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Open Access

Influence of Free Consultation Services on Patients’ Willingness to Pay in Online Medical Platforms

Bohua Zhang1, Zhijun Yan1, Xiuwei Song1(), Yingguang Liao1, Peilun Li1
School of Management and Economics, Beijing Institute of Technology, Beijing 100083, China
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Abstract

Online medical platforms have emerged as a popular means for patients to access high-quality medical services efficiently. These platforms offer a variety of services, including paid consultations and free consultations. Given that doctors can increase their revenue through these platforms, researchers should investigate how to improve patients’ willingness to pay for these services. Drawing upon social exchange theory, stimulus-organism-response theory, and the information systems (IS) success model, this study proposes a model and five hypotheses to examine the influence of free medical consultations on patients’ willingness to buy paid services. To test these hypotheses, a questionnaire survey was conducted, and the collected data were analyzed using the structural equation model. The results indicate that the quality of information and services provided by doctors during free consultations positively affects patients’ willingness to pay. By introducing information quality and service quality into the IS success model in the context of free medical consultations, this study contributes to the literature on online medical platforms and expands our understanding of patients’ behavior. The findings of this study can be useful for online medical platforms and doctors to design effective platform functions and individual behavioral strategies.

Keywords

doctor performancefree online consultationfree serviceonline medical platformwillingness to pay

References

[1]

N. Huang, Z. Yan, and H. Yin, Effects of online–offline service integration on e-healthcare providers: A quasi-natural experiment, Prod. Oper. Manag., vol. 30, no. 8, pp. 2359–2378, 2021.

Crossref Google Scholar
[2]

X. Zhang, S. Liu, Z. Deng, and X. Chen, Knowledge sharing motivations in online health communities: A comparative study of health professionals and normal users, Comput. Hum. Behav., vol. 75, pp. 797–810, 2017.

Crossref Google Scholar
[3]

Z. Yan, L. Kuang, and L. Qiu, Prosocial behaviors and economic performance: Evidence from an online mental healthcare platform, Prod. Oper. Manag., vol. 31, no. 10, pp. 3859–3876, 2022.

Crossref Google Scholar
[4]

J. Liu, Y. Bian, Q. Ye, and D. Jing, Free for caring? The effect of offering free online medical-consulting services on physician performance in e-health care, Telemed. E Heath., vol. 25, no. 10, pp. 979–986, 2019.

Crossref Google Scholar
[5]
C. N. Cofer, Motivation and Personality. A. H. maslow, Q. Rev. Biol., vol. 30, no. 4, p. 425, 1955.
Crossref
[6]
S. Panahi, J. Watson, and H. Partridge, Potentials of social media for tacit knowledge sharing amongst physicians: Preliminary findings, https://www.mendeley.com/catalogue/8fbfe85c-57f3-31ed-8035-fd1a64817d10/, 2012.
[7]

J. N. Wang, Y. L. Chiu, H. Yu, and Y. T. Hsu, Understanding a nonlinear causal relationship between rewards and physicians’ contributions in online health care communities: Longitudinal study, J. Med. Internet Res., vol. 19, no. 12, p. e427, 2017.

Crossref Google Scholar
[8]

L. Wang, L. L. Yan, T. Zhou, X. Guo, and G. R. Heim, Understanding physicians’ online-offline behavior dynamics: An empirical study, Inf. Syst. Res., vol. 31, no. 2, pp. 537–555, 2020.

Crossref Google Scholar
[9]

T. C. Lin, M. C. Lai, and S. W. Yang, Factors influencing physicians’ knowledge sharing on web medical forums, Health Informatics J., vol. 22, no. 3, pp. 594–607, 2016.

Crossref Google Scholar
[10]

Z. Yan, T. Wang, Y. Chen, and H. Zhang, Knowledge sharing in online health communities: A social exchange theory perspective, Inf. Manag., vol. 53, no. 5, pp. 643–653, 2016.

Crossref Google Scholar
[11]

M. Zhang, X. Guo, and T. Wu, Impact of free contributions on private benefits in online healthcare communities, Int. J. Electron. Commer., vol. 23, no. 4, pp. 492–523, 2019.

Crossref Google Scholar
[12]

H. Yang, X. Guo, and T. Wu, Exploring the influence of the online physician service delivery process on patient satisfaction, Decis. Support. Syst., vol. 78, pp. 113–121, 2015.

Crossref Google Scholar
[13]

X. C. Chen, G. H. Lei, C. J. Wu, and L. L. Fen, Current status and countermeasures of patients right to choose doctors in China, (in Chinese), China Health Law, vol. 22, no. 4, pp. 44–48&60, 2014.

