Metamodeling the e-waste domain to support decision-making

Abstract

PurposeThis paper proposes a conceptualization of the e-waste domain, formalized through a metamodel, to express complex e-waste realities in a simple manner. This also enables the transition from a structural model to a behavioral model to implement analysis techniques.Design/methodology/approachThe methodology used is design science research (DSR), a problem-solving paradigm which seeks to construct a working artifact and prove its relevance. The artifact, a metamodel for the e-waste domain, was constructed through an iterative manner and later analyzed to conclude its theoretical relevance and contributions in this domain. As part of the approach, the authors used supplementary techniques such as systematic literature review (SLR), conceptual modeling (CM) and system dynamics (SD).FindingsThe application in the e-waste domain of CM techniques such as metamodeling, model-to-model transformation and simulation is valuable for supporting decision-making, especially when combined with SD. The approach presented in this paper, the conceptual tools and different simulation techniques could also be applied in other complex domains to obtain similar results.Practical implicationsThe modeling method to apply simulation techniques is targeted toward the e-waste domain experts to understand, design, implement, measure and improve strategies and public policies.Originality/valueThe use of CM techniques to model and analyze structural and behavioral e-waste scenarios.

Understanding supply chain resilience through conceptual modelling techniques

“…New elements can also be added as long as the current association and generalization relationships are respected. For example, future research could extend the metamodel to include additional attributes and dynamic elements to create simulation scenarios and improve understanding of the domain (Herrera et al , 2020). In particular, the ability to create simulation scenarios allows decision-makers to test strategies while minimizing the use of valuable resources such as people, time and money.…”

“…The studied literature agrees that without using conceptual modelling techniques, it is difficult to fully understand the domain in which one is working and thus to exploit its full potential (Mentzer et al, 2001;Herrera et al, 2020). To address this, we identified the use of conceptual modelling techniques as a mechanism to better understand the SCRES domain and, therefore, contribute to the development of its theory and practice.…”

“…blockchain-based supply chain (Shoaib et al , 2020) and small and medium supply chains (Tounsi et al , 2012)]. Others, such as Herrera et al (2020), have focussed on specific parts of the supply chain process, using conceptual modelling techniques to conceptualize the e-waste domain as part of the reverse logistics process. Others still, have focussed on conceptualizing entire domains of supply chains such as management (Mentzer et al , 2001), collaboration (Jiang et al , 2016), information management (Messina et al , 2020) and the supply chain’s performance (Theeranuphattana and Tang, 2008).…”

“…This, in turn, makes it possible to express complex SCRES realities simply, ensuring that the models are accurate so that there is no ambiguity in their interpretations. In fact, some researchers have identified similar issues in other supply chain domains and have resorted to conceptual models to solve them (Tounsi et al , 2012; Mentzer et al , 2001; Jiang et al , 2016; Herrera et al , 2020). The use of conceptual modelling tools can therefore benefit the SCRES domain, as it is composed of a set of formal techniques, which help to structure the related knowledge (Olivé, 2007).…”

Evolution of the Business Model: Arriving at Open Business Model Dynamics

“…This network, which contains the elements and their interrelations, becomes a key aspect in improving the creativity of the business and preventing them from falling into the "commodity trap" [10], and in addressing the lifecycle of value and resources, and supporting associated processes. For example, in reverse logistic networks the waste collection process can involve different actors, such as recyclers (formal or informal), manufactures, and distributors, multiple resources such as packaging, products, or a product part, and different activities such as transport and collection [11]. NCBs can be distinguished depending on their type of network and the way in which value flows.…”