Service Mode Research Articles

Exploring the Impact of Online Medical Team Engagement on Patient Satisfaction: A Semantic Features Perspective.

Online medical teams (OMTs), a new mode of online healthcare service, have emerged in online health communities (OHCs) in China. This study attempts to explore the underlying mechanism of how OMTs' engagement influences patient satisfaction through the lens of semantic features. This study also scrutinizes the moderating effect of multiple specializations on the link between OMTs' engagement and semantic features. We utilized a linear model that had fixed effects controlled at the team level for analysis. A bootstrapping approach using 5000 samples was employed to test the mediation effects. The findings reveal that OMTs' engagement significantly improves language concreteness in online team consultations, which subsequently enhances patient satisfaction. OMT engagement has a negative impact on emotional intensity, ultimately decreasing patient satisfaction. Multiple specializations strengthen the impact of OMT engagement on both language concreteness and emotional intensity. This study contributes to the literature on OMTs and patient satisfaction, providing insights into patients' perceptions of OMTs' engagement during online team consultation. This study also generates several implications for the practice of OHCs and OMTs.

Research on Library Space Construction and Services under the Background of Smart Library

The rapid development and application of the new generation of digital intelligence technology, as well as the continuous growth of users' personalized needs, promote the continuous innovation and reform of library functions and services. Especially with the rise of the meta-universe, the service mode of traditional library is undergoing innovation and reshaping from document service to information service, knowledge service and space service. As a "constantly growing organism", in the process of accelerating technological upgrading and deepening humanistic concepts, the concept, connotation, characteristics and construction path of smart space also develop and change. This paper mainly studies the transformation of library space construction and service under the background of the development of new generation technology and the construction of smart library, so as to better guide the development of smart space.

Innovation and Practice of "yae920.com" One-stop Service Mode from the Perspective of Digital Transformation

With the deepening of digital transformation, the medical service industry is facing huge innovation opportunities and challenges. This paper studies the "yae920.com" one-stop service model and discusses the impact of digital transformation on its service innovation and practice. The study first analyzed the overall impact of the digital transformation on the medical service industry, including the optimization of the service process, the improvement of the patient experience, and the improvement of the operational efficiency. Then, through the method of case study, it expounds how "yae920.com" innovates the one-stop service mode in the process of digital transformation, including the integration and optimization of functions such as online appointment registration, online consultation and consultation, electronic prescription circulation, online drug purchase and distribution and so on. The research also deeply explores the challenges and coping strategies encountered by "yae920.com" in the process of service model innovation, as well as the practical results achieved. The research results show that the digital transformation provides strong support for the innovation of the "yae920.com" one-stop service mode, and effectively improves the service efficiency and patient satisfaction. The research in this paper has certain reference value for promoting the digital transformation and service mode innovation of the medical service industry.

Knowledge collaboration and online medical teams’ performance: a multiple participation perspective

PurposeOnline medical teams (OMTs) have emerged as an innovative healthcare service mode that relies on the collaboration of doctors to produce comprehensive medical recommendations. This study delves into the relationship between knowledge collaboration and team performance in OMTs and examines the complex effects of participation patterns.Design/methodology/approachThe analysis uses a dataset that consists of 2,180 OMTs involving 8,689 doctors. Ordinary least squares regression with robust standard error is adopted for data analysis.FindingsOur findings demonstrate a positive influence of knowledge collaboration on OMT performance. Leader participation weakens the relationship between knowledge collaboration and team performance, whereas multidisciplinary participation strengthens it. Passive participation and chief doctor participation have no significant effect on the association between knowledge collaboration and OMT performance.Originality/valueThis study provides valuable insights into how knowledge collaboration shapes OMTs' performance and reveals how the participation of different types of members affects outcomes. Our findings offer important practical implications for the optimization of online health platforms and for enhancing the effectiveness of collaborative healthcare delivery.

