Research Proposal Cloud Computing

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RESEARCH PROPOSAL

CLOUD BASED ERP : BENEFIT AND PITFALLS

LIVERPOOL BUSINESS SCHOOL

MODULE LEADER: Mr. ALEX WATTMODULE GUIDE : Mr. BOB MCLELLAND

RESEARCH SKILLS ANALYSIS (MGTMIM001 2009-2010)

TABLE OF CONTENTS

1. INTRODUCTION........................................................................................ 3

1.1.AIM.......................................................................................................... 4

1.2.OBJECTIVES ..........................................................................................4

2. LITERATURE REVIEW ...........................................................................5

3. METHODOLOGY .....................................................................................8

4. METHODS ..................................................................................................13

4.1.INTERVIEWS ........................................................................................13

4.2.FOCUS GROUPS .................................................................................13

4.3.SAMPLING ............................................................................................14

4.3.1. CASE SELECTION ......................................................................14

4.4.DATA ANALYSIS ...............................................................................14

5. ETHICS .......................................................................................................16

6. RESEARCH SUITABILITY ....................................................................16

7. PROJECT MANAGEMENT ....................................................................17

8. REFERENCES ...........................................................................................18

9. APPENDIX .................................................................................................23

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1. INTRODUCTION

Cloud computing is a new buzzword in the business industry today. The idea leading to cloud

computing paradigm is that the computing resources and software are available to the end

user, whether an organisation or an individual, in a virtualized environment (cloud) and the

user can access it on demand and using a ‘pay as you go’ approach. These services in

industry are respectively referred to as Infrastructure as a Service (Iaas), Platform as a

Service (PaaS), and Software as a Service (SaaS) (Hayes, 2009). One of the issues faced by

the organisations in the world today is need to make the organisational data globally

accessible while taking into account the intra organisational and extra-organisational data and

a cloud can be a very enabling medium for achieving this.

Enterprise resource planning software is a monolithic piece of software that integrates the

entire organisation into one giant entity while capturing, changing and automating the

organisational processes. The decision to implement an ERP is a very important decision and

is a onetime affair in most of the organizations of small and medium size. Chances of a

successful implementation of an ERP in an organisation are less. Also, it takes sizeable

amount of manpower, cost and effort to deploy and maintain the ERP. An entire ERP

application being outsourced is a relatively new idea and has been under discussion

frequently for its advantages and some latent disadvantages. In today’s world with such

economic conditions, it becomes imperative for an organization to reduce its operating costs

while increasing overall efficiency with the same amount of resources and to fulfil consumer

demands simultaneously. This is where a cloud based ERP can really help an organisation, if

not for some very pertinent disadvantages that have to be overcome to make this a more

viable option to a “best of breed” or an off the shelf ERP solution, globally.

A cloud based ERP is fundamentally different from the traditional ERP as it is designed from

scratch to provide a web based service to the customer. It shifts the main responsibility of the

infrastructure required by the organisation to an external service provider that specializes in

providing web based services. ‘Cyberinfrastructure’ makes the deployment of the business

systems easier and increases the scope of the applications that could be realised within the

organisational constraints such as budget and time. One of the major advantages is that the

user is abstracted from the maintenance of the software. A cloud based ERP can provide an

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organization much needed flexibility in terms of access to the required business processes

modules in the ERP when it intends to expand its range of operations or it acquires a new

organization. It can also help to divert the attention of the dedicated workforce away from the

maintenance and development and direct it towards the core processes that actually benefit

the organisation in a much better way.

Barriers to adoption of a cloud based ERP system are organisation specific. However, there

are some common issues that push organisations towards the adoption of such a system.

These comprise of cost savings, fault tolerance, on demand service, scalability and flexibility.

