Classical Newsvendor Model Research Articles

The Application of Electronic Information Technology in Building Engineering

At the present stage, the degree of social information intelligence continues to increase, electronic information technology has been widely used in various industries, has become an important part of People's Daily life. Electronic information technology can also promote the development and progress of enterprises, most of the enterprises have begun to use electronic information technology in the process of development, it can be seen that the electronic information technology has considerable prospects for development, this paper analyzes the construction engineering enterprises for the use of electronic information technology, hoping to provide a certain reference to the relevant personnel. The paper firstly reviewed the classic newsvendor model and expounded the establishment and solution to the model. Then the model of the supply chain system was established based on the classical newspaper model. Finally, based on the basic theory of repurchase contract, a repurchase agreement was established. The supply chain buyback contract under the newsvendor model can not only realize the coordination of supply chain, but also realize the distribution of profit in the supply chain.

Newsvendor model with voucher sales: a distributionally robust approach

AbstractVouchers as a popular short‐term marketing tool are widely used by many firms, through which retailers can lock in customers and obtain working capital in advance. Consumers can use the voucher to reduce the product purchase price to an equal face value or purchase the product at a discount. We apply the classical newsvendor model to study the merits of vouchers for the retailer's ordering decision in the face of uncertainties in both the market demand and voucher redemption rate. We propose a distributionally robust approach to solve this newsvendor problem. The approach only requires the first and second moments of the demand and redemption rate distributions and yields a lower bound on the expected profit. Specifically, we derive the optimal ordering decision in closed form and obtain the optimal expected profit based on the limited distribution information. We find that a higher redemption rate does not necessarily increase the retailer's profit and the voucher quantity, but always increases the retailer's order quantity. Interestingly, we show that when the buyback price of the voucher is relatively high, increasing the voucher redemption rate is more profitable for the retailer. In addition, the retailer's profit, and the quantities of the product and the voucher decrease with the buyback price of the voucher.

Optimal Purchasing Decisions with Supplier Default in Portfolio Procurement

As global public health events and regional conflicts have greater influence on supply chains nowadays, supplier default in procurement becomes more and more common in practice. However, there is less research on portfolio procurement purchasing decisions in the case of fixed-term contract supplier default. This paper focuses on the optimal purchasing decision of buyers by using a combination of fixed-term contracts and spot transactions, which is a beneficial extension of the classical newsvendor model. When supplier default is not considered, the optimal purchase quantity in the fixed-term contract is first obtained, which maximizes the buyer’s expected profits. Research shows that supplier default has an important impact on the optimal purchasing decision making in portfolio procurement. The optimal purchase quantity of the buyer in the fixed-term contract decreases with the increase in the default rate of the contract supplier, which implies that the default from the contract supplier inhibits a larger purchase quantity in the fixed-term contract. In addition, it is proved that the buyer’s expected profits from portfolio procurement increases with the decrease in the contract supplier’s default rate. Finally, numerical experiments and sensitivity analysis are conducted to prove the result, and some management opinions on the optimal decision-making in portfolio procurement with fixed-term contracts and spot transactions are put forward.

The newsvendor problem with a non-stationary demand process and exact accounting of holding costs

This work presents an extension of the classical newsvendor model that considers the inventory costs more accurately based on the actual stock-level within the selling period, and not on the stock-level at the end of it. The new feature of this model is that the selling period, which is relatively long, is comprised of n epochs, where the demand distribution in each epoch is known but is not stationary, and holding costs are considered only for the epochs in which the item was stored. A mathematical model is developed to calculate the expected profit, and an optimality equation is provided from which the optimal order quantity can be derived. Using a numerical analysis in a factorial experimental design of a non-homogeneous Poisson demand process, we evaluate the performance of the suggested model in comparison to two approximated standard newsvendor models that disregard the exact inventory costs.

Optimal inventory management with buy-one-give-one promotion

Recently, the Buy-One-Give-One (BOGO) model, where the firm donates one unit of its product for every unit purchased, has emerged as a viable option to practice corporate social responsibility. Despite growing public attention to the BOGO model, optimal inventory management and profitability associated with BOGO has not yet been explored adequately in the academic literature. Under the BOGO promotion, inventory management naturally becomes a key decision, since the firm has to produce an extra unit for each unit sold. In this article, we examine optimal inventory management of the BOGO model under stochastic demand and compare it to the standard newsvendor model as well as a model with cash donation. Analogous to the standard newsvendor model, we clearly define the BOGO fractile and optimal stocking quantity. We show that, counterintuitively, it is not necessarily optimal to produce more units under BOGO, due to the trade-off between give-away commitment and reduced product margin. Moreover, although the BOGO model invariably yields a lower profit than the classic newsvendor model or cash donation model if demand remains the same, there often exists a certain level of positive demand shift that renders BOGO more profitable, which helps explain growing presence of BOGO in the marketplace.

