A Multi-Entity Input Output (MEIO) Approach to Sustainability -   Water-Energy-GHG (WEG) Footprint Statements in Use Cases from Auto and Telco   Industries
  A new Input-Output model, called the Multi-Entity Input-Output (MEIO) model, is introduced to estimate the responsibility of entities of an ecosystem on the footprint of each other. It assumed that the ecosystem is comprised of end users, service providers, and utilities. The proposed MEIO modeling approach can be seen as a realization of the Everybody-in-the-Loop (EitL) framework, which promotes a sustainable future using behaviors and actions that are aware of their ubiquitous eco-socio-environment impacts. In this vision, the behavioral changes could be initiated by providing all actors with their footprint statement, which would be estimated using the MEIO models. First, a naive MEIO model is proposed in the form of a graph of actions and responsibility by considering interactions and goods transfers among the entities and actors along four channels. Then, the unnormalized responsibility and also the final responsibility among the actors are introduced, and then are used to re-allocate immediate footprint of actors among themselves. The footprint in the current model is limited to three major impacts: Water, Energy, and GHG emissions. The naive model is then generalized to Provider-perspective (P-perspective) and End User-perspective (E-perspective) MEIO models in order to make it more suitable to cases where a large number of end users are served by a provider. The E-perspective modeling approach particularly allows estimating the footprint associated to a specific end user. In two use cases from the auto and Telco industries, it has been observed that the proposed MEIO models are practical and dependable in allocating footprint to the provider and also to the end user, while i) avoiding footprint leakage to the end users and ii) handling the large numbers end users. In addition, it will be shown that the MEIO models could be sued to integrate Scope-3 and LCA approaches. 
Reza Farrahi Moghaddam, Fereydoun Farrahi Moghaddam, Mohamed Cheriet
q-fin.GN