• November 29, 2015
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# Chapter five; Results

In order to facilitate the analysis of these missing factors, an Regression Analysis Of Variance (ANOVA) technique is utilized to enable discussion of viewpoints with regard to consumer behaviour  and its relationship with marketing and its impact, (Tenenhaus, et al,2005).

# Regression Analysis

ANOVA has been used here to the variety of interval data and to understand the inferences about the population and their means and differences.

In ANOVA technique, the test statistic is F distributed with k-1 and n-k degree of freedom if the response variable is normally distributed. The purpose of calculating F statistic is to determine whether the value of SST (Sum of square for treatments) is large enough to reject the null hypothesis, and if SST is large then F is large. A large F indicates that mostly variation in the response variable is due to the treatments rather than to random causes. We reject the hypothesis only if,

F > F α, k-1, n-k

where

SST

MST = ——— MST – Mean Square for Treatments

k – 1

SSE

MSE = ———            MSE – Mean Square for Error

n – k

# Test Hypotheses

Ho: There is no direct relationship between consumer behavior and marketing

H1: Understanding Consumer behavior positively impacts on an organization

 Levene Statistic df1 df2 Sig. 1,721 4 212 216 Test of Homogeneity of variance

If the Levene’s Test (test of Homogeneity of variance) indicates a significant value “Sig.” less than 0.05, then the variances are significantly different. If not, and the “Sig” is greater than 0.05, then the variances are not significantly different and therefore considered equal. Table below represents the Homogeneity of consumer choice for Chinese clothing industryand marketing behaviour where the “Sig” is greater than 0.05. Since there is  lack of  significance of the Homogeneity of variance,Ho is rejected. As the test has indicated significant differences between mean scores, the ANOVA is used to explore differences between the individual group means.

 Sum ofSquares df Mean Square F Sig. Between Groups 16,532 4 5,198 4,001 ,021 Within Groups 316,466 212 1,498 Total 332,654 216 One Way ANOVA analysis of variance

# Test of Homogeneity of Variances

The ANOVA results indicate significant difference level between the two groups is less than 0.05, thereby indicating the outcome of Consumer choice for clothes in the Chinese clothing industry as illustrated in Table below. In instances where the ANOVA is greater than 0.05, it is acceptable that there are few or no differences between the groups. It is possible to observe significant differences between groups during post-hoc comparisons when ANOVA significance is less than 0.05, as indicated on Table below by the asterisk, which provides the post-hoc comparisons of Table below

 (I) Q1(J) Q1 MeanDifference(I-J) Std. Error Sig. 95% Confidence Interval Lower Bound Upper Bound 2,001,003,004,00 -,44467-,99891*-,68267 ,33211,32333,73562 1,000,0341,000 -1,2907-1,7819-2,7431 ,4212-,01731,3706 2,001,003,004,00 ,41456-,35465-,15142 ,31113,17448,71120 1,000,0741,000 -,4112-,9467-2,0725 1,2706,01701,5795 3,001,002,004,00 ,88951*,45475,20323 ,32101,17448,71566 ,033,0651,000 ,0163-,0370-1,8215 1,6809,94672,0462 1,002,004,003,00 ,67617,24142-,21333 ,76181,71230,72576 100010001000 -1,5716-1,7715-2,1472 2,64212,07451,7205 * mean difference significant at the .05 level: Post-Hoc Comparisons table

Particular aspects of the questionnaires, specifically the 23 individual questions and 7 group questions, for a total of 25 questions were analysed using ANOVA in order to determine the differences between responses concerning ages and locations. Based on the ANOVA results, there is no significant difference present between the singular and group questions scores, with each having a mean score of nine. It is important to note that interpretation of the results must include consideration of the qualification set forth if a different variable set is used, which could very well result in an entirely different outcome.

Throughout the subsequent analysis, any question with a significance level above the established homogeneity (p>0.05) will be the primary focus, with those questions having a significance level below the established homogeneity (p<0.05) will be secondary.

