Write a Business Research Proposal for Cloud Computing System.
The application of cloud computing as a platform has started catching wind globally more so with development of technology (Wang 2013). From multinational companies to small enterprises have started embracing cloud services as part of their strategic operations (Weinman 2012). However there are various pitfalls which are necessary to be looked into before assessing whether the system can be considered as a viable business platform. This research will therefore try to evaluate the viability of cloud computing system as business opportunity to be exploited. The business research proposal will also highlight, a proposed research methodology to be used to assess whether cloud computing system is an investable venture, or not.
The main objective of this business proposal is to analyze the viability of cloud computing as a business venture. To accomplish the main objective, the research will try to evaluate two main aspects; the first will be the potential investment areas of cloud computing, and the second will be to analyze the potential challenges which the cloud computing system is expected to face.
The main scope of the project is to deal with the various functionality which can be related to the concept of the cloud computing. The access to the different features of the cloud computing and how they can be taken advantage of.
What is cloud computing?
Using the definition by the National Institute of Standards and Technology as highlighted by Wang et al (2015), cloud computing is 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
Common characteristics of cloud architecture
There are various systemic characteristics that form up the whole cloud computing system. These characteristics need to be looked at before considering it for adoption and possible implementation;
On demand service: cloud computing operates under the pretext that the consumer will access the cloud services at any point in time without need for contacting the service provider (Antonopoulos and Gillam 2017). This means that the system has to work as seamlessly as possible in order to avoid any need for service support.
Loose coupling: to ensure that an on demand service is always maintained at all times, the necessary cloud computing applications are built in a way that decreases tight component interdependencies (Suakanto 2012). By doing so, if there is any fault in one of the components, the system would continue working appropriately without incurring any problem in the functionality.
Wide network access: a cloud computing system is supposed to provide a reachable wide network access and a platform that accommodates heterogeneous users with varying cloud computing needs (Halpert 2011).
Independent scalability: it is indicated by Suakanto (2012) that a cloud computing system is supposed to ensure that every component of the application would be a service interface which would be responsible for its own scalability.
Parallelization: this mainly focuses on the aspect of distributing tasks to multiple machines and execution would be done in more than one manner (Ali, Khan and Vasilakos 2015).
Justification of the Cloud service model
A prospectors question would then be, why a cloud computing system? The cloud service system helps the different business organizations to implement the concept according to their requirement and how they want to use the service. There are basically three types of cloud service models which are available that are explained below:
Advantages of cloud computing.
Scalability concept: (Avram 2014) indicates that the cloud service is elastic in nature which basically means that the resources can be scaled up and scaled down according to the need of the organization. Sometimes it can be seen that the need of resources are high at that particular time it can be scaled up and on the other hand when the need is less it can be decreased accordingly.
Operational benefits: There are different types of operational benefits which can be achieved from the concept of the cloud and with the mitigation of the business to the concept of the cloud. Some of the aspects which can be stated with the approach of the operational benefits are stated below:
Flexibility and mobility aspect: The main focus point which is related to the concept of the flexibility is that the access to the cloud can be achieved from anywhere (Linthicum 2018). In most of the situations the data of the user are stored in the concept of the cloud computing which mainly means that the organization or the user can directly access the data from anywhere.
IT staffing: in most of the cases the aspect which is related to the IT staffing play a dominating role. In the concept of the cloud computing the maintenance sector is removed from the aspect which leaves less human intervention into the approach.
Self-service providing: in the concept of the cloud computing it can be stated that one of the most common approach to the aspect is the self-service were the user can us the interface which are available to them in a variety of manner (Ali, Khan and Vasilakos 2015). In this context it can be stated that the interface which are available by the concept of the cloud computing are very easy to use and any person can easily indulge into the aspect
Reduced cost: The reduction of the cost concept can be considered one of the most vital aspects relating to the working towards the concept of the cloud. The cloud services gives direct provisioning for the aspect of using the resources of the technology as needed and pay accordingly. In this aspect the utilization of the resources are maximum (Avram, 2014). The sector of updating the software and other maintenance cost are also highly reduced in the concept. The main cost reduction in this aspect would be the sector of involving highly OT expert professional into the service (Almorsy, Grundy and Müller 2016).
