In China, most of the people, even with a minor medical condition, also preferred to visit the emergency department (ED) of territory hospitals (TH) rather than visiting the primary health-care centers (PHC) [1, 2]. The reason behind this is the lack of trust in the competence of health-care professionals and the quality of delivered care in these PHCs [1]. The Chinese government had realized the associated criticalities, therefore, increased funding to strengthen primary health-care infrastructure and uplifted as community health center (CHC) in urban areas, while well-equipped small hospitals in rural areas [3, 4]. The local government in some cities of China started promoting to visit public sector CHC (PCHC) first, rather than visiting the ED of TH. Therefore, some of these local governments offered subsidized rates for dispensing drugs and a higher reimbursement rate for the delivered care in these PCHCs [4]. Surprisingly, the outpatient flow towards PCHCs was still in decline, as 63% in 2005 reached up-to 59% in 2013, which means that these PCHCs were operating about 41 percent underutilization rate [5]. There was a dire need to take such initiatives that can build trust in the quality of delivered health-care at PCHC, which results in increasing the outpatients' flow towards these PCHCs and ultimately lead to achieving optimal resource utilization in these PCHCs.
In China, m-health service adopters, either doctors or consumers, are significantly increasing. A Chinese m-health service provider, namely "Chunyu Yisheng," having a strength of about 0.41 million doctors, 92 million users, with more than 80,000 daily health-care consultations queries [6, 7]. Another Chinese online health-care platform, "Ping An Good Doctor," has about 77 million registered users, with about 0.25 million daily health-care consultation queries [8]. Surprisingly, similar forty-three online health-care service providers were operating in China [9]. These companies experienced that a tiny portion of these queries was generating revenues, as about 2.5% for "Chunyu" [7], and about 1% for "Hao Daifu Zaixian," a web-based online health-care service provider in China [10]. The reasons behind this were the prescription of medicines without physical check-up as a concern for doctors as well as m-health consumers, resulting in dissatisfaction, while the doctor was of the patients' own choice [11, 12]. There was a dire need to revisit the existing m-health service delivery model that can build confidence over m-health services resulting in a revenue-generating business model.
So, one such m-health service provider entered into a joint venture with a local government body in Wuhan China and introduced a dedicated section in the PCHC [6]. These PCHCs are capable of dealing with outpatients having minor medical conditions and referrals in case of an urgent medical condition. The consultation services will be provided by the doctors, who are associated with the top-level (e.g., territory) hospitals. These doctors will also train the staff of the concerned PCHC to uplift the quality of delivered health-care services [6]. Therefore, we considered those doctors as our targeted respondents, who were associated with a territory hospital. In this joint venture, an m-health consumer makes an appointment with the concerned doctor using m-health APP, and then to get an offline health-care consultation in the PCHC as per scheduled time [6]. All those m-health users who can be treated online can get an online health-care consultation, while those needing a physical examination before prescribing medication can be examined in the PCHCs. Zhang et al. [10] argued that offline healthcare satisfaction could hinder online healthcare awareness and adoption. M-health services that are equipped with PCHCs will provide an offline health-care consultation facility. As a result, the doctors will not feel reluctant to prescribe treatment. We posit that equipping m-health services with PCHCs can help the doctors to prescribe treatment with confidence. As a result, doctors and m-health users can experience satisfactory health-care consultation services. One such m-health service provider planned to establish similar three-hundred health-care facilities in China [7]. M-health services that are equipped with PCHCs will help to bridge the strengths of both parties, resulting in a win-win situation for private sector m-health service providers and PCHCs.
Private sector m-health services that are equipped with PCHCs is a newly emerging mobile-based healthcare service delivery model, which is not mature enough, and not investigated earlier. In addition, a unifying policy to govern the Chinese m-health industry does not exist [13] as some of the local governments are supporting to use m-health services [6] while the legislation can also be seen that banned appointment making with the doctors of public hospitals using m-health applications [13]. In this scenario, it is of great importance to examine the doctors' behavioral intent to prescribe treatment using m-health services that are equipped with PCHCs, which is a public-private joint venture. So, the objective of this study is to investigate essential factors which influence the doctors' behavioral intent to prescribe treatment using this emerging mobile-based healthcare service delivery model in China.
Contribution
To the best of our knowledge, this study is the first to examine factors essential in the adoption of such a public-private joint venture that is formed between the public sector community health centers and the private sector m-health service providers. This study explored that m-health service providers can facilitate to divert the outpatients' flow towards community health centers. This facilitation will help to achieve optimal resource utilization in these community health centers. The outpatients referred to those who are with minor medical conditions and can be treated online and in the community health centers. This study explored that m-health users can get an offline health-care consultation facility in community health centers. This offline health-care consultation facility will help to build confidence over m-health service providers and ultimately lead towards a revenue-generating business model for m-health service providers. This study investigated the adoption of such a public-private joint venture that can provide online as well as offline health-care consultation to m-health consumers. This will be the first study that employed channel expansion theory to investigate m-health adoption. This will be the first study that extended UTAUT theory with the channel expansion theory constructs to investigate m-health adoption. This will be the first study that employed perceived government support and media richness to investigate m-health adoption.
