Keywords

1 Theoretical Framework

Digital marketing has benefit healthcare services in the point of view of visibility regarding online space [1]. It enables individuals to choose healthcare services because of their immediate response to their problems [1]. Telemedicine not only permits medicine services to employ technology and telecommunication links which enable people, patients having healthcare services at a distance [2] (but ensures quality, profitable and is equally distributed to all people asked for it [3]. Telemedicine offers access to individuals to health care at any time, any distance, any job and family barriers and obligations [4]. Telemedicine is easily used by individuals because is available at digital stores and mHealth (mobile Health) applications are easily download to smart phones, laptops etc. and enable distance communications between medics, experts and patients [5, 6]. It is convenient for patients in case of lining in rural areas to catch up on the issues via mHealth (mobile Health) application [7]. In addition, telemedicine systems may can save a life in case of emergency [8]. The role of telemedicine services was of a great importance in during the COVID-19 Pandemic [8].

Health industry has reached a new era due to digitalization and digital networks, nowadays known as telemedicine. Telemedicine involved, digital, technological, legal, economic sides [9, 10]. In the digitalization era, the patience became e-patience or an online patience. e-health service, e-patient, e-health, e-healthcare providers are more than familiar to individuals nowadays. In addition, telehealth is considered as an assistive machinery applicative way to relieve the absence of healthcare personnel and professionals [11]. In Whitten and Sypher [12] it is claimed that telemedicine could be classified in three categories. The first one refers to synchronous versus asynchronous. The second one refers to data transfer and storage. The last one refers to robotic telemedicine services [12]. Digital marketing efforts to enhance telemedicine services success is outstanding. In addition to this digital media tried to offer better and quicker access to telemedicine platforms [13]. Digital marketing efforts are based on Image [14], communication tools [15]. Furthermore, internet permit physicians to acquire numerous supports from medical marketing [16].

More specifically it evaluates the impact of Perceived innovation (Compatibility), Willingness to recommend (Advocacy), Perceived Credibility, Perceived Risk, Use Intention, Risk Acceptance, Information Sharing, Perceived Risk, Perceived Usefulness on Commitment, Perceived Quality, Satisfaction conceptual constructs.

Commitment is the long-enduring willingness toward a product or a service [17] and warrant to echo purchasing [18]. In Servetkiene et al. [19] quality evaluation grounded on patients’ perceptions, ponders and occurrences regarding health care system. Patients’ satisfaction must be defeated by former experiences as well as hopes that could probably at least partially defeated by assessing patient perceived health care quality [19]. Patient perceived healthcare quality approaches a wider range of perception toward healthcare system [20]. Consequently, Patient perceived healthcare quality can be viewed as a collaboration between expectation and real experiences [19]. Crow et al. [21] claimed that Patient perceived healthcare quality is strongly connected with patients’ needs. Τhe difference between consumer expectations and real situations is expressed as satisfaction [22]. Amin et al. [3] claimed that satisfaction I strongly related to customers behavior intentions, plus loyalty, plus continues persuasions and word of mouth. Satisfaction has a positive effect on patients’ continuous intentions [23, 24] usage intention and m-health emergency use [25]. Still, Amin et al. [3] supported that satisfaction could be seen as the patients’ and individuals’ favorable feeling toward telemedicine services.

2 Methodology

2.1 Statistical Hypotheses

The research hypotheses are the following ones: Ho1i: Perceived Innovation (Compatibility) has a significant effect on Commitment, Perceived Quality, Satisfaction. Ho2i: Willingness to recommend (Advocacy) has a significant effect on Commitment, Perceived Quality, Satisfaction. Ho3i: Perceived Credibility has a significant effect on Commitment, Perceived Quality, Satisfaction. Ho4i: Perceived Risk has a significant effect on Commitment, Perceived Quality, Satisfaction. Ho5i: Use Intention has a significant effect on Commitment, Perceived Quality, Satisfaction. Ho6i: Risk Acceptance has a significant effect on Commitment, Perceived Quality, Satisfaction. Ho7i: Information Sharing has a significant effect on Commitment, Perceived Quality, Satisfaction. Ho8i: Perceived Risk has a significant effect on Commitment, Perceived Quality, Satisfaction. Ho9i: Perceived Usefulness has a significant effect on Commitment, Perceived Quality, Satisfaction.

2.2 Sample-Methodology-Instrument

Tο test the research hypotheses, a survey was conducted on 412 participants who answered a questionnaire, which was distributed electronically in the format of a google form. 200 (48.5%) were females whereas 212 (51.5%) were males. For the data analysis the study used Pearson coloration coefficient [26].

The purpose of the study a questionnaire/instrument was constructed. It is defined by 12 conceptual constructs named Perceived Innovation (Compatibility) (3 items, e.g. Use of the Telemedicine Services is compatible with all aspects of my medical needs), Willingness to recommend (Advocacy) (4 items, e.g. I would be happy to recommend Telemedicine Services to others), Perceived Credibility (5 items, It is safe for me to use telemedicine services), Perceived Risk (3 items, It is dangerous for health to use the Telemedicine Services), Use Intention (3 items, e.g. For future medicals I will be using Telemedicine Services), Risk Acceptance (3 items, e.g. There is a possibility of loss of control over private data due to the use of Telemedicine Services), Information Sharing (3 items, I clearly explained to Telemedicine Services my medical conditions), Perceived Risk (3 items, It is dangerous for health to use the Telemedicine Services), Perceived Usefulness (4 items, I believe that using telehealth would enhance his or her health status), Commitment (4 items, I do not choose other forms of health services if I have the option to choose Telemedicine Services), Perceived Quality, (4 items, Telemedicine Services offer services whose quality is consistent and Satisfaction (4 items, I am pleased with my experience with telemedicine services).

