CHAPTER 4 DATA ANALYSIS, PRESENTATION AND INTERPRETATION

Transcription

1 CHAPTER 4 DATA ANALYSIS, PRESENTATION AND INTERPRETATION 4.1 OVERVIEW The responses given by 385 faculty members and 30 directors working in NBA accredited institution business schools in Northern India were entered into the SPSS database for analysis. The chapter reports the findings of the research questions being captured by the survey conducted for faculty members and directors. The data collected was entered into the SPSS software and essential statistical tools were employed along with the descriptive statistics for analysis and report generation. Tables and figures in the chapter house data along with the narrative reporting, which link the data to research questions of this study. These research questions were as follows: (1) What are the factors contributing towards the retention of faculty members in Business schools in Northern India? (1) Why does faculty members leave and joins the other Business school? (3) How is the employee relationship amongst the faculty members in Business schools in Northern India? These all mentioned research questions are tried to be answered using the self-designed questionnaires for faculty members and directors that has the potential to quantify the responses given by the respondents. 4.2 DESCRIPTION OF THE SAMPLE The first section of the faculty survey instrument requested (N=385) faculty respondents to provide their demographic information. The information included: gender, marital status, designation, education, length of service with the current and last working institute. The demographic information gathered is presented in Table below. 63

2 Table 4.1 Demographic characteristics of the sample Demographic Characteristic percentage n Gender Male Female Marital Status Married Unmarried Designation Assistant Professor Associate Professor Professor 8 30 Education Post Graduation M.Phil 7 27 Ph.D Pursuing Ph.D NET Spouse in same profession Length of service (wish to continue) in present working institute Less than 2 years Next 2-5 years Next 6-9 years 3 13 More than 10 years Length of service (stay) in the last working institute Less than 2 years years years 6 23 More than 10 years

3 After the demographic section, the next section of survey required respondents to rate the identified factors that had caused them to join the existing working institute and leave the last working institute. A composite score for each of the factors was derived by calculating the mean of the responses to the question. The gap between expectation of faculty members at the time of joining and the offerings offered by the Business Schools against the expectations of the faculty members after joining is also tried to examined. T-test is applied for the same. The section attempted to make observation regarding the employee relationship faculty members have in their working institute. The section also tried to explore the factors that tend the faculty members to stay in their working institution in the forthcoming years. The overall satisfaction of the faculty members is also tried to be identified. A likert scale was used with the scores ranging from 1-5.Scores of 1 indicated the response of the respondent strongly disagree due to the factor whereas 5 indicated the response of respondent strongly agree due to the described factor. To test the internal consistency and reliability of the extent to which the individual factors could be combined under one common factor, the Cronbach s Alpha was computed while conducting Exploratory Factor Analysis. 4.3 DATA ANALYSIS AND PRESENTATION OF DATA The findings of the study are presented with the help of bar charts, frequencies, percentages and tables in the existing chapter. The essential descriptive statistical tools are employed to get the results. The results are then presented and interpreted by the researcher to make the layman understand the findings of the study. 65

4 4.3.1 Results of the Survey Conducted for Faculty Members Section A Table 4.2 Type of appointment Type of appointment Frequency Percent Regular Temporary / Contractual Total Figure 4.1 Type of appointment Table 4.2 and Figure 4.1 shows that 381 (99%) faculty members have regular appointment from the Business Schools whereas only 1% of the faculty members are having temporary appointments in the B-Schools they are working. It is observed from the results that very less percentage of the faculty members are having temporary/contractual appointment fixed for a certain period.the major portion of the faculty members have a regular type of appointment irrespective of any pre-fixed tenure. 66

5 Table 4.3 Marital status Marital Status Frequency Percent Married Unmarried Total Figure 4.2 Marital status Table 4.3 and Figure 4.2 depicts the marital status of the faculty members working in the NBA accredited B-Schools in Northern India. The table shows that 64% of the faculty members are married and 36% of the faculty members are not married. Table 4.4 Spouse in same profession Spouse in same profession Frequency Percent Yes No Total Figure 4.3 Spouse in same profession

6 Table 4.4 and Figure 4.3 shows that only 13% faculty members have their spouse in the same profession whereas 87% of the faculty members do not have spouses working in the same profession. Table 4.5 Designation Designation Frequency Percent Assistant Professor Associate Professor Professor Total Figure 4.4 Designation Table 4.5 and Figure 4.4 depict the number of faculty members working at different academic designation working in the NBA accredited Business Schools in Northern India. The table shows 69% faculty members working as Assistant Professors, 23% of the faculty members designated as Associate Professors and 8% of the faculty members are associated as Professors, although the %age is very low. 68

7 Table 4.6 Educational qualification Educational Qualifications Frequency Percent Post Graduate M.Phil Ph.D NET Qualified Ph.D pursuing Figure 4.5 Educational qualification Table 4.6 and Figure 4.5 reflects the qualification of the faculty members those are serving their services in business schools. The table shows all the faculty members as post graduates. The table reflects 7% faculty members holding M.Phil degree whereas majority of the population i.e. 93% of the faculty members not holding M.Phil degree. The table depicts the number of faculty members holding Ph.D degree in their respective area of specialization, working with the NBA accredited Business Schools in Northern India. The table shows that 24% faculty members are holding Ph.D degree whereas majority of the faculty members i.e. 76% are not holding Ph.D degrees. The table shows the number of faculty members as UGC-NET Qualified. The amazing thing that came into notice was that only 19% of the faculty members working in the NBA accredited Business Schools in Northern India are UGC-NET qualified. Whereas 81% of the faculty members were found non UGC- NET qualified. The table shows the number of faculty members pursuing Ph.D in their respective area of specialization. The finding which cannot be neglible in any concern is that there is a very low percentage of the faculty members holding Ph.D degree. And on the other hand, which cannot be avoided is only 32% of the faculty members are pursuing Ph.D degree and 68% of the faculty members are not pursuing Ph.D degree.

