Apr-Jun.12 - the Nitie

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4. Handles issue with professionalism. Loadings of Factor IV: Professionalism: Commu- 0.766 0.625 Variance explained = 9.003% Eigen value = 1.354 No. of variables = 2 Factor V: Appearance: 5. Ability to complete transaction. 0.717 0.685 2. Representative appears knowledgeable. 8. The customer support representative was courteous. 0.839 0.749 Factor VI: Technical knowledge and courtesy: 15. Having technical knowledge. 0.625 0.569 Variance explained = 8.063% Eigen value = 1.210 No. of variables = 1 0.819 0.800 Variance explained = 6.868% Eigen value = 1.030 No. of variables = 2 Total variance explained: 70.22% Total number of variables: 15 Source: Primary data Naming of factors and discussion: The six factors named in table 5 are explained below: This is the most high Eigen value and total variance. The co-operation given by representatives, importance to long term relations with customers, customer values, helping the customers know the cause for the problem and giving solution, and being helpful to resolve your issue or need contributed with higher factor loadings of 0.889, 0.854, 0.498 and 0.486 respectively with an explained variance of 23.445% and with high communalities ranging between 0.815 and 0.533 indicating that the attributes within this factor have very high association among them. Hence it should be given top priority to be monitored. With an explained variance of 12.190% of issues, representatives responding timely with high factor loadings such as 0.879, 0.765, and 0.548 respectively and with high communalities indicating that the variables within factor 2 are closely associated. It accounted for 10.453% of variance and three variables namely responsiveness to special needs of the customers, knowledge on customer’s same contributed by 0.812, 0.789 and 0.533 respectively. The attributes responsive to special needs and knowledge of representative on our problem play a leading roles in gaining customer satisfaction and the shown least leading role. Two variables were loaded on this factor and together they accounted for 9.003% of the variance with such high factor loadings as 0.766 and 0.717 respectively. The higher value of communality for the two attributes indicates that higher amount of variance is explained by the extracted factors. It could be concluded that the above attributes are powerful and strong variables which determines customer satisfaction. There is only one variable, namely the courteousness of the company executive, loaded on this factor and it accounted for 8.063% of variance with a factor loading of 0.830 indicating that this factor plays a successive role in gaining customer satisfaction. With a total variance of 6.868% two variables, namely the courtesy of the customer support staff, and their technical knowledge with factor loading 0.819 and 0.625 respectively were loaded on to this factor. Their communalities indicate that their courtesy plays a leading role in gaining customer satisfaction but their technical knowledge has shown the least role. Measurement of buyer’s satisfaction: response. Failure to meet the needs and expectations is assumed to result in dissatisfaction with the product or service, Vol. 36, No. 2, April-June, 2012 6
The mean scores for expectations as well as perceptions, and the gap between these two for all the given variables are calculated with the Tata Indicom cellular services (Table 6). Graph 1: GAP ANALYSIS Table 6: Mean scores, gaps and satisfaction on 15 statements of Gap analysis on Tata Indicom’s sales and service executives Sl. No. Attributes 2. Representative appears knowledgeable 1. problem 5. Ability to complete transaction 8. The customer support representative was courteous 3. Helps you to know the cause and gives solution 7. Knowledge of representative on our problem Perception Means (P) Expectation Means (E) Gap (P –E) % of satisfaction 1.980 2.030 -0.05 97.536 2.070 2.260 -0.19 91.592 1.950 2.350 -0.4 82.978 1.950 2.350 -0.4 82.978 2.010 2.470 -0.46 81.376 1.780 2.190 -0.41 81.278 6. 1.780 2.270 -0.49 78.414 4. Handles issues with 2.100 2.710 -0.61 77.490 professionalism 9. Representatives on being helpful and his ability to resolve your issue or need 1.810 2.450 -0.64 73.887 15. Having technical 1.900 2.610 -0.71 72.796 knowledge 10. Representative responds 1.850 2.840 -0.99 65.140 in a timely manner 11. Resolves mistakes quickly 1.660 2.630 -0.97 63.117 12. Responsive to special 1.850 3.080 -1.23 60.064 needs 13. Future co-operation given 1.870 3.550 -1.68 52.676 by Tata Indicom 14. Gives importance to the 1.720 3.380 -1.66 50.887 customer values and maintains long-term relations with them Note: 2. A positive gap indicates that customers perceived that service delivery exceeded their expectations; while a negative gap indicates that service delivery did not meet their expectations. On the basis of mean scores calculated, it was found that customers have ranked top Vol. 36, No. 2, April-June, 2012 7
Page 1 and 2: ISSN 0970-3365 Vol. 36, No. 2 April
Page 3 and 4: IN THIS ISSUE… Page No, 1. Buyers
Page 5 and 6: Buyers’ Expectations, Perceptions
Page 7 and 8: The sample was selected by using sy
Page 9: one variable was loaded on this fac
Page 13 and 14: It is also observed that there is a
Page 15 and 16: Increasing Bottom-Line Through Six
Page 17 and 18: causes of mistakes or defects in bu
Page 19 and 20: 3 Application of Six Sigma in Found
Page 21 and 22: For Hammer… DPMO = DPMO = No. of
Page 23 and 24: These defects were then evaluated o
Page 25 and 26: pouring. This will eliminate pin ho
Page 27 and 28: Desai, D. A. and Patel, M. B. (2009
Page 29 and 30: and strategic efforts to satisfy an
Page 31 and 32: ole theory and identity theory are
Page 33 and 34: eliability values are greater than
Page 35 and 36: Ashforth, B. E., & Humphrey, R. H.
Page 37 and 38: Pugh, S.D. (2001), “Service with
Page 39 and 40: The presence of autocorrelation in
Page 41 and 42: for the juice production process. A
Page 43 and 44: 5.0 COMPUTATION OF ARLs The ARLs of
Page 45 and 46: the same shift in the process mean
Page 47 and 48: in India, liberalization of the aut
Page 49 and 50: 3. Case study In this case study a
Page 51 and 52: as well as the company management t
Page 53 and 54: 10. Kitcharoen. K, (2004), The Impo
Page 55 and 56: Performance improvement tools DA MA
Page 57 and 58: Criteria C 2 - Company Responsibili
Page 59 and 60: Selection of Facility Location for
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Preference Level Numerical Value
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5. ALTERNATIVES CONSIDERED FOR SPIN
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A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 Raw
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Udyog Pragati Subscription Form I/W
Page 71 and 72:
SL. NO. COURSE DAYS DATE COURSE LEA
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Apr-Jun.12 - the Nitie

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