Discounting Strategy Research Articles

Prescription rebate guarantees: employerinsights.

To describe (1) rebate arrangements for specialty drugs, (2) the use and influence of benefits brokers and consultants, and (3) the importance of rebate-related factors when selecting a pharmacy benefits manager (PBM) among a sample of employers with self-funded pharmacybenefits. A national survey of employer drug benefit decision makers (N = 110) for organizations with self-insured pharmacy benefits. We summarized respondents' current rebate agreements for specialty drugs and their perspectives on the importance of rebates and rebate guarantees overall as well as by type of rebate agreement and by the person or entity identified as most influential in rebate strategy. Nearly two-thirds of employers reported having rebate agreements with a rebate guarantee for specialty drugs (n = 69; 62.7%). The person or entity most influential to rebate strategy decisions was often a benefits consultant (37.3%), a human resources/benefits leader (29.1%), or a benefits broker (21.8%). Employers with rebate guarantees ascribed a higher level of importance to guarantees when selecting a PBM (median [IQR], 9 [7-10]) than employers receiving rebates without a guarantee (7 [6-8]) and those who do not receive rebates (7.5 [4-9]) (P = .001). These findings shed light on the importance of rebate guarantees and the role of employer benefits consultants and brokers in PBM selection. Asthe public discourse on PBMs and drug rebates continues, it is important to recognize the role employer benefits consultants may play in perpetuating employer reliance on guaranteed rebate arrangements.

Incentive strategies of an e-tailer considering online reviews: Rebates or services

This paper mainly considers an e-tailer-Stackelberg supply chain and characterizes the formative processes and distinct impacts of positive reviews and negative reviews on consumer purchases. The e-tailer can adopt either a pre-sales strategy (i.e., service strategy) or an after-sales strategy (i.e., rebate strategy) to encourage consumer purchases and stimulate positive reviews. By studying the above two strategies, we show that: (1) positive reviews and negative ones will exert a synergistic adverse effect on price decisions. (2) Given the exogenous rebate and service levels, the service (rebate) strategy becomes optimal for the e-tailer if consumers are more (less) willing to leave positive reviews. Notably, the e-tailer should refrain from adopting any incentive strategy when consumers exhibit a moderate willingness to provide positive reviews. (3) When the e-tailer can determine rebate and service levels, it should adopt the service (rebate) strategy if the threshold for positive reviews is intermediate (very low or high).

Sharing is caring: Designing incentive rebate strategies for information‐sharing alliances

AbstractInformation security plays a crucial role in organizational governance and management, and information‐sharing alliances (ISAs) have emerged as effective platforms for the secure and controlled sharing of information security knowledge. Despite their potential, many ISAs face financial and operational challenges, including inadequate pricing policies and insufficient incentives for information sharing. This study addresses these challenges by proposing a modeling framework for the fee rebate strategies that ISAs can deploy to motivate effective information sharing. Taking into account the economic implications of both information sharing and information security technology investment, we propose two ISA‐based pricing rebate strategies for information sharing: the split‐return rebate strategy and the swap‐return rebate strategy. Analytical and numerical analyses are conducted to demonstrate the dynamics in different ISA settings under these pricing rebate strategies. The results suggest that in addition to firm size, the price for participating in sharing should be adjusted based on each participating firm's technology investment level, its information‐sharing level, and the marginal cost of information sharing. Also, by focusing on various information‐sharing environments, the study identifies specific conditions under which unfair sharing practices are likely to occur.

Differences in Discounting Behavior and Brain Responses for Food and Money Reward.

