Choice Of Price Research Articles

Simulation of the Stackelberg–Hotelling Game

This work studies the Hotelling game with sequential choice of prices, that is, the Stackelberg–Hotelling (SHOT) game. The game is studied through numerical simulation, which provides the subgame perfect equilibrium solution not only in the unrestricted game but also in the game with reservation cost and with elastic demand. The simulation technique is tested first in the unconstrained game, where the analytical subgame perfect equilibrium solution was already known. Then, the numerical procedure is generalized to cope with the SHOT game with reservation cost and with elastic demand. These enriched formulations of the SHOT game have not been studied so far, so this article provides an exploratory study of them.

Targeted therapies and conventional care for the treatment of ankylosing spondylitis in China: a cost-effectiveness analysis based on the network-meta analysis

ObjectiveThis study aimed to evaluate the long-term cost-effectiveness of conventional care (CC) and seven first-line targeted therapies marketed in China for the treatment of patients with ankylosing spondylitis (AS)–namely secukinumab, ixekizumab, infliximab, etanercept, adalimumab and golimumab and tofacitinib–from the perspective of the Chinese health care system.MethodsThe York model was structured as a 12-week decision tree leading into two Markov models. This study set 1 year as a recurring cycle and a lifetime timeframe for the model. Primary model outcomes included the costs in Chinese yuan (CNY), health outcomes in quality-adjusted life-years (QALYs) and the incremental cost-effectiveness ratio (ICER) under a willingness-to-pay threshold of ¥89,358 (equal to the per capita gross domestic product in China in 2023) per QALY. Parameters in the York model were captured from network meta-analyses and literature including treatment response, short-term disease progression, patient functioning and long-term structural disease progression. Utilities are dependent on indicators such as the BASDAI score, the BASFI score, gender and age. Drug prices were analysed using the median price of the Chinese market from YAOZH net in the basic analysis. Costs and outcomes were discounted at 5.0%. We performed deterministic and probabilistic sensitivity analyses to investigate the robustness of the results. The prices of original drugs and generic drugs were used in the scenario analysis.ResultsCompared with CC, the ICER of golimumab was ¥104,217.4/QALY, which is between 1 and 3 times the GDP per capita, while the ICERs of the other six targeted therapies were less than ¥89,358/QALY. The specific economic rank of the targeted therapy was as follows:secukinumab > ixekizumab > tofacitinib > infliximab > etanercept > adalimumab > golimumab. Treatment response rates such as the BASDAI50, changes in the BASDAI/BASFI scores and the discounting rate were key model drivers. According to the scenario analysis, IL-17 inhibitors were still the most economical intervention when original drugs and generic drugs were used.ConclusionTargeted therapies are cost-effective treatments for AS. Overall, IL-17 inhibitors were the dominant treatment. The choice of the brand-new prices or generic drug prices can greatly affect economics.

Marketing mix analysis of JOSS organic rice based on consumer acceptance

Abstract The Special Region of Yogyakarta has the potential to develop organic rice, both from organic rice production and the organic rice market. JOSS Organic Rice is a superior organic rice product in the Special Region of Yogyakarta because it is a pilot project in the Kulon Progo Regency Government program. This research aims to analyze consumer preferences and marketing strategies based on the marketing mix for JOSS (Jatisarono Organik Sehat Sejahtera) Organic Rice market in Yogyakarta. Consumer preferences refer to people or groups’ personal likes, desires, and tendencies when they choose between various goods, services, or experiences. Marketing mix consists of four attributes, there are attributes product, price, place and promotion. Marketing mix analysis is carried out using descriptive analysis, using a combination of primary and secondary data analysis methods to identify factors that influence the analysis of each variable in the marketing mix. Primary data was obtained through direct surveys of consumers, while secondary data was obtained from previous research, regional statistical data and company data. The result of research shows that consumer preferences for JOSS organic rice are still dominant in product attributes and affordable price attributes. Based on marketing mix analysis, it shows that organic rice consumers in the DIY region prefer product attributes that have a bright white bright white color with total 36 consumers (76.6%) and rice which has a high level of rice integrity with total 44 consumers (93.6%). Place attributes of rice are easy to get in shops and supermarkets. Affordable price attributes and many price choices according to packaging weight. Organic rice is placed at the introductory stage in the product life cycle. It is hoped that the results of this research will provide important insights for JOSS Organic Rice producers and other organic rice business actors to pay more attention to the current condition of their products so they can implement more effective and sustainable marketing strategies to support growth. organic rice industry in the Special Region of Yogyakarta.

