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Consumer Decision-making Styles:
Comparison Between
Shanghai and Hong KongUniversity Consumers
A Consumer Styles Inventory Approach
BY
Chan Hoi Yee, Bertha02005174
China Business Studies Option
A H D P j t S b itt d t th
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A H D P j t S b itt d t th
Acknowledgements
I would like to give my heartiest thanks to my supervisor Dr. Shi Yi Zheng who has
sacrificed a lot of his valuable time for guiding me in doing this honor project,
suggesting precious advice, pointing out and correcting my mistakes. He is very
patient in answering and explaining my questions all the time. I really have learnt a lot
from him.
In addition, I would like to express my sincere thanks to my dearest friends, Mr. Peter
Wong and Miss Susanna Wong, for squeezing lots of time for helping me in
conducting survey.
Also, I would like to thank my family and friends who always gave me support and
encouraged me when I feel depressed in doing the project.
Last but not least, I would like to thank all the teachers in the Hong Kong Baptist
University who teach me a lot about marketing knowledge in the past three years.
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Abstract
Consumers use a variety of decision-making styles. This study investigates
decision-making styles of consumers in Shanghai and Hong Kong by analyzing the
Consumer Style Inventory (CSI), which is administered to 150 Shanghai and Hong
Kong university consumers respectively. Factor analysis is adopted to develop the
CSI inventories.
Findings indicate that six types of decision-making styles and fifteen statements are
valid and reliable in Shanghai, whereas five types of decision-making styles and
twenty statements are valid and reliable in Hong Kong. Significant differences can be
found in the dimension of quality conscious, brand conscious, fashion conscious and
shopping carefulness. Business implications, which address the above findings, are
provided for marketers in the following section. Limitations of this paper are the final
chapter.
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Table of Contents
Content Page
Acknowledgements ii
Abstract iii
Chapter 1. Introduction1.1 Background Information 11.2 Research Problem Development
1.2.1 Why Shanghai vs. Hong Kong? 11.2.2 Why University Students? 2
1.3 Research Objectives 3
Chapter 2. Literature Review2.1 Historical Researches on Decision-making Styles 42.2 The Consumer Style Inventory (CSI) 4
2.3 Application of CSI Across Cultures 6
Chapter 3. Research Methodology3.1 The Sample 73.2 Instrument 73.3 Data Collection Method 83.4 Data Analysis Method 8
Chapter 4. Hypothesis Development4.1 Differences in Brand Consciousness and Price Consciousness 104.2 Differences in Fashion Consciousness and Confusion by
Overchoice11
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Chapter 7. Limitations7.1 Generality of Consumer Characteristics 287.2 Limitation of the Sample 287.3 Limitation of Culture and Economic Background 29
Chapter 8. Conclusion 30
Chapter 9. References 31
Chapter 10. Appendix 3510.1 Explanation of the eight factors loading by Sproles and Kendall 36
10.2 Tables 3810.3 Questionnaires 4710.4 SPSS Outputs 58
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Chapter 1. Introduction
1.1 Background Information
Decision-making is more complex and even more important for consumers today than
in the past. Consumers are besieged by advertising, news articles, and direct mailings
that provide an abundance of information, much of it with mixed messages. In
addition, increases in the number and variety of goods, stores, and shopping malls,
and the availability of multi-component products and electronic purchasing
capabilities have broadened the sphere for the consumer choice and have complicated
decision making [Hafstrom, Chae, and Chung, 1992].
Profiling consumers decision-making styles focuses on studies of the majority of
consumer interest (eg, Bettman, 1979; Sproles, 1985; Thorelli, Becker, and Engeldow
1975; WestBrook and Black, 1985). Consumer affairs specialists use such profiles to
understand consumers shopping behaviour, while advertisers and marketing
researchers use them to segment the consumers into various niches for product
i i i [S i i d A d 1993]
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colonization for a long time. Culturally, both cities have shared modern and traditional
characterizations. They both are international metropolises that have much
international links. However, there are something different. For example, number of
brothers and sisters, source of income, source of information and culture.
Comparing between these two cities can help companies formulating marketing
strategies. For those companies who have only invested in Hong Kong and have
interest to enter into the Shanghai market, they can study the difference and
similarities between these two cities and then formulate an entering strategy for
Shanghai based on the existing marketing strategy for Hong Kong, and vice versa.
1.2.2 Why University Students?
The university students market is quite large. According to the statistics, there are
189,400 university students in Hong Kong in 2004, amounting about 11.5% of the
educational population [Hong Kong Census and Statistics Department, 2004]. And
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people acquire skills, knowledge, and attitudes relevant to their functioning as
consumers in the marketplace [Ward, 1972]. Socialization usually takes place within
the family and may shape consumer patterns. In this way, it may affect not only
present but also future consumer well-being.
1.2 Research Objectives
Although the CSI research is widely conducted in different nations, few of it is related
to Chinese society, related to the comparison between Hong Kong and Shanghai, and
focused on universities students.
There are three main objectives in this paper:
1. To investigate the decision-making style of Shanghai universities consumers by
purifying the items of CSI.
2. To investigate the decision-making style of Hong Kong universities consumers
b if i h i f
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Chapter 2. Literature Review
2.1 Historical Researches on Decision-making Styles
Consumer-interest researchers have long been interested in identifying the underlying
decision styles of shoppers. For example, consumers are identified as economic
shoppers, personalizing shoppers, ethical shoppers, apathetic shoppers [Bellenger and
korgaonkar, 1980; Darden and Reynolds, 1971; Stone, 1954], store-loyal shoppers
[Moschis and Gorge, 1976; Stephenson and Willett, 1969], recreational shoppers
[Bellenger and Korgaonkar, 1980; Stephenson and Willett, 1969], convenience
shoppers [Korgaonkar, 1984; Stephenson and Willett, 1969; Williams et al., 1978],
price-oriented shoppers [Korgaonkar, 1984; Stephenson and Willett, 1969; Williams
et al. 1978], brand-loyal shoppers [Jocoby and Chestnut, 1978; Moschis and Gorge,
1976], name-conscious shoppers [Darden and Ashton, 1974-75], fashion shoppers
[Lumpkin, 1985], brand conscious shoppers [Korgaonkar, 1984] and impulse
shoppers [Gehrt and Cater, 1992]. These classifications have provided a number of
measuring methods for the marketers to segment the general public in the consumer
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consumer choices. Broadly speaking, there are three types of approaches in studying
consumer decision-making styles: the psychographic/lifestyle approach, which
identifies hundreds of characteristics related to consumer behavior; the consumer
typology approach, which classifies consumers into several types; and the consumer
characteristics approach, which focuses on different cognitive dimensions of
consumer decision-making. For a review of these different approaches, see Sproles
and Kendall [1986].
Building on the literature related to consumer decision-making in the field of
marketing and consumer studies [Maynes, 1976; Miller, 1981; Sproles, 1979; Thorelli,
Becker and Engledow, 1975], Sproles [1985] identified nine decision-making style
traits and developed a 50-item instrument using the consumer characteristics approach.
Using data collected from 111 undergraduate women in two classes at the University
of Arizona and employing a factor analysis technique, Sproles [1985] found that six
out of the nine traits were confirmed to be present.
In a later study, Sproles and Kendall [1986] used a similar approach with a slightly
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1. Perfectionistic and high-quality conscious consumer,
2. Brand conscious and price equals quality consumer,
3. Novelty and fashion-conscious consumer,
4. Recreational and hedonistic consumer,
5. Price conscious and value for money consumer,
6. Impulsive and careless consumer,
7. Confused by over-choice consumer, and
8. Habitual and brand-loyal consumer.
Appendix 10.1 (page 35) shows the explanations of the eight factors loading by
Sproles and Kendall. It is a pretty good benchmark for us to explain our data analysis
result.
2.3 Application of CSI Across Cultures
The applicability of the CSI has been investigated across several cultures [Alice and
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Chapter 3. Research Methodology
3.1 The Sample
The sample size is 300, 150 of Shanghai undergraduate students and 150 for Hong
Kong undergraduate students.
3.2 Instrument
A questionnaire based on the exploratory studies of Sproles [1985] and Sproles and
Kendall [1986] was used to measure consumer decision-making styles in Hong Kong
and Shanghai. The questionnaire was translated into Chinese. Some mainland Chinese
and Hong Kong students and professors reviewed the translations. This ensured that
idiomatic or colloquialistic wording was minimized [Douglas and Craig, 1983;
Parameswaran and Yaprak, 1987].
The questionnaire is divided into two parts. The first part contains the forty
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3.3 Data Collection Method
A non-probability sampling survey method is conducted in the universities in Hong
Kong and Shanghai during March 2005. I did the survey in Hong Kong by myself.
The survey in Shanghai universities were done by my relatives who live in Shanghai,
as it is prohibited for the non-Chinese residents to conduct survey without
authorization by the local government and due to the huge transportation fee occurred.
3.4 Data Analysis Method
SPSS was used to analyze the data collected.
Firstly, frequency was used to display the distribution of consumers demographic
background and personal information.
Secondary, CSI for Hong Kong and Shanghai will be developed in two steps
following the method used by Sproles [1985] and Sproles and Kendell [1986].
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and Kendall [1986].
Thirdly, comparison between Shanghai and Hong Kong was done by comparing the
CSI and by calculating the T-Test (by taking the mean score for each of the factor of
CSI).
The negatively worded items had been reversed before the data analysis proceeded, in
order to analyze the data easily. The scores of question 5, 7, 20, 22, 24, 31, 32 and 40
had been reversed.
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Chapter 4. Hypothesis Development
We expect that Shanghai and Hong Kong university consumers will differ in terms of
brand consciousness, fashion consciousness, price consciousness and confusion by
overchoice, based on the explanations as follows.
4.1 Differences in Brand Consciousness and Price Consciousness
Since the late 1970s, one-child-per-couple campaign was taken to curtail the
population explosion. As Chinese per capita income has risen and fertility declined,
Chinese parents' love and money have focused on a single child, resulting in unique
social and economic implications such as the perilous 4-2-1 indulgence: four
grandparents and two parents indulging one child. Many of these children are
self-centered and demand material luxuries from their parents [Baker 1987]. While in
Hong Kong, government did not practice One Child Policy. Many families had two
to four children in the 1980s [The International Encyclopedia of Sexuality: Hong
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H1: Shanghai university consumers are more brand consciousness than Hong
Kong university consumers.
