Search

Over the last decade there has been significant interest in international expansion of emerging market firms (EMFs) due to their distinctive patterns compared with developed market firms (DMFs). In this article, the authors develop an analytical model to generate prescriptive insights for pricing strategies when EMFs enter new foreign markets. Grounded in the international marketing and organizational learning literatures, the model accounts for local and multinational competition, the influence of country-of-origin effects, and the role of organizational learning in foreign markets. The results suggest that when an EMF enters a host market with a local competitor, it could generate higher profits even when charging a lower price than the local competitor. Additionally, the authors find that DMFs enjoy greater profitability than EMFs in foreign markets as a result of positive country-of-origin effects. Finally, the authors propose and validate the use of organizational learning as a process EMFs can use to surmount the negative impact of country-of-origin effects and achieve greater profitability than DMFs. [ABSTRACT FROM AUTHOR]

Featured Application: The proposed dynamic pricing method provides an actionable tool for e-commerce managers aiming to enhance their pricing strategies with real-time adjustments based on customer behavior, competitor pricing, and market dynamics. Through this approach, e-commerce platforms can efficiently leverage machine learning to personalize pricing at an individual customer level, ultimately maximizing revenue opportunities and customer satisfaction. Beyond direct pricing optimization, this method can also be adapted as a robust decision support system for small to medium-sized online retailers. By integrating user-specific purchasing data, the model can help predict optimal pricing actions, enabling businesses to navigate highly competitive markets while maintaining profitability and customer loyalty. One of the key areas of contemporary marketing is the formulation of a pricing strategy, which is one of the four pillars of the traditional marketing mix. One way to implement this strategy is through dynamic pricing. It is currently gaining popularity in many industries for two reasons. Firstly, it is possible, easy, and cheap to collect information about transactions and customers. Secondly, machine learning mechanisms, for which these data are essential, are becoming widely available. The aim of this article is to propose a dynamic pricing method for the e-commerce industry. To achieve this goal, machine learning methods such as the Naive Bayes classifier, support vector machines (linear and nonlinear), decision trees, and the k-nearest neighbor algorithm were used. The empirical results indicate that the linear support vector machine achieved the highest accuracy (86.92%), demonstrating the model's effectiveness in classifying pricing decisions. This article aligns with two leading research trends in dynamic pricing: personalized dynamic pricing (the target model considers customer-related criteria) and the development of systems to assist managers in optimizing pricing strategies to increase revenues (using machine learning methods). This article presents a literature review on dynamic pricing and then discusses the machine learning methods applied. In the final part of this article, verification of the developed dynamic pricing method using real-world conditions is presented. [ABSTRACT FROM AUTHOR]

Ride-sharing is increasingly recognised as a potential solution to transportation issues such as traffic congestion and parking problems. The success of ride-sharing systems depends on the willingness of individuals to share rides, and effective pricing strategies are among the crucial factors. However, creating a fair pricing system for riders and providers remains challenging. This research introduces a new pricing scheme based on the concept of shareability. This concept considers all the possible sharing situations among trips. It is designed to incentivize riders and accommodate providers' criteria. This scheme calculates the trip fare for passengers, considering various ride-sharing scenarios derived from the shareability function, thus ensuring fairness and transparency for passengers. Using the macroscopic fundamental diagram, our model incorporates traffic dynamic conditions. We have applied the method to the real case of Lyon city in France to assess the effectiveness of our approach. Through a comprehensive analysis of various configurations of the proposed pricing scheme and benchmarking with the existing approaches, we demonstrate its superior performance in reducing ride rejections compared to traditional methods. This result showed the proposed method's potential for enhancing ride-sharing systems' effectiveness. [ABSTRACT FROM AUTHOR]

Managerial Economics is an economy branch is, this economic theory and size using methods solve real-world managerial problems. It helps businesses and organizations make informed decisions by using economic analysis. Here are some common applications of managerial economics: Demand Analysis and Forecasting: Businesses use managerial economics to understand consumer behavior and forecast future demand for their products or services. This involves studying factors that affect demand, such as price, income levels, and consumer preferences. Production and Cost Analysis: Managerial economics helps businesses optimize production processes and minimize costs. It involves analyzing production functions, cost structures, and economies of scale to determine the most efficient way to produce goods or services. Pricing Strategies: A product or the right price for the service It is up to a company to decide Crucial to profitability. Managerial economics helps businesses set prices by considering factors like production costs, competition, and consumer willingness to pay. Market Structure Analysis: Understanding the type of market, a company operates in (e.g., perfect competition, monopoly, oligopoly) is essential for making strategic decisions. Managerial economics helps analyses market structures and determine appropriate strategies for each. Risk and Uncertainty Analysis: Businesses often face uncertainty in various aspects, such as demand fluctuations, production costs, and market conditions. Managerial economics provides tools to assess and manage risks, including techniques like decision tree analysis and expected value calculations. Capital Budgeting and Investment Analysis: Managerial economics assists in evaluating investment opportunities and capital projects. It involves methods Payback period analysis of investments. Regulatory and Government Policy Analysis: Managerial economics helps businesses understand and navigate government regulations and policies that affect their operations. This can include areas like taxation, environmental regulations, and trade policies. Strategic Planning: Using economic analysis, businesses can develop long-term strategies for growth and sustainability. This may involve assessing market trends, competitive dynamics, and potential expansion opportunities. Game Theory and Competitive Strategy: Managerial economics incorporates game theory to analyze strategic interactions between competitors. It helps businesses formulate optimal strategies in competitive environments. Resource Allocation: Efficient allocation of resources, including labor, capital, and technology, is crucial for a company's success. Managerial economics provides tools to distribute funds in a manner that optimisesoverall productivity and profitability. Demand Analysis and Forecasting, Production and Cost Analysis, Pricing Strategies, Market Structure Analysis, Risk and Uncertainty Analysis, Capital Budgeting and Investment Analysis and Regulatory and Government Policy Analysis. The Cranach’s Alpha Reliability result. The overall Cranach’s Alpha value for the model is .744 which indicates 74% reliability. From the literature review, the above 50% Cranach’s Alpha value model can be considered for analysis. [ABSTRACT FROM AUTHOR]

