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Module Code: INF6000 Registration Number 140135871 Family Name GU First Name LILI
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YONG CHINESE CONSUMERS PERCEPTION OF FASHION WEBSITE CO-CREATION STRATEGIES
A study submitted in partial fulfillment of the requirements for the degree of
MSc Information Management
at
THE UNIVERSITY OF SHEFFIELD
by
Lili Gu
September 2015
i
Contents
1. INTRODUCTION AND OVERVIEW ................................................................................................................ 1
1.1 RESEARCH BACKGROUND .................................................................................................................................................. 1 1.2 RESEARCH AIMS AND OBJECTIVES .................................................................................................................................... 4
2. LITERATURE REVIEW ...................................................................................................................................... 5
2.1 SOCIAL MEDIA MARKETING ............................................................................................................................................... 5 2.2 ONLINE SOCIAL NETWORK ATTRIBUTES ......................................................................................................................... 8 2.2.1 Information content ................................................................................................................................................. 9 2.2.2 Brand expression ..................................................................................................................................................... 10 2.2.3 Interactive communication ................................................................................................................................. 10
2.3 CONSUMER PARTICIPATION BENEFITS .......................................................................................................................... 11 2.3.1 Consumer learning value ..................................................................................................................................... 12 2.3.2 Social integrative value ........................................................................................................................................ 13 2.3.3 Hedonic value ............................................................................................................................................................ 13 2.3.4 Personal integrative value ................................................................................................................................... 14
2.4 UTILIZATION OF STIMULUS-‐ORGANISM-‐RESPONSE (S-‐O-‐R) FRAMEWORK ............................................................. 15
3. RESEARCH MODEL AND HYPOTHESES ................................................................................................... 17
3.1 EFFECTS OF STIMULI (S) ................................................................................................................................................. 18 3.1.2 Effects of information content ........................................................................................................................... 18 3.1.2 Effects of brand expression .................................................................................................................................. 19 3.1.3 Effects of interactive communication ............................................................................................................. 19
3.2 EFFECTS OF PARTICIPATION BENEFITS (O) .................................................................................................................. 20 3.3 CONTROL VARIABLES ....................................................................................................................................................... 20
4. METHODOLOGY .............................................................................................................................................. 21
4.1 RESEARCH APPROACHES .................................................................................................................................................. 21 4.2 DATA COLLECTION AND ANALYSIS ................................................................................................................................. 22 4.3 SAMPLING .......................................................................................................................................................................... 25 4.4 PRACTICALITIES AND ETHICAL ASPECTS ....................................................................................................................... 26
5. FINDINGS .......................................................................................................................................................... 27
5.1 UNIVARIATE ANALYSIS RESULTS .................................................................................................................................... 27 5.1.1 Characteristics of respondents .......................................................................................................................... 27 5.1.2 Attitudes toward fashion sites attributes (Stimuli) .................................................................................. 29
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5.1.2.1 Information content ..................................................................................................................................................... 30 5.1.2.2 Brand expression .......................................................................................................................................................... 30 5.1.2.3 Interactive communication ....................................................................................................................................... 31
5.1.3 Attitudes toward participation benefits (Organisms) ............................................................................. 32 5.1.3.1 Consumer learning value ........................................................................................................................................... 34 5.1.3.2 Social integrative value ............................................................................................................................................... 35 5.1.3.3 Hedonic value ................................................................................................................................................................. 35 5.1.3.4 Personal improvement ............................................................................................................................................... 36
5.1.4 Attitudes toward intention of future co-‐creation (Response) .............................................................. 37 5.2 BIVARIATE ANALYSIS RESULTS ....................................................................................................................................... 39 5.2.1 Crosstabs ..................................................................................................................................................................... 39 5.2.2 Reliability and validity .......................................................................................................................................... 41 5.2.3 Bivariate correlation .............................................................................................................................................. 43
5.3 MULTIVARIATE ANALYSIS RESULTS ............................................................................................................................... 44 5.3.1 Research model testing ......................................................................................................................................... 44 5.3.2 Hypothesis testing ................................................................................................................................................... 45
6. DISCUSSION ...................................................................................................................................................... 48
6.1 DISCUSSION OF ATTITUDES ............................................................................................................................................. 48 6.2 DISCUSSION OF RESEARCH MODEL AND HYPOTHESIS .................................................................................................. 51 6.3 DISCUSSION OF IMPLICATIONS ........................................................................................................................................ 53
7. CONCLUSION .................................................................................................................................................... 54
7.1 GOAL FULFILLMENT ......................................................................................................................................................... 54 7.2 CONTRIBUTIONS ............................................................................................................................................................... 55 7.3 LIMITATION ....................................................................................................................................................................... 56 7.4 RECOMMENDATION AND FUTURE RESEARCH ............................................................................................................... 57
8. BIBLIOGRAPHY ............................................................................................................................................... 58
9. APPENDIX ......................................................................................................................................................... 64
