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The uncertainty of consumers' perceived value makes online education enterprises face great challenge in developing the pricing strategy. So the purpose of this paper is to research the pricing strategies of online education products by considering knowledge consumers' characteristics.

Considering consumer matching degree and price comparison, this study establishes the utility functions of consumers in normal sales period and discount selling period. On this basis, the research builds pricing models of the online education enterprise under the strategy of price undertaking and intertemporal pricing strategy. It further discusses the impact of consumer matching degree, consumer price sensitivity and different types of consumers on the product price and profit of online education enterprises, and reveals the optimal pricing strategy of the enterprise.

Consumer matching degree and price sensitivity coefficient have positive effects on product price and enterprise profit, but they have different effects on product demand; there are differences in the perceived value of the three types of consumers, and matching consumers are the optimal consumer group; the intertemporal pricing strategy is better than the strategy of price undertaking only when the price sensitivity coefficient is greater than a critical value.

This study enriches the literature on the pricing model of online education products and owns a practical significance to guide the online enterprise to make marketing strategies to increase profit.

In this paper, the authors explore the consequences of showrooming and price matching strategy to combat showrooming under the consideration that brick-and-mortar (BM) stores and online retailers hold different costs.

The authors use a duopoly model to analyze the impact of showrooming behavior on competition between a BM store and an online retailer with different types of customers and different costs. Then, they consider the price matching strategy that a BM store could employ to combat showrooming and explore the effect of such a strategy.

Showrooming behavior is detrimental to the profit of the BM store, and the online retailer suffers a loss of their profit unless the relative cost of the BM store is high and only part of the customers exhibit showrooming behavior. As the fraction of customers who seek price matching increases, profits of both the BM store and the online retailer initially decrease and then may increase, even if there is no showrooming.

Unlike existing studies that ignore different costs between online and offline retailers, the authors set different costs between the BM store and the online retailer to consider the effects of showrooming and price matching strategy.

Price-matching refunds are frequently used by sellers as part of their overall pricing strategy. While previous research on price-matching refunds has focused on providing a rationale for its existence, our focus is on the financial aspect of such pricing policies. In particular, we contend that a price-matching refund offer is a contingent liability undertaken by sellers. As such, this liability, contingent on whether buyers identify a lower price and claim the refund, has financial value. This contingent-claims perspective enables us to draw on the option pricing literature to analyze price-matching refund offers and identify the key parameters that determine the value of a refund “put” option. The option pricing model provides insights regarding the optimal design of price-matching policies. Importantly, this perspective enables us to numerically compare the costs of offering a price-matching refund policy to alternative pricing strategies. Further, the contingent-claims perspective allows us to represent the existing rationales for price-matching matching refund policies in a parsimonious framework

The purpose of this paper is to study the pricing problem of product transfer price under the channel advantages; determine the structure models of optimal transfer price expectation; and compare the differences in pricing of different pricing dominant parties.

Uncertain factors are introduced into dynamic pricing mathematics models; production and storage models are combined; the method of functional analysis is used to solve transfer pricing question under different advantage conditions; and price matching models in supply chain integration are put forth.

There is a proportional relationship between the optimal transfer price expectation and price fluctuation. The party which has channel advantages will gain relatively more profit, but the maximum revenue can be obtained only in the supply chain integration.

There is no appropriate empirical data to verify the models.

The paper provides pricing reference method to monopoly competitive enterprises on different stages. The matching pricing models based on E‐commerce can deal with the price deviation caused by goal difference and random factors automatically.

The paper considers production and inventory pricing, reflects the influence of the whole pricing factors under different channel advantages, and puts forth dynamic matching pricing models and algorithm under the E‐commerce circumstances.

This paper aims to advance interfirm relationship (IR) research by applying a theoretically based typology in IR settings and empirically investigating the association of information technology (IT) and relational reciprocity with IR types.

This study draws on Fiske's relational models theory to conceptualize an IR typology. In a business service context, a questionnaire was administered and IR types modeled via a multivariate logistic regression with IT pervasiveness, IT customization, reciprocity and embeddedness as predicting variables.

The IR typology comprises communal sharing, authority ranking, equality matching, and market pricing types. The authors find that reciprocity is more likely to associate with an equality‐matching relationship and a communal sharing relationship than with a market‐pricing relationship. Pervasive use of IT fosters an equality‐matching IR, but IT‐enabled customization distances an IR from an equality‐matching relationship.

A theoretical implication flows from the innovative application of Fiske's relational models theory to a context of business interactions and investigation of IT in association with IR types. The affirming findings empirically validate the IR typology and offer a new perspective in studying IR structures. This research also exemplifies the theoretical value and great potentials for further exploration of the theory in IR research.

The IR typology equips marketing managers with a useful tool in comprehending the intricate IRs and developing appropriate strategies for effective IR management. In designing IT use in IR interactions, both the scope and specific function of IT should be considered in order to ensure that all aspects affect consistently. Managers may encourage reciprocal exchange in shifting an IR away from a calculating relationship but consider intensive IT to foster an IR emphasizing balance and correspondence.

The novelty of this paper lies in the innovative application of Fiske's relational forms in IR settings and the empirical examination of the IT‐IR structure association. The IR typology advances IR research by offering a theoretically compelling and practically advantageous framework in studying IR structure, and the examination of IT‐IR associations brings to light the significance of IT in IR structures, which has been largely under‐explored.

