No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Impact of product sharing and heterogeneous consumers on manufacturers offering trade-in programs
... However, a number of factors, including pricing, recycling services, and the consumer's valuation of products, might have a complex impact on customers' willingness to participate in the trade-in program. Moreover, for the manufacturer, although remanufacturing the old products collected by trade-in programs can save on production costs [4], providing the cash rebate elevates operational expenses and obscures the cash rebate's impact. Therefore, whether cash rebates for the trade-in program should be provided and by whom are crucial issues that need to be further explored and clarified. ...
As the consumer market becomes more saturated, the e-commerce supply chain (E-SC) has introduced the trade-in program in an attempt to drive consumption. This paper considers the strategy of the E-SC to provide cash rebates for consumers participating in the trade-in program and incorporates the e-commerce platform’s trade-in service efforts into the E-SC’s decision-making system. Depending on who provides the cash rebate, we construct four decision-making models of the E-SC, i.e., the no-cash-rebate model, the manufacturer model, the platform model, and the cooperative model, where both the manufacturer and the platform jointly provide the cash rebate. We show that the platform model reduces the trade-in service level, but the manufacturer model increases the trade-in service level. In addition, since the cash rebate increases operation costs, the sale price of products is inevitably improved. Furthermore, the platform model raises product demand, but the manufacturer model lowers product demand. The cooperative model proves effective in enhancing demand only when the manufacturer contributes a minor share of the cash rebate and the trade-in service is less efficient. Cash rebates can increase the E-SC’s profits, but the degree of this increase becomes smaller as the cash rebates increase. The manufacturer and the platform always want to exploit each other’s cash rebate strategies. Consumer surplus and social welfare are highest in the platform model and lowest in the manufacturer model. Taking into account the profits, consumer surplus, and social welfare, the platform model is the most conducive to E-SC system operations.
... Cheng and Wang (2023) proposed a carbon-constrained closed-loop SC model to discuss the joint impact of the policies and operation measures on the pricing and tradein rebate decisions. Hu and Tang (2024) discussed the trade-in decision under the condition of both product sharing and heterogeneous customers. Taking the carbon tax and the trade-in program into consideration, Li et al., (2024) discussed the optimal pricing and the trade-in rebate decision by developing a manufacturing-remanufacturing models. ...
... Xia et al. (2021) focused on the series-parallel structure of manufacturing systems and individualised the sequential PM intervals for each machine based on its evolving operating condition. Hu and Tang (2024) investigated how manufacturers offering trade-in programmes can respond to product-sharing markets, and find that manufacturer's profit increases with the PM cost when consumers are myopic, but it may be decreasing in the PM cost when consumers are strategic. In addition, there are a few scholars have suggested that manufacturers can maximise their profit by adopting a mixed maintenance strategy, combining scheduled PM and extended maintenance periods to meet customer needs (Ben Mabrouk and Chelbi 2023). ...
In the sharing business model, manufacturers typically increase customer usage through product
design but contend with escalating failure costs stemming from heightened customer usage and
moral hazard concerns. The preventive maintenance (PM) typically serves as a means for manufacturers to tackle the growing failure cost problem. However, manufacturers face the challenge of how
to make PM strategies in intricate operational environments. We formulate a theoretical model to
investigate when a manufacturer should implement PM, taking into account customer usage and
product design. Our results suggest that when the fixed cost of PM is low and the customer moral
hazard is not sufficiently high, or when both the fixed cost of PM and the customer moral hazard
are at moderate levels, it is wise for the manufacturer to implement PM. We also find that the PM
can lead to higher consumer surplus by increasing customer utility, achieving a win-win situation. In
addition, our findings reveal a positive correlation between the PM effort and product quality, with
higher PM effort leading to higher product quality and thus increasing customer usage. In extension
models, we further explore the issues of maximising social welfare, non-zero maintenance time and
endogenous maintenance frequency.
Businesses and governments have increasingly attached importance to trade-in programs due to their environmental and financial benefits. There are always two programs: trade-old-for-new (TON) and trade-old-for-cash (TOC). Compared with TON, TOC provides old consumers with more flexibility. However, TON may increase the new product sales for firms. In this study, we consider that the manufacturer implements a TON program and the third-party collector provides a TOC program. We study the optimal pricing and subsidy decisions and investigate the effects of the TON subsidy on the firms, consumers, and society. Our main results are: (1) It is optimal to set the new product price at a constant level, independent of the trade-in programs. (2) Consumers focus on the product durability level when they make purchase decisions and firms can improve demand for trade-ins by designing suitable product durability. (3) The TON subsidy benefits the manufacturer, consumers, and society, but hurts the third-party collector when the product durability level is low. Moreover, the effects of subsidy constraints depend on the upper limit of policy constraints and the product durability level. (4) The government subsidy is not as high as possible. A suitable subsidy level should be set according to the subsidy constraints. Our analysis provides insights for firms and government on how to use trade-in programs to maximize profits and social welfare.
We develop a two-period model to investigate the trade-in service in a closed-loop supply chain consisting of a manufacturer and a retailer. In the supply chain, we consider two options for the trade-in service. The first one is Scenario M, in which the manufacturer collects the used products from trade-in customers by herself; and the second one is Scenario R, in which the manufacturer outsources the trade-in service to the retailer and obtains the used products from the retailer at a buy-back price. Accordingly, the firm in charge of the service needs to determine a rebate rate. We show that both firms prefer to operate the trade-in service by themselves in most cases, and we derive the condition for each firm to prefer a scenario and also the condition under which the supply chain is better off from a scenario. Compared to Scenario M, trade-in customers can enjoy lower prices in two periods in Scenario R, although the second-period sales price for new customers is higher. We also perform a numerical study to investigate the impacts of major parameters on the optimal prices, rebate rate, profits, and the conditions for each firm's and the supply chain's scenario preferences. The difference between trade-in prices in the two scenarios is larger when trade-in customers are more sensitive to the price, whereas the difference becomes smaller when the manufacturer obtains a higher net gain from handling returned products.
