A PC‐based Spreadsheet Support System for the Newsboy
Inventory Control Problem

Al-Faraj, Taqi N.; Al‐Zayer, Jamal A.; Alidi, Abdulaziz S.

doi:10.1108/eum0000000001290

Cited by 5 publications

(2 citation statements)

References 1 publication

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“…Therefore, the new profit function of the manufacturer becomes: πm = Q*×Pm -(Q* -Cm) + IF (Q*>D, (B -Sm) × (Q*-D),0). In carrying out the experiment using a Monte Carlo simulation, data were drawn from [38] and [39]. The first dataset investigates the number of skis to purchase for the winter season from a sporting goods store while the second dataset considers a retailer who sells a perishable product.…”

Section: Conceptual Model and Frameworkmentioning

confidence: 99%

Simulation Study of Collaborative Inventory Management for Seasonal Products by Incorporating Newsvendor and Buyback Contract

Fillie¹,

Arvitrida²,

Pujawan³

2019

Proceedings of the 2019 1st International Conference on Engineering and Management in Industrial System (ICOEMIS 2019)

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As supply chains become leaner, supply chain (SC) managers are often subjected to decrease inventory. Determining the appropriate inventory level for seasonal products without compromising the level of service provided to customers is crucial. This poses a challenge for supply chain managers to find the best trade-off between having excess or less inventory. A well-known model to determine such trade-offs is the newsvendor model. This model is focused on a decentralized business strategy. This research seeks to evaluate the contributions of collaborative inventory management for seasonal products with demand uncertainties having a single order in a cycle through newsvendor and buyback contract for a two-tier SC for both decentralized and centralized business strategies. To explore the effects of these uncertainties on seasonal products such as newspaper, apparels, perishable foods and major holiday products, a Monte Carlo simulation model was used to optimize the decision variable (the maximum order quantity, Q*) to improve the financial performance of the SC. The results indicate that wholesale price discount and buyback contract are efficient in collaborative inventory management. Buyback contract is less attractive when costs associated with returns are high. High return costs reduce the profitability of the SC significantly.

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Section: Conceptual Model and Frameworkmentioning

confidence: 99%

Simulation Study of Collaborative Inventory Management for Seasonal Products by Incorporating Newsvendor and Buyback Contract

Fillie¹,

Arvitrida²,

Pujawan³

2019

Proceedings of the 2019 1st International Conference on Engineering and Management in Industrial System (ICOEMIS 2019)

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“…Spreadsheets are simple to use and user friendly methods of simulation. Spreadsheet systems have been utilized in the waiting line problems (Al-Faraj et al, 1991a), evaluation of optimal order quantity, Newsboy inventory control problems (Al-Faraj et al, 1991b) and VMI models (Disney and Towill, 2003b).…”

Section: Simulation Tool For Dstscccmentioning

confidence: 99%

Development of a decision support tool for supply chain coordination using contracts

Arshinder¹,

Kanda²,

Deshmukh³

2008

Journal of Advances in Management Research

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Purpose: The purpose of this paper is to describe a decision support tool based on various types of contracts in a two-level supply chain. A supply chain (SC) consists of disparate but interdependent members, dependent on each other to manage various resources (inventory, money and information). The conflicting objectives between these members may cause uncertainties in supply and demand, which can be managed by adopting coordination with the help of contracts (such as buyback, revenue sharing and quantity flexibility). Design/methodology/approach: A decision support tool for SC coordination using contracts (DSTSCCC) has been developed to explore the applicability of contracts and to compare different types of contracts in various situations. The DSTSCC is comprised of an analytical module, which is an extension of the classical newsboy problem and a simulation module. Findings: DSTSCCC helps in determining decision variables for different scenarios of contracts in the best interest of all SC members as well as whole SC. Practical implications: DSTSCCC is a simple-to-use and easy-to-implement decision making tool which helps in taking decisions prior to the actual start of SC activities. The prior decisions may help to handle future exceptions. SC members may jointly select the most profitable contract to share risks and rewards. Originality/value: DSTSCCC comprised of analytical module and simulation module presents an Integrative framework which cannot be dealt in isolation. The output of analytical module becomes input for simulation to quantify performance measures. The improvement in performance measures after satisfying the objectives of all SC members helps in realizing coordination in SC.

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