Analysis of Management Sciences Institute - Case Study Example

www.allwriting.net Sumanta Sanyal Dated: 4/06/2006 Critique and Analyses of Survey Data – “Management Sciences Institute”, UK, Survey Questionnaire Introduction The “Management Sciences Institute”, UK, has prepared a questionnaire that it has distributed to its members so that it could conduct a survey. The primary intention behind conducting the survey is to gather data to assist the organisation in preparing for conferences, publication of its magazines and journals and putting together advertisements for posts required by other organisations to be filled by professionals belonging to it. The organisation has 3,000 members to all of whom the questionnaire was mailed. As in relevance to this report data from 300 respondents has been considered for analyses. Part A - Critique of the Questionnaire The “Management Sciences Institute”, UK, questionnaire is a 27-item affair that is strategically divided into the following five main areas. Questions 1-8 pertain to the members’ personal details Questions 9-14 pertain to the manner in which members interact with the Institute’s Annual Conference initiatives Questions 15-20 pertain to the Institutes Publications and the manner in which the members view and utilise them Questions 21-24 pertain to the Institute’s Website and the manner in which individual members view and utilise it Questions 25-27 constitute 3 questions that assess how members are involved in the Institute’s activities and how they view its committee After adequate study of the questionnaire and other relevant questionnaires prepared for the same purpose for other professional bodies it is found that the items are all relevant to the issue at hand and they also do the job efficiently. Thus, this critique does not in any manner deem it necessary to either add or detract any item to or from the existing list. Nevertheless, it is found necessary to comment on how some of the scoring of the questions can be done so that analyses of responses can be speedily processed and results can be construed efficiently. Scoring: For this purpose question items are taken individually and main area-wise. Members’ Personal Details: Questions 1-8 that pertains to this area has one singularity. Question 1, which seeks to delineate whether a member is an analyst, manager, consultant or academic constitutes an independent variable upon which the other variables in this area are dependent. Thus, it is necessary to at first determine whether a member is any one of these four categories before the other details elicited can be analysed according to this independent variable. This is done in sections 2 & 3 of Part B and it is found that results are easily derivable and construable. Thus, it is found that consultants are the best paid of the four while academics have the eldest age group. Now, something must be said as to how the various items in this area can be scored. Question 2 is not considered too germane to the issue at hand. Question 3 is an interesting case as it asks the members to state in which part of England they operate. If the following scale is assigned – Scotland (1), North England (2), Midlands/Wales (3), South West England (4) and South East/London (5) it is found that the mean of the highest scale 5 is 2.5. This signifies that if the average score for this item is above 2.5 the members primarily operate in the south of England. Any average below that signify that most members operate above that region more the north. This is a rough but very useful indicator of where most members in a particular category are from. The same is true for question 4 that deals with gender. When female is taken at 1 and male at 2 any average score above 1 signifies that there are more males than females in that category. All Yes/No items in the list can be ascribed scores of 0 for negative and 1 for positive. This is true for question 8. Institute Conferences: The first question in this area asks about how many conferences the responding member has attended during the past five years. For none, which is negative, the score is taken as 0 while the score progresses thereafter from 1 to 3 maximum. This is extremely efficient as a manner of coding. Questions 10-13 in this area are multiple choice ones that the manner of handling them is to assign particular scores to the individual choices. Thus, for question 11 which asks why the member has attended a conference within the last five years the scores should be assigned in the following manner: Interested in the subject (1), Networking