The empirical validation of the relationship among the capabilities of cultural and creative enterprises (CCE), customer co-creation value, and enterprise value remains insufficient. Therefore, clarifying the essential capabilities for increasing enterprise and customer value is essential. This study explores the factors that influence value co-creation in cultural and creative enterprises and examines how this influences enterprise and customer value. To measure this, a structured questionnaire was distributed to cultural and creative practitioners in Shanghai, China, and AMOS 24.0 was used for structural equation modelling of the obtained survey data. The results confirm the positive impacts of cooperative innovation capability, customer-linking, and service capability on creating enterprise and customer value. Additionally, the results indicate an interactive relationship between enterprise value creation and customer co-creation value in this context. This study provides management insights for product innovation and to enhance customer service and competitive advantage.

Background: This study aims to establish a multi-agent system model to provide accurate suggestions for the policy proposal of controlling the unreasonable growth of medical expenses charged by public hospitals in China. Methods: A multi-agent system model was employed in this study. Agents of this model were divided into patients, doctors, medical institutions, the government, and medical insurance agencies. The model was composed of two subsystems: the disease and medical-seeking subsystem, and the medical expenses subsystem. Policy intervention experiments were conducted on patients’ medical-seeking preferences, doctors’ public welfare behaviors, and the government’s financial investment. Results: At present, medical expenses in China are unreasonable and keep increasing, and the proportion of medicine and physical examination expenses to total medical expenses for public hospitals is unreasonable. Intervention experiments suggested that expanding the promotion and application of the community first-visit system could rationalize patients’ medical-seeking preferences, increasing doctors’ incomes and reducing workload could significantly restrict doctors’ over-prescription behaviors. Also, improving the government’s financial investment could guide public hospitals to strengthen their commitment to public welfare responsibilities. These interventions could decrease the unreasonable growth of medical expenses of public hospitals. The combined intervention effects on suppliers, demanders, and the government were better than the effect of these agents independently. Conclusions: The main reasons for the unreasonable increase in patient medical expenses at public hospitals could be attributed to patients’ unreasonable medical-seeking preferences, doctors’ weak public welfare incentives, and the government’s inadequate financial investment. Policy-makers should consider proposals to restrict and guide the behaviors of suppliers, demanders, and the government, simultaneously. The government should consider the feasibility, response speed, and implementation cost of policies as well.