9.1 QUESTIONNAIRE ............................................................................................................................................................... 64 9.2 CONSENT FORM ................................................................................................................................................................. 69 9.3 ETHIC FORM ....................................................................................................................................................................... 72 9.4 ETHIC APPROVAL LETTER ................................................................................................................................................ 77 9.5 CONFIRMATION OF ADDRESS FORM .............................................................................................................................. 78 9.6 ACCESS TO DISSERTATION FORM ................................................................................................................................... 80
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Figures
FIGURE 1. THE RESEARCH MODEL BASED ON S-‐O-‐R FRAMEWORK ....................................................................................... 16 FIGURE 2. THE SELF-‐IDENTIFY BASED ON 160 PARTICIPANTS’ ONLINE INTERACTIVE ACTIVITIES. ................................. 28 FIGURE 3. THE COMPARISON ATTITUDES BASED ON 160 PARTICIPANTS TOWARD THREE ITEMS INVOLVED IN
INFORMATION CONTENT DIMENSION. ............................................................................................................................. 30 FIGURE 4. THE COMPARISON ATTITUDES BASED ON 160 PARTICIPANTS TOWARD THREE ITEMS INVOLVED IN BRAND
EXPRESSION DIMENSION. ................................................................................................................................................... 31 FIGURE 5. THE COMPARISON ATTITUDES BASED ON 160 PARTICIPANTS TOWARD THREE ITEMS INVOLVED IN
INTERACTIVE COMMUNICATION DIMENSION. ................................................................................................................. 32 FIGURE 6. THE COMPARISON ATTITUDES BASED ON 160 PARTICIPANTS TOWARD THREE ITEMS INVOLVED IN
CONSUMER LEARNING VALUE DIMENSION. ..................................................................................................................... 34 FIGURE 7. THE COMPARISON ATTITUDES BASED ON 160 PARTICIPANTS TOWARD THREE ITEMS INVOLVED IN SOCIAL
INTERACTIVE VALUE DIMENSION. .................................................................................................................................... 35 FIGURE 8. THE COMPARISON ATTITUDES BASED ON 160 PARTICIPANTS TOWARD THREE ITEMS INVOLVED IN HEDONIC
VALUE DIMENSION. ............................................................................................................................................................. 36 FIGURE 9. THE COMPARISON ATTITUDES BASED ON 160 PARTICIPANTS TOWARD TWO ITEMS INVOLVED IN PERSONAL
IMPROVEMENT AFTER INTERACTION IN ONLINE SOCIAL NETWORK. .......................................................................... 37 FIGURE 10. THE COMPARISON ATTITUDES BASED ON 160 PARTICIPANTS TOWARD TWO ITEMS INVOLVED IN
INTENSION OF FURTHER CO-‐CREATION. .......................................................................................................................... 38 FIGURE 11. THE SELF-‐IDENTIFY BASED ON GENDER. .............................................................................................................. 39 FIGURE 12. THE SELF-‐IDENTIFY BASED ON EDUCATION BACKGROUND. ............................................................................... 40 FIGURE 13. THE SELF-‐IDENTIFY BASED ON WORK EMPLOYMENT. ........................................................................................ 41 FIGURE 14. THE RESULTS OF THE RESEARCH MODEL. ............................................................................................................. 47
Tables
TABLE 1. QUESTIONNAIRE ITEMS ............................................................................................................................................... 25 TABLE 2. DEMOGRAPHICS OF THE SURVEY RESPONDENTS (N=160). ................................................................................. 27 TABLE 3. RESPONSES OF ATTITUDE SCALES TOWARD FASHION SITES ATTRIBUTES. .......................................................... 29 TABLE 4. RESPONSES OF ATTITUDE SCALES TOWARD PARTICIPATION BENEFITS. .............................................................. 33 TABLE 5. RESPONSES OF ATTITUDE SCALES TOWARD PERSONAL IMPROVEMENT. ............................................................. 34 TABLE 6. RESPONSES OF ATTITUDE SCALES TOWARD INTENTION OF FUTURE CO-‐CREATION. .......................................... 37 TABLE 7. RESULTS OF RELIABILITY AND VALIDITY TESTS. ...................................................................................................... 42 TABLE 8. RESULTS OF BIVARIATE CORRELATION ANALYSIS. .................................................................................................. 43 TABLE 9. FIT INDEX OF RESEARCH MODEL. ............................................................................................................................... 44 TABLE 10. STANDARDIZED PATH COEFFICIENT. ...................................................................................................................... 46
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Abstract
Background. The literature exposes the significant role of co-creation strategies through
social media interaction with consumers to brands in Web 2.0 era. Previous studies have
revealed the innovative co-creation in social media marketing was substituting
traditional marketing strategy. Moreover, researchers studied the factors motivating
consumer to participate into online co-creation.
Aims. This study aims to understand young Chinese consumer’s perception on
co-creation within fashion online social network for testing the hypotheses that attributes
of online social network generate consumer participation benefits to influence intention
of co-creation.
Methods. A questionnaire was generated, its construct based on the S-O-R research
model. Data was collected from web survey to 160 young Chinese fashion consumers
(18-35 age) who are followers of fashion brand account on Sina Weibo platform.
Results. Around 3/4 young Chinese consumers identified themselves as fashion
followers who read and watch information only in online social network. Except the
lower agreement on interactive communication, attitudes on other sectors are well, so
that slightly agreement on perceived social integrative value from interaction.
Environmental stimuli reflected significant influence to personal improvement, as well
as social media interaction has significant impact on changing the role of young Chinese
consumers in fashion area. Moreover, Young Chinese consumers slightly agree to
v
participant in future online co-creation. According to the relationship between intention
of future co-creation and the four perceived value from interaction, recent Chinese
fashion brand sites could assists intention of co-creation through consumer learning
value, hedonic value and personal improvement on certain degree.
Conclusions. It is conclude that even though minority hypotheses have not been
successfully supported, all the research objectives are achieved during research process.
Hence, a more appropriate research model and more scientifically sampling would be
desirable. Further studies could generate qualitative research to investigate the reason
why Chinese consumer’s intention of participating in co-creation is not as expected,
combining with Chinese cultural, marketing, fashion context.
vi
Acknowledgement
On the completion of my dissertation, I would like to express my deepest gratitude to all
those whose kindness and advice have made this study possible.
First and foremost, I am greatly indebted to my parents who fund my course of my
master program and my previously long-term education.
Then, I would also like to thank for my supervisor and personal tutor Dr. Jonathan J.
Foster, a respectable, responsible and resourceful scholar. His effective advice and
shrewd comments have guided the study to the valid direction. Undoubtedly, his keen
and vigorous academic observation enlightened me in my future study.
I shall extend my thanks to my friends, Lingfei Zhang, Zonglin Han, Yihang Gao, Jing
Zhang, Yanjing Sun, Jaiyang Tang, Xiaowen Zhang, Haiyun Sun and so on whose
guidance, assistance and company have accelerated and optimized the study in data
collection and data analysis. Especially, thanks for their friendships during the whole
academic year I have been residing in UK.
My sincere appreciation also goes to the participants who have responded the
investigation with great cooperation.
Last but not least, I would like to thank all my teachers and classmates from University
of Sheffield Information School for their constant encouragement and support
1
1. Introduction and Overview
1.1 Research background
Consumer information system is becoming a crucial strategy for corporates beyond
traditional customer relationship management in Web 2.0 era. It opens intriguing area
for future research such as value co-creation or changing consumer behavior from
passive to active (Sawhney et al., 2005; Tuunanen et al., 2013).
“Groundswell” is “a social trend in which people use technologies to get the things they
need from each other, rather than from traditional institutions like corporation” (Li &
Bernoff, 2008, p.9). This phenomenon was happened from three forces: people’s desire
to connect, new technologies, and online economic (Li & Bernoff, 2008). The earliest
utilization of Web 2.0 in 2005, which was proposed by O’Reilly (2005 cited in Tsimonis
& Dimitriadis, 2014) and defined by Constantnides and Fountain (2008 cited in
Tsimonis & Dimitriadis, 2014, p.329) as “a collection of open-source, interactive and
user-controlled online applications expanding the experiences, knowledge and market
power of the users as participants in business and social processes. Web 2.0 applications
support the creation of informal users’ networks, facilitating the flow of ideas and
knowledge by allowing efficient generation, dissemination, sharing and editing/refining
of the informational content.”
