For free or paid? A comparison of doctors' intention to offer consulting services in eHealth
| DOI | https://doi.org/10.1108/IMDS-05-2021-0336 |
| Published date | 08 July 2022 |
| Date | 08 July 2022 |
| Pages | 1816-1852 |
| Subject Matter | Information & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems |
| Author | Jiahe Chen,Ping-Yu Hsu,Yu-Wei Chang,Wen-Lung Shiau,Yi-Chen Lan |
For free or paid? A comparison of
doctors’intention to offer
consulting services in eHealth
Jiahe Chen
School of Business, Western Sydney University, Sydney, Australia
Ping-Yu Hsu
Department of Business Administration, National Central University,
Taoyuan, Taiwan
Yu-Wei Chang
Department of Business Management,
National Taichung University of Science and Technology, Taichung, Taiwan
Wen-Lung Shiau
Department of Business Administration,
Zhejiang University of Technology–Pingfeng Campus, Hangzhou, China, and
Yi-Chen Lan
School of Business, Western Sydney University, Sydney, Australia
Abstract
Purpose –Considering both online and offline service scenarios, this study aims to explore the factors
affecting doctors’intention to offer consulting services in eHealth and compare the factors between the free-
and paid-service doctors. The theory of reasoned action and social exchange theory are integrated to develop
the research model that conceptualizes the role of extrinsic motivations, intrinsic motivations, costs, and
attitudes in doctors’behavioral intentions.
Design/methodology/approach –Partial least square structural equation modeling (PLS-SEM) was
leveraged to analyze 326 valid sample data. To provide robust results, three non-parametric multigroup
analysis (MGA) methods, including the PLS-MGA, confidence set, and permutation test approaches, were
applied to detect the potential heterogeneity between the free- and paid-service doctors.
Findings –The results with overall samples reveal that anticipated rewards, anticipated associations,
anticipated contribution, and perceived fee are all positively related to attitude, which in turn positively
influences behavioral intention, and that perceived fee positively moderates the relationship between attitude
and behavioral intention. Attitude’s full mediation is also confirmed. However, results vary between the two
groups of doctors. The three MGA approaches return relatively convergent results, indicating that the effects
of anticipated associations and perceived fee on attitude are significantly larger for the paid-service doctors,
while that of anticipated rewards is found to be significantly larger for the free-service doctors.
Originality/value –eHealth, as a potential contactless alternative to face-to-face diagnoses, has recently
attracted widespread attention, especially during the continued spread of COVID-19. Most existing studies
have neglected the underlying heterogeneity between free- and paid-service doctors regarding their
motivations to engage in online healthcare activities. This study advances the understanding of doctors’
participation in eHealth by emphasizing their motivations derived from both online and offline service
scenarios and comparing the differences between free- and paid-service doctors. Besides, horizontally
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The authors would like to thank the editor Hing Kai Chan and anonymous referees for their constructive
comments and guidance, which helped a great deal in improving this paper.
Funding: This research was funded by the Ministry of Science and Technology of Taiwan (MOST
111-2410-H-025- 003, MOST 109-2410-H -025-001-MY2) and t he China Scholarship C ouncil (No.
202008600004).
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/0263-5577.htm
Received 29 May 2021
Revised 12 November 2021
3 February 2022
3 April 2022
Accepted 16 May 2022
Industrial Management & Data
Systems
Vol. 122 No. 8, 2022
pp. 1816-1852
© Emerald Publishing Limited
0263-5577
DOI 10.1108/IMDS-05-2021-0336
comparing the results by applying diverse MGA approaches enriches empirical evidence for the selection of
MGA approaches in PLS-SEM.
Keywords Telemedicine, eHealth, O2O commerce, Free and paid online consulting services, Multigroup
analysis, Social exchange theory, Intrinsic and extrinsic motivations
Paper type Research paper
1. Introduction
With the outbreak and rapid spread of influenza and coronavirus disease 2019 (COVID-19),
personal proximity and face-to-face diagnoses in hospitals pose threats to people’shealth
(WHO, 2020).Therefore, eHealth standsout in this unique period, which is definedas the use of
information andcommunication technology (ICT)for health (WHO, 2012). It provides various
healthcare services, including online consultations, electronic health records, telemedicine,
online communities, offline appointments, and drug information. eHealth is also regardedas a
key potentialsolution to the deficienciesof the healthcareindustry, especially in therural areas
of developing countries (Wang et al.,2017). eHealth enables an alternative channel for doctors
and patients;doctors can share their medical knowledge with patientsin their spare time, and
patients canconsult with doctors anytimeand anywhere (Liu et al., 2018;Linet al.,2015). With
increasinglymore users, theeHealth market is projectedto exceed more than USD 160.50 billion
by 2024, with a compound annual growth rate of 21% (Market researchengine, 2017).
eHealth brings about numerous benefits to service recipients, such as the quality,
accessibility, and affordability of online healthcare services (The World Health Assembly,
2018). Thus, governments or eHealth platforms attach more importance to the benefits of
online healthcare services for patients (e.g. time and cost savings), rather than for doctors.
However, the success and sustainability of eHealth largely depend on whether doctors
proactively participate in online healthcare activities (Guo et al., 2017;Wang et al., 2017).
Unfortunately, the proportion of offline doctors engaging in eHealth is still relatively low
compared to the explosive demand of patients, and there are still a large number of doctors
with the reluctance of engaging in eHealth (McKinsey, 2021). Because a shortage of doctors
results in an imbalance between doctor supply and patient demand, it is difficult for countries,
especially developing countries, to implement eHealth strategies (Zayyad and Toycan, 2018).
