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China's resource allocation mechanism in education has become an important factor in determining residential access to educational resources. The purpose of this paper is to analyze the impacts made by the individual natures of buyers, the external environment, as well as the characteristics of residential properties on the willingness price of buyers. The study's aim is to lay theoretical foundations for the determination of problems related with the matters under consideration.

Using the panel data of 54 districts and counties in Beijing, Shanghai, Guangzhou and Shenzhen, the study unifies macro factors and micro factors in a model for empirical analysis.

Basic education resources can affect housing prices via the “capitalization of education.” The degree of those educational resources’ influence on willingness price changes according to personal income levels, standards of living, housing price fluctuations, the convenience of the residential area and the degrees of urbanization in a district. The greater the buyer's income and standard of living is, the higher is their willingness price. Buyers in urbanized areas prefer increases in educational resources. Increased educational resources increase the values of residential downtown areas. In developed areas with private educational facilities, the role of educational resources in influencing property prices is relatively small.

This paper uses data concerning the consumption and investment of residential properties to build a theoretical model for the willingness price of buyers. It unifies macro factors and micro factors in a single model and presents new results about basic education resources and the willingness price of buyers under different conditions.

The world over is becoming urbanized, and people are migrating to cities in large numbers in search of opportunities. The increased urbanization has posed challenges such as congestion, rising crime, and growing urban poverty. The governments respond by providing amenities such as schools, hospitals, and housing to meet to increase in demand for these facilities. However, there is a need for the provision of facilities that meets the expectations of the people, particularly on the proximity of amenities and bundles of utility-bearing housing characteristics. In an attempt to address the challenge mentioned, the study estimated the hedonic characteristics influencing the willingness to accept and willingness to pay for housing facilities in the Eastern Cape Province, South Africa. Using a multiple linear regression model and artificial neural network, the study found out that properties with a bathroom, garage and large floor size have a higher value compared to properties without these facilities.When making decisions to acquire a property, buyers consider the availability of discounts and the prevailing property price. Overall, willingness to pay and accept decisions are mainly determined by location and the price at which homogeneous neighborhood properties were sold. Therefore, the study recommends that urban town planners and other housing authorities prioritize the construction of properties with larger floor areas, parking bays, and bathrooms using a cost-effective mechanism that makes the properties affordable to residents.

This chapter traces the development of the pricing research program of Kent Monroe, beginning with his doctoral dissertation and continuing to the present time. Drawing on psychophysics and adaptation-level theory the early research efforts concentrated on validating two important concepts relative to behavioral pricing research: reference price and acceptable price range. Then the behavioral pricing research program expanded to explore how the context of a purchase situation, including the structure of the prices available for judgment, influences buyers' price perceptions and willingness to buy. In the early years his research included pricing models and research on patronage behavior. Subsequently, concentrating primarily on behavioral pricing research, he began to integrate findings from the research program into examining how various sellers pricing strategies and tactics influence buyers' judgments and purchase decisions. These efforts led to the first edition of his book Pricing – Making Profitable Decisions published in 1979. The book was subsequently revised and expanded in 1990 and again in 2003.

A loyalty program might influence buyer behavior in several ways. Prior research offers evidence that buyers might increase the frequency of purchases and volume per occasion in a loyalty program; however, the effect on buyers' price tolerance has not been studied before. The aim of this paper is to examine buyers' willingness to pay a price premium for a firm offering a loyalty program reward.

An analytical model of dynamic consumer choice is developed, where one of the two selling firms offers a reward for a certain number of purchases. The maximum price premium that a normatively rational buyer should be willing to pay at each level of accumulated purchases is obtained. A price tolerance in controlled settings is obtained and these are compared with normative solutions.

Analytically, it is shown that the maximum price premium increases as purchases are accumulated; and the exact solutions can be found, given the price distributions and program design parameters. In the empirical studies it is found that individuals' maximum premiums are less than the normative levels. On the other hand, as buyers accumulate purchases from the reward offering firm, and get closer to the reward, maximum premiums paid increase – particularly when the reward is immediate.

This paper contributes to the loyalty programs literature by examining the price premium, or switching barrier, aspect of buyer response. Furthermore, the paper not only models and solves the normative strategy, but also obtains actual price tolerance in laboratory settings.

