Incremental Discounts Research Articles

MULTI-ITEM PROBABILISTIC INVENTORY MODELS CONSIDERING DISCOUNT, EXPIRATION, WAREHOUSE CAPACITY, AND CAPITAL CONSTRAINTS

In general, companies have inventory stored in warehouses to be used or sold in the future. To optimize inventory, companies require a model to determine the appropriate order quantity and optimal reorder timing to minimize total inventory costs. To stay within the set capacity, several factors need to be considered in inventory management, such as a product's shelf life, warehouse capacity, and capital. On the other hand, suppliers may offer discounts, and companies tend to take advantage of them. However, they must consider the warehouse capacity and capital availability. This paper constructs two probabilistic multi-item inventory models, considering discounts, expiration, warehouse capacity, and capital constraint. The first model considers all-unit discounts, while the second deals with incremental discounts. We consider three items to be managed and examine three replenishment policies, namely individual order, joint order, and a combined policy of individual and joint order, to minimize the total inventory cost. Sensitivity analysis is performed on the joint order policy to determine the influence of parameter values' changes on the reorder time and total inventory cost.

Development of a Green Supplier Selection Model with the Aim of Optimizing the Selection Criteria and Considering Incremental Discounts

Development of a Green Supplier Selection Model with the Aim of Optimizing the Selection Criteria and Considering Incremental Discounts

Covenant violation concern and investors’ pricing of Level 3 fair value adjustments

We examine the influence of concerns relating to violation of the borrowing covenant on the investors’ valuation of Level 3 fair value adjustments. We reason that managerial bias in Level 3 fair value estimation is greater for firms approaching violation of the borrowing covenant. Based on a sample of Australian real estate firms, we find that managers report upward adjustments to Level 3 investment property values when they approach the threshold where the borrowing covenant is violated; and further find that this deliberate use of discretion is significant for firms closer to the interest coverage thresholds, but not for those approaching the gearing thresholds. We then find that, while fair value adjustments are priced positively, investors apply incremental discounts for firms closer to the violation threshold, or firms which are in technical default of borrowing covenants relative to those that are far from violation. Additionally, we show that the pricing discount on fair value adjustments attributable to the concern over covenant violation is significant only for the weaker governance sub-sample, indicating that effective monitoring mitigates faithful representation concerns about Level 3 fair value estimations.

Inventory Model and Pricing in the Supply Chain Approach VMI Considering Incremental Discount

Given the globalization of competition and the existence of many rivals, the optimization supply chain has been highly regarded. One of the key issues in optimizing supply chain is to increase profitability and cost reduction. Since inventories have a large part of the cost of supply chain, the determination of the optimal level of inventory can have an effective role in cost reductions. In addition to costs reduction, attracting a larger share of the demand market can increase profitability. One of the effective factors in attracting customers is market price. On the other hand, discounts on the supply chain will encourage more buy and, of course, buy will further increase the costs. Therefore, this article addresses the issues of simultaneous pricing and inventory control in a supply chain bi-level, and optimal buy policy the mode of existence of incremental discounts and optimal pricing policies has been determined. In this regard, the mathematical model and numerical examples have been solved.

Simultaneous scheduling of multiple construction projects considering supplier selection and material transportation routing

In a construction supply chain, supply-related decisions can affect project scheduling because the project activities require essential resources to start. This study wants to show how the integration of project scheduling with supplier selection and transportation routing creates value in the entire project supply chain. Therefore, an integrated problem including the three mentioned concepts is considered in an organization managing multiple construction projects. Moreover, the following conditions are assumed in the problem to make it closer to the real situations of construction projects: (1) the quality of all projects is inspected by a single committee; (2) suppliers sell the resources with incremental discounts; (3) generalized precedence relations are considered between the project activities. In order to address the research problem, a mathematical model is proposed based on mixed-integer linear programming. The model is hard to solve because it simultaneously involves multi-project scheduling and vehicle routing. Therefore, a solution method based on the tabu search (TS) algorithm is suggested, validated with small-scale and big-scale examples. This method is used to compare the suggested model with two related models. The comparisons show that the proposed model creates a better balance between costs of different sectors in the project supply chain. Achieving this balance decreases the total cost associated with the problem and increases customer satisfaction. As a result of these findings, project managers and related researchers should pay more attention to supply chain integration in their problems.