H2: Hong Kong university consumers are more price consciousness than
Shanghai university consumers.
4.2 Differences in Fashion Consciousness and Confusion by Overchoice
Hong Kong was a British colony for over 150 years (1842-1997). Citizens were
educated to apprehend Western values. Hong Kong people have long been exposed to,
and fast to learn from, Western culture [Alex, Guijun, Fuan, Nan, 2003]. Nowadays,
Hong Kong people are accustomed to, and want to continue, this lifestyle: Their
aversion to the return of sovereignty to China reflected a fear of lifestyle discontinuity
[Lau and Kuan, 1989]
China adopted an open door policy in 1979; however, the country is not fully open to
l d h hi i d d ill i h
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1996]. When the movie Titanic broke the box-office records across Chinese cities in
1997, Chinese officials expressed their concerned that Western movies could be a
Trojan horse aimed at speeding up the American cultural invasion of China [Platt,
1998].
As Hong Kong universities consumers always and easily come into contact with
information than Shanghai, and Hong Kong has a longer history involvement of
Western values, we expect that university consumers in Hong Kong are more fashion
conscious and more confused by overchoice than Shanghai university consumers.
H3: Hong Kong university consumers are more fashion consciousness than
Shanghai university consumers.
H4: Hong Kong university consumers are more confused by over choice than
Shanghai university consumers.
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Chapter 5. Research Findings and Analysis
5.1 Personal Information of the 300 samples from Shanghai and Hong Kong
5.1.1 Shanghai
Among the 150 university student respondents in Shanghai, 44% (66) were male and
56% (84) were female. Most of the respondents have no sibling (125, 83.3%), few
respondents have two to three siblings (25, 16.7%), while no respondents have more
than three siblings. A majority of them viewed parents as their only income source
(111, 74%), while few of them had multiple income sources (39, 26%). Over one-third
of them paid 1001-1500 as their cost of living (52, 34.7%); then 501-
1000 (48, 32%); 500 (26, 17.3%); and 1501 (24, 16%). Finally,
overwhelming of them viewed television (125, 83.3%), Internet (119, 79.3%),
magazine (113, 75.3%) and family and friends (96, 64%) as their information source.
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(114, 76%), Internet (103, 68.7%), magazine (102, 68%) and newspaper (96, 64%) as
their information source.
---------------------------------------------------------------------------------------------
Table 1: Personal Information of the 300 samplesfrom Shanghai and Hong Kong (Page 39)
---------------------------------------------------------------------------------------------
5.1.3 Comparison
Comparing the characteristics of the two sets of respondents in Hong Kong and
Shanghai, there were some similarities and differences identified.
Similarities
1. The cost of living in Hong Kong and Shanghai are very similar.
2. The information source in Hong Kong and Shanghai are very similar.
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5.2 Decision-making styles of Shanghai university consumers
The 40 items of the consumer decision-making scales of Shanghai were subjected to
principal components analysis (PCA) using SPSS. Prior to performing PCA the
suitability of data for factor analysis was assessed. Inspection of the correlation matrix
revealed the presence of many coefficients of 0.3 and above. The Kaiser-Meyer-Oklin
value was 0.608 [Kaiser, 1970, 1974] and the Barletts Test of Sphericity [Bartlett,
1954] reached statistical significance, supporting the factorability of the correlation
matrix.
Principal components analysis revealed the presence of 12 components with
eigenvalues exceeding 1, explaining 15.113%, 12.663%, 8.073%, 6.216%, 5.901%,
5.401%, 4.747%, 3.783%, 3.310%, 3.055%, 2.853% and 2.686% of the variance
respectively. An inspection of the screeplot revealed a clear break after the six
components. Using Catells [1996] scree test, it was decided to retain six components,
Varimax rotation was performed. The cross-loading items and items that had a factor
loading value less than 0.4 were removed. The rotated solution (presented in
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The interpretation of the six components was consistent with previous research on the
CSI, with Novelty-fashion consciousness items loading strongly on Component 1,
Perfectionistic and high-quality consciousness items loading strongly on Component
2, Habitual and brand-loyal consumer orientation items loading strongly on
Component 3, Impulsive and careless consumer orientation items loading strongly
on Component 4, Price consciousness and value for money orientation items
loading strongly on Component 5 and Brand consciousness and price equals
quality items loading strongly on Component 6. The results of this analysis support
the use of CSI as separate scales.
---------------------------------------------------------------------------------------------
Table 2: Factor Loadings and Construct Reliability of Shanghai CSI (Page 41)
---------------------------------------------------------------------------------------------
5.3 Decision-marking styles of Hong Kong university consumers
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eigenvalues exceeding 1, explaining 4.902%, 3.565%, 2.931%, 2.367%, 1.967%,
1.568%, 1.491%, 1.332%, 1.281%, 1.241%, 1.141%, 1.130%, 1.064% and 1.015% of
the variance respectively. An inspection of the screeplot revealed a clear break after
the five components. Using Catells [1996] scree test, it was decided to retain five
components, Varimax rotation was performed. The cross-loading items and items that
had a factor loading value less than 0.4 were removed. The rotated solution (presented
in Appendix page 107) revealed the presence of simple structure [Thurstone, 1947],
with all components showing a number of strong loadings, and all variables loading
substantially on only one component. The five factor solution explained a total of
53.140% of the variance, with the five components contributing 13.82%, 10.98%,
10.22%, 10.10% and 7.99% respectively.
The interpretation of the five components was consistent with previous research on
the CSI, withBrand consciousness and price equals quality items loading strongly
on Component 1, Perfectionistic and high-quality consciousness items loading
strongly on Component 2, Novelty-fashion consciousness items loading strongly on
C 3 H bit l d b d l l i t ti it l di
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5.4 Comparison of decision-making styles between Shanghai and Hong Kong
universities consumers
5.4.1 Number of Dimensions
The identified dimensions of CSI are very similar for university consumers in
Shanghai and Hong Kong. Shanghai has six and Hong Kong has five dimensions.
With the same dimensions: (1) fashion conscious, (2) high-quality conscious, (3)
brand-loyal, (4) price conscious, and (5) brand conscious. The dimension of
Impulsive and careless was found only in Shanghai CSI.
There is no cross-loading item between Shanghai and Hong Kong CSI. So, the results
support the use of CSI as separate scales.
Impulsiveness is not identified as a dimension of consumer decision-making styles
for the Hong Kong university consumers. The reasons are as follows.
Impulsive shopping is opposite to habitual shopping [Fan and Xiao, 1998], in order to
fi d h h h i h h di i f i l i hil d
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did not load significantly on any factor for the Hong Kong sample. This may be
caused by differences in the interpretation of the question asked in different languages.
However, it is also possible that Shanghai university consumers are loyal to some
brands but at the same time, they are still facing confusion because there are still
many new brands invading into their minds every day. As noted earlier, as more and
more consumer products are becoming available in Shanghai, Shanghai university
students may feel confused and have to try these new brands in a certain extent.
While in Hong Kong, many brands are already in the consumers minds, they do not
have to try, so Hong Kong university consumers are less impulsive.
There is still one reason of why Shanghai has the dimension of impulsiveness while
Hong Kong does not. Impulsive purchases may be interpreted as I have not
gathered enough information for this product before I purchase in Chinese [Fan and
Xiao, 1998]. China has many counterfeit products. How to differentiate and avoid
buying counterfeit products is one of the most salient consumer issues in China. Many
famous brands, both domestic and foreign, are being counterfeited and sold in the
k d h f i d ll f li h hi h i
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5.4.2 Item Loadings
The items loading on each dimension are quite similar, although not exactly the same.
Now, lets take a look of the dimensions while includes more differentiation between
Shanghai and Hong Kong. They are brand conscious and fashion conscious.
Firstly, lets take a look in the brand conscious dimension.
---------------------------------------------------------------------------------------------
Table 5: Comparison of Brand conscious and price equals quality consumerdimension of Shanghai and Hong Kong (Page 44)
---------------------------------------------------------------------------------------------
Only Question 14 loaded the same in both places, while Question 11, 12, 13 and 35
only loaded on Hong Kong but did not load significantly on any factor for the
Shanghai sample. As suggested by Fan and Xiao [1998], national brands may be
treated as a quality product, and the newly imported brands will be treated as
brand-named product by Chinese consumers. We did not consider this concept when
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Only Question 15 loaded the same in both places, while Question 16 and 21 only
loaded on Shanghai but not on Hong Kong, and Question 18, 20 and 22 loaded on
Hong Kong but not in Shanghai. It seems very different, however, it is not. Items 20,
21 and 22 have loaded on the recreational and hedonistic conscious dimension in
Sproles and Kendalls research [1986]. Sproles and Kendall also found their
fashion-consciousness factor was significantly correlated with recreational
consciousness factor. This correlation is quite intuitive because for most consumers to
be fashion conscious, they have to spend time paying attention to changing fashions
[Fan and Xiao, 1998]. To conclude, although the items loaded in Shanghai are
different from Hong Kong, the nature of the items are similar.
5.4.3 T-test: Test of Hypotheses
Independent-sample t-test was conducted to compare the CSI scores for Shanghai and
Hong Kong university consumers, six t-tests instead of only four mentioned in the
H h i D l f d i d di f ll i f
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T-Test 1: Brand conscious and price equals quality consumer
There was significant difference in scores for Shanghai (M =2.3933, SD =0.75881)
and Hong Kong (M =2.8813, SD =0.63799; t(289.46) =-6.029, p =0.00) university
consumers. The magnitude of the differences in the means was large (eta squared
=0.11).
Hong Kong university consumers are more brand conscious than Shanghai. It is
different from what we expected (H1: Shanghai university consumers are more
brand consciousness than Hong Kong university consumers). One possible reason is
the different exposure to brand names. As noted before, Hong Kong is more open to
foreign cultures and brands. The more brands they know the more chance they would
become brand conscious. Furthermore, although the Shanghai university consumers
are indulged by their parents, it is not necessary that they will become brand
conscious.
