Supplier selection under risk of delivery failure: a decision-support model considering managers’ risk sensitivity

Dupont, Lionel; Bernard, Christophe; Hamdi, Faiza; Masmoudi, Faouzi

doi:10.1080/00207543.2017.1364442

Cited by 43 publications

(20 citation statements)

References 37 publications

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“…Thirdly, we contribute to theory expansion by adopting a complexity theory lens to explain that narrowing the contextual outsourcer-outsourcee gap facilitates a mind-set shift in outsourcing relationships from hierarchies to networks and from controlling to empowering. Current research on supplier selection explored the impact of perceived contextual and risks factors of selected supplier's capabilities and performance on the outsourcing firm performance (Lockamy and McCormack 2010, Koufteros, Vickery, and Dorge 2012, Kenyon, Meixell, and Westfall 2016, Dupont et al 2018, Ishizaka and Lopez 2018. For example, it was reported that potential outsourcee's lack of human resources management capabilities, mismatch in organizational culture and poor level of IT integration can be of detrimental effect on the future of the outsourcing relationship (Pawar and Rogers 2013, Plugge and Bouwman 2013, Handley and Angst 2015.…”

Section: Discussionmentioning

confidence: 99%

“…The proposed model involves selection of suppliers for different factories of the firm considering both qualitative and quantitative parameters (Kaur, Singh, and Majumdar 2018). Dupont et al (2018) purposed to use a stochastic mixed integer programming approach to build a decision-support for supplier selection under the risk of delivery failures. Finally, Aamer (2018) applied an extended supplier evaluation method by considering supplier production/operations processes.…”

Section: Outsourcee Selection Modelsmentioning

confidence: 99%

“…A plethora of methods have been used. For example, outsourcing studies have developed frameworks for outsourcee selection applying traditional analytic hierarchy process (AHP) approach (Emrouznejad and Marra 2017), cost benefit AHPSort (Ishizaka and Lopez 2018), fuzzy set theory (Ordoobadi 2009, Kaur, Singh, andMajumdar 2018), group analytic hierarchy process ordering (GAHPO) (Ishizaka and Labib 2011), an integrated combination of both AHP and fuzzy set theory Hung 2010, Che andChiang 2012), a stochastic mixed integer programming approach (Dupont et al 2018),a lean thinking outsourcee evaluation approach (Aamer 2018), and clustering procedures based on artificial neural network (ANN) (Medhi and Mondal 2016). Other studies have expanded beyond outsourcees' attributes and considered factors in the external environments including holistic cost of offshore manufacturing outsourcing to developing countries (Pawar and Rogers 2013), the state of "rule of law" in developing countries (Wiengarten, Pagell, and Fynes 2013) and the impact of national culture on governance effectiveness in outsourcing location decisions Angst 2015).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Contextualisation of the complexity in the selection of developing country outsourcees by developed country outsourcers

Pawar

Huq

Khraishi

et al. 2018

International Journal of Production Research

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Outsourcing research has recognised that selecting the right offshore supplier (outsourcee) in low-cost distant developing countries is complex, but central to outsourcing success. More specifically, the combination of outsourcee contextual internal factors (e.g. capabilities) with outsourced-to country contextual external factors (e.g. political, legal, economic, socio-cultural) as two fundamental and interconnected decisions firms make when outsourcing remains an underexplored research gap. Therefore, through a rigorous three-tier qualitative approach we, firstly, develop a contextual Environmental Separation Index (ESI) decision tool to help outsourcing firms in making more informed decisions when selecting outsourcees and outsourcing locations. Secondly, we operationalise the ESI as intuitive and easy to use decision tool, yet with a provision to deliver a truly context proof outsourcee selection decision. Thirdly, we adopt a complexity theory lens to explain that narrowing the contextual outsourcer-outsourcee gap facilitates a mind-set shift in outsourcing relationships from hierarchies to networks and from controlling to empowering developing country outsourcees. We show from a complexity theory perspective how contextual separation gaps between developed country outsourcers and developing country outsourcees can be an effective way to grasp the evolutionary path of outsourcing relationships.

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Section: Discussionmentioning

confidence: 99%

Section: Outsourcee Selection Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Contextualisation of the complexity in the selection of developing country outsourcees by developed country outsourcers

Pawar

Huq

Khraishi

et al. 2018

International Journal of Production Research

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“…Zeng et al [42] used a stochastic optimization model to establish the total expected travel time cost. Dupont et al [43] used a mixed integer linear programming model to show profit-and-loss targets. Atan and Eren [44] established mixed integer linear methods for several leveling objectives by using a heuristic algorithm.…”

Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

A Hybrid Approach for Project Crashing Optimization Strategy with Risk Consideration: A Case Study for an EPC Project

Ouyang

Chen

2019

Mathematical Problems in Engineering

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This study aims to develop and provide a comprehensive evaluation strategy for schedule-related variations and time-cost analysis for an engineering–procurement–construction (EPC) project. Time-cost analysis is an important aspect of project scheduling, particularly in long-term and costly EPC projects. In this study, a hybrid method is proposed for the time-cost optimization strategy evaluation of a project. Monte Carlo simulation is applied to determine contingency plans and realize the effective management of estimated schedule uncertainties. A mathematical integer linear programming optimization model coded using CPLEX is developed to assess appropriate strategies for project execution under time and cost constraints. A set of project evaluation optimization models considering risk and project crash plan and the relationship between crash cost and delay penalty is also developed for assessing project feasibility. The correlation between project risk and crashing strategy has seldom been evaluated simultaneously in previous research. This work fills this research gap by quantifying the feasibility of a project, with combined data on risk, schedule, and cost as evaluation indicators. It allows project managers to consider management issues and strategies before they implement projects. A practical example with numerical applications is presented to illustrate the contribution of the decision-making support mechanism, and several managerial insights are provided.

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“…The supplier selection problem may include several uncertainties which are related with suppliers. In (Dupont et al, 2018) supplier selection is analyzed while taking into account the risk of delivery failure. Suppliers are located in different geographic areas, and supplies are subject to a positive probability of disruption.…”

Section: Introductionmentioning

confidence: 99%

A Group Decision Approach for Supplier Selection Problem Based on a Multi-criteria Model

Rădulescu¹,

Rădulescu²

2020

STUD INFORM CONTROL

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Supplier selection under risk of delivery failure: a decision-support model considering managers’ risk sensitivity

Cited by 43 publications

References 37 publications

Contextualisation of the complexity in the selection of developing country outsourcees by developed country outsourcers

Contextualisation of the complexity in the selection of developing country outsourcees by developed country outsourcers

A Hybrid Approach for Project Crashing Optimization Strategy with Risk Consideration: A Case Study for an EPC Project

A Group Decision Approach for Supplier Selection Problem Based on a Multi-criteria Model

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