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The purpose of this paper is to identify the main research fields concerning food label designs and build a topic overview. To this end, the literature review method was chosen.

A sample of 121 papers was identified and analyzed using bibliometric analysis. Journals, articles, authors of the sample and the term co-occurrence map, which represents the recurring themes and organizes them in clusters, were defined. To recognize the main research fields, starting from analyzing the terms that compose each cluster, the results were discussed in a focus group composed of five experts.

Food labelling theories are distinctly related to eight research fields: consumer behaviour analysis, consumer willingness evaluation, consumer product evaluation, nutrition and health, daily foodstuff and meal effects, food industry and related products, impacts on market and society and child nutrition.

Several stakeholders could be interested in the results of this paper. Food companies could identify the best practices in food labelling theories to improve their products and labels. Governments could understand how social policies are acknowledged by consumers and how to create new policies. Researchers could identify new issues to investigate. The results could also facilitate bibliographical referencing for those who approach this topic for the first time.

To the best of the authors’ knowledge, studies on food label theories explore the themes from the consumer’s perspective. The authors’ study, in contrast, focused on recognizing the research fields where food label designs are addressed.

Nowadays, the agri-food industry is called to face several sustainability challenges that require the development of new sustainable models. The adoption of new technological assets from Industry 4.0 supports the companies during the implementation of sustainability practices. Several models design the operation management of the food supply chains (FSCs). Because none extant models resulted complete in technological and sustainability elements, this paper aims to propose an innovative and sustainable agri-food value chain model, contributing to extend understating of how supply chains can become more sustainable through the Industry 4.0 technologies.

Thanks to a well-structured and replicable systematic literature review and sequent content analysis, this work recognized and compared the extant FSC models, focusing on the interaction of five key elements: activities, flows, stakeholders, technologies and sustainability. The output of the comparison leading in the definition of the proposed model is discussed in a focus group of 10 experts and tested in a case study.

Fifteen extant models were recognized in literature and analysed to discover their features and to putt in light peculiarities and differences among them. This analysis provided useful insights to design and propose a new innovative and sustainable agri-food value chain model; an example for the olive oil business case is provided.

The adding value of the work is the proposed model which regards innovative elements such as recirculation flows, external stakeholders and Industry 4.0 technologies usage which allows enhancing the agri-FSCs operational efficiency and sustainability.

Following the triple helix (TH) model and the way knowledge is transferred into the industry domain, this chapter aims to define features interface that should be implemented in order to facilitate the University–Industry (UI) relationship and thus encourage the spin-off creation.

In order to support this relationship, a new business model configuration of an entrepreneurial ecosystem is proposed, aiming at creating a sustainable environment, where business entities can grow. The field of the Governance of Entrepreneurial Ecosystems is also investigated in order to define a framework for launching, developing, and sustaining a company over time.

This chapter presents a case study developed within the University of Salento (Italy). It capitalizes results from three different research analyses, based on questionnaires and interviews with actors of the spin-off network (professors and researchers, graduating students, admin-tech staff of the Technology Transfer Office, spin-offs’ CEOs/Associates, and R&D managers of external companies) and on results coming from scientific publications and regional/national reports in the innovation context.

A research methodology based on semantic network analysis and sentiment analysis has been applied in order to identify which features an interface should implement in order to facilitate the UI relationship and encourage the spin-off creation.

To support the start-up overcoming the “death valley,” the creation of a link between the strategy used to transfer value to the market and the phase of innovation is proposed inside the business model configuration. Some aspects of a governance model of an entrepreneurial ecosystem were also presented in order to support the business evolution of a single business entity and assuring sustainability over time.

This paper aims to find the best tools to influence the improvement of sustainability in food supply chains (FSCs) by conducting a systematic review of articles. The reader will learn how the different industry 4.0 tools (I4.0T) benefit the FSC and the limitations of each tool.

A review of 436 articles published during the period 2019 to 2022 referenced in the Scopus and Web of Science databases was performed. The review was limited to articles published in English and directly related to Industry 4.0, circular economy and sustainability in the food supply chain.

The results show different contributions of I4.0, with some being more influential than others in improving sustainability in FSCs; for example, Internet of Things and Blockchain have been shown to contribute more toward transparency, traceability, process optimization and waste reduction.

The paper's contribution consisted of ranking according to their importance and the I4.0T that affect sustainability in FSCs by classifying the aspects of each tool and the sustainability factors through a categorization by the Analysis Hierarchy Process.