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The purpose of this paper is to review cases of artificial reefs built through additive manufacturing (AM) technologies and analyse their ecological goals, fabrication process, materials, structural design features and implementation location to determine predominant parameters, environmental impacts, advantages, and limitations.

The review analysed 16 cases of artificial reefs from both temperate and tropical regions. These were categorised based on the AM process used, the mortar material used (crucial for biological applications), the structural design features and the location of implementation. These parameters are assessed to determine how effectively the designs meet the stipulated ecological goals, how AM technologies demonstrate their potential in comparison to conventional methods and the preference locations of these implementations.

The overview revealed that the dominant artificial reef implementation occurs in the Mediterranean and Atlantic Seas, both accounting for 24%. The remaining cases were in the Australian Sea (20%), the South Asia Sea (12%), the Persian Gulf and the Pacific Ocean, both with 8%, and the Indian Sea with 4% of all the cases studied. It was concluded that fused filament fabrication, binder jetting and material extrusion represent the main AM processes used to build artificial reefs. Cementitious materials, ceramics, polymers and geopolymer formulations were used, incorporating aggregates from mineral residues, biological wastes and pozzolan materials, to reduce environmental impacts, promote the circular economy and be more beneficial for marine ecosystems. The evaluation ranking assessed how well their design and materials align with their ecological goals, demonstrating that five cases were ranked with high effectiveness, ten projects with moderate effectiveness and one case with low effectiveness.

AM represents an innovative method for marine restoration and management. It offers a rapid prototyping technique for design validation and enables the creation of highly complex shapes for habitat diversification while incorporating a diverse range of materials to benefit environmental and marine species’ habitats.

This papers aims to study lattice structures in terms of geometric variables, manufacturing variables and material-based variants and their correlation with compressive behaviour for their application in a methodology for the design and development of personalized elastic therapeutic products.

Lattice samples were designed and manufactured using extrusion-based additive manufacturing technologies. Mechanical tests were carried out on lattice samples for elasticity characterization purposes. The relationships between sample stiffness and key geometric and manufacturing variables were subsequently used in the case study on the design of a pressure cushion model for validation purposes. Differentiated areas were established according to patient’s pressure map to subsequently make a correlation between the patient’s pressure needs and lattice samples stiffness.

A substantial and wide variation in lattice compressive behaviour was found depending on the key study variables. The proposed methodology made it possible to efficiently identify and adjust the pressure of the different areas of the product to adapt them to the elastic needs of the patient. In this sense, the characterization lattice samples turned out to provide an effective and flexible response to the pressure requirements.

This study provides a generalized foundation of lattice structural design and adjustable stiffness in application of pressure cushions, which can be equally applied to other designs with similar purposes. The relevance and contribution of this work lie in the proposed methodology for the design of personalized therapeutic products based on the use of individual lattice structures that function as independent customizable cells.

The purpose of this paper is to identify the areas and logic of integration of different stakeholders using different methods and to analyse their applicability and challenges in practical projects. The main aim is to describe how these different methods impact value creation.

Action design research was carried out in a large hospital construction project where the first author acted as an “involved researcher” and the second author acted as an “outside researcher”. Two workshops were organised to evaluate the direct and indirect challenges and benefits of the applied four methods and to explain how different methods enable value creation.

All the studied methods provide good results in terms of usability and commitment to the aims of the project, thus delivering the direct benefits expected. Process, people and tools logic works well in this case project when applying the methods properly. Significant evidence was provided on secondary deliverables of the methods, and all analysed methods had a significant impact in the area of leading people, clarifying what “focus on people” means and how it is enabled.

Focus on people can be achieved through different operative methods if applied in the right way. It is necessary to select the most suitable methods based on all the direct and indirect deliverables.

This case project offered a platform to analyse integration methods in a real-life project using the collaborative contract method. The authors were able to participate in the analysis by taking action from the very beginning of the project in terms of training, learning, continuous development and coaching of these methods and evaluating the applicability.

In this study, the authors propose a novel digital twinning approach specifically designed for controlling transient thermal systems. The purpose of this study is to harness the combined power of deep learning (DL) and physics-based methods (PBM) to create an active virtual replica of the physical system.

