Measuring the efficacy of inventory with a dynamic input–output model

Barker, Kash; Santos, Joost R.

doi:10.1016/j.ijpe.2009.08.011

Cited by 128 publications

(79 citation statements)

References 31 publications

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“…Santos and Haimes, 2004;Steenge and Bočkarjova, 2007;Hallegatte, 2008;Barker and Santos, 2010;Rose et al, 2011). Recently however, more research focuses on assessing the indirect losses outside the affected region in more detail as well.…”

Section: Disaster Impact Modelingmentioning

confidence: 99%

A Multiregional Impact Assessment Model for disaster analysis

Koks

Thissen

2016

Economic Systems Research

145

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This paper presents a recursive dynamic multiregional supply-use model, combining linear programming and input-output (I-O) modeling to assess the economy-wide consequences of a natural disaster on a pan-European scale. It is a supply-use model which considers production technologies and allows for supply side constraints. The model has been illustrated for three floods in Rotterdam, The Netherlands. Results show that most of the neighboring regions gain from the flood due to increased demand for reconstruction and production capacity constraints in the affected region. Regions located further away or neighboring regions without a direct export link to the affected region mostly suffered small losses. These losses are due to the costs of increased inefficiencies in the production process that have to be paid for by all (indirectly) consuming regions. In the end, the floods cause regionally differentiated welfare effects. ARTICLE HISTORY

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Section: Disaster Impact Modelingmentioning

confidence: 99%

A Multiregional Impact Assessment Model for disaster analysis

Koks

Thissen

2016

Economic Systems Research

145

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“…When using 5, IIM applications tend to compare the total impacts of uniform reductions of exogenous final demand c * by industry of, for example, 10% (Santos and Haimes, 2004) or 20% (Barker and Santos, 2010). Alternatively, uniform uncertainty distributions are applied to all industries (e.g.…”

Section: Problems In the Empirical Assessment Of Wider Disaster Impacmentioning

confidence: 99%

On the limited usability of the inoperability IO model

Oosterhaven

2017

Economic Systems Research

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This note shows that the inoperability input-output model (IIM) estimates only a part of mainly the negative indirect economic impacts of disasters, whereas it neglects most of the positive indirect impacts. This means that the IIM is not suited to prioritize industries for policy interventions that aim at reducing the negative impacts of such disasters. Besides, this note shows that the application of the IIM is problematic and tends to overestimate the subset of impacts that the model is able to quantify. Finally, we identify two approaches that much better capture the variety of different disaster impacts. ARTICLE HISTORY

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“…Santos & Haimes (2004) introduced a demand-reduction model that analysed the effects the inoperability of the sectors had on the demand of other sectors and also proposed a regional analysis within the IIM. Some of the important developments of IIMs include the consideration of inventories and their effect on the dynamic IIM (DIIM) (Barker and Santos, 2010) and agent-based IIM (Oliva et al, 2010). We will consider DIIM and Fuzzy IIM in more detail.…”

Section: Inoperability Modelsmentioning

confidence: 99%

A fuzzy dynamic Inoperability Input–output Model for strategic risk management in Global Production Networks

Niknejad

Petrov́ić

2016

International Journal of Production Economics

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Strategic decision making in Global Production Networks (GPNs) is quite challenging, especially due to the unavailability of precise quantitative knowledge, variety of relevant risk factors that need to be considered and the interdependencies that can exist between multiple partners across the globe.In this paper, a risk evaluation method for GPNs based on a novel Fuzzy Dynamic Inoperability Input Output Model (Fuzzy DIIM) is proposed. A fuzzy multi-criteria approach is developed to determine interdependencies between nodes in a GPN using experts' knowledge. An efficient and accurate method based on fuzzy interval calculus in the Fuzzy DIIM is proposed. The risk evaluation method takes into account various risk scenarios relevant to the GPN and likelihoods of their occurrences. A case of beverage production from food industry is used to showcase the application of the proposed risk evaluation method. It is demonstrated how it can be used for GPN strategic decision making.

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Measuring the efficacy of inventory with a dynamic input–output model

Cited by 128 publications

References 31 publications

A Multiregional Impact Assessment Model for disaster analysis

A Multiregional Impact Assessment Model for disaster analysis

On the limited usability of the inoperability IO model

A fuzzy dynamic Inoperability Input–output Model for strategic risk management in Global Production Networks

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