With society's increasing call for more inclusivity in the fashion industry, adaptive clothing, designed for people with disabilities (PWD), has rapidly emerged as a critical and high-potential product category for U.S. retailers. By analysing thousands of clothing items in the market from 2018 to 2022 at the Stock Keeping Unit level, this study analysed U.S. retailers' merchandising strategies for adaptive clothing. The logistic regression revealed that, statistically, adaptive clothing in the U.S. retail market looked more 'boring' and exhibited lower availability in several categories, including dresses, outerwear & suits, and underwear. Also, compared with nonadaptive ones, adaptive clothing statistically was more likely to be priced higher than the market average. The findings generated critical new knowledge about the business aspect of adaptive clothing by adding a valuable retailers' perspective. The results also call for efforts to make adaptive clothing more diverse in product categories and financially affordable to PWD. [ABSTRACT FROM AUTHOR]

This study presents a novel approach to understanding the complex dynamics of the electric vehicle (EV) market through the lens of differential game theory. We developed a comprehensive model that captures the strategic interactions between EV manufacturers and charging network operators, while incorporating the effects of consumer behavior, market uncertainties, and reference price effects. Using differential game theory, we examined the impact of reference price effects and the charging network's influence on pricing strategies, focusing on three distinct approaches: basic pricing, static pricing considering reference price effects, and dynamic pricing strategies. Our model offers new insights into consumer behavior and price expectations in the rapidly evolving EV market. The key findings reveal that under static or dynamic pricing strategies, the optimal pricing for EV manufacturers is positively correlated with the initial reference price. When the initial reference price is high (low), the optimal pricing strategy resembles skimming pricing (penetration pricing). As the effort level of charging network operators increases and their influence on consumers' purchase decisions grows stronger, EV manufacturers tend to set higher prices. Notably, while dynamic pricing strategies can optimize EV manufacturers' profits, the profits of charging network operators may decrease compared with static pricing strategies. This integrated approach significantly contributes to the field by bridging gaps among market dynamics, pricing strategies, and the infrastructure's development in the context of electric mobility, providing a comprehensive framework for understanding and optimizing the EV ecosystem. Ultimately, this study advances sustainable business models that balance profitability, consumer behavior, and the infrastructure's growth in the rapidly evolving EV market. [ABSTRACT FROM AUTHOR]

Abstract In the context of low-carbon economy, financial constraints are prevalent among both upstream and downstream enterprises, exacerbated by the trend of online retailers extending into offline physical stores. This study first proposes and evaluates three financing combination models: “bank lending + advance payment,” (in short, AF), “bank lending + delayed payment,” (in short, DF), and “bilateral bank lending.” (in short, TF). It then examines the retailer’s dual-channel supply chain pricing and financing decision-making models under unified pricing strategy and independent self-pricing strategy respectively. The evaluation results indicate that among various financing models, the independent self-pricing strategy has the potential to enhance the retailer's profitability, outperforming the unified pricing strategy. In addition, when channel preference is significant, the retailer should prioritize the independent self-pricing strategy. A comparison of the optimal decisions across the three financing combination models indicates that both the cost coefficient of carbon emission reduction and the loan interest rate exert a limiting influence on the decision-making and income of all supply chain parties. Furthermore, the DF model emerges as a financing equilibrium strategy within the supply chain, with a shift to the AF model being considered only when the manufacturer’s loan interest rate is relatively high.

As Islamic banks grow and evolve, pricing methods for their services have become essential to study and implement. This study highlights the significance of understanding the factors influencing Islamic banking service pricing in Algeria. The study aims to analyze how Islamic banks price their services, with a focus on cost, market, and value strategies. Additionally, it seeks to evaluate and recommend ways to enhance the current practices of banks operating in the national market. Algeria is experiencing rapid growth in Islamic banking, making it an ideal location to study this subject. The country is home to two Islamic banks, Al Baraka Bank and Al Salam Bank. Algeria was selected as a new market to allow the findings to be applicable to similar situations elsewhere. The research utilizes secondary data obtained from available information on Islamic bank service fees, comparing them with those of traditional banks. It also conducts financing simulations in both banks and compares them with the traditional theoretical framework. Data was gathered from various sources, including bank websites, annual reports, and previous studies. The research reveals that Algerian Islamic banks do not prioritize scientific methods in pricing their services. The results suggest that these banks operate within a traditional framework under the oversight of the central bank. The central bank's rules depend on the prices of services conventional banks offer. This shapes how customers perceive these banks as representatives of Islamic banking. Islamic banks can utilize the study's results to develop pricing strategies that are more effective and compliant with Islamic law. Regulators can utilize these findings to formulate enhanced policies to bolster the Islamic banking sector. The results also assist researchers in delving deeper into the realm of Islamic banking service pricing. This study refutes the hypothesis that Algerian Islamic banks have enhanced the efficiency of their service pricing by adopting models in line with Islamic finance principles, such as profit-sharing, while considering market conditions and service value. They should embrace more pragmatic and beneficial pricing strategies that align with Islamic law, cater to customer needs, and enhance their competitiveness and value in the national banking market.

