Service Pricing Strategies Research Articles

The Impact of Subsidies on Pricing Decisions in the Battery Swapping Supply Chain Under the “Vehicle and Battery Separation” Model

ABSTRACTTo explore the impact of various subsidies on the battery swapping industry under the “vehicle and battery separation” model, a supply chain comprising a battery manufacturer, a vehicle company, and a battery leasing company is constructed. Based on the no‐subsidy model, decision‐making models are developed for four scenarios that involve subsidizing different entities, including the customer, the battery manufacturer, the battery leasing company, and the vehicle company. Comparative analysis is then conducted. Results show that (1) subsidies do not invariably result in companies lowering prices for their products and services. Under various subsidy strategies, companies tend to adjust their pricing strategies for products and services according to the battery leasing time and the price sensitivity coefficient of battery swapping service. (2) Government subsidies to supply chain entities may not always effectively incentivize more companies to enter the battery swapping industry. Although direct subsidy to vehicle companies could encourage their participation, promoting the involvement of battery manufacturers and leasing companies through direct subsidies may have limited effectiveness. This limitation arises because the optimal profit among various strategies is influenced by factors such as the price sensitivity coefficient of battery swapping service and the battery swapping operating cost sharing ratio. (3) To advance the demand for battery‐swapping vehicles, enhance consumer surplus, and maximize social welfare, the government may prioritize subsidizing vehicle companies. However, when aiming to boost the demand for battery swapping service, the government should consider the level of price sensitivity coefficient of battery swapping service. Specifically, when the price sensitivity coefficient of battery swapping service is low, continuing to subsidize vehicle companies may be advisable. Conversely, when the price sensitivity coefficient is high, it may be more effective to provide subsidies to consumers or battery manufacturers.

Generic Multi-Agent AI Framework for Weighted Dynamic Corridor Price Optimisation

The objective of this analysis is to address the challenges encountered by pricing systems in managing real-time market dynamics. This study presents a fundamental theoretical framework focused on taxonomy and ontology for a domain-specific multi-agent artificial intelligence (AI), serving as an internal price advisor to optimize pricing strategies for products and services. The system is designed to function in conjunction with other corporate AI systems and an Enterprise Resource Planning System (ERP). The ERP serves as a high-quality data foundation, and several other internal and external sources can provide essential data with varying quality. Methods: The proposed AI model builds upon the Weighted Dynamic Corridor Price Optimization framework, which integrates cost-plus and value-based pricing methodologies within a non-linear price corridor bounded by lower and upper thresholds. In the context of supply chain integration, fully-cooperative pricing models can apply Nash equilibrium to enhance supply chain profitability, whilst semi-cooperative models mitigate information asymmetry through the principal-agent theory. The findings from the theoretical analysis of the generic industry- and product-agnostic multi-agent AI system suggest the system’s potential capacity for dynamically computing optimal prices. A generative AI module could facilitate real-time decision-making, enabling sales teams and similar stakeholders to simulate scenarios and refine pricing strategies. In conclusion, the proposed AI system should be capable of delivering adaptive, context-aware, and data-driven recommendations. Depending on its application, the AI system could become very complex, susceptible to errors, and require significant maintenance. Future research should focus on customizing the proposed AI system for specific industries and product categories and validating its applicability through empirical research.

Q-commerce service with behavior-based pricing: self-logistics or platform-logistics?

PurposeConsidering behavior-based pricing strategy, we explore the choice of instant logistics service model and pricing strategy of Quick-commerce channel.Design/methodology/approachWe adopt the Hotelling framework to develop a two-period game in which two horizontally differentiated suppliers sell repetitively purchased products through a traditional e-commerce channel and an instant e-commerce channel in two periods.FindingsThe results show that: (1) when consumer’s mismatch cost and instant logistics cost coefficient are moderate or relatively high or low, platform-operated logistics (PL) is more beneficial to traditional supplier and traditional e-platform, while Q-commerce platform may prefer self-operated logistics. However, for Q-commerce suppliers, as his/her instant logistics cost coefficient increases, he/she tends to prefer PL. (2) If the instant logistics cost coefficient is moderate, traditional suppliers may always earn more than Q-commerce suppliers in both models, despite the higher commission rate of traditional e-platform. (3) When the instant logistics cost coefficient for Q-commerce suppliers is low, traditional suppliers should significantly reduce price for new customers under PL.Originality/valueOur research constructs a competition between traditional and quick commerce channels, using game theory methods to examine the impact of different instant logistics models on the dynamic pricing strategies, profitability and instant logistics efficiency of these two online channels.