Social media, which born with Web 2.0, is increasingly becoming the significant tool in
consumer information system due to it creates huge potential for companies to reach
their customers and increase efficiency (Baird & Parasnis, 2011). The development of
2
Web 2.0 requires the companies to consider the new strategy on brand management by
utilized online social network (Shao et al., 2015). Following this trend, consumer
information systems development from traditional “end-user” turned to new consumer
potential effect. It requires invest interaction on requirements discovery, information
system development and service design (Tuunanen et al., 2013). To approve these
opinions, Constantinides (2013) draws consumer information system on social media
marketing. He outlines nature, effects and status of social media marketing in Web 2.0
market place.
Bring the requirement into fashion market, fashion is recognized as an innovative sector
which requires innovation diffusion (Foster, 2013) and other more effective marketing
strategies such as value co-creation. Fashion consumer could directly access plenty of
fashion information and share their experience with others (Brogi et al., 2013). Fashion
blogging involve different megaphone effect, but they are both effective way of access
to consumers (McQuarrie et al., 2013). Especially set sights on China, through the
western culture influence and Chinese economy growth in mainland, not only numerous
international brands continually enter Chinese market but also various local designed
brands established (Chan, 2015). Firstly, Chinese consumers who have later adoption on
fashion products seem to be the follower during innovation diffusion (Foster, 2013).
Secondly, fashion retailer and producer control the Chinese market trends (Law et al.,
2004). Therefore, on one hand, consumers have to collect reliable and suitable e-WOM
knowledge, which enable them to improve their behavior and style (Song et al., 2013).
On the other hand, Law, Zhang and Leung (2004) recommend fashion retailers should
encourage consumer’s participation and concentrate on consumer’s feedback in order to
3
attract the target consumers. Thirdly, through Web 2.0 development, the recent situation
reveals individualization trends exist in online social media, due to the rapidly growing
use of online journal style blogs instead of online discussion forums (Hodkinson, 2007).
These situations might make fashion blogging plays a valuable role on boosting
purchase (Pihl, 2014) and encouraging consumer interaction (Kulmala et al., 2013) in
recent fashion world. Educating, information sharing, and assisting consumers to
co-develop, become significant jobs for marketers in online consumer engagement
(Brodie et al., 2013). In order to establish long-term successful brands, marketers
become increasingly making great efforts to establish brand social network for their
consumers (Carlson et al., 2008). More and more companies begin to think about the
online customer platform in order to work on consumer engagement for the brand
(Verhagen et al., 2015). Sina Weibo.com is the most famous platform they want in
China, which involves numerous celebrities, business and individual accounts, to be
considered for consumer engagement and value co-creation.
Due to above phenomenon, an increasing number of studies are focus on discovering
co-creation strategies during consumer engagement in social media interaction.
Although not only value co-creation seems as a fresh concept in Chinese market, but
also Chinese consumes usually act as the follower on fashion innovation (Foster, 2013),
Chan (2015) indicates more and more citizens in Mainland China have awareness to
learn innovative information and try new products on fashion to become fashion leader.
Innovations and fashion trends are always starts with young adults, because they have
passions and courage on trying new things (Law et al., 2004). In addition, purchasing
powers of young consumers in China keep increasing due to their disposable revenues
4
are rising (Chan, 2015). Therefore, this research paid more attention on value
co-creation in consumer perspective during the stage of online consumer engagement.
From a theoretical perspective, the proposed research might add new understanding
about the young Chinese consumers’, who is aged 18-35, attitudes on value co-creation
in fashion social network interaction. From a practical perspective, the study might be
significant to provide new insights into the consideration of consumer information
system development through co-creation (Shao et al., 2015). Additionally, the research
results might be helpful on managerial aspect, such as for the fashion companies to
design their consumer engagement and co-creation strategy in Chinese market.
1.2 Research aims and objectives
This study aims to understand young Chinese consumer’s perception on co-creation
within fashion online social network for testing the hypotheses. In addition, it drives to
analyze the data of the research to understand Young Chinese consumers’ behaviors and
attitudes in social media interaction for further customer information system use. In
details, the research objectives can be explained as four topics:
1) Understand the self-identify of young Chinese consumers in social media interaction.
2) Investigate young Chinese consumers’ attitudes on participation in online social
network.
3) Examine the influence of social media interaction on the role of young Chinese
consumer in fashion market place.
4) Examine the young Chinese consumer awareness on future co-creation.
5) Examine the influence factors on future co-creation participation.
5
This research report is organized to displays as follows. The subsequent section reviews
historic literatures in four sub-phases to illustrate the theoretical background guiding the
research. Then, the next section posts research model and hypotheses, which indicate the
guideline of the investigation following behind. Afterwards, methodology is stated with
detailed research process and requirements. Subsequently, the results from data analysis
will be explained and followed with the discussion for interpreting findings. The paper
closes with goal fulfillment, contributions, limitations and the recommendation for
future research.
2. Literature Review
2.1 Social media marketing
Social media marketing, the products of “Groundswell” (Li & Bernoff, 2008), which
involves consumer engagement and value co-creation strategies in web 2.0 market place,
is developed in consumer information systems (Constantinides, 2013). Li & Bernoff
(2008) summarized five objects that businesses could pursue in groundswell linked to
traditional business strategies: 1) listening – research strategy of monitoring consumer
conversations instead of traditional surveys; 2) talking – marketing strategy of
stimulating interactive conversations; 3) energizing – sales strategy of motivating
enthusiastic consumer to help sell each other; 4) supporting – support strategy of
empowering consumer-to-consumer supports; 5) embracing – development strategy of
participating in social media interaction to come up ideas to improve innovation on
products and services. The five strategies are equally significant for companies but
6
“embracing” plays a decisive role on a brand’s highest expectation. Moreover,
Constantinides (2013) explains the four E-marketing levels depending on the progress:
product and service; marketing/ E-marketing organization; Web 1.0 Web site; and Social
Media marketing. In this concept, two approaches of marketing strategy are involved:
passive analysis of marketing intelligence and active public relation marketing. The
recent researches express the consideration of social media influence involved in
consumer information system development lie on the technical movement of web2.0. It
is easy to be found the development of web 2.0 create the advanced consumer
information system following with interdisciplinary challenges.
In order to achieve the best efficiency on implementation of social media marketing in
groundswell, there is an important element, which is called electronic word-of-mouth
(eWOM), could not be ignored. Researchers deem consumer engagement have to deal
with the non-transactional behaviors such as word-of-mouth, consumer supporting
between each other, customer retention and value co-creation (Verhagen et al., 2015).