8 Table 4.7 Wish to continue in the present working institute Wish to continue in present institute Frequency Percent 50 45% Less than 2 years to 5 years % 23% 5 to 10 years % More than 10 years Total Less than 2 years 2 to 5 years 5 to 10 years More than 10 years Figure 4.6 Wish to continue in the present working institute Table 4.7 and Figure 4.6 shows the concern of faculty members for their retention in the institute they are working in.it is evident from the graph that 29% faculty members wish to continue less than 2 years with the institute, where they are presently working in. And on the other hand the highest percentage among all the tenure that cannot be avoided is that 45% faculty members are interested and are concerned for their retention and wish to continue with the present working institute for the next 2 to 5 years. And the statistic which brought into notice that the lowest percentage i.e. only 3% faculty members wish to remain or work for next 5 to 10 years with the institute. On the other hand it was quiet amazing to get 23% faculty members showed their concern and wish to be retained by the present working institute for more than 10 years. The positive aspect of the above mentioned statistics is that 45% of the faculty members altogether almost more than the average wish to continue working in the institute for next 2 to 5 years and more than 10 years. 70

9 Table 4.8 Length of service with last working institute Worked with last institute Frequency Percent Less than 2 years to 5 years to 10 years More than 10 years Total Figure 4.7 Length of service with last working institute In simple terms with the above statistics as is given in Table 4.8 and Figure 4.7, this can be interpreted that if a faculty member is suffering employee burnout and thereby he/she some or the other way come up with an intention to leave and resultant is that they start looking for a good option to opt and which is clearly evident from the statistics of the table and graph shown above i.e. if a faculty member is not satisfied with his/her job ;thereby leaves the job within a very short period as can be seen that majority(60%) faculty members had left their previous working organizations in less than 2 years,28% faculty members left in 2 to 5 years and then it can be seen that if a faculty member continues till 5 years i.e. becomes very less chances to leave the organization as is shown in the graph that only 6% faculty members left their previous working organization from 5 to 10 years. Hence, it can also be seen that if faculty members had been retained by the Business Schools for 5 years, so there remains a very less chances of faculty voluntary turnover. 71

10 Table 4.9 Gender Gender Frequency Percent % Male Female Male 49% Female Total Figure 4.8 Gender Table 4.9 and Figure 4.8 depicts one of the demographic variables of respondents i.e. Gender. The study surveyed 385 respondents in number in which 51% were male faculty members and 49% were female faculty members working at different designations: Assistant professor, Associate professor and Professor in the accredited Business Schools in Northern India. Section- B In the questionnaire used for the present research study, Section -B includes the examination of possible factors responsible for joining the current working institute and factors responsible for leaving the last working management institute from the faculty members as respondents. The five variables are selected on the basis of literature review and interaction held at the time of pilot survey. The five point likert scale is used to get the responses from the respondents considered for the research study. The mean score of the factors measured in the scale of one to five along with the standard deviation is shown in the table. Here 1 reflects Strongly Disagree and 5 represents Strongly Agree. The detailed analysis of data under Section-B is presented below: 72

11 Table 4.10 Factors responsible for joining the current working institute Factors responsible for joining the current working institute Mean Std. Deviation Goodwill of the institute Job security Salary Working environment Career planning and development Goodwill of the institute Career planning and development Working environment Salary Job security Figure 4.9 Factors responsible for joining the current working institute Table 4.10 and Figure 4.9 indicates that the most important factor responsible for joining the current working institute is goodwill of the institute represented by the highest mean score ( ) in the above mentioned table and figure. The other significant factors which are responsible for joining the current working institute are working environment(3.9247) and career planning and development prospects (3.9273). The result also indicates that salary (3.5117) is found to be the least influencing variable for joining the Business Schools. The major factors affecting organizational attractiveness is goodwill of the institute, career planning & development and working environment. 73

12 Table 4.11 Factors responsible for leaving the last working management institute Factors responsible for leaving the last working management institute Mean Std. Deviation Goodwill of the institute Job insecurity Low salary package Working environment Career planning and development Goodwill of the institute Career planning and development Working environment Low salary package Job insecurity Figure 4.10 Factors responsible for leaving the last working management institute The results revealed from the Table 4.11 and Figure 4.10 indicate that the most important factor responsible for leaving the last working institute is lack of career planning and development opportunities at the institute represented by the highest mean score (3.6597) in the above mentioned table and figure. The other significant factors which are responsible for leaving the last working institute are working environment (3.0338), goodwill of the institute (3.0052). The result also indicates that salary (2.9013) and job insecurity (2.6312) is found to be the least influencing variable for leaving the last working Business Schools. 74

13 Section- C In the research study the efforts is done to investigate the employee relationship that faculty members have in NBA accredited Business Schools in Northern India and what impact do those relationships have on the faculty members intention. The twenty one variables representing the various dimensions of the work style and practices of the B-Schools including the behavioral approach, policies and concern of the management of the business schools towards the growth and development for the faculty members working there in, are included in the Section-C of the questionnaire. The Exploratory factor analysis is applied on the responses in order to identify the latent factors which influence the employee relationship of the faculty members working in the Business Schools. Exploratory Factor analysis is a method of data reduction. It does this by seeking underlying unobservable (latent) variables (factors) that are reflected in the observed variables (measured variables). There are various methods that can be used to conduct a Exploratory factor analysis (such as principal axis factor, maximum likelihood, generalized least squares, unweighted least squares).in addition to this, there are also different methods of rotations that can be applied after the initial extraction of factors, including orthogonal rotations, such as Varimax and Equimax, which impose the restriction that the factors cannot be correlated, and oblique rotations, such as Promax, which allow the factors to be correlated with one another. Factor analysis is a technique that requires a large sample size. Factor analysis is based on the correlation matrix of the variables involved, and correlations usually need a large sample size before they stabilize. The results of Exploratory factor analysis are shown in the Table 4.12 below. The Kaiser-Meyer-Olkin Measure of Sampling Adequacy statistic (0.862) indicates that the sample size is adequate to apply factor analysis on the data collected in the research study. The probability (p) value of Bartlett's Test of Sphericity statistic (0.000) indicates that the correlation matrix of the variables considered in the research study is not an identity matrix. This indicates that the factor analysis can be done on the data collected from the faculty members. 75

