Traceability is the ability to follow a product along its lifecycle. It ensures product safety and quality along the supply chain, managing information generated by several players. Even though regulations establish the information that has to be traced, each player generates much more product (and process) information, which could be used to add value to products, with respect to, not only traceability, but also the lifecycle approach. However, the concepts do not appear to be immediately related in scientific panorama. This paper aims to explore the relationship between traceability and lifecycle through a systematic literature review. Six industries (Software, Manufacturing, Automotive, Automation, Aircraft, and Aerospace) and seven subject areas (Software engineering; System engineering; Industry 4.0; New product development; Process management; Data Management; and Environmental sustainability) were identified through bibliometric analysis. To better explore this relationship in the context of the food industry, a content analysis on lead papers’ sample was performed to identify traceability and lifecycle definitions, methodologies and technologies and their relation. The results of the work, synthetised in a proposed research map, will be of interest to those who are approaching the subject for the first time, and for companies involved in product lifecycle management and food traceability.

Global population growth, climate change, and food safety are some of the challenges that the agri-food sector is current facing. Addressing these in a sustainable way requires the adoption of sustainable-oriented innovations capable of developing new knowledge and reshaping production methods and business models. Digitalization and technological evolution in the agri-food sector, culminating within Agriculture 4.0 (A4.0), represent the latest revolution, as testified by the extant body of knowledge. The lack of a systematic model to map the body of knowledge in A4.0 and how it addresses the agri-food sustainability challenges represents the input of our review. We propose a systematic literature review to discover the research routes in A4.0, increasing the understanding of this paradigm as agri-food sustainability enabler. A taxonomy, composed of 566 terms grouped in seven categories representative of the extant research routes, is proposed: the names assumed by agri-food digitalization process, the main aims and issues of A4.0, the features of the agricultural sector, the parameters monitorable and calculable through A4.0, data, and technologies. It emerged that A4.0 absolve the role of enabler in sustainability agri-food providing to the company a set of data and technological sustainable oriented innovations able to solve, according to an interdisciplinary approach, environmental, social, and economic challenges. The findings identify research gaps and theoretical and practical implications for a wide range of stakeholders, such as engineering managers, agri-food companies, researchers, or companies involved in the web content analysis. Limitations and future research route complete the study.

Several research studies discuss the process of agriculture digitalization proposing technologies able to face the current agri-food challenges. However, the extant bibliometric studies do not fully exploit the complementarity of different modern bibliometric tools, such as performance analysis and science mapping and do not consider the entire research field timespan. Therefore, the aim of this study is to complement and update the previous works and provide a broad quantitative and qualitative view of Agriculture 4.0 research by using synergistically performance analysis and science mapping. The analysis was realized on a sample of 2334 papers adopting statistical frequency analysis and VOSviewer. Performance analysis provided key findings about the following indicators: research subject areas, publications trend, most productive journals, document types, authors productivity, authors' and index keywords, most cited papers, most productive and influent institutions, country map collaboration, the documents by funding sponsor. Science mapping provided key findings about the main thematic research field’ clusters and their evolution overtime: technology application in agricultural industry, data model for analysis and prediction, experimentation and applicative studies of smart agriculture, decision support systems for crop monitoring. This study could benefit: food companies, supporting in technologies identification; governments, suggesting policies to stimulate agricultural digitalization process; academics, incentivizing more consciousness about the topic and research agenda; those who approach this topic for the first time, facilitating bibliographical referencing.

Social media have surged prominently as communication channels for corporate social responsibility. However, little is still known about the performance of green versus non‐green communication across different social media. We contribute by examining whether the presence of green features in social media communication exerts a beneficial effect on consumer response in terms of likes, comments, and shares. We also investigate how this effect hinges upon the social media platform where the content is posted as well as the richness of the format (text, photos, videos) utilized for the diffusion. To our scopes, we use an ad hoc dataset of posts of two major large‐scale retailers in Italy across three major social media, namely Facebook, Instagram, and Twitter. Our results show that, while green content generally stimulates larger response than non‐green content, its effect varies across social media, with the highest effect being observed on Instagram (at least for likes) and the lowest on Twitter (at least for comments). Moreover, the extent to which the positive effect of green content increases as media richness increases (i.e., moving from only text to text plus photo, and then to text plus video) is also contingent upon the social media platform. On Facebook, the moderation of media richness is positive and significant, while being insignificant on Instagram. On Twitter, the moderation is even nonmonotonic in the sense that the highest (positive) effect of green content tends to be obtained for either low or high media richness. Our findings offer remarkable implications for firms engaging in environmental sustainability.