Most neuroeconomic research seeks to understand how value influences decision-making. The influence of reward type is less well understood. We used functional magnetic resonance imaging (fMRI) to investigate delay discounting of primary (i.e., food) and secondary rewards (i.e., money) in 28 healthy, normal-weighted participants (mean age = 26.77; 18 females). To decipher differences in discounting behavior between reward types, we compared how well-different option-based statistical models (exponential, hyperbolic discounting) and attribute-wise heuristic choice models (intertemporal choice heuristic, dual reasoning and implicit framework theory, trade-off model) captured the reward-specific discounting behavior. Contrary to our hypothesis of different strategies for different rewards, we observed comparable discounting behavior for money and food (i.e., exponential discounting). Higher k values for food discounting suggest that individuals decide more impulsive if confronted with food. The fMRI revealed that money discounting was associated with enhanced activity in the right dorsolateral prefrontal cortex, involved in executive control; the right dorsal striatum, associated with reward processing; and the left hippocampus, involved in memory encoding/retrieval. Food discounting, instead, was associated with higher activity in the left temporoparietal junction suggesting social reinforcement of food decisions. Although our findings do not confirm our hypothesis of different discounting strategies for different reward types, they are in line with the notion that reward types have a significant influence on impulsivity with primary rewards leading to more impulsive choices.

Can the Conditional Rebate Strategy Work? Signaling Quality via Induced Online Reviews

Online reviews are an important part of product information and have important effects on consumers’ purchasing decisions. Some sellers try to manipulate the market by inducing online reviews. In this study, a signal game model based on Bayesian conditional probability is constructed to analyze the preconditions, decision-making process, and effect on market demand and profit of this behavior. The results show that first, when consumer sensitivity to rebates reaches a certain threshold, low-quality sellers will adopt a conditional rebate strategy to induce consumers to give positive reviews. Second, the optimal rebate cost (β*) is obtained, where β* increases with the product price (p), but it is not necessarily monotonic in consumers’ sensitivity to rebates (ρ) or the proportion of high-quality products (α). Third, the conditional rebate strategy can only work in a market dominated by low-quality goods. Using the conditional rebate strategy in a market dominated by high-quality goods will not bring benefits to low-quality sellers but will harm their profits. This study proposes that some developing online markets have collusive behaviors owing to a lack of regulations and laws, as well as consumers’ concern for small interests. Ensuring the orderly development of online markets will require joint efforts by platform enterprises, government agencies, and consumers.

Consumer rebate strategy for a manufacturer selling price‐quality differentiated products

AbstractIn this study, we consider a scenario where a manufacturer offers two price‐quality differentiated products, which we label “regular” and “upgraded,” through a retailer and uses direct rebates to customers to stimulate sales. Therefore, the critical question posed is: If a customer rebate is provided, should it be on the regular, upgraded, or both products? Consequently, we compare the outcomes of eight options from a manufacturer's perspective. The analysis reveals that the manufacturer's choice is not straightforward. Rebates on both products can lead to higher profit for the manufacturer if the proportion of rebate‐sensitive consumers is moderate. However, product quality becomes critical as the proportion of rebate‐sensitive consumers increases. If the quality of the regular product is too high or too low, then the manufacturer may use a rebate only on the regular product; otherwise, it should be on only an upgraded product. The rebate value on an upgraded product continuously decreases with regular product quality if a rebate is introduced only on an upgraded product, but its nature changes in other contexts. Quality improvement investment is also a critical factor that affects the manufacturer's decision. Because an analytical assessment of the effectiveness of rebate promotion under the price‐quality consideration is still missing in the literature, the decision to initiate a rebate promotion might be considered on an ad hoc basis. Therefore, the explicit thresholds identified in this study can help managers to make rebate decisions comprehensively.

Research on Time-Based Fare Discount Strategy for Urban Rail Transit Peak Congestion

To alleviate peak-hour congestion in urban rail transit, this study proposes a new off-peak fare discount strategy to incentivize passengers to shift their departure time from peak to off-peak hours. Firstly, a questionnaire survey of Shanghai metro passengers is conducted to analyze their willingness to change departure time under different fare strategies. Secondly, based on the survey results, a time-differentiated fare discount model is constructed, considering both the company’s revenue and passengers’ travel benefits, and with the optimization objective of achieving balanced peak-hour and off-peak-hour train loads throughout the day. Subsequently, a genetic algorithm with nested fmincon functions is designed and combined with the actual data of Shanghai rail transit line 9 for arithmetic analysis. Finally, the effectiveness of the model is validated using the survey data. The research results show that the off-peak fare discount strategy can incentivize 6.88% of passengers traveling in the morning peak and 6.66% of passengers traveling in the evening peak to shift to off-peak travel. This research provides theoretical support and decision-making guidance for implementing time-differentiated pricing in urban rail transit systems.

