The transition to Industry 5.0 marks a paradigm shift towards innovation ecosystems that prioritize human-centricity, sustainability, and resilience. This paper advances the understanding of innovation ecosystem governance by introducing the concept of the “Bridge Maker” – a strategic intermediary that plays a pivotal role in aligning diverse stakeholders, fostering collaborative governance, and embedding Industry 5.0 values systemically across ecosystems. Grounded in insights from Complex Adaptive Systems (CAS) theory, Open Innovation (OI), and recent developments in ecosystem orchestration and governance, the Bridge Maker (BM) is positioned as a crucial enabler of ecosystem adaptability and success.
Through a conceptual analysis, this paper addresses two primary research questions: (1) How do Bridge Makers align stakeholders to drive collaboration and innovation within human-centered Industry 5.0 ecosystems? (2) What role do Bridge Makers play in embedding sustainability and human-centric values as systemic ecosystem features? Drawing from recent theoretical advancements (Chesbrough, 2003; Holgersson et al., 2022; Tedesco, 2019) and extending the Adaptive Open Innovation Systems (AOIS) framework, the study proposes a model highlighting the competencies, behaviors, and governance mechanisms required for effective Bridge Making.
The findings suggest that BM operates through trust-building, sense-making, strategic foresight, and adaptive orchestration practices that promote long-term ecosystem resilience. In doing so, they bridge institutional gaps, overcome organizational inertia, and create the conditions necessary for sustainable innovation trajectories. The paper offers practical implications for innovation managers, policymakers, and educators seeking to operationalize Industry 5.0 principles within complex multi-actor environments.
Finally, the study calls for further empirical research to explore the dynamic practices of BM across various industry contexts and to develop actionable guidelines for their identification, training, and support within innovation ecosystems.

The transition toward Industry 5.0 has brought forth a new paradigm within maritime logistics and port governance, where the focus shifts beyond automation to embrace resilience, sustainability, and above all, human-centric innovation. In this context, Port Authorities, particularly those operating under the Landlord model, face unprecedented demands to align infrastructural and technological transformation with comprehensive workforce development strategies. While infrastructure and digital systems have been historically prioritised, the capabilities and adaptability of the human workforce—especially blue-collar maritime workers—have received comparatively less strategic attention.
This study investigates the alignment of workforce development with Industry 5.0 principles, focusing on the evolving competencies, training gaps, and strategic responses of Port Authorities operating under the Landlord model. Framed by the Resource-Based View and the Dynamic Capabilities Theory, the research explores how human capital—particularly blue workers—functions as a core asset for competitive advantage, technological readiness, and organisational resilience.
Employing a qualitative methodology, the study draws on twelve semi-structured interviews with executives, HR managers, and operational staff from Italy’s maritime sector. Thematic content analysis revealed three core patterns: a widespread digital skills gap among blue workers, the fragmented nature of training initiatives across port authorities, and a misalignment between strategic HR objectives and operational governance.
Findings suggest that for Port Authorities to meet the expectations of Industry 5.0, workforce development must be fully integrated into port governance frameworks. Human-centric innovation, environmental sustainability, and digital transformation are not achievable without a skilled and empowered workforce.
The performed analysis additionally underscores the need for cultural and institutional shifts that reframe blue workers as, active agents of technological co-creation and environmental stewardship.
Ultimately, the study advocates for the establishment of structured, collaborative skilling frameworks, potentially through regional Port Skills Councils or transnational maritime academies, to harmonise training standards and close capability gaps. Such interventions would not only strengthen organisational performance but also affirm the role of Port Authorities as key enablers of a resilient and inclusive maritime ecosystem in line with Industry 5.0 values.

