you need to look into the HI6008 proposal and the survey questionnaire within it. The data needs to be collected for those survey questions (which are only few questions) and that data should be statistically analyzed by using SPSS software which can be downloaded from the following link.
http://www.hearne.com.au/Software/SPSS-Statistics-Family-by-IBM/Demos

A presentation needs to be prepared out of the business research proposal which has been prepared by you guys. The presentation should be well made with prezzi or power point or whichever software you want but it should be very presentable.

Student’s id:

Student name:

University name:

Introduction. 3

Demographic analysis: 3

Regression model 2: Brand satisfaction. 12

Conclusion. 20

References. 21

Appendix. 22

Situation of figures and tables

Figure 1: Ethnic differences among the participants. 5

Figure 2: The age-group of the participants. 5

Descriptive analysis: 6

Correlations. 7

Table 2: Correlation between satisfaction reflected products as well as with the variables. 8

Residuals Statisticsa. 11

Figure 3: residual normal curve in histogram.. 12

Table 7: correlation of regression model 2 (I & II). 15

Figure 4: histogram and normal curve fitting of the residuals. 21

# Introduction

The analysis of the customer satisfaction had two main variables for Woolworth, Preston. The satisfaction of the customers might be evaluated measuring the tangibility of the satisfaction as well as the intangible behaviour of the elements. The analysis of the participants review regarding their satisfaction of Woolworth had become the most priority due to understand their perception on satisfaction. Additionally, it was also the objective of analysing the satisfaction using two models to understand the different metrics on their behaviour. The first model was a hybrid model such as

Y (Product satisfaction) = coefficient + B1 (coefficient) + B2 (coefficient)

Whereas the second model had the expression of

Y (Brand satisfaction) = coefficient + B1 (service) + B2 (range)

Both the equation had incorporated the error term for finding the non-linearity of the terms of the satisfaction.

## Figure 1: Ethnic differences among the participants

From the above diagram, we can see that Indian and Chinese people were the major customers as well as the participants in the Preston area (yellow: Chinese, red: Indian). Pakistani people were outnumbered by the Indian and the Chinese people in the region. However, the participation from the Pakistani could not be ignored as their presence was enough considerable as the key data towards evaluating their satisfaction of Woolworth’s in Preston. The below diagram showed that the majority of the respondents were of age group of 25-35. The old aged people such as 13.9% people had participated in the survey only whereas the young people of age group 18-24 had participated at the rate of 27.7%. The rest of the participants was of 36-48 age group.

## Descriptive analysis:

 Descriptive Statistics N Range Minimum Maximum Mean Std. Deviation Satisfaction of products 101 4.0 1.0 5.0 2.188 1.0071 Satisfaction of services 101 4.0 1.0 5.0 2.287 1.0520 Satisfaction of product safety 99 4.0 1.0 5.0 2.485 1.0138 Satisfaction of product return policy 100 4.0 1.0 5.0 2.770 1.1622 Satisfaction of brands in the stores 99 4.0 1.0 5.0 2.283 1.1252 Satisfaction of range of the products 99 4.0 1.0 5.0 2.101 1.0926 Valid N (listwise) 94

#### Table 1: Descriptive analysis of the customer satisfaction

The table 1 had depicted the descriptive analysis of the responses about the survey. The variables like satisfaction of the products sold by the store had seen the mean value of 2.188 with a deviation of 1. In this context, the entire scale of the survey was used by the participants as they had agreed highly as well as disagreed with the product quality of the company. In this context, it could be said that the overall product quality of Woolworths was at the satisfactory level of the customers from Preston. The services from the store in Preston had the similar view

of the customers as the mean value was 2.28. The deviation of the participants’ vote was only 1.05 between ranges of 4 of the scaled measurement. The product safety message from the company as well as from the representatives of the stores had been satisfied the customers in Preston as they had scored towards agreeing with the service. Additionally, the deviation of the participants’ view regarding the product safety was 1.01 whereas the full scale was used by the participants in the survey. Product return policy of the company was not such impressive as it was tallying at the neutral zone mainly. However, the participants voted their satisfaction for the brand and branded products in the stores in Preston area. The main product criteria of a store was the availability of huge range of the products. Woolworth had emerged as one of the best store in Preston area for availing huge ranges of products in its stores. Further, it was also found that the deviation of satisfaction among the participants was low and below the controlling limit of the satisfaction level of the customers.