Fashion blog are defined as a social media which involves enormous data of
consumer-to-consumer electronic word-of-mouth (Kulmala et al., 2013). Ashley and
Tuten (2015) likewise indicated Microblogs, socialized microsites and social networks
might be the most frequently used social media channels for the brand marketing
strategy choice, following with discussion forums and video sharing, because consumers
use these channels more than the others. Photo sharing, mobile applications and social
bookmarks are the less chosen forms on marketers perspective. The variety channels
involved in social media interaction produce eWOM containing a great deal of cognitive
information about brands, products and service among consumers. In this case, social
7
media is identified as a significant tool involving eWOM (Tsimonis & Dimitriadis,
2014). However, considering internet individualization trends and increasingly
significant role of consumer, Hodkinson (2007) deemed that the encouragement of
online interaction should be significantly focus more on individually centered pattern
(blogs). Sloan, Bodey and Gyrd-Jones (2015) supposes that consumer-to-consumer
communication as a type of co-production, it benefit to the corporate and consumer due
to the nature of knowledge sharing. An in-depth study illustrates that eWOM is
distinguished into organic and amplified. The organic eWOM expresses initial opinions
and ideas of social media users, but amplified eWOM might signify co-creation with
brands (Kulmala et al., 2013). In the study of Sawhney, Verona and Prandelli (2005),
they found co-creation on product innovation should be considered beyond the eWOM
in recent market progress.
Consumer engagement as a strategy for dealing with eWOM in social media marketing,
it should be discussed for assisting value co-creation. Sasinovskaya and Anderson (2013)
clarified that online brand communities could motivate consumer involvement and
facilitate product and marketing development. The development of online social media
marketing determines consumer engagement should be switched from collaborative
product innovation into traditional perspective into social media interaction in
co-creation perspective (Sawhney et al., 2005). To be evidence, the finding from Brodie
et al. (2013) study illustrates the link between consumer engagement and co-creation,
arise of perceived co-created value was found in consumer engagement research.
Co-creation is a general concept in e-commerce marketing management (Zwass, 2010).
It is also a significant basis of value to certain brand marketing so that consumer
8
co-creation experiences in social media place an important role for future co-creation
participation (Zhang et al., 2015). Some recent researches released that the interactions
in brand page link with the value co-creation strategy between brands and customer
(Shao et al., 2015). Online value co-creation is the most typical strategy, which relates to
“embracing” strategy in Groundswell (Li & Bernoff, 2008). To sum up, all the studies
indicated the recent trend of business strategy is the shift from one-way consumer
engagement to interactive value co-creation strategy.
2.2 Online social network attributes
Understanding the impact of Internet is much important to corporates’ social media
marketing, and the core points of this is the social media attributes influence on
consumer behavior (Constantinides, 2013). Initially, the attributes of online social
network, which attract consumers to participate into the brand online interaction, are the
precondition of effective consumer engagement. Brodie et al. (2013) claimed that
consumer engagement, which included participation and involvement, is an experiential,
interactive and context-dependent process. Consumer engagement is discussed into
several categories: affective engagement, cognitive engagement, and Behavioral
engagement (Dessart et al., 2015). This relates to consumer engagement, which involves
the design and management of online social network. The level of engagement is
influenced by the satisfaction of brand image, information content and interaction in
online community (Brodie et al., 2013; Nambisan & Baron, 2009). In other words, the
attributes of online social network have significant effect on consumer participation
(Martins & Patrício, 2013).
9
The historical studies provided some suggestions on the environmental stimuli for
consumer passive participation. Zhang et al. (2015) summarized the environmental
stimuli to be “task-relevant (TR) cues” (perceived information fit-to-task) and
“affection-relevant (AR) cues” (perceived visual appeal). On the brand angle, the brand
experience derives from brand-related stimuli such as brand-identifying elements. These
kinds of elements generate brand experience, which includes cognitions, sensorial and
behavioral responses (Chen et al., 2014). Moreover, Brands can be active participants in
social media, their passive participation might have potential to impact consumer
participation in social media interaction (Sloan et al., 2015). Martins & Patrício (2013)
believed that the attributes of social media could be the stimuli for passive participation,
and categorized these attributes into four broader segments: information content, prize
and enjoyment from activity, self-expression and communication. Considering the prize
and activity could be set into information content, the three environmental stimuli of
online social network would be discussed in details.
2.2.1 Information content
Branded fashion community is seems to be a significant channel to provide tips and
advice to fashion consumers (Foster, 2013). Fashion blog development trajectory can be
recognized as several perspectives, such as from private log to taste display, from
community to followers, from advising to modeling, from snapshots to high quality
images (McQuarrie et al., 2013). Kretz and Valck (2010) clarify in detail, several
well-known fashion blogs includes both literal implication and visual implication, but
the others contain explicit elements of storytelling. Hence, the balance on resistance to
10
sponsored content and expectation of fantastic story should be considered for better
interaction. In other words, audiences may not have negative reaction only when some
amplified content violates the typical style of that blog (Kulmala et al., 2013).
2.2.2 Brand expression
Considering the popular thoughts in brand management, customer loyalty can be
managed by social media interaction (Baird & Parasnis, 2011). Brogi et al. (2013)
explained the ‘brand associations’, such as “thoughts, feelings, perceptions, images,
experiences, beliefs and attitudes”, is becoming to be related to fashion brand in online
brand community members’ mind, due to they shared experience on social media. To be
specific, Dessart et al. (2015) generated online brand community engagement
framework. This framework shows the drivers, dimensions and engagement focus
during engagement process. It also points out that the outcome of community
engagement is achieved brand loyalty. Brand experience that customers perceived from
brand page are variable depends on several factors, and the interesting to the brand
might be the most significant one (Chen et al., 2014). However, consumers always
neglect initial passion on brand before they participate are the core issues in social
customer relationship management (Baird & Parasnis, 2011).
2.2.3 Interactive communication
Online social network provide a platform to customer to review and create essential
expressions of recent trends (Pihl, 2014). On the bloggers perspective, fashion bloggers
11
post what they want referring to each other in order to stay in touch with their follower.
Another study illustrates customers join into a brand communities are not just engaged
by a certain brand elements or brand culture, but also engaged by the members who are
congenial to them and attracted by the communities (Dessart et al., 2015). Even though
the influence from other members is significant, it is less efficient than
brand-image-related attributes on supporting the brand community (Carlson et al., 2008).