Reduced time to launch: launch time is the time which is required for any application to be build and the time which would be required for the normal people to use them . With the concept of the cloud computing the organizations can easily indulge in the delivery of the product in a short span of time Weinman, 2012)
Eco friendly: the concept of cloud computing can be considered as eco-friendly due to the fact that it directly reduces the overall cost which is involved into the sector of adaptation of the hardware components (Wang 2013). Thus it can be stated here that, the hardware components are directly moved to the concept of the cloud which is often has a preexisting infrastructure which is centralized such as a data centre
Challenges likely to be faced when implementing cloud computing
Cloud computing however can be stated of having different types of challenges attached to the technology just like any other technology in recent times. In this context lots of researches are being done which directly focus on the aspect of removing all the measures which are related to the pitfalls of the cloud computing concept (Grobauer, Walloschek and Stocker 2011, Martin-Flatin 2014). Some of the challenges of the cloud computing is discussed below:
Security: security in any type of technology that can be considered to be vital. The data of the organization when stored in cloud, they are very much vulnerable to be accessed by unauthorized users (Pandith, 2014). This can be a major challenge given the value of data and information privacy
Data loss: there is high risk of data loss in case of a virus attack. Cloud systems are usually targeted by malicious individuals with the aim of either retrieving or causing damage to the stored data (Wei et al., 2014).
Compatibility issue: compatibility can be directly related to the legacy system. On the other hand it can be stated that the aspect of moving from one cloud service provider to another cloud service provider can be a big problem which is facade most of the times.
License issue: according to a journal by (Oppenheim 2011), the utilization of the software’s can be of big problem due to the license factor which is involved into the implementation of the system. More so since the system is functional from a global stage where different countries have different laws and regulations governing the use of licensed software.
Research question
Main research question: Is cloud computing system viable for business adoption?
Sub questions
We have seen from the literature that cloud computing is a service used by a number of organizations for varying reasons. It has been established that the organization is bound to benefit in various ways by implementing the cloud service but at the same time a fair number of challenges emanating from the cloud computing system have also been noted. It is for this reason that the research proposal will try to do an in-depth analysis to ascertain the viability of adopting the system.
Qualitative research
Qualitative research is a type of research aimed at collecting research results using non numerical methods. It aims to analyze data which in not numeric and inductive in nature, and in most cases used to generate theories (McBurney and White 2013). Since we are trying to evaluate the viability of cloud computing system, part of the data will be heavily reliant on non numeric information more so the secondary data. Qualitative research will also be used to help in generating theories as stated. It will also be used to make inference rather than giving generalizations of the data collected, and finally as stated by Snelson (2016), qualitative research takes the views of each respondent into consideration.
Qualitative research entails a step by step process with each step having its own important relevance (Abutalibov and Guliyev 2012). For this business proposal, there are several proposed steps listed below that are to be followed in order to collect the relevant data.
The first step proposed, is actually defining the research questions which has already been done. The questions have to be focused and aimed at achieving a specific objective (Kishore, Vasundhra and Anand 2011). The research questions formulated will steer the data collection process. If the research question formulated does not meet the set standards, then the researcher is bound to have a hard time to collect relevant data (Kishore, Vasundhra and Anand 2011).
Collection of relevant data necessary for establishing the various parameters involving the cloud computing system is the next proposed step where, the researcher will set up or identify the location where he is to gather the data. The researcher has to be as unobtrusive as possible in order to have as minimal influence on, the results or collection setting, as possible. In as much as qualitative approach to data collection is suited for small target population; it can still be used in a large but manageable target population.
Analysis of the collected data should ensue thereafter to make sense out of that data. Data can be defined as raw unprocessed information. It is through analysis that one can make meaning out off it. There are various activities involved in data analysis i.e. sorting and coding of data for easier synthesis of results.
The findings will have to be scrutinized before presentation to the top management. This is to ensure that the results are valid and reliable and can be used to make the necessary business decision. Qualitative research is known to pose a challenge when it comes to ascertaining the external validity of the findings (Morse 2015). The aspect of biasness in qualitative research has to be taken into consideration lest the validity of the results be affected.
The last step proposed is the actual reporting of the analyzed and validated findings. The top management have to be informed of the conclusion of the research in order for them to take the necessary action on whether to adopt a cloud computing system or not. The methodology of reporting has to be clear and in a manner conversant to the consumers of the report (Edwards and Brannelly 2017).