Female user (driver and rider) safety is a serious concern for ride‐hailing platforms. One way to address this concern is to migrate from the traditional “pooling” system that matches riders with drivers without considering gender to a “hybrid” system with a “female‐only” option. Will such a hybrid system result in a win‐win‐win outcome for all involved parties (riders, drivers and the platform)? To answer this question, we investigate the performance of the two operational systems: a pooling system, and a hybrid system. For each system, we analyze a two‐stage queueing game to determine the equilibrium “joining” and “participating” behavior of riders and drivers, and then derive the platform’s optimal pricing and wage decisions. We posit a mismatch cost incurred by a safety‐concerned female user when she is matched with a male counterpart in a ride. By comparing the equilibrium outcomes associated with the pooling and the hybrid systems, we draw the following conclusions: when safety‐concerned female users’ mismatch cost is above a certain level, switching from a pooling system to a hybrid system can result in a win‐win outcome for safety‐concerned female users and the platform. However, male and safety‐unconcerned female users might be worse off due to this change in the system configuration. Our results also help us to rectify some of our intuitions about these two systems. One, in the pooling system, reducing the mismatch cost associated with safety‐concerned female drivers may not lead to more female riders joining the pooling system, even though it boosts the platform’s profit in general. Two, in the hybrid system, it is not necessary for female riders to pay a higher price when they opt for female drivers instead of male drivers. We also relate our results to certain system configurations adopted by various ride‐hailing platforms to address female safety concerns in different countries.
The last decade has seen the emergence of the sharing economy as well as the rise of a diverse array of research on this topic both inside and outside the marketing discipline. However, the sharing economy’s implications for marketing thought and practice remain unclear. This article defines the sharing economy as a technologically enabled scoioeconomic system with five key characteristics (i.e., temporary access, transfer of economic value, platform mediation, expanded consumer role, and crowdsourced supply). It also examines the sharing economy’s impact on marketing’s traditional beliefs and practices in terms of how it challenges three key foundations of marketing: institutions (e.g., consumers, firms and channels, regulators), processes (e.g., innovation, branding, customer experience, value appropriation), and value creation (e.g., value for consumers, value for firms, value for society) and offers future research directions designed to push the boundaries of marketing thought. The article concludes with a set of forward-looking guideposts that highlight the implications of the sharing economy’s paradoxes, maturation, and technological development for marketing research. Collectively, this article aims to help marketing scholars not only keep pace with the sharing economy but also shape its future direction.
The automotive industry has a decisive role in the economy of developed countries. Sheet metal forming – as one of the main processes in car manufacturing – has similarly important role. Concerning the recent trends in car production, the application of lightweight constructions principles is the main priority to meet customers' demands and the increased legal requirements. To meet these expectations, the application of high strength materials is regarded as one of the most promising possibilities. Applying high strength materials – beside high strength steels like DP1000, TRIP780 recently aluminium alloys, e.g. AA7021 or AA7075 – have a positive response for many of the requirements: increasing strength results in the application of thinner sheets together with significant mass reduction, leading to lower consumption with increased environment protection; however it can often lead to the decrease of formability, too. In this paper, an introduction on recent material developments in the automotive industry concerning both the use of new generation high strength steels and light metals with particular emphasis on aluminium alloys will be given. A comparison between steel and aluminium application in the automotive industry is given from various points of view. Since our main topic is the sheet metal forming, in this paper the body-in-white manufacturing in the automotive industry is the primary focus field. Keywords: High strength steels, Aluminium, Automotive industry, Low cost manufacturing
It is well known that strategic consumers can harm firms’ profits by delaying their purchases, to buy at discounted price. A retailer can induce consumers to purchase at the right price and time by acting on the two components of the consumer’s surplus in each period, that is, the willingness to pay (WTP) and the selling price. We develop a multi-period model to investigate pricing and advertising decisions in a supply chain, in the presence of two types of consumers, namely, myopic and strategic. We assume that the retailer’s advertising positively affects the consumer’s WTP at a decreasing rate over time. The manufacturer sets the wholesale price and its share in the retailer’s advertising cost, while the retailer determines the retail prices during the different periods of the selling season, along with the advertising budget. Our approach makes it possible to determine endogenously the number of price drops during the selling season and the depth
of each discount. Assuming decentralized decision-making in the supply chain, we determine the conditions under which the retailer prefers a single-pricing policy to a markdown-pricing policy. We show that the manufacturer has a say in the retailer’s choice through its participation rate in the retailer’s advertising cost. Interestingly, we obtain that an integrated supply chain would, roughly speaking, adopt the same pricing policy as in the decentralized case. To start with, we assume that the WTP is distributed uniformly, and later on, we assess the impact of changing the distribution on the results.
Bundling in this era of eCommerce and high technology is a potent and widespread selling tool. The literature has focused on three static bundling strategies under which the products are sold separately (pure components or PC) or only in a bundled form (pure bundling or PB) or both (mixed bundling or MB). In a generalization, and motivated by real world examples, this paper examines the relative effectiveness of temporal bundling. We consider a firm that sells to a market of myopic and strategic consumers, and a selling season consisting of two stages. We compare four strategies – PC-PC (i.e., pure components in each of two stages), PB-PB, PB-PC and PC-PB – relative to MB. Our results show that PB-PB maximizes profits under low marginal costs; PC-PC prevails under high marginal costs given a large proportion of myopic consumers; and PB-PC is profit maximizing under moderate marginal costs when most consumers are strategic. These temporal strategies dominate MB except when the market is comprised entirely of strategic consumers. Finally, while temporal mixed bundling – MB-MB – is weakly superior to other temporal strategies, the latter are much easier to implement, as shown by real-world uses, and suffice to capture most of the profits. Related interesting pricing implications are discussed. Three extensions to the main model are also proposed.
The emergence of a collaborative economy has been driven by advances in information technology that allow consumers to borrow and rent goods among peers on a secondary sharing market. In a dynamic setting, consumers make intertemporal decisions about purchases and their participation in the sharing market. This study introduces an overlapping-generations model to analyze product pricing and consumer choice with and without a sharing market. The model quantifies the impacts of a peer-to-peer economy on the demand for ownership, the product price, and all participants’ payoffs, including consumer surplus, profits, and social welfare. Given consumers that are heterogeneous with respect to their consumption needs and valuations, it illustrates which of them are prone to participate in a sharing economy and whether a retailer (or manufacturer) can benefit from the presence of a secondary exchange. A sharing market tends to increase the price of new products by a “sharing premium,” which positively depends on the retailer’s commitment ability. The price increment becomes relatively smaller for higher-cost products. Low-cost products and sufficiently impatient consumers together make a peer-to-peer economy unattractive for retailers. For high-cost products, however, the latter stand to gain from the existence of a sharing market. Most important, the introduction of a peer-to-peer economy increases both consumer surplus and social welfare, thus creating an implicit imperative for a social planner to help promote collaborative consumption, for instance, by providing incentives for retailers and manufacturers that tend to offset possible expected negative payoff effects from consumer sharing.
