Price Preferences Research Articles

Helping hampered bidders—Do subsidy auctions work as intended?

AbstractThe use of preference or discriminatory auctions, where one class of bidders is offered favored treatment over another class, has received mixed attention in the literature. Research has shown there is often an economic benefit of such policies in procurement auctions thanks to lower costs for buyers as incentives are offered to disadvantaged sellers. In this paper, we study one type of preferential procurement auction: the subsidy. Using a set of controlled experiments, we compare actual bidder behavior to what is predicted in equilibrium and find consistent (but overly aggressive) patterns overall. By testing a common bid strategy assumption, we also identify a behavioral framing bias that may trap sellers in these suboptimal strategies. Finally, we compare subsidies to another common discriminatory mechanism—the price preference—and find evidence that buyers interested in increasing the welfare of disadvantaged sellers should use subsidies instead of price preference auctions, thanks to a surprising difference in outcomes between preference types. Due to the wide use of bid preference auctions to support both policy and social aims, our findings have both financial and societal implications.

Analysis of Consumer Preferences for Used Cars Using K-Means Clustering as a Basis for Building Business Actions

Transportation is a crucial aspect of modern mobility, enabling the movement of goods and individuals. Private vehicles, such as motorcycles and cars, are the dominant choice for many due to their convenience and practicality. However, with numerous car options, consumers often struggle to select used cars that match their needs and preferences. In this research, data mining is employed to cluster used cars based on consumer preferences for price, rating, and performance using the K-Means Clustering algorithm. The data consists of used car information from various sources. The K-Means algorithm groups the cars into clusters based on price, rating, and performance criteria. The results reveal three consumer groups with different preferences in these areas. This information provides valuable insights for consumers to make informed decisions and offers guidance to the automotive industry for designing more effective business actions.

Electric bike sharing: Price sensitivity and pricing preferences

In order to attract the highest possible number of users, municipal authorities and operators of bike sharing systems (BSS) often set very low prices for their services. This frequently results in non-profitability or dependency on public funding. Furthermore, low prices may discourage customers who are concerned regarding the quality of services. In our study, we investigate the impact of socio-demographic characteristics and travel habits on price sensitivity for an e-bike sharing system. We use Van Westendorp's price sensitivity meter (PSM) and the general linear model (GLM) to determine differences in optimal prices for various users and types of BSS. We find that optimal prices may be higher than the ones fixed by authorities and that discounts for female and younger users may result in higher demand for BSS. Moreover, car users are willing to pay less for a BSS than people who never use a car.

Signaling through timing of stock splits

We develop a dynamic structural model of stock splits, in which managers signal their private information through the timing of the split decisions. Our approach is consistent with the empirical evidence which shows that the majority of stock splits have a 2:1 ratio of old-to-new shares, but are announced at various pre-split price levels. Moreover, it explains why split announcement returns are decreasing with the pre-split price. In addition, by matching the model to the data, we estimate the nominal share price preferences of investors and decompose the split announcement return into the value of new information and the signaling cost.

Another look at the price clustering behavior: evidence from the Muscat stock exchange

PurposeThe price clustering behavior is becoming a core part of the market efficiency theory especially with the development of trading strategies and the occurrence of major and unprecedented shocks which have led to severe inquiry regarding asset price dynamics and their distribution. However, research on emerging stock market is scant. The study contributes to the literature on price clustering by investigating an active emerging stock market, the Muscat stock market one of the Arabian Gulf Markets.Design/methodology/approachThis research adopts the artificial intelligence technique and other statistical estimation procedure in understanding the price clustering patterns in Muscat stock market and their main determinants.FindingsThe findings reveal that stock prices are marked by clustering behavior as commonly highlighted in the previous studies. However, we found strong evidence of price preferences to cluster on numbers closer to zero than to one. We also show that the nature of firm’s activity matters for price clustering behavior. In addition, firms with traded bonds in Oman market experienced a substantial less stock price clustering than other firms. Clustered stock prices are more likely to have higher prices and higher volatility of price. Finally, clustering raised when the market became highly uncertain during the Covid-19 crisis especially for the financial firms.Originality/valueThis study provides novel results on price clustering literature especially for an active emerging market and during the Covid-19 pandemic crisis.