14 EFA 1 in the text denotes the Exploratory Factor Analysis employed for the first set of data investigating the employee relationship in business schools. EFA 2 denotes the Exploratory Factor Analysis employed for the second set of data exploring the faculty retention strategies. Table 4.12 KMO and Bartlett s Test (EFA 1) KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy..862 Bartlett's Test of Approx. Chi-Square Sphericity Sig..000 KMO measure of sampling adequacy is an index to examine the appropriateness of factor analysis. High values 0.5 and 1.0 indicate factor analysis is appropriate. Values below 0.5 imply that factor analysis may not be appropriate. From the above Table 4.12, it is seen that Kaiser Mayer Olkin measure of sampling adequacy index is and hence the factor analysis is appropriate for the given data set. Bartlett s Test of Sphericity is used to uncorrelated. It is based on chi-square transformation of the determinant of correlation matrix. A large value hypothesis in turn this would indicate that factor analysis is appropriate. Bartlett s test of Sphericity Chi-square statistics is , that shows the 21 statements are correlated and hence as inferred in KMO, factor analysis is appropriate for the given data set. 76

15 Reliability Analysis Cronbach s alpha is a measure of internal consistency, that is, how closely related a set of items are as a group. An investigation has been made with the reliability of data using a reliability test to see whether the random error causing inconsistency and in turn lower reliability is at managerial level or not. The point to be noted is that a reliability coefficient of 0.70 or higher is considered acceptable in social science research. A high value of alpha is often considered as evidence that the items measure an underlying (or latent) construct. As is depicted from the Table 4.13, the value of alpha coefficient for the 21 items is 0.907, suggesting that the items have relatively high internal consistency. Table 4.13 Reliability statistics (EFA 1) Cronbach's Alpha N of Items The Communalities can be defined as the proportion of each variable's variance that can be explained by the principal components (e.g., the underlying latent factors). It is also defined as the sum of squared factor loadings. The communalities of the variables including in the analysis is shown in the table. The results indicate that the communalities of all the measured variables are significant except in case of filling performance appraisal form at the time of performance appraisal period, predefined HR policies, continuously looking to shift and granting special leaves to attend conferences and research related activities. 77

16 Table 4.14 Communalities of the measured variables(efa 1) 78 Initial Extraction Recognized and appreciated for my work Motivated by seniors Communication between staff members is effective and trustworthy The institute has good synergy, working conditions and efficient staff I can trust on my superiors in the institute Equal respect and fair treatment to all employees Conflicts are immediately resolved and managed effectively by the leader Disciplinary actions in the form of official notice, memo are immediately charged on a mistake Regular faculty meetings are conducted The Institute's atmosphere is friendly and co-operative The institute has predefined HR policies Promotions are fair as per the performance of a faculty rather going favoritism Need to fill appraisal form at the time of performance appraisal period My appraisal is discussed with me My academic achievements(research) are given weight age for promotion and career development Receive constructive feedback about the quality of my work Fairly compensated for the work I do as per qualification and experience My job matches with my skill sets I like my job here and the people I work with Continuously looking for the opportunity to shift elsewhere Special leaves are provided to attend FDP,Conferences and research related activities Extraction Method: Principal Component Analysis.

17 With principal factor axis method, the initial values on the diagonal of the correlation matrix are determined by the squared multiple correlation of the variable with the other variables. The values in extraction column indicate the proportion of each variable's variance that can be explained by the retained factors. Variables with high values are well represented in the common factor space, while variables with low values are not well represented. The initial number of factors is the same as the number of variables used in the factor analysis. However, not all 21 factors will be retained. In the study only the first three factors are retained. The Eigenvalues are the variances of the factors. Because the factor analysis is conducted on the correlation matrix, the variables are standardized, which means that the each variable has a variance of 1, and the total variance is equal to the number of variables used in the analysis. Total Variance This Total column contains the eigenvalues. The first factor will always account for the most variance (and hence have the highest eigenvalue), and the next factor will account for as much of the left over variance as it can, and so on. Hence, each successive factor will account for less and less variance. The Percentage of Variance column contains the percent of total variance accounted for by each factor. The Cumulative % column contains the cumulative percentage of variance accounted for by the current and all preceding factors. The results indicate that the three factors together account for percent of the total variance. The number of rows in Extraction Sums of Squared Loadings panel of the table corresponds to the number of factors retained. The values in Rotation Sums of Squared Loadings panel of the table represent the distribution of the variance after the varimax rotation. Varimax rotation tries to maximize the variance of each of the factors, so the total amount of variance accounted for is redistributed over the three extracted factors (see Table 4.15).One of the popular methods used in Exploratory Factor Analysis is Principal Component Analysis, where the total variance in the data is considered to determine the minimum number of factors that will account for maximum variance of data. 79

18 Table 4.15 Total variance explained(efa 1) Component dimensio n0 Total Initial Eigenvalues % of Variance Cumulat ive % Extraction Sums of Squared Loadings Total % of Variance Cumulat ive % Rotation Sums of Squared Loadings Total % of Variance Cumulat ive % Extraction Method: Principal Component Analysis. 80

19 Table 4.16 Rotated component matrix (EFA 1) Component 1 Interactional Justice 2 Distributive Justice 3 Procedural Justice I like my job here and the people I work with.749 The Institute's atmosphere is friendly and co-operative.742 My job matches with my skill sets.728 I can trust on my superiors in the institute.723 Recognized and appreciated for my work.717 Communication between staff members is effective and trustworthy.702 The institute has good synergy, working conditions and efficient staff.675 Motivated by seniors.669 Equal respect and fair treatment to all employees.655 The institute has predefined HR policies.525 My appraisal is discussed with me.818 My academic achievements(research) are given weight age for promotion.802 and career development Fairly compensated for the work I do as per qualification and experience.773 Promotions are fair as per the performance of a faculty rather going.751 favoritism Recieve constructive feedback about the quality of my work.706 Continously looking for the opportunity to shift elsewhere Need to fill appraisal form at the time of performance appraisal period.516 Regular faculty meetings are conducted.684 Disciplinary actions in the form of official notice, memo are immediately.678 charged on a mistake Conflicts are immediately resolved and managed effectively by the leader.530 Special leaves are provided to attend FDP,Conferences and research.488 related activities Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 5 iterations. 81

