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How supply chain actors manage their exposure to both supply-and demand-side risks is a topic that has been insufficiently examined within the transaction cost economics (TCE) literature. TCE studies often only examine transaction risks in the context of bilateral exchanges. This study aims to contribute to a shift within the TCE literature from a focus on bilateral transactions, to examining transactions within a supply chain context. In this article, various models are constructed that examine how supply chain actors' usage of contracts to manage their exposure to supply (demand)-side transaction risks can affect their exposure to demand (supply)-side transaction risks. The models show that when supply chain actors follow the recommendations from the traditional TCE model regarding the use of contracts, it may increase rather than decrease their exposure to transaction risks. However, when supply chain actors take into account simultaneously both supply-and demand-side transactions when making their contract decisions, as is recommended in this article, a reduction in exposure to transaction risks is more likely. This study offers managers various strategies for taking a supply chain-wide approach to reduce transaction risk exposure.

The present study examines the management of transaction risks in supply chains. Risk management studies often ignore the wider supply chain context in which individual transactions take place. However, risk management strategies which are suitable to use when only a single transaction is considered may be inappropriate when other transactions in the supply chain are taken into account. This study addresses this issue by examining: (1) how risks arise as a result of interdependencies between the various transactions making up the supply chain; and (2) what types of contractual-based strategies actors can use to manage their risk exposure. To realize these aims, the study applies an extended Transaction Cost Economics (TCE) framework with a supply chain orientation. The framework illustrates how different types of interdependencies - pooled, sequential and reciprocal - expose companies to different sources of risk. Three strategies companies can use when facing barriers to risk minimization in sequentially interdependent supply chains are analyzed: risk transferring, risk altering and risk sharing. Examples from the agri-food sector are discussed to demonstrate the functioning of these strategies.

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The use of digital technologies in agriculture has received significant attention in the last decade. There is increasing interest in the potential opportunities for digitalization at a broader bioeconomy scale; however, there is limited knowledge of the potential barriers to a digital bioeconomy. This chapter reviews current knowledge on barriers to digital agriculture and uses a case study to relate these barriers to the bioeconomy scale. We found that adoption barriers are not just technical, but include economic, social, and institutional dimensions, and occur at multiple scales involving technology design, farm systems (including supply chains), the agricultural innovation system, and society. Additionally, these barriers can be highly interconnected. For example technical issues around data interoperability cannot be addressed independently of social issues at the farm scale related to perceptions around privacy and transparent use of farmer data. Examining these multi-dimensional and multi-scale issues through a bioeconomy lens highlights the need for directionality in digital bioeconomy innovation and alignment of national policies and initiatives. Rather than assuming that greater use of digital tools is inherently positive for a national bioeconomy, nations should purposely assess and anticipate the potential implications of digitalization. Our review highlights three opportunities for directionality in the digital bioeconomy. The first is for technology design and development to directly respond to and address societal (not only end-user) needs and barriers to uptake. The second is to design and develop data governance, business models, and standards for data, which are transparent, inspire trust, and share benefits of digital technologies among supply chain stakeholders. The third is to considerably broaden the assessment of societal value from digital agriculture. Addressing the adoption barriers to the digital bioeconomy will come from integrated applications of digitalization that are purpose or ‘mission’ led, rather than inherently techno-centric.