In this paper, we consider a dynamic supply chain where a manufacturer produces and distributes a featured product through an exclusive retailer to end consumers. The manufacturer decides the product quality and wholesale price, while the retailer sets the retail price in the presence of a revenue-sharing contract and consumers’ reference quality effects. The objective of this study is to investigate the impacts of myopic behaviour regarding the reference quality on the product quality and pricing strategies and profits of both members. Our results suggest that the manufacturer’s myopia leads to a higher quality, higher price strategy and a higher quality–price ratio which benefits consumers. Meanwhile, relative to the far-sighted behaviour, myopia results in a more quality-sensitive but less price-sensitive market demand. What’s more, we find that the manufacturer is apt to act in a far-sighted way, but the retailer isn’t always willing to cooperate with a far-sighted manufacturer. Taking myopic strategies for both members is likely to gain a high profit of the whole supply chain for a relatively high marginal contribution of product quality on demand and a relatively low revenue-sharing proportion.
Following Becker (1957) we ask whether competition will eliminate the effects of behavioral biases. We study the case of shrouded product attributes, such as main- tenance costs, expensive add-ons, and hidden fees. In standard competitive models with costless advertising all firms choose to reveal all product information. We show that information revelation breaks down when some naive consumers do not anticipate shrouded attributes. Firms will not compete by publicly undercutting their competi- tors' add-on prices if (i) add-ons have close substitutes that are only exploited by sophisticated consumers, or (ii) many consumers drop out of the market altogether when the add-on market is made salient. We show that informational shrouding flour- ishes even in highly competitive markets, even in markets with costless advertising and
Resale platforms such as Swappa and ThredUP, which provide a channel for product‐holders to sell used products, have become common. Interestingly, in the presence of resale platforms, some firms, such as Apple, set lower rebates for the trade‐in‐for‐upgrade (TU) mode instead of implementing the trade‐in‐for‐upgrade‐and‐cash (TUC) mode as Huawei does. In this paper, we build game‐theoretical models to explore how a firm should adjust its trade‐in strategy (e.g., choose pricing and mode selection between TU and TUC) in reaction to the emergence of third‐party resale platforms. We derive several insights. First, we find that using the TU mode helps to encourage consumer repurchases, whereas the TUC mode may have a greater promotion effect on consumers’ first purchases. Second, we show that in the TUC mode, the amount of the trade‐in rebate is not affected by the presence of the resale platform. Differently, in the TU mode, whether the firm should provide a more generous trade‐in rebate depends on the unit product cost when the resale platform is present. Third, in response to the resale platform, the firm should choose the TU mode to take advantage of the platform's promotion effect if the unit product cost is high and choose the TUC mode to avoid the platform's cannibalization effect if the unit product cost is low. To verify the robustness of our findings, we consider the effects of reduced consumer uncertainty and the dynamic pricing mechanism in the extended models. Our main findings concerning trade‐in rebate and mode selection remain valid.
Problem definition: We study the economic rationale for certified pre-owned (CPO) programs and characterize the mechanism through which they influence secondary markets to create value for durable goods firms and consumers. Academic/practical relevance: Our study on understanding the market impact of CPO programs is highly relevant for industry given their prevalence in practice. Our work also contributes to the adverse selection literature in the context of the “lemons problem” by uncovering the mechanism underpinning CPO programs and how they improve market efficiency. Methodology: We use a game-theoretic durable goods model that captures CPO program features to identify how CPO programs improve market efficiency. We further investigate how CPO program size, as determined by program qualification criteria, plays a role in improving market efficiency. Results: We show that the mechanism underpinning CPO programs consists of two mutually reinforcing effects: a more effective segmentation of used product buyers through high- and low-quality product differentiation and a higher trade-in discount to used product owners. The former effect generates a higher revenue, which, in turn, allows for a higher trade-in discount. This translates to more high-quality products being traded in, more new products being purchased, and more used products being sold in the secondary market (i.e., increased market efficiency). We also show that these two effects are strengthened as the CPO program size increases. Finally, we test hypotheses deriving from our theoretical results in the context of the U.S. automotive industry. Our empirical findings are consistent with the conclusions of our theoretical work. Managerial implications: Durable goods firms can proactively manage their CPO programs by appropriately setting trade-in discounts and managing price discrimination between CPO and non-CPO products. CPO program qualification criteria can be used to alter CPO program size and, hence, the level of market efficiency improvement induced by these choices.
Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.1176 .
Today, the world has entered the era of the circular economy, and environmental regulations have become more stringent. This article considers a monopolistic recycling platform (RP), which offers three recycling strategies (trade-in for cash, trade-in for refurbishment, and trade-in for new) to generate more profits based on the heterogeneity of consumers in terms of perceived quality. There are three modes of RPs with diversified recycling strategies: (1) only trade-in for cash (e.g., Lehuiso); (2) trade-in for cash and for refurbishment (e.g., Gazelle); and (3) trade-in for cash, for refurbishment, and for new coexisting (e.g., Suhuishou). We develop a game model and derive optimal decisions of the RP under the three trade-in modes respectively. Comparing the different trade-in modes, we find that for the RP, the decision of which mode to offer among trade-in for cash, for refurbishment, and for new service, depends on the quality depreciation coefficients of used and refurbished products and the value of new products. We also conduct extensive numerical analysis and show the optimal service strategies for the three trade-in modes.
A continuous supply of used products ensures large-scale remanufacturing. Manufacturers can delegate used product collection to third-party collectors (3PCs) that provide a trade-old-for-cash (TOC) program, in addition to collecting used products through a trade-old-for-new (TON) program. However, few studies have investigated the interactions between collection delegation and channel structure in a supply chain. To fill this gap, we develop game-theoretic models in a supply chain under traditional retail channel and dual-channel structures to explore whether and when the manufacturer adopts the collection delegation policy and examine the optimal channel choice for trade-ins. Our finding shows that the manufacturer always benefits from collection delegation, but the retailer would be worse off from such delegation in certain cases. To be specific, under the retail channel structure, collection delegation has no impact on the retailer when the salvage value of used products is relatively low, whereas it hurts the retailer when the salvage value is relatively high. However, under the dual-channel structure, collection delegation never affects the retailer. Moreover, we find that the manufacturer's channel choice depends on the consumer acceptance of the direct channel and the salvage value of used products. We further consider the case that the manufacturer does not introduce the TON programs to explore the effects of TON and the case that the new and remanufactured products are sold at different retail prices to examine the equilibrium strategies. Our results can provide useful managerial insights for decisions-makers who face the choice of collection delegation under different channel structures.