20 Rotated component matrix table contains the rotated factor loadings, which are the correlations between the variable and the factor. Because these are correlations, possible values range from -1 to +1. The results indicate that the twenty measured variables can be clubbed into three factors. The three factors are Interactional Justice, Distributive Justice and Procedural Justice reflecting Organizational Justice. The rotated factor matrix showing the factors along with their variables is shown in the Table Rotated Method: Varimax with Kaiser Normalization Interpretation of factors is facilitated by identifying the statements that have large loadings in the same factor. The factor can be interpreted in terms of the statement that loads high on it. The type of employee relationships faculty members have in NBA accredited Business Schools in Northern India is found sound, fair and good. Interactional justice, procedural justice and distributive justice under the head of organizational justice is found to be the factors making the employee relationship sound and better amongst the faculty members in Business Schools. With effect of organizational justice in the Business Schools, faculty members wishes to stay and does not want to shift elsewhere as they are found highly embedded in their jobs having fair compensation, career planning & development opportunities, constructive feedback,fair appraisal policies and promotions which shows their commitment towards the job and organization. Organizational Justice: Building Employee Relationship in Business Schools Organizational Justice Organizational justice is a multidimensional construct that describes the role of fairness in an organizational context which is quiet evident with the loadings in the Table 4.16.The organizational justice dimensions are named as distributive justice, procedural justice and interactional justice. Interactional justice is composed of interpersonal and informational justice dimensions. Interpersonal justice is related to the degree to which people are treated with politeness, dignity, and respect by authorities or third parties involved in executing procedures or outcomes. While, Informational justice is related to the explanantions provided to people that convey information about why procedures were used in a certain way or why outcomes were distributed in a certain fashion. A meta-analytic enquiry shows that interpersonal and informational justice dimensions have positive outcomes, 82

21 such as job satisfaction, organizational commitment, in-role performance, and less intention to leave the organization. Procedural justice is one of the three dimensions of organizational justice. Organizational justice is a multidimensional construct that describes the role of fairness in an organizational context. When there are fair procedures in an organization, employees have the opportunity to assess and have control over outcomes. The voice in decision making, opportunity to correct errors of judgement, equal and unbiased application of the rules, and decisions made on the basis of accurate information are sources of procedural justice in organizations. Employees with favorable perceptions of procedural justice in an organization are engaged with their work and thus have high levels of organizational commitment and elevated levels of in-role an d extra role performances in the work place. Distributive Justice assessment is important for employees, because they want to learn whether the management of the organization has fair distribution of work rewards or not. Employees perceptions of distributive justice emerge from their assessments of fairness regarding pay levels, work schedules, and work assignments. Employees with favourable perceptions of distributive justice experience lower burnout, are satisfied with their jobs, have high organizational commitment, perform effectively in the workplace and demonstrates less intention to leave the organization. 83

22 Section-D Gap Analysis between the expected and offered services provided by Business Schools: When a faculty member joins a new institute, he/she is having a lot of expectation from the new institute. After spending some tenure in the institute, he/she starts comparing the actual offerings of the institute he/she received after joining with expected services he/she had at the time of joining. If the offerings do not matches with the expectations of employees, there emerges a feel of dissatisfaction and faculty members starts pointing towards the grey areas of the institute which needs attention. In order to analyze the difference between expected services and offered services by the B-Schools to their faculty members, the t-test is applied.the null hypothesis of t-test can be expressed as H0: There is no significant difference between the expected services by the faculty members from the institute and services offered by the institute to the faculty members. H1: There exists significant difference between the expected services by the faculty members from the institute and services offered by the institute to the faculty members. The results of the t-test is shown in Table 4.17, the results indicate that with 95% confidence level the null hypothesis cannot be accepted since the p value of all the individual variable is less than 5% as well as the t statistic is statistically significant (greater than < 2) the results also indicate that initially the expectation level of faculty members is very high represented by greater mean scores as compared to mean score of the offered services of the institute. Hence, it can be concluded by the results that institutes are not able to fulfill the expectation level of faculty members, in other words the actual offerings by the institute are significantly inferior to what is expected by the faculty members (see Table 4.17). 84

23 Table 4.17 Gap Analysis between the expected and offered services provided by Business Schools Variable Mean Score (S.D) T- Statistic (P Value) Remark Spouse Hiral Programmes FDP Cell Expected 2.91 Offerings (1.31) (.000) (0.999) Expected 4.07 (1.02) Offerings 3.08 (.000) (1.22) Significant Different Exist Significant Different Exist Exit Interviews Expected 3.91 (1.03) Offerings 2.40 (1.10) (.000) Significant Different Exist Written HR policies HR Department Schemes Employee Benefits Financial assistance for research Expected 4.36 Offerings (.879) (.000) (1.19) Expected 4.22 (1.00) Offerings 2.62 (.000) (1.23) Expected 4.42 (0.869) Offerings 2.41 (.000) (1.07) Expected 4.53 (0.898) Offerings 3.30 (.000) (1.21) Expected 4.38 (0.90) Offerings 3.33 (.000) (1.09) Significant Different Exist Significant Different Exist Significant Different Exist Significant Different Exist Significant Different Exist 85

24 Special Incentives for publications Best faculty cum researcher award Sixth pay commission Faculty Induction programmes Expected 4.32 Offerings (0.953) (.000) (1.08) Expected (1.07) (.000) Offerings 2.33 (1.14) Expected 4.49 (0.895) Offerings 2.93 (.000) (1.27) Expected 4.92 (4.44) Offerings 2.50 (.000) (1.14) Significant Different Exist Significant Different Exist Significant Different Exist Significant Different Exist Spouse hiral programmes t-test was applied to evaluate difference in expectations and offerings to faculty members by the NBA accredited Business Schools in Northern India. If the value of t- test is less than the standard value at 48 degree level of significance the null hypothesis is accepted otherwise alternate hypothesis is accepted. The null hypothesis has been rejected because the t-test value (5.462) is more than the cut-off value ( at 48 degree level of significance). Hence there is significant difference exist between the expectations and offerings of spouse hiral programmes to the faculty members of accredited Business Schools. FDP Programmes t-test was applied to evaluate difference in expectations and offerings to faculty members by the NBA accredited Business Schools in Northern India. If the value of t- test is less than the standard value at 48 degree level of significance the null hypothesis is accepted otherwise alternate hypothesis is accepted. 86

