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This editorial paper aims to provide a framework to categorise and evaluate the domain of Chain and Network Science (CNS), and to provide an envelope for the research and management agenda. The authors strongly feel that although considerable progress has been made over the past couple of years in the development of the CNS domain, a number of important and exciting challenges are still waiting to be tackled. This paper provides a definition of the object of study of CNS, its central problem area, the organisation and governance of chain and network co-operation, and the relationships between chain organisation and technology development, market dynamics, and the economy and society at large. It indicates relevant sources of knowledge among the various academic disciplines. It touches upon CNS problem solving by identifying areas for knowledge development and CNS tool construction.

Purpose -The paper seeks to delineate the emergence of demand chain management (DCM) from a theoretical perspective and to illustrate its occurrence in practice. Design/methodology/approach -The DCM concept is examined empirically through a case study with retailers involved in the beef chain in the state of Rio Grande do Sul (Brazil). Findings -The paper reveals that the DCM concept derives from the supply chain management (SCM) concept, but with a strong emphasis on demand management due to the incorporation of the market orientation perspective. In the beef business in the Rio Grande do Sul, two distinct practices were observed: SCM and DCM practice. The SCM practice is tightly related to the traditional beef market, whereas the DCM practice emphasizes understanding customers and the sequential capabilities for responding to their requirements. Originality/value -By establishing the evolutionary development from SCM to DCM, businesses will certainly gain insights about how to become more responsive, and this will improve effectiveness and yield more delighted customers.

This paper presents empirical results of research on the influence of social aspects on the organization of transactions in the domain of chains and networks. The research method used was a gaming simulation called the Trust and Tracing game in which participants trade commodity goods with a hidden quality attribute. Previous sessions of this gaming simulation identified a list of variables for further investigation (Meijer et al, 2006). The use of gaming simulation as data gathering tool for quantitative research in supply chains and networks is a proof-of-principle. This paper shows results from 27 newly conducted sessions and previously unused data from 3 older sessions. Tests confirmed the use of network and market modes of organization. Pre-existing social relations influenced the course of the action in the sessions. Being socially embedded was not beneficial for the score on the performance indicators money and points. The hypothesized reduction in measurable transaction costs when there was high trust between the participants could not be found. Further analysis revealed that participants are able to suspect cheats in a session based on other factors than tracing. Testing hypotheses with data gathered in a gaming simulation proved feasible. Experiences with the methodology used are discussed.Keywords: gaming simulation, social relations, trust, transactions, supply networks 1. Introduction Chain and network sciences is a stream of research that focuses on an application domain rather than on an aspect domain. Aspects to be investigated range from pure technology to social relationships. A typical consumer good has been traded in a series of transactions before it reaches the consumer. The sequential businesses involved in the supply of the good can be viewed as one supply network. Focusing on the actual route of a particular product through the network identifies the supply chain of this good. Typically, the aspects are not investigated independently but in an interdisciplinary approach. Interdisciplinary research requires research methods suited for studying multiple aspects simultaneously. Meijer et al (2006) presented a gaming simulation that made participants learn about transactions and embeddedness in a trade network. In the discussion the authors identified a need to collect more data to answer specific questions about what drives the course of the game sessions. They listed a series of variables that could be of value for research in the simulated supply network. The current paper is the result of continued research into the variables identified using the Trust and Tracing game (T&T game) by playing 27 additional sessions and using quantitative data analysis.The next section describes the methodological contribution. The current paper is showing a proof-of-principle of using a gaming simulation for quantitative research in the chain and network domain. Section 3 introduces the theoretical framework and hypotheses, based on New Institutional Economics. Materials and methods are in Section ...

Introduction 1.1 The digital transformation of food systems is in a twilight zone 1.2 The need for a paradigm shift to navigate through the twilight zone 1.3 Responsible research and innovation looked through five lenses 2 Five lenses to be used for navigating the twilight zone 2.1 Business models in the data economy 2.1.1 Data economy and economies of digitalisation 2.1.2 Digitalisation and business models: the micro questions 2.1.3 The meta questions: values and currencies 2.1.4 Ecosystem thinking 2.1.5 Cultivating data ecosystems 2.1.6 Implications for navigating the twilight zone: 2.2 Responsible Data Sharing 2.2.1 The (un)willingness to share data 2.2.2 Fair data markets 2.2.3 Autonomy and control 2.2.4 Care for the commons 2.2.5 Trust 2.2.6 Implications for navigating the twilight zone 2.3 Digital Inclusiveness 2.3.1 Digital infrastructure -availability and affordability 2.3.2 Capabilities -awareness, abilities, and agency 2.3.3 Technological design and power 2.3.4 System complexity 2.3.5 Inclusiveness and exclusiveness as a choice?2.3.6 Implications for navigating the twilight zone Navigating the Twilight Zone -pathways towards digital transformation of food systems | 3 2.4 Integrative Artificial Intelligence 2.4.1 The big data gap 2.4.2 Privacy-preserving AI 2.4.3 Knowledge re-use 2.4.4 Transparency and explainability 2.4.5 An "integration first" approach to AI 2.4.6 Implications for navigating the twilight zone 2.5 Cross-Sectoral Integration 2.5.1 Rural development 2.5.2 Food and Health 2.5.3 Circularity and logistics 2.5.4 Water management 2.5.5 Citizen dialogue platforms 2.5.6 Implications for navigating the twilight zone: 3 A multidisciplinary, collaborative, agile approach for navigating the twilight zone 3.1 Requirements for a multidisciplinary, collaborative, agile approach 3.2 A multidisciplinary, collaborative, agile project approach 3.3 Connecting the dots by Digital Innovation Hubs 4 Conclusions and recommendations 4.1 Conclusions 4.2 Recommendations for a responsible and sustainable digital transformation of food systems 4.