in-house PPC, particularly on the control using real-time information from the shop floor. We propose future research directions for the unexplored tasks and functions of the Aachen PPC model.Research limitations/implications: The selection of search terms and the texts' interpretation is based on an individual assessment. The revelation of unexplored tasks and functions of the Aachen PPC model might have a different outcome if the search term combination is parameterized differently.Originality/value: Using the Aachen PPC model, which holistically models PPC, the findings give comprehensive insights into the current advances of tools, methods, and challenges relevant to planning and controlling production processes under Industry 4.0.