Myopic Consumers Research Articles

Dynamic pricing strategy for content products considering consumer fairness concerns and strategic behavior

PurposeThe development of the digital age has made data and information more transparent, enhancing the strategic perspectives of both buyers (strategic waiting) and sellers (price fluctuations) in their decision-making. This research investigates the optimal dynamic pricing strategy of the content product developer in relation to their consideration of consumer fairness concerns to elucidate the impact of consumer fairness concerns on the dynamic pricing strategy of the developer.Design/methodology/approachThis paper assumes that monopolistic content developers implement a dynamic pricing strategy for the content product. Through constructing a two-period dynamic pricing game model, this research investigates the optimal decisions of the content developer, contingent upon their consideration or disregard of consumer fairness concerns. In the extension section, the authors additionally account for the influence of myopic consumers on these optimal decisions.FindingsOur findings reveal that the degree of consumer fairness concerns significantly influences the developer’s optimal dynamic pricing decision. When a developer offers content products with lower depth, there is a propensity for the developer to refrain from incorporating consumer fairness concerns into a dynamic pricing strategy. Conversely, in cases where the developer offers a high-depth content product, consumer fairness concerns benefit the developer. Furthermore, our analysis reveals a consistent benefit for the developer from the inclusion of myopic consumers.Originality/valueFew studies have delved into the conjoined influence of consumer fairness concerns and strategic behavior on dynamic pricing strategy. Our findings indicate that consumer fairness concerns can enhance the efficiency of the value chain for content products under specific conditions. This paper not only enriches the existing literature on dynamic pricing by incorporating consumer fairness concerns theoretically but also offers practical insights. The outcomes of this research can guide content product developers in devising optimal dynamic pricing strategies.

Impact of product sharing and heterogeneous consumers on manufacturers offering trade-in programs

Many large manufacturers offer trade-in programs as a way to protect the environment and to generate greater revenues by attracting and retaining consumers. However, the emergence of product-sharing platforms alters consumers’ purchase decisions. We develop an analytical framework for examining how manufacturers that offer trade-in programs can respond to product-sharing markets and heterogeneous consumers. Two classes of consumers are considered: myopic and strategic. This study establishes that a sharing market reduces the manufacturer’s profit when consumers are strategic rather than myopic. Moreover, a smaller salvage value will always (resp. sometimes) boost the manufacturer’s profit when consumers are myopic (resp. strategic). The manufacturer’s profit increases with the product’s depreciation rate and maintenance cost when consumers are myopic, but it may be decreasing in the depreciation rate and maintenance cost when consumers are strategic. We show that these unexpected results follow from the interaction – under certain parameters – between a propelling effect (that encourages consumers to trade in old products) and a hauling effect (that discourages consumers from buying new products). Finally, the manufacturer derives more profit from strategic than from myopic consumers regardless of whether or not there is a product-sharing market.

Buy Now Pay Later—A Fad or a Reality? A Perspective on Electronic Commerce

The Millennials and Generation Z use online shopping for a holistic experience and buy more expensive or better-quality products with buy now pay later payment methods for their highly demanding needs. The authors aimed to deepen understanding of this phenomenon by finding related knowledge fields and discovering the type of economy that will represent an increasing market share for the method of domestic e-commerce payments. The methodology used combined computer-assisted review, descriptive statistics, and linear regression to explain the market share of 23 economies worldwide. Student credit card use, myopic consumer law, buying tendencies. and dark financial triangles were identified as related topics. Logistics performance, ease of doing business, and postal development were found to be significant factors. Finally, economies with medium ranks are inclined to adopt this kind of payment easily. Hence, major implications, both managerial and academic, must be addressed. High responsibility should be borne by industry associations, which should run information campaigns by collaborating with public institutions. From the point of view of theoretical implications, studying the buy now and pay later concept and its outcomes might deepen understanding of consumer behaviour, decision-making processes, risk perception mitigation, debt behaviours, and credit adoption.

Reputation Building under Observational Learning

Abstract A patient seller interacts with a sequence of myopic consumers. Each period, the seller chooses the quality of his product, and a consumer decides whether to trust the seller after she observes the seller’s actions in the last $K$ periods (limited memory) and at least one previous consumer’s action (observational learning). However, the consumer cannot observe the seller’s action in the current period. With positive probability, the seller is a commitment type who plays his Stackelberg action in every period. I show that under limited memory and observational learning, consumers are concerned that the seller will not play his Stackelberg action when he has a positive reputation and will play his Stackelberg action after he has lost his reputation. Such a concern leads to equilibria where the seller receives a low payoff from building a reputation. I also show that my reputation failure result hinges on consumers’ observational learning.

