ANALISIS DE ARMONICOS EN EASYPOWER

The present research involves a survey of MBA graduates in Ireland. A detailed mail questionnaire was distributed to 550 graduates who took their MBA in Ireland. The survey instrument, and the sampling and analysis used are detailed below.

3.5.1 The Survey Instrument

The mail questionnaire used in this thesis (Appendix 1 provides a copy of the survey instrument) is composed of a total of 35 questions. These are sub-divided into five constituent parts (Section A, B, C, D and E). Section A, entitled Personal Profile, provides important background data on responding MBA graduates. Questions 1 to 3 questions the respondents on issues such as the year of completion of their MBA, and an indication of their age and gender. They were then asked a number questions pertaining to both their educational attainment and career development. Subsequently, participants were asked whether they held a third level qualification prior to commencing the MBA as well as the academic discipline of their pre MBA award. Furthermore, respondents were invited to provide details on their career to date. Included here were questions on whether they had changed jobs and/or career since completing their MBA and on their current work position. Survey participants were also asked to provide an indication of their level of satisfaction with regard to their career to date. Finally, Section A is completed with respondents confirming whether there were entrepreneurship modules on their MBA programme.

Section B of the research instrument attempts to focus specifically on those survey participants who took an entrepreneurship module/s as part of their MBA degree.

Having “filtered” graduates who did not take entrepreneurship as part of their MBA programme, Section B enquires as to the objectives of participating MBAs on taking entrepreneurship and whether these objectives were met. This part of the questionnaire further explores the impact of entrepreneurship module/s on respondents perception of the discipline, their subsequent career decisions and aspiration to pursue entrepreneurial activity. Section C of the survey instrument dwells on those responding graduates who have commenced ventures. It commences with examining participants rationale for start-up and explores their entrepreneurial behaviour to date. Issues here include an examination of when they started their most recent venture, whether they ventured more than once and the timing of this relative to MBA completion. Next, respondents were questioned on features of their particular entrepreneurial start-up (sector and type of organisation). Finally, responding MBA graduates were asked about their venture’s employment levels, sales, workforce and profitability trends, and geographical area of trading. Section D explored the extent to which responding graduates might consider venture start-up in the future. It examined the link between business ideas and their non-pursuance as well as the level of future entrepreneurial intent among participants. The research instrument concludes with Section E. This single “open question” invited MBA graduates to share any comments or suggestions which may add to the topic under investigation.

The present work used a combination of closed-ended and open-ended questions. Bryman (2004) explains that when asked open questions, respondents can reply however they wish. With closed questions, respondents are “presented with a set of fixed alternatives from which they have to choose an appropriate answer” (Bryman 2004). He further advises that one of the most significant considerations for

researchers is whether to ask questions in an open or closed format. Multiple-choice questions are generally easier for both respondent and researcher while open questions ensure survey participants are given the opportunity of elaborating on particularly poignant issues relevant to the research agenda (Domegan and Fleming, 2007). Kumar (2005) notes that closed-ended questions should be used for eliciting factual information while open-ended questions are used for seeking opinions, attitudes and perceptions. Accordingly, as factual information, opinions, attitudes and perceptions are all important to this investigation, both types of questions were used.

3.5.2 Sampling

Goddard and Melville (2005) observe that sampling involves the examination of a representative number of people or things (subset) from the total population being investigated. The purpose of sampling is to gain a level of understanding of the total population based on the characteristics of the sample. Accordingly, Robson (2005) stresses that it is unusual to be able to deal with the whole population in a survey and that a sample is a selection from the population. Before a survey can be conducted, it is necessary to determine the sampling frame for the study. Domegan and Fleming (2007) further advise that a sampling frame is a list of the total units within a defined population.