Background: Hypertension is the most prevalent chronic disease among China’s older population, which comprises a growing proportion of the overall demographic. Older individuals with chronic diseases have a higher risk of developing depressive symptoms than their healthy counterparts, as evidenced in China’s older population, where patients with hypertension exhibit varying rates of depression depending on residing in urban or rural areas. Objective: This study aimed to investigate factors influencing and contributing to the disparities in depressive symptoms among older urban and rural patients with hypertension in China. Methods: We used a cross-sectional study design and derived data from the 8th Chinese Longitudinal Health Longevity Survey of 2018. The Fairlie model was applied to analyze the factors contributing to disparities in depressive symptoms between urban and rural older populations with hypertension. Results: The sample size for this study was 5210, and 12.8% (n=669) of participants exhibited depressive symptoms. The proportions of depressive symptoms in rural and urban areas were 14.1% (n=468) and 10.7% (n=201), respectively. In rural areas, years of education (1-6 years: odds ratio [OR] 0.68, 95% CI 1.10-1.21; ≥7 years: OR 0.47, 95% CI 0.24-0.94), alcohol consumption (yes: OR 0.52, 95% CI 0.29-0.93), exercise (yes: OR 0.78, 95% CI 0.56-1.08), and sleep duration (6.0-7.9 hours: OR 0.29, 95% CI 0.17-0.52; 8.0-9.9 hours: OR 0.24, 95% CI 0.13-0.43; ≥10.0 hours: OR 0.22, 95% CI 0.11-0.41) were protective factors against depressive symptoms in older adults with hypertension, while gender (female: OR 1.94, 95% CI 1.33-2.81), self-reported income status (poor: OR 3.07, 95% CI 2.16-4.37), and activities of daily living (ADL) dysfunction (mild: OR 1.69, 95% CI 1.11-2.58; severe: OR 3.03, 95% CI 1.46-6.32) were risk factors. In urban areas, age (90-99 years: OR 0.37, 95% CI 0.16-0.81; ≥100 years: OR 0.19, 95% CI 0.06-0.66), exercise (yes: OR 0.33, 95% CI 0.22-0.51), and sleep duration (6.0-7.9 hours: OR 0.27, 95% CI 0.10-0.71; 8.0-9.9 hours: OR 0.16, 95% CI 0.06-0.44; ≥10.0 hours: OR 0.18, 95% CI 0.06-0.57) were protective factors, while years of education (1-6 years: OR 1.91, 95% CI 1.05-3.49), self-reported income status (poor: OR 2.94, 95% CI 1.43-6.08), and ADL dysfunction (mild: OR 2.38, 95% CI 1.39-4.06; severe: OR 3.26, 95% CI 1.21-8.76) were risk factors. The Fairlie model revealed that 91.61% of differences in depressive symptoms could be explained by covariates, including years of education (contribution 63.1%), self-reported income status (contribution 13.2%), exercise (contribution 45.7%), sleep duration (contribution 20.8%), ADL dysfunction (contribution −9.6%), and comorbidities (contribution −22.9%). Conclusions: Older patients with hypertension in rural areas had more depressive symptoms than their counterparts residing in urban areas, which could be explained by years of education, self-reported income status, exercise, sleep duration, ADL dysfunction, and comorbidities. Factors influencing depressive symptoms had similarities regarding exercise, sleep duration, self-reported income status, and ADL dysfunction as well as differences regarding age, gender, years of education, and alcohol consumption.

Background: This study aimed to explore the collaborative relationship in translational medical research from the perspective of clinicians in China. The findings are expected to help practitioners optimize and experience the greatest advantages of collaboration. Methods: We conducted a national internet-based survey from July 29 to October 12, 2020. Of the 806 responses, 804 were completed with valid responses (valid response rate = 99.8%). The collected data were presented as descriptive statistics and analyzed using nonparametric tests (including the Wilcoxon rank test and Kruskal–Wallis H test) and stepwise logistic regression. Results: Of the 804 participants, 733 were either willing or very willing to collaborate in translational medical research. Clinicians’ willingness was influenced by their current research type, role in current translational medical research, burdens of their present research, preferred partners for collaboration at the institutional or individual level, and preferences for independent or dependent relationships. Conclusions: Clinicians should evaluate their time, role, burdens, personal preferences for research relationships, and appropriate partners based on their current translational medical research and its goals, before deciding to collaborate.

Collaborative innovation between hospitals and biomedical enterprises is crucial for ensuring breakthroughs in their development. This study explores the structural characteristics and examines the main roles of associated key actors of collaborative innovation between hospitals and biomedical enterprises in China. Using the jointly owned patent data within the country’s healthcare industry, a decade-long collaborative innovation network between hospitals and biomedical enterprises in China was established and analyzed through social network analysis. The results revealed that the overall levels of collaborative innovation network density, collaborative frequency, and network connectivity were significantly low, especially in less-developed regions. In terms of actors with higher degree centrality, hospitals accounted for the majority, whereas a biomedical enterprise in Shenzhen had the highest degree centrality. Organizations in underdeveloped and northwest regions and small players were more likely to implement collaborative innovation. In conclusion, a collaborative innovation network between hospitals and biomedical enterprises in China demonstrated high dispersion and poor development levels. Stimulating organizations’ initiatives for collaborative innovation may enhance quality and quantity of such innovation. Policy support and economic investments, strategic collaborative help, and resource and partnership optimization, especially for small players and in less-developed and northwest regions, should be encouraged to enhance collaborative innovation between hospitals and the biomedical industry in China and other similar countries or regions.