Frontiers in Business, Economics and Management ISSN: 2766-824X | Vol. 19, No. 3, 2025 25 A Study on Customer Perceived Service Quality of E- Commerce Enterprises in China Xiangzhi Zeng *, Candido Perez Baguio University, Department of Graduate School, Baguio City, Philippines * Corresponding author: Xiangzhi Zeng (Email: 412862520@qq.com) Abstract: The customer's perceived service quality determines the survival and development of e-commerce enterprises. In the fiercely competitive e-commerce field, e-commerce enterprises need to continuously improve their customer service management level, and the application of big data can optimize the customer service management of e-commerce enterprises. The customer's perceived service quality determines the survival and development of e-commerce enterprises. In the fiercely competitive e-commerce field, e-commerce enterprises need to continuously improve their customer service management level, and the application of big data can optimize the customer service management of e-commerce enterprises. This paperThe customer's perceived service quality plays a decisive role in the survival and development of e-commerce enterprises. In the fiercely competitive e-commerce market environment, improving the customer service management level is a key task for e- commerce enterprises. Research on customer perceived service quality is helpful to make a scientific and objective judgment on the service quality of e-commerce enterprises, which has practical significance for the development of enterprises and can provide reference and guidance for the development of e-commerce enterprises. Keywords: E-commerce; Customers’ perceived service quality; Big data; Market Environment; Enterprise Development. 1. Introduction In order to make the research more specific and in-depth, this paper selects the customer-perceived service management of e-commerce enterprises as the research object. Influenced by the ubiquity of big data, e-commerce enterprises have embarked on the path of data-based development. Many e-commerce companies have introduced various big data technologies and management to improve the operational management level of e-commerce enterprises [1]. Customer service management, as an indispensable part of the management system of e-commerce enterprises, has also applied various big data technologies. Therefore, it is very necessary and important to optimize the customer service management of logistics enterprises based on big data. 2. Data and Methods The survey subjects of this paper are online shopping customers. In order to save time, effort, and be efficient, the researchers decided to use online survey to obtain the required survey information. an online questionnaire software to collect questionnaire information from respondents at a (specify the period collected.) was used. This software is called "Questionnaire Star" and could collect data and conduct statistical analysis. Considering the convenience of information acquisition and the representativeness of the questionnaire, this paper takes online shopping residents as the object and conducts a sample survey on the customer perceived service quality of e-commerce companies, including a total of 270 respondents from were. In addition, this paper also adopts the literature research method, which provides a theoretical and practical basis for this paper. 3. Problems in the Perception of Service Quality by Customers of Online Stores Lack of Customer Relationship Management System With the increasingly fierce market competition, a large part of the competition between logistics enterprises are reflected in the level and quality of service. Service has become a magic weapon for logistics enterprises to gain a competitive advantage. However, most enterprises in the market fail to establish such a typical data development application system as customer relationship management with high quality. The statistics of marketing, service, and data with customers are not well controlled. Although some enterprises have accumulated certain customer information, they lack effective management of customers and their information by using advanced scientific management methods. It is easy for enterprises to lose the opportunity for development and is not conducive to grasping market opportunities [4]. 3.1. Slow Service Response Slow service response is reflected in the untimely response of customer service. During the peak period of consumer consultation such as e-commerce promotions, the customer service staff of the enterprise online store is insufficient and unable to respond to customer messages in time. Many customers must wait for several hours or even the next day to receive a reply after sending a message, causing customers to lose their enthusiasm for buying and choose other stores with faster response. For example, during the "Double Eleven" event, the average response time of the customer service of a clothing enterprise online store exceeded 30 minutes. Many customers gave up placing orders due to the long waiting time. The order loss rate due to slow response during the event was as high as 20%. 