Abstract
Infrastructure construction companies encounter numerous challenges in managing large and dispersed teams, along with fragmented or non-existent operational data. These challenges often result in delays, inefficiencies, and over-budget projects. Road pavement works are an example of this, as they heavily rely on expensive heavy construction equipment that requires detailed planning and real-time adjustments. Also, pavement quality is closely linked to the quality of the asphalt mixture in terms of viscosity and compactability, which is significantly influenced by temperature. This paper describes the features, challenges and results of a road paving real-time management system that was conceived in a co-creation environment with a construction company. Such a partnership has allowed to specify the requirements of such an application aligned with the identified needs of a real-world development. According with the state-of-the-art, this innovative system is unique in the way it is manufacturer-agnostic and designed to be compatible with most situations. It is also data production-oriented to allow future developments that may provide business analytics or scientific research in the road paving area. This work also presents the development of sensors such as a high precision geolocalized infrared matricial temperature sensor for the application of the bituminous mixture, the data and communication structure, and a web-based interface that manages the construction projects for different stakeholders.

Abstract
Recently, we have been observing a significant evolution in products, machines, and manufacturing processes, towards a more digital and interoperable reality. In this sense, the power transformers sector has also been evolving to develop smart transformers for the future, capable of providing the digital capabilities to leverage new services and features that follow its entire life cycle, from the design and manufacturing to the use and dismantling/recycling. In this sense, this paper aims to present and demonstrate how an innovative digital twin platform can be used in a secure and trustable way for the enhancement of the power transformers’ performance and potential lifespan, enabling, at the same time, the promotion of new business models. A real use case is also presented to demonstrate the applicability of Asset Administration Shells (AAS) for power transformer life cycle management, as well as the use of the International Data Spaces (IDS) for the secure and trustable horizontal interoperability along with the different actors of the value chain, from the manufacturers to the power network and maintenance services companies.

Abstract
This paper aims to thoroughly discuss the use of Digital Twin technology in complex operations environments, highlighting its potential applications and the research challenges that need to be addressed. This is necessitated by the fact that currently there is no comprehensive literature review and framework for implementing Digital Twin technology in complex operations environments. Furthermore, existing interpretations of DT implementation are inadequately detailed and not very informative in this area. This may be a consequence of the difficulties of collecting and extracting useful information from data in real-time. Another drawback worth mentioning is that Digital twins at the moment center on an individual or isolated part instead of integrating the whole system and no current work talks about this holistic approach. This paper will focus on Digital Twins in complex operations environments and their applications. A review of scientific literature on the use of Digital Twins in complex operations environments is performed and the articles are categorized by the problems and challenges that they address requiring DT as a solution. A selection of papers that focus on this topic and represent the current situation of research will be emphasized. In conclusion, this work will be utilized as a baseline study to propose a Digital Twin reference framework, which eventually leads to implementing and evaluating a comprehensive Digital Twin methodology in complex systems. © 2023 IEEE.

Abstract
In today's competing business market, companies are constantly challenged to dynamically adapt to customer expectations by diminishing the time response that goes from the beginning of the business opportunity to the satisfaction of the customer need. Simultaneously, there is increased recognition of the advantages that companies obtain in focusing on their core business and seeking other competencies through partnerships with other partners by forming collaborative networks. These new collaborative organizational structures require a new set of methods and tools to support the management of manufacturing processes across the entire supply chain. The present paper addresses the collaborative production planning problem in networks of non-hierarchical, decentralized, and independent companies. By proposing a collaborative planning intelligent framework composed of a web-based set of methods, tools, and technologies, the present study intends to provide network stakeholders with the necessary means to responsively and efficiently address each one of the market business opportunities. Through this new holistic framework, the managers of the networked companies can address the challenges posed during collaborative network formation and supply chain production planning.

Abstract
The successful adoption of Industry 4.0 technologies by firms requires them to formulate a digital strategy and implementation roadmap. An established approach to assess firms' needs towards digitalization is through maturity models. While there is a large number of maturity models in the literature, they present several limi-tations related to their generalizability and theoretical foundations. Our study aims to build and empirically validate an Industry 4.0 digital maturity model, based on the Technology-Organization-Environment framework. We conducted a systematic literature review of 55 digital maturity models, which we synthesized to create an integrated digital maturity assessment model. We tested our model through a focus group with industry experts and 24 companies from various manufacturing sectors. Our review suggests that existing digital maturity models have underestimated the relevance of the Environment dimension. Our empirical data suggests that companies often invest in digital technologies without considering critical organizational and environmental constraints.

Abstract
Circular Economy business models rely on complex data exchange between organizations, which require a supporting digital infrastructure facilitating the circularity-related processes. In a digital platform context, value is generated not by the underlying technologies but by its allied ecosystem: community, users, developers, and integrated applications. These ecosystems come with an intrinsically complex interorganisational structure often overlooked during the development phase, leading to low platform adoption and obsolete platforms in the mid to long-term. Developed through a combined action-research and design science research approach, we propose a framework to support the design and deployment of circular economy ecosystems from a sociotechnical perspective, including practices from the requirements engineering, circular innovation ecosystems and digital platforms literature. © 2023, IFIP International Federation for Information Processing.