Concerns regarding a cloud based system include security, scalability, ease of migration and

licensing issues. There are some notable disadvantages that need to be overcome. A very

pertinent issue is regarding the security of the organizational data. Since the data is stored in

the cloud, an organization does not have a direct control over it. The security of the

organizational data is the responsibility of the service provider and this throws up a lot of

issues for an organization to consider before and after migrating to a cloud based ERP.

Another important issue is of a possible vendor lock in that might disallow the organisation to

migrate to another service provider when it desires it.

1.1 AIM:

To investigate the possible long and short term advantages and the disadvantages that an

organisation can derive from the adoption of a cloud based ERP

1.2 OBJECTIVES:

To analyse if a cloud ERP could prove to be a suitable alternative to the traditional

on-premise ERP (mission critical application).

To identify the merits and demerits of a cloud based ERP

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2. LITERATURE REVIEW

ERP systems are currently the prevailing form of business computing for many large

organisations in the private and public sector (Gable, 1998). An ERP manages and integrates

all the business functions in an organisation and this makes it much more than simple

software that take no thought to acquire (Boykin, 2001; Chen, 2001; Yen, Chou, & Chang,

2002). Organizations view ERP-enabled standardization as a vital means to integrate

dispersed organizational systems and provide a seamless access to information organization-

wide (Osterle et. al, 2000). ERP stores and processes data and allows it to be accessed in an

appropriate format, while stretching beyond the organisational boundaries (Gupta, 2000) (Al-

Mashari & Zairi, 2000) (Gardiner et al, 2002). Because these systems touch so many aspects

of a company’s it internal and external operations, their successful deployment and use are

critical to organizational performance and survival (Tanis et. al, 2000).

One of the major challenges in ERP adoption is flexibility with the integration of newly-

acquired business functionalities into its data processing systems with the minimum time

possible (Gupta, 2000). The flexibility of ERP systems refers to the extent to which an ERP

system may be dynamically reconfigurable to define new business models and processes

(Stedman, 1999). In the near-term perspective, managers find ERP implementation projects

the most difficult systems development projects (Wilder and Davis, 1998). ERP projects are

set apart by their complexity due to enterprise wide scope. Failures of ERP system

implementation and integration (Glass & Vessey, 1999) have been known to lead to

organizational bankruptcy (Bulkeley, 1996 ; Davenport, 1998 ; Markus & Tanis, 2000) or

partial adoption of the ERP system with only a few modules in place (Bingi et al., 1999;

Davenport, 1998).Customization is meant to describe changes or additions to the

functionality available in the standard ERP software. Even in the light of the benefits of

implementing ERP software, some organizations still choose to customize (Davenport, 1998;

Light, 2001). However, customization is very difficult when an organisation wants to

implement a whole new set of modules.

The online delivery of the software has been a long standing dream of the software vendors

and distributors, alike. Sato et al. (1999) and Bennett et al. (2000) put forward several areas

for future research, including integrating ERP and other systems on the Internet. Cloud

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computing is a fairly established system and has been in the offering since 2000-01 (Bennett

et al., 2000). The concept is deceptively simple and logical. Instead of buying the the license

for an application like an ERP software and then installing it on a machine, it is much cheaper

and convinient to lease the application from a company that created the software (Dubey &

Wagle, 2007).

A Cloud is a type of parallel and distributed system consisting of a collection of

interconnected and virtualised computers that are dynamically provisioned and presented as

one or more unified computing resources based on service-level agreements established

through negotiation between the service provider and consumers (Fox, 2009 ; Buyya, et al.,

2008). Applications built on cloud architectures run ‘in-the-cloud’ where the physical

location of the infrastructure is determined by the provider (Varia, 2008) and is abstracted

from the organisation, thus allowing the focus to shift from IT to business innovation. The

benefits of cloud computing are widely discussed in practice, focusing on increased agility,

availability, flexibility, cost savings and interoperability (Kim, 2009).

