Introduction
Cloud computing is a considerably new development which has taken root in the business world (King, 2008). Mell & Grance (2011) define cloud computing as a model that enables the convenient, ubiquitous, and network access to configurable computing resources that are pooled together. These resources include computer services, network servers, networks, and storage space for data. These resources can be provided to prospective customers and also forfeited without the need for significant management effort. The interaction between the provider of cloud computing services and the customer is also not required for this model (Mell & Grance 2011).
Cloud computing consists of several characteristics, some of which include measured service, rapid elasticity, on-demand self-service, resource pooling, and broad network access. While these are technical terms, its significance and uses for small business are quite direct. Business can exploit the various deployment models depending on their needs and resources base. For instance, the private cloud can be used exclusively by a singular business that has various business units in its organization structure. The community cloud can be used by a group of consumers in the same organization who share similar concerns (Mell & Grance 2011).
The cloud computing technology can help businesses improve their operations and efficiency. Given that it is relatively new technology, there are more businesses that are expected to take up the technology compared to those who have taken it up. The adoption of the technology is the product of several factors (Hasan, Zgair, Ngotoye, Hussain & Najmuldeen, 2015). Despite the numerous benefits that the business could leap from cloud computing, its adoption is the result of the interplay of several factors. This study will highlight the factors that affect the adoption of cloud computing by small businesses (Hasan et al., 2015).
Background of the Problem
The development of cloud computing has offered various benefits and options for the business. Powelson (2011) argues that the small that do not adopt and integrate cloud computing into their operations risk forfeiting several advantages that are associated with the use of cloud computing. These include the ubiquitous accessibility as a well as a reduced capital requirement (Powelson, 2011). Even so, there is still need for increased knowledge as well as an understanding of how small businesses stand to benefit from the adoption of cloud computing. In addition to understanding the benefits of cloud computing, it is also imperative to highlight the issue of cost effectiveness, especially with regard to the minimum size of the small business at below which the adoption of this technology is no longer effective (Yallapragada & Bhuiyan, 2011).
There are also other challenges such as the security of the information, especially for the small businesses that store sensitive information in the cloud. Other issues that require to be addressed include the reliability of the cloud computing technology. The reliability of the technology is a pressing concern for the consumer. It is important for the businesses to retrieve the information stored in the cloud when the demand arises. The current study will explore these and many other concepts that relate to cloud computing and its adoption by small businesses.
Problem Statement
While the benefits of cloud computing are known and desirable for businesses, the problem is a lack of knowledge regarding if and to what extent a relationship exists between cost-effectiveness, reliability, security effectiveness, and the need for cloud-computing technologies and small business leaders’ decisions to adopt cloud-computing technologies (Hailu, 2012; Hasan et al., 2015; Powelson, 2011; Ross, 2010).
There is a need to determine whether the use of cloud computing is cost effective, especially for the small businesses which many not have a lot of data to store (Etro, 2009). There is also need to determine the effectiveness of the securing safeguards that are in place to ensure that people who are not denied access to the information stored in the cloud, especially now that cybercrime is more of a threat for businesses than before. This study helps bridge this information gap by generating primary information on the factors that influence the uptake of cloud computing.
Research Questions
R1: To what extent does a relationship exist between cost-effectiveness, reliability, security effectiveness, the need for cloud-computing technologies and small business leaders’ decisions to adopt cloud computing technologies?
R2: To what extent does a relationship exist between cost-effectiveness and small business leaders’ decisions to adopt cloud computing technologies?
R3: To what extent does a relationship exist between reliability and small business leaders’ decisions to adopt cloud computing technologies?
R4: To what extent does a relationship exist between security effectiveness and small business leaders’ decisions to adopt cloud computing technologies?
R5: To what extent does a relationship exist between the need for cloud-computing technology and small business leaders’ decisions to adopt it?
Purpose of the Study
The purpose of this quantitative correlational study is to analyze if and to what extent a relationship exists between cost-effectiveness, reliability, security effectiveness, the need for cloud-computing technologies and small business leaders’ decisions to adopt cloud-computing technologies as perceived by 385 small business leaders in South Florida.
Alignment: The research topic aligns with IT Innovation and Strategy, which is a topic of DBA 8671 - Technology and Innovation Management course.