Google Scholar
[14]

X. P. Xiang, J. L. Wei, F. Peng, M. Hao, and H. Le, Analysis of the main reasons for patients to choose a hospital, (in Chinese), Chinese Hospital Management, vol. 31, no. 1, pp. 13–15, 2011.

Google Scholar
[15]

J. Dang, Q. Li, and X. Dai, Study on influencing factors of patients going out for medical treatment, (in Chinese), Management Observer, no. 36, pp. 184–186, 2019.

Google Scholar
[16]

H. Zhou, C. Ye, B. Zhu, R. Wang, Z. Peng, B. Wang, and J. Peng, Multilevel model analysis on health seeking behavior of patients with chronic diseases in Shenzhen city, (in Chinese), Chinese Journal of Social Medicine, no. 4, pp. 249–251, 2011.

Google Scholar
[17]

X. Huang, P. Sun, X. Zhang, and J. Wu, What affects patients’ choice of consultant: An empirical study of online doctor consultation service, Electron. Commer. Res., vol. 22, pp. 1–23, 2022.

Crossref Google Scholar
[18]
Y. J. Yu, Research on the impact of network reviews on patient selection of doctor in telemedicine services, Master dissertation, Department of Industrial Engineering, Nanjing University, Nanjing, China, 2020.
[19]

M. Yi, J. Wu, J. Cai, and J. Gao, Online doctor selection behavior based on multi-source information of text and pictures from the perspective of trust, (in Chinese), Information Science, vol. 39, no. 9, pp. 84–93, 2021.

Google Scholar
[20]

M. M. Palmeira and J. Srivastava, Free offer ≠ cheap product: A selective accessibility account on the valuation of free offers, J. Consum. Res., vol. 40, no. 4, pp. 644–656, 2013.

Crossref Google Scholar
[21]

H. Huang, Y. Huang, Z. J. Yan, and H. Zhang, Social influence, competition, and free riding: Examining seller interactions within an online social network, MIS Q., vol. 46, no. 3, pp. 1817–1832, 2022.

Crossref Google Scholar
[22]

B. Mahadevan, Business models for internet-based E-commerce: An anatomy, Calif. Manag. Rev., vol. 42, no. 4, pp. 55–69, 2000.

Crossref Google Scholar
[23]

J. Hamari, N. Hanner, and J. Koivisto, “Why pay premium in freemium services?” A study on perceived value, continued use and purchase intentions in free-to-play games, Int. J. Inf. Manag., vol. 51, no. 4, p. 102040, 2020.

Crossref Google Scholar
[24]

J. Hamari, N. Hanner, and J. Koivisto, Service quality explains why people use freemium services but not if they go premium, Int. J. Inf. Manag. J. Inf. Prof., vol. 37, no. 1, pp. 1449–1459, 2017.

Crossref Google Scholar
[25]
J. B. Watson, Psychology: From the Standpoint of a Behaviorist. Philadelphia, PA, USA: JB Lippincott, 1919.
Crossref
[26]

A. Mehrabian and J. A. Russell, The basic emotional impact of environments, Percept. Mot. Skills, vol. 38, no. 1, pp. 283–301, 1974.

Crossref Google Scholar
[27]

H. Zhang, Y. Lu, B. Wang, and S. Wu, The impacts of technological environments and co-creation experiences on customer participation, Inf. Manag., vol. 52, no. 4, pp. 468–482, 2015.

Crossref Google Scholar
[28]

H. Liu, H. Chu, Q. Huang, and X. Chen, Enhancing the flow experience of consumers in China through interpersonal interaction in social commerce, Comput. Hum. Behav., vol. 58, no. 5, pp. 306–314, 2016.

Crossref Google Scholar
[29]

X. Hu, Q. Huang, X. Zhong, R. M. Davison, and D. Zhao, The influence of peer characteristics and technical features of a social shopping website on a consumer’s purchase intention, Int. J. Inf. Manag., vol. 36, no. 6, pp. 1218–1230, 2016.

Crossref Google Scholar
[30]

T. Zhou, Examining users’ knowledge sharing behaviour in online health communities, Data Technol. Appl., vol. 53, no. 4, pp. 442–455, 2019.

Crossref Google Scholar
[31]

W. H. DeLone and E. R. McLean, Information systems success: The quest for the dependent variable, Inf. Syst. Res., vol. 3, no. 1, pp. 60–95, 1992.

Crossref Google Scholar
[32]

W. H. DeLone and E. R. McLean, The DeLone and McLean model of information systems success: A ten-year update, J. Manag. Inf. Syst., vol. 19, no. 4, pp. 9–30, 2003.

Crossref Google Scholar
[33]

P. B. Seddon, A respecification and extension of the DeLone and McLean model of IS success, Inf. Syst. Res., vol. 8, no. 3, pp. 240–253, 1997.