Harms of inconsistency: The impact of user-generated and marketing-generated photos on hotel booking intentions

User-generated photos (UGPs) and marketer-generated photos (MGPs) play a crucial role in reducing uncertainty during hotel booking. However, inconsistencies between these two sources of information can lead to negative consequences. This study employs the elaboration likelihood model (ELM) and Cognitive Dissonance Theory to construct two paths through which inconsistent information from UGPs and MGPs affects hotel booking intention, validated through a study with four contextual experiments involving 810 participants. Inconsistent information significantly negatively impact hotel booking intention. Perceived risk and negative emotions mediate the inconsistent effects of content and color, respectively. When price preferences are high (vs. low), the effect of inconsistent information on booking intentions is stronger. Furthermore, tourists with hedonic (vs. utilitarian) motives are less tolerant of inconsistent information. This study contributes significantly to the theoretical framework of online marketing and emphasizes the importance of considering the impact of inconsistent information on tourists in practical marketing activities.

Understanding consumers to inform market interventions for Singapore's shark fin trade

Abstract Sharks, rays and their cartilaginous relatives (Class Chondrichthyes, herein ‘sharks’) are among the world's most threatened species groups, primarily due to overfishing, which in turn is driven by complex market forces including demand for fins. Understanding the high‐value shark fin market is a global priority for conserving shark and rays, yet the preferences of shark fin consumers are not well understood. This gap hinders the design of evidence‐based consumer‐focused conservation interventions. Using an online discrete choice experiment, we explored preferences for price, quality, size, menu types (as a proxy for exclusivity) and source of fins (with varying degrees of sustainability) among 300 shark fin consumers in Singapore: a global entrepôt for shark fin trade. Overall, consumers preferred lower priced fins sourced from responsible fisheries or produced using novel lab‐cultured techniques. We also identified four consumer segments, each with distinct psychographic characteristics and consumption behaviours. These preferences and profiles could be leveraged to inform new regulatory and market‐based interventions regarding the sale and consumption of shark fins, and incentivize responsible fisheries and lab‐cultured innovation for delivering conservation and sustainability goals. In addition, message framing around health benefits, shark endangerment and counterfeiting could reinforce existing beliefs among consumers in Singapore and drive behavioural shifts to ensure that market demand remains within the limits of sustainable supply. Read the free Plain Language Summary for this article on the Journal blog.

New Retail Research of Korean Fresh Products in the Post-COVID Era- - Take Coupang Rocket Delivery as an Example

Premised on the growth of e-commerce industry and increased consumer income leve ls in South Korea, the consumer preferences has a significant change.This transformation is marked by a transition from mere price preferences to a focus on product quality. Consumers are no longer content with merely seeking affordability; instead, they now demand superior product quality and efficient logistics. Leveraging a robust infrastructure and a well-developed logistics network, South Korea has pioneered a novel retail model that blends online and offline elements, prominently exemplified by the Coupang Rocket Delivery system. With individuals seeking isolation and risk reduction during the COVID-19 pandemic , the model of Rocket Delivery has fostered exceptional growth. In this new paradigm, Coupang emerges as the quintessential representative of South Korea's network-driven retail enterprises, adapting swiftly to the evolving circumstances. The post-pandemic scenario forecasts even deeper convergence of online and offline operations for e-commerce enterprises. To navigate the challenges of this new retail era, an adept utilization of modern logistics, artificial intelligence, and other advanced technologies is imperative.

Optimization of Train Timetables in High-Speed Railway Corridors Considering Passenger Departure Time and Price Preferences

Optimization of Train Timetables in High-Speed Railway Corridors Considering Passenger Departure Time and Price Preferences

An Empirical Assessment of Factors Impacting Stock Prices of Nepalese Commercial Banks

This study examines the impact of various financial variables on the pricing of commercial banks in Nepal. Key financial metrics analyzed include earnings per share, dividend yield, price-toearnings (P/E) ratio, earnings yield, book value per share, money supply, market-to-book value ratio, and stock return. The research highlights the importance of market financial ratios in the investment decisions of Nepalese investors. Using data from 10 out of 20 commercial banks listed on the Nepal Stock Exchange, spanning 110 yearly observations from fiscal years 2012/13 to 2022/23, multiple regression models were employed to determine the relationships between these factors. The findings reveal that earnings per share, dividend yield, P/E ratio, book value per share, money supply, market-to-book value ratio, and stock return are significantly positively correlated with the prices of commercial banks. Conversely, earnings yield shows a negative correlation. Despite the strong preference for price and profitability metrics, the study's limited sample size and focus on commercial banks may affect the generalizability of the results. This research provides critical insights, particularly emphasizing the importance of earnings per share, dividend yield, P/E ratio, and book value per share in guiding investors' financial decisions in Nepal. The findings are anticipated to benefit investors, scholars, policymakers, and other stakeholders by enhancing their understanding of the factors influencing stock prices in the Nepalese banking sector.