Artificial Intelligence (AI) is rapidly transforming organizational practices and enabling more sustainable business models, especially in the context of the circular economy. While its potential is widely acknowledged, empirical evidence on the factors that influence AI adoption and its actual impact on circular economy practices—particularly in the context of small and medium-sized enterprises (SMEs)—remains limited. This study investigates the drivers of AI adoption among innovative Italian SMEs and assesses how AI contributes to the implementation of circular economy strategies. Grounded in the Unified Theory of Acceptance and Use of Technology (UTAUT), the study explores the role of four key constructs—Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions—in shaping AI adoption decisions. It also examines the extent to which AI adoption promotes circular economy practices. The empirical analysis is based on data collected through a structured online questionnaire distributed to 1,664 innovative SMEs across Italy, of which 52 provided complete responses. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), a technique particularly suitable for testing complex models with small to moderate sample sizes. The findings partially validate the proposed theoretical framework. Performance Expectancy, Social Influence, and Facilitating Conditions are found to significantly influence AI adoption, while Effort Expectancy does not emerge as a significant predictor—suggesting that ease of use is less critical, possibly due to growing digital literacy or available technical support. Most importantly, the results show that AI adoption positively affects circular economy practices, supporting the view of AI as not only a technological asset but also a strategic enabler of sustainability. This study contributes to the literature by bridging the gap between technology adoption theories and circular economy research. It also offers practical insights for managers and policymakers aiming to promote digital and sustainable transitions. Emphasizing AI’s strategic value, the study encourages investment in both technological infrastructure and supportive organizational environments to foster innovation and sustainable development.

Circular economy has emerged as an industrial approach that aims to overcome the traditional “take-make-dispose” economic model, which is based on the intensive extraction of raw materials and the design of products with a limited lifespan. The circular economy approach consists in a closed system in which products, materials and resources are continuously reused, remanufactured and recycled. The implementation of circular economy principles in companies requires a gradual redesign of products, which consists of a concurrent design of products and related manufacturing processes that enhance competitiveness measures, rationalize product/process/resource design decisions and improve operational efficiency in product development. Given this premise, the transition of companies towards a circular economy paradigm challenges companies to rethink their linear approach of doing business, leading to the research dilemma of answering: Is it economically convenient for a company, in terms of economic margin, to develop circular products starting from a linear positioning? To answer this research question, an agent-based model and simulator (ABM) has been developed characterized by four kinds of heterogeneous firms: the supplier, the manufacturer, the user and the recycler.
The adoption of an agent-based model, which is coherent with the approaches of complexity science, allows for investigating the phenomenon considering its complex nature, and the consequent dynamic non-linear relations among the various actors involved: manufacturers, suppliers, customers and consumers, recyclers. Results show that the manufacturer only partially follows consumer sentiment, as it retains a large proportion of linear products. Even when consumer sentiment is low, it is in the manufacturer’s interest to move even slightly towards circular products.

In this dynamic and full-opportunity world, firms must face challenges in markets and technologies. One of the main assets that firms can use to address these challenges is innovation, and an important element is to define the most appropriate innovation strategy. Inside innovation strategy, fundamental decisions are about selection, acquisition, and timing. The innovation selecting consists of the selection of the innovations to develop; the innovation acquiring consists of how firms acquire the innovation (the main strategies can be simplified with insourcing (make), outsourcing (buy), or collaborating (collaborate). In particular, with respect to timing, firms are heterogeneous and two main approaches can be identified: technological leaders and technological followers that work on the technological knowledge developed by the technological leaders. In this paper, the two approaches have been investigated to study the impact on the firm’s performance. To conduct this investigation, the Patent Agent-Based Innovation Model and Simulator (PABIM has been enhanced. The PABIM is characterized by heterogeneous firms that are organized as a directed random graph. The use of an agent-based model allows for the exploration of emergent dynamics and their subsequent effects on performance. The results indicate that when a firm can adopt all the acquisition strategies (make, buy, collaborate), the optimal strategy concerning timing for firm performance is the leaders’ approach, independently of the sector innovation intensity. The study recommends that managers and policymakers adopt a comprehensive approach to innovation management, integrating pertinent technical knowledge related to product or process development with the necessary resources for effective implementation.