One of the prominent pricing decisions a retailer can make is its choice of pricing strategy. Previous research investigating consumers' responses to stores with frequent, shallow price advantages relative to competitors (a frequency strategy) versus stores with infrequent, deep price advantages (a depth strategy) was all conducted by allowing people to simultaneously view prices from multiple stores, a setting that emphasized across-store comparisons. The present research finds that when a store's prices are evaluated separately, as opposed to simultaneously across stores, many of the prominent findings of previous research are reversed. The authors demonstrate that without simultaneous comparisons across stores, consumers shift from using across-store prices as reference points to using within-category reference prices. As a result of this shift, deep price advantages are easier to evaluate than frequent price advantages, and therefore more influential on consumers' formation of price image. When stores are evaluated separately, the result is most often a depth advantage, where stores with a HILO pricing strategy are evaluated as having a lower price image than EDLP stores, even when the average prices are the same. These results cannot be explained by prior work related to frequency and depth pricing strategies that relied on across-store comparisons. [ABSTRACT FROM AUTHOR]

This study explores key factors influencing sales performance in contemporary business environments, focusing on corporate image, product quality, customer relationship management (CRM), innovative marketing strategies, sales team development, and pricing approaches. Using a quantitative approach, the research analyzes data from companies across various industries to identify how these elements contribute to improved sales outcomes. The findings reveal that a positive corporate image enhances customer trust and loyalty, which in turn boosts sales. High-quality products lead to customer satisfaction and repeat purchases, while effective CRM practices, characterized by personalized service and responsiveness, play a crucial role in customer retention and sales growth. Innovative marketing, particularly through digital and social media channels, is highlighted as a significant driver of sales in today's competitive environment. The study also emphasizes the importance of continuous training and development for sales teams, along with pricing strategies that align with customer expectations, in achieving better market share and performance. In addition, the research considers the influence of broader economic factors, such as inflation and economic growth, on consumer purchasing power and sales performance. This study offers valuable insights for business leaders and marketers looking to enhance their sales strategies and sustain growth in a dynamic market environment. [ABSTRACT FROM AUTHOR]

Purpose: This research aims to identify the determinants factors for açai berry price liter in Belem Metropolitan Region (RMB) at Para state, Brazil, according to the perception of its entrepreneurs. Methodology: An exploratory with a qualitative approach research, conducted through face-to-face semi-structured interviews with açaí entrepreneurs, in the RMB. The collected information was treated with content analysis, using ATLAS.Ti 8 software, in three categories of analysis: determining factors for pricing based on costs; determining factors for market-based pricing; determining factors for pricing based on costs and market. From these three categories, the description of the factors and variables took place. Results: It was concluded that açaí entrepreneurs predominantly adopt strategies for price formation based on costs, as opposed to determinants based on market factors, using inadequate information and methods of price formation, based only on personal experience and perceived need, lacking training and formal education, under the study field, drawing attention support from agencies that promote entrepreneurship, and definition of public policies for development and improvement of activity of producing açaí pulp in Belem and region. Contributions of the Study: From a theoretical perspective, this research contributes to study and discussion of sales price formation approaches. As a practical contribution, this research emphasizes the açaí fruit in establishments belonging to Para metropolis, favoring the development and improvement of local enterprises. Finally, given that açaí is a food product of cultural and economic significance for the RMB, this research contributes socially by portraying and bringing to discussion the reality of these businesses management. [ABSTRACT FROM AUTHOR]

As Islamic banks grow and evolve, pricing methods for their services have become essential to study and implement. This study highlights the significance of understanding the factors influencing Islamic banking service pricing in Algeria. The study aims to analyze how Islamic banks price their services, with a focus on cost, market, and value strategies. Additionally, it seeks to evaluate and recommend ways to enhance the current practices of banks operating in the national market. Algeria is experiencing rapid growth in Islamic banking, making it an ideal location to study this subject. The country is home to two Islamic banks, Al Baraka Bank and Al Salam Bank. Algeria was selected as a new market to allow the findings to be applicable to similar situations elsewhere. The research utilizes secondary data obtained from available information on Islamic bank service fees, comparing them with those of traditional banks. It also conducts financing simulations in both banks and compares them with the traditional theoretical framework. Data was gathered from various sources, including bank websites, annual reports, and previous studies. The research reveals that Algerian Islamic banks do not prioritize scientific methods in pricing their services. The results suggest that these banks operate within a traditional framework under the oversight of the central bank. The central bank's rules depend on the prices of services conventional banks offer. This shapes how customers perceive these banks as representatives of Islamic banking. Islamic banks can utilize the study's results to develop pricing strategies that are more effective and compliant with Islamic law. Regulators can utilize these findings to formulate enhanced policies to bolster the Islamic banking sector. The results also assist researchers in delving deeper into the realm of Islamic banking service pricing. This study refutes the hypothesis that Algerian Islamic banks have enhanced the efficiency of their service pricing by adopting models in line with Islamic finance principles, such as profit-sharing, while considering market conditions and service value. They should embrace more pragmatic and beneficial pricing strategies that align with Islamic law, cater to customer needs, and enhance their competitiveness and value in the national banking market. [ABSTRACT FROM AUTHOR]

This paper studies supply chain pricing and production/ordering decisions under carbon tax policy and retailer's stochastic demand. Firstly, a supply chain model with random demand obeying normal distribution is established. Based on this, a stochastic optimization problem with the goal of maximizing expected social welfare is constructed. The multi-agent consensus is used to solve the optimization problem, and the pricing and production/ordering decisions with random demand obeying normal distribution are obtained. Finally, the theoretical results are verified by numerical simulation, and the influence and effectiveness of multi-agent consensus theory on supply chain decision-making are demonstrated in the presence of random demand and sudden failure of an enterprise in the supply chain and further analyze the impact of carbon tax policy on supply chain decision-making. [ABSTRACT FROM AUTHOR]