Crossref Google Scholar
[34]

G. Zheng and X. Han, Online medical development status and thinking, (in Chinese), Electronic Commerce, no. 4, pp. 21–22, 2018.

Google Scholar
[35]

S. L. Rynes, B. Gerhart, and L. Parks, Personnel psychology: Performance evaluation and pay for performance, Annu. Rev. Psychol., vol. 56, no. 1, pp. 571–600, 2005.

Crossref Google Scholar
[36]
P. Blau, Exchange and Power in Social Life. New York, NY, USA: John Wiley & Sons, 1964.
[37]

J. Nahapiet and S. Ghoshal, Social capital, intellectual capital, and the organizational advantage, Acad. Manag. Rev., vol. 23, no. 2, pp. 242–266, 1998.

Crossref Google Scholar
[38]
P. Raghubir, Free gift with purchase: Promoting or discounting the brand? J. Consum. Psychol. , vol. 14, nos. 1&2, pp. 181–186, 2004.
Crossref
[39]

K. Z. K. Zhang, M. Benyoucef, and S. J. Zhao, Building brand loyalty in social commerce: The case of brand microblogs, Electron. Commer. Res. Appl., vol. 15, no. 2, pp. 14–25, 2016.

Crossref Google Scholar
[40]

E. B. Ponte, E. Carvajal-Trujillo, and T. Escobar-Rodríguez, Influence of trust and perceived value on the intention to purchase travel online: Integrating the effects of assurance on trust antecedents, Tour. Manag., vol. 47, pp. 286–302, 2015.

Crossref Google Scholar
[41]

C. Gan, Gratifications for using social media: A comparative analysis of Sina Weibo and WeChat in China, Inf. Dev., vol. 34, no. 2, pp. 139–147, 2018.

Crossref Google Scholar
[42]

X. Chen, Q. Huang, and R. M. Davison, The role of website quality and social capital in building buyers’ loyalty, Int. J. Inf. Manag. J. Inf. Prof., vol. 37, no. 1, pp. 1563–1574, 2017.

Crossref Google Scholar
[43]

X. Guo, X. Zhang, and Y. Sun, The privacy-personalization paradox in mHealth services acceptance of different age groups, Electron. Commer. Res. Appl., vol. 16, no. 1, pp. 55–65, 2016.

Crossref Google Scholar
[44]

J. Wan, Y. Lu, B. Wang, and L. Zhao, How attachment influences users’ willingness to donate to content creators in social media: A socio-technical systems perspective, Inf. Manag., vol. 54, no. 7, pp. 837–850, 2017.

Crossref Google Scholar
[45]

D. Gefen, Customer loyalty in e-commerce, J. Assoc. Inf. Syst., vol. 3, no. 1, pp. 27–53, 2002.

Crossref Google Scholar
[46]

R. C. Mayer, J. H. Davis, and F. D. Schoorman, An integrative model of organizational trust, Acad. Manag. Rev., vol. 20, no. 3, pp. 709–734, 1995.

Crossref Google Scholar
[47]

F. M. Thompson, S. Tuzovic, and C. Braun, Trustmarks: Strategies for exploiting their full potential in e-commerce, Bus. Horiz., vol. 62, no. 2, pp. 237–247, 2019.

Crossref Google Scholar
[48]

X. Lin, M. Featherman, and S. Sarker, Understanding factors affecting users’ social networking site continuance: A gender difference perspective, Inf. Manag., vol. 54, no. 3, pp. 383–395, 2017.

Crossref Google Scholar
[49]

D. J. Kim, D. L. Ferrin, and H. R. Rao, A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents, Decis. Support. Syst., vol. 44, no. 2, pp. 544–564, 2008.

Crossref Google Scholar
[50]

Y. Zhu and Z. Bao, The role of negative network externalities in SNS fatigue: An empirical study based on impression management concern, privacy concern, and social overload, Data Technol. Appl., vol. 52, no. 3, pp. 313–328, 2018.

Crossref Google Scholar
[51]

J. P. Fraedrich and O. C. Ferrell, The impact of perceived risk and moral philosophy type on ethical decision making in business organizations, J. Bus. Res., vol. 24, no. 4, pp. 283–295, 1992.

Crossref Google Scholar
[52]

J. Chen and X. L. Shen, Consumers’ decisions in social commerce context: An empirical investigation, Decis. Support. Syst., vol. 79, no. 11, pp. 55–64, 2015.

Crossref Google Scholar
[53]

H. Xu, H. H. Teo, B. Tan, and R. Agarwal, The role of push-pull technology in privacy calculus: The case of location-based services, J. Manag. Inf. Syst., vol. 26, no. 3, pp. 135–174, 2009.