Multi-objective multi-product sustainable newsvendor management in an emerging economy: Evidence and applications

The idea of a sustainable newsvendor problem has been considered by some researchers recently; nonetheless, an inclusive multi-objective model including all sustainability pillars with a multi-product supply chain has not been designed yet. In this paper, the newsvendor model is developed considering all sustainability criteria to study a two-stage procurement system. The classic newsvendor model of optimizing supplier-retailer payoff is considered in this research to illustrate the economic perspective of sustainability. Moreover, other objectives are formulated to model the social and environmental pillars of sustainability. These objectives minimize the environmental effects of the standard newsvendor problem regarding the malicious environmental effects of unrecyclable unsold products. To solve the formulated model a compromise programming approach is hybridized with Lagrange relaxation and sub-gradient optimization for the proposed model. For more clarification, a real-world case study from the Fast-moving consumer goods (FMCG) industry with real data has been employed alongside sensitivity analysis. Moreover, to evaluate the efficiency of the proposed solving approach, the Genetic Algorithm (GA) and Simulated Annealing (SA) algorithm were also designed and their parameters were tuned using the Taguchi method. Comparing the obtained results with the classical newsvendor model, the single economic objective loses at least 0.76% and at most 14.1% of its achievements by a trade-off with sustainable criteria. Furthermore, results indicated that both in terms of optimality and solution time, the proposed method has an extraordinary performance compared to GA and SA.

Joint decision of pricing and ordering in stochastic demand with Nash bargaining fairness

Taking fairness concerns of retailer into account, we extend the classical newsvendor model to a new type with Nash bargaining preference. Depending on the demand forms, three models are proposed: one benchmark case for deterministic demand, and two stochastic demand cases for multiplicative and additive patterns, respectively. We theoretically prove the existence and uniqueness of the optimal joint decision on pricing and ordering by maximising the fairness-concerned retailer’s utility function theoretically. The optimal strategy of the supplier is acquired via one dimensional search method numerically. The results show that the optimal price is increasing in terms of the fairness-concerned parameter, Nash bargaining power and wholesale price. But the optimal ordering changes in an opposite way. Numerical examples and experiments agree well with our theoretical analysis. It is worth noting that the degree of retailer’s fairness concerns can improve the retailer’s utility and performance of the supply chain, which is different from the traditional fairness-neutral scenario.

Inventory strategies for perishable products with two-period shelf-life and lost sales

We develop an inventory model for perishable products with a two-period shelf-life. The demand during a stock out in either period is treated as lost sales. Besides the initial regular order, the manager also has an opportunity to adjust the mid-cycle inventory with either expedited order or returns. An expedited order plan allows the manager to place an emergency order if the mid-cycle leftover inventory is low, while a returns plan offers the manager a chance to return some units within the validity period to suppliers if the leftover inventory is high. We show that both adjustment plans have their own thresholds, which exhibit a similar policy to that in the classical newsvendor model. Due to the dynamics of inventory, we investigate how the regular order is affected by each adjustment plan. Our findings indicate that the expedited order plan has a better performance in controlling the wastage risk, but it results in a higher shortage risk than the returns plan. Considering the respective advantages of the two plans, we show the existence of a new plan that is the combination of the two and justify the motivation for the manager to use it in the perishable inventory management.

A heuristic approach to in-season capacity allocation in a multi-product newsvendor model

Based on an actual problem, we develop and test two heuristics for optimizing the newsvendor’s response to new in-season demand information for a multi-product single-period problem. In this model, in addition to the quantities produced prior to the beginning of the selling season, the newsvendor can produce additional quantities of some products after the selling season begins. Sales data of all products is updated daily, and using these updates, the newsvendor can test if the quantities already produced are still optimal. If the newsvendor finds that the actual demand of a product up to a point in time indicates that the quantity already produced is too small, then the product becomes a candidate for an incremental production quantity. In Heuristic I, we fix the pre-season production quantities to those that are optimal for the classic newsvendor model. In Heuristic II, because the newsvendor may have some recourse during the selling season, we allow for reductions in the pre-season production quantities from the optimal classic newsvendor model production quantities. Using a simulation experiment, we show that even under an unbiased forecast, both heuristics result in higher profit, with Heuristic II outperforming Heuristic I. The increase in profits from using the heuristics increases significantly with the number of products for which the forecast is biased. In addition, the improvements in profits decrease significantly as the lead time and the penalty for late production increase.