When Less is More: A Short-form Tool to Increase Segmentation Implementation

Background Segmentation remains underutilised in social marketing research and practice. Simple segmentation tools that are easy to administer and simple for audience members to complete may increase the use of segmentation across the social marketing process. Focus of the Article Segmentation is a foundational marketing principle which allows marketers to tailor marketing activity to the needs of specific groups (segments). Evidence shows that behaviour change is more likely when more principles are used, yet segmentation remains underutilised. Data-driven methods are used to identify segments based on several variables collected via surveys, but they take time, require large sample sizes and technical analyses; and can be costly and time consuming. Importance to the Field Simple diagnostic tools are needed to simplify data collection and increase the use of key social marketing principles such as segmentation. Methods Three studies were conducted to create and verify a short diagnostic segmentation tool and later refine a tool that reflects contemporary social marketing practice. The first employed multiple linear regression to predict segment membership based on previously performed two-step cluster analysis. The second applied the tool to another data set to verify whether the tool could predict segment membership accurately. The final study delivers a short diagnostic tool following the same development approach to a data set drawn from a larger sample that included objective measures ensuring focus moved beyond how individuals think and feel. Results Segments in the first study had been defined by five variables (derived from 16 survey questions). The tool was able to predict segment membership to a high level of accuracy from five questions. In the second study the tool was used to predict segments, which had high correspondence to the segments identified in that analysis, which was also based on five variables (16 questions). The third study extended development to an analysis using 16 defining variables, based on 40 survey questions. The final tool predicted segment membership to a high degree of accuracy based on five survey questions. Recommendations for Research or Practice Segmentation is important for developing understanding that enables social marketers to design social change programs to meet the needs of more people. This simple tool developed and verified within and across samples has potential to simplify data collection enabling greater uptake of segmentation in social marketing practice. The final tool incorporated objective measures to ensure segmentation moves beyond the myopic consumer focus that has dominated social marketing. Future research could use the approach in this paper to derive short diagnostic tools with a broader range of behavioural contexts and with more diverse populations. Limitations The behavioural measures used in these studies were self-report measures, and the use of a more objective measure would further strengthen both the segmentation analysis and short diagnostic tool.

Dynamic pricing and advertising in the presence of strategic consumers and social contagion: A mean-field game approach

In this paper, we introduce a framework for new product diffusion that integrates consumer heterogeneity and strategic social influences at individual level. Forward-looking consumers belong to two mutually exclusive segments: individualists, whose adoption decision is influenced by the price and reputation of the innovation, and conformists, whose adoption decision depends on social influences exerted by other consumers and on the price. We use a mean-field game approach to translate consumer strategic interactions into aggregate social influences that affect conformists’ adoption decision. The game is played à la Stackelberg, with the firm acting as leader and consumers as followers. The firm determines its pricing and advertising strategies to maximize its profit over a finite planning horizon. We provide the conditions for existence and uniqueness of equilibrium and a numerical scheme to compute it. We conduct a series of numerical simulations to analyze firm’s strategy and diffusion processes for different parameter constellations. Our results suggest that the firm adopts a penetration pricing strategy in the presence of strategic consumers, whereas it decreases the price first and then increases it in face of myopic consumers. Moreover, our model asserts that diffusion of innovations is considerably shaped by the consumer heterogeneity. Indeed, our results show that as the fraction of one segment increases in the market, the consumers in the other segment have less tendency towards adoption.

Dynamic pricing of new experience products with dual-channel social learning and online review manipulations

Online reviews normally come from two distinct sources: first-party reviews are reviews published (by consumers) on a firm's own platform, and third-party reviews are ratings and feedback generated on a third-party website (e.g., a social media profile). Manipulations of first-party reviews could affect their credibility. We consider a two-period monopoly dynamic pricing problem with dual-channel social learning (SL) and truncated review manipulations (i.e., a firm may delete extremely low and high ratings). We propose a critical measure for SL outcome (SLO) that gauges consumers’ quality evaluation through SL and drives equilibrium outcomes. We first consider the case of a firm with myopic consumers. Without manipulations, we find that the optimal policy typically consists of increasing and decreasing prices regarding a threshold structure of SLO. The optimal price, expected profit and consumer surplus are monotone in SLO. More accurate dual-channel reviews benefit the firm and its consumers. With manipulations, we characterize the optimal price path in closed form using a novel index of manipulated SLO. Manipulations yield a higher expected profit increasing with manipulated SLO, but can induce three outcomes: benefiting all consumers, or benefiting some but hurting the others, or hurting all. More first-party reviews always facilitate the firm, but can benefit consumers only under weak manipulations. However, more third-party reviews can be detrimental for the firm but conducive for consumers under strong manipulations. We also discuss the robustness of our main qualitative insights and some extensions with additional salient features. Research implications and future directions are discussed finally.