Public healthcare systems are challenged by the soaring costs of medications that require increasing resources, often at the expense of other investments. The increasing pharmaceutical budget poses a threat to the allocation of funds for essential preventive and primary healthcare services while also raising concerns about equitable access, particularly in models where patients bear part of the costs out of their own pockets. Proposals on how to ensure ongoing and long-term accessibility, efficiency, and financial stability are required. The escalating costs of medicines may be explained in part by the mismatch between the traditional value-based pricing and reimbursement frameworks and the type of clinical development of targeted therapies and precision medicine in clinical practice. New appraisal methods and managed access strategies should be adapted to therapies targeting small populations and addressing increased uncertainty. Fair pricing strategies, transparent healthcare investments based on problems and outcomes, regulatory reforms, international cooperation, and critically examining the drug acquisition model are potential solutions. Transitioning from an industry-driven pricing approach to a health-driven payment model can help align the cost of treatments with actual health outcomes, establishing a foundation for a healthcare system that addresses immediate challenges and fosters long-term well-being. Acknowledging the lack of a universally applicable solution, the practical implementation of interventions requires a reframing of the pricing and access system and adaption to the targeted therapeutic approaches. Balancing innovation with financial sustainability necessitates a collaborative, adaptive, and transparent approach, as well as transitioning toward health-driven payment models, moving the focus from the cost of medications to the well-being of populations worldwide.

In the face of a competitive and ever-changing business landscape, companies often grapple with the challenge of sustaining their products in declining markets. To combat this issue, effective strategies such as promotional efforts play a pivotal role in boosting demand and maintaining market position. Additionally, businesses are increasingly focusing on ecological safety and greening efforts to minimize their environmental impact while ensuring the production of environmentally friendly products. These green initiatives not only contribute to environmental sustainability but can also enhance retailer profitability. This article presents an innovative inventory model tailored for perishable products within a stochastic environment. The model integrates elements such as linear pricing, time dynamics, promotional efforts, and a demand rate that depends non-linearly on the level of greening efforts. The model also considers partial backlogging of shortages, lost sales, time-dependent product deterioration, and investments in preservation technology to mitigate deterioration effects. The primary objective is to calculate the retailer's profit function, taking into account cycle time, selling price, promotional effort, and greening effort as key variables. To address this complex problem, the article introduces an algorithm for finding feasible solutions. Furthermore, the concavity of these solutions is demonstrated through graphical analysis. A numerical example is provided to illustrate the application of the model, and sensitivity analysis is conducted to elucidate how changes in inventory parameters impact decision variables. We will also depicted the short representation of proposed study in Figure 1.

One of the key areas of contemporary marketing is the formulation of a pricing strategy, which is one of the four pillars of the traditional marketing mix. One way to implement this strategy is through dynamic pricing. It is currently gaining popularity in many industries for two reasons. Firstly, it is possible, easy, and cheap to collect information about transactions and customers. Secondly, machine learning mechanisms, for which these data are essential, are becoming widely available. The aim of this article is to propose a dynamic pricing method for the e-commerce industry. To achieve this goal, machine learning methods such as the Naive Bayes classifier, support vector machines (linear and nonlinear), decision trees, and the k-nearest neighbor algorithm were used. The empirical results indicate that the linear support vector machine achieved the highest accuracy (86.92%), demonstrating the model’s effectiveness in classifying pricing decisions. This article aligns with two leading research trends in dynamic pricing: personalized dynamic pricing (the target model considers customer-related criteria) and the development of systems to assist managers in optimizing pricing strategies to increase revenues (using machine learning methods). This article presents a literature review on dynamic pricing and then discusses the machine learning methods applied. In the final part of this article, verification of the developed dynamic pricing method using real-world conditions is presented.

The management implications of pricing healthcare services, especially hospitals, have received insufficient scholarly attention. Additionally, disciplinary overlaps have led to scattered academic efforts in this domain. This study performs a thematic synthesis of the literature and applies retrospective analysis to hospital service pricing articles to address these issues. The study's inputs were sourced from well-known online repositories, using a structured search string and PRISMA flow chart to select the pertinent documents. Our thematic analysis of pricing literature encompasses: (a) comprehension of hospital service pricing nature; (b) pricing objectives, strategies and practices differentiation; (c) presentation of factors impacting hospital service pricing. We observe that hospital pricing is an intricate and unclear matter. The terms 'pricing strategies' and 'pricing practices' are often used interchangeably in academic literature. Hospital service pricing is influenced by costs, demand and supply factors, market structure, pricing regulation and third-party reimbursements. The study's findings provide policy implications for service pricing in hospitals, in addition to suggesting avenues for future research on hospital pricing. [ABSTRACT FROM AUTHOR]

Purpose: This research aims to identify the determinants factors for açai berry price liter in Belem Metropolitan Region (RMB) at Para state, Brazil, according to the perception of its entrepreneurs. Methodology: An exploratory with a qualitative approach research, conducted through face-to-face semi-structured interviews with açaí entrepreneurs, in the RMB. The collected information was treated with content analysis, using ATLAS.Ti 8 software, in three categories of analysis: determining factors for pricing based on costs; determining factors for market-based pricing; determining factors for pricing based on costs and market. From these three categories, the description of the factors and variables took place. Results: It was concluded that açaí entrepreneurs predominantly adopt strategies for price formation based on costs, as opposed to determinants based on market factors, using inadequate information and methods of price formation, based only on personal experience and perceived need, lacking training and formal education, under the study field, drawing attention support from agencies that promote entrepreneurship, and definition of public policies for development and improvement of activity of producing açaí pulp in Belem and region. Contributions of the Study: From a theoretical perspective, this research contributes to study and discussion of sales price formation approaches. As a practical contribution, this research emphasizes the açaí fruit in establishments belonging to Para metropolis, favoring the development and improvement of local enterprises. Finally, given that açaí is a food product of cultural and economic significance for the RMB, this research contributes socially by portraying and bringing to discussion the reality of these businesses management.