Accurate response in agricultural supply chains

• An MMFE-based accurate response framework can improve a commercial seed manufacturer’s profitability significantly. • Implementation of the MMFE in practice can be challenging due to scarcity of historical data and the inconsistent number of forecast updates. • Seeds with low to moderate demand uncertainty should be processed in a few batches relatively early in the planning horizon. • Seeds with high demand uncertainty should be processed according to the multi-ordering strategy following forecast evolutions. In this paper, we introduce an accurate response framework in the context of commercial seed production by deploying the multiordering newsvendor model with dynamic forecast evolution to determine the timing and the quantity of production. We also demonstrate the challenges associated with applying the Martingale Model of Forecast Evolution (MMFE) to real data and propose practical remedies. More specifically, we fit the MMFE to the data for a variety of seeds (SKUs) produced by a major seed manufacturer and rank these SKUs based on their demand volume and volatility. We then assess the value of the MMFE-based accurate response by benchmarking it against the classic newsvendor model. We find that the MMFE-based accurate response can considerably increase the seed manufacturer’s profits by neatly dividing the product portfolio into four quadrants, according to demand volume and volatility, to determine the production timing and quantity. Such portfolio categorization would also enable the salesforce to better allocate their efforts to increase forecasting accuracy for the most critical products in their portfolio.

Procurement decisions over multiple periods under piecewise-linear shortage costs and fixed capacity commitments

Abstract We study optimal procurement in a case where the buyer must match supply against uncertain demand using a combination of low-cost order-in-advance procurement contracts and a high-cost real-time balancing mechanism. The procurement contracts have a two-level structure in which the commitment to procure a fixed quantity for multiple periods has a lower unit-price than period-specific commitments. Moreover, the balancing mechanism implies a salvage value for unused supply and piecewise-linear shortage costs: small shortages (relative to the total quantity procured) are balanced with a lower unit cost than larger shortages. Minimizing procurement costs results in a stochastic non-linear multivariate optimization problem, which can be interpreted as a generalization of the classic newsvendor model. We derive the optimality conditions for this problem and show how they can be utilized to obtain a cost minimizing procurement strategy by solving a series of single variable equations. The model is then applied to support procurement decision making of a pulp & paper company that procures natural gas worth tens of millions of euros annually. This allows us to highlight some key practical implications of our work.

The newsvendor problem with barter exchange

Barter exchange, as an alternative to move distressed inventory, has become increasingly popular in business. Many companies barter their unsold product for the product they need via barter exchange platforms at full prices. In this paper we consider the newsvendor problem with the barter exchange option. A retailer (the newsvendor) facing stochastic demand not only sells its product, but also buys other product that it needs from the market. It either trades its unsold product for the product it needs on a barter platform or disposes of its unsold product at discounted prices at the end of the selling season like in the classical newsvendor model. We derive the retailer’s optimal order quantity, then analytically and numerically examine the impacts of barter on the retailer’s inventory decisions and profit. We find that barter exchange can help the retailer to manage demand uncertainty and improve profit. The optimal order quantity decreases with barter commission and barter uncertainty, while increases with demand uncertainty and the value of the product that the retailer needs. Barter is more advantageous with lower barter commission, larger demand uncertainty, lower barter uncertainty, and higher value of the product it needs.

Beklentile Dayalı Riske Maruz Değer Kriterli Gazete Satıcısı Modeli

In this paper, we use Expectile-based Value at Risk (EVaR) measure as an objective function to determine newsvendor solutions with risk considerations. When the newsvendor makes a decision with risk-driven behavior, the optimal order quantity deviates from the classical expected profit-maximizing quantity. Our EVaR minimization model extends the classical newsvendor model through a one-parameter risk measure and facilitates trade-off analysis between the capital to be held in reserve and the expected profit. To illustrate the proposed model, we present optimal solutions based on different levels of risk aversion and risk-taking for three different demand distributions.

The Loss-Averse Retailer’s Order Decisions Under Risk Management

This paper characterizes the retailer’s loss aversion by introducing a loss aversion coefficient and proposes a new loss aversion utility function for the retailer. To hedge against the risk arising from the uncertain market demand, we use the Conditional Value-at-Risk (CVaR) measure to quantify the potential risks and obtain the optimal order quantity for the retailer to maximize the CVaR objective of loss aversion utility. It is shown that that the optimal order quantity for a retailer to maximize the expected loss aversion utility is smaller than expected profit maximizing (EPM) order quantity in the classical newsvendor model, which can help to explain decision bias in the newsvendor model. This study shows that the optimal order quantity with the CVaR objective can decrease in retail price under certain conditions, which has never occurred in the newsvendor literature. With the optimal order quantity under the CVaR objective, it is proved that the retailer’s expected loss aversion utility is decreasing in the confidence level. This confirms the fact that high return means high risk, while low risk comes with low return. Based on the results, several management insights are suggested for the loss-averse newsvendor model.