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would not consider too much about brands. In addition, according to Oliver [1994],
consumers in China always focus on durability when shopping, so Shanghai
university consumers focus on quality in their shopping.
T-Test 3: Novelty and fashion-conscious consumer
There was significant difference in scores for Shanghai (M =3.0156, SD =0.89521)
and Hong Kong (M =3.4333, SD =0.65517; t(273.03) =-4.612, p =0.00) university
consumers. The magnitude of the differences in the means was moderate (eta squared
=0.07).
Hong Kong university consumers are more fashion conscious than the Shanghai. This
result is the same as we expected (H3: Hong Kong university consumers are more
fashion consciousness than Shanghai university consumers).
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T-Test 5: Price conscious and value for money consumer
There was no significant difference in scores for Shanghai (M =3.6000, SD =0.81306)
and Hong Kong (M =3.5689, SD =0.71476; t(298) =-1.290, p =0.725) university
consumers. The magnitude of the differences in the means was small (eta squared
=0.00).
We expect that Hong Kong university consumers are more price consciousness than
Shanghai university consumers (H2), but this is not the case, there are no differences
between them, and both of them are quite price conscious. According to Oliver [1994],
consumers in China are still encouraging frugality, many of them still have the mind
that To practice thrift is a virtue (). This may be one of the reasons that
Shanghai university consumers are as price conscious as the Hong Kong students.
T-Test 6: Impulsive and careless consumer
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We also expect that Hong Kong university consumers are more confused by over
choice than Shanghai university consumers (H4), however, from the result of factor
analysis, the confused dimension is even not appear in both places. It shows that
university consumers in Shanghai and Hong Kong can take advantage of the available
information and make better choices [Fan and Xiao, 1998]. It may be because both of
them are highly educated and have certain judgment of the markets, so they can utilize
the information, regardless of the information received.
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Chapter 6. Business Implications
6.1 For Shanghai
Shanghai university consumers are perfectionistic and impulsive. They always make
special effort to obtain the best quality and perfect choice; however, there are too
many counterfeit products that make them feel regretted after the purchase. Marketers
should stress on improving the overall attributes of the products so that the quality of
product could match the requirement of consumers. Overall quality of product can be
divided into two items: extrinsic and intrinsic [Olson and Jacoby, 1972; Jonansson,
1989; Gabbot, 1991]. Extrinsic attributes refer to the brand, country of origin,
advertising, independent consumer, price, after sell services, and distribution channel.
Intrinsic attributes refer to physical product attributes such as shape, type of surface,
color, weight, material used, taste and performance. Using good quality as an
outstanding and clear image would catch the attention of the consumers. Better
customer services should also be provided. As the consumers are still in the stage of
impulsive purchasing, they are still trying each product, offering them a good product
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6.2 For Hong Kong
Hong Kong university consumers are brand and fashion conscious. Therefore,
companies should try to do deep marketing researches to and build their brand once
they enter Hong Kong market. In addition, the content and style of marketing and
promotion programs should be fun, trendy and fashionable.
6.3 For both Shanghai and Hong Kong
Both Shanghai and Hong Kong university students are price conscious. Marketers
should promote their products by offering benefits to consumers, in order to make
them feel that their purchases are value for money.
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Chapter 7. Limitations
There are several limitations that warrant future research.
7.1 Generality of Consumer Characteristics
Consumers have different perceptions on different types of products. For example,
their value for a luxury and durable product, which is totally different from an inferior
and non-durable product [Kaynak,E. & Cavusgil, S.T., 1983]. We cannot assume that
a consumer with high brand consciousness would consider name products on every
decision. Other characteristics may lack perfect generality as well [Sproles and
Kendall, 1986]. Indeed, a consumer may have different consumer styles for each
product category. Therefore, future research should look at consumer decision-making
in various product categories for details.
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university consumers in Shanghai and Hong Kong.
7.3 Limitation of Culture and Economic Background
The Shanghai and Hong Kong student sample may not exhibit certain consumer
decision-making characteristics due to the cultural reasons, for example the Man-to
nature orientation, Man-to-himself orientation, Relational orientation, Time
orientation and Personal-activity orientation [Oliver, 1994]. And the economic
reasons, for example, the income of the families, should also be take into account also.
However, the CSI used in this study provides a good starting point for further
development of the CSI inventory in Shanghai and Hog Kong consumer context.
More items and dimensions that are idiosyncratic to Shanghai and Hong Kong culture
need to be developed in future studies. It would be helpful to develop more items to
improve the psychometric properties of three dimensions; they are quality and price
conscious.
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Chapter 8. Conclusion
The objectives of this study were fulfilled. Decision-making styles of university
consumers in Shanghai and Hong Kong are classified, and several similarities and
differences in decision-making styles were identified. The most important findings are
that Shanghai university consumers are perfectionistic and impulsive, whereas Hong
Kong university consumers are brand conscious and fashion conscious, and they both
have the characteristic of price conscious. This paper provides a good starting point
for marketers who want to enter Shanghai or Hong Kong market. Marketers should
pay more attention in these aspects as to win consumers hearts. They should also take
into account of the culture issues that do not cover in this paper.
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18. Jacoby, Jacob and Robert W. Chestnut. (1978) Brand Loyalty: Measurement and
Management, New York: John Wiley and Sons.
19. Johansson, Johny K. (1989), Determinants andEfects of the Use of Made in
Labels, International Marketing Review, 6,1, pp 47-58
20. Kaiser (1970), A second generation Little Jiffy. Psychometrika, 35, 401-415
21. Kaynak,E. & Cavusgil, S.T. (1983).Consumer attitudes towards products of
foreign origin: do they vary across product classes? International Journal of
Advertising, 2, pp.147-157
22. Kim, Jae-On and Charles W.Mueller (1978), Introduction to Factor Analysis:
What it is and How to Do it, Bevely Hills, CA: Sage Publications.
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29. Moschis, George P. (1976), Shopping orientations and Consumer Uses of
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30. Moschis, George P. (1976), Shopping orientations and Consumer Uses of
Information. Journal of Retailing, 52(Summer): 61-70,93
31. Moschis, George P. and Roy L, Moore (1979), Decision making amoung the
Youth: A Socialization perspective, Journal of Consumer Research, 6(setember):
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(Spring): 35-49.
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36. Shim, Soyeon and Kenneth C. Gehrt. (1996), Hispanic and American
Adolescents: An Exploratory Study of Their Approach to Shopping, Journal of
Retailing, 72,3:307-324
37. Sproles, George B (1985), From Perfectionism to Fadism: Measuring Consumers
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42. Stone, Gregory. P. (1954) City Shoppers and Urban Identification: Obervations
on the Social Psychology of City Life., American Jounral of Sociology, 60:36-45
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Chapter 10. Appendix
Appendix Page
10.1Explanation of the eight factors loading by Sproles and Kendall 36
10.2Tables 38
10.3
Questionnaires 47
10.4SPSS Outputs 58
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10.1 Explanation of the eight factors loading by Sproles and Kendall
Factor 1: Perfectionistic and high-quality consciousness
Items loading on this factor measure a consumers search for the best quality in
products. Those consumers who have higher perfectionism could also be expected to
shop more carefully and systematically. They are not satisfied with the good enough
product.
Factor 2: Brand consciousness and price equals quality
It measures consumers orientations toward buying the more expensive, well-known
national brands. High scorers are likely to believe that a higher price means better
quality. They appear to have positive attitudes toward department and specialty stores,
where brand names and higher prices are prevalent. They also appear to prefer best
selling, advertised brands.
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10.2 Tables
Table Page
Table 1Personal Information of the 300 samples from Shanghai and Hong Kong 39
Table 2Factor Loadings and Construct Reliability of Shanghai CSI 41
Table 3
Factor Loadings and Construct Reliability of Hong Kong CSI 42
Table 4Comparison of Habitual and brand-loyal consumer dimensionof Shanghai and Hong Kong
43
Table 5Comparison of Brand conscious and price equals quality consumer dimensionof Shanghai and Hong Kong
44
Table 6Comparison of Novelty and fashion-conscious consumer dimensionof Shanghai and Hong Kong
45
Table 7Comparison of decision-making styles between Shanghai and Hong Konguniversities consumers
46
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Table 1
Personal Information of the 300 samples from Shanghai and Hong Kong
Shanghai Hong Kong
Frequency
Percentage
Frequency
Percentage
Male 66 44.0 56 37.3
Female 84 56.0 94 62.7
Gender
Total 150 100.0 150 100.01 125 83.3 16 10.7
2 13 8.7 52 34.7
3 12 8.0 52 34.7
More than 3 0 0 30 20.0
NumberofBloodSiblings
Total 150 100.0 150 100.0
Parents 111 74.0 41 27.3
Scholarship/Grant/Loan 8 5.3 6 4.0
Part-time 3 2.0 30 20.0
Partly Parents, partlyPart-time
15 10.0 41 27.3
Partly Parents, partlyScholarship/Grant/Loan
7 4.7 9 6.0
PartlyScholarship/Grant/Loan, partly Part-time
3 2.0 13 8.7
Partly Parents,Scholarship/Grant/Loan, and Part-time
3 2.0 10 6.7
IncomeSource
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500 26 17.3
$1500 42 28.0
501-1000 48 32.0$1501-$2000 45 30.0
1001-1500 52 34.7
$2001-$2500 31 20.7
1501 24 16.0
$2501 32 21.3
CostofLiving
Total 150 100.0 150 100.0Television 125 83.3 127 84.7
Radio 26 17.3 44 29.3
Newspaper 86 57.3 96 64
Magazine 113 75.3 102 68
Internet 119 79.3 103 68.7
TransportationAdvertisement
65 43.3 64 42.7
Exhibition 26 17.3 20 13.3Family and friends 96 64 114 76
Others 0 0 9 6
Inform-ationSource
Total 656 437.1 679 452.7
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Table 2
Factor Loadings and Construct Reliability of Shanghai CSI
Shanghai CSI Construct
Reliability
Factor
Loading
Novelty and fashion-conscious consumer 0.7647shcsi15 I usually have one or more outfits of the very newest style. .848shcsi16 I keep my wardrobe up-to-date with the changing fashions. .884shcsi21 Going shopping is one of the enjoyable activities of my life. .702
Perfectionistic and high-quality conscious consumer 0.7283shcsi01 Getting very good quality is very important to me. .893shcsi02 When it comes to purchasing products, I try to get the very best orperfect choice.