Analysis of online rebates and commission formats in a retailer‐Stackelberg supply chain with cashback website

AbstractMotivated by the fact that many e‐tailers offer online rebates through cashback websites to attract more consumers, and wield channel leadership, we construct a retailer‐Stackelberg supply chain comprised of one e‐tailer, one manufacturer, and one cashback website. Cashback websites have two commission formats: sharing and fixed. We first explore the online rebate strategy of the e‐tailer (under the two commission formats); and then study the e‐tailer's commission format selection strategy when offering rebates. Our analysis reveals that: (i) the product valuation and fraction of low‐end consumers play key roles in shaping the e‐tailer's online rebate and commission format selection strategies; (ii) the e‐tailer's rebates increase the wholesale price under sharing commission, but decrease it under fixed commission; (iii) the e‐tailer's rebates may be a trap for consumers because they may pay a higher retail price after rebates; (iv) under both commissions, the e‐tailer's rebates hurt the manufacturer, but could enhance supply chain performance; and (v) when offering rebates, low‐end consumers and the manufacturer are better off under sharing commission if its product valuation is sufficiently low, while high‐end consumers are better off under fixed commission. Additionally, the e‐tailer has a stronger incentive to provide rebates when the manufacturer acts as the leader; temporary rebate promotion may lead to a triple win situation for the manufacturer, e‐tailer, and consumers.

Optimal joint trade‐in rebate strategies in a retailer‐led supply chain

This study investigates the joint trade‐in rebate strategies in a supply chain with independent manufacturers selling substitutable products via a dominant retailer. We model their interplay as a Stackelberg game and analyze their joint trade‐in rebate decisions. We find that the differentiated trade‐in rebate scheme is better for the retailer, and the manufacturers cooperating in making their trade‐in rebate decisions can achieve win‐win results in most cases. However, replacement consumers could benefit from the retailer's uniform trade‐in rebate scheme and the manufacturers not cooperating in their trade‐in decisions. The latter is always more beneficial to the environment.

Manufacturer rebate strategy under chain to chain competition

This article builds an analytical framework for manufacturers developing rebate strategies under the chain to chain competition. We demonstrate that rebates are likely to be implemented by manufacturers in both more cost-effective and less cost-effective business environments. We show that manufacturers are more likely to use more cost-effective rebates than less cost-effective rebates when the price competition between two chains is intensified. Rebate can be a dominant strategy for both manufacturers and retailers under two conditions: the market with a small percentage of the rebate-sensitive segment, plus (1) fierce competition and more cost-effective rebates, or plus (2) less cost-effective rebates. Our research provides a reference frame to design price discrimination mechanisms and some management insights for manufacturers.

Operation and Management Strategy of Online Car-Hailing Platforms Based on Big Data Diagnosis and Game Perspective

With the implementation of a series of preferential strategies by online car-hailing companies, the contradiction between online car-hailing and traditional taxis and passengers has become more and more intense. Coordinating the interests of the three parties has become increasingly important. In order to coordinate the contradiction between online car-hailing and traditional taxis and passengers and to manage the online car-hailing and traditional taxis reasonably, this paper conducts research on the operation and management strategy of online car-hailing platform based on big data diagnosis and game perspective. In order to solve the problem of online car-hailing platform operation and management strategy, this paper adopts a research method combining qualitative judgment and quantitative analysis and conducts research by combining specific logic deduction, field investigation, empirical research, mathematical analysis, and computer simulation. The results found that while the platform rate was reduced to 0.085, the daily income of online motorists increased from 170 yuan to 236 yuan, by 38.6%. In the event of a reduction in taxi fares to -3500, one hire the daily income of motorists increased from 134 yuan to 212 yuan, an increase of 57.8%. This shows that reducing the percentage of the platform has the greatest impact on the revenue of online car-hailing companies, and the recharge rebate strategy has the least impact on the revenue of online car-hailing companies. The strategy of reducing elementary money concessions can greatly increase the income of taxi drivers, but it also reduces nearly one-third of the income of taxi companies.