Entrepreneurial education ecosystems are increasingly recognized as strategic environments within universities that foster entrepreneurial knowledge, culture, and venture creation. However, the interplay between institutional factors and educational outcomes in these ecosystems remains underexplored, particularly from a dynamic, system-level perspective. This study addresses this gap by developing a theory-driven agent-based model—the Entrepreneurial education ecosystems Model: “3E Model”—to simulate how formal (e.g., corruption, bureaucracy, access to credit) and informal (e.g., social perception of entrepreneurship, cultural diversity) institutional factors influence entrepreneurial learning dynamics in university-based ecosystems.
Grounded in entrepreneurial ecosystem theory, stakeholder theory, and institutional theory, the model captures the interactions of heterogeneous agents including students, faculty, investors, and institutional actors. The simulation results reveal that institutional quality significantly shapes the accumulation of entrepreneurial knowledge, the formation of entrepreneurial culture, and the motivation to launch startups. In particular, corruption and bureaucratic burden emerge as major impediments, reducing both knowledge diffusion and entrepreneurial activity. Conversely, favorable social perceptions of entrepreneurship significantly enhance ecosystem performance, with evidence of threshold effects: only after surpassing a certain level of societal support does venture creation accelerate. Cultural diversity also contributes positively by enriching knowledge exchanges, though its impact is more gradual.
The model demonstrates the non-linear and interdependent nature of institutional influence in 3Es, confirming that both formal (structural) and informal (cultural) institutions jointly determine ecosystem vitality. Practically, the 3E Model serves as a decision-support tool for universities and policymakers, enabling the simulation of interventions to strengthen entrepreneurial education. The findings suggest that aligning institutional reforms with cultural initiatives—such as reducing administrative barriers while promoting entrepreneurship as a legitimate career path—can generate synergistic effects that boost entrepreneurial outcomes. The study concludes by outlining future research directions, including model refinement through empirical calibration and the inclusion of feedback loops between education and institutional change.

Organisational resilience, defined as the capacity to absorb and recover from shocks affecting an organisation’s operations, becomes increasingly more important in today’s environment. While existing research has mainly explored structural and strategic factors contributing to organisational resilience, the role of managerial decision-making modes in this context remains underexamined. This paper addresses this gap by developing an agent-based model that simulates how different modes of decision-making affect resilience. The model captures stylised organisations as collections of interdependent departments operating on performance landscapes with varying complexity. The study compares silo-based, sequential, collaborative, and proposal-based decision-making across 144 simulated scenarios, incorporating shocks of varying severity. The results reveal that collaborative and proposal-based decision-making modes enhance shock absorption and recovery in complex task environments, while simpler modes perform well in settings where tasks are less complex. Proposal-based coordination offers balanced performance.

The global energy sector is undergoing a deep transition to mitigate climate change and enhance energy security through sustainable sources (International Energy Agency, 2023). Green hydrogen (GH2) has emerged as a strategic solution for decarbonizing hard-to-abate sectors, aligning with Paris Agreement targets to limit global warming to 1.5°C (Deloitte, 2023; Fuel Cells and Hydrogen 2 Joint Undertaking, 2019). The GH2 value chain operates as a complex adaptive system, characterized by nonlinear relationships, emergent behaviors, and evolving stakeholder interactions (Peyerl & van der Zwaan, 2024; Zhang & Li, 2024). This work examines the economic, social, and environmental impacts of innovations in GH2 production within a European-funded project focused on developing a photocatalytic reactor for water splitting into hydrogen and high-value co-products. Using an Agent-Based Model (ABM) developed in NetLogo, the research simulates stakeholder interactions, capturing emergent dynamics often overlooked by traditional top-down models (Macal & North, 2010). The model is able to estimate the number of plants required to meet Spain’s GH2 demand by 2030 (Pawelec et al., 2023) and highlights how stricter sustainability criteria can promote best practices, stimulate innovation, and open economic opportunities. The model demonstrates the strategic potential of GH2 in driving decarbonization, technological advancement, and social inclusion. Moreover, by embedding sustainability across the value chain, the ABM provides policymakers and industry stakeholders with actionable insights to optimize GH2 deployment, lower costs, and support the broader transition to a low-carbon energy system (World Economic Forum, 2021). This research contributes to the growing body of knowledge needed to guide future investments, policy frameworks, and cross-sector collaborations.