25 The null hypothesis has been rejected because the t-test value (13.198) is more than the cut-off value ( at 48 degree level of significance). Hence there is significant difference existing between the expectations and offerings related to FDP programmes to the faculty members of accredited Business Schools. Exit Interviews t-test was applied to evaluate difference in expectations and offerings to faculty members by the accredited Business Schools in Northern India. If the value of t-test is less than the standard value at 48 degree level of significance the null hypothesis is accepted otherwise alternate hypothesis is accepted. The null hypothesis has been rejected because the t-test value (19.537) is more than the cut-off value and quiet higher than the cut off value ( at 48 degree level of significance). Hence there is significant difference existing between the expectations and offerings as far as Exit interviews are concerned to the faculty members of accredited Business Schools. Written HR policies t-test was applied to evaluate difference in expectations and offerings to faculty members by the NBA accredited Business Schools in Northern India. If the value of t- test is less than the standard value at 48 degree level of significance the null hypothesis is accepted otherwise alternate hypothesis is accepted. The null hypothesis has been rejected because the t-test value (23.715) is more than the cut-off value ( at 48 degree level of significance). Hence there is significant difference existing between the expectations and offerings towards HR policies formulation by the Business Schools. HR department t-test was applied to evaluate difference in expectations and offerings to faculty members by the NBA accredited Business Schools in Northern India. If the value of t- test is less than the standard value at 48 degree level of significance the null hypothesis is accepted otherwise alternate hypothesis is accepted. 87

26 The null hypothesis has been rejected because the t-test value (18.942) is more than the cut-off value ( at 48 degree level of significance). Hence there is significant difference existing between the expectations and offerings as far as existence of HR department is concerned in the accredited Business Schools. Schemes t-test was applied to evaluate difference in expectations and offerings to faculty members by the NBA accredited Business Schools in Northern India. If the value of t- test is less than the standard value at 48 degree level of significance the null hypothesis is accepted otherwise alternate hypothesis is accepted. The null hypothesis has been rejected because the t-test value (28.849) is more than the cut-off value ( at 48 degree level of significance). Hence there is significant difference existing between the expectations and offerings as far as existence of schemes like super annuation allowance, long term stay bonus is concerned to be provided to the faculty members in the accredited Business Schools. Employee Benefits t-test was applied to evaluate difference in expectations and offerings to faculty members by the NBA accredited Business Schools in Northern India. If the value of t- test is less than the standard value at 48 degree level of significance the null hypothesis is accepted otherwise alternate hypothesis is accepted. The null hypothesis has been rejected because the t-test value (15.165) is more than the cut-off value ( at 48 degree level of significance). Hence there is significant difference existing between the expectations and offerings as far as employee benefits being provided by the Business Schools to its faculty members are concerned. Financial Assistance for Research t-test was applied to evaluate difference in expectations and offerings to faculty members by the NBA accredited Business Schools in Northern India. If the value of t- 88

27 test is less than the standard value at 48 degree level of significance the null hypothesis is accepted otherwise alternate hypothesis is accepted. The null hypothesis has been rejected because the t-test value (15.271) is more than the cut-off value ( at 48 degree level of significance). Hence there is significant difference existing between the expectations and offerings as far as financial assistance being provided for the research activities to the faculty members of the Business Schools is concerned. Special Incentives for Publication t-test was applied to evaluate difference in expectations and offerings to faculty members by the NBA accredited Business Schools in Northern India. If the value of t- test is less than the standard value at 48 degree level of significance the null hypothesis is accepted otherwise alternate hypothesis is accepted. The null hypothesis has been rejected because the t-test value (23.268) is more than the cut-off value ( at 48 degree level of significance). Hence there is significant difference existing between the expectations and offerings of special incentives for publication being provided by the accredited Business Schools to its faculty members. Best Faculty cum Researcher Award t-test was applied to evaluate difference in expectations and offerings to faculty members by the NBA accredited Business Schools in Northern India. If the value of t- test is less than the standard value at 48 degree level of significance the null hypothesis is accepted otherwise alternate hypothesis is accepted. The null hypothesis has been rejected because the t-test value (23.505) is more than the cut-off value( at 48 degree level of significance). Hence there is significant difference existing between the expectations and offerings as far as existence of Best Faculty Cum Researcher Award such practice is concerned for the faculty members in the accredited Business Schools. 89

28 Sixth Pay Commission t-test was applied to evaluate difference in expectations and offerings to faculty members by the NBA accredited Business Schools in Northern India. If the value of t- test is less than the standard value at 48 degree level of significance the null hypothesis is accepted otherwise alternate hypothesis is accepted. The null hypothesis has been rejected because the t-test value (19.244) is more than the cut-off value ( at 48 degree level of significance). Hence there is significant difference existing between the expectations and offerings as far as existence of Sixth commission in the term of compensation being given to its faculty members by the accredited Business Schools is concerned. Faculty Induction Programmes t-test was applied to evaluate difference in expectations and offerings to faculty members by the NBA accredited Business Schools in Northern India. If the value of t- test is less than the standard value at 48 degree level of significance the null hypothesis is accepted otherwise alternate hypothesis is accepted. The null hypothesis has been rejected because the t-test value (9.930) is more than the cut-off value ( at 48 degree level of significance). Hence there is significant difference existing between the expectations and offerings as far as existence of HR practice that is Faculty Induction programmes which is given to the newly joined faculty member in the accredited Business Schools is concerned. 90

29 Section-E In the research study the efforts are made to investigate the influential factors that are affecting the faculty member to stay in their working institution. The twenty two variables representing the various dimensions of the HR practices of the B- Schools including the policies and concern of the management of the Business Schools towards the growth and development for the faculty members and their retention with the business schools are included in the Section-E of the questionnaire. The Exploratory factor analysis is applied on the responses in order to identify the latent factors which influences the faculty members to stay and continue working in the Business Schools. This will not only help in knowing the major factors affecting retention of faculty members but will also help in exploring retention strategies of faculty members and proposed model for retention of faculty members. Exploratory Factor analysis is a method of data reduction. It does this by seeking underlying unobservable (latent) variables (factors) that are reflected in the observed variables (measured variables). There are various methods that can be used to conduct a Exploratory factor analysis (such as principal axis factor, maximum likelihood, generalized least squares, unweighted least squares).in addition to this, there are also different methods of rotations that can be applied after the initial extraction of factors, including orthogonal rotations, such as Varimax and Equimax, which impose the restriction that the factors cannot be correlated, and oblique rotations, such as Promax, which allow the factors to be correlated with one another. Factor analysis is a technique that requires a large sample size. Factor analysis is based on the correlation matrix of the variables involved, and correlations usually need a large sample size before they stabilize. The results of Exploratory factor analysis are shown in Table 4.18 shown below. The Kaiser-Meyer-Olkin Measure of Sampling Adequacy statistic (0.828) indicates that the sample size is adequate to apply factor analysis on the data collected in the research study. The probability (p) value of Bartlett's Test of Sphericity statistic (0.000) indicates that the correlation matrix of the variables considered in the research study is not an identity matrix. This indicates that the factor analysis can be done on the data collected from the faculty members. 91

