Market research project for IRMA placement
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This document provides an analysis and recommendations from a group project conducted among PRM 35 participants at IRMA. It includes: - Qualitative analysis of important factors for job selection including increased focus on government organizations. - Quantitative segmentation of participants into 3 clusters based on job preferences. Cluster 1 prefers marketing roles in tier 2 cities while fresher, etc. - Positioning of 7 organizations on attributes like brand and work culture. ITC is positioned as having a strong brand but mild work culture. - Recommendations to the placement office include inviting more government organizations and maintaining transparency in the selection process.
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Market research project for IRMA placement
- 1. IRMA PRM 35 PLACEMENTOFFICE IRMA PRM 35 BY: GROUP 8 SECTION B
- 2. Allocation of Project Qualitative Techniques Quantitative Techniques Segmentation Positioning Utility determination Suggestions to Placement Office Objective: To give the submissions to IRMA Placements Office regarding the jobs valued and preferred by participants based on the detailed research conducted among PRM 35 participants Sampling Plan: • Simple random sampling • 74 sampling size K means Clustering Factor Analysis Conjoint analysis ROADMAP
- 5. Qualitative Analysis of Interview Major factors/parameters for choosing a company during placements Expectation from IRMA Placements • Organization pool to be increased with more emphasis on Government organizations Feedback/suggestions for IRMA Placement Office • Government organizations to be invited • Conduct resume-building workshops • Maintain Transparency & Neutrality in placements • Students should decide which company will come for placements and in what order • IRMA placements must occur before other B-schools’ Placements Job Profile Sector Salary Career growth Location Work flexibility Brand Organizational values
- 6. Insights From Interview Agribusiness 15% CSR 22% Microfinance 15% NGO 11% Livelihood 11% Dairy 7% Govt 11% Social enterprise 4% Others 4% Sectoral Preference Tier 2 31% District 38% Tier 1 19% Tier 3 6% Village/ Block 6% Location Preference Market 22% Adhocracy 21% Clan 43% Hierarchy 14% Work-culture Preference
- 7. Sales 9% HR 9% Marketing 23% Microfinance 27% Supply Chain 18% Operations 5% Others 9% Specialization Preference < 6 Lakh 9% 6 - 8 Lakh 55% > 8 Lakh 36% Min-package Preference 7 - 9 Lakh 86% > 9 Lakh 14% Average-package Preference Undecided 37% Higher Studies 27% Career Growth 27% Civil Services 9% Future Goals
- 9. Basis Variables for Segmentation Standard Deviation of Basis Variables Std. Deviation Diverse job profiles from organizations 1.51 Branches/Offices 1.44 Sponsoring higher education 1.33 Entry position in the organization 0.93 Compromise on your preferred designation 1.68 Higher preference to other factors in comparison to “preferred sector” 1.50 Join an organization where no IRMA alumni have worked in the past 1.41 Alumni feedback 1.11 Pre-Placement Talks 0.97 Perks and other benefits 0.85 Bond or contract 1.59 Job profile 1.04 Designation 1.89 Attrition rate in the organization 1.10 Notice Period 1.56 Basis Variables (selected) Diverse job profiles from organizations Designation Bond/ Contract Notice Period Market trend impacting preferred sector Descriptive Variables Package Location Language Work experience Gender Age Educational Background
- 10. Verification of chosen basis variables Total Variance Explained Component Initial Eigenvalues Extraction Sums of Squared Loadings Total % of Variance Cumulative % Total % of Variance Cumulative % 1 1.611 20.134 20.134 1.611 20.134 20.134 2 1.549 19.366 39.500 1.549 19.366 39.500 3 1.272 15.899 55.400 1.272 15.899 55.400 4 1.005 12.564 67.963 1.005 12.564 67.963 5 .880 11.003 78.966 6 .742 9.272 88.238 7 .619 7.744 95.981 8 .321 4.019 100.000 We have taken only those basis variable. Whom standard deviation is greater than 1.40. Eight components are taken in Diverse job profile from organizations, designation, Bond/ contract, Notice period, Market trend impacting the choice of preferred sector, Branches, Higher preference to other factors in comparison to “preferred sector” and Join an organization where no IRMA alumni have worked in the past. Initial five basis variables are explaining 78.966% of variance. So we taken only those basis variables for clustering. So we did clustering on Diverse job profile from organizations, designation, Bond/ contract, Notice period and Market trend impacting the choice of preferred sector.