Promoting sales of knowledge products on knowledge payment platforms: A large-scale study with a machine learning approach

With the digital transformation of the global economy, a new mode of knowledge service has emerged on open innovation platforms such as those for the sharing economy. This mode is the paid knowledge-sharing service, where knowledge providers share knowledge with only those who have paid for it. Since an individual customer's purchases are influenced by others around them, we adopted social influence theory to explain sales of such services on paid knowledge-sharing platforms. A machine learning approach was applied to analyze 27,223 text reviews from the Zhihu Live platform (a well-known and large-scale open knowledge community in China). Hierarchical regression models were built to verify twelve proposed hypotheses about the knowledge providers, knowledge quality, interaction quality, and ratings. The results confirm the positive effect on sales of responsiveness (a dimension of interaction quality), and the negative effect on sales of free provider-driven knowledge contributions.In summary, this study provides a comprehensive framework for antecedent factors of sales of knowledge-sharing services. By introducing to knowledge management notions from the field of e-commerce (e.g., price, quality), this study broadens the understanding of the free-to-paid phenomenon on knowledge-sharing platforms.

Study on low-carbon service mode of park-level integrated energy system with flexible supply and demand balance

Against the backdrop of “carbon peaking and carbon neutrality” goals in China, the park-level integrated energy system is a significant approach to meeting the energy consumption demand of users and improving the utilization rate of new energy. To take into account both the interests of integrated energy services (IES) providers and the current power market rules in China, targeting at low-carbon energy consumption, a balancing service mode for integrated energy services providers is created herein based on the idea of balancing multiple interests of regional integrated energy services providers. It aims to break down the market barriers and address the tricky problem that the integrated energy services industry fails to establish a sophisticated industrial system under the original mode. Combining the integrated energy services with the auxiliary market of power balance, the paper analyzes the characteristics of energy flow within the system, and puts forward the optimization scheme of regional integrated energy balancing services under the low-carbon background. The objective is solved by Mayfly algorithm and compared for analysis, and the results show that the optimal daily operating cost is 2632.59 yuan and the daily carbon emission is 3869.90 kg under the typical industrial scenario. The examples provided here show that the optimization plan for integrated energy balancing services can reduce carbon emissions from the park-level integrated energy system and boost the revenue for integrated energy service providers. It provides theoretical support for the green transformation of energy enterprises and promotes the healthy development of the global integrated energy industry.

Optimization of physical education teaching resources and service mode under the background of big data and cloud computing

With the rapid development of big data and cloud computing, the field of physical education has begun to actively explore the application of these new technologies. Big data can collect and analyze a large amount of teaching information, help understand students’ learning needs and preferences, optimize resource allocation, and improve teaching efficiency. Cloud computing can realize the online and personalized teaching resources and services, providing convenient and rich learning experience. This study first analyzes the role and influence of big data and cloud computing in the optimization of physical education teaching resources and service mode, and then verifies the actual effects of these technologies through empirical research, analyzes the existing problems and potential challenges, and puts forward corresponding solutions and suggestions. The results show that big data and cloud computing help to improve the efficiency and user satisfaction of physical education, and have important value in promoting the modernization of physical education.

Catalyzing the Success of Implementation of After-School Physical Activity Program in Primary School under the “Double-Reduction” Policy

The implementation of “Double-Reduction" policy creates a suitable external environment for the further development of after-school physical education services. In this study, literature review, questionnaire and interview methods are used as the main research methods to investigate the development status of after-school physical education services in urban primary schools in Guilin under the “double-reduction" policy environment, and to analyze and discuss the main influencing factors of after-school physical education services, such as coverage, contents, form and duration, participation and service mode, as well as quality and evaluation. The results revealed that: Under “double-reduction" policy, the after-school PE service coverage of primary schools in Guilin needs to continue to expand, and should strive to reach full coverage; Parents and students have strong demand for diversified after-school PE services, but there is a shortage of PE teachers, insufficient benefit guarantee for teachers to participate in after-school services, and the lack of quality and evaluation system. The paper suggests that relevant government departments should formulate after-school PE service policies to strengthen guidance, integrate high-quality after-school PE resources to participate in after-school service by purchasing services, strengthen the motivation of PE teachers to participate in after-school service, construct a reasonable after-school PE service evaluation system, and improve the quality of after-school PE service.

