The optimization and impact of public sports service quality based on the supervised learning model and artificial intelligence

This study focuses on improving public sports service quality and its social impact. In the modern social environment, public sports service, as a critical channel to promote the national fitness program and improve national physical health, has a direct impact on the public’s participation in sports activities and overall physical health. However, the current public sports service has many deficiencies in terms of facilities, service processes, personnel quality, etc., resulting in uneven service quality, which makes it difficult to meet the growing demand of the public^{16,17,18,19,20}. Therefore, optimizing public sports service quality and improving public sports participation and physical health levels has become an urgent problem to be solved in this study.

The theoretical framework of this study is mainly based on the theory of service quality, public sports service, and IT applications. Firstly, the service quality theory is the cornerstone of this study. This theory emphasizes that service providers should pay attention to customers’ needs and expectations, and satisfy customers’ satisfaction by providing high-quality services. In the field of public sports services, this means the need to pay attention to the needs and expectations of the public on sports facilities, service processes, personnel quality, and so on, and optimize the service quality accordingly. Secondly, the public sports service theory provides concrete theoretical support for this study. The theory emphasizes the public welfare and universality of public sports services, aiming to promote the development of national fitness by offering high-quality sports services. Based on the relevant viewpoints of public sports service theory, this study analyzes the current situation and influencing factors of public sports service quality and proposes targeted optimization strategies^21,22,23. Finally, the IT application theory furnishes theoretical support for applying a supervised learning model in optimizing public sports service quality. With the continuous development of IT, machine learning techniques such as supervised learning models have been widely used in various fields. In the field of public sports services, the supervised learning model can be used to conduct training and learning from historical data, predict future service demand, optimize resource allocation, and improve service quality^{24,25,26,27,28}.

This study employs multiple research methods to systematically explore how to improve public sports service quality. It mainly includes literature analysis, field research, questionnaire survey^29,30,31, data analysis, and IT application theory^32,33. The details are detailed below.

This study aims to identify key factors that affect public sports service quality through theoretical analysis and empirical research. Moreover, it proposes targeted optimization strategies to enhance public sports service quality, promote the implementation of national fitness programs, and improve the overall physical health level of the population. Through the comprehensive application of various research methods such as field research, literature analysis, questionnaire survey, data analysis, and supervised learning model application, this study can provide comprehensive theoretical support and empirical basis for improving public sports service quality^34,35,36. The theoretical framework of the study is illustrated in Fig. 1.

The theoretical framework of this study.

Figure 1demonstrates that the innovation of the theoretical framework lies in its comprehensiveness and foresight. It innovatively integrates public sports service theory, service quality theory, and IT application theory, constructing a multidimensional and interdisciplinary analytical framework³⁷. This innovation not only breaks through the limitations of traditional research on single theories but also fully considers the driving role of modern IT applications in optimizing the quality of public sports services. Furthermore, this theoretical framework also emphasizes practical application, highlighting the close integration of theoretical guidance and empirical research, furnishing feasible ideas and strategies for improving the quality of public sports services³⁸. Hence, the theoretical framework’s innovativeness plays an essential guiding role in promoting research and practice in public sports services.

Based on this, guided by the theoretical framework, this study innovatively applies supervised learning models to the optimization research of public sports service quality, achieving the construction of technical models³⁹. As a powerful machine learning technology, the supervised learning model can accurately predict future service demands by mining potential patterns and trends in historical data through training and learning⁴⁰. In the domain of public sports services, by utilizing supervised learning models to analyze and process massive service data, key factors affecting service quality can be identified, and resource allocation and service strategies can be optimized accordingly^41,42,43. The results of the technical model construction based on supervised learning models are displayed in Fig. 2.

Technical model based on supervised learning.