To achieve this goal, we introduce a deep neural network (DNN) as the digital twin and a Finite Element (FE) model as the physical system. This integrated approach is used to address the challenges of controlling an unsteady heat transfer problem with an integrated feedback loop.

The results of our study demonstrate the effectiveness of the proposed digital twinning approach in regulating the maximum temperature within the system under varying and unsteady heat flux conditions. The DNN, trained on stationary data, plays a crucial role in determining the heat transfer coefficients necessary to maintain temperatures below a defined threshold value, such as the material’s melting point. The system is successfully controlled in 1D, 2D and 3D case studies. However, careful evaluations should be conducted if such a training approach, based on steady-state data, is applied to completely different transient heat transfer problems.

The present work represents one of the first examples of a comprehensive digital twinning approach to transient thermal systems, driven by data. One of the noteworthy features of this approach is its robustness. Adopting a training based on dimensionless data, the approach can seamlessly accommodate changes in thermal capacity and thermal conductivity without the need for retraining.

This paper presents a new and well-structured framework that aims to assess the current environmental impact from a Greenhouse Gas (GHG) emissions perspective. This tool includes a new set of Lean Key Performance Indicators (KPIs), which translates the well-known logic of Overall Equipment Effectiveness in the field of GHG emissions, that can progressively detect industrial losses that cause GHG emissions and support decision-making for implementing improvements.

The new metrics are presented with reference to two different perspectives: (1) to highlight the deviation of the current value of emissions from the target; (2) to adopt a diagnostic orientation not only to provide an assessment of current performance but also to search for the main causes of inefficiencies and to direct improvement implementations.

The proposed framework was applied to a major company operating in the plywood production sector. It identified emission-related losses at each stage of the production process, providing an overall performance evaluation of 53.1%. The industrial application shows how the indicators work in practice, and the framework as a whole, to assess GHG emissions related to industrial losses and to proper address improvement actions.

This paper scrutinizes a new set of Lean KPIs to assess the industrial losses causing GHG emissions and identifies some significant drawbacks. Then it proposes a new structure of losses and KPIs that not only quantify efficiency but also allow to identify viable countermeasures.

This paper aims to provide an overview of the application of blockchain to agri-food supply chains, including key issues and trends. It examines the state of the art and conceptual structure of the field and proposes an agenda to guide future research.

This article performs a bibliometric analysis using VOSviewer software on a sample of 205 articles from the WoS database to identify research trend topics.

The number of publications in this area has increased since 2020, which shows a growing research interest. The research hotspots are related to the integration of blockchain technology in the agri-food supply chain for traceability, coordination between all actors involved, transparency of operations and improvement of food safety. Furthermore, this is linked to sustainability and the achievement of the sustainable development gtoals (SDGs), while addressing key challenges in the implementation of blockchain-based technologies in the agri-food supply chain.

The application of blockchain in the agri-food supply chain may consider four key aspects. Firstly, the implementation of blockchain can improve the traceability of food products. Secondly, this technology supports sustainability issues and could avoid disruptions in the agri-food supply chain. Third, blockchain improves food quality and safety control throughout the supply chain. Fourthly, the findings show that regulation is needed to improve trust between stakeholders.

The paper provides a comprehensive overview of the blockchain phenomenon in the agri-food supply chain by optimising the search criteria. Moreover, it serves to bridge to future research by identifying gaps in the field.

This paper aims to identify and empirically analyze useful and applicable metrics for measuring and managing the sustainability performance of small and medium-sized enterprises (SMEs).

To achieve the objective of the paper, potential metrics were adopted from previous research related to industrial sustainability and an empirical analysis was carried to assess the applicability of the metrics by collecting empirical data from Italian footwear SMEs using a structured questionnaire. The SMEs were selected using a convenience sampling method.

The results of the within-case analysis and the cross-case analysis indicate that the majority of the metrics were found to be useful and applicable to each of the SMEs and across the SMEs, respectively. These metrics emphasized measuring industrial sustainability performance related to financial benefits, costs and market competitiveness for the economic sustainability dimension; resources for the environmental sustainability dimension; and customers, employees and the community for the social sustainability dimension.

