This study aims to survey the bibliometric properties of distributed decisions, decentralized decisions, and fuzzy articles published between 1995 and 2023 in the Web of Science (WoS) database. During the analysis process, the keywords “distributed decision, decentralized decision, and fuzzy” were scanned in all languages, both in the titles and the content of all publication types. As a result of the analysis, 79 articles in all fields comprised the dataset. The most used keywords in the articles were related to the distributed decision, decentralized decision, and fuzzy logic, and the most frequently cited publications were examined using the social network analysis method, which uses VOSviewer (version 1.6.19) to visualize the relationships. The study’s goal on “active researchers, active journals, journal metrics, title document type, active countries, and active institutions” was to look at the words most frequently used in articles on distributed, decentralized, and fuzzy logic. The social network analysis represented the relationships between these keywords and the most frequently cited publications. The findings demonstrated a significant correlation between using these keywords in academic literature and their contribution to this field’s research. These results can assist researchers in finding potential partners and keeping up with current research trends. Overall, this study offers important new perspectives on the state of research on fuzzy logic, distributed decision making, and decentralized decision making.

The world that we live in where the social and organizational life rapid social and cultural transformations are experienced, and the intensities of change and competition are intensely perceived has a dynamism. In this dynamism, every human being is a part of an organization. In these organizations, there is a culture which is defined in various ways by various thinkers and it is a rather complex concept. However, all definitions have reached the conclusion that the culture is a common entity shared with a community. In the 1980s, the concept of organizational culture has emerged. While many formal definitions exist, organizational culture is basically a term used to describe the environment where people work and the influence it has on how they think, act, and experience work. Therefore, organizational culture is stated as a system of values, behaviors, habits, norms, beliefs and that direct the behaviors of individuals in an organization. As each individual has a unique personality, every organization has its own personality that distinguishes it from other organizations. Hence, organizational culture consists of several abstract and complementary factors. Literature has shown that there are many factors affecting the success of organizational culture. The prioritization of these factors for the organizations and the effective use of the available resources are gaining importance at this stage. At this stage, different approaches are taken in the literature to prioritize and sort the criteria. MCDM approach which is one of the most prominent approaches was used in this study. The proposed approach was tested based on the opinions of the decision makers and the results were shared.

Nowadays, population growth and technological advancements are contributing to the growth of global electricity demand. The aim of this research is to form a new distributed decision-making protocol (DDM) to increase the reliability and sustainability of HES. Using this DDM, it is intended to minimize the effects of planned and unplanned production interruptions on the independent and autonomous energy producers within the HES. By implementing this protocol, energy producers in the HES are intended to collaborate and achieve mutual benefits in cases where they are not able to fulfill the needs of their customers. As a case study, there are sixteen independent power plants that are simulated as CN enterprises in four independent communities. The DDM protocol aims to manage the collaboration among independent energy producers, to use the sources of the producers effectively, to increase the profit rates, and to optimize the sustainability of the energy supply for each community. The results demonstrates that the proposed protocol gives satisfying results under the criteria of profit, demand fulfillment rate, sustainability, and resource utilization both for each energy producers and entire HES. Moreover, the increase in collaboration rate within each community increased these parameters by average of 90%.