The variables with significant p-values prompted further analysis with regard to age groups and location in order to determine whether these have any bearing on the overall data and behaviour analysis. This further analysis produced an unexpected result: the inclination toward Chinese clothes over the international options. This inclination is indicated by the interpretation of numerical numbers for question ‘clothes buying from Chinese manufacturers and shops and hypothesis are that this is due to increased media exposure to Chinese shops and brands. Other mitigating factors may include opinions of international brand origins, the innovation of the available designs, quality of artisanship, and other aspects. As mentioned previously, a portion of the respondents indicated preference for Chinese products based on their unique Chinese features. These features may instil a sense of national pride or familiarity that indicates an urge to cultivate and communicate individual identity.

# Inclination towardChinese shops and Chinese manufacturers

This preference for Chinese products was seen more prevalently among those respondents above the 30 age range. When compared to younger respondents, it is perceived that national association is more definite in the older consumers than in the younger, indicating a potential shift in brand preference through life progression.

By comparison, the international shop perceptions provided inconclusive results and registered insignificant numbers. This was also true for the results regarding concern over family and friends’ opinions and influences on buying decisions, as well as the patterns demonstrated in past purchasing decisions and their influences on present and future selections. The attendance of fashion shows and media influence were, conversely, highly influential and considered to be avenues for research on emerging trends and arenas for further individual exploration, as well as unique style development.

# Uniqueness of Style

These findings are supported by literature, indicating that more mature women prefer fashionably edgy apparel in order to provide and support their established individual identities while maintaining preferred comfort levels. Comfort was secondary to uniqueness in younger consumers, likely due to their still identifying a preferred individual style that allows for unique personality while still conforming to expectations. Cost is, again, a mitigating factor in the final decision making, and this is true at all age levels, with some consumers preferring to use the images of name brand, high prices articles as a means of inspiration when making more affordable purchase decisions.

# Impact of Media

Magazines, fashion catalogues, and websites have been indicated to be the preferred primary source of media influence in the clothing industry. This is likely due to fashion conscious consumers being the targeted demographic for advertising and media surrounding the industry. Younger consumers appear to be more influenced by media, again likely due to not having established individual preferences and identities, where older consumers are less swayed due to already having identified personal preferences and established brand loyalty.

# Design Across the Market

The preference of younger buyers to purchase generic clothes from non-branded outlets indicates that the t age set is of the opinion that there is a lack of design variation in across the market, which enables the generic brands to be acceptable among their particular circles. The ANOVA results support this hypothesis, indicating that there is a general perception that there is extensive similarity of design across market participants. This lends support for the purchase of generic clothes, as indicated by the post-hoc comparisons, which show no significant difference across age groups with quality and price being the primary motivating factors, ( Fatma, 2006)

The definition of “buying clothes” varied from respondent to respondent, with potential definitions including comfort (mean 5.22) and everyday clothing (mean 5.19) with the older respondents more inclined toward comfort over fashion. Having comfort as the primary influence when selecting garment purchases becomes more evident as the respondent age increases, with mature women (age 45+) nearly universally selecting this as the primary factor for fashion consumerism. This would indicate that a similar study conducted with older participants would potentially net opposite results from those found here.

Unlike age, location did not appear to significantly influence purchase decisions within the Chinese sample. Most of the variance in group of mean is not possible to explain statistically across different cities, as the variance is homogeneous in most of the cases,

# Suggestions for future work

1. A study focusing on how subjective norms affect consumer behaviour as the findings of this study indicate that this was ranked low on the scale of influence.
2. Further study with endogenous variables (intention and behaviour) has the potential to determine more effectively the relationship between behaviour control and intention in the consumer behaviour pattern.
3. Studies on the older and more mature group of consumers (age 45+) has the potential to create previously untapped niche markets and opportunities for the industry, enabling better marketing toward this demographic.
4. Specific brand study with relation to the consumer behavior may indicate an overall preference or crowd mind.

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