Location and Price Competition on a Uniform Path with Different Pricing Policies

AbstractThis paper models duopolistic competition between an online retailer and a physical store retailer with the online retailer modelled as a firm with uniform delivered pricing policy and the physical store as a firm with a mill pricing policy. Both firms seek to maximize their respective profits through an appropriate choice of location and price. The market is assumed to be given by a “uniform path” - a tree whose node weights and arc lengths are equal. Modelling reality, we consider two alternate types of transportation costs faced by the online retailer: either dependent on the relative location of the firm and a customer or independent of it. Beginning with the framework of a Stackelberg, i.e., sequential game, optimal location and price strategies are analytically derived for both sequences of market entry by the two competitors. Cases in which the leader faces the first entry paradox or can become a monopolist by strategically deterring entry by the follower are delineated. Thereafter, Nash Equilibrium solutions to the simultaneous game are identified. Salient insights from the results include: (a) the competitive pressure faced by the physical store in the presence of online competition (b) the inability of an online retailer to compete in “large” markets under the first type of transportation cost and (c) the advantage to the physical retailer of being a market leader.

Strategic Recommendation: Revenue Optimal Matching for Online Platforms (Student Abstract)

We consider a platform in a two-sided market with unit-supply sellers and unit-demand buyers. Each buyer can transact with a subset of sellers it knows off platform and another seller that the platform recommends. Given the choice of sellers, transactions and prices form a competitive equilibrium. The platform selects one seller for each buyer, and charges a fixed percentage of prices to all transactions that it recommends. The platform seeks to maximize total revenue. We show that the platform's problem is NP-hard, even when each buyer knows at most two buyers off platform. Finally, when each buyer values all sellers equally and knows only one buyer off platform, we provide a polynomial time algorithm that optimally solves the problem.

Digital Apparel Try-Ons: A Technological Odyssey into the World of Virtual Dressing Rooms and Consumer Engagement

This individual can now enjoy internet shopping whenever they want and from anywhere in the world thanks to the invention of smartphones and tablets. Online shopping has unquestionably taken the place of conventional methods for purchasing apparel and daily necessities. People benefit from a reputation as they pick internet buying. Almost all online retailers offer payment on delivery, free shipment, and special rates these days. These internet merchants have eliminated the hassles of parking, stuck in traffic, and standing in line to make purchases. They have also helped folks who consistently lament their lack of time. This is the primary justification for why most consumers now shop online. They may easily access a wide choice of affordable prices here, and they also get quick customer service and free home delivery. There is no denying that these are a few of the alluring aspects that draw customers in. Even though there is a minor problem that can make people lose interest in online buying, they might not be able to try on garments in such situations. By establishing a virtual changing room setting, the aim is to improve accessibility and time efficiency for trying on clothing. Our proposed methodology consists of three main components: skin color recognition, model alignment, and user image extraction from the video stream. Through user extraction, we may create an augmented reality environment by taking the user area out of the video stream and superimposing it on top of a simulated world within the user interface. To match the 2D cloth models with the use of scaling, rotation, and positioning using the 3D locations of the joints.

Do Attractive People Get a Better Deal? An Experimental Study

The goal of our research is to shed light on the existence of an effect of seeing the images of human faces (i.e. “a face effect”) on economic decision-making behavior. We conduct a series of controlled experiments using photographs of human faces in a newsvendor setting. Our experimental data provides evidence that the human face plays the role of an environmental moderator which triggers and intensifies the social considerations. To gain a deeper understanding of behavioral responses, we examined the impact of faces with varying characteristics, with a particular focus on the effects of facial attractiveness and perceived gender. We find that the decision-makers systematically deviate from their choices of wholesale prices when they imagine seeing the counterpart’s face. To explain how facial attractiveness and gender affect the decision choices, we develop a behavioral model that incorporates altruistic and fairness concerns.

HOUSING MARKET DISCOUNT RATES: EVIDENCE FROM BARGAINING AND BIDDING WARS

AbstractWhen selling a home, through the choice of the list price, sellers make a trade‐off between achieving a quick sale at a low price or waiting for higher bids. This list‐price setting decision is governed by a discount rate. Using data on housing sales in the Netherlands, we derive gross discount rates under bilateral bargaining and bidding wars. The estimated discount rates are 25%–35%, which are considerably higher than long‐run housing market discount rates and may result from the seller's unfamiliarity with the selling process. The rates are higher for sellers that already moved and have a low education.