Bi-preference Learning Heterogeneous Hypergraph Networks for Session-based Recommendation

Session-based recommendation intends to predict next purchased items based on anonymous behavior sequences. Numerous economic studies have revealed that item price is a key factor influencing user purchase decisions. Unfortunately, existing methods for session-based recommendation only aim at capturing user interest preference, while ignoring user price preference. Actually, there are primarily two challenges preventing us from accessing price preference. First, the price preference is highly associated to various item features (i.e., category and brand), which asks us to mine price preference from heterogeneous information. Second, price preference and interest preference are interdependent and collectively determine user choice, necessitating that we jointly consider both price and interest preference for intent modeling. To handle above challenges, we propose a novel approach Bi-Preference Learning Heterogeneous Hypergraph Networks (BiPNet) for session-based recommendation. Specifically, the customized heterogeneous hypergraph networks with a triple-level convolution are devised to capture user price and interest preference from heterogeneous features of items. Besides, we develop a Bi-Preference Learning schema to explore mutual relations between price and interest preference and collectively learn these two preferences under the multi-task learning architecture. Extensive experiments on multiple public datasets confirm the superiority of BiPNet over competitive baselines. Additional research also supports the notion that the price is crucial for the task.

Effect of consumers’ materialistic values on consumption guilt as reflected in price preferences

ABSTRACT While simplistic arguments portend a possible relationship between consumers’ materialistic values and consumption guilt, empirical evidence in this regard, however, remains equivocal at best. In this paper, we address this issue by establishing the effect of materialism on consumption guilt – delimited by regulatory influence (promotion/prevention) – as reflected in consumers’ relative preferences for structurally distinct but financially equivalent price alternatives. Specifically, we conduct an experiment with consumers’ trait materialistic values, measured as a continuous variable, as an independent variable, with extraneous social influence as a two-level (promotion/prevention) manipulated moderator, consumption guilt as the mediating variable, and consumers’ relative price preference (as mentioned above) as the dependent variable of choice. Subsequently, we conduct a regression analysis, followed by a floodlight analysis, and, a series of mediation analyses, including a mediated moderation analysis, in establishing the effect of materialism on consumption guilt. Our results indicate that consumers higher/lower in materialism, both experienced consumption guilt. Subsequently, these consumers mitigated consumption guilt by preferring the price structure that best allowed them to do so in consummating the purchase of a new product – the mediating effect of consumption guilt. Our findings imply indirect price-discrimination opportunities for sellers, wherein demand for products increases as consumers (self) mitigate consumption guilt through price preferences, irrespective of their dominating materialistic tendencies. In summary, herein, we empirically establish the long-conjectured relationship between materialism and consumption guilt, unequivocally, both for consumers high, or low, in materialism.

Analysis of Consumer Decision-making from the Perspective of Anchoring Effect

The anchoring effect is a kind of heuristic deviation. When people make judgments about someone or something, they are easily dominated by the first impression or the first information, which is like an anchor sinking into the sea to fix people's thoughts somewhere. This paper analyses the fluctuation of inflation rate, the reduction of interest rate, and the change of COVID-19 policy in China in recent years. Consumers' price preferences are anchored by past prices, which prevents them from accurately predicting future price changes. If consumers believe that prices will remain the same in the future, they will use the current price as a benchmark for future prices, and they will base their consumption decisions on this price. However, if the price changes in the future, consumers will be priced wrong, so they will make wrong consumption decisions. Because of the anchoring effect, people have impulsive consumption, retaliatory consumption, and conservative consumption. In order to reduce the negative impact of the anchoring effect on the economy, this paper suggests that people should be fully aware of the market price, make reasonable expectations of inflation, avoid impulse consumption and retaliatory consumption.

