AnalysisA Socio-economic Indicator for EoL Strategies for Bio-based Products
Graphical abstract
Introduction
Climate change has led citizens, managers, researchers and policy makers to define possible solutions for the unsustainable use of resources (Costanza et al., 2016; Drupp et al., 2018). The bioeconomy is an economy based on the use of bio-based raw materials, in which new advanced technologies are increasingly employed to create a range of innovative products (alongside the production of traditional goods), minimizing the use of fossil-based resources (Urmetzer et al., 2020) and thereby reducing carbon emissions (Vita et al., 2019). This sector has gained importance in most advanced economies (Maier et al., 2019) and has received particular attention from European Union (EU) institutions. Notably, the updated Bioeconomy Strategy from the European Commission aims at supporting key EU policy priorities, such as the renewed Industrial Policy Strategy, the Circular Economy Action Plan and the Communication on Accelerating Clean Energy Innovation (European Commission, 2018a).
The diversity of bio-based value chains (Vivien et al., 2019), resources and transformation processes (Pelli and Lähtinen, 2020), spatial and temporal patterns (Wohlfahrt et al., 2019), policies (Ramcilovic-Suominen and Pülzl, 2018) and circular economy models (D'Amato et al., 2019b) underlines the complexity of the bioeconomy field (Priefer et al., 2017). According to recent scientific literature, circular economy (CE) and bioeconomy are two concepts that tend to overlap being both focused on what and how resources should be managed (D'Amato et al., 2017; Loiseau et al., 2016). CE is most frequently depicted as a combination of reduce, reuse and recycle activities, whereas it is often times not emphasized that CE requires a systemic shift (Kirchherr et al., 2017). Bioeconomy aims to replace non-renewable resources with bio-based substitutes (D'Amato et al., 2017) highlighting the introduction of bio-based energy and material to moderate environmental risks (Bugge et al., 2016). A relevant perspective shared by these two concepts is the industrial symbiosis of productive processes, where an industry by-product is another industry input (D'Amato et al., 2019b). In this vein, CE represents an economy based on societal production-consumption systems that maximizes the service produced from the linear “nature-society-nature” material and energy throughput flow (Korhonen et al., 2018) to achieve a better balance and harmony between economy, environment and society (Ghisellini et al., 2016).
Circularity and efficiency are not automatically rooted in bioeconomy strategies (Bezama, 2016) and some authors introduced the idea of circular bioeconomy to ensure that bioeconomy is a valid support to resource efficiency (Dahiya et al., 2018; Karan et al., 2019). The concept of the emerging circular bioeconomy is focused on providing alternative business models for the development of sustainable products and processes (Carus and Dammer, 2018; D'Amato et al., 2018) that can solve EoL issues typical of a linear economy (DeBoer et al., 2019), even though several limits concerning the circular bioeconomy have been discussed, since the level of productivity of productions factors is not satisfied by the supply and sink capacity of natural processes (Giampietro, 2019).
Some authors have highlighted the need to study models of business innovation for sustainability and circularity (Pieroni et al., 2019). In particular, Triple Layered Business Model Canvas is able to support innovative and sustainable business models in a circular perspective (Joyce, 2017; Manninen et al., 2018).
CE is a relatively young and still emerging research field, whose uncertainty present formidable challenges for policy makers and practitioners. Scholars have attributed the limited progress in CE implementation to an array of barriers whose understanding is paramount for the transition to CE (Araujo Galvão et al., 2018). An extensive list of 29 potential barriers were identified by Werning and Spinler (2020). Other studies distinguished between technical and economic factors, considered as “hard” drivers or barriers, and regulatory and cultural factors, considered as “soft” drivers or barriers (de Jesus and Mendonça, 2018). Literature highlighted that technological barriers were the main brake to the progress of CE models, but another work found that cultural barriers, particularly a lack of consumers' interest and awareness as well as a cautious company culture, are considered the main obstacle by businesses and policy makers in the EU (Kirchherr et al., 2018).
At the same time, several studies outlined that appropriate indicators still need to be selected to assess CE(Elia et al., 2017). In this context, Saidani et al. (2019) provided a taxonomy of CE indicators, where multiple dimensions are used to measure or represent circularity and are categorized into 10 different categories. However, as emphasized by Kirchherr et al. (2018), only a few metrics associate the CE concept to the three dimensions of sustainable development (i.e. society, economy and environment) and this is one of the major limitations of most of the circularity metrics developed so far (Pauliuk, 2018). While connecting the CE concept with the key objective of sustainable development, Corona et al. (2019) provided an overview of all the circularity metrics available in the literature over the last years. Selecting quantitative micro-scale indicators from scientific literature and macro-scale indicators from the European Union ‘CE monitoring framework’, Moraga et al. (2019) suggest that current metrics are not able to measure every CE strategy. The CE monitoring framework is the European Commission proposal for assessing its advancement in the EU and Member States (European Commission, 2018b). This framework divides indicators into different themes, namely production and consumption, competitiveness and innovation, waste management and secondary raw materials. These topics are strictly related to the priority areas of the CE Action Plan in Europe (European Commission, 2015): plastics, food waste, critical raw materials, construction and demolition, and biomass and bio-based products.