As more customers purchase pre-owned apparel, firms are increasingly adopting resale based business models. These models typically operate as either (i) a trade-in and resale program, wherein a firm offers a trade-in discount on a new product and resells the traded-in products, or (ii) a P2P resale marketplace where customers can buy and sell used products to each other. Since different firms choose different resale strategies, it is not clear which strategy is more profitable. Furthermore, although firms that adopt each resale model also promote their environmental benefits, there are concerns that these firms are greenwashing, i.e., mis-representing the environmental benefits of their business models. Hence, we investigate the profitability and environmental impacts of these resale marketplace models and find that the trade-in model may be more profitable despite the lower reverse logistics cost in the P2P model, and the P2P resale marketplace may be more profitable despite the trade-in program having direct control over the supply and demand of used products. Furthermore, both models can be better for the environment depending on the product characteristics and perceived quality difference between the used products sold in these programs. We further identify when each model is better for profitability and environment concurrently and when there is misalignment. Other results and managerial insights include comparative pricing of new and used products, market coverage, total sales, and resales, and the impact of product durability on pricing. The insights presented in this paper provide useful guidelines for firms, non-governmental organizations, and environmental advocacy groups.
A ride-sharing platform (RSP), such as Uber or Lyft, can sometimes offer passengers an option to share (pool) the ride with fellow passengers. On the one hand, a passenger who pools benefits from paying a lower fare and the RSP benefits from increasing occupancy per car, thereby serving more passengers. On the other hand, a passenger who pools takes more time, on average, to reach her destination and may have to share the ride with a stranger, and the RSP gets a lower profit margin per passenger than from solo rides. We develop a queueing model to find the RSP’s optimal revenue at equilibrium when passengers are strategic and drivers are independent agents, and design the RSP’s revenue-maximizing price-service menu. We find that offering both solo and pooled rides is optimal when the distribution of passenger-type is not skewed and congestion is not high. Counter intuitively, when congestion is high, the RSP benefits from offering only one ride choice. Simulation-based results extend these findings when more than one route exists. We provide a numerical example based on real-life data. When the number of drivers is endogenous, equilibrium revenue per driver can decrease when the passenger arrival rate increases.
Problem definition: We consider an intermediary’s problem of dynamically matching demand and supply of heterogeneous types in a periodic-review fashion. Specifically, there are two disjoint sets of demand and supply types, and a reward for each possible matching of a demand type and a supply type. In each period, demand and supply of various types arrive in random quantities. The platform decides on the optimal matching policy to maximize the expected total discounted rewards, given that unmatched demand and supply may incur waiting or holding costs, and will be fully or partially carried over to the next period. Academic/practical relevance: The problem is crucial to many intermediaries who manage matchings centrally in a sharing economy. Methodology: We formulate the problem as a dynamic program. We explore the structural properties of the optimal policy and propose heuristic policies. Results: We provide sufficient conditions on matching rewards such that the optimal matching policy follows a priority hierarchy among possible matching pairs. We show that those conditions are satisfied by vertically and unidirectionally horizontally differentiated types, for which quality and distance determine priority, respectively. Managerial implications: The priority property simplifies the matching decision within a period, and the trade-off reduces to a choice between matching in the current period and that in the future. Then the optimal matching policy has a match-down-to structure when considering a specific pair of demand and supply types in the priority hierarchy.
Problem definition: Mobile communications technologies and online platforms have enabled large-scale consumer-to-consumer (C2C) sharing of their underutilized products. This paper studies a manufacturer’s optimal entry strategy in the product-sharing market and the economic implications of its entry. Academic/practical relevance: Sharing of products or services among consumers has experienced dramatic growth in recent years. The impact of C2C sharing on traditional firms can be very significant. In response to C2C product sharing, many manufacturers (e.g., General Motors and BMW) have entered the product-sharing market to provide business-to-consumer (B2C) rental services in addition to outright sales to consumers. Methodology: We employ a game-theoretic analytical model for our analysis. Results: Our analysis shows that when C2C sharing has a low transaction cost and the manufacturer’s marginal cost of production is not very high, the manufacturer will find it not optimal to offer its own rental services to consumers. In contrast, when the C2C sharing transaction cost is high or the manufacturer’s marginal cost of production is high, the manufacturer should offer enough units of the products for rental to squeeze out C2C sharing (in expectation). When the C2C-sharing transaction cost and the manufacturer’s marginal cost are both in the middle ranges, the manufacturer’s rental services and the C2C sharing will coexist, in which case the manufacturer’s entry in the sharing market may reduce the total number of units of the product in the whole market, but increase the consumer surplus and the social welfare. This reduced number of products due to the manufacturer’s B2C rental service also suggests less environmental impact from production. Managerial implications: The production cost and the C2C sharing transaction cost play critical roles in determining the manufacturer’s optimal quantity to use for its B2C rental services and the equilibrium outcome. In some situations, the manufacturer’s entry in the sharing market provides not only economic benefits to the firm and consumers, but also environmental benefits to the society as a whole.
Operations management has the tradition of coming from and going back to real‐life applications. It deals with the management of the process of matching supply with demand. The emerging business process in a sharing economy or an innovative marketplace calls for active management at the operational level. We take a neoclassical perspective by drawing inspiration from the classic models in operations management and economics. We aim at building connections and identifying differences between those traditional models and the new applications in sharing economy and innovative marketplaces. We also point out potential future research directions.
The booming on-demand ride-sharing economy induces drivers who do or do not own cars to provide services on ride-sharing platforms. To meet growing demand, in practice the platforms have cooperated with car-rental companies that rent cars to without-car drivers to improve their supplies. However, this might harm the platforms, consumers, and drivers, since such a second capacity source may increase customers’ waiting time and reduce drivers’ utilization. In this paper, we study the impact of without-car drivers in a car-rental company on a ride-sharing platform, consumer surplus, and driver surplus. The platform must decide whether to cooperate with the car-rental company, which entails a per-service price charged to customers and a per-service wage paid to (with-car and without-car) driver. In turn, the car-rental company charges without-car drivers who would like to provide services on the platform a price, and pays a commission rate to the platform. We analyze a stylized model in which customers decide whether to use the platform based on price and expected waiting time, and drivers base decisions about whether to work for the platform on wage and the probability of getting jobs. Driven by these two features, we find that the platform would prefer to cooperate with the car-rental company, and the optimal price and wage (profit) of the platform are not necessarily monotonic (increases) in the potential number of without-car drivers or the commission paid by the company. We also find that when the commission rate is high or the fixed payout ratio is low, cooperation can yield a win-win-win outcome for the platform, customers, and drivers. This provides a plausible explanation of why most ride-sharing platforms would cooperate with car-rental companies in practice. In addition, we find that such a win-win-win outcome can easily be achieved for a large customer size or delay cost but a small (with-car and without-car) driver size or service rate.
