Service Pricing Strategies Research Articles

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

Ride-hailing system requires efficient management of dynamic demand and supply to ensure optimal service delivery, pricing strategies, and operational efficiency. Designing spatio-temporal forecasting models separately in a task-wise and city-wise manner to forecast demand and supply-demand gap in a ride-hailing system poses a burden for the expanding transportation network companies. Therefore, a multi-task learning architecture is proposed in this study by developing gated ensemble of spatio-temporal mixture of experts network (GESME-Net) with convolutional recurrent neural network (CRNN), convolutional neural network (CNN), and recurrent neural network (RNN) for simultaneously forecasting these spatio-temporal tasks in a city as well as across different cities. Furthermore, a task adaptation layer is integrated with the architecture for learning joint representation in multi-task learning and revealing the contribution of the input features utilized in prediction. The proposed architecture is tested with data from Didi Chuxing for: (i) simultaneously forecasting demand and supply-demand gap in Beijing, and (ii) simultaneously forecasting demand across Chengdu and Xian. In both scenarios, models from our proposed architecture outperformed the single-task and multi-task deep learning benchmarks and ensemble-based machine learning algorithms.

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

Public charging stations (CSs) serve for electric vehicles (EVs) to charge during urban travel. Optimizing the charging time, location distribution, and power of EVs can increase the revenue of charging system operators (CSOs) and provide flexible regulation resources for the power grid. However, the optimization scheduling of CSs involves the charging choices of various users, which are influenced by their autonomy and bounded rationality. To guide users and encourage their participation in the charging schedule, we introduce the Nudge method from behavioral economics. To achieve collaborative optimization of non-economic Nudges and economic incentive strategies applying to multiple charging stations in a complex nonlinear environment involving users, CSO, and the transportation network, we leverage multi-agent deep reinforcement learning (MADRL). We construct a simulation environment using historical and survey data tailored to real users. This environment facilitates the training of agent groups to enhance decision-making processes. Case studies in a metropolis demonstrate that the agent group aimed at revenue improvement yields significant improvements in the CSO's revenue compared to fixed service fees and pricing strategies without Nudges. Moreover, the agent group aimed at power curve tracking achieves a lower average relative error in aligning the total charging power with the desired curve of the power system. This paper integrates sociological methods into the optimization of physical systems by MADRL, providing a new approach for the scheduling of EV charging considering user behavior.

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

Mobile Edge Computing (MEC) federations aim to establish a joint edge service model between Edge Infrastructure Providers (EIPs) and clouds, facilitating the sharing and utilization of MEC services and resources. However, in such a hierarchical multi-EIP MEC federation environment, optimizing service caching, task partitioning, and pricing strategies to maximize the profits gained by EIPs and minimize the cost of mobile devices (MDs) is challenging. To address this challenge, This paper first formulates a two-stage multi-leader, multi-follower Stackelberg game between EIPs and MDs. Then, a new method combining a Stackelberg-based Multi-Agent Deep Deterministic Policy Gradient (STMADDPG) algorithm and a Transformer-based Popularity Prediction (TPP) model is devised to learn the optimal strategies. Extensive experiments with real-world datasets are conducted to demonstrate the excellent performance of the proposed STMADDPG-TPP method.

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

This study investigates the optimal service pricing strategies for manufacturers within the burgeoning field of influencer live-streaming marketing. By examining a dynamic where manufacturers collaborate with social media influencers, the research evaluates the efficacy of bundling products and services versus separate pricing under varying conditions. The study uncovers that the gap between the two service pricing models will increase as the service cost increases. Moreover, the lower the service cost, the more obvious the relative advantage of the bundling model. That is, bundling is most beneficial when service costs are low, whereas separate pricing becomes advantageous as service costs escalate. In addition, the decrease in the rate of product defects can lead to an increase in the relative advantage of the bundling model. Intriguingly, the optimal promotional approach for influencers shifts in response to these pricing strategies, favoring a combined product-service promotion when services are priced separately. The study further reveals a direct correlation between product defect rates and profitability, especially under separate pricing scenarios. These insights offer valuable guidance for manufacturers and influencers in strategizing their offerings and promotions in the digital marketplace.