Inventory and pricing decisions when dealing with strategic consumers: A comprehensive analysis

This work focuses on firms that sell perishable products to risk-averse strategic consumers over two periods: the full-price period and the clearance period. The risk-aversion level of strategic consumers affects their expected utility in both periods, which will determine their purchasing behaviour. Typically, firms implement either quantity commitment (QC), price commitment (PC) or rational-expectation equilibrium (REE) policies to plan for risk-averse strategic consumers’ purchasing behaviour. In this study, we develop and analyze a novel model on the sales policy, full price, and the initial inventory decisions in the above setting. Results show that the risk-aversion level of strategic consumers has structural implications on optimal policies. First, firms should implement QC when the risk-aversion level is higher than a critical threshold; otherwise, PC is better. Second, the critical threshold of risk aversion increases as the unit cost of a product and clearance price decrease and as the consumer valuation increases. This can affect the optimal policy (QC, PC or REE). Finally, PC is always optimal when strategic consumers are risk seeking. We also conclude that the optimal policy is significantly affected by the proportion of strategic consumers when we consider different kinds of consumers (e.g. myopic consumers).

Strategic retailers and myopic consumers: Competitive pricing of perishable goods

We present an experimental study of dynamic pricing in which two retailers compete to sell perishable goods over a finite horizon. Consumers arrive at the market one at a time and remain there for a single period. Each consumer compares the two simultaneously posted prices, one by each retailer, and then decides probabilistically whether to purchase the good from Retailer 1, from Retailer 2, or not purchase it at all. The competing retailers are assigned to one of three between-subject experimental conditions. In one condition they start each session with equal inventories and in two other conditions with unequal inventories. Following a short learning period, equilibrium best-response solutions, which serve as benchmarks for our analysis, account well for the mean posted prices; however, small but systematic deviations from equilibrium play significantly diminish the retailers’ profits. These deviations decrease considerably in size with experience.

Bundle Pricing, Reservation and Refund Policies in a Two-Level Supply Chain

Refunding and bundling reservation are known as two popular methods to increase profit where in recent years have gained attention of researchers. One main application of refunding policy emerges for online product sale methods, where consumers can be refunded by returning goods which are not favorite according to their interest. Examining three scenarios including refunding, bundle reservation and refunding along with bundle reservation policies, we will investigate a model for each corresponding scenario. We try to compare two refund and bundle reservation pricing policies in a two-level supply chain including one manufacturer and one wholesaler, and we provide a combined model including two products. The demand is constant and also the population-related information about the division of the population into two types of consumers, strategic consumers (consumers who can predict the second stage discount) and myopic consumers (consumers who can not predict the second stage discount) are available. In addition, the percentage of consumers who refund the product due to regret, the inability to install the product or other reasons, is constant and is independent of the amount of refund. We show that the combined model is optimal and has a higher profit margin than any other policy alone.

Data Tracking under Competition

We explore the welfare implications of data tracking technologies that enable firms to collect consumer data and potentially use it for price discrimination. The model we develop centers around two features: first, competition between firms and, second, consumers' level of sophistication. Our baseline environment features a firm that can collect information about the consumers it transacts with in a duopoly market, which it can then use in a second monopoly market. We characterize and compare the equilibrium outcomes in three settings of interest: (i) an economy with myopic consumers, who, when making purchase decisions, do not internalize the fact that firms have the ability to track their behavior and use this information in future transactions, (ii) an economy with forward-looking consumers, who take into account the implications of data tracking when determining their actions, and (iii) an economy where no data tracking technologies are used either due to technological or regulatory constraints. We find that the absence of data tracking may lead to a decrease in consumer surplus, even when consumers are myopic. Importantly, this result relies critically on competition: consumer surplus is higher when data tracking technologies are used in the marketplace only when multiple firms offer substitutable products to consumers. Our results contribute to the debate of whether to regulate firms’ use of data tracking technologies by illustrating that their effect on consumers depends not only on their level of sophistication, i.e., the extent to which they internalize how their data may be used, but also on the degree of competition in the market. Finally, in contrast to earlier work, we show that firms may have no incentive to self-regulate their use of consumer data even when consumers fully internalize and anticipate how their data may be used.