As observed in real world practices, trade-ins can be offered by either the manufacturer or the retailer. The party offering the trade-in program faces the trade-off between the fixed trade-in cost incurred and the additional revenue generated. By conducting a game-theoretic study, we analytically explore in this paper the optimal choice of trade-in provider in a dyadic supply chain with a single manufacturer and a single retailer. We show that the trade-in models can bear a much higher manufacturing cost and induce a higher new product sale than the benchmark case without trade-ins. It is possible that both the manufacturer and retailer prefer to undertake the trade-in program, which would lead to a conflict; or both firms prefer to be a free-rider instead of being the trade-in provider, which would fall into a prisoner's dilemma. Moreover, the powerful manufacturer has an incentive to delegate the trade-in service to the retailer when facing a higher fixed trade-in cost, but the delegation option is always worse off for the retailer compared to the scenario in which the retailer provides trade-ins by herself. We also show that the trade-in scenarios always benefit the environment and consumers of the replacement segment, but hurt the primary segment consumers. The social welfare would actually be higher in the scenarios with trade-ins if the fixed trade-in cost is relatively low and the residual value of old products is relatively high.
Trade‐in programs have been widely adopted to enhance repeat purchase from replacement customers. Considering that a market consists of replacement and new segments, we study the joint and dynamic decisions on the selling price of new product (hereafter, “selling price”) and the trade‐in price involved in the program. By adopting a vertical product differentiation choice model, we investigate two scenarios in this paper. In the base model, the manufacturer has sufficiently large production capacity to fulfill the customer demand. We characterize the structural properties of the joint pricing decisions and compare them with the optimal pricing policy under regular selling. We further propose a semi‐dynamic trade‐in program, under which the new product is sold at a fixed price and the trade‐in price can be adjusted dynamically. Numerical experiments are conducted to evaluate the performance of the dynamic and semi‐dynamic trade‐in programs. In an extended model, we consider the scenario in which the manufacturer stocks a batch of new products in the beginning of the selling horizon and the inventory cannot be replenished. Following a revenue management framework, we characterize the structural properties with respect to time period and inventory level of new products.
To derive conditions for manufacturer and retailer to implement trade-in policies voluntarily and identify the optimal channel format for trade-in, we construct traditional retail channel model and dual-channel model under two scenarios: without trade-in and with trade-in. We find that the retailer would implement trade-in policy voluntarily in traditional retail channel only if old customers’ market share exceeds a certain threshold. Interestingly, the result is opposite in dual-channel case. The traditional retail channel and the dual-channel could be the optimal choice for implementing trade-in respectively, depending on different value ranges of customers’ acceptance of direct online channel.
New trade-in services such as online trade-in, trade-in on e-commerce platforms and omni-channel trade-in, are emerging due to the development of e-commerce. To offer these new trade-in services, firms need to determine the optimal product price and rebate and decide whether to pay the rebate with a gift card (G) or cash (C). To address these challenges for firms, our paper considers a firm selling a new product to new consumers and offering a trade-in service to replacement consumers. In addition, we develop theoretical models to examine the optimal decisions in the cases of G and C and explore the optimal payment for the rebate. We reveal that G payment is a better choice for the firm only if the used product residual value is relatively low and the market size ratio between replacement and new consumers is relatively low; otherwise, the firm should choose C payment. Interestingly, replacement consumers’ preferred trade-in rebate payment (i.e., C payment) leads a lower trade-in demand than G payment and C payment may be harmful. In the extension, we consider a firm with online and offline sales channels and different types of replacement consumers who own different used products, and find that our main results regarding the optimal rebate payment still hold. Moreover, we find that in the context of a used product with a relatively medium residual value, firms with online and offline sales channels are more likely to choose G than firms with one sales channel; otherwise, firms are more likely to choose C.
Trade‐in programs for electronics products, e.g., mobile phones, have been increasingly popular. These programs target at customers (we call them “bargainers”) who seek to salvage or upgrade their old devices. There are two widely adopted trade‐in options: trade‐in‐for‐upgrade and trade‐in‐for‐cash. In this paper, we consider a firm who offers both trade‐in options, i.e., a hybrid trade‐in program, to acquire old products, then refurbishes and resells them, together with new product over a finite selling horizon. The bargainers choose which option to trade in their products while new customers decide whether to buy a new product or a refurbished one. When the selling price of new product is exogenous, we derive the optimal trade‐in prices of old product and resale price of refurbished product. We show that the optimal trade‐in and resale policies are of a threshold‐type and trade‐in‐for‐upgrade should be offered with a premium refund (compared to trade‐in‐for‐cash) only in early periods of the selling horizon. We further consider two variants of the above base model. In the first extension, the new product has a fixed amount of initial inventory and is not replenishable during the selling horizon. In the second extension, the new product price can also be determined by the firm. Our numerical results demonstrate that the hybrid trade‐in program could generate significantly more profit than either upgrade‐only or cash‐only trade‐in program.
The sharing economy, a term we use to refer to business models built around on-demand access to products and services mediated by online platforms that match many small suppliers or service providers to many small buyers, has emerged as an important area of study in operations management. We first describe three “canonical” applications that have garnered much attention from the operations management community. We use these applications to highlight distinguishing features of sharing economy business models and to point out research questions that are new. Then we draw connections between classical operations management theory and models and those that have been used to study sharing economy applications. We do so to put in context some of the recent work on the sharing economy and to showcase the underlying modeling toolkit and identify opportunities for future research.
As environmental regulations are becoming increasingly strict, firms are setting up remanufacturing systems and using trade-in programmes that take back used products to stimulate demand. Meanwhile, they are starting to sell remanufactured products to secondary markets to avoid the problem of cannibalization. In this study, we establish a two-period model in which a monopolistic original equipment manufacturer (OEM) offers a trade-in programme to improve sales and collect used products. At the same time, the OEM can elect to remanufacture these used products and resell them to a secondary market. The results for the static pricing case show that the two primary driving factors, customers’ maximum willingness to pay into the secondary market and production cost, produce different outcomes. Depending on the relationship between these two key factors, seven outcomes exist. Specifically, although all used products are collected and the secondary market is available, the OEM may not remanufacture or may partially remanufacture. We study the above problem using a dynamic pricing case in which the product price during the second period is different from that in the first period. We find that the OEM prefers to offer a menu such that all rather than just some holders participate in the trade-in programme. Furthermore, in the dynamic pricing case, all rather than some of these used products are remanufactured, in contrast with the static pricing case. However, the layout of the OEM's trade-in and remanufacturing policies under the static pricing case is similar to that under the dynamic pricing case. We further extend our study to include a competitive situation and find that the results for the core model can essentially be reproduced under competition.
