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This paper aims to investigate how user expectations affect value-added service (VAS) investment and pricing decisions of two-sided platforms. It draws on the information asymmetry theory and offers suggestions on how platform operators can manage user expectations.

According to the game theory, this study considers three user expectations (responsive, passive and wary). By framing the Hotelling duopoly model and comparing the VAS investment, price and platform profits, the optimal platform decision is analyzed and discussed.

The conclusions demonstrate that the monopolistic two-sided platform obtains more profits from the informed users with responsive expectations than uninformed users with passive or wary expectations. The marginal investment cost and cross-network externalities are two key factors that determine the platform's VAS investment and pricing strategies of passive or wary users. Furthermore, considering the expectation preferences, i.e. the uniformed users hold wary expectations with more information and hold passive expectations with less or no information, the results suggest that the proportion of wary users to all uninformed users increases the platform's VAS investment, profits and the price of informed users, and increase (decrease) the price of uninformed users when the cross-network externalities of informed users are relatively small (larger).

These results can provide insightful enlightenment into how platform operators utilize bilateral users' expectations and information level to guide their VAS investment and pricing decisions.

This paper is one of the first to explore the impact of three user expectations and the heterogeneity of preferences in informing users' passive or wary expectations, based on different levels of information on the decision-making of two-sided platforms regarding VAS.

The intention of the empirics is to contribute to the general understanding of investor responses to market price shocks. The authors review assumptions about investor behavior in response to price shocks and investigate alternative rebalancing heuristics.

The authors use market data over 40 years to define market shocks. Portfolio rebalancing implements constrained Markowitz mean-variance (MV) heuristics.

Momentum rebalancing in portfolio management outperforms contrarian rebalancing in the study interval. Sensitivity analysis by decade, sector constraints and proportion of security holdings bought or sold continue to support momentum rebalancing.

The results are consistent with under-responding to price shocks at consensus levels in financial markets. The theoretical background provides a basis for experimental lab studies of shocks of different magnitudes under conditions in which participants have information on the levels of other participants and a condition in which they can only observe their previous estimates.

Managing portfolios in the face of price disturbances of different magnitudes is informed by empirical studies and their implications for investor behavior.

This is the first study the authors can locate that uses market data with alternative rebalancing heuristics to estimate price returns from the respective heuristics over a time interval of 40 years. The authors support the results with sensitivity estimates and consider implications for the underlying agent heuristics in light of background studies.

Large-scale farm management in China has developed rapidly in recent years. Large-scale farmers face substantial operating risks, requiring extensive price risk management. However, the agricultural insurance and futures markets in China are incomplete. This study aims to analyze the price-risk-management behaviors of large-scale farmers under incomplete market conditions, with a focus on the interconnections between large scale farmers' subjective preferences (risk preferences, time preferences), liquidity constraints and their price risk management.

The authors construct an analysis framework to reveal the impact of large-scale farmers' risk preferences, time preferences and liquidity conditions on their price-risk-management behaviors under incomplete market conditions. Using data from field surveys and subjective preference experiments involving 409 large-scale grain farmers in China, an empirical analysis was conducted using the bivariate probit model.

The results show that risk-averse farmers will use risk transfer (such as contract farming) and risk diversification (such as multi-period sales) to avoid price risk. However, farmers subject to liquidity constraints and strong time preferences will not choose risk diversification, and the interaction between time preferences and liquidity constraints will strengthen this decision. The larger the farm-management scale, the greater the impact.

The authors focus on rapidly developed large-scale farm management in China. Appropriate price risk management is required by large-scale farmers due to their substantial operating risks. Considering the incomplete conditions of agricultural insurance and futures markets, the results of this study will help identify behavioral characteristics of large-scale farmers and optimize their price-risk-management strategies, further stabilizing large-scale farm management.

The purpose of this study is to estimate the housing wealth effect on non-durable consumption using data from the Spanish Survey of Household Finances (Encuesta Financiera de las Familias, SHF) for the period 2002–2017.

The authors aim at identifying the effect of anticipated and unanticipated housing wealth changes on consumption with the sample of homeowners, following Paiella and Pistaferri (2017).

Results of this study lead us to conclude that there exists a strong housing wealth effect on consumption for the Spanish households.

The authors provide evidence against the permanent income model. They also analyse how the results change with income expectations, age and the household indebtedness rate. Finally, they detect a strong excess sensitivity to income.