2.3 Consumer participation benefits
Consumer participation benefits as the outcomes from online consumer engagement in
consumer perspective are discussed in several studies. Verhagen et al. (2015) founded
consumer desired more personal benefits than engage with organization and other
consumers within the platform. Dessart et al. (2015) supported that all participants of
their study express active learning, endorsing and sharing behaviors in the brand
communities that they chose. The Uses and Gratifications (U&G) framework (Katz et al.,
1974 cited in Nambisan & Baron, 2009) identifies consumer benefits from participation
in online social network on four aspects: 1) cognitive benefits reflect information
acquisition; 2) social integrative benefits reflect interactive ties; 3) personal integrative
benefits reflect individual indentification; 4) hedonic or affective benefits reflect
enjoyable experience. Cognitive benefits which was also mentioned as information
benefits (Gummerus et al., 2012) or consumer learning value (Zhang et al., 2015), social
integrative value (Zhang et al., 2015) which is also called social benefits (Gummerus et
al., 2012) and hedonic value (Zhang et al., 2015) which is also named entertainment
benefits (Gummerus et al., 2012) are the components in consumer engagement. Base on
12
the framework of three experience components (Nambisan & Baron, 2009), Zhang et al.
(2015) utilized “pragmatic, sociability, and hedonic” components as the framework for
the study on co-creation experiences in social media.
2.3.1 Consumer learning value
The pragmatic dimension focuses on consumer real experience in cognitive benefits
during the process of acquire information in social media (Kohler et al., 2011).
Consumer engagement is initiated by consumer need for information (Brodie et al.,
2013). The learning value was highly mentioned (Nambisan & Baron, 2009; Zhang et al.,
2015) in several consumer benefits. In the social media interaction, the value consumer
learned information from social media interaction is called knowledge about the brand
that includes brand icon, product promotion, brand cultures, strategies, and value
proposition (Zhang et al., 2015). These facts acquired from brand-related learning forms
the nature of cognitive benefits and based on the interaction with the corporate
(Nambisan & Baron, 2009). However, there is perception gap between customer
self-cognition and reality on the reason why they interact with brands on social media
and follow their official sites. In other word, consumers are more willing to get
suggestions via social media in reality, but they suppose that they have more awareness
on getting discounts or purchasing products (Baird & Parasnis, 2011). The reason why
Internet, which serves for collaborative innovation with consumer, was recognized as a
powerful platform where innovation was been discussed, while consumer knowledge has
the most significant impact on innovation management (Sawhney et al., 2005).
13
Therefore, Zhang et al. (2015) regard pragmatic components as consumer learning
value.
2.3.2 Social integrative value
As similar as pragmatic dimension, sociability component relates to the relational phases
within the interaction between the brands and consumers in social media (Kohler et al.,
2011). It relies on the building and maintaining the relationship among the participants
including consumers and brands. Nambisan and Baron (2009) divide sociability
components into social network, social identity enhancement and the belongingness
perception. Tsimonis and Dimitriadis (2014) also believed brand page was a great place
for socialization and consumers could get value from visual relationships they
established. In fashion blogs, Pihl (2014) explains that fashion blogs is a type of
community that fashion bloggers and audiences share information and styles combining
several fashion brands. As well as this opinion, another study supports that audience's
purpose of providing, sharing and observing advice and tips are recognized as the
interactive function of fashion blogs (Kulmala et al., 2013). Hence, sociability
dimension is recognized as social integrative value by the researchers (Zhang et al.,
2015).
2.3.3 Hedonic value
A study argued beyond the sociological principles, brand community involves
psychological sense in some phases such as sharing consciousness, traditions and
14
responsibility (Carlson et al., 2008). The feeling experiences that consumer is stimulated
from social media interaction is considered as hedonic dimension of co-creation (Kohler
et al., 2011). Tsimonis and Dimitriadis (2014) explained the interactive activities on
online brand media made the users having fun with the whole process. As a popular kind
of online community, brand page using is a strategic marketing tool for a company
because its ease of use when customers access to brand pages (Chen et al., 2014).
Meanwhile, Hedonic and cognitive benefits are perceived, the free share of emotion and
opinion in feedback are recognized as the reason of hedonic benefits in online
community (Verhagen et al., 2015). The consumer interaction on social media could be
the source of enjoyable, interesting, entertaining, and pleasant senses which shape the
nature of hedonic benefits (Zhang et al., 2015). It is easy to be seen that there is a strong
link between hedonic value and social integrative value. Base on the concept of
Nambisan and Baron (2009), the hedonic components can be conceptualized as hedonic
value (Zhang et al., 2015).
2.3.4 Personal integrative value
Interactions in online social network would generate a sense of self-efficacy, also,
consumers who provide ideas and solutions requires hearing back from those who once
provided useful information (Nambisan & Baron, 2009). However, Chinese fashion
consumer play the role as fashion followers (Foster, 2013), they did not have more
confidence and personal idea to share styles and solve the questions. The study of
Thomas, Peters and Tolson (2007) released that personal style stressed the meaning of
designers and brands within social media. In the other words, style sharing as the nature
15
of fashion social network makes brands and designer notice the individual sense of style,
while they spread their fashion concept in social media. Consumer could learn and
improve their fashion sense during online interaction. Considering the Chinese fashion
context (Law et al., 2004), the individual components can be modified as personal
improvement.
2.4 Utilization of stimulus-organism-response (S-O-R) framework
Stimulus-Organism-Response (S-O-R) framework suggested that while a certain
encounter as a stimulus, the people react on it and develop internal organism that control
their responses (Mehrabian & Russell, 1974 cited in Lee et al., 2011). Lee, Ha and
Widdows (2011) developed their study rely on the framework to understand consumers
behaviors and reaction on products.
In e-commerce aspects, Fang (2012) built study on S-O-R framework in order to explore
the role of interactivity strategies in consumer decision-making through research
consumer behaviors. Moreover, Jai, Burns and King (2013) utilized S-O-R framework to
generate research model on consumers’ online shopping and their trust intention. Zhang
et al. (2014) also built the study on S-O-R framework in Chinese social-commerce, and
examined how the environmental stimuli of social commerce (stimuli) act on virtual
customer experience (internal organisms), to impact on social commerce intention
(external responses). Furthermore, Fang’s (2014) study investigated eWOM adoption in
social network sties through utilizing S-O-R framework as the adoption model.
To be specific on co-creation, Nambisan and Baron (2009) have used “interaction
characteristics – consumer benefits – participation” to test the mediation effects. They
16
also concluded the integrated framework could be applied in different context of
consumer value co-creation such as further participation in innovation support. Another
study (Zhang et al., 2015) based on this, to investigate how the influent attributes of
social media (S) influence co-creation experience (S) in order to understand the intention
on future participation (R) in China.
Obviously, S-O-R framework was generally utilized for the previous studies on
understanding consumer behavior. The Most of stimuli in previous studies were
identified as the attributes of certain environmental sector such as product attributes in
study on products, or social media attributes in study on online interaction. Moreover,
there are dimensions under stimulus and organism for multi-dimensioned test the
relationships the researches need.
Figure 1. The research model based on S-O-R framework
17
3. Research model and hypotheses
Based on the literature review, the research model is being presenting in Figure 1.