Retailers and manufacturers are increasingly selling extended warranties to obtain high profitability. In addition to the traditional extended warranty (EWR), that offers a free repair and replacement service, a new extended warranty (EWT) comes to the market, under which an additional trade-in service is provided during the warranty coverage. The service provider faces three important decisions: (1) Whether to offer EWR or EWT? (2) How to set the optimal selling prices of EWR and EWT? (3) When choosing to sell EWT, how to determine the optimal trade-in price? To address such challenging issues, we first develop two theoretical models regarding EWR and EWT for a retailer, and further consider the cases where a manufacturer sells the extended warranties and the upgraded product has different failure probabilities. The results show that EWT should never be offered at a higher price than EWR, and when the handling cost for used products is relatively low, EWT will outperform EWR. While the optimal EWR and EWT selling prices increase with the product failure probability, the optimal trade-in price decreases with it. Interestingly, the optimal trade-in discount is not always increasing or decreasing with the failure probability. Moreover, an earlier trade-in time is usually better for the service provider. Compared with the retailer, the manufacturer will always set a lower warranty selling price, but neither of them will always offer a lower trade-in price or discount. We also find that the upgraded product's failure probability will affect the retailer's optimal warranty strategy and profit.
Firms usually offer trade-in programs to entice consumers to purchase next generation products. By considering the purchase behavior of both myopic consumers and strategic consumers, we propose a game-theoretic analytical model to determine the optimal price of the next generation products and the optimal trade-in rebate. We find that firm’s optimal price of the next generation products increases with the incremental value. The optimal trade-in rebate decreases with the trade-in duration. The firm’s optimal profit increases with the trade-in duration, but decreases with the incremental value.
An on-demand service platform connects waiting-time-sensitive customers with independent service providers (agents). This paper examines how two defining features of an on-demand service platform—delay sensitivity and agent independence—impact the platform’s optimal per-service price and wage. Delay sensitivity reduces expected utility for customers and agents, which suggests that the platform should respond by decreasing the price (to encourage participation of customers) and increasing the wage (to encourage participation of agents). These intuitive price and wage prescriptions are valid in a benchmark setting without uncertainty in the customers’ valuation or the agents’ opportunity costs. However, uncertainty in either dimension can reverse the prescriptions: Delay sensitivity increases the optimal price when customer valuation uncertainty is moderate. Delay sensitivity decreases the optimal wage when agent opportunity cost uncertainty is high and expected opportunity cost is moderate. Under agent opportunity cost uncertainty, agent independence decreases the price. Under customer valuation uncertainty, agent independence increases the price if and only if valuation uncertainty is sufficiently high.
The online appendix is available at https://doi.org/10.1287/msom.2017.0678 .
We consider an on-demand service platform using earning-sensitive independent providers with heterogeneous reservation price (for work participation) to serve its time and price-sensitive customers with heterogeneous valuation of the service. As such, the supply and demand are “endogenously” dependent on the price the platform charges its customers and the wage the platform pays its independent providers. We
present an analytical model with endogenous supply (number of participating agents) and endogenous demand (customer request rate) to study this on-demand service platform. To coordinate endogenous demand with endogenous supply, we include the steady-state waiting time performance based on a queueing model in the customer utility function to
characterize the optimal price and wage rates that maximize the profit of the platform. We first analyze a base model that uses a fixed payout ratio (i.e., the ratio of wage over price), and then extend our model to allow the platform to adopt a time-based payout ratio. We find that it is optimal for the platform to charge a higher price when demand increases; however, the optimal price is not necessarily monotonic when the provider capacity or
the waiting cost increases. Furthermore, the platform should offer a higher payout ratio as demand increases, capacity decreases or customers become more sensitive to waiting time. We also find that the platform should lower its payout ratio as it grows with the number of providers and customer demand increasing at about the same rate. We use a set of actual data from a large on-demand ride-hailing platform to calibrate our model parameters in numerical experiments to illustrate some of our main insights.
We describe an equilibrium model of peer-to-peer product sharing, or collaborative consumption, where individuals with varying usage levels make decisions about whether or not to own a homogeneous product. Owners are able to generate income from renting their products to nonowners while nonowners are able to access these products through renting on an as-needed basis. We characterize equilibrium outcomes, including ownership and usage levels, consumer surplus, and social welfare. We compare each outcome in systems with and without collaborative consumption and examine the impact of various problem parameters. Our findings indicate that collaborative consumption can result in either lower or higher ownership and usage levels, with higher ownership and usage levels more likely when the cost of ownership is high. Our findings also indicate that consumers always benefit from collaborative consumption, with individuals who, in the absence of collaborative consumption, are indifferent between owning and not owning benefitting the most. We study both profit-maximizing and social-welfare–maximizing platforms and compare equilibrium outcomes under both in terms of ownership, usage, and social welfare. We find that the difference in social welfare between the profit-maximizing and social-welfare–maximizing platforms is relatively modest.
The online appendix is available at https://doi.org/10.1287/mnsc.2017.2970 .
This paper was accepted by Gad Allon, operations management.
Trade-in remanufacturing is a commonly adopted business practice under which firms collect used products for remanufacturing by allowing repeat customers to trade in used products for upgraded ones at a discount price. This paper studies how customer purchasing behavior and remanufacturing e ciency a ect the economic and environmental values of such a business practice. We demonstrate a new benefit of trade-in remanufacturing: it helps exploit the forward-looking behavior of strategic customers, which could be much more significant than the widely recognized revenue-generating and environmental benefits of remanufacturing. High remanufacturing e ciency does not necessarily benefit a firm. With overly high remanufacturing e ciency, product durability is so high that repeat customers are reluctant to trade in and upgrade their used products. When customers are highly strategic, trade-in remanufacturing creates a tension between profitability and sustainability: on one hand, by exploiting the intensive forward-looking customer behavior, trade-in remanufacturing is quite valuable to the firm; on the other hand, with highly strategic customers, trade-in remanufacturing has a substantial negative impact on the environment and social welfare, since it may induce significantly higher production quantities without improving customer surplus. With nearly myopic customers, however, trade-in remanufacturing benefits both the firm and the environment. Therefore, understanding the interactions between customer purchasing behavior and trade-in remanufacturing is important to both firms and policy makers. Finally, to resolve the above tension, we study how a social planner (e.g., government) should design a public policy to maximize social welfare. The social optimum can be achieved by using a simple linear subsidy/tax scheme for both new production and remanufacturing. The proposed policy can also induce the firm to set the socially optimal remanufacturing efficiency.
Many innovating firms use trade-in programs to encourage consumers’ repeat purchasing. They can choose between dynamic pricing and preannounced pricing strategies to mitigate the impacts of consumers’ strategic behavior. This paper develops a dynamic game framework to explore the optimal pricing strategy when the firm sequentially introduces new generations of products to a market populated by strategic consumers with trade-in option offered. Results show that under either pricing strategy, the firm has an incentive to sell the old generation products to new consumers in the second period if the salvage value of the old generation product is high enough. When consumers are sufficiently strategic, if both the innovation incremental value of the new generation product and the salvage value of the old generation product are low enough, the firm is better off following the preannounced pricing strategy. Besides, as the firm becomes more farsighted, the comparatively dominant position of preannounced pricing over dynamic pricing disappears gradually.