The separation of service provider from infrastructure provider has made it much easier for

new services to be established online quickly and with low financial risk, and to scale those,

services as demand dictates (Murray, 2009 ; Buyya, 2009). Using someone else’s

infrastructure on a pay-per-use basis converts the fixed costs into a variable cost based on

actual consumption , reducing initial investment and risk (Buyya, et al., 2008) (Fox, 2009).

Also the demand for online services can be very variable and poor response due to overload

can risk losing customers (Pandey, et al. , 2009). Cloud computing provides easy scalability

and the flexible creation and dismantling of resources that customers need only temporarily

for special projects or peak workloads (Leavitt, 2009 ; Fox, 2009 ; ECONOMIST, 2009)

giving it choice and control over its infrastructure. The ability to scale the use of cloud power

to match the demand also mitigates the risk of failure (ECONOMIST,2009) while making the

organisations more adaptable.

Cloud based ERP has a much smaller time scale for configuration and deployment. This has a

fundamental impact on the agility of a business and the reduction of costs associated with

time delays (ISACA, 2009 ; Hayes, 2009) allowing organisations to realise the competitive

advantage at a much earlier stage than the non adapters. Organisational data is available and

accessible globally through internet improving the overall collaboration in the organsation

(Scale, 2009 ; Armbrust, et al., 2009).

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When data is stored beyond the organisation, even with lock-tight security and data

management standards, there are confidentiality and privacy risks associated with this model,

not to mention potential industrial sabotage (Fox, 2009 ; Leavitt, 2009 ; Pandey et al., 2009 ;

Das et al.,2009). Also, with a distributed application architecture, there is no possibility for

local customization and development an you are limited to the interface the service provider

gives you (Fox, 2009).

Besides security, there are legal and regulatory issues that need to be taken care of. When

moving applications and data to the Cloud, the providers may choose to locate them

anywhere on the planet (Pandey et al., 2009) which subjects it to the laws of that country. For

example, specific cryptography techniques could not be used because they are not allowed in

some countries. Performance concerns may stop some companies from using cloud

computing for transaction oriented and other data-intensive applications (Leavitt, 2009)

(Hayes, 2009). Cloud services have reduced the cost of content storage and delivery, but they

can be difficult to use for nondevelopers, as each service is best utilised via unique web

services, and have their own unique quirks. (Tari, et al., 2009). A user could also get a nasty

surprise if they have not understood what they will be charged for (Broberg, et al., 2008).

Vendor lock-in is another problem that an organisation may have to face if they want to

migrate towrds a new service provider. (Armbrust, et al., 2009).

People are focusing on the core technologies that will lead their business forward over the

next five years and want to know how to manage varying degrees of risk wisely. They are

wary of making a complete jump in computing ideology in one fell swoop (ECONOMIST,

2009)

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3. METHODOLOGY

The learning style assessment was undertaken by the researcher adopted from Kolb and

McCarthy(1984). The results indicated that the researcher’s style is one of the interpretivist

and a diverger.

Research, according to (Smith & Dainty, 1991), is concerned with problem solving

investigating relationships and building on the body of knowledge. It is a plan or design with

the view to finding a solution to the research problem by social workers. Formulating and

clarifying the research topic is the most important aspect of the research project as it is the

starting point of the entire process (Alvesson & Skoldberd, 2000 ; Ghauri & Gronhaug,

2005 ; Mouton & Marais, 1990). Once the research topic is finalised, it becomes easier to

choose the research method. To understand the pros and cons of a cloud bases ERP system, it

is essential, that the background of the cloud based systems and virtualization of resources is

established along with the factors that may affect the bias of the subject (Denzin & Lincoln,

1998 ; Bogdan & Biklen, 1992).

Kolb (1984) created his famous model out of four elements: concrete experience, observation

and reflection, the formation of abstract concepts and testing in new situations. Kolb and Fry

(1975) argue that the learning cycle can begin at any one of the four points - and that it

should really be approached as a continuous spiral. The researcher tilts towards the diverger

which suggests a preference for an interpretivist approach. Saunders, et al. (2003) discusses

deductive and inductive research methods. Johnson (1996) describes the inductive theory as a

mirror image to deductive which starts with an established theory (Spens & Kovacs, 2006).