- 11. Number of Clusters Omega Values Number of Clusters Pooled VRC Omega values 2 87.282 3 109.449 -56.57 4 75.049 46.92 5 87.574 -14.03 6 86.065 -4.03 7 80.527 16.82 8 91.805 -35.07 9 68.014 1 2 3 4 5 6 Series1 -56.57 46.92 -14.03 -4.03 16.82 -35.07 -80.00 -60.00 -40.00 -20.00 0.00 20.00 40.00 60.00 AXISTITLE Omega Graph Number of clusters = 3 Scree Plot – Data Cluster number 2 3 4 5 6 7 8 9 Inter cluster distance 2.94 3.70 3.78 3.86 4.25 4.31 4.52 4.71 Intra cluster distance 3.23 2.87 2.80 2.63 2.42 2.32 2.21 2.15 Ratio (Intra/Inter) 1.10 0.78 0.74 0.68 0.57 0.54 0.49 0.46 0 0.2 0.4 0.6 0.8 1 1.2 1 2 3 4 5 6 7 8 Scree Plot Number of clusters = 3
- 12. Cluster Membership 0.000 5.000 10.000 15.000 20.000 25.000 30.000 35.000 1 2 3 Cluster Number of Cases in each Cluster Total number of respondent is 74. Cluster number 1 has maximum number of members 29. Cluster number 2 has 23 members. Cluster number 3 has 22 members.
- 13. Inter-Cluster Comparison C 1 C 2 C 3 Package 8 to 10 Lakh average package highest # (14/29) highest # (12/23) highest # (9/22) Preferred functional area 1st mkt (10/29) mkt (7/23) mkt (7/22) least preferred Sales, Op, IT – 1 IT, Sales – 0 Sales – 0 Work experience # of fresher highest # (15/29) highest # (12/23) highest # (8/22) 1 to 2 years 4/29 min (3/23) max (5/22) 2 to 3 years max (7/29) min (3/23) 5/22 Home state not preferring home state as work location min (11/29) max (15/22) Tier City you like to work Preferring Tier 2 city highest # (18/29) highest # (12/23) highest # (14/22)
- 15. Cluster 1 Features Package 6 to 8 lakh 8 to10 lakh > 10 Lakh Functional Area Marketing 2 6 2 Work Ex Fresher 3 9 3 Job Location Tier2 7 8 3 Job Location Tier1 Tier2 Tier3 Work Ex Fresher 5 10 0 Home Town Job Yes 6 12 0 Alien to Local Language Yes 3 10 0 Functional Area Marketing Finance HR General Management Tier2 6 1 3 5 Fresher 5 4 2 3
- 16. Cluster 2 Features Package 6 to 8 lakh 8 to10 lakh >10 Lakh Functional Area Marketing 1 3 3 Work Ex Fresher 3 6 3 Job Location Tier2 3 8 1 Job Location Tier1 Tier2 Tier3 Work Ex Fresher 4 8 0 Home Town Job No 6 8 0 Alien to Local Language Yes 9 9 0 Functional Area Marketing Finance General Management Work Ex Fresher 5 3 1 Job Loc Tier2 5 1 3
- 17. Cluster 3 Features Package 6 to 8 lakh 8 to10 lakh > 10 Lakh Functional Area Marketing 1 3 3 Work Ex Fresher 1 3 4 Job Location Tier2 4 8 2 Job Location Tier1 Tier2 Tier3 Work Ex Fresher 4 4 0 Home Town Job No 6 9 0 Alien to Local Language Yes 3 4 0 Functional area Marketing Finance Operations General Manage ment Count Count Count Count Fresher 4 2 1 1 Tier2 2 2 5 4
- 18. Selected Conjoint Attributes For Partitioning 0.000 10.000 20.000 30.000 40.000 50.000 Package Sector Functional Area Job Location Attribute Importance Value We got these importance value of attribute through conjoint analysis. We choose package and sector as basis variable for partitioning of data. This will help us to verify number of segments in our data.