opportunity (2), Personal development (3) and Professional development (4). The mean should be taken as 5 (adding all the scores and dividing by the number of alternatives) and averages in a category that is above the mean should signify developmental interest while below mean average should mean that the member is interested or seeks network opportunity. While this is not an exact means of determining status it nevertheless does the analyses sufficiently. This same is true for item 10 as well. Item 14 is assigned scores already in the following manner: Very interested (1), Quite interested (2) and Not interested (3). The mean of 1.5 should be taken to get the average level of interest in a particular choice. Since there are 10 choices here averages for each of the choices should be gathered and the level of interest in each for each category should be ascertained. This is same for other questions in the following areas that are similar to this. Items in the other two remaining areas are of the same type as is already mentioned in the stated areas before and since there is nothing singular about them they should also be dealt with in the manner similar to that already discussed. It is also necessary to understand that item choices that signify positive interest should be assigned numbers starting from 1 and the score should increase progressively as the level of positive interest decreases. For example, item 16 that asks how happy the respondent with the content of the Institute’s publications should be scored as follows. Very satisfied (1), Quite satisfied (2) Quite dissatisfied (3) and Very dissatisfied (4). The average is 2 and anything above that signifies negative response while below signifies a positive one. Part B – Analysis Section 1: Table 6: . Descriptive Statistics N Minimum Maximum Mean Std. Deviation VAR00002 300 .00 3.00 1.2233 1.00507 VAR00003 300 .00 1.00 .6867 .46462 VAR00004 300 .00 1.00 .6767 .46853 VAR00005 300 .00 1.00 .4333 .49636 VAR00006 300 .00 1.00 .1800 .38483 VAR00007 300 .00 1.00 .5967 .49139 VAR00008 300 .00 1.00 .5433 .49895 VAR00009 300 .00 1.00 .7367 .44118 VAR00010 300 .00 1.00 .2500 .43374 VAR00011 300 .00 1.00 .6367 .48176 VAR00012 300 1.00 4.00 2.1200 1.02425 VAR00013 300 1.00 3.00 2.0367 .45018 VAR00014 300 1.00 3.00 1.5300 .69573 VAR00015 300 1.00 3.00 1.7167 .79066 VAR00016 300 1.00 3.00 2.5500 .73209 VAR00017 300 1.00 3.00 2.3733 .75444 VAR00018 300 1.00 3.00 1.5833 .73361 VAR00019 300 1.00 3.00 1.5400 .66070 VAR00020 300 1.00 3.00 1.6600 .75252 VAR00021 300 1.00 3.00 2.0933 .82476 VAR00022 300 1.00 3.00 1.6467 .78136 VAR00023 300 1.00 3.00 2.3533 .76405 Valid N (listwise) 300 Table 6 contains data on the members’ opinions on the Institute’s annual conferences. The number of conferences attended within the last five years is seen to be just a little over 1 as per the data on Variable 2. Variables 3-7 denote the barriers that members find towards attending conferences. The most frequently quoted reasons seem to be Variables 3 & 4 – that is, topics and locations. Variables 8-11 give reasons why members did attend. The most quoted reasons seem to be networking opportunities and professional development – Variables 9 & 11. Variables 12 denotes how useful members have found the conferences to be. Since the mean response is above the mean score of 2 it seems that the members have primarily not found the conferences very useful. Variables 13 denotes how the members found the conferences – Too formal, About right and Too informal. The response seems to be that they just about think that the conferences are about right as the mean is very near the mean score of 2. Variables 14-23 denote certain points of interest that members have in some topics. Members have most interest in Variable 16, denoting health, and Variable 17, denoting information. Table 7: Descriptive Statistics N Minimum Maximum Mean Std. Deviation VAR00002 300 1.00 3.00 2.0100 .43650 VAR00003 300 1.00 4.00 1.9900 .95197 VAR00004 300 1.00 3.00 2.0000 .78019 VAR00005 300 1.00 3.00 2.1300 .76270 VAR00006 300 1.00 3.00 2.0233 .79471 VAR00007 300 1.00 3.00 1.6933 .79250 VAR00008 300 1.00 3.00 1.8267 .64135 VAR00009 300 1.00 3.00 1.9700 .77746 VAR00010 300 1.00 3.00 2.0267 .33615 VAR00011 300 1.00 4.00 2.1467 1.07813 VAR00012 300 1.00 3.00 2.0600 .84386 VAR00013 300 1.00 3.00 1.6967 .78318 VAR00014 300 1.00 3.00 2.0733 .83883 Valid N (listwise) 300 Table 7 contains data on the members’ opinion on the institute’s publications. Variables 2-14 contains this. Going by the means of all the variables, most of them are above 1.5 which is the mean