For the better understanding of the participation process of online consumer, S-O-R
framework is an appropriate theory due to it has been utilized in previous studies. The
design of the research model was enlighten by the concept, taken by Foster (2013), the
reason why Chinese consumers adopt fashion innovation lately as follower rather than
the leader is might because the preference of receiving tips and advices from social
media. Meanwhile, the research model was drawn on S-O-R framework (Nambisan &
Baron, 2009; Zhang et al., 2015) with fill items in different dimensions regarding to
historical studies.
Researcher modified the stimuli into three dimensions according another study from
Martins and Patrício (2013). They summarized previous studies and claimed that the
attributes of company social network that stimulate consumer participation depend
closely on their participation goal. They also categorized participation goals, five main
phases can be found are information content, brand expression, interactive
communication and activities participation. McQuarrie, According to fashion blog
develops more cultural impacts on consumers than its financial value (Miller & Phillips,
2013), this research ignored “activities participation” in financial aspects, in order to use
the S-O-R model to study the relationship between environmental stimuli and benefits in
cultural perspective.
Social research and social theory has a constant relationship. In other words, not only
conceptual framework informs research, but also our research and findings impact the
theorizing (May, 2001). Hence, in order to find some new and generate interesting idea
18
in the investigation of young Chinese fashion consumes, researcher considered “personal
improvement” as personal integrative value in the model. It is intent to investigate one of
the research question “Does social media interaction help to change the role of young
Chinese consumers in fashion market place?”
Independent variable is deemed as a cause, while dependent variable is deemed as an
effect (Weisberg & Bowen, 1977). Therefore, the relationships in research model could
be simplified as two pairs of effect-cause relationship in this model: 1) fashion sites
attributes as effect when participation benefits as cause; 2) participation benefits as
effect when intention of co-creation participation as cause. Except the core relationship,
the other relationships such as the sex, education and occupation on participants’
attitudes should be examined (Weisberg & Bowen, 1977).
Hypotheses that assume the certain situations cause the phenomenon (Weisberg &
Bowen, 1977) are necessary in this research. According to the historical studies and the
research model, the relationships between each two elements in the model could be
recognized as several hypotheses in this research.
3.1 Effects of stimuli (S)
3.1.2 Effects of information content
H1a. The information content as one of fashion site core attitudes is positively related to
the consumer learning value dimension of participation benefits.
H1b. The information content as one of fashion site core attitudes is positively related to
the social integrative value dimension of participation benefits.
19
H1c. The information content as one of fashion site core attitudes is positively related to
the hedonic value dimension of participation benefits.
H1d. The information content as one of fashion site core attitudes is positively related to
the personal improvement of participation benefits.
3.1.2 Effects of brand expression
H2a. The brand expression as one of fashion site core attitudes is positively related to
the consumer learning value dimension of participation benefits.
H2b. The brand expression as one of fashion site core attitudes is positively related to
the social integrative value dimension of participation benefits.
H2c. The brand expression as one of fashion site core attitudes is positively related to
the hedonic value dimension of participation benefits.
H2d. The brand expression as one of fashion site core attitudes is positively related to
the personal improvement of participation benefits.
3.1.3 Effects of interactive communication
H3a. The interactive communication as one of fashion site core attitudes is positively
related to the consumer learning value dimension of participation benefits.
H3b. The interactive communication as one of fashion site core attitudes is positively
related to the social integrative value dimension of participation benefits.
H3c. The interactive communication as one of fashion site core attitudes is positively
related to the hedonic value dimension of participation benefits.
20
H3d. The interactive communication as one of fashion site core attitudes is positively
related to the personal improvement of participation benefits.
3.2 Effects of participation benefits (O)
H4. The customer learning value dimension of participation benefits is positively related
to the intention of future participation in online value co-creation.
H5. The social integrative value dimension of participation benefits is positively related
to the intention of future participation in online value co-creation.
H6. The hedonic value dimension of participation benefits is positively related to the
intention of future participation in online value co-creation.
H7. The personal improvement of participation benefits is positively related to the
intention of future participation in online value co-creation.
3.3 Control variables
Community members who have strong passion to share their personal sense of fashion
might be the opinion leader in fashion market (Thomas, 2007). Four control variables
have been considered into research model: 1) gender; 2) educational background; 3)
occupation; 4) self-identify according to the explanation of people’s activity pattern in
groundswell (Li & Bernoff, 2008). The item of self-identify, as well as other three
control variables, is intent to be considered in whether the participant’s characteristic
seem to be more follower (Foster, 2013) or more leader, would differ their attitudes.
21
4. Methodology
This research is based on the positivism philosophy on epistemological consideration, or
in other words, it is regarding to objectivism in ontological orientation. The reason why
this research philosophy was determined is because it was built on the S-O-R model and
co-creation participation framework. According to Bryman (2008), objectivism is an
ontological view that believes the rules and regulation as the standardized practice for
developing social factors. This philosophy might ignore the intangible factors such as
cultural and organizational cause. This research removed the cultural and geographic
influences by developing the research process on recent model.
According to research objectives, the questions below might be investigated:
1) What is the role that young Chinese consumers define themselves on social media
according to their interactive behavior?
2) What are young Chinese consumers’ attitudes on participation in social network?
3) Does social media interaction help to change the role of young Chinese consumers in
fashion market place?
4) To what degree are young Chinese consumers willing to participate for co-creation
in the social media for fashion innovation?
5) How do online social network attributes associate with intention of co-creation
participation?
4.1 Research approaches
According to the philosophy and the process of this research, which has been intended to
22
utilize research model and hypothesis, it was accepted with a quantitative approach.
Moreover, a deductive theory is been set to guide the research due to the research was
built on the recent grounded theory in the studies of online social network participation
and value co-creation. The study considered a general view on online social interaction
and then investigated the fashion content to test the strength of the model in Chinese
cultural background. This is known as deduction where theorizing comes before
research (May, 2001). It was in a particular domain with a theoretical consideration in
this field to deduce hypotheses must be a deductive study (Bryman, 2008). For example,
this research summarized the online social network attitudes (Martins & Patrício, 2013)
into three dimensions as stimuli, utilized three participation benefits as the dimensions of
organisms (Nambisan & Baron, 2009; Zhang et al., 2015), and set personal improvement
as participation benefits. In order to understand their significant related to intention of
further participation in co-creation, S-O-R model (Zhang et al., 2015) was used to guide
the research. All the relationships are hypotheses based on the literature.
4.2 Data collection and analysis
This research collected and analyzed the primary data, intending to understand the
relationship between attributes of online social network and consumer participative
behaviors through investigating the consumer perception on online interaction in fashion
social media. Data collection utilized the quantitative method for quantitative data.