## Correlations

Satisfaction of products Satisfaction of product safety Satisfaction of product return policy
Pearson Correlation Satisfaction of products 1.000 .507 .398
Satisfaction of product safety .507 1.000 .573
Satisfaction of product return policy .398 .573 1.000
Sig. (1-tailed) Satisfaction of products . .000 .000
Satisfaction of product safety .000 . .000
Satisfaction of product return policy .000 .000 .
N Satisfaction of products 98 98 98
Satisfaction of product safety 98 98 98
Satisfaction of product return policy 98 98 98

## Table 2: Correlation between satisfaction reflected products as well as with the variables

The product satisfaction of the and safety details had positive correlation depicting the participants’ view regarding the safety related matter as one of the most important issue for satisfying their desire. The returning policy of the company had positive but low correlation with each other as the policy to return a product was little confusing as well as complicated issue in Woolworth (Zikmund et al. 2012). However, the safety and return policy had positive relation with medium level correlation. Therefore, it could be analysed that products’ returning policies and safety related issues had some positive binding towards the customer’s perception as both of them were imbibed to the written format for them.

Regression model 1: Product satisfaction

 Model Summaryb Model R R Square Adjusted R Square Std. Error of the Estimate Durbin-Watson 1 .524a .274 .259 .8626 1.845 a. Predictors: (Constant), Satisfaction of product return policy, Satisfaction of product safety b. Dependent Variable: Satisfaction of products

### Table 3: Regression model

The above table showed the value of R2 where the predictability of the model was found to be as low as 27%. However, the value of R was medium. In the below table, the ANOVA analysis of the model was found where the F ratio was significant (Collis, & Hussey, 2013). The square if the regression and residual had a composite within the total numbers of the respondents. The significant F-ratio had stated that the alternative hypothesis of building satisfaction using the safety message and return policy of the products could test the positive side from the viewpoint of the customers.

ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 26.707 2 13.354 17.949 .000b
Residual 70.680 95 .744
Total 97.388 97
a. Dependent Variable: Satisfaction of products
b. Predictors: (Constant), Satisfaction of product return policy, Satisfaction of product safety

### Table 4: ANOVA analysis of regression model 1

Coefficientsa

Model Unstandardized Coefficients Standardized Coefficients t Sig. 95.0% Confidence Interval for B
B Std. Error Beta Lower Bound Upper Bound
1 (Constant) .762 .254   2.999 .003 .258 1.267
Satisfaction of product safety .409 .105 .416 3.898 .000 .201 .618
Satisfaction of product return policy .140 .093 .160 1.497 .138 -.046 .325
a. Dependent Variable: Satisfaction of products

### Table 5: regression equation of model 1

The above table showed the regression coefficient where the two variables of product satisfaction was measured. Safety measurement of the product for the customers had significant positive value from the participants whereas the return policy of the products had low significance among the participants’ perception. The regression equation of the model was as followed:

Y (CS) = .762 + .409 * product safety + .140 * return policy + .254

However, the equation showed that the satisfaction of the customers were not linear as there were significant errors present. Additionally, the value of the Durbin-Watson test provided the information of the hypothesis test where the significance of product satisfaction could be understood. In this context, the value of the Durbin-Watson test was more than the upper limit of the residuals (O’Leary, 2013). Therefore, the null hypothesis was not rejected as product satisfaction was not influenced by both the policy of returning and safety message. It also analysed that the product satisfaction had no auto correlated residuals that could be used as the time series value.

## Residuals Statisticsa

Minimum Maximum Mean Std. Deviation N
Predicted Value 1.311 3.507 2.163 .5247 98
Residual -2.2275 1.7306 .0000 .8536 98
Std. Predicted Value -1.624 2.561 .000 1.000 98
Std. Residual -2.582 2.006 .000 .990 98
a. Dependent Variable: Satisfaction of products

# Regression model 2: Brand satisfaction

 Correlations Satisfaction of brands in the stores Satisfaction of services Satisfaction of range of the products Satisfaction of product return policy Satisfaction of product safety Pearson Correlation Satisfaction of brands in the stores 1.000 .576 .594 .402 .582 Satisfaction of services .576 1.000 .585 .447 .467 Satisfaction of range of the products .594 .585 1.000 .400 .480 Satisfaction of product return policy .402 .447 .400 1.000 .589 Satisfaction of product safety .582 .467 .480 .589 1.000 Sig. (1-tailed) Satisfaction of brands in the stores . .000 .000 .000 .000 Satisfaction of services .000 . .000 .000 .000 Satisfaction of range of the products .000 .000 . .000 .000 Satisfaction of product return policy .000 .000 .000 . .000 Satisfaction of product safety .000 .000 .000 .000 . N Satisfaction of brands in the stores 94 94 94 94 94 Satisfaction of services 94 94 94 94 94 Satisfaction of range of the products 94 94 94 94 94 Satisfaction of product return policy 94 94 94 94 94 Satisfaction of product safety 94 94 94 94 94