Auction timing and market thickness

A seller faces a pool of potential bidders that changes over time. She can delay the auction to have a thicker market later on. The seller imposes static distortions (through her choice of reserve prices) and dynamic distortions (through her choice of market thickness). Under a condition on types that generalizes increasing hazard rates, we show that (i) regulating only static distortions can harm efficiency; (ii) when regulating only dynamic distortions, a social planner should reduce market thickness; (iii) if a planner can affect both types of distortions, she should still choose a lower market thickness than the seller, i.e., market thickness is inefficiently high; (iv) the extent of timing disagreement between the seller and a social planner is higher when they both have to use an efficient auction than when they both have to use an optimal one.

Exploring which factors impact restaurant willingness-to-pay by menu course

ABSTRACT While hospitality researchers have examined what impacts willingness-to-pay in restaurants, they have yet to determine if willingness-to-pay varies by menu course. The impact of sustainability messages and historical information on willingness-to-pay has also not been explored. This study used choice-based conjoint analysis to examine the effects of food quality, service quality, ambiance, sustainability information, historical information, and price on willingness-to-pay for three different courses in a restaurant: appetizer, entrée, and dessert. The choice of menu items and prices was based on an examination of casual dining restaurants in the U.S. The results indicate that while food quality, ambiance, and service quality were significant for all three courses, there were some interesting differences by course. While food quality was consistently the highest-rated antecedent, demographic information significantly changed the value of other antecedents for appetizers. For desserts, the uncommon menu item was the most chosen item. The sustainability and historical information messages were not significant, indicating that consumers may be experiencing information overload.

Supply chain management with uncertainty in consumer perception of product greenness under an eco-label policy

The urgency of environmental preservation necessitates green manufacturing and supply chain advancements. This research examines a green supply chain problem influenced by eco-label policies, focusing on two prevalent market eco-label types. One allows the manufacturer to determine product greenness, while the other requires compliance with standards set by a non-governmental organization (NGO). We also explore the variability in consumer comprehension of eco-label implications and purchasing behaviors with different eco-labeled products. Through consumer utility and manufacturer profit models, we discover that the manufacturer's production and pricing choices significantly impact consumer behavior. Increased investigation costs may enhance consumer utility through improved product greenness, potentially boosting manufacturer profit via price hikes. However, if investigation costs are minimal, the NGO-label may be rejected due to decreased utility and profit. These insights could help direct supply chains by providing a theoretical foundation for green production decisions and future eco-label policies, whether determined by an NGO or the manufacturer.

Endogenous choice of price or quantity contract with upstream advertising

AbstractWe investigate a supply chain comprising a manufacturer engaged in advertising and two retailers who compete with differentiated products. We examine the endogenous choice between competing on quantity or price for the retailers. Our analysis reveals that, depending on the level of product substitutability, the range of possible outcomes is varied and includes Cournot, Bertrand, and Cournot‐Bertrand under informative advertising. This result contradicts the established understanding that firms tend to engage in Cournot competition as their dominant strategy. Furthermore, we find that under persuasive advertising, Cournot or Bertrand outcomes may be optimal, but Cournot‐Bertrand never arises as an equilibrium.

From uniform to bespoke prices: Hotel pricing during EURO 2016

Using novel data on the pricing for hotel rooms in Paris during the summer of the 2016 European Football Cup, we document the co-existence of uniform and bespoke pricing within the same industry and even within the same firm. Although stay dates have heterogenous potential demand, hotels initially price them uniformly. However, as time goes by, they progressively set customized prices. We show that standard revenue management techniques can explain the shift and find evidence that the inability to form expectations about future demand was a determinant of the initial choice of uniform prices. Finally, we find that firm characteristics have a role in shaping the transition.

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.

Methods and ways of improving progect management in the field of tourism and recreation in the context of european integration

The purpose of the proposed article is a theoretical study of project management methods in the field of tourism and recreation, highlighting the ways of improving the management process, which justify the need for a modern tourist enterprise to direct efforts to the development or improvement of new products or services. The methodology is based on scientific and special research methods. Methods of analysis, synthesis, systematization, classification, generalization of economic and methodical literature, scientific publications were used. Horizontal analysis, vertical analysis, trend analysis, comparative analysis, analysis of relative indicators were also used. Scientific novely. Scientific novelty. The study of the features of various approaches to project management in the field of tourism and recreation necessitated a thorough analysis of their advantages and disadvantages. The author considered key problems in management processes and identified ways to overcome them during the implementation of tourism activities by business entities. Conclusions. The article solves important problems of the tourism sphere through the effective management of projects in tourism and recreation, the appropriate choice of price and marketing policy strategies, ensuring the quality of tourism and recreation services. based on the analysis of the considered projects in the field of tourism and recreation, we emphasize that the effectiveness of the design process depends on productive management; coordinated activity of project participants; peculiarities of national culture, resources, market conditions; strategies for the sustainable development of tourism in a specific region. Project management in the field of tourism and recreation needs to take into account the peculiarities of tourist services, which consist in the instability of demand, changes in quality and storage conditions, and correctly chosen methods of project management create opportunities for increasing the competitiveness of the destination. It has been proven that the effectiveness of project management in the field of tourism and recreation largely depends on teamwork, creativity of specialists, cooperation and support at different hierarchical levels.