B2C platforms are increasingly implementing trade-in programs to boost sales. Most of these platforms have adopted dual-format retailing model including both self-run stores and third-party stores. Under trade-in program framework, B2C platforms will determine the optimal trade-in rebate, and whether to offer the rebate to consumers with gift card (GC) or cash coupon (CC). GC can only be used in self-run stores, while CC can be used in both stores. To entice more consumers to trade-in products, platforms may launch trade-in efforts in the market. To address such decision-making challenges, we consider a B2C platform who owns a self-run store and hosts a third-party store, and examine the optimal trade-in strategy for the platform by developing four theoretical models. We first present two models without considering trade-in efforts, i.e., one model regarding GC payment, and one model regarding CC payment, and then extend them by taking trade-in efforts into consideration. Some interesting findings and insights are achieved. In particular, we find that both GC and CC do not always benefit the platform. Interestingly, offering high quality and low selling price for products in both the self-run store and the third-party store are also not always beneficial to the platform. So is the competition between both stores. Launching trade-in efforts may lead to a lower trade-in rebate but a higher profit for the platform. A counterintuitive finding is obtained that a higher gift card redemption rate is not beneficial to the platform, and vice versa.
In recent years, mobile communications technologies and online sharing platforms have made collaborative consumption among consumers a major trend in the economy. Consumers buy many products but end up not fully utilizing them. A product owner's self-use values can differ over time, and in a period of low self-use value, the owner may rent out her product in a product-sharing market. This paper develops an analytical framework to study how consumer-to-consumer product sharing affects the distribution channel, where the manufacturer has to build its production capacity beforehand and the retailer sells the product to forward-looking consumers. Our analysis reveals that there exists a threshold for the capacity cost coefficient, above which product sharing will increase the manufacturer's optimal capacity and below which it will reduce the manufacturer's optimal capacity. We find that the sharing market tends to increase the retailer's share of the gross profit margin in the channel. Furthermore, the existence of the sharing market tends to benefit the firms when capacity is relatively costly to build, but it is more likely to increase the retailer's profit than the manufacturer's profit, i.e., product sharing can sometimes benefit the downstream retailer at the expense of the upstream manufacturer. This article is protected by copyright. All rights reserved.
We study how acquisition policies for used products as a source for a remanufactured consumer product affect system performance. We introduce a consumer choice model of new product purchase and used product return, which is consistent with the classic Bass diffusion model of sales over time. We capture new and remanufactured product sales, the evolution of the install base, and consumer return and repurchase decisions over the life cycles of new and remanufactured product. Our analyses lead to two main findings on the acquisition policies. First, if the buyback price is less than the margin of a new product, then a trade-in policy is likely to yield higher profit than a buyback policy. Second, we show that the profitability is highest when the time lag between the introduction of a new product and initial demand for a remanufactured version of the product is at or near the sweet spot, which is the age of the product at which the costs of acquisition and remanufacturing are at minimum. Further, when the time lag between the introduction of a new product and initial demand for its remanufactured version is near the sweet spot, then simple pricing methods are close to optimal.
Recent technological advances in online and mobile communications have enabled collaborative consumption or product sharing among consumers on a massive scale. Collaborative consumption has emerged as a major trend as the global economic recession and social concerns about consumption sustainability lead consumers and society as a whole to explore more efficient use of resources and products. We develop an analytical framework to examine the strategic and economic impact of product sharing among consumers. A consumer who purchased a firm’s product can derive different usage values across different usage periods. In a period with low self-use value, the consumer may generate some income by renting out her purchased product through a third-party sharing platform as long as the rental fee net of transaction costs exceeds her own self-use value. Our analysis shows that transaction costs in the sharing market have a nonmonotonic effect on the firm’s profits, consumer surplus, and social welfare. We find that when the firm strategically chooses its retail price, consumers’ sharing of products with high marginal costs is a win-win situation for the firm and the consumers, whereas their sharing of products with low marginal costs can be a lose-lose situation. Furthermore, in the presence of the sharing market, the firm will find it optimal to strategically increase its quality, leading to higher profits but lower consumer surplus.
This paper was accepted by J. Miguel Villas-Boas, marketing.
We investigate retailers’ dynamic pricing decisions in a stylized two-period setting with possible supply constraints and demand from both myopic and strategic consumers. We present an analytical model and then test its predictions in a behavioral experiment in which human subjects played the role of pricing managers. We find that the fraction of strategic consumers in the market systematically moderates the optimal pricing structure. When this fraction exceeds a certain threshold, the retailer offers relatively small late season markdowns to discourage strategic consumers from waiting and to incentivize them to buy during the early season; otherwise, the retailer offers relatively large markdowns to divert all strategic consumers to the late season, where the majority of revenue is made. Our model analyses suggest that the latter policy is optimal under fairly broad conditions. Our experiment shows that after some significant learning, aggregate behavior is able to approximate the key qualitative predictions from our model analysis, with one notable deviation: in the presence of a mixture of myopic and strategic consumers, subjects act somewhat myopically–they underprice and oversell in the main selling season, which significantly limits their ability to generate revenue in the markdown season. This article is protected by copyright. All rights reserved.
We study a firm that makes new products in the first period and collects used products through trade-in, along with new product sale, in the second period. To conduct a convincing analysis, we initially evaluate the problem in a duopoly situation in which one firm (firm A) implements trade-in and the other one (firm B) does not. We subsequently introduce the competitive environment in a two-period planning horizon to identify thresholds that determine the trade-in operations, and then derive the equilibrium decisions of the resulting scenarios. We characterize the optimal production quantities that are associated with parameter b (the sum of used product salvage value and government subsidy) in the Nash equilibrium. Results indicate that adopting trade-in could bring competitive advantage for firm A in terms of market share and profit. If the new product sale is comparatively profitable, then the trade-in firm may forgo some of the collection margin by raising the trade-in rebate and selling additional units to increase new product sale in the second period. Moreover, the total collection quantity does not always increase with government subsidy. We consequently expand the model to the case where both firms compete in trade-in and derive the corresponding decision space of the duopoly firms. Finally, we explore the effect of adopting trade-in on consumer surplus and compare it in the two models. © 2015 Elsevier B.V. and Association of European Operational Research Societies (EURO) within the International Federation of Operational Research Societies (IFORS). All rights reserved.
