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We develop a conceptual framework for studying collective adaptation in complex socio-cognitive systems, driven by dynamic interactions of social integration strategies, social environments and problem structures. Going beyond searching for 'intelligent' collectives, we integrate research from different disciplines and outline modelling approaches that can be used to begin answering questions such as why collectives sometimes fail to reach seemingly obvious solutions, how they change their strategies and network structures in response to different problems and how we can anticipate and perhaps change future harmful societal trajectories. We discuss the importance of considering path dependence, lack of optimization and collective myopia to understand the sometimes counterintuitive outcomes of collective adaptation. We call for a transdisciplinary, quantitative and societally useful social science that can help us to understand our rapidly changing and ever more complex societies, avoid collective disasters and reach the full potential of our ability to organize in adaptive collectives.

The ripple effect refers to disruption propagation across the supply network affecting its global performance. To cope with it, supply networks should be resilient. This study investigates the drivers of supply network resilience, viewed as adaptive capacity to disruptions, focusing on trust and investigating the moderating role of network topology on the relationship between trust and resilience. We first develop an NK agent-based model of the supply network to simulate resilient performance. Then, a simulation analysis is carried out, to assess the effect of trust on the resilience of supply networks displaying different complex topologies. Our results confirm that trust positively affects supply network resilience; however, across the different topologies, the beneficial effect of trust varies. In particular, we find that trust is beneficial at most for the following topologies: local, small-world, block-diagonal, and random. For centralised, diagonal, and hierarchical topologies improving trust increases resilience at a moderat e level. We also find that, as the frequency of disruptions rises, the positive effect of trust on resilience decreases. Managerial implications of the main findings are finally discussed. [ABSTRACT FROM AUTHOR]

Supply chains (SC) are increasingly complex and if the resulting complexity is not managed effectively, it could lead to adverse consequences for the firm. The effect big data analytics (BDA) can have on managing distinct types of SC complexity is not well-understood in the extant literature. Based on a sample of 166 firms from Pakistan, this study empirically investigates the effects of BDA, and structural and dynamic SC complexities, on SC resilience. The study also investigates the role of BDA as a mediator between SC complexities and SC resilience. We find that structural SC complexity positively affects SC resilience, while there doesn't seem to be a significant impact for dynamic SC complexity. We also find a mediating effect of BDA for structural and dynamic SC complexities on SC resilience. Our results contribute to the extant literature investigating BDA and SC resilience by offering a more nuanced understanding of distinct types of SC complexities. We establish a more critical understanding of the role of BDA in mediating the critical link between the two types of SC complexity and SC resilience. The proposed model highlights that there are both direct and indirect effects between structural SC complexity and SC resilience, however dynamic SC complexity only influences SC resilience via BDA. These findings provide strategic insights for SC executives as to where to invest in BDA to build much-needed SC resilience. [ABSTRACT FROM AUTHOR]

Previous literature has emphasized that developing trust among supply chain (SC) firms is a critical element in achieving SC effectiveness. Since developing trust is an expensive task, however, making an informed decision whether to invest or not in trust requires careful assessment of trust benefits. Therefore, we advance a simulation-based methodology to quantify performance improvements associated with trust in SCs. We develop an NK simulation model of a generic SC that captures the SC dynamics under two alternative scenarios, characterized by the presence and absence of trust respectively. A procedure is then illustrated to quantify the benefits of trust in the SC. We also apply our proposed methodology to a real-world SC. Results show that, when trust is pervasive across the SC, performance increases at both the levels of the overall SC and its leading firm., March 31, 2017IntroductionA critical element in achieving supply chain (SC) effectiveness resides in developing trust among SC firms. A significant literature has in fact pointed out the positive effects of [...]

Adopting industrial symbiosis (IS) is a key strategy for pursuing sustainable development and developing circular economy. In this regard, a powerful approach is promoting the development of regional business networks of IS relationships (ISNs), such as the well‐known Kalundborg ISN in Denmark. Nevertheless, a formalized method supporting the development of effective ISNs at the regional level is still lacking in the literature and practice. This paper develops a methodology to support the design of regional ISNs, consisting of two steps: (1) building a waste‐input relationship table, which can be used as a dictionary of the potential IS synergies implementable among couples of companies; and (2) identifying and selecting the potential symbiotic synergies that can be implemented among the companies belonging to a given regional area. The proposed methodology is tested for the case of Apulia region (Southern Italy), where more than 300 feasible IS synergies are identified. The method is useful both for companies interested to exploit IS benefits, and also for regional policymakers prone to develop IS in practice. [ABSTRACT FROM AUTHOR]