Model integration. Integrated socio-economic model on food waste

The model architecture described in this deliverable provides the framework through which data and simulations from the data on food waste at a consumer level and at a retail level can be integrated into simulation models. This report highlights the technical approaches followed to achieve model integration. This report highlights the technical approaches followed to achieve model integration. An integrated whole-of-system modelling approach will be developed as a part of the REFRESH project to allow the development of a decision-relevant, and dynamic policy support tool, by which a road map to the reduction of European food waste by 50% by 2030 can be developed. The vital first step (highlighted in this report) is to develop the structures to allow model integration between different model types: Agent-Based Models and Bayesian Networks. These structures were developed and tested to ensure that the model types can be integrated. The architecture described in this deliverable provides the framework through which data and simulations from the data on food waste at a consumer level and at a retail level can be integrated into simulation models. Since a sizable share of the food waste is generated either at the consumer level or at the interaction between consumers and retailers, we address the modelling effort with two integrated ABM-BN models. The first model reproduces the dynamic evolution of food waste choices of consumers as consequence of social interactions. The second focuses instead on the conditions for the successful diffusion and adoption of innovations to reduce food waste at the retailer level. The systemic modelling approach proposed will allow the development of selected simulation scenarios at the consumer and retail level, facilitating decision making in the face of uncertainty. These integrated setups are first iterations of working integrated models, aimed at validating technically the setups as well as the integration process itself. As they are, there are certainly factors that are likely to be important in determining food waste, which are not yet included in the models. However, the latter are flexible and can accommodate further details, and variables. Their construction is purposefully flexible in terms of components of decisions. The integration with Bayesian Networks ensure that Agent-Based models will learn from data originated from the other refresh WPs and will evolve, allowing the introduction of new variables and factors that will lead to the improvement of the different simulation scenarios. The REFRESH project implements a behavioural economics approach in order to identify and measure the most important socio-economic conditions and potential policy interventions driving businesses’ and consumers’ choices in the generation of food waste. More specifically, this work aims to provide new information on consumer and business behaviour by measuring the effects of major tangible factors of food waste, by identifying hidden and emerging profiles of consumer’ and business’ behaviours affecting food waste, and by allowing the detection of intangible food waste drivers. Such an objective is achieved through the development and the testing of Agent-Based Models (ABMs) and Bayesian networks (BNs)

Food waste reduction in supply chains through innovations: a review

Purpose – Agri-food supply chains are facing a number of challenges, which cause inefficiencies resulting in the waste of natural and economic resources, and in negative environmental and social impacts. Food waste (FW) is a result of such inefficiencies and supply chain actors search for economically viable innovations to prevent and reduce it. This study aims to analyse the drivers and the barriers that affect the decision of supply chain operators to adopt innovations (technological – TI, organisational – OI and marketing – MI) to reduce FW. Design/methodology/approach – The analysis was carried out using a four-step approach that included: a literature review to identify factors affecting the decision to adopt innovations; analysis of FW drivers and reduction possibilities along agri-food supply chains through innovations; mapping the results of Steps 1 and 2 and deriving conclusions regarding the factors affecting the adoption of innovations to reduce and prevent FWFindings Results show that different types of innovations have a high potential in reducing and preventing FW along the supply chain; however, they still must be economically feasible to be adopted by decision makers in the food supply chain. TI, OI and MI are often interrelated and can trigger each other. When it comes to a combination of different types of innovation to reduce and prevent FW, a good example of combining TI, OI and MI may be observed in the retail sector in Europe. Here, innovative smartphone apps (TI) to promote the sale of products nearing their expiration dates (OI in terms of organising the sales differently and MI in terms of marketing it differently) were developed and adopted via different retailing channels, leading to the creation of a new business model. Practical implications This study analyses the drivers of FW generation together with the factors affecting the decision to adopt innovations to reduce it and provides solutions to supply chain operators to prevent and reduce FW through different types of innovations. Originality/value Literature has not systematically addressed innovations aiming at the reduction of FW yet. This paper provides a comprehensive literature review of the determinants of innovation adoption and offers a novel view on the problem of FW reduction by means of innovation, by linking factors affecting the decision to innovate with FW drivers. Supply chain, Food waste, Technological innovation, Organisational innovation, Marketing innovationpublishedVersio

From social interactions to private environmental behaviours: The case of consumer food waste

Consumer food waste, like many environmental behaviours, takes place in private, and is not directly subject to social monitoring. Nevertheless, social interactions can affect private opinions and behaviours. This paper builds an agent-based model of interactions between consumers heterogeneous in their sociability, their initial opinions and behaviours related to food waste, and their willingness to consider different opinions, in order to assess how social interactions can affect private behaviours. Compared to existing models of opinion dynamics, we innovate by including a range of “cognitive dissonance” between stated opinions and actual behaviours that consumers are willing to accept before changing one of the two. We calibrate the model using questionnaire data on household food waste in Italy. We find that a limited degree of mixing between different socio-demographic groups, namely adult and young consumers, is enough to trigger change, but a certain openness of mind is required from more wasteful individuals. Equally, a small group of environmentally committed consumers can attract a sizeable share of the population towards low-waste behaviours if they show a certain variability of opinions and are willing to compromise with individuals in their close neighbourhood in terms of opinions. These findings can help design effective interventions to promote pro-environmental behaviours, taking advantage of the beneficial network effects while anticipating negative externalities