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.

An analysis of pricing strategy for bike-sharing services: The role of the inconvenience cost

In actual bike-sharing services, an operator can adopt any of three pricing strategies, namely, pay-per-use (Strategy P), flat-fee (Strategy F) and a hybrid of pay-per-use and flat-fee (Strategy H). When the operator launches the mode of picking up and returning bikes at designated shared bike parking points, users often perceive the inconvenience cost because of having to go to the designated parking points to pick up and return shared bikes. This paper investigates operators’ pricing strategies in monopoly and duopoly markets and analyzes the effects of the inconvenience cost on different pricing strategies. We find that in the monopoly market, it is advantageous for the operator to choose Strategy H if the inconvenience cost is relatively small; otherwise, it is advantageous to choose Strategy F. In the duopoly market, the operator can choose Strategy P. In particular, when the two operators bring the same inconvenience cost to users, there exist two pricing strategy combinations in equilibrium, namely, P/F and F/P. When the two operators bring different inconvenience costs to users, there exist five pricing strategy combinations in equilibrium, namely, P/F, F/P, H/F, F/H and F/F.

СУТНІСНА ХАРАКТЕРИСТИКА ЦІНОУТВОРЕННЯ НА ЕЛЕКТРОПОСТАЧАЛЬНИХ ПІДПРИЄМСТВАХ

The article examines the place of electricity supply enterprises among trade enterprises in Ukraine. The importance of forming an effective pricing strategy and tactics for goods or services produced or provided by an energy industry enterprise was determined. It was revealed that the definition of the essence of pricing at electricity supply enterprises remains logically incomplete, which complicates this process. The main approaches to the interpretation of the concept of "price" and "pricing" have been studied. It is proposed to define the concept of price for electricity supply enterprises – it is a monetary reward that electricity suppliers are willing to pay to producers, which is determined on the basis of the interaction of the laws of cost, demand and supply at a specific time when an agreement is concluded between the electricity supplier and the producer. The purpose of the study is to unify and systematize approaches to determining the essence of pricing at electricity supply enterprises. In the conditions of the instability of the development of enterprises and with the strengthening of the European integration processes of the economy, there is an urgent need to ensure the continuity of activity, which may depend on the effectiveness of the price policy. The sphere of trade in Ukraine is a defining type of activity in the sphere of circulation, which is an intermediate link between the production and consumption of goods and services and ensures a balance between them. The existence of a large number of sellers determines the need to manage the pricing process at the enterprise. According to the data of the State Statistics Service of Ukraine, in the total number of economic entities of Ukraine, in recent years, the largest share belongs to enterprises of wholesale and retail trade. A separate segment of trade enterprises are electricity supply enterprises that provide exchange on the electric energy market and have been operating in Ukraine for a while now. In the conditions of the market economy, for the efficient and profitable operation of the enterprise, it is necessary to choose the most effective strategy and pricing tactics for the goods or services that the enterprise produces or provides.

Seizing the value of data: Selecting appropriate pricing strategies for data-based services in manufacturing

Utilizing data in the industrial environment offers manufacturing companies numerous opportunities to optimize their own processes and develop new service offerings that go beyond existing business models. Many companies have already recognized this potential and have developed their own data-based solutions. But despite these efforts, many of the solutions developed, ultimately fail on the market. This is commonly caused by companies struggling to develop suitable business models for their technical solutions. A crucial factor in this regard is the lack of adequate economic evaluation during the development phase. On the revenue side, the selection of a suitable pricing strategy represents an important decision. It determines the acceptance on the market as well as the profitability of a data-based business model. Due to the growing share of data-based value creation, new challenges and opportunities arise in this regard. This paper presents an approach to select and develop a suitable pricing strategy for data-based services in the industrial environment. For this purpose, challenges in the selection of pricing strategies with a special focus on intangible goods such as data are examined first. Subsequently, existing pricing mechanisms are identified and discussed. Based on this, a process model for determining suitable pricing strategies is derived, which companies can use in the context of their business model development. The method is then validated with an industrial use case and the results are discussed.