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The acceptance and perception of people regarding 3D bioprinted meat are considered as primary concerns but have not been widely evaluated. This study aimed to determine how biospheric, altruistic, egoistic, ecological worldviews, awareness of consequences, social norms and personal norms affect the consumption intention of 3D bioprinted meat as a future food source.

The values-beliefs-norms theory grounded this study. An online survey was conducted with 600 valid respondents for analysis utilizing the structural equation modeling method.

It was found that the ecological worldview had the highest significance, and biospheric and egoistic values positively impacted individuals’ ecological worldview. The awareness of consequences and social norms was also seen to directly influence personal norms, leading to consumption intention. However, it was determined that altruistic values toward an ecological worldview had no significant effect, as an individual's moral values are not affected by other people's well-being.

This study was able to assess and discover the positive consumption intention among Filipinos, highlighting societal norms and pro-environmental behavior. The findings may help manufacturers market 3D bioprinted meat effectively and aid studies on environmentalism, social movements and consumer behavior, leading to acceptance of the development and proliferation of cultured meats.

There have been no studies on cultured meats such as 3D bioprinted meat in the Philippines. The current study was able to fully assess the pro-environmental behavior among Filipinos and intention for 3D bioprinted meat against the generic behavioral assessment among related studies. Comparison was presented based on the findings.

Limiting the use of antibiotics in food animals is a cornerstone of contemporary EU policy. Despite that marketing of antibiotics for growth promotion and nutrition has been banned since 2006, the use is still high and varied. This paper aims to investigate the forces behind the different usage patterns in Italy, with one of the EU’s most extensive use of antibiotics in animals, versus Sweden, with the union’s most restricted use, including how these usage patterns are related to EU and national policies.

The industrial network approach/the 4R resources interaction model is adopted to investigate the major forces behind the different antibiotic usage patterns. Furthermore, the study relies on the notion of three main characteristics related to the use of a resource activated in several user settings (Håkansson and Waluszewski, 2008, pp. 20–22). The paper investigates the Swedish and the Italian using settings, with a minimised, respectively, extensive usage of antibiotics. The study is exploratory in nature and based on qualitative data collected through a combination of primary and secondary sources.

The paper underlines the importance of integrating forces for policy to succeed in attempts to reduce the use of a particular resource. It reveals that Sweden’s radically reduced use was based on great awareness, close interactions between animal-based food producers and policy – and that integrating forces were supported by an era of state-protected food production, with promising ability to distribute the cost of change. The Italian characteristics hindering the integration of forces mounting for reduced use were restricted awareness, top-down business and policy interactions – and a great awareness about the difficulties of distributing the cost of change.

The study deals with the analysis of forces affecting the different usage of antibiotics within two EU settings. The investigation, based on the industrial network approach’s notion of connectivity of economic resources, that is, of exchange having a content and substance beyond discrete transactions, reveals how indirect related contextual forces, neglected by policy, have an important influence on the ability to achieve change, in this case of antibiotics usage patterns.

Small-scale farmers are highly heterogeneous with regard to their types of farming, levels of technology adoption, degree of commercialization and many other factors. Such heterogeneous types, respectively groups of small-scale farming systems require different forms of government interventions. This paper applies a machine learning approach to analyze the typologies of small-scale farmers in South Africa based on a wide range of objective variables regarding their personal, farm and context characteristics, which support an effective, target-group-specific design and communication of policies.

A cluster analysis is performed based on a comprehensive quantitative and qualitative survey among 212 small-scale farmers, which was conducted in 2019 in the Limpopo Province of South Africa. An unsupervised machine learning approach, namely Partitioning Around Medoids (PAM), is applied to the survey data. Subsequently, the farmers' risk perceptions between the different clusters are analyzed and compared.

According to the results of the cluster analysis, the small-scale farmers of the investigated sample can be grouped into four types: subsistence-oriented farmers, semi-subsistence livestock-oriented farmers, semi-subsistence crop-oriented farmers and market-oriented farmers. The subsequently analyzed risk perceptions and attitudes differ considerably between these types.

This is the first typologisation of small-scale farmers based on a comprehensive collection of quantitative and qualitative variables, which can all be considered in the analysis through the application of an unsupervised machine learning approach, namely PAM. Such typologisation is a pre-requisite for the design of more target-group-specific and suitable policy interventions.

This study aims to evaluate how the structure of medical compression stockings, including three compression levels and five cross-sections from the ankle to the thigh part, will be changed after washing in different conditions and further investigate the effect of the washing parameters on the medical compression stockings.

By washing medical compression stockings in different conditions and measuring the structures (including the density, the girth, the transversal and lengthwise dimension, the weight per unit area and the thickness) of medical compression stockings from the knee to the thigh part.

It was concluded that the density, the weight per unit and the thickness increase and the girth, the transversal and lengthwise dimension, the weight per unit and the thickness decrease. The change degree of Class one and Class two is greater than Class 3. Moreover, the washing temperature is the most significant factor affecting all the structures of medical compression stockings. Meanwhile, the mechanical actions of the washing machine, like drum speed and washing time, also influence different medical compression stockings structures to different degrees.

The washing parameter not only includes the temperature and washing cycles but also has other factors, such as the drum speed and washing time. In addition, different kinds of factors will be influenced by each other.

This study can provide consumers advices on the washing of medical compression stockings, and attribute to the optimization of materials and structures to maintain its properties for manufacturers.