Twin transition —integrating digitalisation and ecological sustainability— has become a structural priority for European regional development, as reflected in major frameworks such as NextGenerationEU and the 2021–2027 Cohesion Policy. These programmes aim not only to support recovery but also to reshape the technological and institutional foundations of regional economies. However, a significant knowledge gap remains: while the twin transition requires coordinated and systemic change, we still lack a clear understanding of how it unfolds across different regional contexts —particularly given persistent disparities in structural capacity and institutional agency. This paper addresses that gap by investigating the relationship between regional industrial path development and the capacity of regions to engage in twin transitions. Drawing on an established typology of development paths —including extension, upgrading, branching, diversification, creation and importation—and on a review of regional case studies, we develop a configurational framework that links these development paths to a set of structural and institutional causal conditions. These conditions are operationalised into indicators grounded in the literature, and applied to the Italian regional context through a fuzzy-set Qualitative Comparative Analysis covering the period 2007–2017. The findings show that regional engagement in twin transitions could result from distinct combinations of development paths and enabling conditions. Extension, upgrading, and importation path —when coupled with enabling regional conditions— are the most conducive to twin specialisation.
The study contributes to debates on bridging evolutionary economic geography and transition-oriented policy, and provides a scalable diagnostic tool to inform place-based strategies tailored to structurally diverse regional contexts.

This paper investigates how people’s perceptions of socio-economic indicators in Romania and the Republic of Moldova influence the development of the business environment at local and regional level, in the context of growing challenges to economic and social resilience. Based on a questionnaire applied to a sample of 3228 respondents, the study analyzes eight key indicators, grouped into two composite indices: “Economic and social policies” (I1) and ” Access to basic services/resources (critical infrastructures) services” (I2). These two indices were then combined into a third, entitled ” Overall socio-economic perceptions” (I3), to provide an integrated picture of the well-being of the population. During the course of the work the K-means clustering algorithm and the Silhouette indicator were applied to validate the optimal number of clusters, using the RStudio software the research identified different relevant county-level clusters. In the case of the I1 index, Romanian counties clustered in a distinct cluster from those in the Republic of Moldova, suggesting significant differences in income satisfaction, job security and access to public services. In contrast, for I2, the analysis revealed five clusters, reflecting greater variation in perceptions of access to utilities, energy, education and health. Thus, even though the majority of counties in Romania received high scores, there were also a few counties that scored lower, for which some improvements should be made. The results provide a useful tool for policy makers and business actors, suggesting areas with different needs and varying investment potential. The study highlights the importance of understanding local perceptions in formulating development and intervention policies.

This article analyses the green aspects of technologies embedded within the Fintech sector, providing insights into the intersection of financial innovation and environmental sustainability. The technological advancements introduced in the financial sector over the past decades hold considerable potential to facilitate the ecological transition and promote environmental sustainability – a potential that has been widely acknowledge in the literature. However, there is still little research on the green attributes of the technologies underlying the Fintech sector, particularly through the lens of patents, which serve as concrete indicators of technological innovation.
Our findings contribute to the understanding of technology, finance, and sustainability, emphasising the value of patent data in tracking progress and guiding future developments.
Through the use of statistical analyses and the Social Network Analysis techniques, we define a multi-step methodology and a set of new measures that allow us to analyse Fintech technologies, as described by the underlying patents, in the light of the environmental and eco-friendly perspective, as proposed by the WIPO IPC Green Inventory classification. The statistical analysis of the green Fintech patents reveals several notable trends. The relative frequency of patents containing a number of green technology classifications within the complete dataset exhibits an increasing trends, although this has stabilised in recent years.
Furthermore, the data indicate a modest deceleration in the overall growth of this segment, suggesting a potential plateau in the expansion of green-oriented innovations in the Fintech domain.
Our results offer an original perspective on the idea of green, expanding the analysis to encompass the collective behaviour of the Fintech ecosystem of technologies and, eventually, any other industrial sector.