Impact of Service Quality, Pricing Strategies, User Trust, and Technological Innovation in Indonesia's Online Transportation Services Industry

This study investigates the impact of service quality, pricing strategies, user trust, and technological innovation on customer satisfaction in Indonesia's online transportation services industry. Using a sample of 400 respondents, the research employs regression analysis to identify the relationships between these variables. The findings reveal that service quality is the most significant predictor of customer satisfaction, followed by user trust, pricing strategies, and technological innovation. The results highlight the interrelated nature of these factors, suggesting that improvements in one area can positively influence the others. The study underscores the importance of maintaining high service standards, establishing user trust, implementing effective pricing strategies, and leveraging technological advancements to enhance customer satisfaction. These insights provide valuable implications for practitioners aiming to optimize user experiences and foster loyalty in a competitive market.

The influence of service quality, price, and promotion on GO-FOOD user loyalty

This research aims to analyze the impact of service quality, price, and promotion on Go-Food users in Jakarta, Indonesia. A total of 150 respondents from Jakarta participated in this study, providing data through a distributed questionnaire. Utilizing IBM SPSS Ver. 25, the author conducted statistical tests on the collected data. Results revealed that service quality (X1) and price (X2) had no significant impact on customer loyalty. However, the promotion variable was found to significantly influence customer loyalty among Go-Food users in Jakarta. This suggests the need for Go-Food to reassess its service quality and pricing strategies. Additionally, this research provides valuable insights for GoTo investors in their decision-making processes. Future studies could explore other variables affecting Go-Food user loyalty in Jakarta, thereby contributing to the theoretical foundation of online food delivery services

Gated ensemble of spatio-temporal mixture of experts for multi-task learning in ride-hailing system

Gated ensemble of spatio-temporal mixture of experts for multi-task learning in ride-hailing system

Advancing urban electric vehicle charging stations: AI-driven day-ahead optimization of pricing and Nudge strategies utilizing multi-agent deep reinforcement learning

Advancing urban electric vehicle charging stations: AI-driven day-ahead optimization of pricing and Nudge strategies utilizing multi-agent deep reinforcement learning

Service pricing and charging strategy for video platforms considering consumer preferences

AbstractHeterogeneity of consumer preferences is a crucial feature of the platform economy, and service price and charging strategies crucially influence customer choice behavior. To enhance consumer experience and boost product value, video platforms offer value‐added services, also known as premium membership features. For instance, Youku's benefits of value‐added service include seamless video playback, high‐definition picture quality, and exclusive episodes. This study constructs a two‐stage Hotelling model from monopoly to duopoly competition. Considering the heterogeneity of consumer preferences for product quality and platform usage costs, we analyze the impact mechanism of the customer preferences heterogeneity and the service pricing of video platform enterprises. In addition, we analyze the Nash equilibrium strategies of competing enterprises in the competition scenario, and we consider two charging strategies: freemium and bundled sales. The results indicate that the consumer sensitivity factors significantly impact the optimal pricing of services and the profits of enterprises and that this impact varies with the heterogeneity of customer composition and the type of charging strategies. For the optimal solutions in a competition scenario, the proportion of quality‐sensitive customers is positive for the freemium model, whereas it is negative for the bundled sales model. Furthermore, we analyze the impact of heterogeneous customer composition on the choice of charging strategy utilizing numerical analysis. This study provides a theoretical basis and decision support for product development and value‐added service pricing that can be applied to video platform enterprises and other media platforms.

Optimal service caching, pricing and task partitioning in mobile edge computing federation

Optimal service caching, pricing and task partitioning in mobile edge computing federation

A Comparative Study of Customer Perception Towards Various Supermarkets

This research undertakes a comparative analysis of customer perceptions towards different supermarkets, aiming to discern the factors that influence consumer preferences in the retail sector. Employing a mixed-methods research design that includes surveys and in-depth interviews, the study explores key elements such as service quality, product assortment, pricing strategies, and overall shopping experiences that contribute to customer satisfaction and loyalty. The research seeks to identify patterns and variations in customer perceptions across diverse supermarkets, taking into account factors like location, brand reputation, and demographic considerations. Additionally, it aims to uncover the relative importance of specific attributes in shaping customer preferences and loyalty in the highly competitive supermarket industry. The findings of this study are anticipated to provide valuable insights for supermarkets to enhance their strategies, improve customer satisfaction, and remain competitive in the dynamic retail landscape.