.690
shcsi04 I make special effort to choose the very best quality products. .799Habitual and brand-loyal consumer 0.6791shcsi33 There are so many brands to choose from that often I feel confused. .774shcsi37 I have favorite brands I buy over and over. .708shcsi39 I go to the same stores each time I shop. .831
Impulsive and careless consumer 0.6189shcsi30 Often I make careless purchases I later wish I had not. .640shcsi31 I take the time to shop carefully for best buys. .802*shcsi32 I carefully watch how much I spend. .640*
Price conscious and value for money consumer 0.4742shcsi05 I really dont give my purchases much thought or care. .803shcsi07 I shop quickly, buying the first product or brand I find that seemsgood enough.
.763*
Brand conscious and price equals quality consumer -shcsi14 The most advertised brands are usually very good choices. .93
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Table 3
Factor Loadings and Construct Reliability of Hong Kong CSI
Hong Kong CSI Construct
Reliability
Factor
Loading
Brand conscious and price equals quality consumer 0.7501hkcsi11 The higher the price of a product, the better its quality. .666hkcsi12 Nice department and specialty stores offer me the best products. .734hkcsi13 I prefer buying the best-selling brands. .786
hkcsi14 The most advertised brands are usually very good choices. .764hkcsi35 The more I learn about products, the harder it seems to choose thebest.
.53
Perfectionistic and high-quality conscious consumer 0.6006hkcsi01 Getting very good quality is very important to me. .582hkcsi02 When it comes to purchasing products, I try to get the very best orperfect choice.
.692
hkcsi03 In general, I usually try to buy the best overall quality. .582hkcsi04 I make special effort to choose the very best qualit y products. .573hkcsi08 A product doesnt have to be perfect, or the best, to satisfy me. .50Novelty and fashion-conscious consumer 0.6491hkcsi15 I usually have one or more outfits of the very newest style. .675hkcsi18 To get variety, I shop different stores and choose different brands. .553hkcsi20 Shopping is not a pleasant activity to me. .786*hkcsi22 Shopping other stores wastes my time. .729*
Habitual and brand-loyal consumer 0.7339hkcsi37 I have favorite brands I buy over and over. .797
hkcsi38 Once I find a product or brand I like, I stick with it. .827hkcsi39 I go to the same stores each time I shop. .752Price conscious and value for money consumer 0.5055
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Table 4
Comparison of Habitual and brand-loyal consumer dimension of Shanghai
and Hong Kong
Habitual and brand-loyal consumer
Shanghai Hong Kong
shcsi33There are so many brands to choose from thatoften I feel confused.
shcsi37 + hkcsi37I have favorite brands I buy over and over.
shcsi39 + hkcsi39I go to the same stores each time I shop.
hkcsi38Once I find a product or brand I like, I stick withit.
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Table 5
Comparison of Brand conscious and price equals quality consumer dimension
of Shanghai and Hong Kong
Brand conscious and price equals quality consumer
Shanghai Hong Kong
hkcsi11The higher the price of a product, the better itsquality.
hkcsi12Nice department and specialty stores offer methe best products.
hkcsi13I prefer buying the best-selling brands.
shcsi14 + hkcsi14The most advertised brands are usually very good choices.
hkcsi35
The more I learn about products, the harder itseems to choose the best.
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Table 6
Comparison of Novelty and fashion-conscious consumer dimension of
Shanghai and Hong Kong
Novelty and fashion-conscious consumer
Shanghai Hong Kong
shcsi15 + hkcsi15I usually have one or more outfits of the very newest style.
shcsi16
I keep my wardrobe up-to-date with thechanging fashions.
hkcsi18To get variety, I shop different stores and choosedifferent brands.
hkcsi20Shopping is not a pleasant activity to me.
shcsi21
Going shopping is one of the enjoyableactivities of my life.
hkcsi22Shopping other stores wastes my time.
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Table 7
Comparison of decision-making styles between Shanghai and Hong Kong
universities consumers
Mean Std.Deviation
Sig.(2-tailed)
SignificanceDifference?
etasquared
Effect size
T-Test 1: Brand conscious and price equals quality consumer
SH 2.3933 .75881
HK 2.8813 .63799
0.00 0.11 Large
T-Test 2: Perfectionistic and high-quality conscious consumerSH 4.2222 .67739
HK 3.7973 .49480
0.00 0.11 Large
T-Test 3: Novelty and fashion-conscious consumer
SH 3.0156 .89521HK 3.4333 .65517
0.00 0.07 Moderate
T-Test 4: Habitual and brand-loyal consumer
SH 2.9222 .82143
HK 3.0422 .78890
0.198 0.01 Small
T-Test 5: Price conscious and value for money consumer
SH 3.6000 .81306
HK 3.5689 .71476
0.725 0.00 Small
T-Test 6: Impulsive and careless consumer
SH 2.6778 .53431
HK .0000 .00000
0.00 0.93 Very large
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10.3 Questionnaires
Questionnaires Page
Shanghai Version 48
Hong Kong Version 53
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________
5
1
1.
1 2 3 4 5
2. /
1 2 3 4 5
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7.
1 2 3 4 5
8. /
1 2 3 4 5
9.
1 2 3 4 5
10.
1 2 3 4 5
11.
1 2 3 4 5
12. /
1 2 3 4 5
13.
1 2 3 4 5
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18.
1 2 3 4 5
19.
1 2 3 4 5
20.
1 2 3 4 5
21.
1 2 3 4 5
22.
1 2 3 4 5
23.
1 2 3 4 5
24.
1 2 3 4 5
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29.
1 2 3 4 5
30.
1 2 3 4 5
31.
1 2 3 4 5
32.
1 2 3 4 5
33.
1 2 3 4 5
34.
1 2 3 4 5
35.
1 2 3 4 5
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40.
1 2 3 4 5
1.
2.
() ()1. 12. 2
3. 34. 3
1.
2. //
3.
4.
5. //6. //
7. //
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________
5
1
1.
1 2 3 4 5
2. /
1 2 3 4 5
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7.
1 2 3 4 5
8. /
1 2 3 4 5
9.
1 2 3 4 5
10.
1 2 3 4 5
11.
1 2 3 4 5
12. /
1 2 3 4 5
13.
1 2 3 4 5
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40.
1 2 3 4 5
1.
2.
() ()
1. 12. 23. 3
4. 3
1.
2. //
3.
4.
5. //
6. //
7. //
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10.4 SPSS Outputs
SPSS Outputs Page
10.4.1Personal Information of the 300 samples from Shanghai and Hong Kong 59
10.4.2Decision-making styles of Shanghai university consumers 65
10.4.3
Cronbachs alpha Reliability method: Shanghai CSI 85
10.4.4Decision-making styles of Hong Kong university consumers 90
10.4.5Cronbachs alpha Reliability method: Hong Kong CSI 108
10.4.6
Comparison of decision-making styles between Shanghai and Hong Konguniversities consumers
113
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10.4.1 Personal Information of the 300 samples from Shanghai and Hong Kong
Shanghai
Sex (SH)
66 22.0 44.0 44.0
84 28.0 56.0 100.0
150 50.0 100.0
150 50.0
300 100.0
Male
Female
Total
Valid
SystemMissing
Total
Frequency Percent Valid Percent
Cumulative
Percent
Number of Blood Siblings (SH)
125 41.7 83.3 83.3
13 4.3 8.7 92.0