High Utility Item-Set Mining From Retail Market Data Stream With Various Discount Strategies

High Utility Item-set Mining (HUIM) is the futuristic remodel version of Frequent Item Mining (FIM). It has the ability to discover customer purchase trends in the retail market. By using that knowledge, retailers can incorporate innovative schemes (discounts, cross-marketing, seasonal sales offers,... etc) to enhance profit. Even though many HUIM algorithms are proposed to detect profitable patterns, most of them cannot be applied to all kinds of retail market data sets due to certain assumptions. The first assumption is that the items always produce a positive profit. But in reality, even though overall profit could be positive, some of the items make negative profit. The second one is they are developed for static transactional data. Those are useful to take decisions at some intervals like quarterly, half-yearly, yearly. But, to take decisions at any time by analyzing the present sales trend, it is required to process the data stream.

Customized Critical Peak Rebate Pricing Mechanism for Virtual Power Plants

To address the increasing impact of extreme temperatures (ETs) on the power system and electricity supply, demand response (DR) programs are widely used to reduce peak demands at ETs. The customized pricing mechanisms are required for an effective DR to target the potential consumers accurately. This paper proposes a frequency control ancillary service and critical peak rebate (FCAS-CPR) strategy based on cumulative prospect theory (CPT) for a virtual power plant (VPP) in coupled FCAS and DR markets. In order to develop a customized pricing model in the proposed strategy, the load clustering technique is applied. This aims to classify the loads based on the typical characteristics of consumers’ reactions to ETs. The consumers’ load reactions to ETs are described by the peak temperature sensitivity and the lag length. Then, the subjective decisions of irrational consumers are reflected based on the CPT. Last, the interaction between VPP consumers and the retailer is modeled as a Stackelberg game and solved by the Salp Swarm Algorithm (SSA). The simulation results verify the effectiveness of the proposed FCAS-CPR pricing mechanism, which can efficiently reduce the peak loads to mitigate impacts of ETs on power systems, while achieving a win-win outcome in maximizing the utilities of both the retailer and VPP consumers.

Critical peak rebate strategy and application to demand response

Time-of-use (TOU) pricing strategy is an important component of demand-side management (DSM), but the cost of supplying power during critical peak periods remains high under TOU prices. This affects power system reliability. In addition, TOU prices are usually applicable to medium- and long-term load control but cannot effectively regulate short-term loads. Therefore, this paper proposes an optimization method for TOU pricing and changes the electricity consumption patterns during the critical peak periods through a critical peak rebate (CPR). This reduces generation costs and improves power system reliability. An optimization model for peak-flat-valley (PFV) period partition is established based on fuzzy clustering and an enumeration iterative technique. A TOU pricing optimization model including grid-side and customer-side benefits is then proposed, and a simulated annealing particle swarm optimization (SAPSO) algorithm is used to solve the problem. Finally, a CPR decision model is developed to further reduce critical peak loads. The effectiveness of the proposed model and algorithm is illustrated through different case studies of the Roy Billinton Test System (RBTS).

Optimal rebate strategy for an online retailer with a cashback platform: commission-driven or marketing-based?

This paper analyzes an emerging rebate mode where a cashback website not only serves as a promotional device in generating more sales for an online retailer, but also makes decisions on its marketing effort autonomously under certain product availability conditions set by the online retailer. Using a game-theoretic approach, this paper analyzes the optimal decision of both parties in commission-driven rebate mode and marketing-based rebate mode in a market dominated by the online retailer and cashback website respectively. Our main findings are as follows: (1) In the Retailer Stackelberg (RS) game, which rebate mode an online retailer will adopt is related to the marketing cost of the rebate channel and the consumer utility discount (UD) factor. (2) Both rebate modes will help the retailer to expand the market and increase profit because of price differentiation. (3) There is a possible price trap in marketing-based rebate mode. (4) In RS game, the effect of consumer UD factor on the optimal marketing effort is related to the product availability in the rebate channel. (5) In both RS game and Cashback-website Stackelberg (CS) game, the online retailer should strive to become a leader. However, the cashback website prefers the online retailer to be a leader when marketing cost is relatively low in the marketing-based mode. Our results, consistent with several real-world observations, have useful implications for marketers.

