Compete in Price or Service?—A Study of Personalized Pricing and Money Back Guarantees

Retailers use both pricing and service strategies to respond to intensified competition. Here we develop a duopoly model to investigate the impact of the increasingly popular personalized pricing strategy (PPS) and the widely used Money Back Guarantee (MBG) customer returns policy. We consider two retailers who differ in customer satisfaction rates. Each retailer chooses a pricing strategy, PPS or uniform pricing, and a product return strategy, MBG or ‘no returns.’ We show that both PPS and MBG are dominant strategies, but their impact on retailers’ prices and profits are different; while PPS intensifies price competition and may lead to a prisoner’s dilemma in which both retailers may lose profit, MBG mitigates price competition and may result in a Pareto improvement in both retailers’ profits. Both PPS and MBG increase the size of the overall market, but not the total duopoly profit. The total customer surplus and social welfare may increase under either strategy. In addition, we obtain some interesting observations as to how our results may change if the product quality/customer satisfaction rate is endogenously chosen in the duopoly. Some of our findings are in contrast to related results reported in the literature.     

品牌权益影响下的双渠道供应链定价决策及协调研究

针对一个制造商开通直销渠道销售产品与零售商的价格竞争问题,文章基于制造商与零售商共享品牌权益的视角,研究在制造商双渠道供应链结构中,价格和品牌权益同时作用下的双渠道供应链定价决策,分别分析在集中决策下和分散决策下,品牌权益对两种渠道价格和利润的影响。研究发现：在集中决策下,两种渠道的价格、利润与品牌权益成正相关;在分散决策下,当品牌权益超过一定临界值时,其对制造商直销渠道的价格和制造商总利润的影响大于零售商。鉴于品牌权益对供应链定价决策的重要影响,文章建立制造商和零售商之间的品牌权益成本共担机制,并通过数值仿真分析发现,当实施品牌权益成本共担机制时,制造商和零售商的销售价格和利润均是最优的。因此,零售商应加强与制造商的互动,共同创造高品牌权益的同时,也应共同分享高品牌权益。     

Optimal retail sales strategies for old and new products in monopoly and horizontal competition scenarios

Advances in technology have made product updates more frequent and allowed consumers to choose different versions of the same product based on their preferences. It is crucial for retailers to understand how to formulate optimal sales strategies based on those different consumer preferences. To this end, we develop game models that consider the heterogeneity of consumer preferences under both monopoly and horizontal competition scenarios and perform the sensitivity analysis to examine the impact of consumer proportions and consumer preferences on retailers’ sales strategies. The results show that (i) regardless of competition or monopoly status, the original retailer can always maximize profit by setting prices based on the market share of traditional consumers, as long as the retailer sells both new and old versions of the product; (ii) the greater the competitive advantage of the competitor, the more advantageous the hybrid sales mode; (iii) if the price of the old product is below a certain threshold, there will be a positive profit for the original retailer when selling both the old and new products; and (iv) when consumer acceptance of competing retailers is lower, entering the retail market is not a good choice for competing retailers.     

Whether to offer return-freight insurance or open a physical showroom: A strategic analysis of an online retailer’s decisions

Return-freight insurance (RI) and physical showroom (PS) can be a double-edged sword for retailers, as they can help consumers reduce product mismatch and information uncertainty but may lead to higher return rates and operating and construction costs. In this study, we examine four corresponding configurations regarding whether to provide RI (yes-R, no-N) and whether to open a PS (yes-S, no-N): NN, RN, NS, and RS. First, we find that offering RI or opening a PS does not necessarily expand market demand. Whether demand grows is closely related to the RI premium. When the RI premium is low, the RN strategy, which offers only RI, can expand the market, and the NS and RS strategies, where retailers open a PS, can shrink the market. In addition, retailers offering RI charge a higher sales price, while those opening a PS adopt a price reduction strategy. Second, the optimal strategy configuration for retailers depends on four factors: the RI premium, the proportion of consumers, the retailer’s cost of handling returns and the PS construction cost. Retailers consider opening a PS only when both the proportion of high-cost consumers and the PS construction cost are low. An interesting result is that when the RI premium is higher, offering RI still benefits the retailer. Third, we present an intuitive decision support matrix to help retailers recommend the optimal strategy configuration, using the RI premium as a proxy for the product online return rate and the proportion of high-cost consumers as a proxy for the degree of product standardization. Depending on whether products with high (low) return rates are highly personalized or standardized, retailers decide whether to use an NS (RS) or NN (RN) strategy.     