12 4.0 8.0 100.0
150 50.0 100.0
150 50.0
300 100.0
1
2
3
Total
Valid
SystemMissing
Total
Frequency Percent Valid PercentCumulative
Percent
Source of Income (SH)
111 37.0 74.0 74.0
8 2.7 5.3 79.3
3 1 0 2 0 81 3
Parents
Scholarship/Grant/Loan
Part-time
ValidFrequency Percent Valid Percent
Cumulative
Percent
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Cost of Living (SH)
26 8.7 17.3 17.348 16.0 32.0 49.3
52 17.3 34.7 84.0
24 8.0 16.0 100.0
150 50.0 100.0
150 50.0
300 100.0
$1501
Total
Valid
SystemMissing
Total
Frequency Percent Valid PercentCumulative
Percent
Information Source (SH)300 100.0SystemMissing
Frequency Percent
Television (SH)
25 8.3 16.7 16.7
125 41.7 83.3 100.0
150 50.0 100.0
150 50.0
300 100.0
No
Yes
Total
Valid
SystemMissing
Total
Frequency Percent Valid PercentCumulative
Percent
Radio (SH)
124 41.3 82.7 82.7
26 8.7 17.3 100.0
150 50.0 100.0
150 50.0
300 100.0
No
Yes
Total
Valid
SystemMissing
Total
Frequency Percent Valid PercentCumulative
Percent
Newspaper (SH)C
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Hong Kong
Sex (HK)
56 18.7 37.3 37.3
94 31.3 62.7 100.0
150 50.0 100.0
150 50.0
300 100.0
Male
Female
Total
Valid
SystemMissing
Total
Frequency Percent Valid PercentCumulative
Percent
Number of Blood Siblings (HK)
16 5.3 10.7 10.7
52 17.3 34.7 45.3
52 17.3 34.7 80.0
30 10.0 20.0 100.0
150 50.0 100.0150 50.0
300 100.0
1
2
3
>3
Total
Valid
SystemMissing
Total
Frequency Percent Valid PercentCumulative
Percent
Source of Income (HK)
41 13.7 27.3 27.3
6 2.0 4.0 31.3
30 10.0 20.0 51.3
41 13.7 27.3 78.7
9 3.0 6.0 84.7
Parents
Scholarship/Grant/Loan
Part-time
Partly Parents, partlyPart-time
Partly Parents, partlyScholarship/Grant/Loan
Valid
Frequency Percent Valid PercentCumulative
Percent
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Information Source (HK)300 100.0SystemMissing
Frequency Percent
Television (HK)
23 7.7 15.3 15.3
127 42.3 84.7 100.0
150 50.0 100.0
150 50.0
300 100.0
No
Yes
Total
Valid
SystemMissing
Total
Frequency Percent Valid PercentCumulative
Percent
Radio (HK)
106 35.3 70.7 70.7
44 14.7 29.3 100.0
150 50.0 100.0
150 50.0
300 100.0
No
Yes
Total
Valid
SystemMissing
Total
Frequency Percent Valid PercentCumulative
Percent
Newspaper (HK)
54 18.0 36.0 36.0
96 32.0 64.0 100.0
150 50.0 100.0
150 50.0
300 100.0
No
Yes
Total
Valid
SystemMissing
Total
Frequency Percent Valid PercentCumulative
Percent
Magazine (HK)
48 16 0 32 0 32 0NV lid
Frequency Percent Valid PercentCumulative
Percent
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Transportation Advertisment (HK)
86 28.7 57.3 57.364 21.3 42.7 100.0
150 50.0 100.0
150 50.0
300 100.0
NoYes
Total
Valid
SystemMissing
Total
Frequency Percent Valid PercentCumulative
Percent
Exhibition (HK)
130 43.3 86.7 86.720 6.7 13.3 100.0
150 50.0 100.0
150 50.0
300 100.0
NoYes
Total
Valid
SystemMissing
Total
Frequency Percent Valid PercentCumulative
Percent
Family and friends (HK)
36 12.0 24.0 24.0
114 38.0 76.0 100.0150 50.0 100.0
150 50.0
300 100.0
No
YesTotal
Valid
SystemMissing
Total
Frequency Percent Valid PercentCumulative
Percent
Others (HK)
141 47.0 94.0 94.0
9 3.0 6.0 100.0150 50.0 100.0
150 50.0
300 100.0
No
YesTotal
Valid
SystemMissing
Total
Frequency Percent Valid PercentCumulative
Percent
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Correlation M atrix SH C SI 01 SH C SI 02 SH C SI 03 SH C SI 04 SH C SI 05 SH C SI 06SH CSI 01 1 0.468476 0.566205 0.619297 -0.06757 0.415655
SH CSI 02 0.468476 1 0.468217 0.361046 0.116942 0.526069
SH CSI 03 0.566205 0.468217 1 0.603896 -0.20735 0.476839
SH CSI 04 0.619297 0.361046 0.603896 1 -0.03195 0.490067
SH CSI 05 -0.06757 0.116942 -0.20735 -0.03195 1 0.004879
SH CSI 06 0.415655 0.526069 0.476839 0.490067 0.004879 1
SH C SI 07 0.04714 0.021945 -0.22114 0.025578 0.311903 0.14484
SH C SI 08 0.336379 0.456334 0.297271 0.350266 0.063793 0.358551
SH C SI 09 0.296712 0.266531 0.321982 0.382919 -0.32896 0.368282
SH C SI 10 0.098645 0.311492 0.286536 0.170389 -0.22654 0.330286SH C SI 11 0.107465 0.159822 0.34144 0.242674 -0.24135 0.235988
SH C SI 12 0.166504 0.130526 0.249611 0.254599 -0.12626 0.329876
SH C SI 13 0.115883 0.275283 0.227922 0.180403 0.010653 0.248206
SH C SI 14 -0.11262 -0.02891 -0.07222 -0.18696 -0.02553 -0.035
SH C SI 15 0.184559 0.240006 0.08335 0.202646 -0.04431 0.166949
SH C SI 16 0.052591 0.160901 0.03193 0.081044 -0.03375 0.034904
SH C SI 17 0.091405 0.278279 -0.00845 0.120837 -0.0954 0.062353
SH C SI 18 0.290323 0.428142 0.119435 0.36165 0.224544 0.234709
SH C SI 19 0.172789 0.236736 0.238647 0.365102 -0.06007 0.191606
SH C SI 20 0.114939 0.000614 -0.04404 0.183556 0.193714 0.043689
SH C SI 21 0.063491 0.084534 -0.03089 0.127326 0.179243 0.111281
SH C SI 22 0.031155 -0.16607 -0.18548 0.07138 0.275827 0.031092
SH C SI 23 -0.02519 0.168893 -0.13455 -0.03377 -0.00609 0.102139
SH C SI 24 -0.10137 -0.07199 -0.40816 -0.15303 0.384698 -0.34038
SH C SI 25 -0.07456 0.090315 -0.10635 -0.06155 0.168385 -0.08957
SH C SI 26 -0.17149 -0.05438 0.007934 -0.22402 0.070522 -0.05587
SH C SI27 0 159842 0 111958 0 140431 0 05066 0 030338 0 159087
Correlation
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Correlation M atrix SH C SI 07 SH C SI 08 SH C SI 09 SH C SI 10 SH C SI 11 SH C SI 12SH C SI 01 0.04714 0.336379 0.296712 0.098645 0.107465 0.166504
SH C SI 02 0.021945 0.456334 0.266531 0.311492 0.159822 0.130526
SH C SI 03 -0.22114 0.297271 0.321982 0.286536 0.34144 0.249611
SH C SI 04 0.025578 0.350266 0.382919 0.170389 0.242674 0.254599
SH C SI 05 0.311903 0.063793 -0.32896 -0.22654 -0.24135 -0.12626
SH C SI 06 0.14484 0.358551 0.368282 0.330286 0.235988 0.329876
SH CSI 07 1 -0.19982 0.217684 -0.01742 -0.04106 0.043123
SH CSI 08 -0.19982 1 0.34122 0.376158 0.315378 0.135987
SH CSI 09 0.217684 0.34122 1 0.618969 0.510331 0.592811
SH CSI 10 -0.01742 0.376158 0.618969 1 0.667219 0.469828SH CSI 11 -0.04106 0.315378 0.510331 0.667219 1 0.495489
SH CSI 12 0.043123 0.135987 0.592811 0.469828 0.495489 1
SH C SI 13 -0.05652 0.311848 0.150963 0.089085 0.248123 0.223821
SH C SI 14 -0.08476 0.109365 0.106239 0.166047 0.213947 0.279788
SH C SI 15 -0.09763 0.144413 0.158689 0.112215 -0.00038 0.090177
SH C SI 16 -0.12978 0.096432 0.046423 0.090299 -0.07101 -0.00178
SH C SI 17 0.073631 0.081187 0.286752 0.181063 0.026743 0.266663
SH C SI 18 0.080854 0.273392 0.154152 0.213067 -0.02955 0.127527
SH C SI 19 -0.21438 0.086988 0.093844 0.21999 0.055726 -0.02365
SH C SI 20 0.130962 -0.08556 -0.04257 -0.20139 -0.18227 0.053875
SH C SI 21 0.117302 0.132127 -0.06244 -0.03551 -0.1154 -0.00979
SH C SI 22 0.227257 -0.10491 -0.16738 -0.25896 -0.22048 -0.0087
SH C SI 23 -0.07567 0.17075 -0.14382 0.052334 -0.08367 -0.18249
SH C SI 24 0.385143 -0.16932 -0.19552 -0.19291 -0.23399 -0.01622
SH C SI 25 0.214487 0.086416 0.022627 0.025939 0.080108 0.024743
SH C SI 26 0.019374 -0.15726 -0.29577 -0.25053 -0.23299 -0.33964
SH C SI27 0 288911 0 021897 0 104228 0 048302 0 123542 0 07965
Correlation
