Information sharing in a distributed enterprise: Impact on supply chain performance and decision-making

Owusu, Isaac; Hauan, Steinar

doi:10.1016/s1570-7946(06)80374-3

Cited by 1 publication

(1 citation statement)

References 7 publications

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“…The decision to include them in our dataset was made on the basis that these papers specifically refer to DSCS and how the research presented could contribute to the field. For example, the article by Owusu and Hauan (2006) investigates distributed information sharing; although the main body of the paper is not on DSCS and is more generic, the authors specifically note that the outcomes of the research may be relevant to DSCS. This paper is therefore included in our dataset of the ten ancillary papers.…”

Section: Study Typementioning

confidence: 99%

Distributed Approaches to Supply Chain Simulation

Mustafee

Katsaliaki

Taylor

2021

ACM Trans. Model. Comput. Simul.

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The field of Supply Chain Management (SCM ) is experiencing rapid strides in the use of Industry 4.0 technologies and the conceptualization of new supply chain configurations for online retail, sustainable and green supply chains, and the Circular Economy. Thus, there is an increasing impetus to use simulation techniques such as discrete-event simulation, agent-based simulation, and hybrid simulation in the context of SCM. In conventional supply chain simulation, the underlying constituents of the system like manufacturing, distribution, retail, and logistics processes are often modelled and executed as a single model. Unlike this conventional approach, a distributed supply chain simulation (DSCS) enables the coordinated execution of simulation models using specialist software. To understand the current state-of-the-art of DSCS, this paper presents a methodological review and categorization of literature in DSCS using a framework-based approach. Through a study of over 130 articles, we report on the motivation for using DSCS, the modelling techniques, the underlying distributed computing technologies and middleware, its advantages and a future agenda, and also limitations and trade-offs that may be associated with this approach. The increasing adoption of technologies like Internet-of-Things and Cloud Computing will ensure the availability of both data and models for distributed decision-making, which is likely to enable data-driven DSCS of the future. This review aims to inform organizational stakeholders, simulation researchers and practitioners, distributed systems developers and software vendors, as to the current state-of-the art of DSCS, and which will inform the development of future DSCS using new applied computing approaches.

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Section: Study Typementioning

confidence: 99%