Initially, Social survey as one of the main methods of data collection in quantitative
research, its capacity is quantifiable data collection on a great deal of people who are
representative of the research population to test hypotheses (Bryman, 2004). The
23
research to young Chinese consumers, who are fashion fans, aged 18-35, chose the
fashion brand sites followers in Weibo.com (a Chinese blog site as similar as Facebook
and Twitter) as the people who were surveyed. Moreover, Academic survey as one type
of social survey, it prefers to gather information, which can be used to test or build
theory to explain behavior. In the other word, the outcomes of attitude surveys managed
the relationship between attitudes and behavior (Weisberg & Bowen, 1977). This
research not only intended to investigate their realistic perception on the intention of
online co-creation participation in recent Chinese fashion market, but also purposed to
understand the improvements that fashion sites need through examining consumers’
attitudes on online social network interaction. Therefore, survey was chosen to be the
research method in this academic research due to it is aimed at collecting data about the
attitudes related to social phenomenon (Weisberg & Bowen, 1977) and from a control
group of people (Bryman, 2004).
Anonymous online questionnaires were taken for participants’ convenience. I intended
to collect quantitative data with close-ended questions in structured approach in order to
understand participants’ perception and test the hypotheses. In questionnaire, the
questions towards consumers’ attitudes that base on the theory and recent journal finding
will be set into close-ended questions, which are significant for ease the data processing
(Bryman and Bell, 2011). This consideration is due to open-ended questions could only
indicate main opinion that participants hold, in other words, it can only reveal how
participants feel but cannot justify how strongly they feel (Social and Community
Planning Research, 1972). The questionnaire includes two types of questions: multiple
choice for data collection of control variables and Likert scale (Oakshott, 2014) for data
24
collection of independent and dependent variables will be considered as main types of
question. The questions of Likert scale have been designed as the statement sentences
for getting attitudinal responses instead of simply asking participants (Social and
Community Planning Research, 1972).
Sufficient statement of objectives guarantees the survey design can be formed to fulfill
the objective (Weisberg & Bowen, 1977). The first research question “what is the role
that young Chinese consumers define themselves on social media?” was considered in
design of Q4 (Appendix 9.1). The second research question “what effects young Chinese
consumers’ participation in social network, and what their attitudes on participation?”
was considered in design of Q5 – Q10 (Appendix 9.1). The third research question “does
social media interaction help to change the role of young Chinese consumers in fashion
market place?” was considered in design of Q11 (Appendix 9.1). The last research
question “to what degree are young Chinese consumers willing to participant for
co-creation in the social media for fashion innovation?” was considered in design of Q12
(Appendix 9.1).
In order to reduce comprehending deviation, I translated the questionnaire into Chinese
due to target participants are young Chinese people. A kind of Chinese online tool, as
similar as GoogleForm, was utilized in the process of data collection that involved
distributing questionnaire, collecting answers, and organizing information. All the data
and information of responses were recorded and automatically generated as a security
Windows Office Excel file in my online account.
The file was downloaded and the numeral data it contains are analyzed with Micorsoft
Office Excel, SPSS (Bryman and Bell, 2011; Bryman, 2008) and AMOS (Blunch, 2008).
25
Micorsoft Office Excel generated the univariate analysis (Bryman, 2008); data analysis
by utilization of SPSS20.0 was conducted for the bivariate analysis (Bryman, 2008), and
multivariate analysis was developed with AMOS21.0. The attitudes toward different
items were expressed in pie charts, bar charts and detailed tables. The comparison
between group attitude differences was generated to interpret relationships in
two-variable table (Weisberg & Bowen, 1977). Structural equation modeling (SEM)
approach (Blunch, 2008) was used in the data analysis to test the hypotheses and
research model.
Table 1. Questionnaire items
Construct Item Information content INFC1.The content is adequacy on quality and update frequency
INFC2. The content is informative and supportive for my needs
INFC3. The content on fashion site is chic and unique
Brand expression BREP1. The fashion sites is expressively excellent on products
BREP2. The fashion sites is expressively excellent on brand image
BREP3. The fashion sites is expressively excellent on brand culture
Interactive communication INTC1. The communication is easy and free
INTC2. The communication is responded and helpful
INTC3. The interactive atmosphere is positive and harmonious
Consumer learning value CLV1. My interactions enhance my knowledge about the products
CLV2. My interactions enhance my knowledge about the brand
CLV3. My interactions facilitate me to obtain event information
Social integrative value SIV1. My interactions expand my social network
SIV2. My interactions enhance the strength of my affiliation
SIV3. My interactions enhance my sense of belongingness
Hedonic value HEV1. My interactions are enjoyable and relaxing
HEV2. My interactions entertain and stimulate my mind
HEV3. I drive enjoyment from problem solving and idea generation
Personal improvement PSIP1. My interactions motivate my creative and sharing activity
PSIP2. My interactions inspired my innovation on personal style
Intention of co-creation IFCC1. I intend to further participate in interactions on fashion site
IFCC2. I am interested in participating in further interactions
4.3 Sampling
Our research objectives determine target population should match three conditions:
Chinese consumers; 18-35 age group; and fashion brand social network follower. The
amount of population is difficult to be recognized because there are no official results
26
satisfying all three conditions. Hence, purposive sampling, which is included in
non-probability sampling type, is used in this research, due to purpose of research is to
acquire the attitudes toward social media interaction from young Chinese consumers in
fashion market. Purposive sampling is also called judgmental sampling, because it
allows me to choose cases which might enable to meet research objectives (Saunders et
al., 2009). In practice, the fashion sites followers were almost centralized in the site
involving multiple brands information. The limited amount of users following the brand
sites would make data collection difficult in limited time period if probability sampling
has been utilized. Hence, web survey has been generated with non-probability sampling
(Callegaro et al., 2015). The logic for selecting cases is based on the purpose of this
research. For example, I contact friends who match the three elements and send massage
or email to the followers under a certain fashion brand accounts in Sina Weibo. Even
though this method could not guarantee the responses of the chosen cases are
representative of the population’s common attitudes, it is a cheaper method to find a
smaller and more practicable group as similar as the population (Weisberg & Bowen,
1977).
4.4 Practicalities and Ethical aspects
According to the study focus on young Chinese consumer’s perspective, I can easily
access to participants and take interaction with them. Considering the ethical issues for
the participants, all consumers be surveyed are adults. The most important issues need to
be considered is the survey included introduction of the research aim and objectives to
inform them the results are using for academic study. The languages in inform content
27
page is polite to invite their participation.