30 EFA 2 in the text denotes the Exploratory Factor Analysis employed for the second set of data exploring the faculty retention strategies. Table 4.18 KMO and Bartlett's Test (EFA 2) KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy..828 Bartlett's Test of Approx. Chi-Square Sphericity Sig..000 KMO measure of sampling adequacy is an index to examine the appropriateness of factor analysis. High values 0.5 and 1.0 indicate factor analysis is appropriate. Values below 0.5 imply that factor analysis may not be appropriate. From the above Table 4.18, it is seen that Kaiser Mayer Olkin measure of sampling adequacy index is and hence the factor analysis is appropriate for the given data set. Bartlett s Test of Sphericity is used to uncorrelated. It is based on chi-square transformation of the determinant of correlation matrix. A large value hypothesis in turn this would indicate that factor analysis is appropriate. Bartlett s test of Sphericity Chi-square statistics is , that shows the 15 statements are correlated and hence as inferred in KMO, factor analysis is appropriate for the given data set. The statements less than 0.4is deleted from the communalities of measured variables. Only 15 statements out of 22 are further carried out for factor analysis so as to get better refined result. The Communalities can be defined as the proportion of each variable's variance that can be explained by the principal components (e.g., the underlying latent factors). It is also defined as the sum of squared factor loadings. The communalities of the variables including in the analysis is shown in the Table

31 Table 4.19 Communalities of the measured variables (EFA 2) Initial Extraction Recognition, Rewards and Designations FDP s and Training programmes Employee benefits Career planning and development Organizational climate and culture Work life balance Co-operation from work teams Job security Job enrichment Performance appraisal and performance management Physical working facilities / infrastructure Social environment in the organization Flexible working schedules Goodwill / Brand of the institute Difficulty in family relocation The results indicate that the communalities of all the measured variables are significant except in case of salary and incentives, quality of employer s leadership,role clarity,satisfaction with current profile,proximity with own residence,opportunity to grow and develop and financial assistance to research and project work.therefore these seven items are deleted and not carried forward for exploring factor analysis. 93

32 Reliability Analysis Cronbach s alpha is a measure of internal consistency, that is, how closely related a set of items are as a group. An investigation has been made with the reliability of data using a reliability test to see whether the random error causing inconsistency and in turn lower reliability is at managerial level or not. The point to be noted is that a reliability coefficient of 0.70 or higher is considered acceptable in social science research.a high value of alpha is often considered as evidence that the items measure an underlying (or latent) construct. As is depicted from the Table 4.20, the value of alpha coefficient for the 15 items is 0.842, suggesting that the items have relatively high internal consistency. Table 4.20 Reliability statistics (EFA 2) Cronbach's Alpha N of Items

33 Table 4.21 Total variance explained (EFA 2) Comp onent Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings Total % of Variance Cumulat ive % Total % of Variance Cumulat ive % Total % of Variance Cumulat ive % Extraction Method: Principal Component Analysis. With principal factor axis method, the initial values on the diagonal of the correlation matrix are determined by the squared multiple correlation of the variable with the other variables. The values in extraction column indicate the proportion of each variable's variance that can be explained by the retained factors. Variables with high values are well represented in the common factor space, while variables with low values are not well represented. The initial number of factors is the same as the number of variables used in the factor analysis. However, not all 15 items will be retained. Only some of the items having load value more than 0.5 will be referred to as faculty retention strategies. In the study only the first three factors are retained. The Eigenvalues are the variances of the factors. Because the factor analysis is conducted on the correlation matrix, the variables are standardized, which means that the each variable has a variance 95

34 of 1, and the total variance is equal to the number of variables used in the analysis (see Table 4.21). Total Variance This Total column contains the eigenvalues. The first factor will always account for the most variance (and hence have the highest eigenvalue), and the next factor will account for as much of the left over variance as it can, and so on. Hence, each successive factor will account for less and less variance. The Percentage of Variance column contains the percent of total variance accounted for by each factor.the Cumulative % column contains the cumulative percentage of variance accounted for by the current and all preceding factors. The results indicate that the three factors together account for percent of the total variance. The number of rows in Extraction Sums of Squared Loadings panel of the table corresponds to the number of factors retained. The values in Rotation Sums of Squared Loadings panel of the table represent the distribution of the variance after the varimax rotation. Varimax rotation tries to maximize the variance of each of the factors, so the total amount of variance accounted for is redistributed over the three extracted factors.one of the popular methods used in Exploratory Factor Analysis is Principal Component Analysis,where the total variance in the data is considered to determine the minimum number of factors that will account for maximum variance of data. Rotated component matrix table contains the rotated factor loadings, which are the correlations between the variable and the factor. Because these are correlations, possible values range from -1 to +1. The results indicate that the fifteen measured variables can be clubbed into three factors. The three factors affecting retention of faculty members are Quality of Work Life, Employee Value Proposition and Organizational Image.The rotated factor matrix showing the factors along with their variables is shown in the Table

35 Table 4.22 Rotated component matrix (EFA 2) 1 Quality of Work Life (QWL) 97 Component 2 Employee Value Proposition (EVP) 3 Organizational Image Social environment in the organization.747 Job security.741 Job enrichment.726 Co-operation from work teams.673 Work life balance.632 Physical working facilities / infrastructure.612 Organizational climate and culture.585 Flexible working schedules.552 Recognition, Rewards and Designations Career planning and development.793 FDP's and Training programmes.767 Employee benefits.615 Performance appraisal and performance management.491 Difficulty in family relocation Goodwill / Brand of the institute.583 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 5 iterations.