Theoretical Basis: Extended Unified Theory of Acceptance and Use of Technology (UTAUT2) will be used in this research because it aligns with the research topic of factors influencing cloud-computing technology adoption in small businesses (Venkatesh, Thong, & Xu, 2012).
Significance of the Study
This study is important because the information generated can be used in decision making by both players in the private and public sector. For instance, the information generated helps the private sector, more so the providers of cloud-based services to design the best approaches to increasing the uptake of cloud computing by small businesses. The government can also use this information in the formulation of policies that help small businesses weather the challenges that prevent them from taking up the technology. Additionally, the study helps contribute to the knowledge base on the impediments and the benefits of the adoption of cloud computing technology; information that can be used by small businesses in the decision making on whether or not to adopt the technology.
Hypothesis
H1a: A significant relationship exists between cost-effectiveness, reliability, security effectiveness, the need for cloud-computing technologies and small business leaders’ decisions to adopt cloud-computing technologies.
H10:A significant relationship does not exist between cost-effectiveness, reliability, security effectiveness, the need for cloud-computing technologies and small business leaders’ decisions to adopt cloud-computing technologies.
H2a: A significant relationship exists between cost-effectiveness and small business leaders’ decisions to adopt cloud-computing technologies.
H20: A significant relationship does not exist between cost-effectiveness and small business leaders’ decisions to adopt cloud-computing technologies.
H3a: A significant relationship exists between reliability and small business leaders’ decisions to adopt cloud-computing technologies.
H30: A significant relationship does not exist between reliability and small business leaders’ decisions to adopt cloud-computing technologies.
H4a:A significant relationship exists between security effectiveness and small business leaders’ decisions to adopt cloud-computing technologies.
H40: A significant relationship does not exist between security effectiveness and small business leaders’ decisions to adopt cloud-computing technologies.
H5a: A significant relationship exists between the need for cloud-computing technology and small business leaders’ decisions to adopt cloud computing technologies.
H50: A significant relationship does not exist between the need for cloud-computing technology and small business leaders’ decisions to adopt cloud computing technologies.
Variables
The independent variables are cost-effectiveness, reliability, security effectiveness, and need of cloud-computing technologies. The dependent variable is small business leaders’ decision to adopt cloud-computing technologies for the organization.
Theoretical Foundations and Review of the Literature/Themes
Advantages of Cloud Computing for Small Businesses
Cloud computing provides various benefits for small businesses; benefits that can help them grow and expand their reach. Firstly, cloud computing helps businesses minimize their costs, a fact that is influential on their profit margins (Apstu, Puican, Ukaru, Suciu & Toroda, 2013). This is achieved by reducing the need for the hardware through the virtualization process. This enables the value of the hardware already at the business to improve meaning that the business can achieve more operations without the need to spend on more hardware (Aljabre, 2012). Small businesses can also achieve more cohesiveness and collaboration by using cloud computing. The information saved in the cloud can be downloaded by the employees, allowing them to share information (Apstu et al., 2013).
The additional benefit of saving files in the cloud is increased flexibility. This is because employees can access the files without necessarily being at the business premise. This also means that businesses do not need to back up their information on a singular server (Carter, 2015). The aspect of security and access can be addressed by limiting the access to the files to the employees who have clearance (Apstu et al., 2013). In addition to these benefits, cloud computing also enables a higher degree of integration in the business by allowing access to other providers who use cloud-based services. For instance, back-office operations can be integrated with other departments such as accounting, human resources, and marketing. This relieves valuable time that can be used in order more pressing matters (Galarneau, 2009).
Factors affecting the Uptake of New Technology
Various scholars have postulated different theories have been postulated to explain the factors that affect the rate at which new technology is adopted. Venkatesh, Thong & Xu (2012) advanced the unified theory of acceptance and use of technology which summarized the research that had been performed previously on the issue. The scholars argue that the behavioral intention by people to use new technology is explained by constructs such as effort expectancy, facilitating conditions, performance expectancy and social influence. Performance expectancy describes the extent to the adoption of a certain technology will help an individual to perform a given task. More people will adopt a new technology if it helps them achieve certain goals or perform certain tasks in an expedient manner (Venkatesh, Thong & Xu, 2012).
The construct of effort expectancy is the extent to which the use of the new technology is easy for the individual. This means that new technology that is easy to use will most like be adopted at a higher rate compared to a technology where the ease of use is relatively low. The construct of social influence relates to how much the consumers think that the adoption of new technology is important. It also entails the perception of the people who are close to the consumer such as family members and friends. The implication of this construct is that if more friends and family members perceive the adoption of a certain technology as important, it is highly likely that the individual will also adopt the technology (Venkatesh, Thong & Xu, 2012).