Influence of strategic consumers on the network goods market

One of the important trends in modern economic development is the expanding variety ofso-called network commodities. Network commodity is such a good the usefulness of which for each consumer depends on the total number of using it consumers. The purpose of the paper is to study dynamic pricing in the network commodity market with a positive network effect in the presence of two types of consumers: myopic, taking into account only the current utility of the commodity, and strategic, focused on utility for the entire period of use of the commodity. Market dynamics, including price trajectories maximizing the monopolist supplier's revenues, are established by running numerical experiments on the corresponding theoretical model. The features of this dynamics are revealed for the cases of a large share of myopic consumers and under the conditions of dominance of strategic consumers. It is demonstrated that, in contrast to the situation in the market of ordinary commodities, a monopoly supplier of the network commodity may be interested in the presence of strategic consumers in the market. The more such consumers are present, the shorter the period of warming up the market by the supplier by means of low prices and the higher the rate of the consequent price growth. Strategic consumers find themselves hostage of their own focus on the integral effect in consumption. The directions of further research of the market of network commodities with the heterogeneous consumers are presented.

Stocking Decisions for a Firm With the Presence of Prudent Consumers

This article examines the stocking quantity for a firm in the presence of prudent consumers. First, we analyze the conditions for prudent consumers to purchase products based on the estimations of perceived value bias and product availability, and then solve the firm’s optimal stocking decisions. We observe that if the firm wants to determine an optimal stocking quantity to maximize the expected profit, it must search for more information about prudent consumers’ perceived value bias, return cost, and estimates of product availability. We further compare prudent and myopic consumers and analyze how the firm’s optimal stocking quantity would change when facing these two types of consumers. This result indicates the firm facing prudent consumers should take measures (such as increasing stocking quantity or providing relevant information) to increase the perception of product availability; however, when consumers in a market are myopic, the firm should properly increase the consumers’ return cost by increasing compensation to the firm for returned products.

How Does Heterogeneous Consumer Behavior Affect Pricing Strategies of Retailers?

This paper presents the latest progress on pricing and revenue management. Consumer's switching purchase behavior occurs frequently in perishable goods retail market, and we propose a two-period dynamic pricing model among online and offline retailers under heterogeneous purchase behavior of myopic consumers and strategic consumers. Through equilibrium solution and analysis, this study discusses the optimal pricing strategy under the influence of the service perception factor and the proportion of two kinds of consumers. Moreover, this paper analyzes the effect of three pricing strategies on profits to prove the effectiveness of price matching strategy implemented by offline retailers. The results show that the strategic behavior of heterogeneous consumers does not always have a negative impact on the profits of two retailers. The offline retailers can strategically choose to set higher prices to increase profits, and online retailers can also reduce the impact of heterogeneous consumer behavior by disclosing product attribute information. It is unwise for online retailers to take the initiative to match the price set by the offline retailers. In contrast, offline retailers can achieve a win-win situation for both retailers by matching the price of the online retailers actively.

The Impact of Cost Reduction on Price Matching Strategy in the Presence of Hybrid Consumers

This article mainly considers the impact of cost reduction on price matching strategy when a firm sells products in two periods. The cost reduction in the second period is due to technological advancement and production learning. The market is made up of myopic consumers and strategic consumers. The conclusions show that firm’s optimal profit will decrease with the increase of the fraction of strategic consumers. Besides, when the production learning effect dominates, the firm sells at a reduced price in two periods. When the technological advancement effect dominates, the firm maintains a uniform price for sale throughout the sales period. Finally, both the technological advancement and production learning effect can effectively reduce the loss of profits caused by strategic consumers, and the effect of the technological advancement is more significant.