36 Rotated Method: Varimax with Kaiser Normalization Interpretation of factors is facilitated by identifying the statements that have large loadings in the same factor. The factor can be interpreted in terms of the statement that loads high on it. The factors those who loads more than 0.5 are considered contributing more towards the retention of faculty members and are titled as retention strategies of faculty members in NBA accredited Business Schools in Northern India by the researcher listed below: Career Planning and Development (0.793) FDP s and Training Programs ( 0.767) Social Environment in the institution (0.747) Job Security (0.741) Job Enrichment (0.726) Co-operation from work teams (0.673) Work life balance (0.632) Employee Benefits (0.615) Physical working facilities and Infrastructure (0.612) Goodwill / Brand of the Institute (0.583) Organization climate and culture (0.585) Flexible working schedules (0.552) 98

37 Table 4.23 Overall faculty level of satisfaction Mean Std. Deviation Overall level of satisfaction with the current working institute Recommendation to your friend to join the institute Figure 4.11 Overall faculty level of satisfaction The Table 4.23 and Figure 4.11 depict the relationship between the satisfaction level of the faculty members. Recommending someone is one of the sources of recruiting the employees. If a faculty member is satisfied with the Business School he/she is working in; thereby recommends their friends, relatives and known potential candidates to apply in the Business School where they are working in. As it is also evident through the stats of the Table 4.22 i.e. the mean score of the faculty satisfaction towards their job is and thereby it can be seen that the mean score of recommending friend to join the same working institute is There is not a lot difference between both the mean scores. 99

38 4.3.2 Results of the Survey Conducted for Directors Table 4.24 Average stay of faculty members in the Institute Average stay of faculty Frequency Percent 1 to 4 yr to 7 yr more than 7 yr Total Figure 4.12 Average stay of faculty members in the Institute Table 4.24 and Figure 4.12 reveals the average stay of a faculty member at NBA accredited Business School in Northern India. To this concern, 50% of the respondents say that faculty on an average stays for 4 to 7 years.40% of the respondents supports the average stay tenure from 1 to 4 years.10% of the respondents state more than 7 years. It is very clear from the Table 4.24 that majority of the faculty members stays with the institute for 4 to 7 years. This can be exceptional in case of some institutes where stays for more than 7 years. 100

39 Table 4.25 Average number of faculty members leaving the Institute in an academic year Average number of faculty leaving Frequency Percent upto to to more than Total Figure 4.13 Average number of faculty members leaving the Institute in an academic year The data tabulated in the Table 4.25 and bar graphs presented in the Figure 4.13 highlights the average number of faculty members leaving the institute in an academic year.50% of the respondents claims up to 4 faculty members leaving the institute in an academic year.20% of the respondents support 8 to 12 and more than 12 faculty members quitting the institution in an academic year.10% of the respondents supports 4 to 8 faculty members in number leaving the NBA accredited Business School in Northern India in an academic year. 101

40 Table 4.26 Is exit interview conducted after acceptance of resignation letter Exit Interview conducted Frequency Percent YES NO Total Figure 4.14 Is exit interview conducted after acceptance of resignation letter The above mentioned Table 4.26 and Figure 4.14 reveals the finding that 60% of the NBA accredited Business Schools in Northern India conducts exit interview once the resignation letter is accepted from the faculty member.40% of the accredited Business Schools seems to be least bothered to know that why the faculty members are leaving institute as the study finds that 40% of the institutions do not conduct exit interviews. 102

41 Table 4.27 Who conducts exit interview Exit Interview Conducted by Frequency Percent Top Management HR Department 0 0 Employer 0 0 Director HOD Figure 4.15 Who conducts exit interview The data tabulated in the Table 4.27 and Figure 4.15 reveals that in 50% of the NBA accredited Business Schools exit interview is conducted by Top Management.80% of the Business Schools prefer having conduct exit interview by Director. The exit interview conducted by HOD is found only in 40% of the Business Schools. The results claim that there is no involvement of employer and HR department in any of the accredited Business Schools in Northern India when it comes to organizing exit interview. 103

42 Table 4.28 Are employees open at exit interview Employees open at exit interview Frequency Percent YES NO Total Figure 4.16 Are employees open at exit interview The above tabulated data in the Table 4.28 and the graph presented in the Figure 4.16 shows that 70% of the faculty members at NBA accredited Business Schools in Northern India are found having their opinions open at exit interview. Majority of the faculty members in their exit interview are found frank and free in quoting the reasons responsible for their voluntary turnover decision. The free and frank opinion of the faculty members can help the program administrators and academic leaders to revise the policies and design best HR practices in order to retain the existing remaining faculty members. 104

43 Table 4.29 Is HR practices and policies amended on the basis of exit interview HR practices and policies revised on the basis of exit interview Frequency Percent YES NO Total Figure 4.17 Is HR practices and policies amended on the basis of exit interview The data tabulated in the Table 4.29 and the graphical presentation of the data in Figure 4.17 highlights the fact that only 50% of the NBA accredited Business Schools revise and amend their policies and practices on the basis of exit interview results. Only half the Business Schools makes a concern in revising the HR policies and designing HR practices for retaining faculty members. Only 50% of the NBA accredited business schools have a revision in their policies on the basis of the results of the exit interview and the remaining 50% do not have any revision in their policies. 105

44 Table 4.30: Number of PhD holders / scholars associated with the institute as faculty members Ph.D holders / scholars as faculty members Frequency Percent 1 to to to more than Total Figure 4.18 Number of PhD holders/scholars associated with the institute as faculty members The above mentioned Table 4.30 and Figure 4.18 presents the number of Ph.D holders & research scholars associated with the NBA accredited Business Schools in Northern India as faculty members. The data reveals that 50% of the business schools have more than 12 faculty members in their Business Schools those who are Ph.D or pursuing Ph.D in their respective domains.30% of the Business Schools have only 5 to 8 doctorates or scholars pursuing doctoral education as faculty members. Only 10% of the Business Schools are found having 1 to 12 faculty members holding PhD degrees or pursuing research. 106