The purpose of this study was to empirically evaluate a modified version of Sheth's model (1981) of buying behavior, in order to determine retail buyers’ willingness to trade off on negotiation variables when placing items on automatic replenishment (AR). A total of 103 usable questionnaires were returned from corporate buyers from five major department store chains located throughout the USA, yielding a 41 percent response rate. Multiple regression analysis indicated that the modified portion of Sheth's model used in this study was satisfactory in exploring relationships that exist between buyers and vendors when determining what products can be placed on AR. The model was significant and respectable in explanatory power, and the significant or highly related variables were: merchandise driven mentality; price/value; color; design; and type of merchandise category. These were all significant or highly related to the buyer's willingness to trade off on the negotiation variables (price, packaging, delivery and assortment). Future research is needed to explore the development of a model that explains the process and decision criteria for successful AR programs.

This paper includes an examination of two key issues on price decisions: (1) how should price decisions be made (the strategic and normative issue) within market contexts, and (2) how are price decisions actually made (the execution and implementation of price decisions). The paper closes with some observations useful for applied research and strategies for making effective pricing decisions. The propositions and literature review show that one pricing strategy does not fit a brand in all market contexts that brand executives experience annually in managing brands. Setting specific price points requires continuing deliberate management responses to dynamic market contexts. This paper provides useful sense-making conjunctive steps to accomplish such deliberate thinking effectively relevant for different market contexts.

The influence of security practices is increasingly common in the supply chain management and logistics literature. However, an under-researched area exists within the logistics service provider (LSP) selection process. The purpose of this paper is to introduce a security capability into the LSP selection process. Specifically, this research seeks to understand partner willingness to compensate and collaborate with service providers that possess a security capability.

Adaptive choice modeling is adopted to assess the influence of a security capability in the LSP selection process. This study represents the first use of this method in supply chain management and logistics research. Cluster analysis is also performed to uncover specific buyer segments along with traditional regression-based significance testing and counting analysis.

The findings indicate that security can have an important influence on the LSP selection process. In particular, the findings note a willingness to pay for a security capability in LSP selection. Applying segmentation techniques to the findings, three LSP buying segments are determined, each placing different importance and value on LSP capabilities.

This research notes an ongoing provider deficiency in security offerings. Partner firms sometimes maintain a cost focus, but others show a willingness to pay higher prices for access to partners with a security capability. Key practitioner findings include the need to include security with other traditional selection variables. The study walks the researcher and manager through the development of segments based on LSP capabilities.

This manuscript investigates logistic service provider selection. The authors detail an advanced form of conjoint analysis, adaptive conjoint modeling, for first time consideration. Additionally, this is the first study to integrate security into the LSP selection process. This is also the first study to identify a willingness to pay for a security capability.

Discusses a conceptual model of consumers′ product evaluation that should help marketers′ understanding of price setting. Provides a conceptual model that incorporates acceptable value range and that examines the influence of price and store name information on quality, monetary sacrifice, value, and willingness to buy. Argues that unlike brand name image, which takes considerable time, money and managerial talent to develop, price and retail outlet are two distinct marketing tools for making quick position movements in a competitive market. Concludes that understanding the effects of price and store name information should lead to more effective and efficient behaviour in the marketplace by both buyers and sellers.

Lease contracts at the time of sale influence buyers' expectations about future returns of farmland ownership and may thus contribute to price dispersion. This paper investigates the conjecture that existing land lease contracts influence buyers' and sellers' costs of being information deficient and thus their bargaining position, their expectation formation about future returns, and thus ultimately the farmland price.

The authors link different levels of information, search, and bargaining costs to three buyer types and their land use intentions. Relying on a rich dataset of farmland transactions in the German Federal State of Saxony-Anhalt from 2014 to 2019, the authors use a hedonic pricing model to investigate five hypotheses applying multivariate one-sided tests.

The authors find buyer-specific effects related to lease status and lease term of a lot. Tenant buyers pay less than non-farmer buyers for leased lots, whereas non-tenant farmers pay a markup. While prices decrease for all buyer groups with an increasing lease term, this effect is the strongest for non-tenant farmer buyers. This study’s results suggest that an existing lease contract impacts buyers' costs of being information deficient, their bargaining positions and expectation formation, and ultimately the price discovery process.

To the authors’ knowledge, this is the first study that decomposes the effects of tenancy on farmland prices by buyer type and lease term. The study provides insights into price dispersion for identical characteristics of farmland and explains why empirical studies have found mixed or no empirical evidence that lease contracts influence the price discovery process.