Exploring Cloud Computing Adoption in Private

Jour of Adv Research in Dynamical & Control Systems, Vol. 10, 08-Special Issue, 2018

Exploring Cloud Computing Adoption in Private Hospitals in India: An Investigation of DOI and TOE Model Sambit Bhuyan, Research Scholar, Siksha O Anusandhan (Deemed to be University), Bhubaneswar, India. E-mail:[email protected] Dr. Manoranjan Dash, Associate Professor, Siksha O Anusandhan (Deemed to be University), Bhubaneswar, India. E-mail:[email protected]

Abstract--- This study intends to analyse the reception of Cloud Computing in Indian health care centres and to explore the components that effect the adoption of cloud computing. There are various factors that affect the cloud computing adoption. Health care sector need to methodically assess these variables before moving to cloud. The research model was developed to find out the determinants influencing the acceptance of cloud computing in private hospitals. The Diffusion of Innovation (DOI) theory’s innovation characteristic and Technology-OrganizationEnvironment (TOE) framework was integrated to conceptualize the research model. Empirical data was collected from 189 respondents working in private hospitals in India who had experience in Information technology usage and implementation. The structural equation modelling used the sample data to test against the proposed research model. It will also find out cloud computing adoption determinants in private hospitals. Keywords--- Cloud Computing, DOI, TOE, Health Care, Indian Hospitals.

I.

Introduction

Cloud computing is an upcoming technology which is implemented by many organizations. Cloud computing will benefit the organizations in terms of cost improvement, enhancing efficiency and increasing operational adaptability. It can be treated as a fifth utility after water, power, phone and gas (Buyya et al., 2009). Cloud computing involves four primary organization models. The models vary based on the foundational framework layer and the physical framework. The cloud models available are Private Cloud, Public Cloud, Community Cloud and Hybrid Cloud. The three major cloud service models are Software as Service (SaaS), Platform as a Service (PaaS) and Infrastructure as a Service (IaaS) (Cloud Security Alliance,2009; Dustin et al.,2010 ; Ali et al.,2014;Mell et al.,2009). Enterprises are realigning their IT scene to receive cloud computing. The cloud based arrangements can possibly enhance business process by bringing down IT consumptions, convey constant applications, and offer access to pervasive capacity, boundless computing power, and market data mobilization (Armbrust et al.,2009;Low et al.,2011;Sultan ,2010; Garrison et al.,2012). Numerous hospitals are thinking about moving from conventional frameworks to present day mobile based technologies due to complex nature of Hospital Information Systems (HIS). Cloud computing gives an option for these innovations and can be utilized as a new type of IT outsourcing. Cloud computing solutions will be utilised in hospitals for sharing patient data and ease data accessibility with right treatment and diagnosis. It can also support electronic health record containing medical history, test result, images etc that can be accessed by physician in real time. (Grindle et al.,2013; Ahuja et al.,2012). There is no requirement for Healthcare sectors to purchase costly equipment and licenses since it will be taken care by the cloud service provider. This will also reduce the maintenance cost of IT staff and IT Department (Masrom et al.,2014). There are numerous advantages in cloud computing but few organizations are embracing it (Abdollahzadehgan et al.,2013). The healthcare cloud computing market in the healthcare industry will exhibit an exponential rate of growth at 21.3% CAGR in the next three to four years. The business will touch US$6.79 billion by 2018 end. There is a 50% gap in healthcare infrastructure in India compared to global healthcare as per Zinnov Management Consulting [21]. The infrastructure needs to be scaled up to cater the huge population in India, thus creating an opportunity for Cloud. The cloud can dramatically change the IT landscape in Healthcare sector. There are various business activities like HRMS, Store Keeping, Supplies, Billing, Accounts, Third party insurance can be migrated to cloud. As per a study, the aggregate business for Cloud arrangement in the Indian healthcare services (Hospitals) could be around $600 million by 2020. The existing hospitals currently spend approximately $191 million. This IT spending is expected to

ISSN 1943-023X Received: 5 Apr 2018/Accepted: 15 May 2018

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reach $1.5 billion by 2020.This study develops a research model by combining the model TOE and DOI perspectives.

II.