The sampling frame for the present work was the list of membership of the MBA Association of Ireland. This database was selected because it affords a representative sample of the total number of MBAs in the Republic of Ireland (the unit of study) and has member graduates from all the universities and Institutes of Technology in

Ireland. The sample providing the information required was of crucial importance to the representativeness of the research. Ideally the survey should have covered all MBA graduates of Irish third level institutions. Clearly this was not possible. Not only would the expense of such a survey have been prohibitive but, more importantly, to generate a list of MBA graduates of Irish Universities and Institutes of Technology was impossible due to the time span (1992-2004), the issue of confidentiality and data protection legislation. To overcome the problem of generating a suitable sample frame, the assistance of the MBA Association of Ireland (MBAAI) was sought and permission was granted to use their list of membership for the year 2005. This list, which included MBA graduates up to 2004, is available to all members of the association (available within their official diary) and includes such information as the graduates’ name, institution and year of graduation, their job title and the organisation they currently work within. It does not include their postal address. However, with the information available, this researcher used the “Golden Pages” to establish a postal address for every member and thus a comprehensive database of 550 MBAs was created.

It was not possible to establish postal addresses for all members of the MBA Association of Ireland. In this instance, the accompanying contact phone number was used to establish, where possible, a relevant postal address. In a number of cases it was not possible to ascertain contact details and, accordingly, these individuals were discarded from the research database. The final database includes MBA graduates from 1992-2004. This study was augmented with personal interviews. These were conducted in Autumn 2008 and detailed later in this chapter.

3.5.3 The Pilot Survey

Robson (2005) advises that the first stage of any data gathering exercise should be, if at all possible, a pilot study which he terms a “dummy run”. This can help present any problems involved in the process of converting questionnaire design into research reality. Furthermore, Creswell (2003) proposes that pilot tests should be done under conditions that reflect in miniature the main survey. He contends that their primary advantages are in testing both the accuracy and reliability of sampling frames and the physical presentation of the survey. Importantly, Jankowicz (1999) suggests that pilot studies should include a “small number of people taken from the same population as the sample”.

The pilot study for the present study was conducted on November 1st 2005. In total 12 (approximately 2% of the total sample) questionnaires were posted to randomly chosen MBAs. Domegan and Fleming (2007) indicate that between 5 and 10 respondents are appropriate for such a pilot study. All questionnaires were returned within a two-week time period. Respondents were then contacted and views were sought on the survey instrument. Specifically, issues including the questionnaire format, instructions, and sequence and wording of questions were discussed. No changes resulted from this process and the final version of the questionnaire was printed and posted to the aforementioned database of MBA graduates on December 5th, 2005.

3.5.4 Administration of the Questionnaire

The survey instrument was professionally printed in an A5 booklet format and totaled 8 pages in length. This was done to ensure ease of completion for the respondent. It was accompanied by a one-page cover letter (see Appendix A). Adam and Healy (2000) advise that a cover letter should be brief and outline who you are and the overall purpose of the study. They also suggest printing the cover letter on official headed paper from the researcher’s department or institution. The cover letter for the present research, dated November 25th, 2005, gave a brief personal introduction, outlined the overall objective of the research and explained the fact that respondents were assured of absolute anonymity. It was printed on University of Limerick headed paper. Both the questionnaire and covering letter were inserted into an A5 envelope (stamped addressed envelope enclosed) and mailed on December 5th, 2005.

3.5.5 Response and Non-Response Response Rate

In total, 550 envelopes were posted and 208 completed questionnaires were returned. This represents a response rate of 37.8%. Domegan and Fleming (2007) observe that mail surveys are often plagued by low rates of return and, typically, a 10% response rate is not unusual. Accordingly, 37.8% is regarded as being a very satisfactory participation rate for a mail survey.

While the survey response rate for the current study may be deemed acceptable, the author was keen to give some consideration to the non-respondents. Adam and Healy (2000) conclude that while it is unavoidable to have a non-response aspect to a

survey, researchers must ensure it has no side effect on the results of the study. They contend:

Bias can occur when respondents who would have differed markedly from the general case decide not to take part in the study.

(Adam and Healy 2000, p.79)

One way to test for such bias, they advise, is to use late respondents as surrogates for non-respondents and to compare their responses to a random sample of respondents. Significant differences between the two groups may indicate a non-response bias (Adam and Healy 2000). Accordingly, the author randomly selected the final 5% of completed questionnaires to be received in the survey. This amounted to a total of 11 documents. These responses were compared to a random sample (5%) of the remaining survey questionnaires from the present study. A statistical analysis was conducted and no perceivable differences were identified thus indicating a limited degree of non-response bias.