score. Thus, interest in the institute’s publications is not very sustained among members and the institute should do more to make them more interesting. Table 8: Descriptive Statistics N Minimum Maximum Mean Std. Deviation VAR00002 300 .00 1.00 .9400 .23788 VAR00003 300 .00 4.00 1.9333 1.21124 VAR00004 300 .00 4.00 2.0100 1.27619 VAR00005 300 .00 1.00 .3867 .48780 VAR00006 300 .00 1.00 .3833 .48701 VAR00007 300 .00 1.00 .4100 .49266 VAR00008 300 .00 1.00 .1767 .38202 Valid N (listwise) 300 Table contains data on the members’ opinion on the institute’s website. Variable 2 asks if the members have access to the website and the mean shows that they predominantly do. This is a simple Yes/No question and the score is predominantly ‘Yes’. Variable 4 shows that the members think that the site content is just about good. The mean is very near the score mean of 2. Variables 5-8 show how user-friendly the site is and the answers show that it is not too so. This is because all the means are below the score mean of 0.5. The overall opinion of the institute website is not too good. Table 9: Descriptive Statistics N Minimum Maximum Mean Std. Deviation VAR00002 300 .00 1.00 .7667 .42366 VAR00003 300 .00 1.00 .8200 .38483 VAR00004 300 .00 1.00 .1233 .32937 Valid N (listwise) 300 Table 8 contains data on the institute’s committee and getting involved for the members. The first two variables ask about details on the committee and all the members seem to be conversant with it as the items are Yes/No ones and the high means show positive responses but the last variable, which asks if the members want to get actively involved, fails with a very low mean signifying that most of the members are not interested. Section 2: Table 1: Frequency distribution by job type. Frequency Percent Valid Percent Cumulative Percent Valid Analyst 80 26.6 26.7 26.7 Manager 100 33.2 33.3 60.0 Consultant 50 16.6 16.7 76.7 Academic 70 23.3 23.3 100.0 Total 300 99.7 100.0 Missing System 1 .3 Total 301 100.0 It is noted that only 300 respondents are considered. There is an excess of 1 due to data entry error. Table 1 shows the frequency distribution of the members by job type. It is noted that out of the 300 members who had responded, 80 are analysts, 100 are managers, 50 are consultants and 70 are academics. Table 2-5 contain tabulated descriptive statistics of the respondents regularly grouped according to their job types. The statistics present very interesting facts that are being revealed hereafter. Table 2: Table 2: Descriptive statistics of Analyst Respondents Descriptive Statistics N Minimum Maximum Mean Std. Deviation Location 80 1.00 5.00 3.9250 1.28058 Gender 80 1.00 2.00 1.7125 .45545 Age (yrs) 80 21.00 41.00 31.8375 6.35340 Moves 80 .00 2.00 .5625 .57023 Salary Income 80 14.20 35.50 27.0038 4.71683 Valid N (listwise) 80 This contains the descriptive statistics of the analysts’ group pertaining to location, gender, age, moves and salary income in that order. The location statistics mean reveals that most of the analysts are located in the south of England. The values of the South West are 4 and the South East/London areas are 5. Thus, the high mean of above 3.9 means that most of the analysts are concentrated in the South, particularly around the London area. This is typical of job area patterns in England for most managerial jobs. The gender mean at above 1.7 means that most of the analysts are males where female scores 1 and male scores 2. The lowest age is 21 yrs and the highest 41 yrs. The mean age is 31.8 approx. with a standard deviation of 6.3 approx. The lowest salary income is 14.2 and the highest is 35.5 with mean at 27 approx. with standard deviation at 4.7 approx. This is the lowest salary income group among the four study groups, as all the tabulated data in this section reveals. Table 3: Table 3: Descriptive statistics for Manager Respondents Descriptive Statistics N Minimum Maximum Mean Std. Deviation Location 100 1.00 5.00 4.1900 1.10732 Gender 100 1.00 2.00 1.8200 .38612 Age (yrs) 100 28.00 60.00 42.6800 9.48564 Moves 100 .00 2.00 .4000 .68165 Salary Income 100 23.20 45.40 33.7360 5.59279 Valid N (listwise) 100 This contains the descriptive statistics of the managers’ group with the same criteria as that of the analysts’ group. Here again the location statistics reveal that most of the managers are located primarily in the South with possible concentration in the London area. This is also typical of English job area patterns and it is even more pronounced in the managers’ group than in the analysts’ with a mean well above 4. There are even