Development of Order Quantity Optimization Model for Growing Item Considering the Imperfect Quality and Incremental Discount in Three Echelon Supply Chain

This research develops an optimization model for determining the order quantity for growing items by considering the imperfect quality and incremental discount by involving three supply chain members: farmers, processors, and retailers. The farmers are responsible for caring for the newborn items until they reach their ready-to-eat weight. The processors perform two roles, namely processing and screening. In the processing role, the processors process the grown items by a slaughtering and packaging process. Afterward, they inspected the processed items and categorized the items into good and poor quality. Finally, they shipped the end products to retailers. The retailers are responsible for selling good-quality items to the final consumers. This research considers two kinds of poor quality. First is the poor quality of growing items in terms of mortality rate. The second is the poor quality of final products on the processor side. The processed items with poor quality are then sold to the secondary market at lower prices in one batch at the end of the period. This model also considers the incremental discounts offered by vendors to farmers and retailers to consumers for specific amounts of purchases. The model's objective function is to maximize the total supply chain profit, with the number of orders quantity, cycle time, and the number of batches delivery set as the decision variables. The sensitivity analysis results show that the most sensitive parameter in the model is the probability that the live items survive throughout the growth period.

Optimization Model for Determining Order Quantity for Growing Item Considering Incremental Discount and Imperfect Quality

This research develops an optimization model of order quantities for growing items by considering incremental discounts and imperfect quality. For growing items, the assumption that inventory weights that always fixed cannot be applied. The supply system has grown so that the weight of the inventory has increased over a certain period. The proposed inventory system has two periods namely growth and consumption period. Suppliers offer incremental discounts for certain purchases. In this research also considered the existence of imperfect quality, where for newborn items purchased at the beginning of each cycle found items with poor quality and death. During the growth period, not all items survive until the end of the period, therefore also considering the probability density function of survival and death of growing items. The proposed inventory system is maximization profit, with total profits being an objective function, and cycle times and order quantities as decision variables. Costs involved include purchased cost by considering by incremental discounts, setup costs, holding costs, and disposal costs. Application and model validation is demonstrated by numerical examples in the poultry industry. The model developed in this study can be used as a suggestion for companies to make purchasing decisions.

Supplier Selection and Order Allocation Problem Modeling with the Aim of Comparing Incremental Discounts Versus Wholesale Discounts by Using GA and NSGA Algorithms

Supplier Selection and Order Allocation Problem Modeling with the Aim of Comparing Incremental Discounts Versus Wholesale Discounts by Using GA and NSGA Algorithms

Solving inventory lot-sizing with supplier selection under alternative quantity discounts and vehicle capacity

In this paper, we present a multi-product and multi-period inventory lot-sizing problem with supplier selection under alternative quantity discounts and vehicle capacity. Each supplier offers quantity discounts (all-units and incremental discounts) to motivate the buyer for purchasing large quantity. In addition, we consider that the capacity each vehicle of the supplier transport the products to the decision maker (buyer). The objectives are to minimise total costs, where the costs include purchase cost of the products, ordering cost for the suppliers, transportation cost for the suppliers and holding cost of the remaining inventory in each period. The problem is formulated as a mixed integer linear programming (MILP) model. Finally, a numerical example is provided to illustrate the solution procedure. The MILP model can provide a satisfactory solution with a very short elapsed runtime. The results, the buyer needs to determine what products to order in what quantities with which suppliers in which periods, in order to satisfy overall demand.

Model Penentuan Lot Pemesanan Dengan Mempertimbangkan Unit Diskon dan Batasan Kapasitas Gudang dengan Program Dinamis

The classical model of dynamic programming in determining the economical lot size of orders generally considers the cost of orders and inventory costs. However, firms are often confronted with the situation of determining the number of economic orders if the seller gives incremental discounts to the buyer and limits the warehouse capacity. In this paper, explains the model of determining lot order by considering discount and limitation of warehouse capacity with dynamic program. The dynamic program model is compared with the Economic Order Quantity (EOQ) model considering the discount and the limitation of warehouse capacity. The comparison result shows that dynamic programming model can minimize total inventory cost compared to EOQ.

Quasi Exclusive Dealing

A firm's discounting policies over a single product raise concerns analogous to dealing in two situations. First, the firm may offer conditional discounts structured in such a way as to induce customers to take most of their requirements for a given product from the defendant. In addition, a firm may employ “slotting” fees or similar allowances paid by manufacturers to retailers, with the possible result that rivals have difficulty obtaining access to shelf space. Neither practice is literally exclusive dealing, because neither involves a condition that the purchaser not deal in the goods of a rival, although they may create a pricing incentive for it not to do so.Most quantity discount programs are undoubtedly designed to reflect the reduced costs of larger transactions. But suppose that a discounting program is clearly in excess of anything justified by significant savings. For example, suppose that the program gives incremental discounts stretching up to very large volumes and permits the aggregation of all purchases over a lengthy period, say one year. If dealing under equivalent structural conditions and subject to equivalent defenses were lawful, the discount arrangement should be lawful as well. But the competitive impact must in fact be less because any equally efficient rival can take the customer by bidding a better price and even compensating the customer for the loss of the discount from the defendant. Some discounts take the form of upfront payments from producers to grocers or other retailers for access to the retailer's shelf space. For example, a grocer may wish to allocate scarce display space to only two of the three major brands of prepared baby food. These allowances are generally paid to retailers in order to induce them to carry and display a product whose prospects are uncertain to the retailer. The special characteristic of the slotting allowance that gives it this risk-transferring property is that it is a discount that diminishes as the volume of goods sold increases, effectively making the supplier share in the risk that a product will not succeed at retail.Challenges to above cost discounting, where the engine of exclusion is price, must meet more severe structural requirements than dealing. Indeed, predatory pricing is a “monopolization” offense requiring significant market shares in at least the 60-70% range, and it would be perverse to assess stricter structural requirements in cases involving below cost pricing than in those challenging prices that are above cost.