Approaches to reliability and Validity in qualitative research
The subject of validity and reliability in qualitative tools is a thorny issue to the nature of the research itself. The validity and reliability actually affects the credibility of any research. It is also these two aspects that will determine the soundness of the findings to be presented which will in turn have implications to the decisions taken thereafter (Leung 2015). Due to these implications, the issue of validity and reliability in qualitative research has to be handled with due care.
Validity in quantitative research is the ability and accuracy of the chosen quantitative research method to measure that which it is intended to measure while reliability is the degree of a research tool to repeatedly offer the same results on repeated trials (Salkind 2010)…
For this research, it is proposed that three methods suggested by Ihantola and Kihn (2011) be employed. These three methods can be used to measure conformance to both validity and reliability of the research. The said methods are credibility for measuring internal validity, applicability which is used to measure external validity, and finally consistency which can be used to measure reliability
There are several proposed approaches to ensure that both validity and reliability standards are conformed to in this research.
Using the three named measurement tools, for example applicability, the researcher will propose to structure the questionnaire in such a manner that the description is deeply elaborate such that external validity is conformed to as much as possible. Self reflection is also a method that can be used to minimize deviation of external validity.
Credibility on the other hand can assured by the researcher increasing the duration of engagement with the target area under study. This will help the researcher have as much information as possible on a subject matter. Many at times as cited by Leung (2015), qualitative researchers tend to reach premature conclusion to inquiry due to limited duration of interaction with the area or individuals under study. Deviant case analysis is also a method that can be employed for checking the credibility of the data collection method
For consistency, one of the common proposed methods is by using an external auditor to come and evaluate how reliable the research instrument is. The audit inquiry is supposed to show whether the process or the tool used to collect data is able to do so consistently.
Sampling, and Sample Size,
Sampling can be termed as the process of selecting or identifying a specific item for investigation from a bigger group known as target population (Naderifar, Goli and Ghaljaie 2017). A sample will allow the research to collect data for making inferences. Sample size on the other hand can be termed as a portion or a number of items selected from the arget population (the whole population under study) (Keller and Casadevall-Keller 2010).
With respect to qualitative research method, this business research proposal should employ non-probabilistic sampling purposive to be exact which as explained by Etikan (2016) provides the researcher with a multitude of tools at his disposal to obtain his sample. The researcher however has to be careful since this type of sampling technique is said to portray a high level of bias if not controlled.
Data Collection Method,
When carrying out qualitative research, there are several avenues or methods for data collection namely; interviews, document analysis, observations, focus groups just to mention a few (Sutton and Austin 2015). The proposed qualitative methods for data collection for this research are two. Structured and semi structured interviews, and document analysis.
Secondary data necessary to provide theoretically data will be obtained using document analysis where relevant documents will be selected. The interviews on the other hand will be done to employees of three organizations who have already established the cloud computing platform. Interviews as explained by McBurney and White (2013).are preferable since they are a cost effective method o data collection and it is easy to seek further elaboration from the respondent if need be.
Quantitative research
Unlike qualitative research, quantitative research is a research design with numerical methods of collecting and processing data. It is a design used many at times to collect primary data from respondents (Jensenius 2014). One of the known positive factors of this type of researcher design is that, it can be used to collect a data from a large sample size and in a faster and efficient manner at that, as compared to the alternative research resign (Vogt 2011). There are various aspects of the proposal which will require numerical data to be collected and analyzed. Quantitative method will allow us to carry an objective statistical analysis on the viability of cloud computing system without individuals’ influence on the data collected (Bryman 2012). Using simple statistical presentations, qualitative method will aid the business proposal to make presentations which can simpler and easier to understand as compared to qualitative research (Bernard 2013). These are just but some of the benefits which have prompted this research to adopt the use of quantitative research to supplement qualitative design.
There are various steps that are proposed in order to carry out a successful quantitative research. Just like qualitative research, the first step should be an analysis of the problem which has been established as whether or not to adopt the cloud computing system.
The next proposed step should be a review of relevant literature which should act as the base foundation on which the research findings should be laid upon. Review of already written literature is done by analyzing secondary information collected using qualitative research (Duignan 2014). Formulation of the research hypothesis should ensue thereafter.
Selection of the research design is also a very important part of the process which is proposed to be given due consideration. In most cases, the type of research design used for similar research is what is normally termed as descriptive research design. Descriptive research design will help us define the characteristics of cloud computing system and its viability before adoption (Omair 2015).