The Endowment Effect in China Rural Land and Property Market

To evaluate how the endowment effect be the obstacle in the agricultural and property market and to find key factors which have impact on endowment effect, this article re-defined what the endowment effect is in rural-land property market, which is mainly focus on how the decision-maker establish choices and evaluates the worth of the deals they hold. Then, this paper studies the phenomenon of price preference among supply and demand-side of farmland and property market in the application of Shaanxi province. Third, this paper exams the Chengdu's villagers voluntarily and compensation of the withdrawal from rural homesteads (WRH) with the obvious conflict between supplying and demanding of urban and agricultural building land resources. Based on the re-definition and main applications, this paper indicates that the key factors which affect the endowment effect includes emotional ties, degree of substitution of goods as well as products, income levels, price preferences on the demand sides as well as supply sides of the land market, perceived risk evaluation of future income situation, forecasted risk of the stability of the rural land property rights, the labour situation among various types of farmers, age, membership in cooperatives and whether there is a local intermarriage or not. This paper will also critically examine how endowment effect influence supply and demand relationships in the land and property markets, how the government might issue directives or create policies to support or discourage endowment effect in the farmland market and how to establish the innovation of "three rights of separation" in the land market. The potential remedies and suggestions are provided.

Debunking True Purchase Price Limits in Teenagers

This project aims to explore whether or not the endowment effect, a concept in behavioral economics, holds true for adolescents, since this population has not been studied before. The endowment effect occurs when there is a gap between a buyer’s willingness to pay (WTP) and a seller’s willingness to accept (WTA) at a certain price. A WTA:WTP ratio equal to 1 would exhibit traditional economic rationality, and a ratio above 1 would exhibit the endowment effect. This study used survey research in the form of having participants explicit state prices, to investigate how the WTA-WTP discrepancy, a measurement of the endowment effect, varies across economic goods and survey procedure (or how survey questions were worded). The final conclusion that can be drawn from this paper is that high school students exhibit the endowment effect only for durable goods (shoes and electronics), and exhibit the reverse trend of the endowment effect for perishable goods (food and beverage). Additionally, the survey procedure and socioeconomic status were not a contributing factor to the endowment effect. These results, which differ from previous literature regarding the endowment effect, emphasize the increased importance of studying teenage purchasing pricing preferences, compared to prior studies that focused solely on undergraduate business students.

Price-aware enhanced dynamic recommendation based on deep learning

Price is one of the essential elements influencing consumer purchase behavior. Like consumers’ preferences in products, their price preferences also dynamically change over time. However, dynamic price preferences haven’t been fully considered in existed recommendation studies. In this study, we propose a deep learning-based dynamic recommendation model by considering consumers’ dynamic preferences in both product and price. We specially design a review-and-rating-based sequence generator to select products whose prices the consumers are satisfied with to form the new purchase sequence. We also develop a multi-level attention mechanism in the transformer layer to explore the correlations between consumers’ price choices and to combine the price preferences with the product preferences. Experimental results show the proposed model outperforms the state-of-the-art models on some real-world datasets. Our findings can help retailers understand consumers’ price preferences and make informed decisions related to pricing, discounting, and bundle sales strategies.

Research on Enterprise R&D Strategy of Product-Service Innovation Guided by Quality Preference

Research and development (R&D) plays a crucial role in reducing enterprise costs and enhancing competitiveness in the market. Customers’ quality preference for product-service is a key driver of enterprise sales. Consequently, studying R&D investment strategies holds significant research value. This paper aims to provide a comprehensive analysis of the relationship between customers’ quality preference for product-service, R&D investment, and product-service price. To achieve this, we improve the Stackelberg game model to consider these factors and use numerical simulation to investigate the optimal R&D strategy. Results show that an enterprise’s absorptive capacity positively influences its market demand and profit, while negatively impacting its competitors. A higher customers’ quality preference coefficient indicates a stronger competitive advantage. Moreover, implementing a non-cooperative R&D strategy not only helps enterprises expand their R&D investment scale and accumulate knowledge and technology, but also plays a positive role in increasing sales volume and profits. We suggest that enterprises should focus on improving their absorptive capacity and diversifying R&D strategy, while also considering customers’ quality preferences and market demand when making R&D investment decisions. Careful consideration should be given to the pros and cons of cooperative and non-cooperative R&D strategies to choose the most suitable approach.

The Navajo Nation Healthy Diné Nation Act: Community Support of a 2% Tax on Unhealthy Foods.

