IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v15y2018i9p1972-d168884.html
   My bibliography  Save this article

Understanding the Role of Mobile Internet-Based Health Services on Patient Satisfaction and Word-of-Mouth

Author

Listed:
  • Dongxiao Gu

    (The School of Management, Hefei University of Technology, Hefei 230009, China
    The School of Informatics, Computing and Engineering, Bloomington, IN 47405-3907, USA
    These authors contributed equally.)

  • Xuejie Yang

    (The School of Management, Hefei University of Technology, Hefei 230009, China)

  • Xingguo Li

    (The School of Management, Hefei University of Technology, Hefei 230009, China
    These authors contributed equally.)

  • Hemant K. Jain

    (College of Business, The University of Tennessee at Chattanooga, 615 McCallie Ave, Chattanooga, TN 37403, USA
    These authors contributed equally.)

  • Changyong Liang

    (The School of Management, Hefei University of Technology, Hefei 230009, China)

Abstract

With the rapid advancement of Web 2.0 technologies, Internet medicine, and mobile healthcare, the influence of the use of patient-oriented Mobile Internet-based Health Services (MIHS) on patient satisfaction and the electronic word-of-mouth (WOM) of health service agencies is becoming the focus of the academic research community. Many large hospitals, including some Internet hospitals, have provided various online healthcare service platforms that enable patients to expediently consult with physicians and obtain healthcare services in an online to offline format. The purpose of this study is to analyze the main mechanisms of how the features and users’ experiences of MIHS influenced patient satisfaction and continuous use behaviors of the system to generate additional WOM dissemination behaviors. Based on post-adoption behavior and Expectation Confirmation Model of Information Technology Continuance (ECM-IT), this study conducted an empirical study through data collection from users (patients) from a large hospital providing online healthcare services. A total of 494 pieces of data were collected and analyzed using SmartPLS2.0(SmartPLS GmbH, Hamburg, Gernmany). The results show that: (1) patient satisfaction with MIHS and their intentions to continue use of MIHS have significantly positive influences on WOM; (2) patient satisfaction with MIHS is positively influenced by perceived usefulness and confirmation of MIHS performance expectations; (3) and patient intentions to continue use of MIHS are also affected by some technology factors, such as facilitating conditions and perceived risk, as well as some subjective feelings, such as perceived usefulness and perceived interactivity. The results of this study provide important implications for both research and practice of public health.