Managing Conflicting Interests of Stakeholders in Influencer Marketing

A successful campaign should be able to attract investment from the brand, and meanwhile manage the conflicting interests in the campaign cost between the brand and the influencers. As such, the agency between these two stakeholders plays a vital role. Motivated by the above, we stand in the agency's shoes to formulate an interesting yet practical problem, namely Profit Divergence Minimization in Investment-Persuasive Influencer Marketing Campaign (PDMIC). This problem aims to (i) minimize the divergence of the actual hiring prices from the asking prices of the influencers and meanwhile (ii) maintain the attractiveness of the pricing scheme for the influencers to the brand. We show that this problem is NP-hard. To mitigate the challenge of the extremely large searching space of the hiring prices of the influencers, we solve this problem by firstly considering a restrictive searching sub-space and then gradually expanding the searching sub-space to the whole space in the end (specifically, from binary price choices to a set of integer prices and then to any price in the feasible price range). We propose effective yet efficient approximate algorithms for solving the problem in each of these settings. Extensive experiments demonstrate the superiority of our methods.

Impact of China’s Foreign Direct Investment on The Rwandan Economic Growth

The purpose of this study was to investigate the exact impact in quantitative terms of China’s FDI on the Economic development of the African continent with reference to Rwanda. The target population comprised 10 staff members of National Institute of Statistics of Rwanda, Rwanda Development Board, Ministry of Trade and Industry, Ministry of Finance and Economic Planning, United Nations (UN) Statistics, and World Bank's World Development Indicators. The sample size was 10 key informants. The researcher used questionnaire, interview guide and desk review as data analysis tools. The SPSS was used to analyze data into descriptive and inferential statistics. Results discover that in Rwanda a foreign direct investment depends on the consumer prices index. The study found out that 54.3% agreed with the consumer prices index, foreign direct investment is influenced by owner-occupiers' housing costs as it was evidenced by 62.8%, it was seen the retail prices index, where 56.7% agreed. Correlation analysis between the Owner-occupiers' housing costs and economic growth show a significant correlation between owner-occupiers' housing costs and job creation (r=.206; p-value=.000). This was statistically correlated given the p value was <0.005 proposing that increase in owner-occupiers' housing costs has led to a job creation in Rwanda. The study demonstrated that 64.6% agreed that the nominal effective exchange influence foreign direct investment, 45.1% strongly agreed with the real effective exchange rate. Correlation results felt that choice of price or cost felt that it is significantly correlated with a growth domestic product (r=0.123*; p value=0.034). The study sought to evaluate the effect of Balance of Trade on the economic growth of Rwanda. The study evidenced that participants agreed that the financial account statements by 55.5% while the study found that capital account is affecting foreign direct investment. It was shown by 53.0%. Results show a significant correlation between capital account and poverty reduction (r=0.105, p-value=0.071). The correlations were statistically significant given that the p value was < 0.05 proposing that an increase in capital account was insignificant with the economic growth and vice versa. The study concludes that inflation rate, exchange rate and balance of trade and thus FDI, have a significance effect on the economic growth in Rwanda. The study recommends that foreign direct investment strategies could be adopted in everyday activities. It would be appropriate to consider most favored nation and trade liberalization and investment as a criteria of exporting companies for improving economic growth. Future research can be conducted using longitudinal research to identify factors which contribute to economic growth. Keywords: Foreign Direct Investment, Economic Growth, Rwanda.