Behavioural economics : assessing food waste innovations diffusion through ABM models - insights from Italy and the Netherlands

Food Waste is problem related to all the actors of the Food Value Chain: producers, retailers and consumers. In this context, retail sector plays an important role in tackling the food waste problem. Food waste at the retail level can be reduced through the adoption of food waste reducing innovations. The authors investigate the most relevant factors that promote the adoption of those innovations among retailers

The use of systems models to identify food waste drivers

In developed countries, the largest share of food waste is produced at household level. Most studies on consumers’ food waste use models that identify covariates as significant when in fact they may not be, particularly where these models use many variables. Here, relying on EU-level Eurobarometer data from 2013, we use alternative analytical methods that avoid these problems (Bayesian Networks) to identify the impact of household characteristics and other variables on self-assessed food waste. Our analysis confirms that the country, the age of the respondent, the status (student/non-student), and a belief that the family wastes too much are related to the level of self-assessed food waste. But we found no evidence that waste behaviours differ between people living in urban and rural areas, and little support of a difference between genders. Households from lower-income EU countries (e.g. Portugal, Greece, Bulgaria, Cyprus and Latvia), as well as students and young adults tend to report higher levels of food waste. Hence, the adoption of an EU strategy based on the concept of subsidiarity, and of country-level policy measures targeting different age groups is suggested. Furthermore, our analysis shows that policy makers need to be wary of relying on analysis based on large datasets that do not control for false-positives, particularly when sample sizes are small

Effect of electric current stimulation in combination with external fixator on bone healing in a sheep fracture model

Biophysical stimulations with electric and electromagnetic fields have been demonstrated to accelerate the bone-healing rate. This study has been designed to investigate the effects of electricity directly connected with the central pins of an external fixator in an experimental osteotomy model in sheep. Thirty mg/kg of tetracycline chloride were administered on the 30th and on the 45th day after surgery for histomorphometric studies. Plain radiographs were obtained in standard projections every 15 days after surgery and were analyzed with a software program (Corel Photo-Paint Pro X2, Corel Corporation, Ottawa, Canada). The specimens obtained after 60 days were examined with histological analysis. The results show that biophysical treatment with alternating electricity in combination with external fixator enhances new-bone formation. The translational value of this study, due to the similarities between ovine and human species, suggests that this treatment could be useful in speeding the bone-healing rate both in animals and humans

Default and Control Networks Connectivity Dynamics Track the Stream of Affect at Multiple Timescales

In everyday life, the stream of affect results from the interaction between past experiences, expectations and the unfolding of events. How the brain represents the relationship between time and affect has been hardly explored, as it requires modeling the complexity of everyday life in the laboratory setting. Movies condense into hours a multitude of emotional responses, synchronized across subjects and characterized by temporal dynamics alike real-world experiences. Here, we use time-varying intersubject brain synchronization and real-time behavioral reports to test whether connectivity dynamics track changes in affect during movie watching. The results show that polarity and intensity of experiences relate to the connectivity of the default mode and control networks and converge in the right temporoparietal cortex. We validate these results in two experiments including four independent samples, two movies and alternative analysis workflows. Finally, we reveal chronotopic connectivity maps within the temporoparietal and prefrontal cortex, where adjacent areas preferentially encode affect at specific timescales

D4.2 - Model development and data protocol

The generation of food waste stems from a complex set of interacting behaviours of both food consumers and suppliers. Therefore, a complete approach to the problem requires an analysis of both sources of waste. Both Agent Based Models and Bayesian Networks provide a modelling approach that fits this purpose, since they allow the study of complex systems. WP4 of the REFRESH project implements a behavioural economics approach in order to identify and measure the most important socio-economic conditions and potential policy interventions driving businesses\u2019 and consumers\u2019 choices in the generation of food waste. More specifically WP4 aims to provide new information on consumer and business behaviour by measuring the effects of major tangible factors of food waste, by identifying hidden and emerging profiles of consumer\u2019 and business\u2019 behaviours affecting food waste, and by allowing the detection of intangible food waste drivers. Such an objective is achieved through the development and the testing of Agent-Based Models (ABMs) and Bayesian networks (BNs). The report is structured as follows: Chapter 3 defines what a model is and the modelling approaches that will be utilized within REFRESH WP4. Chapters 4 and 5 illustrate the characteristics of ABMs and BNs. Chapter 6 outlines an ABM aimed at assessing the adoption of innovations for preventing or reducing the food waste generated by companies of the retail sector. Chapter 7 outlines a BN for characterizing consumers\u2019 behaviour with respect to food waste. Chapter 8 anticipates potential modes of interaction between ABMs and BNs. Chapter 9 identifies a number of good practices to ensure effective data management and facilitate data exchange

Testing current synthesis models of the X-ray background

We present synthesis models of the X-ray background where the available X-ray observational constraints are used to derive information on the AGN population properties. We show the need for luminous X-ray absorbed AGNs, the QSO2s, in reproducing the 2-10 keV source counts at relatively bright fluxes. We compare a model where the evolution of absorbed AGNs is faster than that of unabsorbed ones, with a standard model where absorbed and unabsorbed AGNs evolve at the same rate. It is found that an increase by a factor of ~2 from z=0 to z~1.3 in the ratio between absorbed and unabsorbed AGNs would provide a significant improvement in the data description. Finally, we make predictions on the AGNs to be observed in deep X-ray surveys which contain information on the AGN space density at high redshift.Comment: 11 pages with 8 figures, A&A accepte