Suggested Citation

  • Dongxiao Gu & Xuejie Yang & Xingguo Li & Hemant K. Jain & Changyong Liang, 2018. "Understanding the Role of Mobile Internet-Based Health Services on Patient Satisfaction and Word-of-Mouth," IJERPH, MDPI, vol. 15(9), pages 1-23, September.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:9:p:1972-:d:168884
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/15/9/1972/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/15/9/1972/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. King, Robert Allen & Racherla, Pradeep & Bush, Victoria D., 2014. "What We Know and Don't Know About Online Word-of-Mouth: A Review and Synthesis of the Literature," Journal of Interactive Marketing, Elsevier, vol. 28(3), pages 167-183.
    2. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    3. Jaeki Song & Fatemeh Mariam Zahedi, 2005. "A Theoretical Approach to Web Design in E-Commerce: A Belief Reinforcement Model," Management Science, INFORMS, vol. 51(8), pages 1219-1235, August.
    4. Lu, Irene R.R. & Kwan, Ernest & Thomas, D. Roland & Cedzynski, Marzena, 2011. "Two new methods for estimating structural equation models: An illustration and a comparison with two established methods," International Journal of Research in Marketing, Elsevier, vol. 28(3), pages 258-268.
    5. Yu-Shan Chen & Chang-Liang Lin & Ching-Hsun Chang, 2014. "The influence of greenwash on green word-of-mouth (green WOM): the mediation effects of green perceived quality and green satisfaction," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(5), pages 2411-2425, September.
    6. Viswanath Venkatesh & Tracy Ann Sykes, 2013. "Digital Divide Initiative Success in Developing Countries: A Longitudinal Field Study in a Village in India," Information Systems Research, INFORMS, vol. 24(2), pages 239-260, June.
    7. Shirley Taylor & Peter A. Todd, 1995. "Understanding Information Technology Usage: A Test of Competing Models," Information Systems Research, INFORMS, vol. 6(2), pages 144-176, June.
    8. Naresh K. Malhotra & Sung S. Kim & James Agarwal, 2004. "Internet Users' Information Privacy Concerns (IUIPC): The Construct, the Scale, and a Causal Model," Information Systems Research, INFORMS, vol. 15(4), pages 336-355, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Muhammad Khalilur Rahman & Noor Raihani Zainol & Noorshella Che Nawi & Ataul Karim Patwary & Wan Farha Wan Zulkifli & Md Mahmudul Haque, 2023. "Halal Healthcare Services: Patients’ Satisfaction and Word of Mouth Lesson from Islamic-Friendly Hospitals," Sustainability, MDPI, vol. 15(2), pages 1-17, January.
    2. Xiaoxiang Li & Shuhan Zhang & Rong Chen & Dongxiao Gu, 2021. "Hospital Climate and Peer Report Intention on Adverse Medical Events: Role of Attribution and Rewards," IJERPH, MDPI, vol. 18(5), pages 1-17, March.
    3. Adnan Muhammad Shah & Mudassar Ali & Abdul Qayyum & Abida Begum & Heesup Han & Antonio Ariza-Montes & Luis Araya-Castillo, 2021. "Exploring the Impact of Linguistic Signals Transmission on Patients’ Health Consultation Choice: Web Mining of Online Reviews," IJERPH, MDPI, vol. 18(19), pages 1-21, September.
    4. Fuyong Lu & Xintao Wang & Xian Huang, 2023. "Counseling for Health: How Psychological Distance Influences Continuance Intention towards Mobile Medical Consultation," IJERPH, MDPI, vol. 20(3), pages 1-21, January.
    5. Jiexiang Jin & Mi Hyun Ryu, 2024. "Sustainable Healthcare in China: Analysis of User Satisfaction, Reuse Intention, and Electronic Word-of-Mouth for Online Health Service Platforms," Sustainability, MDPI, vol. 16(17), pages 1-18, September.
    6. Xiaodan Yu & Hongyang Wang & Zhenjiao Chen, 2024. "The Role of User-Generated Content in the Sustainable Development of Online Healthcare Communities: Exploring the Moderating Influence of Signals," Sustainability, MDPI, vol. 16(9), pages 1-21, April.
    7. Mengling Yan & Hongying Tan & Luxue Jia & Umair Akram, 2020. "The Antecedents of Poor Doctor-Patient Relationship in Mobile Consultation: A Perspective from Computer-Mediated Communication," IJERPH, MDPI, vol. 17(7), pages 1-16, April.
    8. Yanmei Jiang & Antonio K. W. Lau, 2023. "Understanding Post-Adoption Behavioral Intentions of Mobile Health Service Users: An Empirical Study during COVID-19," IJERPH, MDPI, vol. 20(5), pages 1-21, February.
    9. Guetz, Bernhard & Bidmon, Sonja, 2023. "The Credibility of Physician Rating Websites: A Systematic Literature Review," Health Policy, Elsevier, vol. 132(C).
    10. Bin Ding & Wei Liu & Sang-Bing Tsai & Dongxiao Gu & Fang Bian & Xuefeng Shao, 2019. "Effect of Patient Participation on Nurse and Patient Outcomes in Inpatient Healthcare," IJERPH, MDPI, vol. 16(8), pages 1-16, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sumeet Gupta & Haejung Yun & Heng Xu & Hee-Woong Kim, 2017. "An exploratory study on mobile banking adoption in Indian metropolitan and urban areas: a scenario-based experiment," Information Technology for Development, Taylor & Francis Journals, vol. 23(1), pages 127-152, January.