45 Table 4.31 Impact of efficient faculty departure on institute An efficient faculty leaving the institute may cause Frequency Percent Disrupt teaching & research programs Causes academic loss for students Adds recruitment & stationary cost Incurs no cost to the Institute 0 0 Figure 4.19 Impact of efficient faculty departure on institute Faculty plays a prominent role in the smooth functioning of an institution. The importance of faculty has been discussed in detail in chapter one of the present study. The related literature has also underpinned the impact of faculty turnover on the institution. The above mentioned Table 4.31 and Figure 4.19 reflect the impact of faculty members turnover on the institution. The results reveals that the separation of faculty from the working Business School incurs and adds no cost to the institute.80% of the respondents firmly believes that the departure of a talented and efficient faculty not only causes academic loss for the students whereas also disrupt teaching and research programs. The amazing result signifies the role of faculty in the institutional development. 107

46 Table 4.32 Factors responsible for leaving the institute as per exit interview Factors responsible for leaving the institute as per exit interview Frequency Percent Salary Working environment 3 10 Research opportunities 6 20 Employee benefits Work life balance 3 10 Figure 4.20 Factors responsible for leaving the institute as per exit interview The study has also made an attempt to identify the reasons responsible for the faculty members leaving the institute as per exit interview. The exit interview results in the response of respondents claim employee benefits and salary to be the foremost reasons responsible for quitting. Research opportunities, Work life balance and working environment are not found having any significant impact on the turnover decision of a faculty member. The results in turn shows the inability of the NBA accredited Business Schools in Northern India in offering lucrative salary packages and benefits to the faculty member which in turn leads to the voluntary turnover decision (see Table 4.32 and Figure 4.20). 108

47 Table 4.33 Policies and procedures practiced for betterment of faculty members In the Institute Faculty members are rewarded for their loyalty Faculty members are fairly appraised and promoted Support is provided in the education and personal growth of faculty members Faculty members perceive that they have freedom of their work Faculty members are provided opportunity giving add on responsibility not simply adding more task Faculty members are recognized for their major accomplishments on the job Faculty members are challenged in their jobs Communication to faculty members for their work is important Ways are looked forward to make faculty members more efficient Working conditions are comfortable for faculty members Practices have clear policies related to salaries, raises and bonuses Faculty members perceive that their benefits are sufficient Faculty members perceive that they are being paid fairly Salaries of faculty members are as per AICTE/UGC norms Std. Mean Deviation The study tried to know the policies and procedures being adopted by Business Schools as in concern to the faculty members related aspects.the result explores clear policies related to salary,raises and bonuses,salaries of faculty members as per AICTE/UGC norms,comfortable working conditions,recognitions and rewards,freedom to work in one s own style,support in the educational and personal growth,adding new responsibilities,effective communication, fair appraisal and promotional avenues found to be the procedures and policies being adopted by the Business Schools for betterment of faculty members.the results as shown in the Table 4.33 and Figure 4.21 has also highlighted the policies,procedures and practices which are not being followed and adapted by majority of the NBA accredited Business Schools. The results claim that majority of the business schools donot reward faculty members for their loyalty and are not challenged in their jobs. 109

48 Figure 4.21 Policies and procedures practiced for the betterment of faculty members 110

49 Table 4.34 Modes adopted for faculty retention Modes adopted for faculty retention Frequency Percent Good salary Working environment 6 20 Recognition & Rewards / Incentives Research / FDP 9 30 Spouse hiral programs 6 20 Career planning & development Employee benefits Job enrichment 6 20 Superannuation allowance 0 0 Long term stay bonus 3 10 Study leaves to complete Ph.D Figure 4.22 Modes adopted for faculty retention 111

50 The study also tried to investigate the strategies being adopted by the NBA accredited Business Schools to retain the efficient faculty members. The results(see Table 4.34 and Figure 4.22) cites Employee benefits, Career planning and development, Good salary structure, Recognition and rewards / incentives and study leaves to complete Ph.D as faculty retention strategies being adopted by majority of the business schools to retain efficient faculty members as per the response of respondents. Superannuation allowance and long term stay bonus considered to be very effective and efficient in retaining the productive employees are found not adopted by any of the accredited business schools in Northern India to retain faculty members. Table 4.35 Ever dealt with faculty members who are disruptive and have intention to leave in short term Dealing with disruptive faculty members/have an intention to leave Frequency Percent YES NO Total Figure 4.23 Ever dealt with faculty members who are disruptive and have intention to leave in short term The above tabulated data in Table 4.35 and graphical presentation in Figure 4.23 shows the concern of NBA accredited Business Schools towards the retention of faculty members.it has been identified from the responses of respondents that 80% of the Business Schools deals with those faculty members who have an intention to leave the institute in short term. As these disruptive faculty members are no more remain productive and are suffering from employee burnout. The academic leader identifying the source of dissatisfaction 112

51 tries to talk with the faculty member before taking any strong decision. This shows the concern of B-schools.But, the other aspect which cannot be denied is that in spite of having dealt up with such faculty members, still the faculty members leaves the institute. Therefore effective practices and retention plans need to be designed. Table 4.36 Is counseling done before accepting resignation letter Counseling done before accepting resignation letter from the faculty members Frequency Percent YES NO 0 0 Total Figure 4.24 Is counseling done before accepting resignation letter It has also been identified that the NBA accredited Business Schools before accepting the resignation letter from the faculty member also counsels them.counselling is done so that anyhow the faculty members changes their decision and gets retained. While counseling the faculty members, it is also tried to know that why is he/she joining the other institute and leaving the present working institute. The expectations and demands of faculty member is pondered by the management and in case if they are able to meet up to the demands of a faculty member. In those cases faculty member tends to remain in the working institute and quits the decision to join other institute. The above mentioned data in Table 4.36 and presentation of data in Figure 4.24 reflects a good gesture of Business Schools as all the Business Schools believe that effective counseling can sometime works for retention. 113

52 Table 4.37 Is the institute seriously facing the problem of faculty turnover and retention Institute seriously facing the problem of faculty turnover and retention Frequency Percent YES NO Total Table 4.25 Is the institute seriously facing the problem of faculty turnover and retention From the respondents, this was also tried to know that whether the NBA accredited Business Schools in Northern India are seriously facing the problem of faculty voluntary turnover & retention or not. The finding of the study which is tabulated above in the Table 4.37 and presented in the Figure 4.25 reveals that the Business Schools are not very seriously facing any problem related to turnover and retention of faculty members. The majority of business schools i.e. 70% of directors says that they are able to retain the faculty with them. 114