Impact of China’s Foreign Direct Investment on The Rwandan Economic Growth

The purpose of this study was to investigate the exact impact in quantitative terms of China’s FDI on the Economic development of the African continent with reference to Rwanda. The target population comprised 10 staff members of National Institute of Statistics of Rwanda, Rwanda Development Board, Ministry of Trade and Industry, Ministry of Finance and Economic Planning, United Nations (UN) Statistics, and World Bank's World Development Indicators. The sample size was 10 key informants. The researcher used questionnaire, interview guide and desk review as data analysis tools. The SPSS was used to analyze data into descriptive and inferential statistics. Results discover that in Rwanda a foreign direct investment depends on the consumer prices index. The study found out that 54.3% agreed with the consumer prices index, foreign direct investment is influenced by owner-occupiers' housing costs as it was evidenced by 62.8%, it was seen the retail prices index, where 56.7% agreed. Correlation analysis between the Owner-occupiers' housing costs and economic growth show a significant correlation between owner-occupiers' housing costs and job creation (r=.206; p-value=.000). This was statistically correlated given the p value was <0.005 proposing that increase in owner-occupiers' housing costs has led to a job creation in Rwanda. The study demonstrated that 64.6% agreed that the nominal effective exchange influence foreign direct investment, 45.1% strongly agreed with the real effective exchange rate. Correlation results felt that choice of price or cost felt that it is significantly correlated with a growth domestic product (r=0.123*; p value=0.034). The study sought to evaluate the effect of Balance of Trade on the economic growth of Rwanda. The study evidenced that participants agreed that the financial account statements by 55.5% while the study found that capital account is affecting foreign direct investment. It was shown by 53.0%. Results show a significant correlation between capital account and poverty reduction (r=0.105, p-value=0.071). The correlations were statistically significant given that the p value was < 0.05 proposing that an increase in capital account was insignificant with the economic growth and vice versa. The study concludes that inflation rate, exchange rate and balance of trade and thus FDI, have a significance effect on the economic growth in Rwanda. The study recommends that foreign direct investment strategies could be adopted in everyday activities. It would be appropriate to consider most favored nation and trade liberalization and investment as a criteria of exporting companies for improving economic growth. Future research can be conducted using longitudinal research to identify factors which contribute to economic growth. Keywords: Foreign Direct Investment, Economic Growth, Rwanda

Technology Company Merger and Acquisition: a Study of Indonesian and European Union Competition Law

Technology has become an essential part of human activities, people's needs and demands for it are significantly increased. People have become dependent on technology because they use it to travel, communicate, learn, do business and simplify human life. Currently, technology-based companies are growing rapidly all over the world, as we can see how Google, Facebook, Twitter, Microsoft, Apple, and various other companies dominate the market. Likewise in Indonesia, people's activities cannot be separated from various products from technology-based companies, such as Gojek, Tokopedia, Shopee, Grab, Traveloka, etc. Recently, Gojek and Tokopedia officially merged to become the GoTo Group and are claimed to be the largest technology group in Indonesia. This merger is usually carried out by business actors to seek more profit and to become a company that wins the market both on a national and international scale and in fact has a significant impact on changes in structure and control over the market so that there is a potential for abuse of dominant position to occur by limiting the choice of both products, quality, and price. Based on this case, this normative research using the case approach and statute approach aims to analyze how Indonesian competition law regulates technology company mergers, by comparing it with European Union competition law. The conclusion of this research is, lesson learn from European Union, Indonesian Competition Law needs to adapt the Data Protection Law in reviewing tehcnology company mergers in Indonesia.

Is My Transaction Done Yet? An Empirical Study of Transaction Processing Times in the Ethereum Blockchain Platform

Ethereum is one of the most popular platforms for the development of blockchain-powered applications. These applications are known as ÐApps. When engineering ÐApps, developers need to translate requests captured in the front-end of their application into one or more smart contract transactions. Developers need to pay for these transactions and, the more they pay (i.e., the higher the gas price), the faster the transaction is likely to be processed. Developing cost-effective ÐApps is far from trivial, as developers need to optimize the balance between cost (transaction fees) and user experience (transaction processing times). Online services have been developed to provide transaction issuers (e.g., ÐApp developers) with an estimate of how long transactions will take to be processed given a certain gas price. These estimation services are crucial in the Ethereum domain and several popular wallets such as Metamask rely on them. However, despite their key role, their accuracy has not been empirically investigated so far. In this article, we quantify the transaction processing times in Ethereum, investigate the relationship between processing times and gas prices, and determine the accuracy of state-of-the-practice estimation services. Our results indicate that transactions are processed in a median of 57 seconds and that 90% of the transactions are processed within 8 minutes. We also show that higher gas prices result in faster transaction processing times with diminishing returns. In particular, we observe no practical difference in processing time between expensive and very expensive transactions. With regards to the accuracy of processing time estimation services, we observe that they are equivalent. However, when stratifying transactions by gas prices, we observe that Etherscan’s Gas Tracker is the most accurate estimation service for the very cheap and cheap transactions. EthGasStation’s Gas Price API, in turn, is the most accurate estimation service for regular, expensive, and very expensive transactions. In a post-hoc study, we design a simple linear regression model with only one feature that outperforms the Gas Tracker for very cheap and cheap transactions and that performs as accurately as the EthGasStation model for the remaining categories. Based on our findings, ÐApp developers can make more informed decisions concerning the choice of the gas price of their application-issued transactions.