This research study aims to investigate the factors influencing customer choices between e-cab services and traditional taxis in Calabar, focusing on service quality, operational efficiency, pricing strategies, and customer incentives. Addressing gaps in existing literature, the study explores the unique preferences and decision-making criteria of customers in the Calabar metropolis when selecting transportation services. Employing a cross-sectional, descriptive design, the research utilized a structured questionnaire to collect data from 463 adults who have used both e-cab and traditional taxi services. The questionnaire was developed by the researchers, validated by experts and trial-tested for reliability purposes. The reliability coefficient was estimated at .93 using the Cronbach alpha reliability estimate. Collected data were subjected to analysis using descriptive statistics, relative important index, independent t-test and analysis of variance. The analysis revealed that the key factors influencing customer choices in Calabar between e-cab services and traditional taxis include convenience, cleanliness, ride comfort, safety, and cost-related incentives; Customer demographics such as age, gender, and income level did not significantly influence preferences between e-cabs and taxis in Calabar and that service speed, reliability, and competitive pricing strategies play a crucial role in customer decision-making. Recommendations include prioritizing service quality, implementing competitive pricing strategies, and focusing on service speed and reliability to enhance customer satisfaction and retention. [ABSTRACT FROM AUTHOR]

This article, published in the British Journal of Management & Marketing Studies, examines the relationship between pricing strategies and consumer purchase decisions in Nigeria. The study used a survey research design and collected data through questionnaires. The findings showed that skimming pricing had a negative correlation with consumer purchase decisions, while penetrating pricing and discount pricing had a positive relationship. The study suggests that manufacturers and marketers should use pricing strategies that are favorable to consumers to attract repeat purchases. The article also provides information on various pricing strategies and their impact on consumer purchase decisions, as well as a review of empirical literature and theoretical frameworks related to pricing strategies. [Extracted from the article]

The expansion of iBuyer's use of PropTech to major housing markets raises a series of questions for both buyers and sellers when making instant, all-cash offers. This study uses a sequence of experiments to identify the proper implementation of existing behavioral real estate concepts to improve the iBuying process, a burgeoning area of residential real estate. We find strong evidence of anchoring for all-cash offers in that sellers are nearly twice as likely to transact when they are first presented with the net proceeds offer price (market value minus costs) rather than starting with the higher gross market value offer price. After the sale, seller regret aversion becomes strong when the seller's house is subsequently sold for 10% or more than the all-cash buyer paid, but regret aversion is mitigated with communication of the improvements made to enhance the selling price. We further find that sellers do not know which all-cash buyer's Automated Valuation Model (AVM) is the most accurate and are therefore much more influenced by brand awareness than model sophistication. Finally, while the extant literature has examined offer price strategies for home sellers, this is the first investigation of buyer offer price strategies. In stark contrast to selling strategies, pricing strategies do not matter when making an offer to buy. [ABSTRACT FROM AUTHOR]

Service quality, loyalty programs, pricing strategies and customer engagement play a vital role in customer retention and firms' performance. The current study aims to investigate the service quality, loyalty programs, pricing strategies and customer engagement, and to examine the mediation effects on firms' performance. A quantitative method was employed using a survey to collect data from a random sample of relevant managers in travel agencies. Structural equation modelling (WarpPLS) is used to test the research propositions. The research uses a survey for data collection of 350 responses from travel agents' managers to test the associations between service quality, loyalty programs, pricing strategies and customer engagement, and customer retention and firms' performance. The finding revealed that the service quality, loyalty programs, pricing strategies and customer engagement have positively affected customer retention. In addition, customer retention has positively affected firms' performance. These findings have empirical implications for policymakers, trip planners, travel marketer's, governments and academics. [ABSTRACT FROM AUTHOR]

Artificial intelligence-powered recommendation systems have gained popularity as a tool to enhance user experience and boost sales. Platforms often need to make decisions about which seller to recommend and the strength of the recommendation when conducting recommendations. Therefore, it is necessary to explore the recommendation strategy of the platform in the case of duopoly competition. We develop a game model where two competing manufacturers sell products through an agency contract on a common platform, and they can decide whether or not to provide recommendations to the manufacturers. Our highlight lies in the endogenous recommendation strength of the platform. The findings suggest that it is optimal for the platform to offer recommendation services when the commission rate is high. The platform also prefers to only recommend one manufacturer in the market with low or high competition, but it prefers to recommend both manufacturers in moderately competitive markets. From the view of manufacturers, they can benefit from the recommendation service as long as the commission rate is not too low. Moreover, recommending only one manufacturer consistently yields stronger recommendations compared to recommending multiple manufacturers. However, the impact of recommendation on prices is influenced by the commission rate and product substitutability. These results have significant implications for platform decision making and provide valuable insights into the trade-offs involved in the development of recommendation systems.

Dynamic pricing is frequently used in online marketplaces, ticket sales, and booking systems. The commercial principles of dynamic pricing systems are often kept secret; however, their application causes complex changes in human behavior. Thus, a scientific tool is needed to evaluate and predict the impact of dynamic pricing strategies. Publications in the field lack a common quality evaluation methodology, public data, and source code, making them difficult to reproduce. In this paper, a data-driven method, DPRank, for evaluating dynamic pricing systems is proposed. DPRank first builds a surrogate price elasticity of demand model using public data generated by a hidden dynamic pricing model, and then applies the surrogate model to build an exposed dynamic pricing model. The hidden and exposed dynamic pricing models were then systematically compared in terms of quality using a Monte Carlo simulation in terms of a company’s revenue. The effectiveness of the proposed method was tested on the dataset collected from the website of a Russian railway passenger carrier company. Depending on the train type, the quality difference between the hidden and exposed models can vary by several dozen percent on average, indicating the potential for improving the existing (hidden) company’s dynamic pricing model.