A multiproduct economic order quantity model with simulated annealing application

PurposeThis paper aims to present a set of five models for the economic order quantity problem. Four models solve problems for a single product: incremental discounts with or without backorders and all-unit discounts with or without backorders, and the last model solves problems for the multiproduct case.Design/methodology/approachA basic integer non-linear model with binary variables is presented, and its flexible structure allows for all five models to be utilised with minor modifications for adaptation to individual situations. The multiproduct model takes into consideration the work of Chopra and Meindl (2012), who studied two types of product aggregations: full and adaptive. To find optimal or near-optimal solutions for the multiproduct case, the authors propose a simulated annealing metaheuristic application. Numerical examples are presented to improve the comprehension of each model, and the authors also present the efficiency of the simulated annealing algorithm through an example that aggregates 50 products, each one with different discount schemes and some allowing backorders.FindingsOur model proved to be efficient at finding optimal or near optimal solutions even when confronted with mathematical complexities such as the allowance of backorders and incremental discounts. Originality/valueFinally our model can process a mix of products with different discount schemes at the same time, and the simulated annealing metaheuristics could find optimal or near optimal solutions with very few iterations.

Threshold discounts comparison: All-unit or incremental?

An increasingly ubiquitous discount format in retailing that is taking over traditional price cuts is threshold discount, under which a price reduction is awarded to a purchase that meets a minimum quantity or minimum spending requirement. One of the most frequently used forms of threshold discounts is the all-unit discount, where a discount applies to all units of the promoted item that the customer purchases as long as the total basket size reaches the predetermined minimum requirement. On the other hand, under another type of threshold discounts known as incremental discount, the reduced price is granted for only the units purchased beyond the threshold; the customer still pays the full price for the first units up to the threshold. In this paper, we are interested in comparing the effectiveness of using all-unit discounts and incremental discounts in a retail setting. We consider a retailer selling to a market of heterogenous consumers, whose purchase decisions are modeled and analyzed at the individual customer level. The optimal discount terms and the seller’s profits when using the all-unit and incremental discounts are investigated under different market scenarios. We show that when the discount terms can be fully optimized, the incremental discount is always more profitable to the retailer than the all-unit discount. Furthermore, in many cases, the resulting consumer utility as well as the social welfare is also greater under the incremental discount than under other discount schemes. Our study suggests that the incremental discount, while not currently popular in retailing, is in fact a very profitable and efficient retail pricing mechanism that deserves more attention.

Audit Firm Reputational Consequences of Alleged Non-Accounting Misconduct by Clients

This study examines whether U.S. audit firms experience reputational damage when clients are accused of misconduct that does not affect auditor litigation risk. Auditors have minimal, if any, responsibility related to non-GAAP securities fraud class actions, our proxy for such misconduct, but bounded rationality suggests that auditors could still incur reputational damage from these suits. In the year after suit filing, fees are lower for the auditor’s clients in the same city-industry as the sued client, but are unchanged for clients of other auditors in the same city-industry. This effect is stronger (1) for new engagements, suggesting auditors must provide incremental discounts to win new clients, and (2) when suits are severe, likely because the negative information is more salient. Overall, these results provide evidence that reputation is an important incentive for U.S. audit firms. This study also contributes to mounting archival evidence of systematic biases and cognitive errors by corporate decision-makers.