An individual makes a number of observations which are then moulded into a concept or

generalization. Since the researcher is trying to develop and understanding into the

advantages and disadvantages of a virtualised ERP from an organisational perspective, which

has a high number of conflicting views (ECONOMIST, 2009), inductive approach is a better

option as it helps to deal with uncertainty by linking all the contextual factors into a single

overall view.

Methodology is a way of thinking about and studying social reality (Strauss & Corbin, 1990).

Bazeley (2004) mentions that approaches taken to defining “qualitative” and “quantitative”

have long been associated with different paradigmatic approaches to research, different

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assumptions about the nature of knowledge (ontology), and the means of generating it

(epistemology) . Babbie and Mouton (2001), Denzin and Lincoln (1994), Du Plooy (2001),

Marshall and Rossman (1995), and Mason (2002) describe qualitative research as a paradigm

that allows the researcher to get an “insider perspective on social action”. Babbie and Mouton

(2001) further describe the primary goal of this research approach as describing and then

understanding as opposed to merely explaining social action. Qualitative research contributes

to discovery and theory-building (Gilles, 2000) which is what is being attempted by the

researcher here with respect to a cloud based ERP.

Qualitative techniques based on the interpretation of non-numerical data can provide meaning

to human behaviour missing in quantitative data (Rossman & Marshall, 1999 ; Creswell,

1994). It seeks to develop sensitizing concepts and the meanings of central themes in the life

world of the subjects (Maykut & Morehouse, 1994). Acquisition of an ERP is a major

decision which affects the organisation on multiple levels. The ‘intangible’ factors related to

changes and its adaptability or competitive advantage, are difficult to quantify and a

qualitative approach is a better suited mode of research here. Qualitative approach is based on

the belief that the persons are actors who take an active role in responding to situations and

the realisation that the response is based on a certain meaning (Strauss & Corbin, 1990 ;

Rossman & Rallis, 2003). The understanding of this meaning is defined and redefined

through interaction with sensitivity to conditions and the relationship between condition,

action and the result. Qualitative analysis allows for finer differences to be brought to light

which will allow the researcher to investigate his case thoroughly. Denzin & Lincoln, (1998)

summarise the characteristics of this approach as enabling the researcher to study phenomena

in their natural settings, while attempting to interpret these phenomena in terms of the

meanings people bring to them.

Observations are the starting point for this approach (Kvale, 1996) and seek to develop

theory, but not test it (Rossman & Rallis, 2003). Qualitative researchers analyze their data

inductively using a bottom up approach. Induction is usually described as moving from

specific observations to broader generalisation and theories (Miles & Huberman, 1994).

Glaser & Strauss (1967) and later Strauss & Corbin (1990) mentioned grounded theory where

the theory is grounded in the observations made by the researcher. Inductive approach is

intended to aid the researcher to understanding of meaning in data through the development

of emergent themes or categories. These themes are likely to be based on premises of the

research such as security, adaptability, performance factors, scalability etc and will guide the

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researcher when examining and analysing the data, thereby forming theory. Since qualitative

methods can be used to explore substantive areas about which little is known or have

conflicting views (Stern 1980; Rossman & Marshall, 1999), this approach is better suited to

this research topic.

Grounded theory is an inductive, comparative, and interactive approach research that offers

several open-ended strategies to identify emergent themes. Grounded theory used the

inductive approach towards the research with no preconceived notions (Glaser & Strauss,

1967) about the research topic. This use of induction and deduction is supported by Bryman

and Bell (2003) who argue that grounded theory is an iterative process which includes

elements of both induction and deduction. The analysis within grounded theory is done as

the constant comparative method. This included comparing incidents within each category,

comparing categories to each other, clarifying the developing theory, and writing a coherent

theory as a result. (Glaser & Strauss, 1967 ; Strauss & Corbin, 1990). A key concept for this

approach is “theoretical sensitivity” (Glaser, 1978), which can be described as an ability to

perceive the interactions between the relevant themes and factors. The researcher finds this an

apt approach due to his interpretivist nature and the fact that the cloud computing is a novel

concept that can be adopted by every organisation due to various set of factors which can

have a varying degree of influence on the decision.