Aiming at the pricing and emission reduction decision-making problem of a two-level supply chain consisting of multiple manufacturers and multiple retailers, this paper proposes a consistent pricing mechanism based on multi-agent structure to coordinate the supply chain, and the operation of supply chain participants from competition to cooperation. The proposed algorithm is distributed and collaborative, thus eliminating the need for a central snap-ins, central price coordinators, or leaders. Firstly, a two-level supply chain social welfare model with multi-agent structure is established, and the system nodes in this model are scalable. Then, the pricing and carbon tax policies of the supply chain under different dominant rights are discussed to determine the optimal transaction price and carbon tax policies in order to maximize social welfare. The research results show that the transaction price increases with the increase of the carbon tax rate, and the social welfare decreases with the increase of the carbon tax rate, so the government should formulate the carbon tax within a reasonable range. It is also found that the overall social welfare obtained when there is no dominant node is higher than the social welfare obtained when there is dominant node. It can guide the market to optimize the allocation of resources according to production needs, so as to achieve the maximum efficient use and social welfare.

The growth of the knowledge payment market is driven by the emergence of knowledge payment platforms that match providers looking to achieve cognitive surplus through knowledge sharing with consumers looking to acquire high-quality knowledge quickly. Like many digital platforms, expanding consumer market to generate revenue has been a challenge for knowledge payment platforms as well and subsidy strategy is seen as the most important way for the same. In this paper, we focus on the pricing and subsidy strategies of two knowledge payment platforms with providers of different ability to balance the revenue from consumers and subsidies to providers. Specifically, we introduce a duopoly competition model and characterize the technical service fees and subsidies in this model. Further, we respectively analyze the impacts of providers’ ability gap on two competing platforms’ pricing and subsidy strategies, market shares, as well as profits. We find that as providers’ ability gap increases, the platform with high-ability providers adopts strategies of increasing technical service fees and subsidies, while the platform with low-ability providers has to adopt strategies of decreasing technical service fees and subsidies. In addition, compared with low-quality platform, the platform with high-ability providers can occupy a larger share in consumer market. However, influenced by multiple factors, the provider market is relatively complex and the presence of high-quality platform cannot always ensure a larger share of it. Finally, we also find that as the difference in providers’ ability of two competing platforms increases, the profit gap between these platforms also widens.

In order to respond to and take advantage of consumers' growing interest in green products, an increasing number of firms are expanding their market share by introducing green versions of their brown products. However, firms are faced with the challenge of how to distribute green products to avoid mutual encroachment with brown products. To solve this problem, this paper constructs a Stackelberg game model consisting of a manufacturer (leader) and a retailer (follower), in which the manufacturer provides brown and green products, and then develops two channel structures for green products to be sold through the manufacturer (direct selling) and the retailer (agent selling). The results show that the manufacturer's choice of green product distribution channels is affected by the direct selling costs and the market share of green consumers and their product preferences. When the direct selling cost is zero or consumers are green, the manufacturer always chooses direct selling. However, with an increase in the direct selling costs, if green consumers have a large difference in their preference for green and brown products, the manufacturer chooses agent selling, and vice versa. In particular, the impact of the market share of green consumers on the profits of the manufacturer is different in the two channel structures. The higher the market share of green consumers under agent selling, the more beneficial it is for the manufacturer. However, under direct selling, the profits of the manufacturer show an "inverted U" trend with the increase in the market share of green consumers. In addition, under certain conditions, the direct selling channels opened by the manufacturer are not necessarily to sell green products, but to maximize the market share of brown products. The strategy is to set high prices for green products in direct selling channels to stimulate consumers to buy brown products. These findings can provide insights for manufacturers to design appropriate green product distribution strategies. [ABSTRACT FROM AUTHOR]

As there have been no effective and reliable transaction mechanisms to standardize user credibility during distributed electricity transaction, an electricity transaction matching mechanism based on blockchain and mixed continuous double auction were proposed. Credit value was introduced by the mixed continuous double auction into adjustment to prices offered by users. The continuous double auction transaction matching was done through credit value and the weighted mean of offered prices. This type of matching mechanism works effectively in minimizing the effects of malicious node on electricity resource allocation and improving total revenues as well as the transaction enthusiasm of users. To maximize the total revenues, the pricing strategies based on equilibrium value were proposed, and the transactions between user electricity digital certificate and fees were realized trough blockchain. Finally, the transaction mechanisms were verified to be workable through distributed electricity transaction simulation experiments. [ABSTRACT FROM AUTHOR]

Artificial intelligence-powered recommendation systems have gained popularity as a tool to enhance user experience and boost sales. Platforms often need to make decisions about which seller to recommend and the strength of the recommendation when conducting recommendations. Therefore, it is necessary to explore the recommendation strategy of the platform in the case of duopoly competition. We develop a game model where two competing manufacturers sell products through an agency contract on a common platform, and they can decide whether or not to provide recommendations to the manufacturers. Our highlight lies in the endogenous recommendation strength of the platform. The findings suggest that it is optimal for the platform to offer recommendation services when the commission rate is high. The platform also prefers to only recommend one manufacturer in the market with low or high competition, but it prefers to recommend both manufacturers in moderately competitive markets. From the view of manufacturers, they can benefit from the recommendation service as long as the commission rate is not too low. Moreover, recommending only one manufacturer consistently yields stronger recommendations compared to recommending multiple manufacturers. However, the impact of recommendation on prices is influenced by the commission rate and product substitutability. These results have significant implications for platform decision making and provide valuable insights into the trade-offs involved in the development of recommendation systems. [ABSTRACT FROM AUTHOR]

