Buyer-supplier currency exchange rate flexibility contracts in global supply chains

Ogunranti, Gbemileke A.; Ceryan, Oben; Banerjee, Avijit

doi:10.1016/j.ejor.2020.05.053

Cited by 17 publications

(16 citation statements)

References 21 publications

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“…0.0 0.6 (7,10) 1 (7.10) 0.6 (4,11,12) ; 0.8 (7,10) 0.4 (5,10,14,15,16) ; 1 (4,11,12) 0.2 (2,4.8,10,11,12) ; 1 (5,14,15,16) 0.4 (5,14,15,16) ; 1 (2,8,10) 0.6 (8,10) ; 0.8 (2) 0.4 (1,3) ; 1 (2) 0.6 2 ; 0.7 (1,3) 0.9 (1,3) 1 (1,3) 0 0 0 0.1 0.486 (10) ; 0.54 (7) 0.81 (10) ; 0.9 (7) 0.148 (10) ; 0.54 (4,11,12) ; 0.72 (7) 0.324 (10) ; 0.36 (5,14,15,16) ; 0.9 (4,11,…”

Section: Calculation Of Frequency Matrices Of Independentmentioning

confidence: 99%

“…1 (1) 0 0 0 0.3 0.15 (10) ; 0.3 (7) 0.25 (10) ; 0.5 (7) 0.12 (6) ; 0.2 (10) ; 0.3 (4,11,12) ; 0.4 (7) 0.08 (3) ; 0.1 (10) ; 0.12 (1) ; 0.2 (5,6,7,14,15,16) ; 0.5 (4,11,12) 0.04 (6) ; 0.1 (2,4,8,10,11,12) ; 0.2 (1,3,7) ; 0.5 (5,14,15,16) 0.08 (3,7,11) ; 0.12 (1) ; 0.2 (4,5,6,14,15,16) ; 0.5 (2,8,10) 0.04 (12) ; 0.12 (4,...…”

Section: Calculation Of Frequency Matrices Of Independentunclassified

“…Affected by market globalization, an unstable supply and demand, shortened life cycle of products and technology, turbulent external environment of enterprises, complex cooperation networks, and other factors causes the relationship of a supply chain to become increasingly complex, which has some negative characteristics. As a result, the internal and external risks of a supply chain are increasing [2][3][4]. Most research studies on supply chain risks have focused on the classification of trigger events, which are usually called supply chain risk and are understood as the starting point for risk identification [5,6].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Supply Chain Risk Prevention and Control Based on Fuzzy Influence Diagram and Discrete Hopfield Neural Network

Zhong

2021

Discrete Dynamics in Nature and Society

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Efficient and reasonable supply chain management helps enterprises improve their efficiency, reduce costs, shorten cash flow times, and reduce enterprise risks. Risk prevention and control is a safety symbol for supply chains. To explore different influence degrees of multirisk factors and multilinks on enterprises, we propose a supply chain risk prevention and control model based on a fuzzy influence diagram and Hopfield neural network. Using the model that both calculates the risk size and occurrence probability of the supply chain and allows identifying various risk prevention and control levels, the supply chain risk is evaluated both objectively and fairly. We analyzed the theoretical and practical properties of supply chain risk prevention and control models and used it in the H company to illustrate this model.

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Section: Calculation Of Frequency Matrices Of Independentmentioning

confidence: 99%

Section: Calculation Of Frequency Matrices Of Independentunclassified

Section: Introductionmentioning

confidence: 99%

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Supply Chain Risk Prevention and Control Based on Fuzzy Influence Diagram and Discrete Hopfield Neural Network

Zhong

2021

Discrete Dynamics in Nature and Society

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“…e first field concerns the operations of multinational supply chains. To address the risks associated with uncertainty in overseas demand and exchange rates, Ogunranti et al [34] show two categories of currency-exchange-flexibility contracts in which the payments by the buyer in the global supplier's currency lead to a higher expected profit for the two parties and vice versa, while exchange rate volatility results in a reduction of the optimal product order quantities. Many multinationals move their business to low-tax countries due to cost pressures, Wu and Lu [35] study the effectiveness of the cost-plus or resale price approach to improve multinational earnings.…”