## Table 7: correlation of regression model 2 (I & II)

Brand satisfaction showed that the supportive presence from the participants due to satisfaction gain from the services as well as the available ranges of the products in the store of Woolworth. The positive correlation of brand satisfaction with the variables indicated that the satisfactory outcome of the variables could provide positive viewpoints of the participants due to having satisfied viewpoint regarding other variables mainly (Davenport, 2013). The positive correlation behaviour of the variables with the brand satisfaction of the participants was the hints of consistent relationship between the service, availability of the products, safety message and return policy of Woolworth. The following table had shown us that the brand value could be predicted from the model 2 (I) by 43% while the II could predict 50% of the brand satisfaction. The Durbin-Watson value was 2.46, higher than the upper boundary of critical values. Thereby, the null hypothesis was not rejected here.

## Model Summaryc

Model R R Square Adjusted R Square Std. Error of the Estimate Durbin-Watson
1 .657a .432 .420 .8078
2 .713b .508 .486 .7603 2.467
a. Predictors: (Constant), Satisfaction of range of the products, Satisfaction of services
b. Predictors: (Constant), Satisfaction of range of the products, Satisfaction of services, Satisfaction of product return policy, Satisfaction of product safety

## c. Dependent Variable: Satisfaction of brands in the stores

### Table 8: Regression summary of model 2

The ANOVA analysis showed that model I had higher significant value on the brand satisfaction of the stores where the service and range of the products could make the significant difference of the sentiment of the customers. In this regard, the model II showed lesser significant value as the residuals were lesser consistent to each other.

 ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 45.169 2 22.584 34.608 .000b Residual 59.384 91 .653 Total 104.553 93 2 Regression 53.110 4 13.278 22.971 .000c Residual 51.443 89 .578 Total 104.553 93 a. Dependent Variable: Satisfaction of brands in the stores b. Predictors: (Constant), Satisfaction of range of the products, Satisfaction of services c. Predictors: (Constant), Satisfaction of range of the products, Satisfaction of services, Satisfaction of product return policy, Satisfaction of product safety

### Table 9: ANOVA analysis of regression model 2

The following table showed the coefficients of the models where the t test of the regression model was significant for the model I. the regression equation was prepared from the test to predict the brand satisfaction of the participants as followed:

Y (BS) = .606 + .355* SS + .382 * range +.21

The model could predict the brand satisfaction as per the service and products’ availability in the stores at Preston.

The model II showed that inclusion of safety and the return policy of the company in evaluating the brand satisfaction of the customers were failed as the low t test value did not support the alternative hypothesis (Bryman & Bell, 2015). Therefore, in this case, the null hypothesis was tested positive. The equation of prediction through this model was as followed:

Y (BS) = .2 + 267 (Range) + .284 (services) -.29 (Return) + .355 (PS) + .239

The negative coefficient of return policy of the product in Woolworth had shown the negative impact on the brand satisfaction due to the inclusion of return policy of the company for having some controversy regarding the specific service. The consistency of the residuals had shown that the research might get such recognition for brand satisfaction among the customers at Preston.

 Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. 95.0% Confidence Interval for B B Std. Error Beta Lower Bound Upper Bound 1 (Constant) .606 .210 2.892 .005 .190 1.022 Satisfaction of services .355 .099 .348 3.571 .001 .158 .552 Satisfaction of range of the products .382 .095 .390 4.009 .000 .193 .571 2 (Constant) .200 .239 .838 .404 -.275 .676 Satisfaction of services .267 .099 .262 2.708 .008 .071 .463 Satisfaction of range of the products .284 .094 .290 3.026 .003 .097 .470 Satisfaction of product return policy -.029 .089 -.031 -.323 .747 -.206 .149 Satisfaction of product safety .355 .103 .339 3.438 .001 .150 .559 a. Dependent Variable: Satisfaction of brands in the stores

### Table 10: correlation between the independent and depended variables of model 2

The return policy of the company had lesser influence on the brand satisfaction as it had high t test value in its hand.

 Excluded Variablesa Model Beta In t Sig. Partial Correlation Collinearity Statistics Tolerance 1 Satisfaction of product return policy .117b 1.309 .194 .137 .771 Satisfaction of product safety .324b 3.711 .000 .364 .716 a. Dependent Variable: Satisfaction of brands in the stores b. Predictors in the Model: (Constant), Satisfaction of range of the products, Satisfaction of services

### Table 11: External variables statistics of model 2

 Residuals Statisticsa Minimum Maximum Mean Std. Deviation N Predicted Value 1.048 4.584 2.191 .7557 94 Residual -1.5561 3.0332 .0000 .7437 94 Std. Predicted Value -1.513 3.166 .000 1.000 94 Std. Residual -2.047 3.990 .000 .978 94 a. Dependent Variable: Satisfaction of brands in the stores

# Conclusion

From the above analysis, it could be concluded that the model 1 and 2 both had tested the alternative hypotheses positively due to the positive responses from the participants. However, there was chance of accepting the null hypothesis as at some point of view, customer satisfaction and brand satisfaction could not be evaluated with the used variables. In those cases, some more variables must be evaluated for better measurement as well as to test the hypotheses. It was also seen from the analysis that the main variables in both the models had significant influence to predict the overall satisfaction of the customers through product and brand.