This paper aims to examine the dynamics of house prices in metropolitan cities in an emerging economy. The purpose of this study is to characterise the house price dynamics and the spatial heterogeneity in the dynamics.

The author explores spatial heterogeneity in house price dynamics, using data for 35 Indian cities with a million-plus population. The research methodology uses panel econometrics allowing for spatial heterogeneity, cross-sectional dependence and non-stationary data. The author tests for spatial differences and analyses the income elasticity of prices, the role of construction costs and lending to the real estate industry by commercial banks.

Long-term fundamentals drive the Indian housing markets, where wealth parameters are stronger than supply-side parameters such as construction costs or availability of financing for housing projects. The long-term elasticity of house prices to aggregate household deposits (wealth proxy) varies considerably across cities. However, the elasticity estimated at 0.39 is low. The highest coefficient is for Ludhiana (1.14), followed by Bhubaneswar (0.78). The short-term dynamics are robust and show spatial heterogeneity. Short-term momentum (lagged housing price changes) has a parameter value of 0.307. The momentum factor is the crucial dynamic in the short term. The second driver, the reversion rate to long-term equilibrium (estimated at −0.18), is higher than rates reported from developed markets.

This research applies to markets that require some home equity contributions from buyers of housing services.

Stakeholders can characterise stable housing markets based on long-term fundamental value and short-run house price dynamics. Because stable housing markets benefit all stakeholders, weak or non-existent mean reversion dynamics may prompt the intervention of policymakers. The role of urban planners, and local and regional governance, is essential to remove the bottlenecks from the demand side or supply side factors that can lead to runaway prices.

Existing literature is concerned about the risk of a housing bubble due to relaxed credit norms. To prevent housing market bubbles, some regulators require higher contributions from home buyers in the form of equity. The dynamics of house prices in markets with higher owner equity requirements vary from high-leverage markets. The influence of wealth effects is examined using novel data sets. This research, documents in an emerging market context, the observations cited in low-leverage developed markets such as Germany and Japan.

This paper aims to clarify the effect of discount discrepancy (DD) on consumers’ purchase intention (PI). The authors propose, test and provide evidence and explanations about the moderation of justification in the relation between consumers’ perceived DD and PI.

The authors conducted three experimental studies with a 2 × 2 factorial design, focusing on consumers’ processing of price discounts. Participants were informed that this study aimed to gather opinions on fashion, clothing and retail sales promotions. They accessed the questionnaire via Qualtrics. Each participant took part in only one study. The experimental conditions were manipulated through scenarios.

Study 1 tested and supported the moderation of justification on the effect of DD on PI. Study 2 tested and supported the moderation of the type of justification for the effect of DD on PI. Study 3 confirmed the findings in Study 2 and revealed the more effective type of justification.

The authors focused on a typically hedonic product category (fashion clothing). Further research should include a wider variety of goods and services, which could lead to different explanations or generalizations.

Sales promotions must refrain from generating DD between the initial price discount and the subsequent smaller discounts. Practitioners must evaluate the gains of an initial, more considerable percentage discount to attract consumers to the store and sell them other products versus the cost of losing sales because of DD. Management should recognize the importance of giving the correct justification for perceived DD, aligning the firm’s justification with the consumer’s motivation to buy the product.

The authors offer subsidies for effective consumer protection policies.

By studying the influence of justification on the effect of DD on PI, the authors propose a mechanism that would reduce the negative effect of DD on consumers’ PI.

The purpose of this paper is to present a framework for the assessment of the fundamental value of house prices in the largest Ukrainian cities, as well as to identify the thresholds, the breach of which would signal a bubble.

House price bubbles are detected using two approaches: ratios and regression analysis. Two variants of each method are considered. The authors calculate the price-to-rent and price-to-income ratios that can identify a possible overvaluation or undervaluation of house prices. Then, the authors perform regression analyses by considering individual multi-factor models for each city and by using a within regression model with one-way (individual) effects on panel data.

The only pronounced and prolonged period of a house price bubble is the one that coincides with the Global Financial Crisis. The bubble signals produced by these methods are, on average, simultaneous and in accordance with economic sense.

The framework described in this paper can serve as a model for the implementation of a tool for detecting house price bubbles in other countries with emerging, small and open economies, due to adjustments for high inflation and significant dependence on reserve currencies that it incorporates.

A tool for measuring fundamental house prices and a bubble indicator for housing markets will be used to monitor the systemic risks stemming from the real estate market. Thus, it will help the National Bank of Ukraine maintain financial stability.