Extensive research efforts have been devoted to the definition of useful indicators for monitoring bio-based products, addressing all or some of the three pillars of sustainability (Egenolf and Bringezu, 2019; Jander and Grundmann, 2019). Nonetheless, in this process, socio-economic aspects have been overlooked (Ronzon and M'Barek, 2018) and, although some progress has been made (e.g. Falcone et al., 2019), there is a strong need for further investigation. Moreover, a central issue concerning the sustainability of the bioeconomy relates to the EoL stage, since a sustainable bio-based product may generate value by avoiding the landfill (Russo et al., 2019; Zhou et al., 2019).
Indeed, the relative value of various EoL options plays a key role in the life cycle of bio-based products (Lokesh et al., 2018). From an environmental perspective, this has been evidenced by Spierling et al. (2018). However, the importance of also acknowledging socio-economic dimensions when evaluating EoL options has been underlined by Majer et al. (2018) and, in this respect, D'Adamo et al. (2020a) proposed a suitable indicator to capture the socio-economic value of bioeconomy sectors, outlining that more research was needed on the EoL stage.
This paper contributes to fill this gapgap by proposing a new socio-economic indicator for EoL (SEI-EoL), also by testing it on a bio-based product. A new model based on an integrated analytic hierarchy process–multicriteria decision analysis (AHP-MCDA) methodology is developed and the resulting SEI-EoL is proposed as a tool for assessing the socio-economic performance of EoL options. The model is built using four steps: the first two steps draw on a literature review to identify potential EoL options and define the relevant socio-economic criteria; in the third step, experts assign weights and values to the criteria, which are associated with several groups of stakeholders. Finally, the fourth step calculates the SEI-EoL for each alternative EoL option relating to the specific case study of polylactic acid (PLA)–based film for food packaging.
The case study of PLA-based film for food packaging was selected from the Horizon 2020 STAR-ProBio project. This choice was based on three main considerations. First, the product enables the consideration of all potential EoL alternatives. Second, several authors have presented an environmental analysis of PLA EoL options (Beigbeder et al., 2019; Maga et al., 2019), but the need to include socio-economic dimensions in future analyses has been emphasized (Blanc et al., 2019). Third, the growing market share of this typology of materials require particular consideration (Falcone and Imbert, 2019) and represents an opportunity to provide actionable advices to practitioners and tailored policy recommendations to decision makers proven that the CE literature often lacks advice (Kirchherr and van Santen, 2019).
The paper is organized as follows. Section 2 describes the methodology, presenting the four steps of the analysis. Section 3 shows the results associated with the SEI-EoL, providing a detailed picture of the selected case study. Finally, Section 4 discusses the implications of the analysis and Section 5 provides concluding remarks.
Section snippets
Materials and Methods
The MCDA methodology can compare multiple alternatives, even when they are conflictual (Saarikoski et al., 2019). To this end, a number of criteria must be identified. A final outcome is obtained from the scores achieved by each alternative (against each criterion), combined with weighting factors, which are assigned on the basis of the relevance of each criterion (Arsić et al., 2018). To facilitate this process, the AHP methodology, developed by Saaty (1980), elaborates a list of priorities
Results
SEI-EoL aims at defining the best EoL option for bio-based products, taking into account socio-economic impact. The best option is identified by the highest cumulative value on several socio-economic criteria, utilizing an aggregated MCDA-AHP methodology.
Policy Implications and Actions
Thanks to the contribution provided by experts, the third round of the survey enabled us to gain a better understanding of key policy interventions and actions to be implemented. First of all, interviewees provided a number of recommendations for improving our preliminary list of items (see Table 3), suggesting a revision of several redundant/overlapping items. In particular, almost all experts (18) outlined that the “price of carbon dioxide” should be embedded within the “polluters' pay
Conclusions
The new Circular Economy Action Plan released by European Commission promotes the assessment of the entire life cycle of products in order to evaluate circularity performances. In this regard, the European Commission's Bioeconomy Strategy highlights that the sustainability of bio-based products must consider the entire life cycle, including the EoL stage. Since prior research has neglected the social-economic dimension of the EoL stage, the present study introduced a new indicator called
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
The authors are very grateful to the financial support received from the STAR-ProBio project (Sustainability Transition Assessment and Research of Bio-based Products). The project was funded by the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No. 727740, Work Programme BB-01-2016: Sustainability schemes for the bio-based economy.
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