Coordination of networking and computing: toward new information infrastructure and new services mode

Coordination of networking and computing: toward new information infrastructure and new services mode

Studying of Community Book Resources Sharing Service Design Based on Social Behavior Organization

This article studies the design of community book resource sharing services, analyzes the nature of social behavior organizations and how to effectively intervene through design methods, analyzes the advantages and disadvantages of existing competitive products, observes the needs of community residents for book resource sharing, and conducts service design research from the perspective of social behavior organizations. Through the "Book · Meeting" - Community Resident Book Resource Sharing Service System, it has been put into practice. We carry on innovation design from reading in idle resources sharing, planning and implementation, online interactive sharing, offline communication experience, build “read + share” community books resources sharing service system based on social behavior, carry on the practice and verification, conclude that studying service mode on social behavior organization is feasible, realize interdisciplinary research and broaden the research field of community development.

Survey on the Demand for Elderly Care Services of Community Residents in Beijing and Analysis of Influencing Factors

Objective: To investigate the current situation of the demand for geriatric care services of community residents in Beijing and analyse the factors affecting it, so as to provide a reference basis for meeting the demand for diversified and professional geriatric care services. Methods: A random sampling method was used, employing a self-made questionnaire to randomly survey 1558 elderly individuals at community health service centers in eight urban districts where elderly care centers are planned to be built, analyzing the influencing factors of different characteristics of the elderly care service needs from three aspects using a dichotomous logistic regression model: predisposing, enabling, and need factors.Results: 69.7% of the elderly had the need for home care services, 22.8% wanted to get care services at elderly care centres, 15.9% wanted to get care services at nursing homes, 12.3% had the need for community care services, and 7.4% didn't know where to get care services; 68.5% had the need for care services for the elderly with disabilities/semi-disabilities, 58.0% for care services for the elderly with dementia, 58.0% for care services for the elderly with common diseases, and 58.0% for care services for the elderly with dementia. 58.0 per cent, 54.7 per cent for care for the elderly with common or frequent illnesses, 34.9 per cent for rehabilitation training, 33.0 per cent for plumbing care, and 7.5 per cent for hospice/hospice care. At the same time, there were urban-rural differences in the demand for elderly care services, with suburban elderly having a higher demand for care services than urban ones (P < 0.05). Elderly people's demand for care services was mainly related to age, place of residence, and gender in the causative factors, mode of residence and physical condition in the able factors, and mode of care services and care needs in the need factors(P <0.05). Conclusion: The demand for elderly care services is differentiated by the factors of residence, age and gender; accurately matching the demand for elderly care services, innovating the mode of elderly care services and improving the quality are important strategies to improve the elderly health service system.

Study on the Innovative Grid-based Party Building Governance in Tai ‘an City

The leadership of party building is the key content of grassroots work, the integration of various elements and the cohesion of development forces, and the basis for the embodiment of people’s sense of integration and happiness. In recent years, Tai ‘an city has actively implemented the leadership policies of the party and the state, after comprehending the internal logic of party building leadership. The city relied on intelligent platforms to innovate service modes and new methods of grid governance of party building leadership through the establishment of micro-grids, the aggregation of micro-forces, the investigation of micro-demands, the provision of micro-services, and other practices, thus striving to achieve fine, efficient and convenient party building management.