Efficacy of retailer rebates and delayed incentives under customer heterogeneity

In automobile and household appliances, the manufacturer’s decision to offer retailer rebates to retailers or delayed incentives directly to end customers is very important. Under game theoretic environment, we show that delayed incentive is an important tool not only for price discrimination but it also provides more flexibility to the manufacturer. We differentiate the impact of delayed incentives and retailer rebates. We draw implications for optimal rebate strategies for both retailer rebates and delayed incentives. We also discuss delayed incentives in the form coupons that give more control to the manufacturer, whereas retailer rebates require retailer’s participation. Analysis and numerical insights show that the manufacturer prefers better observance of retail price. We provide a decision rule to the manufacturer on how to select the rebate type based on customer heterogeneity.

Rebate Strategy Selection and Channel Coordination of Competing Two-Echelon Supply Chains

Rebate has long been a crucial tool that has attracted researchers from a diverse range of fields including marketing and supply chain management. When a manufacturer uses a retailer for reaching end customers, the rebate strategy undertakes an additional dimension. Here we show whether the two rebate strategies, manufacturer rebate and channel rebate, can be the optimal choice for the manufacturer and the retailer. And we aim at full coordination with rebate. Game theory is exploited to identify the equilibrium rebate decisions, which are fully characterized with two rebate strategies considering rebate sensitivity. Furthermore, we demonstrate how the decisions depend on parameters, such as market size, rebate redemption rate, and competition intensity in monopoly and duopoly supply chain systems. Our work also coordinates the supply chain with two coordination policies and examines if they can achieve full coordination. Counterintuitive findings suggest that the channel rebate with sensitivity and discrimination is not effective and the manufacturer rebate is the unique optimal option. Besides, the coordination can be realized with a centralized rebate in monopoly setting when the manufacturer forgoes her own interest. Then full coordination can be achieved in duopoly setting with a new coordination policy, rebate combination, given the redemption rate for the channel rebate is lower compared with the manufacturer rebate. Managerial insights are suggested that offering rebates with discrimination can have significant inventory and coordination policy implications and can lead to a double win under a well-controlled redemption rate.

Collaborative Rebate Strategy of Business-to-Customer Platforms Considering Recycling and Trade-Ins Simultaneously

B2C (business to customer) platforms like JD.com and Suning.com often cooperate with professional recycling companies, and implement recycling programs and trade-in programs simultaneously, especially for electronic products. The former means that platforms recycle old products from customers with cash, whereas the latter means that platforms allow customers to trade in old products for new ones. Under this background, we discuss how to develop the optimal rebate strategy for B2C platforms based on the market recovery price of old products, and give the optimal rebate prices and feasible conditions of single-rebate, dual-rebate, and none-rebate strategies. The results show that the single-recycling rebate strategy is dominant when the residual value of old products is low, and when the residual value of old products is high, platforms should choose in turn the single-trade-in rebate strategy, dual-rebate strategy, single-recycling rebate strategy, and non-rebate strategy with the increase in the cost of new products. In order to obtain higher profits, B2C platforms should provide appropriate rebates to better coordinate the recycling program and the trade-in program on the basis of the market recovery price, the residual value, and the durability of old products as well as the cost, the selling price, and the upgrade range of new products.