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Correlation M atrix SH C SI 13 SH C SI 14 SH C SI 15 SH C SI 16 SH C SI 17 SH C SI 18SH C SI 01 0.115883 -0.11262 0.184559 0.052591 0.091405 0.290323
SH C SI 02 0.275283 -0.02891 0.240006 0.160901 0.278279 0.428142
SH C SI 03 0.227922 -0.07222 0.08335 0.03193 -0.00845 0.119435
SH C SI 04 0.180403 -0.18696 0.202646 0.081044 0.120837 0.36165
SH C SI 05 0.010653 -0.02553 -0.04431 -0.03375 -0.0954 0.224544
SH C SI 06 0.248206 -0.035 0.166949 0.034904 0.062353 0.234709
SH C SI 07 -0.05652 -0.08476 -0.09763 -0.12978 0.073631 0.080854
SH C SI 08 0.311848 0.109365 0.144413 0.096432 0.081187 0.273392
SH C SI 09 0.150963 0.106239 0.158689 0.046423 0.286752 0.154152
SH C SI 10 0.089085 0.166047 0.112215 0.090299 0.181063 0.213067SH C SI 11 0.248123 0.213947 -0.00038 -0.07101 0.026743 -0.02955
SH C SI 12 0.223821 0.279788 0.090177 -0.00178 0.266663 0.127527
SH CSI 13 1 0.418649 0.287159 0.309919 0.154354 0.049854
SH CSI 14 0.418649 1 0.129874 0.052354 0.211116 -0.19813
SH CSI 15 0.287159 0.129874 1 0.689501 0.425182 0.191463
SH CSI 16 0.309919 0.052354 0.689501 1 0.45665 0.312971
SH CSI 17 0.154354 0.211116 0.425182 0.45665 1 0.343528
SH CSI 18 0.049854 -0.19813 0.191463 0.312971 0.343528 1
SH C SI 19 -0.1313 -0.25004 0.204408 0.255884 0.276206 0.613846
SH C SI 20 0.218704 -0.04276 0.301506 0.3644 0.383572 0.309045
SH C SI 21 0.204634 0.217297 0.450454 0.44442 0.298588 0.302609
SH C SI 22 0.204973 0.053929 0.392409 0.492136 0.13009 0.16353
SH C SI 23 0.311207 0.153723 0.431493 0.429013 0.063272 0.152282
SH C SI 24 -0.04929 0.159589 0.15576 0.230321 0.325447 0.229426
SH C SI 25 -0.07488 0.016548 -0.20264 -0.33997 -0.1275 -0.11964
SH C SI 26 0.239134 0.069945 -0.06079 0.094308 -0.23782 -0.17081
SH C SI27 0 11432 0 01428 0 1761 0 26357 0 006785 0 14792
Correlation
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Correlation M atrix SH C SI 19 SH C SI 20 SH C SI 21 SH C SI 22 SH C SI 23 SH C SI 24SH C SI 01 0.172789 0.114939 0.063491 0.031155 -0.02519 -0.10137
SH C SI 02 0.236736 0.000614 0.084534 -0.16607 0.168893 -0.07199
SH C SI 03 0.238647 -0.04404 -0.03089 -0.18548 -0.13455 -0.40816
SH C SI 04 0.365102 0.183556 0.127326 0.07138 -0.03377 -0.15303
SH C SI 05 -0.06007 0.193714 0.179243 0.275827 -0.00609 0.384698
SH C SI 06 0.191606 0.043689 0.111281 0.031092 0.102139 -0.34038
SH C SI 07 -0.21438 0.130962 0.117302 0.227257 -0.07567 0.385143
SH C SI 08 0.086988 -0.08556 0.132127 -0.10491 0.17075 -0.16932
SH C SI 09 0.093844 -0.04257 -0.06244 -0.16738 -0.14382 -0.19552
SH C SI 10 0.21999 -0.20139 -0.03551 -0.25896 0.052334 -0.19291SH C SI 11 0.055726 -0.18227 -0.1154 -0.22048 -0.08367 -0.23399
SH C SI 12 -0.02365 0.053875 -0.00979 -0.0087 -0.18249 -0.01622
SH C SI 13 -0.1313 0.218704 0.204634 0.204973 0.311207 -0.04929
SH C SI 14 -0.25004 -0.04276 0.217297 0.053929 0.153723 0.159589
SH C SI 15 0.204408 0.301506 0.450454 0.392409 0.431493 0.15576
SH CSI 16 0.255884 0.3644 0.44442 0.492136 0.429013 0.230321
SH C SI 17 0.276206 0.383572 0.298588 0.13009 0.063272 0.325447
SH C SI 18 0.613846 0.309045 0.302609 0.16353 0.152282 0.229426
SH CSI 19 1 0.163781 0.186896 0.063998 0.164519 -0.04705
SH CSI 20 0.163781 1 0.501429 0.636987 0.179964 0.463182
SH CSI 21 0.186896 0.501429 1 0.621332 0.502195 0.430473
SH CSI 22 0.063998 0.636987 0.621332 1 0.328238 0.492539
SH CSI 23 0.164519 0.179964 0.502195 0.328238 1 0.216493
SH CSI 24 -0.04705 0.463182 0.430473 0.492539 0.216493 1
SH C SI 25 -0.17609 -0.29965 -0.05585 -0.18114 -0.00083 0.082917
SH C SI 26 -0.26623 -0.00959 0.16801 -0.00217 0.202167 -0.01863
SH C SI27 0 17821 0 1628 0 1753 0 27951 0 18733 0 02181
Correlation
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Correlation M atrix SH C SI 25 SH C SI 26 SH C SI 27 SH C SI 28 SH C SI 29 SH C SI 30SH C SI 01 -0.07456 -0.17149 0.159842 -0.12027 -0.14442 -0.11565
SH C SI 02 0.090315 -0.05438 0.111958 -0.15977 -0.07272 -0.02445
SH C SI 03 -0.10635 0.007934 0.140431 -0.19381 0.012693 -0.01161
SH C SI 04 -0.06155 -0.22402 0.05066 -0.13081 0.012588 0.022937
SH C SI 05 0.168385 0.070522 0.030338 0.086874 0.014687 -0.04382
SH C SI 06 -0.08957 -0.05587 0.159087 -0.02127 0.092807 0.088939
SH C SI 07 0.214487 0.019374 0.288911 0.103636 -0.02228 -0.03977
SH C SI 08 0.086416 -0.15726 0.021897 -0.10145 0.077831 0.02501
SH C SI 09 0.022627 -0.29577 0.104228 -0.28281 -0.14313 -0.02684
SH C SI 10 0.025939 -0.25053 0.048302 -0.21699 -0.08942 -0.02764SH C SI 11 0.080108 -0.23299 0.123542 -0.01937 -0.08565 -0.01302
SH CSI 12 0.024743 -0.33964 0.07965 -0.20937 -0.0873 -0.0009
SH C SI 13 -0.07488 0.239134 -0.11432 -0.09216 -0.03755 0.07942
SH C SI 14 0.016548 0.069945 -0.01428 -0.1168 -0.11681 0.051632
SH C SI 15 -0.20264 -0.06079 -0.1761 -0.15295 -0.12298 0.039347
SH C SI 16 -0.33997 0.094308 -0.26357 -0.10237 -0.04737 0.075177
SH C SI 17 -0.1275 -0.23782 0.006785 -0.20252 -0.09237 -0.00011
SH C SI 18 -0.11964 -0.17081 -0.14792 -0.09319 -0.00538 -0.1414
SH C SI 19 -0.17609 -0.26623 -0.17821 -0.06916 0.000745 -0.03889
SH C SI 20 -0.29965 -0.00959 -0.1628 -0.04137 0.017154 -0.06869
SH C SI 21 -0.05585 0.16801 -0.1753 0.028492 -0.00369 0.109098
SH C SI 22 -0.18114 -0.00217 -0.27951 0.054004 0.037179 -0.02337
SH C SI 23 -0.00083 0.202167 -0.18733 0.045738 0.004073 0.137421
SH C SI 24 0.082917 -0.01863 -0.02181 0.02352 0.031297 -0.06713
SH CSI 25 1 0.07485 0.312088 0.166662 0.023446 0.148611
SH CSI 26 0.07485 1 0.08148 0.134348 0.138943 0.161239
SH CSI27 0 312088 0 08148 1 0 095973 0 047732 0 00105
Correlation
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Correlation M atrix SH C SI 37 SH C SI 38 SH C SI 39 SH C SI 40SH CSI 01 0.100394 0.24923 0.102622 0.01186
SH CSI 02 0.151943 0.1214 0.171759 0.087681
SH C SI 03 0.330955 0.194888 0.376568 0.018698
SH C SI 04 0.311958 0.251114 0.210017 0.080959
SH C SI 05 -0.07669 -0.12407 -0.14946 0.202147
SH C SI 06 0.232156 0.189153 0.397655 -0.06718
SH C SI 07 0.018949 0.25548 -0.06936 -0.13938
SH CSI 08 0.3238 0.128561 0.295995 0.193496
SH C SI 09 0.363952 0.527268 0.401304 -0.21592
SH C SI 10 0.141651 0.228221 0.23785 -0.22883SH C SI 11 0.200306 0.281485 0.252226 -0.21056
SH C SI 12 0.250098 0.588595 0.244111 -0.30351
SH C SI 13 0.229355 0.074189 0.184583 0.28503
SH C SI 14 -0.08177 0.145494 -0.12923 0.098963
SH C SI 15 0.146172 0.078793 -0.06907 0.093642
SH C SI 16 0.137662 0.030218 0.036125 -0.03466
SH C SI 17 0.034302 0.297275 -0.2465 -0.02727
SH C SI 18 0.092869 0.119205 -0.01003 -0.02646
SH C SI 19 0.085598 -0.01783 -0.02546 -0.06896
SH C SI 20 -0.09436 -0.04399 -0.14685 0.118116
SH C SI 21 0.064906 0.028196 -0.12211 0.135859
SH C SI 22 -0.04794 -0.06865 -0.19658 0.058149
SH C SI 23 0.005501 -0.32063 -0.07201 0.026669
SH C SI 24 -0.21173 0.072377 -0.49965 0.045132
SH C SI 25 0.069303 0.107976 -0.06913 -0.09133
SH C SI 26 0.09702 -0.19871 0.174095 0.199637
SH C SI27 0 135907 0 337204 0 084299 0 18495
Correlation
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KMO and Bartlett's Test
.608
3602.776
780
.000
Kaiser-Meyer-Olkin Measure of Sampling
Adequacy.
Approx. Chi-Square
df
Sig.