Reliability analysis of intelligent manufacturing systems based on improved FMEA combined with machine learning

Along with the booming of intelligent manufacturing, the reliability management of intelligent manufacturing systems appears to be becoming more significant. Failure mode and effects analysis (FMEA) is a prospective reliability management instrument extensively utilized to manage failure modes of systems, products, processes, and services in various industries. However, the conventional FMEA method has been criticized for its inherent limitations. Machine learning can handle large amounts of data and has merits in reliability analysis and prediction, which can help in failure mode classification and risk management under limited resources. Therefore, this paper devises a method for complex systems based on an improved FMEA model combined with machine learning and applies it to the reliability management of intelligent manufacturing systems. First, the structured network of failure modes is constructed based on the knowledge graph for intelligent manufacturing systems. Then, the grey relation analysis (GRA) is applied to determine the risk prioritization of failure modes. Hereafter, the k-means algorithm in unsupervised machine learning is employed to cluster failure modes into priority classes. Finally, a case study and further comparative analysis are implemented. The results demonstrate that failure modes in system security, production quality, and information integration are high-risk and require more resources for prevention. In addition, recommendations for risk prevention and monitoring of intelligent manufacturing systems were given based on the clustering results. In comparison to the conventional FMEA method, the proposed method can more precisely capture the coupling relationship between the failure modes compared with. This research provides significant support for the reliability and risk management of complex systems such as intelligent manufacturing systems.

Qbnb: An innovative C2B2C2B2C e-commerce mode for integrated on-demand services.

The traditional supply-side-driven e-commerce modes provide consumers with massive amounts of structured information about goods and services. Due to the lack of a tailor-made ability to describe, explain, and accurately understand unstructured service demands, existing technologies and service modes still struggle to fully explore, articulate, and meet the personalized, high-quality, and urgent service demands of the disadvantaged groups in e-commerce. This paper innovatively proposes the concept of "integrated services on demand" and develops its C2B2C2B2C-based "Qbnb" e-commerce mode, operation mechanism and intermediary platform architecture. After conducting exploratory operation training, it demonstrates that the Qbnb mode can effectively achieve centralized allocation of idle social surplus service capacity to cater to the needs of disadvantaged groups in e-commerce. Compared to the traditional e-commerce service mode, Qbnb will significantly expand service demand and capacity, achieve higher service efficiency, and create a broader service consumption market, resulting in many more job opportunities.

Customers’ Cue Utilization in Delivery Restaurant Selection and Its Changes With Different Health Risks

Amid Covid-19, restaurant customers have substantially turned to delivery services. Given that table service and ambience are absent in the delivery service mode, cue utilization for restaurant delivery could be different from that in dine-in consumption. Furthermore, increased hygiene and health concerns may lead to changes in cue utilization patterns after the pandemic. Therefore, we explored how restaurant type and its interactions with brand and review rating affected delivery sales and whether their sales effects changed according to the severity of infection risk. Fixed-effects estimation and marginal analysis were employed to investigate 579,858 observations from 193,286 restaurants in China between 2019 and the second quarter of 2020. The findings revealed that full-service and/or branded restaurants had higher delivery sales than other groups. Interaction effects between restaurant type and brand as well as restaurant type and review rating were also found. Theoretical and practical implications for effective cue utilization are discussed.

The Relationship between Privacy Invasion of Smart Services and Consumers' Intention to Use

While the wide application of smart technology in services brings efficiency and convenience to consumers, it also can't avoid bringing some negative impacts. Nowadays, the problem of privacy invasion raises concerns about the issues of smart services and directly affects consumers' attitudes towards the use of smart services. This study aims to explore the impact of privacy invasion in smart services on consumers' intention to use them. The results of the study emphasize that privacy invasion has a significant negative impact on consumers' intention to use smart services. The conclusions of the study play a theoretical role for enterprises to grasp the psychology of smart service consumers and improve the mode and process of smart services.

The flexible airport bus and last-mile ride-sharing problem: Math-heuristic and metaheuristic approaches

