Hybrid Supply Chains in Emerging Markets: The Case of the Mexican Auto Industry

Cedillo-Campos, Miguel Gastón; Pérez-Araos, A.

doi:10.7166/21-1-77

Cited by 5 publications

(1 citation statement)

References 34 publications

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“…Thus, the modern business of companies providing sequencing service to the final assembly line is to guarantee short response times and driving a policy of highly controlled costs (Ludwig, 2016a;Cedillo-Campos & Perez-Araos, 2010;Bueno & Cedillo-Campos, 2014;Jianga, Wanga & Yan, 2014;Suyabatmaza, Altekinb & Şahin, 2014).…”

Section: Introductionmentioning

confidence: 99%

Decision policy scenarios for just-in-sequence (JIS) deliveries

Cedillo-Campos¹,

Ruelas²,

Lizárraga-Lizárraga³

et al. 2017

JIEM

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Abstract:Purpose: The Just-in-Sequence (JIS) approach is evidencing advantages when controlling costs due to product variety management, and reducing the risk of disruption in sourcing, manufacturing companies and third-party logistics (3PL). This has increased its implementation in the manufacturing industry, especially in highly customized sectors such as the automotive industry. However, despite the growing interest from manufacturers, scholarly research focused on JIS still remains limited. In this context, little has been done to study the effect of JIS on the fluidity of supply chains and processes of logistics suppliers as well as providing them with a decision making tool to optimise the sequencing of their deliveries. Therefore, the aim of this paper is to propose a genetic algorithm to evaluate different decision policy scenarios to reduce risks of supply disruptions at assembly line of finished goods. Consequently, the proposed algorithm considers a periodic review of the inventory that assumes a steady demand and short response times is developed and applied.-581-Journal of Industrial Engineering and Management -http://dx.doi.org/10.3926/jiem.2090Design/methodology/approach: Based on a literature review and real-life information, an abductive reasoning was performed and a case study application of the proposed genetic algorithm conducted in the automotive industry. Findings:The results obtained from the case study indicate that the proposed genetic algorithm offers a reliable solution when facing variability in safety stocks that operate under assumptions such as: i) fixed costs; ii) high inventory turnover; iii) scarce previous information concerning material requirements; and iv) replenishment services as core business value. Although the results are based on an automotive industry case study, they are equally applicable to other assembly supply chains.Originality/value: This paper is of interest to practitioners and academicians alike as it complements and supports the very limited scholarly research on JIS by providing manufacturers and 3PL suppliers competing in mass customized industries and markets, a decision support system to help decision making. Implications for the design of modern assembly supply chains are also exposed and future research streams presented.

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Section: Introductionmentioning

confidence: 99%

Decision policy scenarios for just-in-sequence (JIS) deliveries

Cedillo-Campos¹,

Ruelas²,

Lizárraga-Lizárraga³

et al. 2017

JIEM

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Dynamic Self-Assessment of Supply Chains Performance: an Emerging Market Approach

Cedillo-Campos¹,

Sánchez-Ramírez²

2013

Journal of Applied Research and Technology

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A dynamic self-assessment of performance on supply chains operating in emerging markets is proposed. Based on wellestablished key performance indicators (KPI), this paper provides a decision support aid. Although it has been validated in the automotive industry, the standardized model's approach makes it applicable to other industries. It is the result of a large literature review and identification of best practices from the automotive industry in which the lack of dynamic tools to evaluate logistics performance of suitable supply chains to the current competitive exchange rate was detected. Developed under a system dynamics approach (DS), the model analyzes different scenarios taking into account KPI and its dynamic relationships. The results obtained were validated through the statistical technique of design of experiments (DOE). This model also considers the specific features of the automotive operations in emerging countries as well as their importance in the future development of the manufacturing industry. In this context, the tool exposed is a key backup to decision making and to dynamically evaluate the variables with major influence on manufacturing supply chains. As a conclusion, findings are discussed and future researches are presented.

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Supply Chain Clustering: Is it the Next Logistics Frontier?

Cedillo-Campos

2024

SSRN Journal

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Hybrid Supply Chains in Emerging Markets: The Case of the Mexican Auto Industry

Cited by 5 publications

References 34 publications

Decision policy scenarios for just-in-sequence (JIS) deliveries

Decision policy scenarios for just-in-sequence (JIS) deliveries

Dynamic Self-Assessment of Supply Chains Performance: an Emerging Market Approach

Supply Chain Clustering: Is it the Next Logistics Frontier?

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