M-health services equipped with public sector community health centers (MH-PS-CHCs), an emerging public-private joint venture in China: adoption from M-health Users’ Perspective

ABSTRACT

People with minor medical conditions in China tend to prefer healthcare consultation in the emergency department of tertiary hospitals and avoid public sector community health centers (PS-CHC). The reason behind this is the trust deficit in the quality of medical care at PS-CHC. On the other hand, Chinese m-health companies have a surprising number of registered users and daily healthcare queries. However, the lack of physical check-ups causes a lack of trust in the quality of prescribed treatments for m-health users. One such m-health company entered into a joint venture with a local government body. In this joint venture, the doctors from tertiary hospitals can provide healthcare consultation to m-health users at PS-CHC. This study investigates m-health users’ intention to use m-health services equipped with PS-CHC, an emerging public-private joint venture in China. We extended the technology acceptance model with government support and trust to predict the adoption of such technology-based public-private joint ventures in a better way. The data were collected from 432 m-health users in Hefei and analyzed using Smart-PLS. All eight direct, but only three mediating relationships were to be found significant. This study has implications for researchers, government healthcare authorities, and m-health service providers.

KEYWORDS:

• M-health
• government support
• healthcare service delivery model
• public-private joint venture
• technology acceptance
• trust

Disclosure statement

No potential conflict of interest was reported by the author(s).

Availability of data and materials

The data can be requested from the corresponding author after 24 months of publishing this article. The data will be shared with the mutual consent of all co-authors.

Additional information

Funding

This work was supported by School of Management, University of Science and Technology of China, Hefei, Anhui, China: [Grant Number Talent Start-up funding (Grant Number: 20200138)].

Notes on contributors

Muhammad Adnan Zahid Chudhery

Muhammad Adnan Zahid Chudhery received a Ph.D. degree in Management Science & Engineering from the School of Management, University of Science and Technology of China, Hefei, China, in 2018. He is currently a Senior Lecturer with the International Institute of Finance, School of Management, University of Science and Technology of China, Hefei, China. He has served as an Assistant Researcher at Tongji University School of Economics and Management, Shanghai, China. His research interests include operations management, service operations, total quality management, technology management, and healthcare informatics. He has authored or co-authored case studies published with IVEY Publishing. His research has been published in academic journals, such as IEEE Transactions on Engineering Management, Technological Forecasting and Social Change, Journal of Cleaner Production, and European Journal of Innovation Management.

Sarah Safdar

Sarah Safdar received a Master's degree in Management Science & Engineering in 2019 from the School of Management, Hefei University of Technology, Hefei, China, where she is currently working toward a Ph.D. degree in Management Science & Engineering. Her research interests include operations management, technology management, management information systems, healthcare informatics, and cloud computing. She has co-authored a case study published with IVEY Publishing. Her research has been published in academic journals, such as IEEE Transactions on Engineering Management, Technological Forecasting and Social Change.

Hakeem-Ur Rehman

Hakeem-Ur-Rehman received a Ph.D. degree in Management Science & Engineering from Shanghai Jiao Tong University, Shanghai, China, in 2019. He is currently an Assistant Professor with the Institute of Quality & Technology Management, University of the Punjab, Lahore, Pakistan. His research interests include operations and, supply chain management, quality management. His research has been published in academic journals, such as International Transactions in Operational Research, Journal of Forecasting, IEEE Transactions on Engineering Management, Technological Forecasting and Social Change, and Journal of Cleaner Production.

Raza Rafique

Raza Rafique received a Ph.D. degree in Supply Chain Management from Rutgers University, New Jersey, USA, in 2015. He is currently an Assistant Professor with the School of Management & Marketing, Kean University, New Jersey, USA. His research interests include supply chain management, business analytics, optimization, health care management, and energy network design. His research has been published widely in academic journals, such as Production and Operations Management (POM), Manufacturing & Service Operations Management (MSOM), IEEE Transactions on Engineering Management, Technological Forecasting and Social Change, Journal of Cleaner Production, International Journal of Inventory Research, and International Journal of Disaster Risk Science.

Muhammad Ali

Muhammad Ali is a post-doctorate research fellow at; (a) School of Economics and Management, Dongguan University of Technology, Dongguan, China; (b) School of Management, University of Science and Technology of China, Hefei, China. He also served as an Assistant Professor at Hailey College of Banking and Finance, University of the Punjab, Lahore, Pakistan. His research has appeared in journals such as the Journal of Innovation & Knowledge, The Service Industries Journal, Employee Relations, and Leadership & Organizational Development Journal.

Fenggang Li

Fenggang Li is serving as an Associate Professor at the School of Management, Hefei University of Technology, Hefei, Anhui, China. He has published more than 30 academic papers and one monograph. He has contributed as a principal investigator and participant in more than 30 national key R&D projects, NSFC projects, Anhui NSFC projects, EU-funded projects, and enterprise cooperation projects. His area of research includes artificial intelligence, knowledge management, data mining, intelligent technology, optimization technology and decision-making, enterprise informatics, and medical informatics.