Interview is the primary technique of the researcher here. The main task in interviewing is to

understand the meaning of what the interviewees say (Kvale, 1996). An interview seeks to

determine the factual information along with the contextual information. An interview with

the subject in its natural environment brings out the nuances in their perspectives and the

definitions are continuously refined (Kalnis 1986 as cited in Marshall and Rossman, 1995).

However a cloud based ERP is a relatively new concept and is a major decision on behalf of

an organisation to actually adopt it. It is important that the data gathered from an interview be

viewed in relevance to the background of the subject being interviewed as some of the factual

information may not make much sense or may stand to be misinterpreted if it is not seen

along with the circumstances that affected it (Saunders, et al., 2003).

Quantitative research allows the researcher to familiarize him/herself with the problem or

concept to be studied, and perhaps generate hypotheses to be tested. This approach is often

viewed in contrast to qualitative approach (Bogdan & Biklen, 1992) (Firestone, 1987). In

this paradigm, the emphasis is on facts and objective data (Bogdan & Biklen, 1998) leaving

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out the circumstantial evidence. Guba & Lincoln, (1994) say that research and in has been

dominated by a need to quantify the hypotheses. Guba & Lincoln (1994) have further

challenged the effectiveness of quantitative techniques to quantify hard facts when social

factors are concerned due to the objective nature of the approach as it tends to leave out the

context of the information. Also, it limits the scope of the research as it does not encourage

the researcher to look beyond the aims and objective.

Every method has its drawbacks and qualitative approach is no exception. According to Stiles

(1993), Patton ( 2001) and Lincoln & Guba (1985), validity and reliability are the factors that

affect the quality of the traditional qualitative research. Denzin & Lincoln (1998) put forward

four factors to establish the correctness of the data and research: credibility, transferability,

dependability, and conformability. It would be very difficult for another researcher to

reproduce the survey and replicate the finding for confirmation of the research with the same

amount of validity and personal bias. Generalizing the findings of the report is an aspect of

the high quality reports. Maxwell (1992) suggests that it is easier to generalize findings in the

quantitative research and is a potential drawback in this study. Patton (2001) argues that the

generalizability is a criteria that is subjective to the individual case study. Also, according to

Cassell & Symon (1994), it is easy to drift from the original context of the research when

using the qualitative approach due to the changing context of the research

A phenomenalist considers that each event is unique and is controlled by variables such as

time, location and culture which lead to the conclusion that in probability, no two events are

of similar or identical (Bolender, 1998) when taken with their context. Every organisation

may have its own reasons to either acquire or shun a cloud based ERP and these factors are

unique to each organisation which reflects the disposition of the organisation lending itself to

being subjective. The end result would be a descriptive that is mainly expressed in qualitative

terms.

In general, the researcher is pursuing an inductive qualitative approach due to which a

relation can be established between what the subject is expressing, what he means, the

background and the culture he is from and what he requires. This is supported by Elliott

(1995) and Strauss and Corbin (1990) who has taken the position that qualitative research

lends itself to understanding participants’ perspectives Saunders et al. (2003) and Bazeley

(2004) articulate a case for the epistemological relevance of both forms of knowledge and

that it is important to understand how both are established and grounded. It is not that the

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researcher does not want to pin the issues empirically and statistically. It has more to do with

the caution of not rushing into the subject and realising the fact that the decision to adopt a

cloud based ERP by an organisation is influenced by a lot of contextual factors and the

responsible factors are is not easily fathomed through quantification (Strauss & Corbin,

1990). Apart from this, an ERP is not pervasive, “everyday” computing and it becomes

difficult to gather statistical data from varied sources.