To entice consumers to purchase both current and next generation products, many manufacturers and retailers offer trade-in programs that allow buyers of the first generation product to trade-in the product and purchase the new generation product at a lower price. By considering the interactions between “forward-looking” consumers and a firm when a trade-in program is offered, we analyze a two-period dynamic game to determine the optimal prices of two successive-generation products in equilibrium, and examine the conditions under which trade-in programs are beneficial to the firm. Our model incorporates market heterogeneity (valuation of the first generation product varies among the consumer population), product uncertainty (the incremental value of the new product is uncertain before its introduction), and consumers' forward-looking behavior (consumers take future product valuation and prices into consideration when making purchasing decisions). With the trade-in option, we show that consumers are willing to pay a price that is higher than their valuations of the current product. Furthermore, trade-in programs are more beneficial to the firm when: (i) the durability of the current product is high; (ii) the market heterogeneity is low; or (iii) the uncertainty level (or the expected incremental value) of the new product is high. Finally, when the incremental value of the new product is more uncertain, consumers are more willing to purchase the current product because of the “option” value of the trade-in programs and thus trade-in programs can be more beneficial to the firm in this case.
Companies can adopt trade-in and/or leasing to shorten consumers' upgrade cycle and gain control over secondary markets. In this paper, we consider a monopolistic manufacturer who offers a technology product to a market consisting of heterogeneous consumers. We focus on an exogenous, stochastic innovation process that determines the availability of new technology and consequently, residual value of the current product. We derive the optimal pricing strategy of trade-in and leasing, respectively, examine its impact on the manufacturer's expected profit, and compare the performance of the two strategies. Trade-in protects the manufacturer against residual value risk and allows the flexibility of offering the option at different innovation states separately. Leasing, on the other hand, provides the manufacturer an opportunity to circumvent low new product prices and thus increases expected profit when product reuse profitability is high. The interplay between the two forces, product reuse profitability and new product price, determines the preference between trade-in and leasing. Our findings provide monopolistic manufacturers guidance on how to optimally employ the trade-in and leasing strategies.
Mixed bundling (MB), in which products are sold separately and as a bundle, is a form of second degree price discrimination. In this study we examine how MB and its variants compare against reserved product pricing (RPP), a form of co-promotion. Used by Amazon.com among others, RPP consists of the firm offering individual products and then enticing single product buyers with a discount on the second product. Our analytical model has a monopolist offering two products to a mix of myopic and strategic consumers. We find that as long as the market consists of a “modest” fraction of myopic consumers, RPP is more profitable than mixed bundling and its special cases. We also present pricing results under RPP. An extension shows that RPP can also be more profitable than a form of price skimming. Limitations and future research directions are discussed.
To entice customers to purchase both current and new generation products over time, many firms offer different trade-in programs including programs that require customers to pay an up-front fee. To examine the effectiveness of the trade-in programs, we develop a two-period model in which a firm sells the first generation product in the first period and the second generation product in the second period; however, the firm offers a trade-in program that customers can participate in when purchasing the first generation product in the first period. To participate, each customer has to pay a nonrefundable fee in the first period so that she has the option to trade-in her first generation product and receive a prespecified trade-in value to be used for the purchase of the second generation product in the second period. To capture market heterogeneity and market uncertainty, we examine the case when the valuation of the first generation product varies among customers and the valuation of the second generation product is uncertain a priori. By analyzing a two-period game, we determine the optimal purchasing behavior of each rational customer, and we show that the firm is always better off by offering its own trade-in programs. Also, our numerical analysis reveals that trade-in programs can benefit the firm significantly especially when (i) the residual value of the first generation product is high; (ii) the expected incremental value of the second generation product is high; or (iii) the valuation of the second generation product is highly uncertain.
A growing segment of the revenue management and pricing literature assumes “strategic” customers who are forward-looking in their pursuit of utility. Recognizing that such behavior may not be directly observable by a seller, we examine the implications of seller uncertainty over strategic customer behavior in a markdown pricing setting. We assume that some proportion of customers purchase impulsively in the first period if the price is below their willingness to pay, while other customers strategically wait for lower prices in the second period. We consider a two-period selling season in which the seller knows the aggregate demand curve but not the proportion of customers behaving strategically. We show that a robust pricing policy that requires no knowledge of the extent of strategic behavior performs remarkably well. We extend our model to a setting with stochastic demand, and show that the robust pricing policy continues to perform well, particularly as capacity is loosened or the problem is scaled up. Our results underscore the need to recognize strategic behavior, but also suggest that in many cases effective performance is possible without precise knowledge of strategic behavior.
This article presents a model of the design and introduction of a product line when the firm is uncertain about consumer valuations for the products. We find that product line introduction strategy depends on this uncertainty. Specifically, under low levels of uncertainty the firm introduces both models during the first period; under higher levels of uncertainty, the firm prefers sequential introduction and delays design of the second product until the second period. Under intermediate levels of uncertainty the firm's first product should be of lower quality than one produced by a myopic firm that does not take product line effects into consideration. We find that when the firm introduces a product sequentially, the strategy might depend on realized demand. For example, if realized demand is high, the firm's second product should be a higher-end model; if demand turns out to be low, the firm's second product should be a lower-end model or replace the first product with a lower-end model.
In this paper, we study the impact of trade-in rebates on the firm's ability to practice price discrimination when there are remanufactured products. Using evidence from a case-study of a major IT company, we argue that a trade-in program allows a firm to practice perfect price discrimination through a customized rebate. This occurs because the magnitude of the rebate is supposedly given based on the condition of the used product, however, we observed a low correlation between the rebate given and the physical condition of the returned product. We show analytically how the firm reaps significant benefits from such a trade-in program, even when disposal of the returned units is costly. We also consider the case where a remanufactured product serves as an imperfect substitute for the new product, and how its presence reduces the firm's gains from perfect price discrimination. We argue, however, that despite the negative cannibalization impact and loss of the ability to practice perfect price discrimination, a firm may still offer a remanufactured product to deter entry by a third-party remanufacturer.
It is well known that maximizing revenue from a fixed stock of perishable goods may require discounting prices rather than allowing unsold inventory to perish. This behavior is seen in industries ranging from fashion retail to tour packages and baked goods. A number of authors have addressed the markdown management problem in which a seller seeks to determine the optimal sequence of discounts to maximize the revenue from a fixed stock of perishable goods. However, merchants who consistently use markdown policies risk training customers to “wait for the sale.” We investigate models in which the decision to sell inventory at a discount will change the future expectations of customers and hence their buying behavior. We show that, in equilibrium, a single-price policy is optimal if all consumers are strategic and demand is known to the seller. Relaxing any of these conditions can lead to a situation in which a two-price markdown policy is optimal. We show using numerical simulation that if customers update their expectations of availability over time, then optimal sales limit policies can evolve in a complex fashion.