Demand forecast information sharing in the competitive online and traditional retailers

An important strategic issue for retailing business managers to study is the information strategy. In this paper, we develop a profit-maximization model to investigate the benefits of demand forecast information sharing for the competitive online and traditional retailers with the consideration of the compatibility of the product with online marketing. Both retailers use a Bertrand model to compete. We analyze and compare two scenarios: (1) when forecast information is not shared between the online and traditional retailers; (2) when forecast information is shared between the online and traditional retailers. Our results show that both the online and traditional retailers will be better off from information sharing. Especially when the channel forecast is less accurate, the product is more compatible with online marketing, and the market is more volatile, both retailers will profit more. Based on our results, optimal strategies are derived and probable paths of future research are identified.     

Probabilistic selling vs. markdown selling: Price discrimination and management of demand uncertainty in retailing

Markdown selling (i.e., price reductions over the course of the selling season) is a strategy to implement price discrimination and to manage market uncertainty that has been widely adopted by retailers. This paper explores the potential advantage of introducing an additional tool to the arsenal of retailers, probabilistic selling (i.e., offering consumers a choice to buy a product that can turn out to be any item from a predetermined set of distinct items). We show that both probabilistic and markdown selling strategies serve as price discrimination tools by offering buyers an option to purchase a “damaged” good (an uncertain product under the former and delayed consumption of a product under the latter). However, the two strategies segment markets based on different types of buyer heterogeneity: buyer preference strength under probabilistic selling and buyer patience under markdown selling. Our analytical model reveals that, compared with markdown selling, probabilistic selling can (1) improve margin management by increasing revenue from full-price sales and reducing the magnitude of discounts; and (2) improve inventory utilization by reducing stockouts and the amount of excess inventory. We identify the conditions required for probabilistic selling to be more profitable than markdown selling.     

Managing service shutdowns: Cash refunds or vouchers?

Service shutdowns—extended disruptions of operations—caused by exogenous events are on the rise. Such shutdowns pose major challenges for service providers, customers, and regulators. Providers prefer vouchers as a means of service recovery to limit bankruptcy risk, whereas customers demand cash refunds or vouchers that include a generous bonus. Regulators, on the other hand, insist that customers must be granted the right to be reimbursed in cash. This paper shows that a zero bonus is optimal under the voucher-only strategy, whereas the provider should always include a positive bonus with the voucher under the hybrid strategy that allows customers to choose between the cash refund and voucher options. Surprisingly, despite its higher flexibility in service recovery design, the hybrid strategy can be dominated by the voucher-only strategy in terms of profit and welfare. Moreover, we show that the ranking of strategies differs across the two important dimensions of expected profit and survival under shutdown. Finally, we study competition among providers and show that a high-quality provider is more likely to use cash-back as the service recovery strategy than its low-quality competitor.     

Shopping in the omnichannel supply chain under price competition and product return

In recent years, omnichannel retailing has created value for prospective consumers. The rise of omnichannel retailing has changed consumers' buying habits, and manufacturers are facing stiff competition from retailers. To reduce this competition effect, manufacturers and retailers often work together to reduce showroom display costs. Despite this practice, there is little understanding of how omnichannel retailing impacts supply chain (SC) profit under competitive conditions. We investigate the test-in-store-and-buy-online (TSBO) retailing strategy and its impact on SC profit and price competition between manufacturers. The retailer sells products of both manufacturers through its website but displays products of only one manufacturer in the showroom, which bears the displaying cost. The retailer adopts a return policy for the other manufacturer. Stackelberg game was used to examine how members of the chain interact, and Nash equilibrium was used to find optimal strategies for players under decentralized and integrated channels. The results show that the TSBO strategy in retailing benefits all supply chain players under the integrated channel. A further interesting finding is that omnichannel SC profits are highest when retailers adopt a return policy. When two manufacturers compete and adopt different sales models, the manufacturer who uses the TSBO retail model reaps the most profit. Several other managerial insights are drawn from sensitivity analyses.     

Channel integration and profit sharing in the dynamics of multi-channel firms

With the rapid development of e-commerce, many brick and mortar firms are increasingly creating e-commerce channels that operate quite independently from existing physical channels, which lead to intensive channel conflicts. Channel integration with profit sharing can effectively eliminate channel conflicts and improve channel coordination for these multi-channel firms. In this study, we focus on the strategic role played by channel integration with profit sharing in the online-traditional channel competition. We use a game theoretic approach to investigate this issue. We compare non-integrated channel profits with integrated channel profits to show that both the online and traditional channels always benefit from a channel integration strategy by capturing some portion of the incremental profit gains generated by an integrated channel. We utilize a profit bargaining model to implement profit sharing for the online and traditional channels to achieve their channel integration. Based on our results, optimal marketing strategies are derived.     

