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The paper attempts to discuss the impact of reference price effect on pricing decisions.

With the growth of the Internet and e-commerce, more and more customers purchase products in through online channels and choose products by comparing different prices and services, and the reference price effect has an impact on pricing decisions. To investigate the impact of consumers' reference price effect on the dual-channel supply chain, the authors establish a basic model consisting of a single dominant manufacturer and a single downstream retailer, and analyze the optional decisions under different situations and discuss the influence of reference price effect. Finally, a number case verifies the validity and rationality of the proposed model.

The results show that (1) the reference price effect has varying effects on the price, channel demand and income of manufacturers and retailers in the channel depending on the role of customers' channel preferences. (2) The manufacturer's online channel demand and profits always increase with the reference pricing effect, whereas the retailer's offline demand and profits always decline. (3) When the proportion of consumers preferring offline is higher, the manufacturer's network price and wholesale price increase with the reference price effect, while the retailer's retail price decreases with the reference price effect; when the proportion of consumers preferring offline is lower, the opposite is true, and the centralized decision results are consistent with the decentralized decision results.

This paper can clarify the impact of consumer reference price effects on the operation of dual-channel supply chains, and help inform pricing decisions of manufacturers and retailers in dual-channel supply chains.

The proposed approach can well analyze the impact of consumer reference price effect and give channel their optional decisions.

This paper aims to model the price of cellar tours using a hedonic pricing approach. The authors analyze the complex relationship between the price of an add-on (here, cellar tours) and the price of the reference product (here, wine).

Thanks to a large database containing information on about 1,000 winery experiences, the authors regress the price of cellar tours on wine prices and on a broad set of objective characteristics that are (1) tour specific and (2) common to all tours offered by the winery. These exogenous controls include the type and style of experience offered, amenities and winemaking characteristics.

The authors show that the price of cellar tours follows the price of the most expensive wine sold by the winery, which is a proxy for reputation. The authors find that one of the main determinants of cellar tour prices is visit length: wineries charge more for longer experiences. The number of wines tasted during the visit also increases the price. Prices are higher in places where there is a high level of wine tourism activity, which might be a sign of authenticity.

Wine producers in different countries need to gain insights on how to price cellar tours, which are composite goods. The results can help practitioners price their winery experience according to common practices in different wine regions. The results may also be of interest to professionals in the tourism sector who are in charge of the pricing of by-products (e.g. tee-shirts, books, etc.), or for luxury fashion labels extending their brand in the catering industry with cafes and restaurants.

To the best of the authors’ knowledge, this paper is the first empirical analysis that examines the complex relationship between the price of an add-on and the price of the reference product in the context of wine tourism.

The 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.

This 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.

Our 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.

Few 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.

Brazil uses the dollar as a vehicle currency to invoice its exports. This fact produces a tendency toward equalizing the prices of products in dollars in the international market and reducing the ability of firms to practice pricing-to-market (PTM). This study aims to evaluate the hypothesis by estimating error correction models in panel data, obtaining estimates of PTM for 25 manufacturing products exported by Brazil between 2010 and 2020.

This study uses the correlated common effect estimator proposed by Pesaran (2006) and Chudik and Pesaran (2015b) to estimate the PTM coefficients.

Results of this study indicate that exporters practice local-currency pricing stability for dollar prices. This study obtains that Brazilian exporters tend to stabilize their dollar price for exports, reducing heterogeneity between destination markets. The results are in agreement with the hypothesis of the prevalence of the coalescing effect of Goldberg and Tille (2008) and lower sensitivity of the markup adjustment to the specific market, as pointed out by Corsetti et al. (2018). The pricing of Brazilian exports in dollars reflects a profit maximization strategy that considers an international price system based on global demand for products.

In addition to analyzing the dollar role in the pricing of Brazilian exports through the triangular decomposition, this study also shows the importance of examining the cross-section dependence of errors, considering the heterogeneous cointegration in export pricing models and producing PTM estimates for short-term and long-term.

The purpose of the paper is to construct a model that considers video purchase and then identifies the logical relationships implied by the parameters to explore video platform operation mechanisms.

The authors analyzed the video platform system using a mathematical modeling approach and numerical optimization techniques. Through pricing decisions, the authors obtained equilibrium results for the profitability of the video platforms and analyzed the favorable market factors. The authors then extended the model by analyzing the competitive strategies of the two video platforms in the market.

The authors find that advertiser profitability, ad nuisance, video sensitivity and video creator network effects are important factors influencing the pricing strategy of video platforms. During positive market conditions, video platforms tend to lower their prices until they absorb enough users. As market conditions change, the price adjustment strategies of video platforms are affected by parameter changes and inter-parameter relationships.

The study considers the network effects of video creators, which provides a realistic reference for scholars and managers. In addition, the authors consider the bargaining power of platforms when purchasing content. The authors provide a fresh perspective for scholars while filling a gap in the field as video platforms can acquire a portion of the content on the market by setting a purchase price.

With the rise in wine consumption, accurate wine price forecasts have significantly impacted restaurant and hotel purchasing decisions and inventory management. This study aims to develop a precise and effective wine price point and interval forecasting model.

The proposed forecast model uses an improved hybrid kernel extreme learning machine with an attention mechanism and a multi-objective swarm intelligent optimization algorithm to produce more accurate price estimates. To the best of the authors’ knowledge, this is the first attempt at applying artificial intelligence techniques to improve wine price prediction. Additionally, an effective method for predicting price intervals was constructed by leveraging the characteristics of the error distribution. This approach facilitates quantifying the uncertainty of wine price fluctuations, thus rendering decision-making by relevant practitioners more reliable and controllable.