- 19. Partitioning based on Conjoint Attribute Cluster No. Pooled VRC Omega 2 244.786 3 396.471 -416.899 4 131.257 325.930 5 191.973 -49.993 6 202.696 -50.634 7 162.786 78.400 8 201.275 10.147 9 249.912 -500 -400 -300 -200 -100 0 100 200 300 400 1 2 3 4 5 6 7 8 9 Basis Variable Package Preferred Functional Area
- 21. S. No. Sector Organizations 1 Co-Operatives & Associated Organizations GCMMF 2 Government Development Agencies RGAVP 3 Non- Government Development Organization AKRSP 4 Agri-finance & Microfinance Yes Bank, SBI 5 Social Enterprise Dharma Life 6 Technology & Consultancy PWC 7 Agribusiness & Rural Marketing & CSR Escorts ITC Attributes Brand Reputation Job Profile Package Career Growth Job Stability Job Satisfaction Selection Procedure Work Location Work Culture Selected Organizations & Attributes
- 22. Cluster 1:- Total Variance Explained Total Variance Explained Component Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings Total % of Variance Cumulativ e % Total % of Variance Cumulativ e % Total % of Variance Cumulativ e % 1 4.445 55.568 55.568 4.445 55.568 55.568 2.835 35.435 35.435 2 .942 11.774 67.342 .942 11.774 67.342 2.553 31.907 67.342 3 .713 8.912 76.253 4 .619 7.741 83.995 5 .548 6.846 90.841 6 .310 3.878 94.719 7 .221 2.766 97.485 8 .201 2.515 100.000 As 2 factors are explaining 67.342% of variance. So we taken only two components for making of perceptual map.
- 23. Rotated Component Matrix Rotated Component Matrixa Component 1 2 Brand Reputation .121 .894 Job Profile .362 .732 Package .378 .701 Job Stability .364 .621 Job Satisfaction .757 .388 Selection Procedure .681 .254 Work Location .809 .243 Work Culture .850 .257 Brand reputation, Job profile, Package and Job stability are forming one component of perceptual map. Job satisfaction, Selection procedure, Work location and Work culture are forming second component of matrix.
- 24. Good Brand Reputation Good Work Culture Sector Company Brand Reputation Work Culture Agribusiness & Rural Marketing & CSR ITC High Mild Agri-finance & Microfinance Yes Bank High Mild Non- Government Development Organization AKRSP Low Mild PERCEPTUALMAP
- 25. Cluster 2:- Total Variance Explained Total Variance Explained Compone nt Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings Total % of Variance Cumulativ e % Total % of Variance Cumulativ e % Total % of Variance Cumulativ e % 1 3.018 60.358 60.358 3.018 60.358 60.358 2.176 43.528 43.528 2 .826 16.528 76.886 .826 16.528 76.886 1.668 33.359 76.886 3 .517 10.331 87.218 4 .433 8.663 95.881 5 .206 4.119 100.000 As 2 factors are explaining 76.886% of variance. So we taken only two components for making of perceptual map.
- 26. Rotated Component Matrix Rotated Component Matrixa Component 1 2 Brand reputation .918 .126 Job Profile .873 .311 Job Stability .207 .833 Job Satisfaction .247 .813 Work Culture .684 .447 Brand reputation, Job profile, and work culture are forming one component of perceptual map. Job satisfaction and job stability are forming second component of matrix
- 27. High Job Satisfaction High Brand Reputation Sector Company Brand Reputation Job Satisfaction Agribusiness & Rural Marketing & CSR ITC High Mild Agri-finance & Microfinance Yes Bank High Low Non- Government Development Organization AKRSP Low Mild PERCEPTUALMAP
- 28. Cluster 3:- Total Variance Explained Total Variance Explained Compone nt Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings Total % of Variance Cumulati ve % Total % of Variance Cumulati ve % Total % of Variance Cumulati ve % 1 3.625 51.779 51.779 3.625 51.779 51.779 2.571 36.726 36.726 2 .892 12.742 64.521 .892 12.742 64.521 1.946 27.795 64.521 3 .723 10.327 74.848 4 .638 9.118 83.966 As 2 factors are explaining 64.521% of variance. So we taken only two components for making of perceptual map.