Apart from the within-case analysis and cross-case analysis, it was not possible to conduct statistical analysis since a small number of SMEs were accessible to collect empirical data.

The findings of the paper have considerable academic, managerial and policy implications and will provide a theoretical basis for future research on measuring and managing industrial sustainability performance. By providing a set of empirically supported metrics based on the triple bottom line approach (i.e. economic, environmental and social metrics), this paper contributes to the existing knowledge in the field of industrial sustainability performance measurement.

This study aims to identify the major factors influencing the consumers to prefer milk products and also to analyze the awareness level of the Indian consumers.

In this study, the data is obtained through a structured questionnaire from Indian consumers considering convenience sampling under the nonprobability sampling technique. The consumer preference is explained using a multiple-regression model followed by analysis of variance (ANOVA), which shed insight on the significant differences between the variables that influence consumer preference for dairy products.

Investigation is done to analyze the factors influencing the consumers' buying behavior toward milk and its products. The results showed that quality, health consciousness, price and availability are the most influencing factors to buy milk products. Quantity of milk showed a significant relationship between age, monthly income and family size.

This study helps marketing managers to frame the marketing strategies based on consumer preference, quality, health consciousness, price and availability. The research outcome will not only be advantageous for the entrepreneurial perspective but also takes care of consumer likeliness. Though the research reveals the opinion of Indian consumers, it limits the likeliness of the western world. Because of the scarcity of resources, several dairy products are unexplored, which could pave the future scope of research.

The novelty of this study is to identify the quality, health consciousness, price and availability are the most influencing factors to buy milk products considering ANOVA and the multiple regression model.

The purpose of this paper is to investigate the most recurrent variables characterizing the collaborative relationships of industrial symbiosis (IS) (hereinafter also referred to as “anatomic” variables) established in the attempt to adopt circular economy (CE) by collecting evidence from a rich empirical set of implementation cases in Italy.

The current literature on IS was reviewed, and a content analysis was performed to identify and define the “anatomic” variables affecting its adoption in the circular economy. We followed a multiple-case study methodology investigating 50 cases of IS in Italy and performed a content analysis of the “anatomic” variables characterizing each case.

This research proposes the “anatomic” variables (i.e. industrial sectors involved, public actors involvement, governmental support, facilitator involvement and geographical proximity) explaining the cases of IS in the circular economy. Each “anatomic” variable is discussed at length based on the empirical evidence collected, with a particular reference to the impact on the different development strategies (i.e. “bottom-up” and “top-down”) in the cases observed.

Current literature on IS focuses on a sub-set of variables characterizing collaboration in IS. This research builds on extant literature to define a new framework of five purposeful “anatomic” variables defining IS in the circular economy. Moreover, we also collect and discuss a broad variety of empirical evidence in what is a still under-investigated context (i.e. Italy).

Measuring shared value (SV) created in innovation ecosystems (IEs) is increasingly relevant but complex, given the multidimensional and multiactor nature of both concepts, which challenges traditional performance measurement systems (PMSs). Moving from this gap, the authors propose an integrated approach to extend the balanced scorecard (BSC) for measuring and monitoring SV creation at IE level.

The proposed approach combines the most recent contributions on PMS in IEs and SV to define perspectives and dimensions that are better suited to deal with the nature of both IEs and SV. The approach is also applied to the real case (Alpha) of an Italian IE through a step wise method. Starting from the IE vision, the authors identify in the strategy map the specific objectives related to each perspective/dimension combination and then associate a performance indicator with each objective.

The resulting SV BSC is composed of indicators interconnected along different perspectives and dimensions. The application of the approach to the real case proves its feasibility and highlights characteristics, advantages and disadvantages of the SV BSC when used at IE level. The authors also provide guidelines for its application to other IEs.

The study contributes to the research on PMS by introducing and applying to a real case an integrated approach to assess SV in IEs, overcoming the shortcomings of PMS framed for single firms. It can be of interest for both researchers in the field of ecosystems value creation and practitioners managing or promoting such complex structures.