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Methodology can be considered as a way of studying and thinking about social reality (Strauss & Corbin, 1990). Beazley (2004), argues that approaches used in defining ‘quantitative’ and ‘qualitative’ have for a long time been connected with epistemology (means of generating it), differing assumptions concerning the nature of knowledge (ontology), and differing paradigmatic avenues to research. Manson (2002), Marzhall & Rossman (1995), Du Plooy (2001), Denzin & Lincoln (1994), and Babbie & Mouton (2001), identify qualitative research as a standard that permits the researchers to acquire an ‘insider perspective on a social action’. Babbie & Mouton (2001), additionally identify the primary goal of qualitative research approach as describing and then understanding in contrast to simply clarifying social action. Qualitative research leads to theory-building and discovery (Gilles, 2000), and the researcher here is attempting to achieve this with respect to a cloud based ERP. 

Based on non-numerical data interpretation, qualitative techniques can establish meaning to human behaviour no identifiable in quantitative data (Rossman & Marshall, 1999; Creswell, 1994). It attempts to formulate informing concepts and central themes meanings in the life world of subject study (Maykut & Morehouse, 1994). An organization is affected on multiple levels through the acquisition of an ERP. It is difficult to quantify the ‘intangible’ factors associated with changes and competitive advantage or its adaptability; hence, qualitative research approach is the best suitable mode of research here.  Qualitative approach is founded on the notion that the individuals are actors who assume active roles in reacting to conditions and recognizing that the reaction is grounded on a definite meaning (Strauss & Corbin, 1990; Rossman & Rallis, 2003). Comprehension of this meaning is defined as well as redefined by interacting with sensitivity to conditions, and the association between condition, action and the result.  Qualitative analysis assists in identifying minor differences which will help the researcher to examine his or her case exhaustively. Denzin &Lincoln (1998), present the characteristics of qualitative research approach as empowering the researcher to investigate phenomena in their natural settings, while trying to interpret these phenomena according to the meaning people assert to them. 

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The starting point of this approach is observation (Kvale, 1996), which attempts to establish a theory, but not test it (Rossman & Rallis, 2003). A bottom up approach is used to analyse data inductively by qualitative researchers. Induction is outlined as an advancing from specific observations to wider generalisation and theories (Miles & Huberman, 1994).Glaser & Strauss (1967) and later Strauss & Corbin (1990) acknowledged grounded theory in which the theory is grounded on researcher’s observations. Inductive approach is designated to help the researcher understand the meaning in data by the development of emergent categories or themes.  These themes are expected to be based on the assumptions of the research such as scalability, performance factors, adaptability, security, among others and will direct the researcher when investigating and evaluating data, thus forming a theory. As qualitative techniques are suitable for exploring substantive situations which have conflicting views or little is known about them (Stern1980; Rossman & Marshall, 1999), this approach is suitable for this research topic.

Grounded theory is an interactive, comparative, and inductive theory approach research that provides a number of open-ended strategies to discover emergent themes. Grounded theory uses the inductive approach within a research without prejudged notions (Glaser & Strauss, 1967) related to the research topic. Using deduction and induction is affirmed by Bryman & Bell (2003) who indicate that grounded theory is an iterative process which comprises elements of both deduction and induction. The grounded theory analysis is carried out as a constant comparative technique including comparison of an incident within each category, comparison of categories to one another, clarification of the developing theory, and a documented coherent theory as a result (Glaser & Strauss, 1967; Strauss & Corbin,1990). Theoretical sensitivity is a key concept of this approach (Glaser, 1978), which is the ability to comprehend the interactions between the related factors and themes. The researcher this as an appropriate approach due his interpretivist nature and considering the fact that every organisation can adopt the novel concept of cloud computing owing to several set of factors which may have diverging degree of influence on the decision.      

The researcher has used interview as the primary technique. Understanding the meaning of the information presented by the interviewees is considered to be the main task in interviewing (Kvale, 1996). An interview attempts to find out the factual information in addition to contextual information. Interviewing subjects in their natural environment uncovers the distinctions in their perspectives and the descriptions are endlessly redefined (Kalnis1986 as cited in Marshall and Rossman, 1995). Nevertheless, a cloud based ERP is a new concept and an organisation require to make a major decision before adopting it. It is crucial to view the data gathered from an interview in relevance to the subject being interviewed background because unspecified factual information may be misinterpreted or may not make much sense if it is not seen alongside the circumstances that affected it (Saunders et al., 2003).    

Quantitative research assists the researcher to acquaint one with the concept or problem to be examined, and possibly develop hypotheses to be tested. This approach is considered to be very different from qualitative approach (Bogdan & Biklen, 1992; Firestone, 1987). In this approach, the focus is on objective data and facts (Bogdan & Biklen, 1998) neglecting circumstantial evidence. Guba & Lincoln (1994), argues that research has been controlled by a need to quantify the hypotheses. Guba & Lincoln (1994) additionally challenged the efficiency of quantitative methods to quantify hard facts when social factors are involved as this approach is objective and tends to neglect the context of the information. It also limits the scope of the research because it does not inspire the researcher to see beyond objectives and aims.   