- 29. Rotated Component Matrix Rotated Component Matrixa Component 1 2 Brand reputation .894 -.031 Job Profile .605 .391 Job Stability .654 .305 Job Satisfaction .451 .734 Selection Procedure .073 .886 Work Location .567 .485 Work Culture .669 .374 Brand reputation, Job profile, job stability, work location and work culture are forming one component of perceptual map. Job satisfaction and selection procedure are forming second component of matrix
- 30. Brand Reputation Transparent Selection Procedure Sector Company Brand Reputation Selection Procedure Agribusiness & Rural Marketing & CSR ITC High Less Transparent Agri-finance & Microfinance Yes Bank High Moderately Transparent Non- Government Development Organization AKRSP Low Transparent PERCEPTUALMAP
- 32. Attribute Levels Package Less than 7 Lakhs 7 to 10 lakhs More than 10 lakhs Sector Agribusiness & Rural Marketing Development Microfinance Others Functional Area Finance Marketing Other Job Location Home State Other Total 4 attributes were taken. Total number of levels are 12. Total number of possible card: 3*4*3*2=72 Used orthogonal design to generate cards. 16 experimental card, 2 hold out cards were generated. Conjoint Design
- 33. GeneratedCards Card ID Package Sector Functional Area Job Location Rate 1 More than 10 lakh Agribusiness & Rural Marketing Finance Home State 2 Less Than 7 Lakh Development Finance Home State 3 More than 10 lakh Microfinance Other Other 4 Less Than 7 Lakh Microfinance Finance Home State 5 7 to 10 Lakh Others Finance Other 6 7 to 10 Lakh Agribusiness & Rural Marketing Finance Other 7 Less Than 7 Lakh Development Finance Other 8 Less Than 7 Lakh Microfinance Finance Other 9 More than 10 lakh Others Finance Home State 10 7 to 10 Lakh Development Other Home State 11 Less Than 7 Lakh Agribusiness & Rural Marketing Marketing Home State 12 7 to 10 Lakh Microfinance Marketing Home State 13 Less Than 7 Lakh Others Other Home State 14 Less Than 7 Lakh Others Marketing Other 15 More than 10 lakh Development Marketing Other 16 Less Than 7 Lakh Agribusiness & Rural Marketing Other Other 17 7 to 10 Lakh Microfinance Finance Other 18 Less Than 7 Lakh Development Other Other
- 34. UtilityScoreforCluster1 Utilities Utility Estimate Package Less Than 7 Lakh -0.85 7 to 10 Lakh 0.152 More than 10 lakh 0.695 Sector Microfinance -0.14 Agribusiness & Rural Marketing 0.235 Development 0.183 Others -0.28 Functional Area Finance -0.15 Marketing 0.241 Other -0.1 Job Location Home State 0.17 Other -0.17 (Constant) 4.695 More than 10 lakhs is most preferred level in package. Agribusiness is most preferred sector. Marketing is most preferred functional area. Home state is preferred job location.
- 35. Utility Analysis for Cluster 1 35.328 25.125 29.672 9.875 0.000 5.000 10.000 15.000 20.000 25.000 30.000 35.000 40.000 Package Sector Functional Area Job Location Average Importance of Cluster 1 Attribute Levels Max Utility Score Levels Min Utility Score Package > 10 lakhs 0.695 <7 Lakhs -0.85 Sector Agribusiness and RM 0.235 Other -0.28 Functional Area Marketing 0.241 Finance -0.15 Job Location Home State 0.170 Other -0.17 Constant 4.695 4.3695 Total Utility 6.036 2.9195 7 to 10 Lakh p.a. 0.152 Agri-business & Rural marketing 0.235 Marketing 0.241 Home state 0.17 Constant 4.695 Total utility 5.493 Simulation Cases
- 36. Correlation Correlations Value Sig. Pearson's R .970 .000 Kendall's tau .906 .000 Kendall's tau for Holdouts 1.000 As we can see here high correlation is observed between estimated and observed preferences.