An Order Quantity Scheme for Ramp Type Demand and Backlogging during Stock out with Discount Strategy

An offer of reduction in per unit purchasing cost which depends on purchasing quantity attracts and promotes the customers for bulk purchasing. But bulk purchasing of inventory also increase the distinct related costs such as deterioration and holding. In this model we have presented an inventory problem combining all these factors with ramp type demand and quantity discount under partial backlogging. The new launched electronic items and fashionable products follow a ramp-type function for demand. Initially the demand for such product rises with time, and it becomes constant after a certain time. Here, a mathematical model developed to analyse the suitable purchasing amount and to optimise the model. The model is demonstrated numerically, and a sensitivity analysis is also performed to validate the system.

Ladies' Day at Boston Red Sox Games: How Discounted Admission for Women Impacted Game Schedules

Ladies' Day at Boston Red Sox GamesHow Discounted Admission for Women Impacted Game Schedules Charlie Bevis (bio) At a Monday afternoon ball game on June 23, 1947, an estimated twenty thousand women sought admission to Ladies' Day at Fenway Park for the game between the Boston Red Sox and Detroit Tigers. However, only 9,813 of those women actually scored entry into the ballpark, as the other ten thousand or so were shut out at the ticket window and remained milling outside the ball-park for more than an hour. The Boston Globe reported that it was "the largest Ladies' Day crowd in Boston baseball history," for a promotion that dated back twenty-four years to its reinstitution at Fenway Park in 1923.1 Red Sox management had to deny entrance to thousands of female fans because there were no more seats in the grandstand to fill that afternoon, since total attendance that day was a near-capacity crowd of 34,160. The paid attendance was 20,652, supplemented by those 9,813 with Ladies' Day passes and the 3,695 passes the Red Sox provided to members of local youth groups. The club never anticipated a sellout crowd that day. "Because of this situation, the Red Sox announced a new policy for future Ladies' Days," the Globe reported. "Women will have to buy their tax and service charge tickets in advance," rather than on the day of the game. The "tax and service charge" associated with a Ladies' Day ticket in 1947 was fifty cents, less than one-half the price of the usual $1.20 ticket for an unreserved grandstand seat.2 The unanticipated high demand for Ladies' Day tickets was sparked by the inaugural night game at Fenway Park ten days earlier on Friday, June 13, and accelerated by the next two night games there on Wednesday, June 18, and Friday, June 20. Night baseball's arrival at Fenway that season created enormous excitement in Boston. The Red Sox were the next-to-last ball club in the American League to install lights, expanding the opportunity to attend a weekday ball game to an entirely new swath of the Greater Boston population that had work or home obligations on weekday afternoons. The two Friday night games at Fenway Park kiboshed the usual Friday [End Page 112] afternoon Ladies' Day games, which the Red Sox had regularly staged since the Great Depression. This established June 23 as a replacement for Ladies' Day, which itself created a small pent-up demand. Perhaps more importantly, the fourth night game of the season was slated for Tuesday, June 24, for which advance-sale tickets were no longer available. Many women appear to have opted to attend Ladies' Day on June 23 rather than take their chances on obtaining day-of-game tickets for the June 24 night game, enlarging the usual quorum of women expected for a Ladies' Day game. This surge of women seeking discounted tickets for a two o'clock game on a Monday in June 1947 marked the apex of Ladies' Day attendance for a Red Sox game in Boston. However, the surge was also an omen of the forthcoming obsolescence of the promotion by the Boston Red Sox. Ladies' Day games played an important role in the development of professional baseball as a business. This article uses a five-stage model to examine how Ladies' Day was instrumental in the evolution of game scheduling, using the first seven decades of the Red Sox franchise as a specific example. Each of these five stages served a distinct purpose to bridge an issue, which involved a different discounting strategy for admission as well as a separate rationale to encourage female attendance at the discount: • Stage 1 (1901–1908)—Bridge to popularity in Boston • Stage 2 (1923–1929)—Bridge to Sunday games • Stage 3 (1930–1935)—Bridge through the Great Depression • Stage 4 (1936–1947)—Bridge to night games • Stage 5 (1948–1965)—Bridge to demise of weekday daylight games This essay is structured into six sections. After the first section reviews the roots of Ladies' Day in Boston during the nineteenth century, the essay proceeds chronologically to explore...