    2. Song, Jaeki & Kim, Junghwan & Cho, Kwangmin, 2018. "Understanding users’ continuance intentions to use smart-connected sports products," Sport Management Review, Elsevier, vol. 21(5), pages 477-490.
    3. Andrea Mezger & Pablo Cabanelas & Mª. Jesús López‐Miguens & Francesca Cabiddu & Klaus Rüdiger, 2020. "Sustainable development and consumption: The role of trust for switching towards green energy," Business Strategy and the Environment, Wiley Blackwell, vol. 29(8), pages 3598-3610, December.
    4. Iong, Kit Yeng & Phillips, Jenny O.L., 2022. "Examining the impact of behavioral factors on the intention of adopting E-government services: An empirical study on the hard-to-reach groups in Macao SAR, China," Technology in Society, Elsevier, vol. 71(C).
    5. Haque, Md Ziaul & Qian, Aimin & Hoque, Md Rakibul & Lucky, Suraiea Akter, 2022. "A unified framework for exploring the determinants of online social networks (OSNs) on institutional investors’ capital market investment decision," Technology in Society, Elsevier, vol. 70(C).
    6. Marya Wani & Vishnupriya Raghavan & Dolphy Abraham & Virginia Kleist, 2017. "Beyond utilitarian factors: User experience and travel company website successes," Information Systems Frontiers, Springer, vol. 19(4), pages 769-785, August.
    7. Zagidullin, Marat & Aziz, Nergis & Kozhakhmet, Sanat, 2021. "Government policies and attitudes to social media use among users in Turkey: The role of awareness of policies, political involvement, online trust, and party identification," Technology in Society, Elsevier, vol. 67(C).
    8. Shirazi, Farid & Wu, Yun & Hajli, Ali & Zadeh, Arash H. & Hajli, Nick & Lin, Xiaolin, 2021. "Value co-creation in online healthcare communities," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    9. Marya Wani & Vishnupriya Raghavan & Dolphy Abraham & Virginia Kleist, 0. "Beyond utilitarian factors: User experience and travel company website successes," Information Systems Frontiers, Springer, vol. 0, pages 1-17.
    10. Shaw, Norman & Sergueeva, Ksenia, 2019. "The non-monetary benefits of mobile commerce: Extending UTAUT2 with perceived value," International Journal of Information Management, Elsevier, vol. 45(C), pages 44-55.
    11. Sakshi, & Tandon, Urvashi & Ertz, Myriam & Bansal, Harbhajan, 2020. "Social vacation: Proposition of a model to understand tourists’ usage of social media for travel planning," Technology in Society, Elsevier, vol. 63(C).
    12. Jaeki Song & Fatemeh Mariam Zahedi, 2005. "A Theoretical Approach to Web Design in E-Commerce: A Belief Reinforcement Model," Management Science, INFORMS, vol. 51(8), pages 1219-1235, August.
    13. Pan, Jing Yu & Liu, Dahai, 2022. "Mask-wearing intentions on airplanes during COVID-19 – Application of theory of planned behavior model," Transport Policy, Elsevier, vol. 119(C), pages 32-44.
    14. Hasan, Rajibul & Lowe, Ben & Petrovici, Dan, 2020. "Consumer adoption of pro-poor service innovations in subsistence marketplaces," Journal of Business Research, Elsevier, vol. 121(C), pages 461-475.
    15. Un-Kon Lee, 2021. "The Effect of Confirmation of Nation Brand Image in International Tourism Advertisement on Travel Intention of Foreign Tourists: The Case of Korean ITA for Chinese Tourists," SAGE Open, , vol. 11(1), pages 21582440209, January.
    16. Paul Juinn Bing Tan, 2013. "Applying the UTAUT to Understand Factors Affecting the Use of English E-Learning Websites in Taiwan," SAGE Open, , vol. 3(4), pages 21582440135, October.
    17. Chen, Shih-Chih & Hung, Chung-Wen, 2016. "Elucidating the factors influencing the acceptance of green products: An extension of theory of planned behavior," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 155-163.
    18. Venkatesh, Viswanath & Maruping, Likoebe M. & Brown, Susan A., 2006. "Role of time in self-prediction of behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 100(2), pages 160-176, July.
    19. Garima Malik & A. Sajeevan Rao, 2019. "Extended expectation-confirmation model to predict continued usage of ODR/ride hailing apps: role of perceived value and self-efficacy," Information Technology & Tourism, Springer, vol. 21(4), pages 461-482, December.
    20. Borhan, Muhamad Nazri & Ibrahim, Ahmad Nazrul Hakimi & Miskeen, Manssour A. Abdulasalm, 2019. "Extending the theory of planned behaviour to predict the intention to take the new high-speed rail for intercity travel in Libya: Assessment of the influence of novelty seeking, trust and external inf," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 373-384.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:15:y:2018:i:9:p:1972-:d:168884. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.