# References

Collis, J., & Hussey, R. (2013). Business research: A practical guide for undergraduate and postgraduate students. Palgrave macmillan

Davenport, T. H. (2013). Process innovation: reengineering work through information technology. Harvard Business Press.

Bryman, A., & Bell, E. (2015). Business research methods. Oxford university press.

Zikmund, W., Babin, B., Carr, J., & Griffin, M. (2012). Business research methods. Cengage Learning.

O’Leary, Z. (2013). The essential guide to doing your research project. Sage.

# Appendix

Questionnaire

1. State the ethnic group you belong to

Indian

Pakistani

Chinese

2. State the age group you belong to

18-24

25-35

36-48

49-62

Scale: 1 = Highly agreed …… 5 = Highly disagreed

3. Satisfaction of the products offered in Woolworth’s stores

4. Satisfaction of the services offered in Woolworth’s stores

5. Satisfaction of the product safety offered in Woolworth’s stores

6. Satisfaction of the product return policy offered in Woolworth’s stores

7. Satisfaction of the Woolworth’s brands in the stores

8. Satisfaction of the Woolworth’s range of the products

The Effectiveness of Product Satisfaction towards 3 Major Ethnic Groups of Customers

A case study on Woolworths-Preston

Research topic and its significance

• The Effectiveness of Product Satisfaction towards 3 Major Ethnic Groups of Customers”
• Conflict between values provided to the international and local ethnic group is observed in many cases in the business.
• Diversification strategy applied by the firms in delivering the needs of the customers
• Woolworths’s Preston has three predominant ethnic groups as its customers

Research topic and its significance

• The tactics of Woolworths for satisfying the ethnic group such as Indian, Chinese and Pakistani in the area are diversification
• The quality of the product was a part of customers’ satisfaction program
• The satisfaction of the customers was the main issue for the company to sustain its business and industry position in number 1 in Australia Eich (2014).

Research Questions

• Are there any strategies implemented to attract Chinese, Pakistani and Indian Customers to Woolworths-Preston?
• What product ranges do those most frequently visiting ethnic groups prefer?
• Does Woolworths-Preston provide the right level of services in its product range to the above mentioned 3 major ethnic groups of customers?

Research Questions – explained

• Local ethnic groups had their own cultural background – therefore, Woolworths had to invent different strategy too
• The product availability in the stores of Preston were depended on the taste of the ethnic group.
• The range of the products had some types of impact on drawing the customers
• The service adequacy was anther factor for the store to retain the customers

Methodology

• Selected philosophy to conduct this research was positivism
• Past review of the theoretical research was necessary for this study to compare the current situation of customer satisfaction in Woolworths
• The approach was deductive to deduce the potential gap of the past reviews
• Inferential and descriptive analysis – both were selected to conduct the research

Data collection and analysis

• Survey was conducted in online mode to gather primary data
• Customer satisfaction of Preston area about Woolworths was predicted using variables like product satisfaction, availability service satisfaction etc. (Jeston & Nelis, 2014).
• The brand satisfaction was measured for the company to understand the satisfaction of the customers in different parameters
• Regression analysis of satisfaction was the predictive model for this study

Data analysis

• Data analysis was conducted using the two models to understand the materiality as well as the tangibility of the satisfaction in the viewpoint of the customers (Davenport T. H. (2013)
• The first one had considered to assess the product satisfaction whereas the second one had selected to chose service and availability of the products.

Regression model and results

• The model 1 elaborated that safety message and return policy of the products cannot predict the customers’ product satisfaction
• However, this model found that customer cannot be satisfied with the existing policies (O’Leary 2013)
• The model 2 has predicted that the brand satisfaction could be derived using the range of the products’ as well as services from the representatives
• The model 2 had provided us the predictive value of brand satisfaction regarding Woolworths’ stores in Preston

Reference list

• Davenport, T. H. (2013). Process innovation: reengineering work through information technology. Harvard Business Press.
• Jeston, J., & Nelis, J. (2014). Business process management. Routledge
• O’Leary, Z. (2013). The essential guide to doing your research project. Sage
• Eich, E. (2014). Business not as usual. Psychological Science25(1), 3-6.