Supply chain optimization of continuous process industries with sustainability considerations

Zhou, Zikai; Cheng, Siwei; Ben, Hua

doi:10.1016/s0098-1354(00)00496-8

Cited by 157 publications

(66 citation statements)

References 8 publications

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“…Some relate to the lack of information of managers concerning current or future legislation, as well as on the expected benefits and possible risks of such an approach (Walker, di Sisto et al, 2008). This lack of information is detrimental and often leads to choosing not to engage in SSC (Zhou, Cheng et al, 2000).…”

Section: Methodsmentioning

confidence: 99%

Drivers and barriers to pre-adoption of strategic scanning information systems in the context of sustainable supply chain

Lesca¹,

Caron-Fasan²,

Loza-Aguirre³

et al. 2016

Systèmes d'Information &Amp; Management

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This research is reporting on the pre-adoption of Strategic Scanning (S.Scan) information systems (IS). More specifically, it relates to the pre-adoption phase, that is, the emergence of the idea of such a system and the evaluation of its need for the organization, upstream of any technological consideration. The research question is the following: what are the drivers and barriers that influence the pre-adoption of a S.Scan IS? The objective of this research is to extend knowledge on a subject that has received little attention from the scholars. Research's originality relies on the use of isomorphic processes from neo-institutional framework to study pre-adoption in the field of S.Scan. On the basis of a multi-method research combining qualitative and quantitative exploratory studies in the specific field of sustainable supply chains (SSC), our results highlight 31 drivers and barriers to pre-adoption of S.Scan IS, ten of which have not been identified before, and five types of pressures. They therefore suggest that pre-adoption of S.Scan IS can be subject to both functional and institutional pressures. It can be driven either by competitiveness or conformism pressures, and hindered by performance objectives or lack of coercive pressures. Finally, these results put a question mark about the understanding of the strategic dimension of S.Scan IS by organisations, and the government's role and its responsibility for promoting SSC initiatives and for the adoption of S.Scan IS on this issue.

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Section: Methodsmentioning

confidence: 99%

Drivers and barriers to pre-adoption of strategic scanning information systems in the context of sustainable supply chain

Lesca¹,

Caron-Fasan²,

Loza-Aguirre³

et al. 2016

Systèmes d'Information &Amp; Management

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show abstract

“…Saaty [46] in 1980. Owing to its easy to understand and simple to apply methodology [47], [48], researchers have applied AHP methodology across a number of situations for studying sustainability and supply chain issues including sustainable supply chain technology evaluation and selection, performance measurement system development and prioritization of environmental factors [24], [47], [48], [49], [50].…”

Section: Ahp Methodsmentioning

confidence: 99%

Sustainable Metal Recycling Supply Chains: Prioritizing Success Factors Applying Combined AHP & PCA Techniques

Khatri¹,

Dash²

2015

IJMVSC

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“…The weighted the ε-constraint, the goal programming (GP), the Pareto optimal, and the LP-norm method are the most popular methods in the literature for treating multi-objective optimization problems [63][64][65][66][67] . In multi-objective problems, since the objective functions have several conflicts with each other, obtaining an optimal solution, which can optimize all of the objective functions altogether, is very difficult (or sometimes impossible) in most of the times.…”

Section: Fuzzy Goal Programmingmentioning

confidence: 99%

A Lagrangian relaxation approach to fuzzy robust multi-objective facility location network design problem

2017

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Abstract:This study considers a multi-objective combined budget constrained facility location/network design problem (FL/NDP) in which the system uncertainty is considered. The most obvious practical examples of the problem are territorial designing and locating of academies, airline networks, and medical service centers. In order to assure the network reliability versus uncertainty, an efficient robust optimization approach is applied to model the proposed problem. The formulation is minimizing the total expected costs, including, transshipment costs, facility location (FL) costs, fixed cost of road/link utilization as well as minimizing the total penalties of uncovered demand nodes. Then, in order to consider of several system uncertainty, the proposed model is changed to a fuzzy robust model by suitable approaches. An efficient Sub-gradient based Lagrangian relaxation algorithm is applied. In addition, a practical example is studied. At the following, a series of experiments, including several test problems, is designed and solved to evaluate of the performance of the algorithm. The obtained results emphasize that considering of practical factors (e.g., several uncertainties, system disruptions, and customer satisfaction) in modelling of the problem can lead to significant improvement of the system yield and subsequently more efficient utilization of the established network.

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Supply chain optimization of continuous process industries with sustainability considerations

Cited by 157 publications

References 8 publications

Drivers and barriers to pre-adoption of strategic scanning information systems in the context of sustainable supply chain

Drivers and barriers to pre-adoption of strategic scanning information systems in the context of sustainable supply chain

Sustainable Metal Recycling Supply Chains: Prioritizing Success Factors Applying Combined AHP & PCA Techniques

A Lagrangian relaxation approach to fuzzy robust multi-objective facility location network design problem

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