The empirical findings indicated that the proposed forecast model provides accurate wine price predictions and reliable uncertainty analysis results. Compared with the benchmark models, the proposed model exhibited superiority in both one-step- and multi-step-ahead forecasts. Meanwhile, the model provides new evidence from artificial intelligence to explain wine prices and understand their driving factors.

This study is a pioneering attempt to evaluate the applicability and effectiveness of advanced artificial intelligence techniques in wine price forecasts. The proposed forecast model not only provides useful options for wine price forecasting but also introduces an innovative addition to existing forecasting research methods and literature.

This study highlights the impact of mental accounts on a user's decision-making regarding payment schemes and aims to determine the pricing strategy for the first-enjoy-after-pay service offered by the two-sided media platforms.

This study establishes a game-theoretic model and utilizes backward induction to derive the equilibrium price by maximizing the monopolist's profit.

The findings indicate that the conditions for a two-sided media platform to offer the first-enjoy-after-pay service depend on the trade-off between pleasure attenuation and pain buffering and the effect of time discounts. Moreover, the authors found that the time discount is a critical factor in determining pricing strategies under various payment schemes offered by the platform.

This work adopts a uniform pricing strategy for users who opt for either immediate or post-payment schemes. Nevertheless, it is important to note that this approach has limitations in terms of offering discriminatory pricing for those who choose both payment schemes.

This analytical work provides valuable insights for two-sided media platforms to optimize their payment scheme strategies and pricing considering the influence of a user's mental account.

In a two-sided media platform, the authors provide applicable conditions for the platform to offer first-enjoy-after-pay service considering the effect of mental accounts. Further, the authors show the optimal pricing strategy under different payment schemes provided by the platform.

This study proposes a model that influences customer citizenship behavior during COVID-19, and empirically tests the effects of fast-food restaurant customers' perceptions of justice (price and procedural justice) on trust; trust on satisfaction and loyalty; and trust, satisfaction and loyalty on customer citizenship behavior. Furthermore, it was questioned whether there was a disparity between customer expectations based on the restaurant's image and consumption experience.

The data were gathered from customers of fast-food restaurants in the shopping centers in Turkey. The data set, which included 437 valid questionnaires, was subjected to CFA for validity and reliability, SEM analysis for hypothesis and paired sample t-Tests for the research questions.

The findings of the study indicate that perceived justice affects customer trust, which, consequently, affects customer loyalty and satisfaction during the COVID-19 period. Findings also demonstrate that, while customer loyalty and trust increase customer citizenship behavior, customer satisfaction alone is insufficient to increase customer citizenship behavior. The study also shows that during the COVID-19 period, fast-food restaurants should have raised awareness of employees’ fair behaviors toward the customers and provided additional services to differentiate themselves in the market. Also, it indicates that customer expectations related to price, cleanliness and professional appearance of staff are not met after taking service.

No research has been found in the literature focusing on the expectations, justice, trust, satisfaction, loyalty and citizenship behaviors of fast-food restaurant customers in the COVID-19 pandemic process. Therefore, the results can fill the gap in relevant literature by testing the relationships between justice, trust, satisfaction, loyalty and citizenship during the pandemic and provide inferences for fast-food business owners.

The purpose of this study is to provide an optimal joint strategy of multi-period pricing and sales effort for a retailer with a logit choice demand in an integrated channel.

Customer demand is characterized by a logit choice model, it varies over time and is influenced by price and sales effort. The multi-period decision model for the retailer is constructed using a discrete-time dynamic programming method to determine the optimal price and sales effort in each period.

When the inventory level does not exceed a certain threshold, decreasing price and increasing sales effort over time or as inventory level increases are the optimal strategies. However, once the inventory level exceeds the threshold, the optimal strategy is to maintain both price and sales effort constant as the inventory level changes or to increase price and decrease sales effort over time. Additionally, the greater the influence of sales effort on demand or the higher the arrival rate of customers, the higher the optimal price and the greater the optimal sales effort level.

This study contributes to the existing research on dynamic pricing and sales effort in integrated channels by incorporating a logit choice model. Furthermore, it provides valuable management insights for retailers operating in an integrated channel to make pricing and sales effort decisions based on inventory level and time period.

Pay-what-you-want (PWYW) is a pricing strategy implemented in a variety of settings like supermarkets and museums, in which consumers determine the price they are willing to pay for a product or service based on their perceived utility. The authors propose an analytical model to investigate the impact of PWYW delivery pricing on the online food delivery (OFD) platforms.

Using a game-theoretic model, the authors characterize the equilibrium as a function of the platform's average delivery cost and the consumer's social preferences parameters like fairness and reciprocity. The authors derive the parametric conditions under which PWYW generates higher profits for the platform compared to the traditional pay-as-asked delivery pricing.

For the PWYW strategy to be profitable, the average delivery cost to the platform should be low. Therefore, OFD platform managers should focus on reducing delivery costs. The authors also identify the feasible region in which the platform managers need to maintain the consumer's social preferences.

Under PWYW, the authors recommend that the platform managers impose a minimum delivery fee which consumers can use as a benchmark to minimize zero delivery fee payments and consumers' free-riding tendencies simultaneously. This allows OFD platforms to extract online orders from highly price-conscious consumers.

This is one of the first studies to explore the innovative application of PWYW to a particular segment of delivery pricing in OFD platforms. The authors establish that the overall consumer surplus and social welfare are higher under the PWYW strategy, forming a solid ground for its implementation in OFD platforms.