more male mangers than analysts as the mean at 1.82 reveals. The managerial age group is higher than that of analysts and is between 28 yrs and 60 yrs. The mean at 42.68 is substantially higher than that of the analysts. The standard deviation is also higher at 9.48. Managers are slightly more stationary at their jobs than analysts with mean at 0.4 compared to 0.53 for analysts. Salary income is on an average higher for the managers at mean 33.7 compared to 27 approx for analysts. The lowest income is 23.2 and the highest at 45.4. Table 4: Table 4: Descriptive statistics of Consultant Respondents Descriptive Statistics N Minimum Maximum Mean Std. Deviation Location 50 5.00 5.00 5.0000 .00000 Gender 50 1.00 2.00 1.7800 .41845 Age (yrs) 50 26.00 55.00 41.2800 8.24384 Moves 50 .00 3.00 .3800 .69664 Salary Income 50 25.90 44.90 35.8920 4.38638 Valid N (listwise) 50 This contains the descriptive statistics of the consultants’ group with the same criteria as that of the other groups. The consultants are exclusively settled in the London area with a total mean of 5. Gender mean is high on the male side at 1.7, approximately that of the analysts’ group. Age at lowest 26 yrs and highest 55 yrs shows a lesser range than that of managers. The higher age is lower than that of mangers’ group. The average at 41.28 is slightly lower than that of the managers’ group but much higher than of the analysts’ group. This group is less mobile than the other groups as is obvious by their static positions in London. The mean is at 0.38. Salary income average is slightly higher than that of the managers’ group at 35.89 with lowest at 25.9 and highest at 44.9. Standard deviation is lower than that of the managers’ group at 4.38 suggesting that consultants are better paid than the other groups. In fact, they are the best-paid group with lower average age centred around the London area. Table 5: Table 5: Descriptive statistics of Academic Respondents Descriptive Statistics N Minimum Maximum Mean Std. Deviation Location 70 1.00 5.00 3.5000 1.35935 Gender 70 1.00 2.00 1.7000 .46157 Age (yrs) 70 30.00 60.00 46.6857 9.60607 Moves 70 .00 1.00 .0857 .28196 Salary Income 70 20.60 42.10 32.0286 5.32190 Valid N (listwise) 70 The descriptive statistics of academics’ group reveal that they are mostly well-distributed with concentrations in the South. Gender mean at 1.7 suggests that, like the other groups, the males dominate. This group has the highest age average at 46.68 with lowest at 30 yrs and highest at 60 yrs. They are the least mobile of all the groups with a very low average mean movement rate of 0.085. Their salary income average at 32.02 is slightly lower than that of the managers’ group and the lowest salary income is 20.6 while the highest is at 42.1. Section 3: Section 2 has already dealt with the implications belonging to a particular category has on the member’s salary income, age and other characteristics. In this section we are to deal with how belonging to a particular category can help predict the other members’ characteristics. It is essential to note that gender also can become an independent variable upon which the other variables can be made to depend but it is found that the members are primarily male and thus the predictability will have to depend upon each category. Graph 1: Salary income plotted against category. Graph 1 amply demonstrates that the categories with the highest average income are the consultants. The category with the lowest are the analysts and the academics and mangers go somewhere in between. This is quite in line with what has already been found in section 2. Conclusion The institute questionnaire is not included herein as it is thought that it is sufficiently adequate to assist the institute in efficiently assessing its member’s opinions. Some of the coding and scoring guidelines have been reposited but it is mainly found that the means of doing so already is adequate. So no major suggestions have been put forward. In analysing the responses it has been found that though, primarily, the members have a good opinion of the institute and its attendant mechanisms they do not want to get actively involved. This includes attending conferences. Bibliography Frary, Dr. Robert, A Brief Guide to Questionnaire Development, 2002. Extracted on 2nd June, 2006, from: http://www.testscoring.vt.edu/fraryquest.html Williams, A, How to …. Write and analyse a questionnaire, Journal of Orthodontics, Vol. 30, No 3, 245-252, September 2003. Extracted on 2nd June, 2006, from: http://jorthod.maneyjournals.org/cgi/content/full/30/3/245 Read More