The Healthy Diné Nation Act (HDNA) of 2014 included a 2% tax on foods of little-to-no-nutritious value ("junk foods") on the Navajo Nation. The law was the first ever in the United States and any Indigenous nation worldwide with a population at a high risk for common nutrition-related conditions. To date, research on community support for food tax legislation among Indigenous nations is entirely lacking. To assess the extent of support for the HDNA and factors associated with support including sociodemographic variables, knowledge of the HDNA, nutrition intake, and pricing preferences. Cross-sectional survey. The Navajo Nation. A total of 234 Navajo Nation community members across 21 communities. The percentage of participants who were supportive of the HDNA. Participants were 97% Navajo, on average middle-aged, 67% reported an income below $25 000 annually, and 69.7% were female. Half of the respondents said they "support" (37.4%) or "strongly support" (13.0%) the tax, while another 35% of people said they were neutral or somewhat supportive; 15% did not support the tax. Participants with higher income ( P = .025) and education ( P = .026) and understanding of the legislation ( P < .001 for "very well" vs "not at all") had increased odds of greater support, as did people who believed that the HDNA would make Navajo people healthier (vs not, P < .001). Age, gender, language, and reported nutrition intake (healthy or unhealthy) were not associated with HDNA support, but participants willing to pay 5% or 12%-15% higher prices for fast food and soda had increased odds of greater support ( P values range from .023 to <.001). The majority of Navajo community members surveyed were moderately supportive of the Navajo Nation tax on unhealthy foods. Higher income and education and understanding of the law were associated with greater support, but nutrition intake was not.

Assessment of willingness-to-pay for bio-based fertilisers among farmers and agricultural advisors in the EU

Modern agricultural systems heavily depend on replenishing nutrients in the soils via mineral fertilisers. However, the extensive use and production of mineral fertilisers lead to adverse environmental effects. Furthermore, the raw materials used for the production of mineral fertilisers are unevenly distributed in the world and are susceptible to price fluctuations on the international market. A more circular solution is needed to ensure the sustainable supply of nutrients for agriculture in Europe. Bio-based fertilisers (i.e. fertilisers recycled from various waste streams while avoiding the use of fossil resources) can be a solution. The transition requires significant marketing efforts, but there is very little information on pricing preferences for newly developed bio-based fertilisers. This article aims to fill the gap by performing analyses of willingness-to-pay and price sensitivity using the Van Westendorp pricing technique and its extended version. Our analyses exemplified how the Van Westendorp methodologies can be used to generate insights into the price sensitivity of farmers and agricultural advisors in the EU. The selected methodologies allowed us to consider the ‘revenue vs. market share’ trade-off and thus distinguish the prices that are needed to gain the largest product market share and the prices that are needed to maximise the revenue from the products. Our results suggest that the price for a bio-based fertiliser at the 30–46% discount compared to the price of an equivalent mineral fertiliser would allow to maximise the market share of the product. Yet, to maximise the revenue the prices can be set equivalent to the ones of the mineral fertilisers. Combined with benchmarking studies and technical economic assessments our results contribute to the understanding of the key aspects needed for the development of marketing strategies and business case analyses for newly introduced products, such as bio-based fertilisers.

Dynamic analysis of dual-market low-carbon supply chain: Considering government intervention and joint promotion

The increasingly severe global environmental problems have urged most people to incorporate environmental protection into their daily lives. Therefore, low-carbon supply chain management has become crucial. This paper studies a dual-market low-carbon supply chain operation in urban and rural markets with one manufacturer and two retailers. Three scenarios are considered: no government intervention, government intervention and joint promotion under government intervention. By establishing and solving three differential game models, we give the dynamic technological innovation, advertising and store promotion strategies of the manufacturer and two retailers and show the impact of government intervention and joint promotion on emissions reduction and performance. The results show that: first, government intervention can increase technology innovation efforts and decrease advertising efforts, while joint store promotion under government intervention has a positive effect on manufacturer's advertising and technological innovation efforts; second, government intervention may increase the profits of the manufacturer, although it will undoubtedly reduce the profits of the retailers, while joint store promotion under government intervention can further improve the profits of the manufacturer and retailers; third, compared to the preferences of rural consumers, manufacturer's technological innovation strategy relies more on the price and promotion preferences of urban consumers. Moreover, the preference differences between the two types of consumers have a weak impact on the manufacturer's advertising strategy, while the price preference of rural consumers has a more significant impact on the advertising efforts of the manufacturer. Overall, the research results can provide valuable suggestions for the members of the low-carbon supply chain in the dual market to improve the economic and environmental performance of the low-carbon supply chain.