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Just like any other method, qualitative approach has its drawbacks. According to Lincoln & Guba (1985), Patton (2001), and Stiles (1993), the quality of traditional qualitative research is affected by reliability and validity. Denzin & Lincoln (1998) identified four factors to develop the correctness of the research and data. The four factors include conformability, dependability, transferability, and credibility. It would difficult for a different researcher to repeat the survey and reproduce the finding for confirmation of the research with equivalent amount of personal bias and validity. A key aspect of high quality report is generalizing the findings of the report. Maxwell (1992) indicates that generalizing findings is easier in quantitative technique and is likely a drawback in this study.  Patton (2001) suggests that the generalizability is a criterion that is subjective to a particular case study. Additionally, Cassell & Symon (1994) argue that when using qualitative approach, it is easier to divert from the original context of the study due to changing context of the research.

A phenomena list regards each event as unique and is restricted by variables such as culture, location and time, leading to a conclusion that in probability none of two events are identical or similar (Bolender,1998) when taken with their context. Each organization could have its own grounds to either shun or acquire a cloud based ERP and these factors are specific for every organisation, which reflects the disposition of the organisation lending itself to being subjective. The end result would be mainly expressed in qualitative terms as a descriptive.

Generally, the researcher is following an inductive qualitative approach to establish a relation between what the subject is expressing, meaning of what he says, the culture and background he is from, and the requirements of the subject. Elliott (1995) and Strauss & Corbin (1990) support this by claiming that qualitative research contributes to understanding subject’s perspectives. Saunders et al. (2003) and Bazeley (2004) express a case for the epistemological relevance of both forms of knowledge and that it is critical to understand how both are founded and grounded. This does not mean the researcher does not want to pin the concerns statistically and empirically. It is related to the cautiousness of not rushing into the subject and recognizing that decision to embrace a cloud based ERP by an enterprise is determined by several contextual factors and the responsible factors cannot be easily understood through quantification (Strauss & Corbin, 1990). Additionally, an ERP cannot be considered pervasive daily computing and it is difficult to collect statistical data from diverse sources.

The primary method of data gathering used is interviews. Interviews are descriptive and in a holistic perspective they determine the issues in depth (Kvale, 1996). For any action research project, interviews are an important part because the researcher is provided with an opportunity to examine further, gather data that cannot be acquired in other ways and solve problems (Cunningham, 1993). However, this is disadvantageous in some issues such as time consuming, and if sampling is not done carefully may yield poor quality data. Researchers are also supposed to observe their personal bias so that the results are not skewed jeopardizing the whole research (Williams, 1993; Saunders et al., 2003).

There are three types of interviews namely semi-structured, unstructured and structured (Saunders, et al., 2003). This study uses the semi-structured interview approach since it allows the researcher to dig deep into the interviewee’s background and gives the researcher adequate flexibility to dig into and explore any theme relevant to his or her study (David and Sutton 2004). Interviews use probing as a way to explore new paths that were not considered at the beginning (Gray, 2004). This can be attained by using additional questions that were not in the interviewer’s mind set earlier.      

A disadvantage of semi-structured interviews is that interviewer cannot realize and prompt themes he or she is ignorant of because of the mismatch in the background of the interviewee and interviewer and this should be put into consideration before using this approach (David & Sutton, 2004).

Focus Groups

Researchers use combined multiple methods so as to add something unique to their understanding of particular phenomena. This approach is associated to ethnography which is a combination of observation and interviewing (Willis, 1990) and is valuable to include several perspectives to the data, due to the cascading effect (Lindolf & Taylor, 2002) of the discussions that is collected using different qualitative techniques such as individual interview. It would be nearly impossible to identify and gather these data by interviews only. The group interview is a qualitative data gathering method that allows the moderator/interviewer direct the inquiry and interaction in a very unstructured or structured way, depending on the purpose of the interview (Denzin & Lincoln, 1994). Small sized groups of 5-7 will be used by the researcher. The idea is to maintain a small group size so as to enhance effective management of the group while getting the core of the discussiuon easily. An important factor to consider is the homogeneity of the group and this taken care of automatically.


Qualitative investigation usually employs purposive sampling technique (Rossman &Marshall, 1999). The number of people interviewed in a purposive non-random sample is less significant than the criteria used to select them. Marshall (1996) identifies three techniques of sampling as theoretical, judgment, and convenience sample. This study would utilize the theoretical sampling where the researcher would analyse the emergent themes and select the succeeding sample to detail these themes. Glaser and Strauss (1967) suggest that samples should be collected and previous samples should be compared with the emergent themes in annotative format unless a theoretical saturation point is attained. This would improve the strength and validity of the researcher’s theory.

Case selection

For each individual chosen to be interviewed, it is crucial to have a framework or criteria of requirements in place before the commencement of the interview. This would provide credibility of the data to be gathered. Researchers should also understand that it is not easy to attain statistical representation of every organization in India that are likely to use or use cloud based ERP. Therefore, snowballing is the most practical approach to acquire the next appropriate subject for the interview, but it is this set of criteria that in reality validate the subject to be an ideal candidate for interview.    

Data Analysis

The data analysis technique is used is microanalysis (Strauss & Corbin, 1990). The data is analysed by the researcher as he gathers it and then it is coded into likely emergent themes on basis of his judgment and supported by literature. Coding process is repeated whenever a new data is gathered. A comparison between these codes and previous ones is done and if any emerging new theme is noted. The iterative process in use here is referred to as ‘constant comparison’ that is done for each new set of data gathered until all the themes are saturated by the researcher. That is, it is not possible to obtain new insights from the data.

Axial coding is then employed to the deduced themes and these are ordered towards a central theme on basis of the linkage between their properties. This assists in abstracting the higher level factors and their interrelation. The higher level factors form the foundation for the development of the theory.

To analyse and transcribe the interviews, QSR NVIVO will be used and the ‘node’ feature of the software will be employed to carry out coding and establish central themes.

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