- 37. UtilityScoreforCluster2 More than 10 lakhs is most preferred level in package. Agribusiness is most preferred sector. Finance is most preferred functional area. Home state is preferred job location. Utilities Utility Estimate Package Less Than 7 Lakh -.891 7 to 10 Lakh .043 More than 10 lakh .848 Sector Microfinance -.103 Agribusiness & Rural Marketing .201 Development -.049 Others -.049 Functional Area Finance .014 Marketing .009 Other -.024 Job Location Home State .027 Other -.027 (Constant) 4.572
- 38. Utility Analysis for Cluster 2 50.000 13.043 26.087 10.870 0.000 10.000 20.000 30.000 40.000 50.000 60.000 Package Sector Functional Area Location Average Importance for Cluster 2 Attribute Levels Max Utility Score Level Min Utility Score Package >10 lakhs 0.848 <7 Lakhs -0.891 Sector Agribusiness and RM 0.201 Others or Development -0.049 Functional Area Finance 0.14 Other -0.24 Job Location Home State 0.27 Other -0.27 Constant 4.572 4.572 Total Utility 6.031 3.672 7 to 10 Lakh p.a. 0.043 Development -0.049 Marketing 0.009 Other -0.027 Constant 4.572 Total Utility 4.548 Simulation Cases
- 39. Correlation Correlations Value Sig. Pearson's R .978 .000 Kendall's tau .814 .000 Kendall's tau for Holdouts 1.000 As we can see here high correlation is observed between estimated and observed preferences.
- 40. UtilityScoreforCluster3 More than 10 lakhs is most preferred level in package. Agribusiness is most preferred sector. Marketing is most preferred functional area. Home state is preferred job location. Utilities Utility Estimate Package Less Than 7 Lakh -.890 7 to 10 Lakh .184 More than 10 lakh .706 Sector Microfinance -.219 Agribusiness & Rural Marketing .361 Development .111 Others -.253 Functional Area Finance -.299 Marketing .422 Other -.123 Job Location Home State .071 Other -.071 (Constant) 4.516
- 41. Utility Analysis for Cluster 3 39.019 27.180 24.001 9.800 0.000 5.000 10.000 15.000 20.000 25.000 30.000 35.000 40.000 45.000 Package Sector Functional area Location Average Importance for Cluster 3 Attribute Levels Max Utility Score Levels Min Utility Score Package >10 lakhs 0.706 <7Lakhs -0.89 Sector Agribusiness and RM 0.361 Other -0.253 Functional Area Marketing 0.422 Finance -0.299 Job Location Home State 0.071 Other -0.071 Constant 4.516 4.516 Highest Utility 6.121 3.003 7 to 10 Lakh p.a. 0.184 Microfinance -0.219 Marketing 0.422 Other -0.071 Constant 4.516 Total Utility 4.832 Simulation Cases
- 42. Correlation Correlations Value Sig. Pearson's R 0.988 0 Kendall's tau 0.862 0 Kendall's tau for Holdouts 1 . As we can see here high correlation is observed between estimated and observed preferences.
- 43. Package Sector Functional are Job location 35.328 25.125 29.672 9.875 40.971 26.126 23.759 9.144 39.019 27.180 24.001 9.800 Importance Values Cluster 1 Cluster 2 Cluster 3 Inter-Cluster Comparison
- 44. Suggestions to Placements Office Our Findings: • Most preferred sector across all 3 clusters: Agri-business companies • Most preferred functional area across all 3 clusters: Marketing, Finance and General Management • Most preferred work location across all 3 clusters: Tier 2 • Package preference across all 3 sectors range from Rs.8 L to Rs.10 L
- 45. THANK YOU
Editor's Notes
- Objective:- To conduct a research on PRM 35 participants on the type of jobs valued & preferred by them so that its findings can give important inferences to IRMA placement office about the future placements at IRMA specially to be conducted in 2016. Sampling Of the total PRM 35 participants, 74 participants were selected for the survey via “simple random sampling” technique. A questionnaire was prepared for the same & respondents were asked to fill it. Road Map Under the qualitative techniques, word cloud was generated & interview of 15 participants were taken. Under quantitative techniques, K-means clustering (for segmentation & profiling of clusters), factor analysis (for generation of perceptual maps) & conjoint analysis (for inter-cluster comparison) were done.