Crossref Google Scholar
[54]

H. F. Lin, Effects of extrinsic and intrinsic motivation on employee knowledge sharing intentions, J. Inf. Sci., vol. 33, no. 2, pp. 135–150, 2007.

Crossref Google Scholar
[55]

W. J. F. Hair, B. J. Babin, R. E. Anderson, and C. N. Cofer, Multivariate data analysis, Technimetrics, vol. 30, no. 1, pp. 130–151, 1998.

Google Scholar
International Journal of Crowd Science
Volume 8 Issue 1,
February 2024
Pages 28-37
DOI: 10.26599/IJCS.2023.9100021
Cite this article:
Zhang B, Yan Z, Song X, et al. Influence of Free Consultation Services on Patients’ Willingness to Pay in Online Medical Platforms. International Journal of Crowd Science, 2024, 8(1): 28-37. https://doi.org/10.26599/IJCS.2023.9100021
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Descriptive statistics of interviewees’ personal information.

CharacteristicCategoryNumber of peoplePercentage (%)
GenderMale26868.9
Female12131.1
Age<21266.7
21−3017444.7
31−4010025.7
41−506617.0
51−60123.1
>60112.8
Medical platformHaodf.com9825.2
xywy.com6316.2
ask.39.net7419.0
Baidu Medical7118.3
120ask.com51.3
dxy.com7318.8
other51.3

Construct statistics and factor correlations.

ConstructMeanSDIQSQTPPRPW
IQ5.381.090.74−−−−
SQ5.311.120.510.71−−−
T5.381.150.440.460.72−−
PPR3.161.67−0.22−0.15−0.070.74−
PW5.431.260.300.350.43−0.050.74

Confirmatory factor analysis results of the measurement model.

ConstructItemStandardized estimateAVECRα
Note: AVE: average variance extracted; CR: composite reliability.
IQIQ10.7050.5410.8250.829
IQ20.751
IQ30.740
IQ40.745
SQSQ10.7070.5060.8030.767
SQ20.683
SQ30.756
SQ40.696
TT10.6850.5210.8130.771
T20.708
T30.775
T40.715
PPRPPR10.8050.7010.8750.896
PPR20.833
PPR30.872
PWPW10.7200.5400.7010.780
PW20.749

Goodness of fit assessments for the structural model.

Goodness of fit measuresGoodness of fit rangesSEM
Note: SEM: structural equation model.
χ2/df< 3.002.914
GFI> 0.900.910
AGFI> 0.800.878
CFI> 0.900.936
NFI> 0.900.907
TLI> 0.900.923
RMSEA< 0.080.070

Questionnaire.

ConstructContent
Consultation information quality
Please answer the following questions based on your last free online consultation.
1. The doctor provided information relevant to your needs.
2. The doctor provided ample, well-informed information.
3. The doctor provided accurate and correct information.
4. The doctor provided up to date information.
Consultation service quality
1. The doctor provided services that make you feel professional.
2. The doctor provided you with punctual service according to the prescribed time.
3. The doctor was quick to respond to your questions or needs.
4. The doctor provided you with personalized services that are different from others, depending on your situation.
Patients’ trust
1. The doctor performed as you would have expected.
2. The doctor protected your privacy.
3. The doctor made you feel reliable.
4. The doctor’s conversation with you was honest.
Patients’ perceived privacy risk
1. During the free consultation, you considered it risky to disclose your health information.
2. During the free consultation, you believed that the disclosure of health information may cause uncertain results.
3. During the free consultation process, you believed that there are many potential losses in disclosing personal health information.
Patient’s willingness to pay
1. If the price is reasonable, you are willing to pay the doctor who helped you in your last free medical consultation for more care.
2. You are willing to use the paid services of the doctor who helped you in your last free medical consultation many times in the future, provided the price is reasonable.

Result of exploratory factor analysis.

ItemRegression weight
Component 1Component 2Component 3Component 4Component 5
IQ10.3280.698−0.0960.420−0.083
IQ20.2630.721−0.1810.1870.179
IQ30.2320.711−0.0120.3190.071
IQ40.4050.735−0.1010.1290.154
SQ10.6820.290−0.0810.1460.167
SQ20.6730.212−0.1620.1810.273
SQ30.7270.278−0.0330.2940.279
SQ40.6770.278−0.218−0.0140.013
T1−0.107−0.0840.6590.0540.027
T2−0.1410.0020.712−0.0210.007
T3−0.048−0.1610.7070.001−0.040
T4−0.3480.4540.674−0.0500.371
PPR10.2620.1320.0020.7950.313
PPR20.1270.2140.0650.8340.157
PPR30.1930.117−0.0150.8860.160
PW10.1470.3940.0010.2180.718
PW20.3810.0800.0500.2230.733