Bundling products and service on influencer channels

Bundling products and service on influencer channels

Factors Influencing Customer Decision-Making In Choosing E-Cab Services Over Traditional Taxis In Calabar Metropolis

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.
 

MARKET EXPANSION AND COMPETITIVE POSITIONING IN SATELLITE TELECOMMUNICATIONS: A REVIEW OF ANALYTICS-DRIVEN STRATEGIES WITHIN THE GLOBAL LANDSCAPE

Market expansion and competitive positioning are paramount in the dynamic landscape of satellite telecommunications. This review explores the role of analytics-driven strategies in achieving these objectives on a global scale. Satellite telecommunications providers face intense competition, technological advancements, and evolving customer expectations, necessitating innovative approaches to gain a competitive edge. Analytics plays a crucial role in understanding market trends, consumer behavior, and competitor strategies. By leveraging advanced analytics techniques, companies can uncover actionable insights to inform strategic decision-making. One key area where analytics is instrumental is in identifying untapped market opportunities. Through data analysis, companies can pinpoint underserved regions or niche markets, enabling targeted expansion efforts. Moreover, analytics enables companies to optimize their service offerings and pricing strategies. By analyzing customer preferences, usage patterns, and market dynamics, companies can tailor their offerings to meet specific customer needs. This personalized approach not only enhances customer satisfaction but also improves profitability. Analytics also plays a vital role in enhancing operational efficiency. By analyzing data from satellite networks, companies can identify potential bottlenecks, optimize resource allocation, and improve overall network performance. This not only reduces operational costs but also enhances service reliability and quality. Furthermore, analytics-driven strategies are instrumental in competitive positioning. By analyzing competitor performance, market trends, and customer feedback, companies can identify areas where they can differentiate themselves. This could include offering innovative services, improving customer support, or enhancing network coverage. In conclusion, analytics-driven strategies are crucial for satellite telecommunications companies looking to expand their market presence and enhance their competitive positioning. By leveraging data analytics, companies can uncover valuable insights that inform strategic decision-making, optimize operations, and drive innovation. In an increasingly competitive landscape, the ability to harness the power of analytics is key to long-term success in the satellite telecommunications industry.
 Keywords: Market Expansion, Competitive, Positioning, Satellite, Communications.

Telehealth Consultation for Malaysian Citizens' Willingness to Pay Assessed by the Double-Bounded Dichotomous Choice Method.

Re-envisioning healthcare in technology tools includes robust utilisation of telehealth, improvement in access, quality, care efficiencies and cost-effectiveness of healthcare services. In reality, the technology's potential to transform healthcare may be limited by the ability to pay for it. This study aims to estimate Malaysian citizens' willingness to pay (WTP) for telehealth consultations and determine the factors contributing to it. This is vital to inform decision-making about expansion, preferences and deployment of a pricing strategy for telehealth services. A random sample of 220 adult Malaysians was surveyed using social network services (SNS). Three different WTP bid arrays were identified and each respondent received a randomly drawn bid price. The WTP fee for using the telehealth consultation for 30 min was measured and estimated using a Double-Bounded Dichotomous Choice (DBDC) and the Random Utility Logit Model. The median WTP was estimated to be RM58 (JPY2,198), RM78 (JPY2,956) for 132 respondents' willingness to use telehealth consultation and RM26 (JPY985) for 51 respondents who were unwilling. Further analysis found that WTP is correlated with the perception and willingness of the respondents to use it. Despite most respondents being willing to pay for telehealth consultations, sociodemographic characteristics and affordability influenced the process of making decisions about WTP for telehealth consultation. This finding suggests that the private sector can play a crucial role in the deployment of telehealth. However, there may be a need to consider affordability and how to increase access and use of telehealth services.

The Effect of Service Quality, Price, and Destination Image on Customer Loyalty in the Tourism Industry in West Java

This research investigates the interrelated factors influencing customer loyalty in the tourism industry of West Java. Through a comprehensive study involving 200 respondents, we examine the impact of service quality, pricing strategies, and destination image on customer loyalty. Utilizing a quantitative analysis approach, the study employs structural equation modeling (SEM) with Partial Least Squares (PLS) to unravel the intricate relationships among these crucial constructs. The research contributes to the existing body of knowledge by offering insights into the specific dynamics shaping tourist allegiance in this unique region. Findings from the study provide practical implications for businesses, policymakers, and destination marketers, enabling them to tailor strategies that enhance customer loyalty and contribute to the sustainable growth of West Java's tourism sector.