Self-Adaptive Newsvendor Model with Information Updated

The use of classical newsvendor model is limited by assumptions and prior probability statistics. Self-adaptive newsvendor model is proposed to divide the sales interval and automatically adjust the differential according to the sales information collected by retailer’s information system. Demand interval and its corresponding demand probability value could be adjusted timely to correct the next order prediction quantity. Based on management information system, model calculation tool is designed to improve the feasibility of the model application. Compared to traditional newsvendor model, self-adaptive newsvendor model can effectively meet the needs of short-period, small-quantity, multi-batch products purchasing.

Asymmetry and Ambiguity in Newsvendor Models

A basic assumption of the classical newsvendor model is that the probability distribution of the random demand is known. But in most realistic settings, only partial distribution information is ava...

Advance selling of new products to strategic consumers on flash sale platforms

ABSTRACTFlash sale (FS) is a new business model that offers discounted products in limited numbers over a short period. In this paper we discuss the impact of strategic consumers on advance selling (AS) of new products on FS platforms. We first study the impact of strategic consumers on competing retailers adopting AS to sell a homogeneous new product. And find that the retailers’ AS profits and inventory quantities decrease with the strategic customers’ valuation and valuation decreasing rate. Then we analyse whether FS can mitigate the impact of strategic customers on retailers adopting AS for new products. We consider a newsvendor model involving only one retailer adopting AS to sell a new product. We derive the results by comparing this model with two counterpart models, namely the classical newsvendor model with no strategic customers and a newsvendor model with strategic customers where the retailer does not use FS under AS.

The price-setting limited clearance sale inventory model

The classical newsvendor problem decides the optimal order quantity for a single period, with the assumptions that both the selling price and the end of period salvage value are fixed. However, the salvage value or clearance price in many instances depends on the leftover inventory. A fixed salvage value assumption could lead to suboptimal decisions in many situations. In this paper we determine the optimal pricing and ordering decision for a limited clearance sale inventory model using newsvendor framework with variable salvage value. We consider additive demand model, provide necessary and sufficient conditions for unique pricing and ordering policies, and calculate optimal contract parameters for wholesale price contract in decentralized supply chain setting. We compare our results against classical newsvendor model with fixed salvage value. We analytically prove that the price-setting limited clearance sale inventory model improves the ordering decision and profit level.

Newsvendor revisited: risk premiums of loss aversion

ABSTRACTThe classical newsvendor model in economics and decision theory treats losses and gains equally likely. However, decision makers are usually loss-averse as probable losses have more impact on humans than probable gains. This study presents a new variant of the newsvendor problem of loss-averse decision makers. The optimal order quantity is found by maximizing the expected utility of bounded functions. The implications of loss aversion on the certainty equivalents and risk premiums were also analyzed. Two case studies of exponential utility and normal demand were considered. A new elegant form of the optimal order quantity is established. The results show that when exponential loss aversion exists, the newsvendor optimal quantity serves as a lower(upper) bound on the optimal quantities. Moreover, high loss aversion entails higher RP. Similar findings hold by increasing the overage/underage costs and the demand standard deviation. Possible future extensions are demonstrated at the end of the paper.

Asymmetry and Ambiguity in Newsvendor Models

A basic assumption of the classical newsvendor model is that the probability distribution of the random demand is known. But in most realistic settings, only partial distribution information is available or reliably estimated. The distributionally robust newsvendor model is often used in this case where the worst-case expected profit is maximized over the set of distributions satisfying the known information, which is usually the mean and covariance of demands. However, covariance does not capture information on asymmetry of the demand distribution. In this paper, we introduce a measure of distribution asymmetry using second-order partitioned statistics. Semivariance is a special case with a single partition of the univariate demand. With mean, variance, and semivariance information, we show that a three-point distribution achieves the worst-case expected profit and derive a closed-form expression for the distributionally robust order quantity. For multivariate demand, the distributionally robust problem with partitioned statistics is hard to solve, but we develop a computationally tractable lower bound through the solution of a semidefinite program. We demonstrate in numerical experiments that asymmetry information significantly reduces expected profit loss particularly when the true distribution is heavy tailed. In computational experiments on automotive spare parts demand data, we provide evidence that the distributionally robust model that includes partitioned statistics outperforms the model that uses only covariance information. The electronic companion is available at https://doi.org/10.1287/mnsc.2017.2773 . This paper was accepted by Yinyu Ye, optimization.