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4. METHODS

4.1 INTERVIEWSInterviews are the primary method of data gathering here. Interviews are descriptive and

identify the issues in depth in a holistic perspective (Kvale, 1996). Interviews are an

important part of any action research project as they provide the opportunity for the

researcher to investigate further, to solve problems and to gather data which could not have

been obtained in other ways (Cunningham, 1993). On the downside, they are time consuming

and, unless sampling is done carefully, may yield low quality data. Researcher should also

keep his personal bias in check or the results could be skewed which jeopardizes the entire

research (Williams, 1993 ; Saunders et al., 2003).

Interviews are primarily of three types: Structured, unstructured and semi structured

(Saunders, et al., 2003). The researcher here intends to use semi structured interview

approach as this helps him to delve deep into the interviewee’s background and giving him

enough flexibility to probe and explore any themes that he may find relevant to his research

in some depth (David and Sutton 2004). Probing is the way for interviews to explore new

paths that were not considered at the beginning (Gray, 2004). This may be achieved through

additional questions that were not in the interviewer’s mindset earlier.

One of the drawbacks of a semi structured interviews is that interviewer may not recognise

and prompt those themes of which he is ignorant about due to a mismatch in the backgrounds

of the interviewer and interviewee and this should be kept in mind before taking this

approach (David & Sutton, 2004).

4.2 FOCUS GROUPS The aim of the combined use of multiple methods is to add something unique to the

researchers understanding of particular phenomena. This approach relates to ethnography

which is a blend of interviewing and observation (Willis, 1990) and is very useful to add

various perspectives to the data, due to the cascading effect (Lindolf & Taylor, 2002) of the

discussions that is gathered through other qualitative methods such as individual interviews

etc. These would be difficult to gather and identify through interviews solely. The group

interview is essentially a qualitative data gathering technique that finds the

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interviewer/moderator directing the interaction and inquiry in a very structured or

unstructured manner, depending on the interview's purpose (Denzin & Lincoln, 1994).

The researcher will have small sized groups of 5-7. The idea is to keep the group size small

enough to be managed effectively while capturing the essence of the discussion easily.

Homogeneity of the group is an important factor and this is automatically taken care of ,

since all the participants are from India.

4.3 SAMPLING :

Purposive sampling is one technique often employed in qualitative investigation (Rossman &

Marshall, 1999). With a purposive non-random sample the number of people interviewed is

less important than the criteria used to select them. Marshall (1996) describes three methods

of sampling which are convinience, judgement and theoretical sample. The researcher would

pursue theroretical sampling where he would analyse the emergent themes and choose the

next sample to elaborate these themes. Glaser and Strauss (1967) propose that the samples

should be taken and the emergent themes should be compared to the previous samples in an

interative format unless a theoretical saturation point is achieved. This would increase the

validity and strength of the researcher’s theory.

4.3.1 CASE SELECTION : It is very important to have a criteria or a framework of requirements in place on the basis of

which each individual is chosen to be interviewed. This would give some sort of credibility to

the data being collected. Researcher also keeps in mind that it is difficult to achieve statistical

representation of all the organisations in India that use or are likely to use cloud based ERP.

Hence snowballing is the most practical approach to get the next suitable subject for the

interview but it is this set of criteria that actually justifies him to be an ideal candidate to be

interviewed.

4.4 DATA ANALYSIS The technique for data analysis is microanalysis (Strauss & Corbin, 1990). The researcher

analyses the data as he gathers it and codes it into probable emergent themes which are based

on his judgement and supported by literature. As and when new data is gathered, same

process of coding is repeated with it. These codes are then compared to the previous codes

and if any new themes emerge are noted. This is an iterative process called ‘constant

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comparison’ that is done every new set of data that is collected until the researcher saturates

the themes i.e. no new insights can be obtained from the data.