A Quantitative Study of The Impact of Supply Chain Management on Customer Satisfaction

With the rapid and drastic changes in the business environment, supply chain management has become one of the key factors for the success of enterprises. This study focuses on exploring the impact of supply chain efficiency on customer satisfaction, with special attention to three key factors: service quality, delivery time and price transparency. Through quantitative analysis, it is found that these factors have a significant effect on improving customer satisfaction. The results show that quality service, efficient delivery and clear pricing strategies significantly improve customer satisfaction. In addition, customer trust has been found to mediate between these factors and customer satisfaction. This study provides practical suggestions for enterprises in supply chain management to enhance their competitive advantage.

The Impact of Service Quality on Customer Satisfaction: The Mediating Effect of Perceived Price in Thailand Small Medium Enterprises

This study investigates the impact of service quality on customer satisfaction, with a special focus on the mediating role of perceived price in the context of Thailand's Small and Medium Enterprises (SMEs). In an era where service quality has become a pivotal factor in differentiating businesses, particularly in the SME sector, understanding its influence on customer satisfaction is crucial. The study also explores how the perception of price plays a mediating role in this relationship, a factor that is particularly relevant in the cost-sensitive market of Thailand. A quantitative research methodology was employed, utilizing a structured questionnaire to collect data from a sample of 324 respondents, comprising customers of various SMEs in Thailand. The questionnaire was designed to measure perceptions of service quality, customer satisfaction, and the perceived price. Statistical analyses, including regression analysis and mediation analysis, were conducted to examine the relationships between these variables. The results of the study are expected to provide insightful implications for SMEs in Thailand, demonstrating how service quality directly influences customer satisfaction and how this relationship is further shaped by the customers' perception of price. This research not only contributes to the academic understanding of these dynamics but also offers practical guidance for SMEs in optimizing their service delivery and pricing strategies to enhance customer satisfaction.

Strategi Penentuan Harga Jasa Pendidikan

Setting prices is a crucial step in ensuring the operational viability of a learning institution. The price of educational services will inevitably be impacted by the current boom in the education sector, which is marked by offers of numerous programs and more facilities. The purpose of this study is to learn more about how much educational services cost. Using books, journals, and other literature as well as reading sources and references from the internet, a qualitative research methodology was employed (library research). The research's findings led to the conclusion that pricing strategies for educational services can be based on value (value-based pricing), competition (competition-based pricing), or cost (cost-based pricing).

Pricing optimization of product line with value-added services considering consumer choice behavior

ABSTRACT The global economy is transitioning from product economy to service economy, and the optimization of product line with value-added services is one of the important issues faced by enterprises. Therefore, this paper studies the pricing optimization of product line with value-added services considering consumer choice behavior. First, we apply the multinomial logit (MNL) model to simulate consumer choice behavior, and establish a MNL-based product line pricing optimization model considering value-added services. Then, the optimal pricing strategies for products and services are solved for three different scenarios: single product with service, homogeneous products with services, and heterogeneous products with services. Finally, through numerical experiments, we analyze the changing trends of the optimal pricing, market share and profit of products line with value-added services with some impact factors, such as product quality, service level, consumer sensitivity, and number of products under three different scenarios. We also obtain some managerial implications when an enterprise develops product line with value-added service.

Two-Sided Beneficial Value-Added Service Investment and Pricing Strategies in Asymmetric/Symmetric Investment Scenarios

We explore media platforms’ investment strategies for two-sided beneficial value-added services, which can directly benefit both consumers and advertisers, and ad pricing strategies by using game theory. We consider an asymmetric investment scenario, scenario A, and a symmetric investment scenario, scenario S, and develop game models under each scenario. First, we obtain the equilibrium investments, prices and profits and analyze the influence of the three important parameters—marginal investment costs, positive consumer effects and negative advertising effects, on the equilibrium outcomes in each scenario. Then we compare these equilibrium outcomes between both scenarios. Finally, we conduct numerical simulations to verify the conclusions obtained in both scenarios. We show that in scenario A, the value-added service levels and ad prices of the investment platforms remain constant and then decrease with marginal investment costs. The ad prices and profits of the investment platforms increase (decrease) with positive consumer effects (negative advertising effects). The same change is true for the value-added service levels only under certain conditions. In scenario S, the value-added service levels of the investment platforms change with positive consumer effects or negative advertising effects only when marginal investment costs are high. The ad prices of the platforms always increase with positive consumer effects but increase with negative advertising effects only when marginal costs are low. The profits of the platforms vary monotonically with negative advertising effects, but not necessarily with positive consumer effects. Compared to scenario S, the ad prices of the investment platforms in scenario A are higher, but that is not always true for the value-added service levels.