Responsive Pricing of Fashion Products: The Effects of Demand Learning and Strategic Consumer Behavior

This paper studies the potential benefits of responsive pricing and demand learning to sellers of seasonal fashion goods. As typical in such markets, demand uncertainty is high at the beginning of a season, but there is a potential opportunity to learn about demand via early sales observations. Additionally, although the consumers have general preference for purchasing a fashion product earlier rather than later in the season, they may exhibit strategic behavior—contemplating the benefits of postponing their purchase in anticipation of end-of-season discounts. Our results demonstrate that the benefits of responsive pricing, in comparison with a benchmark case of a fixed-price policy, depend sharply on the nature of the consumers’ behavior. Interestingly, in stark contrast to markets of myopic consumers, when the consumers are all strategic, the benefits of responsive pricing tend to worsen when there is a higher potential for learning. We explain this counterintuitive outcome by pointing to two phenomena: the spread effect and information shaping. For example, sellers of fashion products that consider upgrading their pricing systems to incorporate “accurate response” strategies (i.e., integrating learning and responsive pricing) should be aware of the possibility that such action might lead them to a new and potentially worse equilibrium, particularly when there is a higher opportunity to learn. Despite the fact that price commitment completely eliminates the seller’s ability to learn, it appears to increasingly dominate responsive pricing as the portion of strategic consumers in the market increases. But, although performing better than responsive pricing, a price-commitment policy is typically limited in performing effective discrimination. Finally, we studied the potential benefits of quick response strategies—ones that embed both dynamic pricing and quick inventory replenishment during the sales season—and found that they are particularly significant under strategic consumer behavior. We explain this result by arguing that quick response provides the seller with a real option that serves as an effective implicit threat to the consumers: encouraging them to buy earlier at premium prices rather than wait for discounts at the end of the season. The online appendix is available at https://doi.org/10.1287/mnsc.2018.3114 . This paper was accepted by Martin Lariviere, operations management.

Dynamic Pricing under Cost Reduction in the Presence of Myopic and Strategic Consumers

After release, a product usually suffers cost reductions during its whole lifespan. Compared to the myopic, strategic consumers may have stronger incentive to delay the purchase once they perceive that a significant cost reduction will result in a markdown. The strategic (compared to the myopic) properties influence the seller both quantitatively in terms of proportion of strategic consumers and qualitatively in terms of customer patience. To forecast the reaction of the whole market under cost reduction, it is necessary to acquire the strategic properties. In this paper, we study the impacts of proportion of strategic consumers, customer patience, and cost reduction on dynamic pricing strategy when cost reduction comes from technology advancement. The seller makes pricing strategies when facing unknown future cost, and the buyer makes purchase decisions when facing unknown future price. Our study shows that generally both higher strategic consumer proportion and customer patience contribute to a delay in sales. Further, profit diversion happens under great combination of strategic properties. In addition, with the increase of customer patience, not only strategic but also myopic consumers will buy less. Finally, the strategic properties moderate the pricing strategy in latter stage when there is a cost reduction. This indicates a threshold as combination of strategic properties, upon which seller tends to offer a smaller markdown to discourage strategic waiting, and under which seller tends to offer a greater markdown to divert strategic consumers to the latter period.

Optimal prices and trade-in rebates for successive-generation products with strategic consumers and limited trade-in duration

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.

Estimating switching costs with market share data: an application to Medicare Part D

Choice inertia and switching frictions are well-documented features of the demand for health insurance. In this paper, we estimate switching costs in the Medicare Part D market with aggregate market share data using standard discrete choice models for differentiated products. We consider various modelling assumptions: myopic and forward-looking consumers, and with and without random coefficients. Both myopic and forward-looking consumer models with no random coefficients yield switching cost estimates that closely match the actual average switching frequency, with implied dollar-valued switching costs of $1600 to $2000. We find the inclusion of random coefficients to the myopic consumer model results in smaller estimates of switching costs, but only at the expense of the model’s fit to the switching frequency. The estimated welfare losses from switching frictions are large, but they are smaller under the forward-looking consumer model, amounting to around $500 per enrollee annually, compared to over $1000 under the myopic model.

Advance Selling to Strategic Consumers: Preorder Contingent Production Strategy with Advance Selling Target

Motivated by emerging industry practices, this paper studies the effectiveness of a new advance selling strategy in counteracting strategic consumer behavior: the preorder contingent production (PCP) strategy, where the seller's production decision is contingent on an advance selling target. We find that compared to other advance selling strategies, such as the traditional advance selling strategy and the capacity rationing strategy, the PCP strategy is effective in mitigating strategic waiting behavior and thus can significantly improve the seller's profit performance, especially when consumers’ discount factor is at a medium or high level, the production cost is not too high, or the market size has an unbalanced probability distribution. Moreover, when the market size is deterministic, we show that the PCP strategy can completely eliminate strategic waiting behavior and attain the seller's profit performance under myopic consumer behavior. Finally, we demonstrate that the benefits of the PCP strategy are robust under other model considerations.