Bartlett's Test of
Sphericity
Scree Plot
Component Number
39373533312927252321191715131197531Eigenvalue
7
6
5
4
3
2
1
0
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Communalities
1.000 .793
1.000 .752
1.000 .752
1.000 .751
1.000 .755
1.000 .682
1.000 .721
1.000 .794
1.000 .726
1.000 .801
1.000 .662
1.000 .761
1.000 .740
1.000 .703
1.000 .688
1.000 .784
1.000 .665
1.000 .7801.000 .783
1.000 .747
1.000 .676
1.000 .803
1.000 .760
1.000 .775
1.000 .635
1.000 .801
1.000 .680
1.000 .720
1.000 .681
SH CSI 01
SH CSI 02
SH CSI 03
SH CSI 04
SH CSI 05
SH CSI 06
SH CSI 07
SH CSI 08
SH CSI 09
SH CSI 10SH CSI 11
SH CSI 12
SH CSI 13
SH CSI 14
SH CSI 15
SH CSI 16
SH CSI 17
SH CSI 18SH CSI 19
SH CSI 20
SH CSI 21
SH CSI 22
SH CSI 23
SH CSI 24
SH CSI 25
SH CSI 26
SH CSI 27
SH CSI 28
SH CSI 29
Initial Extraction
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Total Variance Explained
6.045 15.113 15.113 6.045 15.113 15.113
5.065 12.663 27.776 5.065 12.663 27.776
3.229 8.073 35.849 3.229 8.073 35.849
2.486 6.216 42.064 2.486 6.216 42.064
2.360 5.901 47.965 2.360 5.901 47.965
2.160 5.401 53.366 2.160 5.401 53.366
1.899 4.747 58.112 1.899 4.747 58.112
1.513 3.783 61.895 1.513 3.783 61.895
1.324 3.310 65.205 1.324 3.310 65.205
1.222 3.055 68.260 1.222 3.055 68.260
1.141 2.853 71.113 1.141 2.853 71.113
1.074 2.686 73.799 1.074 2.686 73.799
.955 2.387 76.186
.879 2.198 78.383
.842 2.105 80.488
.717 1.792 82.280
.696 1.740 84.019
.639 1.598 85.617
.596 1.490 87.107
.526 1.316 88.423
.498 1.246 89.669
.447 1.119 90.787
.409 1.023 91.810
.395 .987 92.797
.349 .872 93.669
.331 .828 94.497
.283 .707 95.204
.259 .647 95.851
Component1
2
3
4
5
6
7
8
910
11
12
13
14
15
16
1718
19
20
21
22
23
24
25
26
27
28
Total % of Variance Cumulative % Total % of Variance Cumulative %
Initial Eigenvalues Extraction Sums of Squared Loadings
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Com ponent M atrixaCom ponent
1 2 3 4 5 6
SH CSI 01 0.525 0.346SH CSI 02 0.530 0.351
SH CSI 03 0.692
SH CSI 04 0.606 0.368
SH CSI 05 0.445
SH CSI 06 0.644
SH CSI 07 0.518 0.529
SH CSI 08 0.552 0.391
SH CSI 09 0.755SH CSI 10 0.640
SH CSI 11 0.593
SH CSI 12 0.568 -0.374 0.363
SH CSI 13 0.334 -0.391
SH CSI 14 0.483 -0.535
SH CSI 15 0.655
SH CSI 16 0.636 0.333 -0.306
SH CSI 17 0.632 -0.300SH CSI 18 0.541 0.397
SH CSI 19 0.373 -0.529
SH CSI 20 0.680
SH CSI 21 0.689 0.334
SH CSI 22 0.631 -0.328
SH CSI 23 0.465 0.413
SH CSI 24 -0.445 0.569 0.329
SH CSI 25 0.380 0.368
SH CSI 26 0.577
SH CSI27 0.356 0.364
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Com ponent M atrixaCom ponent
7 8 9 10 11 12
SH CSI 01 -0.380SH CSI 02 0.302
SH CSI 03
SH CSI 04 -0.321
SH C SI 05 -0.334 0.365
SH CSI 06
SH CSI 07
SH CSI 08 -0.347
SH CSI 09SH CSI 10 0.309 0.302
SH CSI 11
SH CSI 12
SH CSI 13
SH CSI 14
SH CSI 15
SH CSI 16
SH CSI 17 0.318SH CSI 18
SH CSI 19 0.406
SH CSI 20
SH CSI 21
SH CSI 22
SH CSI 23 0.364 -0.315
SH CSI 24
SH CSI 25 0.378
SH CSI 26 0.371
SH CSI27 0.315 -0.319
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Shanghai CSI - Factor Rotation (1st trail)
Rotated Component Matrixa
.682
.733
.697 .301
.776
.434
.667
.722
.585 .381
.407 -.394 .390 .404
.373 -.386 .437
.532
-.344 .458 .490
.347 .601
.745.664
.784
.438 -.322 -.349
.564 .377
.519 -.334
.694
.752
.794
.536 -.304
.501 -.518 .376
- 360 337 334
SH CSI 01
SH CSI 02
SH CSI 03
SH CSI 04
SH CSI 05
SH CSI 06SH CSI 07
SH CSI 08
SH CSI 09
SH CSI 10
SH CSI 11
SH CSI 12
SH CSI 13
SH CSI 14SH CSI 15
SH CSI 16
SH CSI 17
SH CSI 18
SH CSI 19
SH CSI 20
SH CSI 21
SH CSI 22
SH CSI 23
SH CSI 24
SH CSI 25
1 2 3 4 5 6
Component
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Shanghai CSI - Factor Rotation (2nd trail)
Rotated Component Matrix a
.755
.759
.778
.722
.728
.677
.351 -.328 .327
.735
.733
.811
.684
.757
.805 .356
.614 -.447
SH CSI
01
SH CSI
02
SH CSI
04
SH CSI05
SH CSI
06
SH CSI
07
SH CSI
11
SH CSI
14SH CSI
15
SH CSI
16
SH CSI
20
SH CSI
21
SH CSI
22SH CSI
28
S CS
1 2 3 4 5 6
Component
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Shanghai CSI - Factor Rotation (3rd trail)
Rotated Component Matrix a
.822
.750
.757
.777
.312 .731
.725
.848
.796
.856
.631 .340
.732
.668
.788
SH CSI
01
SH CSI
02
SH CSI
04SH CSI
05
SH CSI
06
SH CSI
07
SH CSI
14
SH CSI15
SH CSI
16
SH CSI
20
SH CSI
21
SH CSI
30
SH CSI
31
SH CSI
1 2 3 4 5 6
Component
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Shanghai CSI - Factor Rotation (4th trail)
Rotated Component Matrix a
.902
.668
.805
.807
.751
.729
.844
.872
.690
.649
.796
.809
.725
SH CSI
01
SH CSI
02
SH CSI
04SH CSI
05
SH CSI
07
SH CSI
14
SH CSI
15
SH CSI16
SH CSI
21
SH CSI
30
SH CSI
31
SH CSI
32
SH CSI
33
SH CSI
1 2 3 4 5 6
Component
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Shanghai CSI - Factor Rotation (5th and the final trail)
Communalities
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
SH CSI
01
SH CSI
02
SH CSI
04
SH CSI05
SH CSI
07
SH CSI
14
SH CSI
15
SH CSI
16
SH CSI
21
SH CSI
30
SH CSI
31
SH CSI
32
SH CSI
33
SH CSI
37
Initial
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Rotated Component Matrix a
.893
.690
.799
.803
.763
.939
.848
.884
.702
.640
.802
.808
.774
.708
.831
SH CSI
01
SH CSI
02
SH CSI
04
SH CSI
05
SH CSI
07
SH CSI
14
SH CSI
15
SH CSI
16
SH CSI
21
SH CSI
30
SH CSI
31
SH CSI
32
SH CSI
33
SH CSI
37
SH CSI
39
1 2 3 4 5 6
Component
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10.4.3 Cronbachs alpha Reliability method: Shanghai CSI
Factor 1: Novelty and fashion-conscious consumer
R E L I A B I L I T Y A N A L Y S I S - S C A L E (A L P H A)
Mean Std Dev Cases
1. SHCSI15 3.1267 1.0574 150.02. SHCSI16 2.6933 1.0294 150.03. SHCSI21 3.2267 1.1652 150.0
N of
Statistics for Mean Variance Std Dev VariablesSCALE 9.0467 7.2126 2.6856 3
Item-total Statistics
Scale Scale CorrectedMean Variance Item- Alpha
if Item if Item Total if ItemDeleted Deleted Correlation Deleted
SHCSI15 5 9200 3 4835 6615 6121
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Factor 2: Perfectionistic and high-quality conscious consumer
R E L I A B I L I T Y A N A L Y S I S - S C A L E (A L P H A)
Mean Std Dev Cases
1. SHCSI01 4.3400 .9471 150.02. SHCSI02 3.9467 .8731 150.0
3. SHCSI04 4.3800 .6822 150.0
N ofStatistics for Mean Variance Std Dev Variables
SCALE 12.6667 4.1298 2.0322 3
Item-total Statistics
Scale Scale CorrectedMean Variance Item- Alpha
if Item if Item Total if ItemDeleted Deleted Correlation Deleted
SHCSI01 8.3267 1.6577 .6458 .5189SHCSI02 8.7200 2.1627 .4692 .7401
SHCSI04 8.2867 2.4340 .5780 .6366
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Factor 3: Habitual and brand-loyal consumer
R E L I A B I L I T Y A N A L Y S I S - S C A L E (A L P H A)
Mean Std Dev Cases
1. SHCSI33 2.6600 1.0221 150.02. SHCSI37 3.4600 1.0969 150.0
3. SHCSI39 2.6467 1.0371 150.0
N ofStatistics for Mean Variance Std Dev Variables
SCALE 8.7667 6.0727 2.4643 3
Item-total Statistics
Scale Scale CorrectedMean Variance Item- Alpha
if Item if Item Total if ItemDeleted Deleted Correlation Deleted
SHCSI33 6.1067 3.3577 .4459 .6427SHCSI37 5.3067 3.1939 .4274 .6723
SHCSI39 6.1200 2.8446 .6153 .4196
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Factor 4: Impulsive and careless consumer
R E L I A B I L I T Y A N A L Y S I S - S C A L E (A L P H A)
Mean Std Dev Cases
1. SHCSI30 2.7067 .7377 150.02. SHCSI31 2.7667 .7634 150.03. SHCSI32 2.5600 .6183 150.0
N ofStatistics for Mean Variance Std Dev Variables
SCALE 8.0333 2.5694 1.6029 3
Item-total Statistics
Scale Scale Corrected
Mean Variance Item- Alphaif Item if Item Total if ItemDeleted Deleted Correlation Deleted
SHCSI30 5.3267 1.4832 .3016 .6987SHCSI31 5.2667 1.2036 .4675 .4604SHCSI32 5.4733 1.3919 .5450 .3806
Reliability Coefficients
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Factor 5: Price conscious and value for money consumer
R E L I A B I L I T Y A N A L Y S I S - S C A L E (A L P H A)
Mean Std Dev Cases
1. SHCSI05 3.8267 .9606 150.02. SHCSI07 3.3733 1.0462 150.0
N of
Statistics for Mean Variance Std Dev VariablesSCALE 7.2000 2.6443 1.6261 2
Item-total Statistics
Scale Scale CorrectedMean Variance Item- Alpha
if Item if Item Total if ItemDeleted Deleted Correlation Deleted
SHCSI05 3.3733 1.0946 .3119 .SHCSI07 3.8267 .9228 .3119 .