Theoretical Background and Literature Review

Cloud computing essentially gives IT services as on demand through Internet technology using the virtualization resource utilization approach. National Institute of Standards and Technology (NIST) defined cloud computing as “a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction”. NIST classified the cloud deployment into the following four categories: private cloud, community cloud, public cloud, and hybrid cloud (NIST.,2012). There are four cloud deployment models: Private cloud is owned and maintained by an organization. The infrastructure is owned by a certain organization. The organization itself maintain the infrastructure or may outsource to the third party. The infrastructure may be located in own premise or off premise (Armbrust et al.,2010). Even the cost of maintaining the private cloud will be high due to hire of IT staff and infrastructure maintenance. In Public cloud, the infrastructure is maintained and provided by the service provider like Google, Amazon for public or organization like healthcare, government institution on a self-benefit, pay per utilize basis (Dustin et al.,2010; Marston et al., 2011).It is advisable for service provider to create a secured, scalable and flexible data centre. Community cloud is shared by many enterprises that belong to particular community and have common line of business in terms of requirements, policy and compliance. Example: The Health department can create a community cloud where the periphery hospitals can share the cloud infrastructure. Hybrid cloud basically a blend of public cloud, private cloud, and community cloud based on the requirements (Cloud Security Alliance,2010 ;Velte et al.,2010). Example: The mail server can be hosted on a private cloud can be used to send data in public cloud. Cloud services offers three service/delivery models: The Platform as a Service (PaaS) model gives a chance to migrate to the cloud their selfdeveloped or procured applications. The service provider manages the cloud infrastructure. The deployed application is controlled by consumer (Dillon et al.,2010; Cloud security alliance,2009). The consumers enjoys the benefit of packaged application on cloud in Software as a Service (SaaS).The software package/applications is accessed by consumers by using client devices provided by the service provider. It is accessed by URL.The infrastructure is maintained by service provider (Wang et al.,2008;Clemons et al.,2011). The consumer gets the infrastructure related support such as servers, operating system, storage, application software ,processing, network and other fundamental computing resources in the Infrastructure as a Service (IaaS) service model (Mell et al.,2009;Bhardwaj et al., 2010; Sohan et al.,2010). The factors responsible for cloud computing adoption in Malaysian public sector was studied. TOE framework combined with DOI theory provided numerous inputs on the behaviour of IT department (Sallehudin et al., 2015).Other studies have given emphasis on audit protocol and computation in cloud (Mohammed,2011;Wei et al.,2014). DOI and TOE framework was adopted in Taiwanese high tech industry to examine the reception of cloud computing. The key factors that are critical for adoption of cloud computing such as cost and security factor was not considered in their research model (Low et al., 2011). Many industries like manufacturing, healthcare have utilized TOE model for an insight on innovation adoption intent (Mishra et al., 2007; Zhu et al., 2006). A survey among the SMEs in Spain concluded that low knowledge and company’s ignorance are the major barriers towards the adoption of cloud computing (Trigueros-Preciado et al., 2013). Technology, organization and environment of TOE model has tried to find out the firm’s need to adopt new technology in European, American and Asian region(Abdollahzadehgan et al., 2013;Zhu et al., 2004). There was a great emphasis given on the knowledge domain while adopting cloud computing. University Technology Transfer Offices utilized TOE framework and DOI theory to analyse the factors that influence the decision of cloud computing adoption (Rohani et al., 2015).DOI and TOE Framework has been considered for a study in Portugal services and manufacturing sector (Oliveira et al., 2014).Record Management system for patient is the core of the health care organization. The cloud computing can offer scalability, effective handing, adequate security to patient personal data (AbuKhousa et al., 2012).The competitive pressure and organizational factors are the critical factors to implement cloud computing (Mangula et al.,2014;Hema et al.,2015). The prominent model Diffusion of Innovation (DOI) theory used for adoption of Information system in an organization. It is coined by E.M. Rogers in 1962 (Alam,2009 ; Azadegan et al.,2010;Dedrick et al.,2004). The five prominent attributes are (1) Relative advantage: how a new technology provide an advantage to an existing technology (2) Compatibility: the extent to which the new technology is compatible to the existing process. (3) Complexity: the degree to which the new technology is complex (4) Observability: to which extent the new


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technology is noticeable (5) Trialability: the new technology needs to be simple to be experimented. The innovation in an enterprise also depends on three factors i.e. Individual (attitude of organization leadership towards change) and External factors (Openness to adopt a new system) Organization structure (Employee strength, complexity, agility).TOE framework describes about the development and acceptance of innovation in an organization (Tornatzky et al.,1990). TOE Framework has three elements (Oliveira et al.,2010; Oliveira et al.,2011).Technology context comprises the existing technologies in an enterprise. Organizational context considers the reporting hierarchy and the employee strength. Environmental context encompass the competitors and government rules and policies. The (TOE) framework operates at an organizational-level. The existing literature assists to define the factors for each context. TOE framework was referred in many research for new innovation (Lin et al.,2008). A richer theoretical base and a large number of constructs can be derived by integrating TOE with other framework which will help to understand the adoption behaviour (Alatawi et al.,2012 ; Chong et al.,2012). Thus, this study integrates DOI and TOE framework.