As environmental and social challenges intensify, regenerative practices in supply chain management (SCM) are emerging as a transformative approach, shifting focus from sustainability to the active restoration of socio-ecological systems. The present study analyses how regenerative principles, including poly-rhythmicity, proportionality, and reciprocity, enhance supply chain resilience through systemic renewal. A comprehensive review of 33 high-impact articles (2010–2024) has identified six key regenerative practices: supply chain plasticity, ecological restoration, circular measures, sustainable resource management (SRM), reshoring, and restorative topophilia. These practices address ecological degradation, economic volatility, and social inequities, all while promoting adaptability. Whilst circularity and SRM predominate in industry applications, there is considerable potential in niche practices such as restorative topophilia, which combines place attachment with ecological restoration. The combination of reshoring and circular principles has the potential to reduce emissions by 30% and stimulate local economies. However, it is important to note that 40% of reshoring initiatives are unsuccessful, resulting in the relocation of production activities that are associated with increased environmental impact. Supply chain plasticity has been demonstrated to exhibit operational resilience; however, it frequently neglects ecological reciprocity, thereby highlighting an evident implementation gap. It is imperative to emphasise the pivotal role that stakeholder engagement, notably from communities and non-governmental organisations (NGOs), plays in transcending the divide between sectors. The present study proposes a framework for “regenerative intelligence” that integrates ecological, social, and supply chain objectives. The study validates institutional redundancy (policy-market synergy) and emphasises poly-rhythmicity as an unexplored lever for resilience. The study provides practical insights for transitioning from protective to proactive regeneration, and it notes two limitations: potential interpretive biases and a focus on academic literature. The study suggests that future research should explore metrics, cultural contexts, and decision-support tools. This work reframes supply chains as catalysts for systemic renewal, advocating for strategies that restore rather than merely sustain.

The present study examines the impact of technology diffusion on energy consumption and efficiency in small and medium enterprises (SMEs) in Montenegro. The focus of this study is a project proposal submitted by a specific SME. The project entails the procurement of the machine for heating and waste collection, as well as the implementation of a digital key for purpose of productivity and energy monitoring. The objective of the project is threefold: firstly, to reduce electricity consumption; secondly, to increase revenue; and thirdly, to promote sustainable practices. This is an empirical study, and as such the results obtained from the real-life consumption of a company can be representative. It was demonstrated that undertaking of project activities would result in the company accruing benefits in both the short and long term. It has been indicated that a reduction in both energy consumption and CO₂ emissions will be observed. However, it is anticipated that the project activities will, over time, lead to the adoption of even more sustainable practices within the company. The paper provides a comprehensive exposition of the demonstration of the Rogers model (TOE and IDP framework) using empirical evidence. Project of this nature are of great benefit to SMEs in Montenegro and the wider region. The provision of financial assistance is but one of the functions of this calls, another is the raising of awareness of various issues. The concept of energy efficiency should not be perceived as disadvantageous, rather, it should be regarded as a concept that is universally accessible and demonstrably manageable in a variety of ways.

The impact of Artificial Intelligence (AI) on Human Capital (HC) responsible for designing, reengineering, and developing Business Models (BM) has not been extensively investigated. Latest research seems to diverge on whether AI has a negative or positive impact on HC competences, HC capabilities, and Business Model Innovation (BMI) processes. Studies indicate that HC is at risk of being wasted or underutilized due to AI, as research verifies that if the human brain is not utilized as much as AI enables today, where AI takes over HC tasks and HC will be wasted, spilled or lost. Other research shows that AI can release unused HC and potential when AI designs and reengineers Business Models (BMs) and Business Model Ecosystems (BMES). In some cases, AI is even shown to be able to release unused HC when downloading, analyzing BMs, and sensing disruptive, radical, and/or incremental BMs.
The paper investigates AI´s impact on HC and HC´s capabilities (HCC) in 7 different Multi Business Model Innovation (MBMI) processes, seeking to determine whether AI can enhance the use and potential of HC, or, conversely, hinder and reduce HCC in MBMI.
The impact of AI and MBMI was studied in seven MBMI projects in different BMESs that are influenced by AI. The effect of AI on HCC was analyzed as a key finding and output to the research question: Does AI lead to HCC Waste, spill, loos or does it increase the grow, increase and release HCC potential?