In Fig. 2, this study constructs a technical model within the research framework, enabling a more precise assessment of the public’s demand for and expectations of public sports services. Specifically, it allows for an in-depth analysis of the public’s detailed requirements in areas such as sports facility characteristics, service process optimization expectations, and staff competency demands. This, in turn, provides strong support for formulating personalized service plans that align with public needs, effectively enhancing overall public satisfaction and participation enthusiasm. At the same time, applying the technical model has strongly promoted the development of public sports services towards greater intelligence and automation, achieving a significant improvement in service efficiency and quality^44,45,46,47.

The methods employed in this study are diverse and systematic, covering the following aspects:

1. (1)

   Literature review: This study conducts a comprehensive and in-depth review of relevant domestic and international literature. The focus is on the research status, existing issues, and improvement strategies concerning the quality of public sports services. By systematically summarizing existing research findings, this study extracts valuable theoretical insights and practical guidance, laying a solid theoretical foundation and providing abundant practical reference examples.

2. (2)

   Field research: The study involves detailed field investigations of various public sports facilities across different regions. It aims to thoroughly understand the usage, maintenance, and user feedback regarding these facilities. By collecting firsthand data, the study gains deep insights into the specific problems and challenges faced by public sports services in actual operations, offering detailed practical evidence for subsequent research.

3. (3)

   Survey questionnaire: A multidimensional questionnaire covering aspects such as satisfaction with sports facilities, service process satisfaction, and staff quality satisfaction is designed and widely distributed to different groups. By gathering extensive user feedback and applying scientific statistical analysis methods, the study aims to gain a deep understanding of the public’s actual needs and expectations, providing reliable quantitative evidence for optimizing service quality.

4. (4)

   Data analysis: This study utilizes various statistical methods. Descriptive statistics are first applied to display basic survey results and data distribution characteristics. Based on this, correlation and regression analysis are employed to investigate the extent to which different factors impact the quality of public sports services, accurately identifying key influencing factors and providing strong data support for formulating optimization strategies.

The application of IT is primarily reflected in the construction and application of supervised learning models. By extensively collecting and organizing large amounts of historical data, and applying supervised learning algorithms for deep training and learning, a model with strong predictive capabilities is developed. This model can achieve accurate predictions of future service demands, optimize resource allocation, formulate personalized service plans, and effectively enhance service quality. Specifically, based on users’ historical behavior and feedback data, the model can accurately identify user needs and expectations, enabling the customization of personalized services. Additionally, the application of the model drives the intelligent and automated transformation of public sports services, significantly improving service efficiency and quality. Through the organic combination and collaborative application of various research methods, this study systematically analyzes the current state and issues of public sports service quality and proposes practical optimization strategies. The ultimate goal is to comprehensively improve public sports service quality, vigorously promote the implementation of national fitness programs, and effectively enhance public participation in sports and overall health. Throughout the research process, literature review, field research, survey questionnaire, data analysis, and the construction and application of technical models complement and collaborate, collectively advancing the study’s development^4,48,49.

The methods integrated within this study’s framework need to be detailed about public sports service quality. In terms of literature review, the study reviews the development and trends of service quality-related theories from numerous academic papers, policy documents, and industry reports. It further examines key factors influencing service quality and their mechanisms from different theoretical perspectives. For example, service management theory analyzes the impact of service process design and personnel management strategies on service quality; Customer satisfaction theory explores the role of public expectations and perception gaps in service quality evaluation. This provides solid theoretical guidance for subsequent research methods. Field research plays a crucial role in addressing the limitations of literature review. Additionally, the functional model’s application processes and rules in different public sports service scenarios need to be developed in detail⁵⁰. For instance, in the service management scenarios of large sports venue, the functional model should dynamically allocate service resources and monitor service quality in real-time, based on factors such as venue event schedules, audience flow, and facility usage. In operation scenarios of community sports activity centers, the model should formulate personalized service plans and activity arrangements based on characteristics such as the community’s age structure, exercise preferences, and participation time patterns. By conducting in-depth analysis and rule formulation for different application scenarios, the study ensures the efficient operation of the functional model in diverse public sports service environments. Thus, it offers strong technical support and decision-making assurance for service quality improvement⁵¹.