- Interpretation:- Respondents were asked to write 10 words that comes to their mind when they think of IRMA placements. All the words were collated in excel & the above Word Cloud was generated (online). As can be seen by the size of the words in the word cloud, most prominent words that came to respondents mind are: 1) Job-profile 2) Package 3) Career-growth 4) Organization 5) Sector 6) Location 7) Job-security 8) Placement Committee
- Note:- The qualitative analysis showed that people choose organizations based on the following major factors/parameters: 1) Job profile (including designation, entry position, type of work etc) 2) Salary provided by the organization (including perks & benefits) 3) Location of the job 4) Brand value of the organization 5) Sector (as preferred by individual) 6) Career growth (during the job & also outside the organization after leaving it) 7) Work flexibility (working hours, decision making flexibility, submission to deadlines, dress code etc) 8) Organization values & culture Some of the feedbacks that participants gave during interview are: 1) More organizations from diverse fields & sectors should be called for placements (& even for internships) specially Government organization. 2) Workshops on resume building should be conducted among the participants to increase their chances in placements. 3) Very high degree of transparency & neutrality be kept for the entire placement process. 4) Placement Committee (on behalf of students) will decide which organization(s) will come for placements at IRMA & in which order. 5) IRMA placements should be conducted before placements of other B-Schools.
- Sectorial preference of participants:- 22% wanting to go in CSR sector; 15% each in Agri-business & microfinance sector; 11% each in NGOs, Livelihood interventions & Government sector. Location preference of participants Majority of participants preferring job location to be at district level (38%) followed by Tier2 cities (31%) & Tier1 cities (19%). Very few people wanting to go to Tier3 cities & village/block level (6% each). Work-culture preference or participants Majority of the participants wants to work in an organization having clan culture, i.e. doing things together (43%), followed by market culture, i.e. getting the job done (22%), adhocracy, i.e. doing things first (21%) & hierarchy, i.e. doing things right (14%).
- Specialization preference of participants:- Majority of the participants are inclined towards specialization in microfinance (27%), marketing (23%) & supply chain (18%) while preference for rest of the specializations are in single digit. Minimum package preference of participants Majority of the participants (55%) wants their minimum package between 6 to 8 lakh per annum. 36% participants wants more than 8 lakh per annum while only 9% of them are ok with less than 6 lakh per annum. Average package preference of participants Maximum of participants (86%) want average package of placements to lie between 7 to 9 lakh per annum while only 14% want it to be more than 9 lakh per annum. Future goals of participants Majority of participants (37%) are undecided about their future goals. 27% of them wants either growth in their future career or to pursue higher studies. Only 7% of them wanted to go in civil services later on in their life.
- Note:- We categorized 15 variables into 6 different categories in the survey questionnaire & found out standard deviation of each of these variables. In each category we chose the variable having highest standard deviation as basis variable – total 5 basis variables were chosen: 1) Diverse job profile from organizations 2) Designation 3) Bond/ contract 4) Notice period 5) Market trend impacting the choice of preferred sector Among the descriptive variables, we chose package, location, language, work experience, gender, age & educational background.
- Both the Scree plot & Omega graph were plotted & confirmed the presence of three (3) distinct clusters being formed among all the participants. In the scree plot, elbow point was occurring at cluster number 3 while omega value is coming out to be lowest (-56.57) for three clusters.
- For Cluster 1 has following features:- Marketing is the most preferred functional area in cluster. Fresher preferred to join marketing area with a package of 8 to 10 lakh. Second preferred area is general management. Members of cluster1 want to work in the tier2 city may be due to the package they are preferring. Members of cluster want to work in their home town. Also in this cluster people are ready to work in those locations of India, whom native language is alien to them. So, placement office should call more number of companies which offer marketing profile with package of 8 to 10 lakhs.
- Cluster 2 has following features:- Marketing is the most preferred functional area in cluster. Fresher preferred to join marketing area with a package of 8 to 10 lakh. Second preferred area is Finance. Members of cluster2 want to work in the tier2 city may be due to the package they are preferring. Members of cluster want to work in their home town. Also in this cluster people are ready to work in those locations of India, whom native language is alien to them. So, placement office should call more number of companies which offer marketing profile with package of 8 to 10 lakhs.