3.5.6 Statistical Analysis

Statistical analysis deals with the processing, interpretation and understanding of quantitative research data. Lucy (1997) suggests:

Statistical analysis is a scientific method of analyzing masses of numerical data so as to summarise the essential features and relationships of the data in order to generalise from the analysis to determine patterns of behaviour, particular outcomes or future tendencies. (Lucy 1997, p.45)

The Statistical Package for the Social Sciences (SPSS) was used for the statistical analysis of the quantitative data in the present research. SPSS is an integrated computer software system for statistical data analysis. Robson (2005) believes that for

a small amount of quantitative data it may be appropriate to carry out analysis “by hand” but that modern software packages such as SPSS have the advantages of power, speed and storage capacity and should be used for larger studies if at all possible. Similiarly, Domegan and Fleming (2007) highlight the powerful data manipulation facilities of SPSS and its usefulness in the analysis and interpretation of large quantities of quantitative research data.

Punch (2001) explains that the analysis of quantitative research is based on assessing relationships between variables and many different ways have been developed to study these. The relationships to be tested are highlighted within the research hypothesis. In this regard, Creswell (2003) explains that hypotheses are predictions the researcher holds about the relationship among variables and are “estimates of population values” (Creswell 2003). Furthermore he suggests that the testing of hypotheses employs statistical procedures in which the investigator draws inferences about the population from a study sample. In total, there are five research hypotheses pertaining to this thesis and each of these are statistically tested in Chapter 4. One of the most popular statistical techniques within data analysis is the chi-square _χ2 _test.

This test is a formal statistical procedure that facilitates an assessment of association between two variables and is used widely within the current research. It highlights the discrepancy between observed and expected frequencies (i.e. those frequencies that might have been expected assuming the null hypothesis was true). Lucy (1997) advises that the _χ2 _{test is an important aspect of hypothesis testing and is best used}

expected distribution. He explains that the formula for the calculation of _χ2 _{is as} follows: 2 ∑ (O- E) _χ2 ₌ E Where:

O = the observed frequency of any value E = the expected frequency of any value

The _χ2 _{value obtained from the above formula is compared with the value in the χ}2

distribution tables for a given significance level (p value) and the number of degrees of freedom (df). If the chi-square value is less than the test value ( 2

s χ < 2

t

χ , p value > 0.05) then there is no significant difference within the sample analysis and the null hypothesis not rejected. The opposite of this is also true. When the chi-square value is greater than the test value ( 2

s χ > 2

t

χ , p value < 0.05) it suggests a significant difference in the sample analysis and consequently, the null hypothesis is rejected in favour of the alternative hypothesis.

The second statistical test used in the present research analysis is Fisher’s exact test. Robson (2005) stresses that statisticians warn against the use of chi-square in cross- tabulations when one or more expected frequencies fall below a particular value, usually taken as 5 in small tables. Fisher’s exact test is a substitute calculation, which may be used in circumstances where the expected frequencies are too low for chi- square. It is used to analyse contingency tables that contain exactly two rows and two

columns, and that contain less than 50 cases. With this test an exact significance value (p value) is compared to a test value. If the exact significance value (p value) is greater than the test value, there is no significant difference in the sample analysis, which suggests the null hypothesis is not rejected. The opposite to this is also true. If the exact significance value (p value) is less than the test value, there is a significant difference in the sample analysis. This indicates a rejection of the null hypothesis in favour of the alternative hypothesis.

Furthermore, the present study uses a limited amount of bivariate analysis. This is done through the Pearson correlation test. Bivariate analysis attempts to measure the likelihood of a number of factors (more than one) affecting a decision (Lind et al., 2002; Blumberg et al., 2005). Bryman (2004, p.230) indicates that it is concerned with the analysis of two variables at a time “in order to discover whether the two variables are related”. A value of less that 50% (< .5) normally indicates a limited degree of association between variables.