After the research design has been selected, it will be easier to now consider where the sample is now going to be obtained from. This brings us to the next proposed step in which will be used to carry out this research and that is the identification of the research sample population. This business proposal should use probabilistic sampling methods to identify the wanted research sample size according to the guidelines provided by Etikan (2016). Choosing the right sample size will be important in ensuring that the research results are able to measure accurately that which it is intended to measure (Bernard 2013).
After a proper sample from the identified individuals and organizations with the relevant information on cloud computing system has been selected, the collection of data should ensue. There are various data collection techniques available that can be used when conducting quantitative research. For the purposes of this business research proposal, questionnaires, interviews and direct measurements will be used.
Another proposed step is analysis of the collected data. Since data collected in quantitative analysis in numerical in nature, it needs to be put into the relevant classifications and various descriptive analysis or statistical techniques like frequencies, mean, cumulative frequency etc, employed in order to make sense of the findings (Hoeks, Kardys, Lenzen, van Domburg & Boersma 2013). The last proposed stage is relaying the findings to the management for decision making
Research Instrument,
As earlier stated, there are various research instruments at the disposal of a researcher that can help him collect data from the target sample. The proposed tool for data collection in this research will be questionnaires. The reason for the selection of questionnaires as the preferred data collection tool is indicated by Saunders, Lewis & Thornhill (2016), who terms them as being efficient and are marginally cheap and easy to formulate and distribute. It is also proposed that structured interviews be used to supplement the questionnaires in collecting data.
Quantitative Data Analysis Process
The basic essence of quantitative research is its nature of data which is numerical. There are various methods of analyzing numerical data however, for this research it is proposed that adoption of descriptive statistics for data analysis will be the most apt choice. Descriptive statistics is aimed at using various statistical techniques to analyze collected data for easy interpretation (Thomas 2014). The research can employ the use of percentages, frequency, and standard deviation among other statistical methods to come up with usable data which can later be presented on tables, graphs or pie charts for easy reporting and explanation.
Sampling and Sample Size
There are various methods of sampling that can be used when carrying out quantitative research. Most of these methods are probabilistic methods. From the characteristic of the identified target population and the size, the correct method of probability sampling can be selected. Simple random sampling is widely used due its simplicity in execution (Saunders, Lewis & Thornhill 2016). The sample size should be manageable enough giving into consideration the aspect of time and resources; at the same time, it should not be too small since it will not depict the true picture of the phenomenon under study (Omair 2014).
Reliability and Validity of Data
There are potential threats identified that can affect the validity of the research findings. For external validity, they can be listed as time, environment and population. The time allocated for the research and the sample size selected can influence the amount of data collected which can in turn have an impact on the validity of the research data (Bernard 2013). The environment where the data is to be collected can also have an impact on the validity of the data. To conform to standards of reliability and validity, the research should use almost similar techniques employed in qualitative research but give due consideration on sampling, and allocation of resources to ensure that external validity standards are adhered to.
Research Limitations
The research is expected to face various limitations; one of them being the limitation to access of information necessary to describe the applicability and viability of a cloud computing system. Given the nature of the research, targeted businesses where the research is to be conducted might be inclined to decline sharing of vital information relevant to this research.
There is also the limitation emanating from bureaucratic processes involved before an organization allows data pertaining to cloud computing system to be collected. This data can be considered to be highly confidential thus posing collection challenges. The bureaucratic nature of organizations might also make the whole process to consume more time than previous anticipated.
There is also lack of willingness by respondents to participate in the study. This can be due to lack of interest or personal fear of incrimination or punishment emanating from the research findings
Research timeline
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Final assembly of the research proposal |
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Presentation of the proposal |
Conclusion
From the report it can be identified that cloud computing can provide the organization with competitive advantage. It however goes without saying that implementation of the system can ace a fair share of challenges but when those challenges are mitigated properly the benefit of such a system are tremendous. In most of the times business bodies tend to move to the concept of the cloud in order to gain competitive advantage in the working of the organization in both internal and external sectors which are discussed in the report. Research is being conducted in different areas of the cloud computing and it can be stated that in the future it would play a dominating role. Further the research proposes various techniques both qualitative and quantitative that can be used to come up with valid and reliable information to be used by the management for decision making on whether to adopt or reject the cloud computing system.
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