26 3.2. Lack of Professionalism in Service Lack of professionalism in service is reflected in the lack of product knowledge of customer service. Customer service staff do not have a deep understanding of the products they sell and cannot accurately answer customers' questions about product functions, materials, and usage methods. In a digital product online store, when a customer asked about the night scene mode effect of a certain mobile phone, the customer service staff could not describe it clearly or even gave wrong information, which affected the customer's trust in the product and thus affected the purchase decision. 3.3. Inadequate After-Sales Guarantee Many e-commerce companies do not realize the importance of customer relationship management and customer service management. In the process of customer service, they simply interact with customers and do not analyze customer needs from multiple perspectives, resulting in a decline in customer satisfaction with the service [3]. For example, this paper randomly surveyed domestic online shopping customers on the perceived service quality of e- commerce companies. The number of survey samples was 270. The results showed that the difficulty in meeting customers' diverse service needs is an important reason affecting customer service satisfaction. As shown in Table 1, the survey results show that customers' satisfaction (very satisfied + satisfied) with six indicators (untimely customer service response, insufficient product knowledge, irregular service process, complex return and exchange policy, low efficiency of after-sales response processing, and slow logistics) ranged from 51.48% to 72.96%, The highest satisfaction rate was for low after-sales response processing efficiency and irregular service process. However, all indicators failed to reach a satisfaction level of 80% or even higher, indicating that e-commerce companies still have a long way to go in meeting the diverse needs of customers. Table 1. Customers’ perceived service satisfaction of e-commerce companies Source: Author Project/Satisfaction (%) Very satisfied Satisfied common Dissatisfied Very dissatisfied Satisfaction with customer service response 20.37 46.67 32.22 0.74 0 Satisfaction with logistics speed 18.89 42.96 37.41 0.74 0 Satisfaction with the service process 22.59 40.37 34.44 1.85 0.74 Satisfaction with product perception 21.11 51.85 25.56 1.48 0 Satisfaction with after-sales processing efficiency 18.25 32.96 43.7 3.7 1.1 This table, titled "Customers’ perceived service satisfaction of e - commerce companies", presents data on customers' satisfaction levels across five different aspects of e - commerce services. The satisfaction levels are categorized into five groups: "Very satisfied", "Satisfied", "common", "Dissatisfied", and "Very dissatisfied", with the percentages of customers in each group for each service aspect shown. Satisfaction with customer service response: Over 67% (20.37% + 46.67%) of customers are either very satisfied or satisfied. Only a small proportion (0.74%) is dissatisfied, and none are very dissatisfied. Satisfaction with logistics speed: Around 62% (18.89% + 42.96%) of customers are very satisfied or satisfied. The dissatisfied proportion is 0.74%, with no very dissatisfied customers. Satisfaction with the service process: Approximately 63% (22.59% + 40.37%) of customers fall into the very satisfied or satisfied categories. However, a slightly higher percentage (1.85% dissatisfied and 0.74% very dissatisfied) shows some negative sentiment. Satisfaction with product perception: Nearly 73% (21.11% + 51.85%) of customers are very satisfied or satisfied, and 1.48% are dissatisfied, with no very dissatisfied customers. Satisfaction with after - sales processing efficiency: The lowest proportion of very satisfied and satisfied customers (18.25% + 32.96% = 51.21%). A relatively higher percentage (3.7% dissatisfied and 1.1% very dissatisfied) indicates more room for improvement in this area. From the table we can get, Overall positive sentiment: In general, e - commerce companies are performing well in most service aspects, as indicated by the high percentages of satisfied and very satisfied customers across multiple areas. Areas for improvement: After - sales processing efficiency stands out as an area that needs enhancement. E - commerce companies should focus on optimizing after - sales procedures to reduce dissatisfaction. Additionally, while the percentages are small, any dissatisfaction in other areas like the service process should also be addressed to maintain and improve overall customer satisfaction. Customer service and product perception strengths: The relatively high satisfaction levels in customer service response and product perception can be leveraged as competitive advantages. Companies can continue to invest in these areas to further strengthen their positive reputation. Figure 1. Analysis of the proportion of factors affecting the development of e-commerce enterprises Legend: 1. E-commerce enterprises lack strategic positioning and long-term planning. 2. E-commerce enterprises fail to meet the diverse needs of customers. 3. Basic logistics services are imperfect. 4. Value-added logistics services are missing. 5. Other reasons. From the chart, we know that E-commerce enterprises fail to meet the diverse needs of customers. 3 accounts for the largest proportion, which is 49.63%. This shows that the perceived service quality of customers directly affects the 27 development of China's e-commerce enterprises. When customers perceive high service quality, they will have trust and goodwill towards the enterprise, and are more likely to become loyal customers of the enterprise, make repeated purchases and long-term consumption, thereby promoting the development of the enterprise and increasing its profits. For example, Haidilao has established a good image in the hearts of customers with its high-quality service, and many customers will patronize it many times because of its considerate service. 