Temporal product bundling with myopic and strategic consumers: Manifestations and relative effectiveness

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.     

Forecast information and traditional retailer performance in a dual-channel competitive market

Independent firms in a dual-channel competitive market are expected to have their own information about the nature of the market. In this research, we develop a game-theoretic model to examine the value of forecast information about consumers' willingness to pay. The model is based on a simultaneously played Bertrand game. Our results indicate that the profits of online as well as traditional retailers always increase with forecast accuracy, and that forecast accuracy has a greater effect on the performance of the traditional retailer than on that of the online retailer. Our results also show that the difference in profit between that of the traditional retailer and the online retailer increases with forecast accuracy. In addition we find that forecast accuracy is much more valuable to the traditional retailer when there is an increasing volatility in the market, an increasing level of consumer valuation of the product, and an increasing intensity in market competition. Based on our results, we derive optimal market strategies and identify directions of future research.     

The Impact of Search and Recommendation Systems on Sales in Electronic Commerce

The Internet and related technologies have vastly expanded the variety of products that can be profitably promoted and sold by online retailers. Furthermore, search and recommendation tools reduce consumers’ search costs in the Internet and enable them to extend their search from a few easily found best-selling products (blockbusters) to a large number of less frequently selling items (niches). As a result, Long Tail sales distribution patterns emerge that illustrate an increasing demand in niches. We show in this article how different classes of search and recommendation tools affect the distribution of sales across products, total sales, and consumer surplus. We hereby use an agent-based simulation which is calibrated based on real purchase data of a video-on-demand retailer. We find that a decrease in search costs through improved search technology can either shift demand from blockbusters to niches (search filters and recommendation systems) or from niches to blockbusters (charts and top lists). We break down demand changes into substitution and additional consumption and show that search and recommendation technologies can lead to substantial profit increases for retailers. We also illustrate that decreasing search costs through search and recommendation technologies always lead to an increase in consumer surplus, suggesting that retailers can use these technologies as competitive advantage.     

Refunds and collusion in service industries

This paper investigates industry-wide agreements on joint refund policies, and how they influence price competition. We compute the profit of fully-colluding, competing, and semicolluding service providers who offer refunds to those consumers who do not show up at the time of service. Our main findings are that both a monopoly serving all consumer types, and semicollusive service providers offer full refunds. In contrast, competing service providers offer only partial refunds. Finally, refund policies are investigated under moral hazard behavior.     

Identifying Sales Performance Gaps with Internal Benchmarking

This research investigates how retailers can benefit from identifying the sales growth potential of in-store salespeople in every product category. The proposed novel approach helps retailers develop an equitable evaluation of their sales force, using both observable and unobservable factors that affect sales. By extending stochastic frontier regression to a multivariate case, the resulting factor-analytic frontier formulation leverages the correlation pattern of sales across product categories and salespeople over time. A unique data set, from a franchise chain with 481 salespeople, operating in 35 stores and selling 11 related product categories, identifies a gap between observed category profits and an estimated profit frontier for each salesperson and category. This novel model also can benchmark each salesperson against all others across product categories while accounting for observable and unobservable factors. This approach has practical value, in that retailers can identify both top-performing salespeople and underperformers, who then might be matched to establish a positive learning environment that aligns top performers with proven sales expertise in a product category with peers who struggle with that category.     

Can behavioral nudges and incentives help lower-income households build emergency savings with tax refunds? Evidence from field and survey experiments

Tax refunds are an opportunity for lower-income households to accumulate emergency savings so they have cash on hand to cover expenses when income is insufficient. Our field experiments testing different behavioral interventions to encourage refund saving via online tax filing show small effect sizes (0.12–0.14) and a low aggregate savings rate (12%) that might be increased were filers to receive financial incentives. We test a key provision of the Refund to Rainy Day Saving and Financial Security Credit Acts using a survey experiment, finding that hypothetical refund saving jumps from 16% with no financial incentive, to 71% and 80% with 25% and 50% matches, respectively, findings which are mostly insensitive to refund size. Our results suggest that public policies to provide greater financial support—including stronger income supports—will better prepare lower-income households for financial emergencies than behavioral interventions to nudge refund saving.     

Is the system reliability profitable for retailing and consumer service of a dynamical system under cross-price elasticity of demand?

