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
Make-to-order (MTO) supply chains (SC), common in aerospace industries, are very complex compared to mass production chains. Moreover, one of the significant long-term challenges is sustainability performance across its entire supply chain. However, this is not an easy task given the complexity involved, so decision support tools are fundamental instruments in understanding the entire supply chain from a sustainability performance perspective. Using simulation as a research method, this article proposes a hybrid and hierarchical performance assessment model, considering key sustainability indicators. The model is hybrid due to the use of different simulation methods- System Dynamics (SD), Discrete Event Simulation (DES), and Agent-based simulation (ABS). The model is applied to an aerospace manufacturer's real case to assess the sustainability performance of alternative SC. Unlike existing contributions, this work addresses the make-to-order supply chain from a sustainability performance perspective and does not compromise the representation of the diverse manufacturing functions and resources.

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.

Abstract

Abstract
Digital Twin (DT) is recognized as a key enabling technology of Industry 4.0 and 5.0 and can be used in collaborative networks formed to fulfillment of complex tasks of the manufacturing industry. In the last years, the variety and complexity of DTs have been significantly increasing with new technologies and smarter solutions. The current definition of DT, such as cognitive, hybrid, and others, embraces a wide range of solutions with different aspects. In this sense, this article discusses DT definitions and presents a five-dimensional analytical framework to classify the different proposals. Finally, to better understand the proposal, we analyzed 12 articles using the analytical framework. We argue this research may help researchers and practitioners to better understand digital twins and compare different solutions.