Menu Implementability and Practical Pricing Schemes

In the context of monopolistic nonlinear pricing, we compare the maximum pro…ts of bundling, incremental discounts, and all-units discounts. When the number of pricing blocks is unrestricted, incremental discounts perform weakly the worst. However, if the performance of incremental discounts is not strictly worse when the number of blocks is unrestricted, then it performs the best when the number of blocks is restricted. It is because incremental discounts have the smallest implementation power and the largest approximation power. These results are applications of our general theory of menu implementability, which characterizes the set of outcomes implementable by a menu of tari¤

Shared resource capacity expansion decisions for multiple products with quantity discounts

When multiple products compete for the same storage space, their optimal individual lot sizes may need to be reduced to accommodate the storage needs of other products. This challenge is exacerbated with the presence of quantity discounts, which tend to entice larger lot sizes. Under such circumstances, firms may wish to consider storage capacity expansion as an option to take full advantage of quantity discounts. This paper aims to simultaneously determine the optimal storage capacity level along with individual lot sizes for multiple products being offered quantity discounts (either all-units discounts, incremental discounts, or a mixture of both). By utilizing Lagrangian techniques along with a piecewise-linear approximation for capacity cost, our algorithms can generate precise solutions regardless of the functional form of capacity cost (i.e., concave or convex). The algorithms can incorporate simultaneous lot-sizing decisions for thousands of products in a reasonable solution time. We utilize numerical examples and sensitivity analysis to understand the key factors that influence the capacity expansion decision and the performance of the algorithms. The primary characteristic that influences the capacity expansion decision is the size of the quantity discount offered, but variability in demand and capacity per unit influence the expansion decision as well. Furthermore, we discover that all-units quantity discounts are more likely to lead to capacity expansion compared to incremental quantity discounts. Our analysis illuminates the potential for significant savings available to companies willing to explore the option of increasing storage capacity to take advantage of quantity discount offerings for their purchased products.

A literature review on lot size with quantity discounts: 1995-2013

Purpose – This paper aims to present a literature review on models developed for the economic order quantity (EOQ) problem with incremental and all-units discounts, extending the work of Benton and Park (1996) which covered the most significant literature, from 1963 to 1994, about EOQ with discounts and that has identified four open areas in this field of study. The modeling of lot size with discounts wishes to give good solutions for realistic situations, such as those concerning the discounts offered by suppliers, to rises in the demand. Design/methodology/approach – The research was carried out in papers published from 1995 to 2013, and indexed in databases as Scopus and ISI Web of Science. The papers were compared through objective function, constraints, discounts, developed algorithms, allowance of shortages or multiproduct, demand pattern and buyer or buyer–supplier perspective. Findings – Results indicate two areas that still remain untouched, and probably the main cause is due to mathematical complexities. The authors have also identified an increasing trend of works that compared just-in-time with the EOQ with quantity discounts policy and also an increasing number of works that solved this category of problems with algorithms. Research limitations/implications – The research does not cover materials published in working papers, monographs, thesis, conferences or journals that are not indexed in those databases. Originality/value – This manuscript fills a gap in the study of EOQ with incremental discounts, as it highlights the leading edge advances in this field and the main differences among models. As a whole, the new trends about modeling EOQ problems with quantity discounts were discovered.

An economic order quantity model with partial backordering and incremental discount

Determining an order quantity when quantity discounts are available is a major interest of material managers. A supplier offering quantity discounts is a common strategy to entice the buyers to purchase more. In this paper, EOQ models with incremental discounts and either full or partial backordering are developed for the first time. Numerical examples illustrate the proposed models and solution methods.

Supplier Selection Problem: A Multi-Objective Model Considering both All-Unit and Incremental Discounts with Multiple-Item

In supply chain management, supplier selection has a special importance. In this paper, a multi-objective model is developed based on decisions on quality, service level and cost of purchased goods. The difference of this research is to consider discount parameter into the model. A numerical example for three proposed suppliers is interpreted. The model has been solved in two steps: 1-single-objective, 2-multi-objective approach. According to Lpmetric solution, results can predict optimum selection of suppliers as well as the purchased goods amount. The results show that the single objective problem has better result than multi-objective function. This paper is organized by six sections: in next section, some previous studies and researches on supplier selection problem considering discount and non-considering discount have been discussed. In section 3, mathematical formulation of the supplier selection model considering all-unit and incremental with multiple-item is presented. In section 4, aLP metrics solution is dedicated. In section 5, a numerical example is given and the results are presented. Finally in section 6, conclusions of this research are discussed.

A multiobjective portfolio rebalancing model incorporating transaction costs based on incremental discounts

In this paper, we propose a multiobjective model of portfolio rebalancing problem considering return, risk and liquidity as key financial criteria. Further, a more realistic situation of financial market is considered where the portfolio, at the end of a typical time period, will be modified by buying and/or selling asset(s) in response to changing conditions. We assume that the transaction costs are paid on the basis of incremental discounts and are adjusted in the net return of the portfolio. A real-coded genetic algorithm (RGGA) is developed to solve the portfolio rebalancing problem and build an optimal portfolio. An empirical study is included to illustrate the behaviour of the proposed model using data of some randomly selected assets listed on the National Stock Exchange (NSE), Mumbai, India.