Journal of Systems Science and Systems Engineering最新文献

Since 2019 humanity has been subjected to the perturbations of pandemic, economic disruption, war, civil unrest and changes in whole-Earth dynamics associated with a human-induced Anthropocene. Each perturbation is like a wave-front breaking on the shore of our historical ways of thinking and acting, increasingly unfit for our human circumstances. This challenge to humanity is not new. In 1970 the French term 'problematique' was coined to refer to a set of 49 interrelated global problems; the classic description of wicked and tame problems was published soon after, yet little progress has been made towards answering the question: what purposeful action will aid human flourishing, create and sustain a viable space for humanity, in our ongoing co-evolution with the Anthropocene-Biosphere? A case for innovation in our ways of knowing and doing is made based on arguments that our social world is constrained by: (i) explanations we accept that are no longer relevant to our circumstances; (ii) outdated historical institutions (in the institutional economics sense) that contribute as social technologies to a broader human created and ungoverned technosphere; (iii) inadequate theory-informed practices, or praxis, and (iv) governance-systems no longer adequate for purpose. Practitioners of knowledge science and systems science are urged to act reflexively to critically evaluate the traditions-of-understanding out of which they think and act.

Many firms have already been actively or passively involved in sustainable supply chain management with the objective of improving the triple bottom line (TBL). But whether the limited funds should be allocated to both community responsibility activities (e.g., corporate philanthropy) and environmental protection activities (e.g., recycling) is a confusing question. This paper provides deep insights into the combination strategy of two corporate social responsibility (CSR) types in a two-tier sustainable supply chain by modeling analysis. The decision models in eight scenarios with different combinations of CSR types are proposed and applied for the determination of equilibrium scenarios. The paper's findings highlight: under certain conditions, (1) the supply chain with two types of CSR is the equilibrium scenario and improves the TBL; (2) counter-intuitively, balancing short- and long-term benefits, firms are more willing to cooperate with partners with relatively low consumers sensitivity of CSR activities; (3) it is wise for the manufacturer to allocate more funding to environmental responsibility than to community responsibility. In addition, considering both short- and long-term benefits, comparing with the manufacturer, the retailer has a stronger incentive to improve recycling efficiency.

As the main channel for people to obtain information and express their opinions, online media generate a huge amount of unstructured news documents every day and make it difficult for people to perceive major societal events and grasp the evolution of events. Previous studies on storyline generation are generally based on document clustering without considering event arguments and relations between events. Event-centric knowledge graph has been used to facilitate the construction of news documents to form structured event representation. Although some studies have attempted to construct timelines based on event-centric knowledge graphs, it is difficult for timelines to depict the complex structures of event evolution. In this paper, we try to represent news documents as an event-centric knowledge graph, and compress the whole knowledge graph into salient complex events in temporal order to generate storylines named narrative graph. We first collect news documents from news platforms, construct an event ontology, and build an event-centric knowledge graph with temporal relations. Graph neural network is used to detect events, while BERT fine-tuning is leveraged to identify temporal relations between events. Then, a novel generation framework of narrative graph with constraints of coherence and coverage is proposed. In addition, a case study is implemented to demonstrate how to utilize narrative graph to analyze real-world event. The experiment results show that our approach significantly outperforms the baseline approaches.