Small and Medium Enterprises (SMEs) are fundamental to Mexico’s economy, representing over 70% of formal employment. Despite their importance, many SMEs, particularly in traditional industries such as leather-footwear, struggle to adopt digital technologies due to outdated infrastructure, limited resources, and cultural resistance to change. The COVID-19 pandemic intensified these challenges, underscoring the need for digital transformation to ensure competitiveness and sustainability.
This study explores how SMEs in Guanajuato’s leather-footwear sector can leverage digital innovation and human capital to overcome transformation barriers, enhance competitiveness, and align with sustainability goals. It examines the intersection between technology, knowledge management, and organizational culture in the context of the Fourth Industrial Revolution. A qualitative, multi-case methodology was employed, using semi-structured interviews with managers from 13 SMEs. These interviews explored four key dimensions: technological infrastructure, digital culture, challenges to adoption, and future strategies. Triangulation with academic literature ensured analytical rigor and contextual relevance.
Findings reveal that only 15% of the companies have sufficient technological infrastructure to support comprehensive digital transformation, while 70% possess only basic tools such as computers and internet access—often underutilized. A significant 85% of managers cited lack of employee training as a major obstacle. Nonetheless, companies with a strong culture of learning and openness to collaboration showed higher adaptability and up to 20% increases in operational efficiency. The pandemic also acted as a catalyst, pushing many firms toward digitalization, although often reactively.
A conceptual model was developed integrating the four dimensions of transformation, offering a framework for SMEs to navigate digital change. The study further proposes knowledge management strategies including training programs, the integration of digital tools, and collaboration with startups and government agencies. These were identified by 60% of interviewees as key enablers of sustainable innovation.
This research contributes to academic understanding of digital transformation in traditional sectors and provides actionable insights for entrepreneurs and policymakers. It aligns with IFKAD’s vision of integrating human expertise and digital innovation to foster socially responsible businesses. By focusing on knowledge as a strategic asset, the study highlights the importance of human capital in driving innovation, sustainability, and long-term resilience in SMEs.

The healthcare system in Mexico faces persistent and multifaceted challenges, such as the exclusion of vulnerable populations, limited access to medical services in rural and marginalized areas, and increasing pressure due to an aging population. The COVID-19 pandemic exacerbated these structural weaknesses, highlighting the urgent need to integrate innovative technological solutions that not only optimize available resources but also expand and improve access to healthcare services.
In response to these needs, a sustainable and inclusive telemedicine ecosystem was proposed, grounded in methodologies from Exponential Organizations (ExO), to ensure long-term scalability, adaptability, and effectiveness.
A diagnostic assessment using the Pan American Health Organization (PAHO) tool revealed a low level of technological maturity at the Centro Médico Puentecillas. To address these gaps, the CANVAS model was applied to redesign the center’s business structure, incorporating ExO SCALE principles: staff autonomy, active community participation, and continuous user engagement.
Additionally, the proposal included the development of a digital platform for managing teleconsultations, telemonitoring, and teleassistance, integrating real-time clinical data collection to support evidence-based medical decision-making and preventive health monitoring.
The methodology focused on identifying key technological and organizational deficiencies, prioritizing intervention strategies such as digital literacy training for medical personnel and infrastructure enhancement to improve system performance and reliability.

This research aims to analyze how operational sustainable business strategies and modern technologies, including employee training influence performance. The methodology is a quantitative approach with a cross-sectional design. Data was collected from 207 SMEs in Aguascalientes, central region of Mexico, through a survey administered to managers or those responsible for operations (INEGI, 2024). The data will be analyzed using EQS software to assess the relationships between the variables. This research aims to provide valuable insights into the factors contributing to firms’ operational performance success. The research model will be assessed by the reliability and validity of the measurement instruments using Cronbach’s Alpha, Dijkstra-Henseler’s rho, Composite Reliability Index, and Average Variance Extracted (AVE). So, the analysis will ensure that the constructs are distinct and not overlapping. The good fit for the proposed theoretical model will be evaluated to suggest that the relationships between the variables were adequately represented (Henseler et al., 2015). The study focuses on the crucial role of sustainable business strategies in enhancing the operational performance of SME (Buttle & Maklan, 2019; Marr, 2016; Marston et al., 2011; Sutherland, 2019). The results obtained in this study indicate that, on the one hand, the factor loading of the variables is within the norm and, on the other hand, sustainable business strategies do have a significant impact on the performance of operational activities in this type of company. This means that for manufacturing SMEs, it is very important to have a sustainable environment that allows all of their operations to be focused on the performance of their internal operating systems. The data collection period was between March and May 2024, considering a stratified random sample of companies within the state of Aguascalientes.