This paper analyzes a BigTech lender's pricing strategies in the business‐to‐customer unsecured loan market using a proprietary data set of consumer loans in China. We find that the credit rating constructed by the BigTech lender is informative of the customers' default risk. Moreover, the interest rate decreases and the credit limit increases with the credit rating. Interestingly, the BigTech lender charges different interest rates to its customers based on the customer channel, although it does not provide information about the customers' default risk. Following the passage of the China Banking Regulatory Commission Act, which reduced credit market competition, the BigTech lender increased the current rate and decreased the credit limit. We rationalize these empirical findings in a simple model of credit contract design. [ABSTRACT FROM AUTHOR]

Background and Objective: The market for heated tobacco products (HTPs) has grown markedly in recent years, and many governments have started to tax HTPs to regulate their use. To evaluate the impacts of HTP taxes on tobacco use behaviors and health consequences, we first need to assess if they effectively raise HTP prices in a tax system that also taxes cigarettes. This study jointly evaluates the pass-through of taxes to prices of HTPs and cigarettes. Data and Methods: We use a unique database on statutory HTP and cigarette taxes and retail prices of Marlboro-branded heated tobacco units and cigarettes from 2014 to 2021, developed by the Campaign for Tobacco Free Kids, in all countries where HTPs are sold. To estimate the pass-through of taxes to prices, we employ a seemingly unrelated regressions model. We also use an event study to test the impact of introducing HTPs to cigarette markets, as well as amending tax codes to include HTPs, on prices and price gaps. Conclusions and Policy Implications: Currently, the debate over whether HTPs should be taxed in comparison with cigarettes considers their potential harm reduction impact, and most countries tax HTPs at much lower rates than cigarettes in order to keep HTP prices lower than cigarette prices. However, the direct pass-through rate of HTP taxes to prices is several times smaller than that of cigarettes, resulting in very similar unit prices of HTPs and cigarettes. Further, while cigarette taxes are over-shifted to cigarette prices, HTP taxes are under-shifted to HTP prices, suggesting that tax gaps between the two products does not translate to price gaps. The results overall suggest that the lower taxes on HTPs do not lead to lower prices as compared to cigarettes and are unlikely to incentivize cigarette smokers to transition to HTPS for lower costs. Under this scenario, taxing both products equivalently could be an option to raise additional tax revenue. [ABSTRACT FROM AUTHOR]

Background: In the consumer-centric global economy of the 21st century, customer retention is a vital concept in the hospitality industry for building and sustaining long-term relationships. Recognizing the challenges of acquiring new customers, the industry acknowledges the significance of retaining existing ones. To achieve their goals, hospitality businesses need a comprehensive strategy that extends beyond price targets, emphasizing the development of effective pricing strategies from the outset. Methods: Data collection took place between June 2022 and January 2023, involving a random sample of seven international hotels located in Tirana, Durres, and Vlora. Quantitative data was collected through surveys utilizing Likert-scale questions. Statistical analysis, including crosstab tests, was employed to explore the relationship between economy pricing strategies and customer retention. Results: The study encompassed 572 participants representing diverse demographic characteristics. Analysis revealed a statistically significant positive relationship between economy pricing strategies and customer retention in international hotels in Albania. These findings underscore the importance of implementing effective pricing strategies to enhance customer loyalty and guide the development of improved strategies within the hotel industry. Conclusions: This study provides empirical evidence of a significant positive relationship between economy pricing strategies and customer retention in international hotels in Albania. Effective pricing strategies play a crucial role in fostering customer loyalty. However, the study's limitations, primarily its focus on specific hotels in Albania, call for further research to validate the generalizability of these findings. The insights gained from this study inform policymakers and industry stakeholders in formulating strategies to enhance customer retention within the hospitality sector.

Background: In the consumer-centric global economy of the 21st century, customer retention is a vital concept in the hospitality industry for building and sustaining long-term relationships. Recognizing the challenges of acquiring new customers, the industry acknowledges the significance of retaining existing ones. To achieve their goals, hospitality businesses need a comprehensive strategy that extends beyond price targets, emphasizing the development of effective pricing strategies from the outset. Methods: Data collection took place between June 2022 and January 2023, involving a random sample of seven international hotels located in Tirana, Durres, and Vlora. Quantitative data was collected through surveys utilizing Likert-scale questions. Statistical analysis, including crosstab tests, was employed to explore the relationship between economy pricing strategies and customer retention. Results: The study encompassed 572 participants representing diverse demographic characteristics. Analysis revealed a statistically significant positive relationship between economy pricing strategies and customer retention in international hotels in Albania. These findings underscore the importance of implementing effective pricing strategies to enhance customer loyalty and guide the development of improved strategies within the hotel industry. Conclusions: This study provides empirical evidence of a significant positive relationship between economy pricing strategies and customer retention in international hotels in Albania. Effective pricing strategies play a crucial role in fostering customer loyalty. However, the study's limitations, primarily its focus on specific hotels in Albania, call for further research to validate the generalizability of these findings. The insights gained from this study inform policymakers and industry stakeholders in formulating strategies to enhance customer retention within the hospitality sector.