- Cluster 3 has following features:- Marketing is the most preferred functional area in cluster. Fresher preferred to join marketing area with a package of 8 to 10 lakh or more than 10 lakhs. Second preferred area is Finance. Members of cluster3 want to work in the tier2 or tier1 cities. Those who want to work in tier 2 city want operations or general management profiles. Members of cluster want to work in their home town. Also in this cluster people are ready to work in those locations of India, whom native language is alien to them.
- Note:- When we run the k-means cluster analysis by taking package and preferred functional area as basis variable. We got number of clusters as three. Which is equal to our previous result.
- Note:- To respondent we provided 53 companies list. Companies are divided in the 7 sectors. Respondent is free to choose any sector. Also, respondent is free to choose any one company in the chosen sector. In final analysis we used mode function to take only one company from each sector (except: Agri-finance & Microfinance, Agribusiness & rural. Because in these two sector data is highly distributed in various companies. So we took two companies.)
- Interpretation From Perceptual Map:- Yes bank is nearest to brand reputation, job profile, package and job stability parameters. It means participants have good perception of Yes bank on these parameters. While Yes bank is showing medium distance from the job satisfaction, work culture and work location. It means participants have medium perception on these parameter. Also, we can say Yes bank is giving high package, having good reputation among participants, offering good profiles to participants and providing stability in job. While satisfaction from job is low, work culture is not employee friendly and work location is not good. PWC is nearest to job satisfaction, work culture and work location. It means participants have good perception of PWC on these parameters. While PWC is showing medium distance from brand reputation, job profile, package and job stability parameters. It means participants have medium perception on these parameter. Also, we can say PWC is offering good work location, providing good work culture and job satisfaction to employees. While offering medium package, average brand reputation, offering satisfactory job profile. Ideal brand:- Ideal brand will be laying in between Yes bank and PWC. Ideal brand will show low distance from all the parameters if it lays in between these two brands.
- Interpretation From Perceptual Map:- ITC is nearest to brand reputation, job profile. So participants perceived ITC as good brand which offer good job profile. GCMMF is nearest to work culture, job stability and job satisfaction. So it is providing best work culture to its employees, employees having high job satisfaction. Ideal Brand:- Ideal brand location will be in between the ITC and GCMMF position. Which will be showing min distance from all the attributes.
- Interpretation from Perceptual Map:- SBI is nearest to Job profile, work location and work culture parameters. It means participants perceive SBI good on these parameters. While it is showing distance from selection procedure and job satisfaction. So, SBI is offering good job profile, providing good work culture to employees, giving good work location to employee. While selection procedure is not transparent in SBI. Yes Bank is nearest to brand reputation. Participants perceive Yes bank as a best organization. AKRSP is nearest to selection procedure. While showing distance from other parameters. So, participants perceived transparent selection procedure for AKRSP. Escort is showing middle distance from all the parameters. Ideal Brand:- Position of Escort will be best suitable for ideal brand. So, we are choosing Escorts as ideal brand for this cluster.
- Note: Card number 17 and 18 are holdout cases.
- Note:- Package is most preferred attribute after that functional area. Location of work is least preferred attribute. Best combination for job for this cluster is in agribusiness sector on marketing profile with package more than 10 lakhs and job at home state. Worst combination for this cluster in other sector on finance profile with package is less than 7 lakhs in other state.
- Note:- Package is most preferred attribute after that functional area. Location of work is least preferred attribute. Best combination for job for this cluster is in agribusiness sector on finance profile with package more than 10 lakhs and job at home state. Worst combination for this cluster is in other or development sector in other profile with package less than 7 lakhs in other state.
- Note:- Package is most preferred attribute after that Sector. Location of work is least preferred attribute. Best combination for job for this cluster is in agribusiness sector on marketing profile with package more than 10 lakhs and job at home state. Worst combination for this cluster is in other sector in finance profile with package less than 7 lakhs in other state.
- Notes:- Package is most preferred attribute across clusters. While Job location is least preferred attribute across clusters. In cluster 1 functional area is second preferred attribute. While in cluster 2 and cluster 3 sector is second preferred attribute.