Higher education institutions (HEIs) have voiced growing concerns about sustainability issues since Agenda 2030 was approved, but this is not enough for societal stakeholders seeking and delivering innovation and excellence. The 17 Sustainable Development Goals (SDGs) were adopted by all UN Member States in 2015 as a universal call to action, and pose a challenge for HEIs as for the efforts made to fulfill them and knowing how to assess their performance. However, the metric management system implemented by HEIs quickly led to rankings emerging, which compare HEIs to metrics not related to the sustainability dimensions of the 17 SDGs. The main aim of the paper is to assess the level of reporting and alignment of SDG achievements with the overall the Times Higher Education (THE) ranking score. For this purpose, our study (i) models and quantifies the impact of HEIs’ disclosure of SDG information on HEIs’ overall THE Impact Rankings score, (ii) analyzes whether the best ranked universities are indeed significantly related to different SDGs than other not-so-well-ranked ones, and (iii) models the differences in the overall score and its alignment with distinct SDGs by dimensions, subjects, and geographical regions. In order to do so, a descriptive analysis, non-parametric tests, and linear and logistic regression analyses were performed. Our results reveal that the overall ranking is related to the reporting of HEIs’ SDG achievements. Moreover, the more positive actions related to health, education, industry, responsible consumption and production, climate action, and partnerships there were, the higher the position of HEIs in the general ranking was. However, we found differences between top-ranking universities and others in geographical location, disclosed information, and impact. Thus, the best-ranked universities are more committed to transferring knowledge to industry to satisfy its needs (SDG9), support strong institutions in their countries, and promote peace and justice (SDG16). Finally, SDG9 and SDG17 are the most relevant and constant SDGs when modeling the alignment of SDGs with HEIs’ dimensions (teaching, research, citations, industry income, international outlook) and subjects (technological and social sciences and humanities). HEIs integrating SDG actions into the strategic management of universities and, consequently, reporting their SDG performance to promote sustainability and contribute to sustainable development, is advisable.

As industries evolve towards greater digitalization, integrating Building Information Modeling (BIM) and digital twin technologies presents a unique opportunity to enhance sustainability in industrial infrastructure. This paper formulates a comprehensive set of principles aimed at guiding the sustainable integration of these technologies within the context of modern industrial facilities, often referred to as “Factories of the Future”. The principles are designed to address critical sustainability challenges, including minimizing environmental impact, optimizing resource efficiency, and ensuring long-term resilience. Through a detailed examination of lifecycle management, data interoperability, and collaborative stakeholder engagement, this work provides a strategic framework for leveraging digital technologies to achieve sustainability goals. The principles outlined in this paper not only promote greener industrial practices but also pave the way for innovation in the sustainable development of industrial infrastructure. This framework is intended to serve as a foundation for future research and practical application, supporting the global shift towards more sustainable industrial operations.

The development of digital technologies captures a significant part of the economy and production, as well as business and management processes. Asset owners are given the opportunity to become additionally owners of digital assets, while the need for conceptual approaches and digital asset management is growing. With the increasing application of Building Information Modelling (BIM) for asset management within architecture, engineering, construction and owner-operated (AECO) sector, BIM-enabled asset management has been increasingly attracting more attentions in both research and practice. The problem associated with the development and production of facilities is related to the discrepancy between as-built as-designed and as-is facilities or complex technical systems. During the stages of design, construction, operation and maintenance (O&M), the actually manufactured (i.e. as-built) complex technical object (or production infrastructure) differs, sometimes significantly, from the designed (as-designed), and at the same time inconsistency between the created production and production infrastructure within which it should operate grows. Solving the problem of discrepancy between the actually created and designed facility or the complex technical system, in the absence of digital technologies, requires considerable time for the so-called “trial operation”, during which the discrepancies are eliminated and a mechanism for managing production and production infrastructure in real conditions is developed. With the development of the digital economy, the need for digitalization of asset management is growing. An analysis of existing information technologies shows that there is a possibility of reducing the cost of production and operation of an asset by concentrating the main costs at the design stage. The article discusses basic approaches to organizing the lifecycle management of technical systems, production and infrastructure in the context of global digitalization which become a useful tool for reduction of trial operation time. Further directions of research are formulated

International Facility Management Association (IFMA) traditionally divides the management of real estate into asset, property and facility management. The paper explores how the emergence of building information modelling (BIM) has influenced the distribution of information about the building among the stakeholders. As-built BIM in industrial buildings is a significant part of digital transformation of industrial assets and emergence of Industry 4.0. The tendency of transferring the ownership of information from facility manager to asset manager as well as the increase of transparency is analysed in the recent literature. The development of as-built BIM has given the possibility to the owners of real estate to become not only the owners of the assets themselves but also the owners of digital assets. In order to clarify current situation in the scientific community, the research interest in building information modelling among the studies mentioning facility management, asset management and property management has been analysed. The role of information about the building components as well as practical examples of operational expenditures reduction are explored and discussed.

The current industrial facility market necessitates the digitization of both production and infrastructure to ensure compatibility. This digitization is presently accomplished using Building Information Modeling and digital twin technologies, as well as their integrated usage, which enhances convergence and adds further value to facility assets. However, these technologies primarily focus on the physical components of industrial facilities, neglecting processes, requirements, and functions. To address these gaps, the inclusion of the Model-Based System Engineering approach, a proven benchmark in systems engineering, is essential. This inclusion is the main objective of this research. This article outlines methods and principles for integrating Model-Based System Engineering into the informational modeling of existing industrial facilities to address current market gaps. It offers practical steps for such integration and compares it to other methods, positioning Model-Based System Engineering as a pivotal tool for enhancing the value of industrial facility digital assets. The main findings include the proposal of BIM and MBSE integration, which aims to create a competitive advantage for industrial facilities by improving customer service and operational efficiency, requiring collaboration from various stakeholders.

In today’s business landscape, the volume of transaction data is rapidly increasing. This study explores the integration of Point of Sale (POS) and Radio-Frequency Identification (RFID) technologies to enhance the analysis of customer transactions using big data tools. By leveraging these technologies, businesses can extract valuable insights to improve processes, optimize inventory, and boost customer satisfaction. The research employs an object—subject management approach, which facilitates real-time decision-making by merging retail transactions of the clients with their movement patterns. An experiment involving around 7000 customers demonstrates the effective collection and processing of POS and RFID data, highlighting the benefits of integrating these data streams. Key metrics, such as time spent in different store sections, provide deeper insights into consumer behavior. The findings reveal the potential of these technologies to transform retail services, offering opportunities for demand forecasting, risk management, and personalized customer experiences. The study concludes that merging POS and RFID data opens new avenues for developing management solutions aimed at enhancing customer engagement and the operational efficiency of the retailer. Future research will focus on further elaborating these solutions to maximize the benefits of integrated data analysis.