The purpose of this study is to present a novel perspective on decision support based on the conventional SEIR pandemic model paradigm considering the risks and opportunities as physical forces deviating the expected performance trajectory of a system. The impact of a pandemic is measured by the deviation of the social system's performance trajectory within the geometrical framework of its Key Performance Indicators (KPIs). According to the overall premise of utilizing Ordinary Differential Equations to simulate epidemics, the deviations are connected to several alternative interventions. The model is essentially built on two sets of parameters: (i) social system parameters and (ii) pandemic parameters. The ultimate objective is to propose a multi-criteria performance framework to control pandemics that includes a combination of timely measures. On the one hand, the current study optimizes prospective strategies to manage the potential future pandemic, while on the other hand, it explores the COVID-19 epidemic in the state of Georgia (USA).

Multi-organization collaboration, which allows partners focus on their core business, is becoming a trend. Besides the interoperability of each partner, the mechanism of selecting qualified and suitable partners is another key issue to guarantee the success of collaboration. Based on our previous work, this paper aims to provide a model-driven approach to solve the partners selecting problem in building collaboration. In this approach, a meta-model is defined to describe the context of collaboration. All the potential partners’ inputs shall be conformed to this meta-model. In order to select the required partners automatically, semantic checks are combined.

Several standards have been defined for enhancing the efficiency of B2B web-supported collaboration. However, they suffer from the lack of a general semantic representation, which leaves aside the promise of deducing automatically the inter-enterprise business processes. To achieve the automatic deduction, this paper presents a social platform, which aims at acquiring knowledge from users and linking the acquired knowledge with the one maintained on the platform. Based on this linkage, this platform aims at deducing automatically cross-organizational business processes (i.e. selection of partners and sequencing of their activities) to fulfill any opportunity of collaboration.