Axial coding is then applied to the derived themes and these are collated towards a central

theme based on the linkage between their properties. This helps in abstracting the high level

factors and their inter-relationships. These higher level factors then form the basis for the

construction of the theory.

QSR NVIVO is going to be used in this research to transcribe and analyse the interviews and

will utilise the “node” feature in the software to perform coding and develop central themes.

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5. ETHICS: Once the research project is embarked upon, care should be taken to keep in mind the

concerned ethical issues (Field and Morse 1992). Ramos (1989) mentioned the problem areas

that the researcher should be aware of: the researcher/participant relationship, the researcher’s

subjective interpretations of data, and the design itself. The principles of ethical propriety,

upon which most of these guidelines are based, involve fairness, honesty and openness of

intent. Some of the ethical issues that should be considered here are informed consent, data

protection, confidentiality and anonymity.

Interviewer’s should inform the subjects about the purpose of the study, expected time for

interview and the scope of the study to enable the subjects to reach their own decision of

whether or not they want to be a part of the study. This should be done orally and in writing

(APPENDIX).Interviewer should comply with the laws of data protection and confidentiality

and the arrangements for the same should be conveyed to the participants. If a subject wants

to remain anonymous, it should be left on him/her.

Certainly, no person should be asked to cooperate in any research that may result in a sense

of self-denigration, embarrassment, or a violation of ethical or moral standards or principles

(Leedy, 1997)..

6. RESEARCH SUITABILITY The researcher is a graduate in Information Technology (B.E.) from Visvesvaraya

Technology University, with a specialisation in mobile systems and distributed computing.

He has also completed his Cisco Certification and Red Hat Certification (Cisco Certified

Network Associate & Red Hat Certified Engineer). He has also worked in Hewlett Packard

Sales Ltd, Bangalore, India where he was employed as a system administrator. This has given

him a decent exposure to networking technologies.

The researcher was always of an entrepreneurial mindset and this led him to LJMU for his

MBA. Here he evolved rapidly over a period of a year in his understanding of various aspects

of business. Cloud computing is an extension of grid computing and technically is a sort of

distributed computing. This got the researcher intrigued in the subject. Coupled with the fact

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that he had taken up Business analysis as his elective, he chose “Cloud Based ERP : Benefits

and Pitfalls” as his topic.

7. PROJECT MANAGEMENTThis research can be treated as a mini project with apt deliverables and a timeline to follow. It

has been broken down into various stages, each with its own time duration. Research starts on

21st Dec, 2009 and the Introduction stage finishes by 24, Dec 2009. At this stage, the aim of

the research and the high level objectives are totally laid out.

Literature review starts on 25, Dec 2009 and includes the use of NVIVO give shape to the

argument flow being presented. The end of this stage should produce a literature review that

is more or less complete.

Methodology involves the learning style assessment and arguments in favour and against of

qualitative methodology as this is the primary approach of the researcher here. This takes 9

days overall and finishes by 25 Jan, 2010. Data collection is a huge task and takes 15 days.

Transcription and coding the data takes another 5 days and this finishes by March 2, 2010.

Final writeup and referencing takes 7 and 3 days respectively and are done by April 7, 2010.

Proof reading takes another 6 days and is done by 16th April, 2010. 2 days are allocated for

any last moment amendments and the report is sent to be printed on 26 April, 2010.

The final copy is submitted on 5 May, 2010.

8. REFERENCESAl-Mashari, M., & Zairi, M. (2000). Supply-chain re-engineering using enterprise-resource planning (ERP) systems: an analysis of a SAP R/3 implementation case”,. International Journal of Physical Distribution & Logistics Management , 30 (3/4), 296-313.

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Alvesson, M., & Skoldberd, K. (2000). Reflexive Methodology. SAGE Publications Ltd.

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9. APPENDIX

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Research Proposal Cloud Computing

Documents

Transcript of Research Proposal Cloud Computing