Effect of timing on reliability improvement and ordering decisions in a decentralized assembly system

Golmohammadi, Amirmohsen; Tajbakhsh, Alireza; Dia, Mohamed; Takouda, Pawoumodom M.

doi:10.1007/s10479-019-03399-5

Cited by 6 publications

(4 citation statements)

References 58 publications

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“…Xie et al (2021) one-period two-stage supply chain, in which a loss-averse retailer facing stochastic demand orders products from a risk-neutral supplier subject to supply IJQRM 41,1 uncertainty where marketing effort exerted by the retailer is employed to enhance the final market demand. Golmohammadi et al (2022) investigated a supply chain under different scenarios where the suppliers have the opportunity to improve their reliabilities through investments. Most of the existing works of literature show that suitable mechanisms can reduce the variance in delivery schedule and thereby improve the supply chain performance.…”

Section: Literature Review and Background Of The Studymentioning

confidence: 99%

Improvement of supplier delivery performance under uncertain capacity allocation and delivery time window

Sakhare,

Chakraborty,

Sarmah

et al. 2023

IJQRM

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PurposeOriginal equipment manufacturers and other manufacturing companies rely on the delivery performance of their upstream suppliers to maintain a steady production process. However, supplier capacity uncertainty and delayed delivery often poses a major concern to manufacturers to carry out their production plan as per the desired schedules. The purpose of this paper is to develop a decision model that can improve the delivery performance of suppliers to minimise fluctuations in the supply quantity and the delivery time and thus maximising the performance of the supply chain.Design/methodology/approachThe authors studied a single manufacturer – single supplier supply chain considering supplier uncertain capacity allocation and uncertain time of delivery. Mathematical models are developed to capture expected profit of manufacturer and supplier under this uncertain allocation and delivery behaviour of supplier. A reward–penalty mechanism is proposed to minimise delivery quantity and time of delivery fluctuations from the supplier. Further, an order-fulfilment heuristic based on delivery probability is developed to modify the order quantity which can maximise the probability of a successful deliveries from the supplier.FindingsAnalytical results reveal that the proposed reward–penalty mechanism improves the supplier delivery consistency. This consistent delivery performance helps the manufacturer to maintain a steady production schedule and high market share. Modified ordering schedule developed using proposed probability-based heuristic improves the success probability of delivery from the supplier.Practical implicationsPractitioners can benefit from the findings of this study to comprehend how contracts and ordering policy can improve the supplier delivery performance in a manufacturing supply chain.Originality/valueThis paper improves the supplier delivery performance considering both the uncertain capacity allocation and uncertain time of delivery.

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Section: Literature Review and Background Of The Studymentioning

confidence: 99%

Improvement of supplier delivery performance under uncertain capacity allocation and delivery time window

Sakhare,

Chakraborty,

Sarmah

et al. 2023

IJQRM

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“…Niu et al (2019) consider ex‐ante and ex‐post production strategies in a co‐opetitive supply chain when market acceptance is uncertain, and the optimal timing of production is influenced by the degree of market acceptance uncertainty. Golmohammadi et al (2022) analyze how the timing of ordering decisions influences players' performance when the manufacturer faces two complementary suppliers with uncertain capacities. Zhang and Wang (2022) also investigate the ordering timing problems, but they consider radio‐frequency identification adoption with a manufacturer and two retailers.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal timing for nonsubsidized policy implementation in the electric vehicle industry

Wang,

Song

et al. 2023

Manage Decis Econ

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This research examines a scenario involving an electric vehicle (EV) manufacturer promoting innovation, a retailer focusing on advertising and service (A&S), and a government implementing nonsubsidized policies to enhance social welfare and spur EV adoption. The nonsubsidized policies under consideration are classified as ex‐ante (EA), ex‐ing (EI), or ex‐post (EP), depending on their chronological deployment. Our findings indicate that EI is consistently suboptimal due to the presence of the (anti‐)synergy effect. However, either the EA or EP policy proves optimal: EA is preferred when consumers value EV innovation and A&S whereas EP is desirable when associated costs are inefficient.

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“…, 2012). Functional-complementary products focus on components assembled into whole machines (Golmohammadi et al. , 2022; Jiang and Wang, 2009).…”

Section: Introductionmentioning

confidence: 99%

Acquisition or investment: a manufacturer quality improvement strategic choice

Wang

Song

Huang

et al. 2023

TQM

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PurposeThis paper explores how the manufacturer’s strategic choice (acquisition or investment) impacts product quality in a supply chain comprising two complementary suppliers and a common manufacturer.Design/methodology/approachThe manufacturer faces six strategic choices to improve product quality: acquiring or investing in the high-capable supplier, the low-capable supplier, or both. As the Stackelberg leader, the manufacturer determines which strategy is adopted, while suppliers are separately responsible for components’ quality and wholesale prices. The authors use game theory and calculate the model with Mathematica.FindingsThe authors develop analytical models to analyze how acquisition costs, investment proportions, component importance and quality improvement coefficients influence decision-makers. The results show that the highest quality may not benefit the manufacturer. Investing in or acquiring a low-capable supplier is better than a high-capable supplier under certain conditions. If the gaps between two suppliers’ quality improvement coefficients and the importance of two components are dramatic, the manufacturer should choose an investment strategy.Originality/valueThis study contributes to the complementary supply chain management by comparing two kinds of strategies-acquisition and investment, with a high-capable supplier and a low-capable supplier.

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Effect of timing on reliability improvement and ordering decisions in a decentralized assembly system

Cited by 6 publications

References 58 publications

Improvement of supplier delivery performance under uncertain capacity allocation and delivery time window

Improvement of supplier delivery performance under uncertain capacity allocation and delivery time window

Optimal timing for nonsubsidized policy implementation in the electric vehicle industry

Acquisition or investment: a manufacturer quality improvement strategic choice

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