The framework presented in this research will contribute to the enhancement of the systemic risk analysis toolkit of the National Bank of Ukraine. Therefore, it will help to prevent or mitigate risks that might originate in the real estate market.

The authors show how to implement an instrument for detecting house price bubbles in Ukraine. This will become important in the context of the after-war reconstruction of Ukraine, with mortgages potentially becoming the main tool for the financing of the rebuilding/renovation of the residential real estate stock.

This paper aims to explore the relationship between prudence in risk attitudes and patience of time preference of Chinese apple growers regarding off-farm cold storage of production and marketing in non-harvest seasons. The authors also consider the effect of farmer participation in cooperative-like organizations known as Farm Bases (FBs).

The authors use multiple list methods and elicitation strategies to measure Chinese apple farmers' risk attitudes and time preferences. Because these farmers can either sell their apples immediately to supermarkets or intermediaries or place them in storage, the authors assess correlations between their storage decisions and their preferences regarding risk and time. The authors also differentiate risks involving gains and losses and empirically examine individual risk attitudes in different scenarios.

Marketing decisions are moderately associated with risk attitudes but not time preference. Farmers with memberships in local farmer cooperatives are likely to speculate more in cold storage. Thus, risk aversion behavioral and psychological motives affect farmers' decision-making of cold storage and intertemporal marketing activities. However, membership in cooperatives does not always result in improved income and welfare for farmers.

The research confirms that behavioral factors may strongly drive vulnerable smallholder farmers to speculate into storage even under seasonal and uncertain marketing volatility. There is the need to think deeper about the rationale of promoting cooperatives and other agricultural forms, because imposing these without careful consideration can have negative impacts.

Do risk and time preferences affect the decision of farmers to utilize storage facilities? This question is important because it is not clear if and how risk preferences affect the tradeoff between consuming today and saving for tomorrow, especially for farmers in developing countries.

The purpose of this paper is to analyse the association between farm/farmer characteristics and unsubsidized farm insurance premium expenditure in Ireland. The distribution of farm insurance expenditures is wide, and it is important to understand the extent to which individual factors influence demand for different levels of insurance premium.

The quantile regression approach and farm accountancy data from the Teagasc National Farm Survey are used to model the association between farm/farmer characteristics and farm insurance demand in Ireland.

Asset values (livestock, buildings and machinery) are positively associated with total insurance expenditure. Both forestry area and crop area are significantly associated with farm insurance expenditure with a stronger influence on the middle and upper part of the distribution. The interaction between farm income and farmer age is positively associated with insurance expenditure pointing to the importance of farm income protection.

The research is mainly concerned with insuring against substantive risks, which are capable of threatening the asset base and continuation of the farm business. Future research can integrate questions in relation to farm safety and farmer health with research on the economic survival of the farm business.

Farmers in Ireland adopt unsubsidized farm insurance as a risk management tool. This situation is relevant to other EU member states including Belgium, Denmark, Germany and Sweden. The findings can be used to inform stakeholders and policymakers about the relative impact of different factors on insurance expenditure.

Previous research has typically focused on the linear relationship between farm/farmer characteristics and insurance demand without accounting for variability across the size distribution. This research is based on the quantile regression approach where the association between farm/farmer characteristics and farm insurance expenditure can be assessed at different points of the distribution.

The purpose of this study is firm value management through corporate finance policy design and scenario analysis to maximize the firm value.

The study develops a system dynamics model for an oil firm and incorporates the financial and physical processes to perform the firm valuation. The model is simulated under the current and alternative investment, capital structure and dividend policies of the case firm, assuming different oil and gas price and tax rate scenarios to identify which combination of policies maximizes the firm value.

The simulation results suggest that lowering the volume of investments, increasing the debt ratio and reducing the dividend payments from the current level increases the share price, given increased oil and gas price expectations and lower tax rates. However, the total firm value outperforms with increased investments toward the end of the simulation period. In case of decreased oil and gas price expectations, lower volume of investments, lower debt ratio and lower dividend payments increase the share prices, given lower taxes.

This study entails significance as it provides a comprehensive financial planning model for an oil firm, which incorporates the complex interactions of key financial and physical processes of the firm. The study contributes to debates on corporate finance policies by integrating multiple theories, accounting for accumulation processes and feedback loops and their non-linear interactions. The study proposes the consideration of combined impact of policies for firm value management.