Theoretical Model And Hypothesis Development
The adoption of e-health and m-health services have been investigated using various theoretical approached including stimulus-organism-response theory [14], protection motivation theory [15], the theory of planned behavior, and value attitude behavioral model [16], trust transfer model [17], technology acceptance model [18–26], and the unified theory of acceptance and use of technology theory [27–34]. The unified theory of acceptance and use of technology (UTAUT) argues that the effort and performance expectancies with social influences and facilitating conditions having a direct effect on the behavioral intention to use new technology. This behavioral intention ultimately affects the usage behavior, while the facilitating conditions have a direct impact as well on the usage behavior [35, 36]. The UTAUT theory is based on a comprehensive examination of several theories, including the theory of reasoned action, the theory of planned behavior, social cognitive theory, and the technology acceptance model [27, 35]. Therefore, UTAUT theory is widely adopted in several technological domains like e-health [37], mobile electronic medical record systems [30], and became a reason to employ in this study. The channel expansion theory posits that the consumers' (e.g., doctors) relevant experiences with a technology-based communication channel (e.g., traditional m-health application) will help to shape their perception about its media richness [38]. M-health services that are equipped with PCHCs will be the extension of the traditional m-health application-based service delivery model. Therefore, we employed the channel expansion theory in this study. The channel expansion theory comprises the perceived media richness, social influence, and situational factors [39]. This study is investigating the adoption of a public-private joint venture in China, and a unifying policy to govern the Chinese m-health industry does not exist [13]. For instance, some of the local governments are supporting to use m-health services [6], while the legislations can also be seen that banned appointment making with a doctor of public hospitals using m-health applications [13]. On the other side, the public sector community health centers having significant governmental support [3, 4]. Therefore, perceived government support got employed as a situational factor. So, this study employed effort expectancy (EE), performance expectancy (PE), social influence (SN), facilitating conditions (FC), and behavioral intention to use (BI) from UTAUT theory. While perceived media richness (PMR), perceived government support (PGS), and social influence (SN) from channel expansion theory. Figure 1 demonstrates the research model.
Perceived Media Richness
M-health services that are equipped with PCHCs will provide a technology-based health-care service delivery model; therefore, the doctors' perception regarding media richness is of great importance. In this study, PMR is the doctors' belief that m-health services equipped with PCHCs will provide a satisfactory communication interface to meet their disease diagnosis needs that will result in the prescription of medication. The media richness can be referred to have better communication amenities (i.e., video conversation) to influence performance than those having limited communication amenities (i.e., audio phone call) [40]. The relationship in-between PMR and usage intention has been studied in various technological domains such as the virtual learning environment [41], and instant messaging [42]. Therefore, we propose:
H1: PMR positively affects behavioral intention to deliver health-care consultation using m-health services that are equipped with PCHCs.
Situational Factor: Perceived Government Support
The local governmental support can be an influential factor in m-government adoption [43], and the information technology diffusion process [44, 45]. In this study, PGS is the doctors' belief that the government will be devoted to putting m-health services that are equipped with PCHCs into practice. Tashkandi et al. [46] considered the governmental regulations as an environmental factor which can influence to adopt cloud computing. The relationship in-between government support and the intention to adopt has been investigated in various technological domains such as m-government among rural farmers [43], open government data [47], and mobile-based outpatient health-care service delivery framework [48, 49]. Therefore, we propose:
H2: PGS positively affects behavioral intention to deliver health-care consultation using m-health services that are equipped with PCHCs.
Social Influence
The social influence is "the degree to which an individual perceives that important others believe he or she should use the new system [35]." In this study, these important others referred to as office colleagues and administration. The relationship in-between SN and behavioral intention have been studied well in various technological domains such as mobile-based payment adoption [50], medical diagnosis support system based on artificial intelligence [36], mobile health [27], mobile payments [51, 52], virtual learning environments [53], and electronic commerce [54]. Therefore, we propose:
H3: SN positively affects behavioral intention to deliver health-care consultation using m-health services that are equipped with PCHCs.
Effort Expectancy
The EE is "the degree of ease associated with the use of the system [35]." In this study, EE is the doctors' belief that it will be easy for them to diagnose a disease and prescribe medication using m-health services that are equipped with PCHCs. We posit that such a belief will help to build confidence for doctors to prescribe treatment. The relationship between EE and intention to use has been investigated in various technological domains like mobile banking [55], electronic government [56], mobile payments [51, 52], virtual learning environments [53], and electronic commerce [54]. Therefore, we propose:
H4: EE positively affects behavioral intention to deliver health-care consultation using m-health services that are equipped with PCHCs.
Performance Expectancy
PE is "the degree to which a person believes that using the system will enhance his or her job performance [35]." In this study, PE is the doctors' belief that m-health services that are equipped with PCHCs will help to improve their disease diagnosis level and to reduce the chances of medical negligence. We posit that PE will help to build confidence for doctors to deliver a satisfactory health-care consultation using m-health services that are equipped with PCHCs. The relationship between PE and intention to use has been investigated in various technological domains like electronic government [56], mobile payments [51, 52], virtual learning environments [53], and electronic commerce [54]. So, we propose:
H5: PE positively affects behavioral intention to deliver health-care consultation using m-health services that are equipped with PCHCs.
Facilitating Conditions
The FC is "the degree to which an individual believes that an organizational and technical infrastructure exists to support the use of the system [35]." Xie et al. [9] explored that about twenty online hospitals in China could deal with online and offline health-care consultations. The online health-care service industry in China is capable of dealing with outpatients [1, 57]. In this study, FC is the doctors' belief that m-health services that are equipped with PCHCs can provide the necessary technological infrastructure for health-care consultation. The relationship between FC and intention to use has been investigated in various technological domains like electronic government [56], and electronic commerce [54]. Therefore, we propose:
H6: FC positively affects behavioral intention to deliver health-care consultation using m-health services that are equipped with PCHCs.