The final construct is facilitating conditions which describe the perceptions of the consumer, the availability of resources to acquire the new technology, and the support that the consumer enjoys with regard to the adoption of the new technology. This means that if a customer perceives a certain technology as being important, possesses the technology to acquire it, and enjoys the support of the stakeholders in the business, there is a high likelihood that he will adopt the technology. These constructs are important to the study because they influence the choice of the variables of study (Venkatesh, Thong & Xu, 2012).
Nature of the Research Design for the Study
This research will be done using quantitative research methodology. The research design is a quantitative correlational design intended to analyze if and to what extent a relationship exists between cost-effectiveness, reliability, security effectiveness, the need for cloud-computing technologies and small business leaders’ decisions to adopt cloud-computing technologies as perceived by 384 small business leaders in South Florida.
Rationale for Methodology
The choice for the quantitative methodology is justified by the nature of the researcher and the benefits that the researcher can draw. The use of the quantitative methodology allows the researcher various benefits that are vital to answering the research question. Firstly, the researcher developed several null and alternative hypotheses to be tested as part of answering the research question (Bamberger, 2000). The quantitative methodology, unlike the qualitative methodology, gives the researcher the ability to apply statistical tests that allow him to test the hypotheses. Additionally, the researcher can determine the causality among and between different variable using tests that require a quantitative methodology. The results derived using the quantitative methodology can also be generalized to other populations (Bamberger, 2000).
Instrumentation or Sources of Data
This study will use both primary and secondary data. While the primary data is required for the answering of the research question and testing of hypothesis, the secondary data is required for discussing the trends emerging from the analysis of data. The secondary information will be acquired from the South Florida Population of small businesses: 901027 (U.S. Census Bureau, 2012). The primary information will be acquired through a survey that will be administered to the respondents who are chosen to participate in the study. The list of the people who comprise the study population will be acquired from Email-List.com. This is an email database that contains the contact information of Small Business Leaders. The database contains up to 1,050,730 contacts from which sample of 384 (Creative Research System Sample Size Calculator, 2012).
Data Collection Procedures
The data will be collected from the respondents using electronic means. An online questionnaire will be hosted by the Survey Monkey platform. The researcher will send an email to the 384 small business leaders acquired from the database described above in which the researcher will request their participant in the research through the completion of a survey over the Internet. The researcher will use set up a previously validated survey by Lease (2005), and later adopted by Ross (2010) and Hailu (2012). The email sent to the participants will also contain a link that will lead the participants to the exact page where the questionnaire is hosted. The researcher will collect the data electronically over the Internet using in Survey Monkey to assure participant’s anonymity.
Data Analysis Procedures
The researcher will employ Statistical Package for the Social Sciences (SPSS) to determine if any correlation exists between cost-effectiveness, reliability, security effectiveness, the need for cloud-computing technologies and small business leaders’ decisions to adopt cloud-computing technologies. Before the analysis of data, the researcher will clean the data and check for missing entries. The researcher will then code the data and enter it into the data analysis platform. The researcher will perform a factor analysis, and the results will be used for linear regression and variance tests. The hypotheses will be tested using the Chi-Square Distribution Test. The researcher will present the data using tables, graphs, and charts in order to ensure summary, simplicity, and ease of understanding.
Ethical Consideration
The researcher will obtain the permission to perform the study from the University department, the Institutional Review Board and the relevant governmental authorities. Given that the research uses human subjects, the researcher will make considerable efforts to ensure that the respondents are not harmed physically or psychologically. Among the considerations to be made by the researcher, the subjects will be required to fill an informed consent form before participating in the study. The informed consent form will explain the purpose of the study, the role that the respondent plays, the use of the information collected, the safeguards to ensure that the information is secure and confidentiality is guaranteed and the benefit and the rewards that the respondent expects for his participation.
The informed consent form will also inform the respondent that participation is on a voluntary basis and that he reserves the liberty to withdraw at any point in the study without the fear of reprisals. The information gathered through the study will only be used for the purposes of this study and will not be divulged to third parties. Any identifying information will be removed before the analysis of data to protect the confidentiality of the respondents.
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