There are some existing studies on eHealth, but rarely from the perspective of doctors. On the
one hand, some studies mainly concentrated on patient behaviors (Cao et al., 2016;Xiao et al.,
2014;Yan et al., 2016;Chang et al., 2019;Le et al.,2019;Zheng et al.,2022) and an information
technology-based perspective (Cao et al., 2016;Hsieh, 2015;Xiao et al.,2014).On the other hand,
other studies mainly explored the online factors influencing doctors’behaviors, including
economic returns (Wang et al., 2017;Guo et al.,2017), reputation and self-efficacy (Zhang et al.,
2017;Lin et al.,2015;Maheshwari et al., 2020); but these factors were only derived fr om online
contexts. That is, the previous research only considered online motivators for doctors, such as
monetary rewards from online medical service users and mutual relationships with online
patients. However, it is not sufficient to grasp the comprehensive motivations of doctors because
eHealth can be seen as an O2O (i.e. online-to-offline or offline-to-online) mode, in which doctors
can provide online services to attract offline outpatients to online eHealth platforms (i.e. offline-
to-onlinemode) and introduce onlinepatients to offline hospitals (i.e. online-to-offline mode). The
factors affecting doctorbehaviors, thereby,can stem from both online and offline channels.
In the realm of eHealth in O2O e-commerce, doctors can be motivated by both online and
offline incentives. From an online perspective, doctors could earn extra economic income (Guo
et al., 2017;Liu et al., 2018;Wang et al., 2017), strengthen doctor-patient relationships (Liu
et al., 2018;Chang et al., 2019), contribute to the health of patients (Liu et al., 2018;Lin et al.,
2015), promote interactions, and accumulate reputation and word of mouth (Zhang et al.,
2017). From an offline perspective, the increased number and income of outpatients, enhanced
Free and paid
consulting
services in
eHealth
1817
associations with offline patients, and contributions to their health would also be attributed to
satisfactory and convincing online consultations offered by doctors.
In terms of online consultations in eHealth, there are two main charging modes: free and
paid modes (Haodf, 2019;Liu et al., 2018). Doctors choose one of the two modes based on
different personal motivations. From the standpoint of free-service doctors, helping patients
solve health problems and improving patient health will provide them with more incentives
to engage in online healthcare activities (Chen et al., 2020;Liu et al., 2018). For paid-service
doctors, they may be more concerned about tangible returns (e.g. increased online services
income and offline outpatient visits), long-term doctor-patient relationships, and
commissions paid to eHealth platforms (Chang et al., 2019). Thus, different motivations
and behaviors perhaps vary under different charging modes (Zheng et al., 2022).
In short, to the best of our knowledge, few works have examined the doctor motivations by
considering both online and offline context in a single model and have divided doctors into
free- and paid-service groups to compare the differences in motivations and behavioral
intentions (Lin et al., 2015;Zhang et al., 2017;Guo et al., 2017;Chen et al., 2020;Zayyad and
Toycan, 2018). Either ignoring factors stemming from offline contexts or pooling doctor
samples at an aggregated data level will bias the research results and cause inaccurate
inferences for both theory and practice. To fill this gap, this study attempts to explore the
factors affecting doctors’intention to offer consulting services in eHealth from both online
and offline perspectives and further distinguish and compare the results between free- and
paid-service doctors. In particular, our research will address the following question:
RQ1. What are the differences in the factors affecting the intention to offer consulting
services between free- and paid-service doctors?
This study develops a research model by integrating the theory of reasoned action (TRA) and
social exchange theory (SET) to investigate doctors’behavioral intentions. Since the TRA has
been widely used to explain individual behavioral intentions (Ham et al., 2019;Alsaleh et al.,
2019;Bock et al., 2005;Bock and Kim, 2002), it is employed to study how doctor motivations
influence their attitudes and behavioral intentions to offer consulting services. Additionally,
the online consultations provided by doctors can be regarded as a kind of knowledge sharing.
It is also akin to the social exchange through which doctors contribute their professional
medical expertise to obtain the benefits they need (Lin et al., 2015;Yan et al., 2016;Zhang et al.,
2017). Since SET has also been acknowledged in the domain of knowledge sharing
(Kankanhalli et al., 2005;Wasko and Faraj, 2005;Yan et al., 2016;Chang et al., 2016;Lin et al.,
2015), it is applied to justify how extrinsic and intrinsic motivations affect doctors’attitudes
and behavioral intentions. Moreover, this study also considers the fees charged by eHealth
platforms as a cost factor because doctors have to pay certain commissions to eHealth
platforms when they offer paid services.
From a theoretical perspective, we consider both online and offline factors and develop an
integrated research model to explore the factors affecting doctors’intentions to offer
consulting services by combining the TRA and SET. Moreover, this study further
distinguishes free- and paid-service modes in the research model and compares the
similarities and differences in motivations and costs between free- and paid-service doctors.
From a practical perspective, our findings confirm that all proposed hypotheses are
significantwith overall samplesand that there indeed are differencesin the factors affectingthe
intention to offerconsulting services between the two groups.Doctors who offer paid medical
consultations are more likely to be motivated by anticipated associations and perceived fee
than free-service doctors, while free-service doctors are surprisingly more likely to provide
servicesdue to anticipated rewardsthan paid-service doctors.Based on the findings, thisstudy
provides eHealth platforms with concrete suggestions about promotion and application
strategies and helps themaccordingly develop policies to attractand retain doctors.
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