The paper proposes investigating the timing of consumer requests for price‐matching refunds, the relationship between the refund timing and consumer repeat store purchase and the reasons for buying from the price‐matching store when a lower competitive price is found before purchase.

In Study 1, qualitative research (consumer interviews) was conducted; Study 2 uses a shopping simulation in which the timing of consumer refund‐seeking behavior is observed, and Study 3 involves a consumer survey in which information on consumer refund‐seeking behavior at real stores is gathered.

The paper finds that consumers request price‐matching refunds more frequently at the time of purchase than after the purchase. Seeking (and receiving) the price‐matching refund is associated with higher repeat store purchase behavior than not having had a refund‐seeking experience. Key reasons for buying from the price‐matching retailer when a lower competitive price is found before purchase include convenience, tangible extras, and store reputation/service quality.

A student convenience sample was used. In Study 2, fictitious stores were used. In Study 3, the timing of refund seeking may have been different on other (not reported) occasions. Ability to seek the refund was not accounted for.

The majority of the retailer's price‐matching cost will come from issuing at‐the‐time‐of‐purchase refunds, when consumers possess more bargaining power. A positive refund‐seeking experience may create a more loyal customer. In addition to being a low‐price signal, price‐matching policies can serve as signs of retailers' customer orientation.

This research fills the gap in understanding the consumer price‐match refund‐seeking behavior and offers practical implications for retailers employing price‐matching guarantees.

The purpose of this paper is to investigate the effects of three price-matching guarantee (PMG) variables, including refund depth, refund period and competitive scope, on consumer response; the moderating role of consumer search costs is also examined.

This study uses a scenario simulation method with a 2×2×2 factorial design to test the research model and hypotheses.

The results indicate that refund depth has a significant effect on price perception and purchase intention, while competitive scope has a significant effect on purchase intention. In addition, the effects of both refund depth and competitive scope on price perception are moderated by consumer search costs.

This study is a pioneering effort to explore the effects of PMGs variables on consumer response in the context of online retailing. These findings provide several important theoretical and practical implications for the PMG strategy of online retailing.

This study aims to explore the impact of decentralized long-term rental apartments on the value of in-community housing from two perspectives of housing price and rent.

This study uses the hedonic model to identify the factors affecting the housing value, and the influence of distributed long-rented apartments on the housing value in the community is analyzed from two aspects of housing price and rent by using the ordinary least square method and propensity score matching method.

The primary finding indicates that decentralized long-term rental apartments increase housing prices while decreasing general rental housing rents in the community, with the average degree of increase ranging from 0.93% to 2.59% and the average degree of decrease ranging from 2.23% to 4.34%. According to additional research, the prices of houses within communities rise by 0.042% for every 1% increase in the share of decentralized long-term rentals, while the rents for other types of rental property fall by 0.162%.

The government can regulate the housing market by regulating the access and layout of distributed long-rent apartments.

The findings of this study indicate that the existence and share of distributed long-rent apartments have a heterogeneous impact on the housing price and rent in the community, respectively.

To expand the literature and enhance understanding of the mentoring process, this research proposes the social exchange theory (SET) as a framework for the exchanges that take place between individuals in a mentoring relationship.

A detailed literature review for mentoring and Fiske's social exchange theory propositions, as well as work by Hofstede on power distance, gender, and diversity studies, provide a new approach to mentoring research.

The four relational structures (communal sharing, authority ranking, equality matching and market pricing) developed by Fiske and the effects of diversity are integrated with the existing mentoring literature to create a new model explaining the effects exchange type and diversity have on the perceived amount of support given and received during the maturation process of the mentoring relationship.

This paper extends an under‐researched area of mentoring with discussion and suggests areas for future research. Specifically, the study focuses on operationalising and testing the proposed, expanded mentoring model in both qualitative and quantitative research for confirmation and further theory building.

By integrating mentoring and Fiske's social exchange theories to provide an alternative explanation for the mentoring process, this paper proposes a number of new possible relationships that will require quantitative, confirmatory research but should add significantly to this area of study. Propositions for further testing are provided as well as suggestions for operationalising and testing the model.

Seeks to study the effect of a low‐price guarantee (PG) on store price image and store patronage intention. Two kinds of low‐price guarantee are studied: a price‐matching guarantee (PMG) where the price difference is refunded and a price‐beating guarantee (PBG) where a retailer offers an additional compensation.

A questionnaire is used to collect information on 180 non‐student respondents in an experimental framework where low‐price guarantee dimension is manipulated through three advertisements for printers.

Findings are: first, that PG indeed lowers store price image, increases the confidence that the store has lower prices and increases patronage intention; second, that, compared with a PMG whose effects are positive but rather small, a PBG further lowers the store price image on the low prices dimension without increasing the intention to search for lower price, this intention being already rather high in the PMG condition; third, that a larger effect is observed for non‐regular customers.

Research limitations are associated with the data collection. For greater reality the study uses an existing retail chain, so specific effects coming from this chain could influence the results but this bias cannot be evaluated as the experiment involves one retailer only.

Practical implications are that price image can be manipulated without any change in pricing policy by a low‐price guarantee and that the interest to adopt a price‐beating guarantee is real.

The contribution of this study lies in its focus on a large PBG level that retailers already apply and in demonstrating that a PG depends on the relationship between the consumer and the retailer with a stronger effect on non‐regular customers.