Airport buses play a crucial role in addressing the last-mile problem of air travel, especially in cities and countries lacking inner-city rail transit systems. Nevertheless, airport buses are currently witnessing a decline in ridership due to drawbacks such as long departure intervals, inflexible stops, and considerable distances between stops. Consequently, delivering high-quality airport bus services has become a pressing concern for public transport operators. Motivated by new flexible buses and ride-sharing services, this paper explores a flexible airport bus service that integrates ride-sharing services for passengers traveling from bus stops to their destinations. This problem entails integrated decisions involving bus stop selection, passenger assignment to drop-off bus stops, as well as bus and ride-sharing routing. Accordingly, this problem presents more challenges in decision-making than traditional flexible bus or ride-sharing routing problems. We first develop an arc-based mixed-integer linear programming model. Subsequently, we design a double decomposition math-heuristic algorithm that builds upon logic-based Benders decomposition and column generation algorithms to obtain a near-optimal solution within practical computation time limits for practical-scale instances. Additionally, we implement an adaptive large neighborhood search algorithm to evaluate the solution quality of this math-heuristic algorithm and to solve large-scale instances. To validate the effectiveness of both the model and the algorithms, we conduct numerical experiments using instances derived from Shenzhen airport bus lines. The experimental results demonstrate that the flexible service mode offers significant advantages in reducing both passenger ride time and vehicle mileage over traditional airport bus or taxi modes.

Cross-sectional Analysis of Health Behavior Tracking, Perceived Health, Fitness, and Health Literacy Among Active-Duty Air Force Personnel.

There is a paucity of evidence connecting health literacy, perceived wellness, self-reported fitness activity, or military readiness to wearable devices. Moreover, we do not currently know the prevalence and impact of health tracker device use in the active-duty Air Force population. This prospective cross-sectional survey assessed self-reported fitness activity, health-related quality of life, health literacy, and health behavior tracking practices and preferences among active-duty Air Force service members. Four hundred twenty-eight respondents completed an online survey, with 247 selecting tracking a health behavior and 181 selecting that they did not track a health behavior. Demographic characteristics of the sample showed no significant differences in age, sex distribution, or mode of service. We found that there were no significant differences in self-reported aerobic and strength training frequency, health literacy, or health-related quality of life. More than half of nontracking respondents either had not considered or had no interest in tracking health behaviors. Nearly three-quarters of tracking respondents tracked more than one health behavior. Further research could explore the extent to which these technologies improve fitness, health outcomes, and overall readiness in the military, involving longitudinal studies tracking fitness improvements and health outcomes among service members using wearable devices.

Electromagnetic radiation estimation at the ground plane near fifth‐generation base stations in China by using machine learning method

AbstractA novel method based on machine learning is proposed to estimate the electromagnetic radiation level at the ground plane near fifth‐generation (5G) base stations. The machine learning model was trained using data from various 5G base stations, enabling it to estimate the electric field intensity at any arbitrary radiation point when the base station provides service to different numbers of 5G terminals which are in different service modes. The inputs required for the model include the transmit power of the antenna, the antenna gain, the distance between the 5G base station and 5G terminals, terminal service modes, the number of 5G terminals and the environmental complexity around the 5G base station. Experimental results demonstrate the feasibility and effectiveness of the estimation method, with the mean absolute percentage error of the machine learning model being approximately 5.98%. This level of accuracy showcases the reliability of the approach. Moreover, the proposed method offers low costs when compared with on‐site measurements. The estimated results can be utilised to reduce test costs and provide valuable guidance for optimal site selection, thereby facilitating radio wave coverage or electromagnetic radiation regulation of 5G base stations.

Open Voice or Private Message? The Hidden Tug-of-War on Social Media Customer Service

Firms use social media as a great marketing tool and a convenient platform to deliver customer service. However, due to its public and social nature, social media tends to amplify a brand's successes as well as failures. Reluctant to subject their customer service to public scrutiny, firms are increasingly turning to private messaging on their social media channels for customer service conversations, which amounts to a reincarnation of traditional customer service in the social media era. Nonetheless, whether customers are willing to relinquish their newfound power is unclear. In this paper, we analyze a natural experiment where the inconvenience of the private channel with the treated firm is suddenly eliminated, and we find evidence that customers prefer to complain through the public channel. A randomized survey experiment further confirms this insight. Overall, firms’ and customers’ diverging preferences toward public or private channel reveal a hidden tug-of-war between the traditional mode of customer service featuring firm control and the recently emerged mode of customer service featuring shared control. These findings have important implications for firms’ customer service operations.