Reliability Coefficients
N of Cases = 150.0 N of Items = 2
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10.4.4 Decision-making styles of Hong Kong university consumers
HK CSI - Factor Analysis
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Correlation M atrix H K C SI 01 H K C SI 02 H K C SI 03 H K C SI 04 H K C SI 05 H K C SI 06H K CSI 01 1.000 0.181 0.318 0.237 -0.040 0.260
H K CSI 02 0.181 1.000 0.467 0.141 0.046 0.329
H K CSI 03 0.318 0.467 1.000 0.320 -0.041 0.398H K CSI 04 0.237 0.141 0.320 1.000 -0.016 0.285
H K CSI 05 -0.040 0.046 -0.041 -0.016 1.000 0.161
H K CSI 06 0.260 0.329 0.398 0.285 0.161 1.000
H K CSI 07 -0.027 -0.039 -0.049 -0.082 0.393 0.198
H K CSI 08 0.088 0.353 0.224 0.154 0.034 0.365
H K CSI 09 0.036 0.208 0.224 0.040 -0.289 0.139
H K CSI 10 0.026 0.077 0.096 -0.043 -0.329 0.022H K CSI 11 0.005 0.014 0.036 0.008 -0.147 0.056
H K CSI 12 -0.039 0.132 0.119 -0.049 -0.147 0.148
H K CSI 13 -0.116 0.061 0.127 -0.058 -0.070 0.061
H K CSI 14 -0.099 -0.080 0.114 -0.063 -0.265 -0.028
H K CSI 15 0.050 0.044 -0.020 -0.091 -0.023 0.100
H K CSI 16 0.044 0.060 0.127 0.007 -0.157 -0.042
H K CSI 17 -0.016 0.129 0.127 0.041 -0.267 0.057
H K CSI 18 0.169 0.125 0.034 0.169 -0.045 0.146
HK CSI 19 0.160 0.045 0.117 0.198 -0.098 0.160
H K CSI 20 0.015 -0.057 -0.129 0.102 0.243 0.121
H K CSI 21 0.000 0.114 0.059 0.081 0.163 0.205
H K CSI 22 -0.087 -0.092 -0.113 -0.016 0.174 0.030
H K CSI 23 0.070 0.091 0.184 0.054 -0.088 0.168
H K CSI 24 -0.057 0.047 -0.090 0.058 0.259 0.013
H K CSI 25 0.088 0.076 0.039 0.159 0.107 0.150
H K CSI 26 -0.098 0.040 0.056 -0.010 0.058 0.116
H K CSI27 0 087 0 096 0 075 0 054 0 182 0 119
Correlation
8/6/2019 Consumer Decision-Making Styles
97/123
Correlation M atrix H K C SI 07 H K C SI 08 H K C SI 09 H K C SI 10 H K C SI 11 H K C SI 12H K CSI 01 -0.027 0.088 0.036 0.026 0.005 -0.039
H K CSI 02 -0.039 0.353 0.208 0.077 0.014 0.132
H K CSI 03 -0.049 0.224 0.224 0.096 0.036 0.119H K CSI 04 -0.082 0.154 0.040 -0.043 0.008 -0.049
H K CSI 05 0.393 0.034 -0.289 -0.329 -0.147 -0.147
H K CSI 06 0.198 0.365 0.139 0.022 0.056 0.148
H K CSI 07 1.000 -0.047 -0.086 -0.168 0.100 0.006
H K CSI 08 -0.047 1.000 0.209 0.160 0.161 0.216
H K CSI 09 -0.086 0.209 1.000 0.543 0.291 0.329
H K CSI 10 -0.168 0.160 0.543 1.000 0.463 0.355H K CSI 11 0.100 0.161 0.291 0.463 1.000 0.381
H K CSI 12 0.006 0.216 0.329 0.355 0.381 1.000
H K CSI 13 0.115 0.049 0.222 0.307 0.469 0.527
H K CSI 14 -0.036 0.055 0.292 0.369 0.380 0.434
H K CSI 15 0.032 0.061 0.126 0.158 0.071 0.114
H K CSI 16 -0.126 0.020 0.273 0.287 0.176 0.116
H K CSI 17 -0.072 -0.014 0.462 0.411 0.277 0.271
H K CSI 18 0.132 0.120 0.192 0.119 0.053 0.132
H K CSI 19 -0.067 -0.008 0.010 -0.090 0.052 0.011
H K CSI 20 0.150 0.166 -0.055 -0.152 0.022 0.103
H K CSI 21 0.278 0.089 0.052 -0.071 0.107 0.113
H K CSI 22 0.032 -0.082 -0.200 -0.077 -0.052 -0.135
H K CSI 23 0.000 0.048 0.139 0.072 0.124 0.083
H K CSI 24 0.328 -0.046 -0.063 -0.044 -0.027 -0.117
H K CSI 25 0.236 0.116 -0.010 -0.114 0.047 0.105
H K CSI 26 0.108 -0.002 -0.095 -0.089 0.002 0.058
H K CSI 27 0 300 0 108 0 015 0 121 0 155 0 090
Correlation
8/6/2019 Consumer Decision-Making Styles
98/123
Correlation M atrix H K C SI 13 H K C SI 14 H K C SI 15 H K C SI 16 H K C SI 17 H K C SI 18H K CSI 01 -0.116 -0.099 0.050 0.044 -0.016 0.169
H K CSI 02 0.061 -0.080 0.044 0.060 0.129 0.125
H K CSI 03 0.127 0.114 -0.020 0.127 0.127 0.034H K CSI 04 -0.058 -0.063 -0.091 0.007 0.041 0.169
H K CSI 05 -0.070 -0.265 -0.023 -0.157 -0.267 -0.045
H K CSI 06 0.061 -0.028 0.100 -0.042 0.057 0.146
H K CSI 07 0.115 -0.036 0.032 -0.126 -0.072 0.132
H K CSI 08 0.049 0.055 0.061 0.020 -0.014 0.120
H K CSI 09 0.222 0.292 0.126 0.273 0.462 0.192
H K CSI 10 0.307 0.369 0.158 0.287 0.411 0.119H K CSI 11 0.469 0.380 0.071 0.176 0.277 0.053
H K CSI 12 0.527 0.434 0.114 0.116 0.271 0.132
H K CSI 13 1.000 0.494 0.183 0.123 0.320 0.078
H K CSI 14 0.494 1.000 0.137 0.215 0.290 -0.053
H K CSI 15 0.183 0.137 1.000 0.652 0.399 0.301
H K CSI 16 0.123 0.215 0.652 1.000 0.514 0.208
H K CSI 17 0.320 0.290 0.399 0.514 1.000 0.300
H K CSI 18 0.078 -0.053 0.301 0.208 0.300 1.000
H K CSI 19 0.049 0.012 0.161 0.212 0.146 0.235
H K CSI 20 -0.010 -0.086 0.322 0.294 0.054 0.258
H K CSI 21 0.103 -0.071 0.317 0.222 0.174 0.279
H K CSI 22 0.011 -0.089 0.295 0.287 0.041 0.149
H K CSI 23 0.187 0.026 0.241 0.141 0.127 0.017
H K CSI 24 -0.099 -0.214 0.111 0.149 -0.022 0.071
H K CSI 25 0.225 0.043 -0.068 -0.062 -0.041 0.018
H K CSI 26 0.129 0.139 -0.163 -0.181 -0.088 -0.204
H K CSI27 0 100 0 046 0 002 0 115 0 186 0 017
Correlation
8/6/2019 Consumer Decision-Making Styles
99/123
Correlation M atrix H K C SI 19 H K C SI 20 H K C SI 21 H K C SI 22 H K C SI 23 H K C SI 24H K CSI 01 0.160 0.015 0.000 -0.087 0.070 -0.057
H K CSI 02 0.045 -0.057 0.114 -0.092 0.091 0.047
H K CSI 03 0.117 -0.129 0.059 -0.113 0.184 -0.090H K CSI 04 0.198 0.102 0.081 -0.016 0.054 0.058
H K CSI 05 -0.098 0.243 0.163 0.174 -0.088 0.259
H K CSI 06 0.160 0.121 0.205 0.030 0.168 0.013
H K CSI 07 -0.067 0.150 0.278 0.032 0.000 0.328
H K CSI 08 -0.008 0.166 0.089 -0.082 0.048 -0.046
H K CSI 09 0.010 -0.055 0.052 -0.200 0.139 -0.063
H K CSI 10 -0.090 -0.152 -0.071 -0.077 0.072 -0.044
H K CSI 11 0.052 0.022 0.107 -0.052 0.124 -0.027
H K CSI 12 0.011 0.103 0.113 -0.135 0.083 -0.117
H K CSI 13 0.049 -0.010 0.103 0.011 0.187 -0.099
H K CSI 14 0.012 -0.086 -0.071 -0.089 0.026 -0.214
H K CSI 15 0.161 0.322 0.317 0.295 0.241 0.111
H K CSI 16 0.212 0.294 0.222 0.287 0.141 0.149
H K CSI 17 0.146 0.054 0.174 0.041 0.127 -0.022
H K CSI 18 0.235 0.258 0.279 0.149 0.017 0.071
H K CSI 19 1.000 0.239 0.158 0.119 0.253 0.033
H K CSI 20 0.239 1.000 0.526 0.541 0.173 0.327
H K CSI 21 0.158 0.526 1.000 0.454 0.359 0.322
H K CSI 22 0.119 0.541 0.454 1.000 0.184 0.406
H K CSI 23 0.253 0.173 0.359 0.184 1.000 0.008
H K CSI 24 0.033 0.327 0.322 0.406 0.008 1.000
H K CSI 25 0.110 0.030 0.055 -0.128 0.025 -0.014
H K CSI 26 -0.115 -0.136 0.122 -0.086 0.040 -0.030
H K CSI27 0 032 0 104 0 039 0 052 0 064 0 105
Correlation
8/6/2019 Consumer Decision-Making Styles
100/123
Correlation M atrix H K C SI 25 H K C SI 26 H K C SI 27 H K C SI 28 H K C SI 29 H K C SI 30H K CSI 01 0.088 -0.098 0.087 0.010 -0.011 -0.057
H K CSI 02 0.076 0.040 0.096 -0.089 0.014 -0.020
H K CSI 03 0.039 0.056 0.075 0.022 -0.065 -0.043H K CSI 04 0.159 -0.010 0.054 0.013 0.041 -0.134
H K CSI 05 0.107 0.058 0.182 0.050 -0.016 0.122
H K CSI 06 0.150 0.116 0.119 0.117 0.005 0.026
H K CSI 07 0.236 0.108 0.300 0.097 -0.050 0.179
H K CSI 08 0.116 -0.002 0.108 0.090 0.011 0.115
H K CSI 09 -0.010 -0.095 0.015 0.021 0.019 -0.011
H K CSI 10 -0.114 -0.089 -0.121 -0.032 -0.029 0.023