The distribution of fresh products presents unique challenges. Kilowatt specifically aims to: optimize and improve the logistics management of the fresh product supply chain; support processes that ensure the quality and organoleptic and nutritional properties of food; reduce food waste; maximize the energy recovery of waste.
The key points of the project can be summarized as follows: business model innovation, enhanced environmental and social sustainability, optimization of the distribution chain, Smart Packaging design, and waste recycling.
The development of the new business model will focus on offering high-quality products certified for safety, authenticity, environmental impact, and strong market orientation. These products will be strategically placed in various outlets based on real-time demand analysis. A sustainable and ethical approach to food marketing will be promoted, with an emphasis on recovering waste materials to produce alternative energy, as well as redistributing unsold products to the third sector to benefit vulnerable groups in society. Logistical activities for goods distribution will be optimized to reduce travel distances, enabling the planning of deliveries over a longer time horizon, minimizing store visits, and reducing the risk of unsold goods.
Finally, smart packaging systems, composed of active wrappers designed to extend product shelf life and integrated with IoT sensors for monitoring, will be developed. Additionally, digestion matrices will be defined to maximize the energy produced from food waste.

The agrifood business system, in terms of sector turnover and employment, assumes significant weight for creating economic value within local socio-economic systems, with a direct impact on population health. Furthermore, the agri-food business system is a sector that has direct repercussions in terms of public health and well-being of people. In recent years, the agrifood sector has undergone numerous changes, both regulatory and technological view. These recent changes along with growing societal awareness, have shifted the focus towards combating food waste in the agrifood supply chain. As an effect, the agrifood business system has garnered increasing attention from policymakers and scholars. Consolidated studies on agri-food business systems have focused their attention on historical and evolutionary aspects, leaving out managerial aspects such as those linked to inter-organizational relationships and the supply chain.
This preliminary study aims to offer a first analysis of the main regulatory and organizational elements within the agri-food supply chain business system. This study, through a qualitative approach, analyzes organizational actors, interorganizational relationships and sustainability-oriented strategies along the entire supply chain. The theoretical approach used is based on knowledge management studies. Adopting an exploratory research design, this study employs qualitative methods to gather in-depth insights into the dynamics of the agrifood supply chain. Given the complexity and diversity of organizational actors within the agri-food business system, this exploratory study aims to identify the main evolutionary trends—both regulatory and managerial—of the agri-food supply chain. The research adopts a qualitative methodology, drawing on secondary data sources such as industry reports, regulatory documents, and academic literature.
This study contributes to the academic and practical discourse on agri-food business system by focusing on the organizational dimensions of the issue. Unlike existing literature, it integrates these additional drivers for change, beginning with the regulatory context. The findings provide initial observations and reflections for practitioners seeking to reduce inefficiency through organizational innovation and for scholars in organizational theory. Furthermore, the proposed regulatory framework emphasizes the importance of integrating data-driven technologies and predictive analytics into decision-making processes, enabling more precise inventory management, better coordination among supply chain actors, and the development of reactive strategies to mitigate waste. These practical implications also extend to policymakers, offering pathways for creating supportive regulatory environments and incentivizing sustainable practices in the agrifood sector.

This study explores how consumers perceive and respond to smart packaging technologies as a practical solution to the growing issue of food waste. While traditional food packaging plays a role in preservation, it often lacks the ability to communicate real-time information about freshness or quality.
Smart packaging, which includes technologies such as sensors, freshness indicators and traceability systems, allows for real-time monitoring of product quality, providing consumers with essential information to make more informed decisions and extend the shelf life of food products.
To understand the factors influencing consumers’ intention to adopt these technologies, the research adopts an extended version of the Technology Acceptance Model (TAM). In addition to the classic variables: Perceived Usefulness (PU), Perceived Ease of Use (PEU) and Attitude toward Smart Packaging (ATT), the study introduces a novel variable such as Willingness to Pay (WP).
Data were collected through a structured online survey using realistic, scenario-based situations, and analyzed using Partial Least Squares Structural Equation Modelling (PLS-SEM).
The preliminary findings show that Perceived Usefulness (PU), Perceived Ease of Use (PEU) and Attitude toward Smart Packaging (ATT) significantly influence consumers’ intentions to adopt such innovative solutions. Conversely, Willingness to Pay (WTP) does not show a statistically significant relationship with consumer intention.
This research contributes to the academic and practical discourse on sustainable innovation in food systems, offering insights for policymakers, businesses and technology developers aiming to promote smart packaging solutions. The study emphasizes the importance of consumer engagement and targeted strategies to support sustainable consumption patterns and reduce food loss across the supply chain.