4. Measures and Methods for Optimizing Customer Service Management of E-Commerce Enterprises Based on Big Data 4.1. Optimizing Basic Customer Service First, it is crucial to improve the response speed of e- commerce companies' customer service. AI + big data technology can be used to collect data from various online shopping customers, and then organize and analyze it. When the e-commerce customer service is not online, AI can be used to provide intelligent answers. Secondly, warehousing services need to be optimized. With the help of big data, a "virtual inventory" database can be developed to update the inventory information of goods at any time, so that customers can intuitively understand the inventory status, turnover status, and sustainability of goods. Finally, it is necessary to optimize the innovation of distribution services. Use big data technology to build a distribution database, which contains customer data, vehicle data, road condition data, product data, etc., and build a distribution information management system so that customers can quickly query the distribution quantity, location, time, and other information through the system [4]. 4.2. Optimize Value-Added Customer Service The core of value-added customer service lies in going beyond basic needs and improving customer stickiness, satisfaction and lifetime value through differentiated, personalized and high-value services. Utilize AI+ big data driven predictive services to analyze user behaviors (such as browsing, adding to cart, customer service consultation records), predict potential problems and proactively reach out (such as compensation plans before logistics delays). For example: Taobao’s “fast refund for undelivered items” and Amazon’s “prepayment for lost packages”. Big data driven predictive services can provide technical basis and decision- making reference for further optimizing customer service quality, information tracking, claims protection and other value-added service indicators in e-commerce enterprise customer service. 4.3. Create an E-Commerce Corporate Culture of "Customer Service First" The key to e-commerce service competition is not the number of service items and products, because these are easy to imitate, but the service culture. Excellent service managers will tirelessly explain their service concepts to customers at the front line and provide services to customers in person. This allows senior management to get in touch with the problems encountered by customers, understand the hard work of front-line employees, and let all employees see the importance of customer service. This is necessary because only participatory leaders can truly let employees experience the essence of "culture" and employees can have the greatest investment. In addition, establishing a customer-oriented organization is also an important part. This organizational structure should convey a clear message to employees: the responsibility of front-line employees is to satisfy customers; the responsibility of managers is to support employees so that they can better serve customers. In this way, front-line employees should be fully empowered because it is the front- line employees who truly understand customers [5-9]. 4.4. Establish a Targeted E-Commerce Enterprise Service Level Evaluation System The customer service level provided by e-commerce enterprises needs to establish a complete evaluation system. According to changes in market conditions, competitor conditions, customer needs, product characteristics, etc., the implementation of customer service should be evaluated regularly to check whether there are claims, mismatches, late delivery, damages, etc., to understand whether the current service level meets the specified standards, so as to make corresponding improvements [9-14]. 5. Conclusion This paper adopts the method of empirical research, through literature research and questionnaire survey, and reveals that the main reason why my e-commerce enterprises are dissatisfied with online shopping customer service is that the customer service is not timely and the after-sales guarantee is weak. It is proposed that based on improving services, the level of customer service management should be improved by cultivating advanced corporate culture and establishing a customer service evaluation system, so as to improve customer service satisfaction. This is very important for improving the competitiveness and profitability of logistics enterprises (especially e-commerce enterprises), and it is also conducive to improving the customer service level of the entire industry. Acknowledgements The research of this paper did not receive financial support, and the required funds were raised by the author himself. Thank you to mentor Candido Perez, and to the other teachers at the Graduate School of Baguio University. References [1] Dandan, S. & Xiaohui, Q. (2020). Research on Decision Optimization of Terminal Distribution Mode of E-commerce Express Delivery Enterprises Based on Big Data. Science & Technology and Innovation (21), 51-52. DOI: 10.15913/j.cnki.kjycx.2020.21.022. 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