Contemporary Business Studies - Academy of Knowledge Process ...

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International Journal of Contemporary Business Studies Vol: 3, No: 1. January, 2012 ISSN 2156-7506 Available online at http://www.akpinsight.webs.com RESEARCH METHODOLOGY A pre-tested questionnaire was administered to the randomly selected people from the cities Cuttack, Bhubaneswar, Odisha, India. Personal interviews with the help of the pre-tested interview schedule were taken. Besides, personal observation was done wherever necessarily applicable. A pilot survey was conducted and the questionnaire was improved in that light. A structured questionnaire was used as a data collection tool. The sample includes male and female from different occupation, age and income group. In order to confine our study, a field survey was conducted across the selected segment of the cities and the respondents were selected randomly; they were approached to be included in the survey. For the sake of convenience the study concentrated on interview, questionnaire-survey method. a) Sample Design: random sampling was used keeping the target segment in mind. b) Sample size: 243 people were approached but the data could be collected from 200 respondents only. c) Data collection Period: The period of the data collection is limited to only a 3 -week period in September and October, 2011. d) Data collection method: A structured questionnaire was prepared and requisite information were collected through personal interviews. e) Tools and techniques used: Multiple regression analysis, Ranking method, Kendalls coefficient, Spearman’s rank correlation and percentage method. ANALYSIS AND INTERPRETATION 1. Ranking of different brands of fairness cream Different brands of fairness creams are ranked on the basis of factors like Brand image, Promotional Offers, Advertisement and Varieties. Table - 2 has been prepared on the basis of the responses gathered from the majority group of respondents. Table-2: Ranking of different brand BRAND Fair & Lovely Fair ever Fair Glow Fair and Handsome Dream Fairness COMPANY HUL Cavin kare Godrej Emami Ponds Factors Rank Brand image (x 1 ) 1 5 2 4 3 Promotional Offers (x 2 ) 2 1 5 4 3 Advertisement (x 3 ) 2 1 4 5 3 Varieties (x 4 ) 1 5 4 3 2 In order to know the relation in between x1, x2, x3, x4, we have worked out Spearman’s Correlation coefficient (Rank correlation coefficient) pair wise. R x1x2 = 1-(6∑D 2 / N 3 -N) = 0.3, R x1x3 = 1- (6∑D 2 / N 3 -N) = 0.05, R x1x4 = 1- (6∑D 2 / N 3 -N) = 0.7 R x2x3 = 1- (6∑D 2 / N 3 -N) = 0.9, R x2x4 = 1- (6∑D 2 / N 3 -N) = 0, R x3x4 = 1- (6∑D 2 / N 3 -N) = 0.1 R x2x3 = the correlation coefficient between Promotional Offers and Advertisement is maximum (0.9); it shows a very high degree of positive correlation in between the said variables. 48 Copyright © 2012. Academy of Knowledge Process
International Journal of Contemporary Business Studies Vol: 3, No: 1. January, 2012 ISSN 2156-7506 Available online at http://www.akpinsight.webs.com Interpretation: It is observed that Fair & Lovely is ranked as the best brand, Fair ever is ranked first for its promotional offers and advertisement and Fair & Lovely stands first for its varieties. The correlation coefficients between the brand image and the varieties, promotional offer and advertisement are more than 0.5, so the variables are highly positively correlated. 2. Reason of looking for a different brand The reason of looking for a new brand of fairness cream is correlated with the quality of new brand, price, current fashion and new in the market. Here the basic interest is to find out the weightage of the independent variables (quality of new brand, price, current fashion and new in the market) on the predictor, the percentage of looking for a different brand of fairness cream by using the Multiple Regression technique. Let Y be the dependent variable = the percentage of looking for a different brand B = the coefficient of determinant (a constant value) X 1 = Quality of new brand X 2 = Price X 3 = Current fashion X4 = New in the market Y = B 0 + B 1 X 1 + B 2 X 2 + B 3 X 3 + B 4 X 4 Step-by-Step Multiple Regression Table-3: Variables Entered/Removed Model Variables Entered Variables Removed Method 1 X4,X3, X1, X2 Enter a All requested variables entered. b Dependent Variable: Y Table-3 shows us the order in which the variables were entered and removed from our model. We can see that in this case three variables were added and none were removed. Table- 4 : Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .733 .537 .450 1.92380 a Predictors : (Constant), X4, X3, X1, X2 Adjusted R Square in table-4 value tells us that our model accounts for 97.8% of variance in the frequency of visits and it signifies that it is a very good model. Table-5: Correlations Y X1 X2 X3 X4 Y 1.000 .629 .558 .026 -.003 X1 .629 1.000 .416 .000 .26 X2 .558 .416 1.000 .392 .412 X3 .026 .000 .392 1.000 0.63 X4 -.003 .26 .412 .63 1.000 ** Correlation is significant at the 0.01 level (2-tailed). Table-5 gives details of the correlation between each pair of variables. There is a very good correlation between the criterion and the predictor variables. The values here are acceptable. 49 Copyright © 2012. Academy of Knowledge Process
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