Platforms are gradually becoming important business organization models, and platforms with bilateral market characteristics such as payment platforms and online shopping platforms are gradually penetrating people's lives. Freemium content mostly exists in particular platforms such as online video platforms, etc. Platforms need to balance upstream and downstream markets when formulating strategies. This paper is the first to explore the time-to-market and pricing strategies of products in bilateral markets. By connecting upstream and downstream markets through cross-network externalities, we construct a system dynamics model of the problem, simulate the diffusion process of new product launches, and solve the problem of the optimal time to market and optimal pricing of the product. The simulation analyzes the effects of different parameters on the optimal time-to-market and pricing strategies, and comparing the diffusion in a unilateral market, we find that in a competitive market environment, the time-to-market and pricing of products are influenced by exogenous variables such as network externalities, and firms can promote their products more efficiently by changing the marketing mix strategy of platform product benefits and quality reputation. Meanwhile, the results obtained by considering bilateral markets when developing strategies for platform-based companies can lead to higher returns. [ABSTRACT FROM AUTHOR]

Sustainable marketing emphasizes how businesses convey the concept of sustainability to consumers through marketing techniques. Previous research has focused on identifying the drivers that influence consumers' purchase intentions for agricultural products. However, there is a lack of research on the quality of the messages that firms convey to consumers from a pricing perspective. To fill this gap, this study builds on the hedonic pricing theory using structural equation modeling to develop a formative model that enables the identification of the determinants that influence the market price of the broiler chicken industry in mainland China. By analyzing the information on 486 raw whole chicken samples in China, the results indicate that the basic, responsible production, and quality assurance attributes of broilers have a substantial effect on their selling price, whereas the marketing message attributes do not. The results of this study are enlightening for producers and marketers of agricultural products who are developing pricing strategies. This study raises important questions about the pricing of agricultural products in sustainable marketing practices, particularly in emerging economies, and suggests avenues for future research conducted in this area. [ABSTRACT FROM AUTHOR]

The use of dynamic pricing strategies can have a tremendous impact on the hospitality industry. Understanding the variety in the type of customers and the perceptions of customers concerning the fairness of dynamic pricing is essential. This study aimed to investigate how a dynamic pricing strategy could positively affect the demand for a hotel located on the West Frisian island of Vlieland. This research was divided into four topics: determining segments and corresponding booking processes, the importance of price when booking, perceived fairness of price change and how to influence booking behaviour. This research used a survey that was presented to customers of the hotel in this case study for six weeks. Three hundred and sixty-eight customers completed the survey. The evidence suggests that implementing a more elaborate pricing strategy would positively affect the demand for this hotel. While price is still an essential factor when booking, it is concluded that this is not the most important consideration for consumers. If a pricing strategy is implemented, the hotel can improve the occupancy rate and generate more hotel revenue while simultaneously keeping the consumers satisfied. Relevant managerial implications include implementing peak load pricing to influence demand.

The paper examines the relationship between pricing strategies on performance of new businesses coming to Yenagoa Metropolis in Bayelsa State. The population of the study consisted of 231 newly registered businesses in Yenagoa, although only 96 were sampled for the study, using purposively sampling technique. Data collected were analyzed using simple statistical tools and the information generated was presented in four figures and tables. The research found out that price skimming has a significant effect on performance of new businesses in Yenagoa metropolis. Again, companies that practice higher price against the price of their competitors obtain greater profit. It was also observed that the Yenagoa business environment perceives low prices and generous introduction as suspicious and regard such as fake and sub-standard. Companies that use presentation pricing statistics struggles with less customer loyalty, as they tend to grow a core customer base of snatchers, these are customers who jump ship to go for the cheaper offerings and more likely to do so as price increases. New businesses coming to Yenagoa should establish a set of superior resources, such as abilities, skills and knowledge because the role of the "price fixing capacity" has a way of effectively improving the company's performance. More so, selecting the right entry pricing strategy (methods companies used to price product & services), is crucial in dictating customers reactions. Therefore, a strategic look at pricing decisions constitutes an aspect that can't be overlooked, as a new business in Yenagoa. [ABSTRACT FROM AUTHOR]

The use of dynamic pricing strategies can have a tremendous impact on the hospitality industry. Understanding the variety in the type of customers and the perceptions of customers concerning the fairness of dynamic pricing is essential. This study aimed to investigate how a dynamic pricing strategy could positively affect the demand for a hotel located on the West Frisian island of Vlieland. This research was divided into four topics: determining segments and corresponding booking processes, the importance of price when booking, perceived fairness of price change and how to influence booking behaviour. This research used a survey that was presented to customers of the hotel in this case study for six weeks. Three hundred and sixty-eight customers completed the survey. The evidence suggests that implementing a more elaborate pricing strategy would positively affect the demand for this hotel. While price is still an essential factor when booking, it is concluded that this is not the most important consideration for consumers. If a pricing strategy is implemented, the hotel can improve the occupancy rate and generate more hotel revenue while simultaneously keeping the consumers satisfied. Relevant managerial implications include implementing peak load pricing to influence demand. [ABSTRACT FROM AUTHOR]

Most knowledge payment platforms are keen to adopt a business model based on transaction revenue and advertising revenue. However, challenge with platforms has been to balance the interests of advertisers as well as their consumers. Increasing of advertising revenue, by having more advertisers may lead to higher consumers’ aversion. To address these queries, we develop a three-sided model to study the optimal pricing strategy of the knowledge payment platform. Specifically, we discuss the impact of the proportion of transaction fees charged by the platform on platform’s strategy under which the platform charges transaction fees from consumers and advertising fees from advertisers. We find that when the proportion of transaction fees charged by the platform is at a low level, the platform’s profit reaches the maximum. Once the proportion of transaction fees charged by the platform is high, which will have a negative impact on the platform’s profit although the platform adopts a strategy of increasing advertising price for advertisers. Besides, we analyze the changes of pricing strategy of knowledge payment platform under different level of network externalities. We find that with the increase of proportion of transaction fees charged by the platform and network externalities, both of the advertising price and platform’s profit are more sensitive to the proportion of transaction fees charged by the platform. On the contrary, as the degree of consumers’ aversion to advertisements increases, the platform’s profit is less sensitive to the proportion of transaction fees charged by the platform.