3 Results

Inventory reliability was assessed by the very well coefficient named Cronbach alpha (α). Coefficient α for the research Instrument equals to 0.907 that confirms reliability ([27,28,29,30]. Coefficient α for Instrument conceptual constructs named Perceived Innovation (Compatibility), Willingness to recommend (Advocacy), Perceived Credibility, Perceived Risk, Use Intention, Risk Acceptance, Information Sharing, Perceived Risk (PeR), Perceived Usefulness, Commitment, Perceived Quality and Satisfaction counts for 0.896, 0,843, 0.901, 0.893, 0.825, 0.837, 0.813, 0.840, 0.806, 0.812, 0.879 and 0.921 respectively suggesting internal consistency [31,32,33,34,35,36,37,38,39].

According to correlation analysis results the posed Ho1 null hypotheses is con-firmed. More especially Perceived Innovation (Compatibility) has a significant effect on Commitment (r = 0.823, p < 0.01), Perceived Quality (r = 0.689, p < 0.01) and Satisfaction (r = 0.714, p < 0.01). In addition, the posed Ho2 null hypotheses is confirmed. More especially Willingness to recommend (Advocacy) has a significant effect on Commitment (r = 0.796, p < 0.01), Perceived Quality (r = 0.691, p < 0.01) and Satisfaction (r = 0.802, p < 0.01). Furthermore, the posed Ho3 null hypotheses is confirmed. More especially Perceived Credibility has a significant effect on Commitment (r = 0.976, p < 0.01), Perceived Quality (r = 0.778, p < 0.01) and Satisfaction (r = 0.845, p < 0.01). Also, the posed Ho4 null hypotheses is confirmed. More especially Perceived Risk has a significant effect on Commitment (r = 0.534, p < 0.01), Perceived Quality (r = 0.597, p < 0.01) and Satisfaction (r = 0.578, p < 0.01). Additionally, the posed Ho5 null hypotheses is confirmed. More notably, Perceived Use Intention has a significant effect on Commitment (r = 0.809, p < 0.01), Perceived Quality (r = 0.836, p < 0.01) and Satisfaction (r = 0.829, p < 0.01). Moreover, the posed Ho6 null hypotheses is confirmed. More especially, Risk Acceptance has a significant effect on Commitment (r = 0.654, p < 0.01), Perceived Quality (r = 0.503, p < 0.01) and Satisfaction (r = 0.624, p < 0.01). Likewise, the posed Ho7 null hypotheses is confirmed. More particularly, Information Sharing has a significant effect on Commitment (r = 0.675, p < 0.01), Perceived Quality (r = 0.692, p < 0.01) and Satisfaction (r = 0.631, p < 0.01). As well, the posed Ho8 null hypotheses is confirmed. More specifically, Perceived Risk has a significant effect on Commitment (r = 0.562, p < 0.01), Perceived Quality (r = 0.589, p < 0.01) and Satisfaction (r = 0.601, p < 0.01). Finally, the posed Ho9 null hypotheses is confirmed. More specifically, Perceived Usefulness has a significant effect on Commitment (r = 0.816, p < 0.01), Perceived Quality (r = 0.834, p < 0.01) and Satisfaction (r = 0.856, p < 0.01). All these results are supported by other authors [1,2,3,4,5,6,7,8,9,10,11,12,13, 17,18,19,20,21, 23,24,25]. There are dozens of healthcare applications on the internet to improve people’s access to healthcare.

4 Discussion and Conclusions

There are thousands healthcare applications easily downloaded on mobile phone, tablet, or laptop that facilitate individuals’ entry to healthcare provided by telemedicine services [3]. According to the authors in [3] telemedicine guarantees quality, profitable and straightforward healthcare services for every individual. Portnoy et al. [7] strongly believed that telemedicine services are useful, economical care for anyone needs health care services, especially in a case of emergency. Telemedicine and e-health services have increase patients; involvement regarding their own health care [5]. Thus, the aim of this paper was to provide the most determinant factors influence the Use of Telemedicine Services. The results of this study confirmed that Perceived Innovation (Compatibility), Willingness to recommend (Advocacy), Perceived Credibility, Perceived Risk, Use Intention, Risk Acceptance, Information Sharing, Perceived Risk and Perceived Usefulness has a significant effect on Commitment, Perceived Quality, Satisfaction. Digital marketers be able to employ the model regarding Factors Influencing the Use of Telemedicine Services to design and organize digital healthcare services for the benefit of the e-patient. These results are in line with authors in [25] claimed that use intentions and satisfaction are strongly connected. In addition, authors claimed that performance expectation effects e-patient satisfaction.

Notwithstanding countless study should be done employing additional investigation procedures concerning big data groups of e-patients [38] and big data procedures [40,41,42,43]. Totaling, AI and Cloud Computing Procedures might scrutinize [11, 43,44,45,46,47] telemedicine platforms and networks vis-à-vis regarding e-patients from different demographical, cultural, economic and educational levels applying machine learning techniques.