Retailing strategy is one of the most crucial factors for industries. A proper retailing strategy can help to enhance consumer service and increase the industry's profit. An improved approach to retailing is suggested in this research to deliver superior customer service while maximizing profits in a dynamic system. The study analyzes a retailing strategy for a demand with cross-price elasticity upon the retail price. A product's cross-price elasticity and the system reliability are critical factors in retailing. Understanding the cross-price elasticity of demand between products helps retailers to make pricing decisions that maximize profits by maintaining demand. Imperfect products are produced due to an imperfect production system. The imperfect ones must be adjusted with some costs to make them perfect for better retailing. The system failure rate is crucial for retailing under cross-price elasticity of demand patterns. Production system reliability, cross-price elasticity of demand, and consumer service are all essential factors that can impact a company's success in the market. The production rate is considered time- and system failure rate-dependent. Contradictory to the literature, a dynamical system is proposed for improved retail management, which is solved using the Euler-Lagrange theory. Finally, one can achieve the expected maximum profit for this retail system with optimum selling prices for different products by reducing the system failure rate. Some numerical illustrations with graphical representations are provided to validate the current study. Numerical examples show that applying cross-price elasticity of demand for more than two identical products provides 35% more profit for the retail industry than a single type of product.     

Using instant refunds to improve online return experiences

In the online return context, offering the consumer a satisfactory return experience is critical to an online seller's success. However, little is known about how online sellers can improve consumers' online return experience. This research examines whether an instant refund service can improve the online return experience. To obtain a comprehensive view of the outcomes of using an instant refund service, this paper also examines how the use of an instant refund affects several pivotal consumer responses. Study 1 analyzed the effects of an instant refund service on consumer responses in a post-purchase pre-return scenario, and Study 2 analyzed the effects of instant refunds on a set of key variables in a post-purchase post-return scenario, including satisfaction with the online return experience. For each study, the hypotheses of the effects of an instant refund on consumer responses were discussed, and a one-factor (instant refund service, yes vs. no) between-subject scenario experiment (with an additional related experiment in study 1) was conducted, using online panel data from Wjx.cn. One-way ANOVA was used to test the hypotheses. It is concluded that an instant refund service increases consumer satisfaction with the experience and improves other consumer responses. In terms of potential side-effects, instant refunds are not significantly associated with stronger product return intentions. These findings can help online sellers decide whether to evolve their conventional refund mode to a new instant refund mode.     

考虑零售商销售努力的双渠道供应链定价策略研究

随着电子商务市场的日益成熟,制造商建设线上直销渠道来适应新的商品销售环境成为趋势。制造商线上直销渠道的建立占领了部分原本属于线下零售渠道的市场份额,对线下零售渠道造成冲击。针对双渠道供应链中的竞争,将零售商销售努力行为考虑在内,通过构建博弈模型分别研究了在集中决策模式和分散决策模式下,制造商与零售商的定价策略。研究发现,在集中决策模式下,线下零售渠道与线上直销渠道之间的价格差异随着两个渠道潜在需求量之间差异的增大而增大,并且两个渠道的最优价格分别与其市场潜在需求成正比。在分散决策模式下,两个渠道的最优价格亦与潜在需求成正比,并且线下零售渠道的最优价格随零售商销售努力程度的增加而增加,线上直销渠道的最优价格随着零售商销售努力程度的增加而减少。     

Price Adjustment Policy with Partial Refunds

Have you ever purchased an item only to notice a short while later that its price was reduced? Many retailers offer to refund customers the full price difference as long as the discount occurred within a short period of time after the original purchase. Such policy looks attractive to consumers as it shields them from future price fluctuations. But can this policy be advantageous for the retailer?In this paper we investigate the price difference refund policy (commonly referred to as price adjustment) and demonstrate how it can result in a higher profit even if all consumers request and receive a price adjustment.Further, the existing literature and practice both assume that if a price adjustment policy is employed, the consumers should get the full price difference refunded. In this paper we endogenize the refund amount, allowing the retailer to determine the optimal percentage of the price difference to be returned to consumers. We fully characterize the conditions under which it is optimal to offer a partial or greater than full price adjustment to customers as well as the optimal refund percentage. Additionally, we demonstrate that the practice of limiting the price adjustment option to a short period after the purchase incident is not necessarily in the best interest of retailers.     

中国制造业企业利润决定机制研究——基于异质性生产率的视角

基于异质性生产率角度提出决定企业利润的数量模型,使用中国制造业企业样本数据研究企业的利润状况,并且提出衡量企业利润状况的两种利润率,即销售利润率与投资利润率,最后实证检验生产率对企业利润的决定作用。研究结论显示:中国制造业企业的投资利润率具有逐渐提高的趋势,而销售利润率却具有逐渐下降的趋势;企业生产率与其利润规模呈显著的正相关关系,并且具有相同生产率的企业选择进入出口市场会获得更高的利润。