Section: Literature Reviewmentioning

confidence: 99%

Exclusivity or Competitor Retail? Impacts of Channel Structures on Multinational Supply Chains considering Green Manufacturing

Rong

Chen

et al. 2021

Mathematical Problems in Engineering

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The development of green supply chains by multinational manufacturers (MNMs) in emerging markets promotes a better corporate reputation and competitive advantage. Selecting viable marketing channels will help reduce risks in overseas markets while positively impacting the green level and the stakeholders. This paper analyzes channel decisions under different scenarios in a game analytical framework and identifies that both exclusive and competitive channels promote the green supply chain, and that the latter leads to a higher green level and benefits the local manufacturer. Whatever profit-seeking or corporate social responsibility- (CSR-) seeking follows, the MNM prefers the competitive channel when the green research and development (R&D) investment coefficient is relatively low and vice versa for the exclusive channel. Moreover, transaction cost undermines the green supply chain, the competitive structure lowers the loss of greenness, and the exclusionary mode raises the MNM’s profits. Another interesting finding is when subsidies are offered by the importing country, the competitive structure is more conducive to the green and the participant’s gains, while the exclusive structure is detrimental to the green and only advantageous for the domestic manufacturer’s benefits. Besides, the revenue-sharing contract results in a higher green level of the supply chain in the channels than before, but the MNM tends to select the exclusive marketing channel with a relatively lower green level due to the profits. Subject to the findings, we propose an improved revenue-sharing contract that achieves the MNM’s competitive retailing option and ensures the emergence of the manufacturers’ win-win solution.

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“…Building a competitive advantage in the business-to-business (B2B) market, in particular, is subject to shaping the long-term partner relationships between companies and their customers and suppliers (Padgett et al, 2020). An individualised, trust-based approach towards the establishment of contacts, interests and the possibilities of cooperation, offers the negotiation and execution of transactions with parties guaranteeing their equivalent positions, called winwin (Ogunranti et al, 2021). A positive evaluation of these activities is essential in maintaining these relationships and a sign of readiness for further cooperation partners, by which several measurable benefits can be seen by each party.…”

Section: Introductionmentioning

confidence: 99%

Role of supplier evaluation criteria in risk mitigation related to purchasing process

Urbaniak

2021

Engineering Management in Production and Services

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The article aims to present the role of supplier evaluation criteria in reducing purchasing risk. Before a purchasing enterprise starts cooperating with suppliers, it set specific requirements and expectations. The fulfilment of these requirements and expectations is verified through the evaluation of suppliers. Evaluation results should indicate potential risks that may arise in the development of partnership cooperation. The article includes the results of empirical research conducted using the computer-assisted telephone interviewing (CATI) technique in medium and large manufacturing companies operating in Poland. The results of the conducted empirical research indicate that companies wishing to partner with suppliers try to limit the level of risk associated with purchases. When evaluating suppliers, manufacturers focus mainly on reducing the risk associated with the defective technical quality of products, timely deliveries, delivery flexibility, time to restore continuity of deliveries, completeness of order fulfilment and delivery documentation, as well as price competitiveness. Also, in the evaluation of suppliers, companies operating in Poland are beginning to pay attention to the reduction of negative environmental impact.

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Buyer-supplier currency exchange rate flexibility contracts in global supply chains

Cited by 17 publications

References 21 publications

Supply Chain Risk Prevention and Control Based on Fuzzy Influence Diagram and Discrete Hopfield Neural Network

Supply Chain Risk Prevention and Control Based on Fuzzy Influence Diagram and Discrete Hopfield Neural Network

Exclusivity or Competitor Retail? Impacts of Channel Structures on Multinational Supply Chains considering Green Manufacturing

Role of supplier evaluation criteria in risk mitigation related to purchasing process

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