III.

Research Model and Hypotheses

The DOI framework innovation characteristics integrated with TOE framework has been depicted below in Fig1:

Fig. 1: The Research Model Relative advantage defines about the benefit that the healthcare organization will receive from the adoption of new technologies above the existing technologies. If the new technologies provide more benefits and advantage than the existing technologies, than it will have a positive influence for adoption. H 1 : Cloud computing acceptance in private hospitals has a positive affect due to relative advantage Complexity basically is perception about innovation of how difficult is to understand and use. The cloud computing has the ability to seamlessly integrate with the existing technologies of healthcare organization. But the lack of cloud specialist in the organization can negatively influence the adoption. H 2 : Cloud computing migration in private hospitals will be negatively influenced by complexity Compatibility defines relative degree of how cloud computing fits to the existing infrastructure. If the cloud computing can help the healthcare sector to scale their applications without much changing to the existing infrastructure, than compatibility will influence positively for cloud computing. H 3 : Cloud computing adoption in private hospitals will be certainly influenced by Compatibility The patient information data of healthcare sectors will be stored in the servers of the cloud service providers. There is a worry that the confidential, sensitive, personal data will be lost and abused due to security breach. The healthcare organization will not be ready for cloud computing for absence of strong security protocol.


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H 4 : Cloud computing implementation in private hospitals will be positively influenced by Technology readiness The top management support will be crucial in cloud computing since they have to identify the potential benefits, allocate human resources, and make budgetary provision for the same. H 5 : Cloud computing adoption in private hospitals will be positively influenced by Top management support The larger healthcare organizations are more likely to take a risk to adopt cloud computing since they have more human resources and financial capacity to do so. Thus, the organization size will positively influence the adoption of innovation H 6 : Organization size surely influence the cloud computing adoption. The healthcare organization will adopt the innovation to be competitive. The competitiveness brings in operational efficiency and helps in brand building. H 7 : Competitive pressure will optimistically provide support to cloud computing.

IV.

Research Method

A survey was carried out that includes the private hospitals in India. First the relevant literature on cloud computing adoption in hospitals were searched and initial constructs were identified. The data was collected and confirmatory analysis was conducted, the reliability of constructs were tested. A questionnaire was developed with the opinion of the experts and also the content validity has been performed. Interval level ranging from ‘‘strongly disagree’’ to ‘‘strongly agree” measured the constructs on a five-point Likert scale. The constructs considered were relative advantage, complexity, compatibility, technological readiness, top management support, organization size and competitive pressure. The qualified professionals (CIOs, IT directors, IT managers) of 235 private hospitals across India were given the questionnaire. The number of valid response received was 189.

Fig. 2: SEM Model


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V.

Data Analysis and Results

Data analysis followed two steps approach. The first step is to test reliability and validity of the measurement model. The second step is to test research hypothesis and Structural Model Framework. Measurement Model CFA (Confirmatory Analysis) was carried out to test the measurement model. The Common Model Fit Indices were used i.e. CFI (Comparative fit index), GFI (Goodness of fit index), AGFI (Adjusted Goodness of fit Index) and RMSEA (Root Mean Square error of approximation) .χ2 /df were used to assess the overall goodness fit of the model. Reliability and Convergent validity of the factors were estimated by composite reliability (CR) and average variances extracted (AVE). Table 1: Fit Indices from Measurement and Structural Models Fit Indices

Recommended value ≤ 3.00 ≥0.9 ≥0.9 ≥0.8 ≤0.08

χ2 /df CFI GFI AGFI RMSEA

Construct

Item

Relative Advantage

RA1 RA2 RA3 Complexity C1 C2 C3 Compatibility CCx1 Cx2 Cx3 Technology TTF1 Readiness TTF2 TTF3 Top Mangement TMS1 Support TMS2 TMS3 Organisational OS1 Size OS2 OS3 Competitive CP1 Pressure CP2 CP3 Cloud Computing CCA1 Adoption CCA2

Measurement model

Structural Model

1.89 0.956 0.923 0.843 0.644

Table 2: Standardised Item Loadings Standardised AVE Item Loadings 0.734 0.887 0.812 0.723 0.810 0.764 0.778 0.771 0.708 0.906 0.868 0.767 0.857 0.834 0.765 0.724 0.733 0.756 0.722 0.734 0.765 0.734 0.765

1.87 0.953 0.921 0.839 0.641

CR

Cronbach’s Alpha

0.72

0.84

0.86

0.71

0.73

0.78

0.68

0.81

0.78

0.81

0.87

0.89

0.68

0.80

0.81

0.72

0.82

0.86

0.73

0.83

0.84

0.78

0.86

0.87

p