5. Findings
In order to developing a clear presentation of results regarding to research progress, this
study organize what I found from the data analysis in three parts: 1) univariate analysis
results would simply descript the significant responses from different sections; 2)
bivariate analysis results would show the results of reliability and validity tests and
significant bivariate correlation between each variables; 3) multivariate analysis results
would demonstrate the results from structural equation model to interpret the test of
research model and hypothesis.
5.1 Univariate analysis results
5.1.1 Characteristics of respondents
Table 2. Demographics of the survey respondents (N=160).
Demographics Category Frequency Percentage Gender Male 47 29.4 Female 113 70.6
Education High school or below 14 8.8 Undergraduate school 97 60.6 Graduate school and higher 49 30.6
Occupation Student 50 31.3 Working 95 59.4 Unemployment 15 9.3
Self-identify Spectator 122 76.3 Joiner 12 7.5 Collector 14 8.8 Critics 5 3.0 Creator 7 4.4
28
Initially, the data (Table 2) from web survey displays there are 113 female respond
questionnaires that is over twice as the number of male responses. It might indicate the
attention ratio of gender on fashion brand sites. Secondly, the responses on education
background centralize at “undergraduate school”, and then it is at graduate school. This
might due to the educational background support the learning awareness on fashion
innovation. Thirdly, there are 59% responses coming from the people who are working,
so the young Chinese people who have income might be the most important consumers
in fashion brand sites. Finally, Figure 2 shows the responses of “self-identify” from 160
participants. About three-quarter of participants regard themselves as a spectator who
only read and watch information (Li & Bernoff, 2008) in the fashion brand sites. It can
be recognized that young Chinese consumer are almost play a follower role in fashion
innovation.
Figure 2. The self-identify based on 160 participants’ online interactive activities.
122
12
14 5 7
I act as a spectator (read and watch information only)
I act as a joiner (aware to maintain my online probile)
I act as a collector (add tags to photos or web sites)
I act as a critics (comment on blog and contribute to experience sharing) I act as a creator (publish a blog and upload video you created)
29
5.1.2 Attitudes toward fashion sites attributes (Stimuli)
Table 3. Responses of attitude scales toward fashion sites attributes.
� Strongly Disagree
Partially Disagree
Slightly Disagree
Slightly Agree
Partially Agree
Strongly Agree Mean
INFC1
3.75% 6
0.00% 0
18.12% 29
25.62% 41
23.12% 37
29.38% 47 4.53
INFC2
1.88% 3
0.62% 1
19.38% 31
24.38% 39
23.75% 38
30.00% 48 4.58
INFC3
0.62% 1
8.75% 14
18.12% 29
26.25% 42
15.00% 24
31.25% 50 4.4
BREP1
3.12% 5
3.75% 6
12.50% 20
23.75% 38
23.12% 37
33.75% 54 4.61
BREP2
3.75% 6
3.75% 6
13.12% 21
28.75% 46
19.38% 31
31.25% 50 4.5
BREP3
3.12% 5
5.00% 8
18.12% 29
23.75% 38
18.12% 29
31.87% 51 4.44
INTC1
5.00% 8
6.88% 11
15.62% 25
25.00% 40
19.38% 31
28.12% 45 4.31
INTC2
5.62% 9
8.12% 13
25.00% 40
18.12% 29
15.62% 25
27.50% 44 4.13
INTC3
4.38% 7
9.38% 15
17.50% 28
21.88% 35
18.75% 30
28.12% 45 4.26
Number of participants: 160
The responses on attitudes toward fashion sites attributes have the highly similarity as
showed in Table 3. The top section of attitudes is “strong agree”, which means a number
of consumers are satisfied to the fashion sites on information content, brand expression
and interactive communication. Most responses shift in agreement part, almost little of
responses was dropped in “strongly disagree” and “partially disagree”. Moreover, the
responses on every sub-dimension reflects a significant drop on “partially agree”, the
reason why it occurs might be participants willing to choose the next option on “strong
agree” rather than “partially agree”. However, only the means of six sub-dimensions,
which are about information content and brand expression, are around 4.5 out of 6.0, the
other three sub-dimension of interactive communication have lower means around 4.2
out of 6.0. To find the reason of this, the finding can be showed in following three
30
dimensions of the environmental stimuli respectively.
5.1.2.1 Information content
Looking at the attitudes toward three sub-dimensions of information content, there is a
consistently increasing trend on degree of agreement and a similar agreement level
among three sub-dimensions (Figure 3). Nonetheless, the responses reflect a significant
difference between INFC3 and other two sub-dimensions on “partially disagree” and
“partially agree”. According to the statement of INFC3 “the content on fashion site is
chic and unique”, it might be assumed that the participations have different
understanding on the word “chic and unique”.
Figure 3. The comparison attitudes based on 160 participants toward three items involved in
information content dimension.
5.1.2.2 Brand expression
Moving to the attitudes toward three sub-dimensions of brand expression (Figure 4),
0
10
20
30
40
50
60
Strongly disagree
Partially disagree
Slightly disagree
Slightly agree
Partially agree
Strongly agree
INFC1
INFC2
INFC3
31
only about five participants choose “strongly disagree” or “partially disagree”. There is
not significant attitudinal divergence among three sub-dimensions. The coherent
increase and drop among three sub-dimensions with slightly individual change are found
from the data.
Figure 4. The comparison attitudes based on 160 participants toward three items involved in brand
expression dimension.
5.1.2.3 Interactive communication
According to the attitudes toward three sub-dimensions of interactive communication
(Figure 5), responses on three sub-dimensions express significant differences. Firstly,
INTC1 are the most welcomes sub-dimension due to it obtained the most responses on
“slightly agree”, “partially agree” and “strongly agree”. It means people feel interaction
on fashion brand site is easy and free. Secondly, INTC3 are the least welcome
sub-dimension due to it obtained the most responses on “partially disagree” and “slightly
0
10
20
30
40
50
60
Strongly disagree
Partially disagree
Slightly disagree
Slightly agree
Partially agree
Strongly agree
BREP1
BREP2
BREP3
32
disagree”. Accordingly, the satisfaction on fashion sites atmosphere is not on the similar
degree as the first sub-dimension. Thirdly, INTC2 obtain nearly similar amount of
responses on “slightly disagree” and “strong agree”. It might reveal a significant amount
of people believed the communication on fashion site is not very responded and helpful.
Only a little of participants answered “strongly disagree” and “partially disagree”.
Figure 5. The comparison attitudes based on 160 participants toward three items involved in
interactive communication dimension.
5.1.3 Attitudes toward participation benefits (Organisms)
The responses on attitudes toward participation benefits have the slight difference as
showed in Table 4. The same problem occurs as the preceding section, the responses on
every sub-dimension reflect a significant drop on “partially agree”. However, differ from
environmental stimuli, the attribute on three dimension of participation value are
distinctive. In this regard, the difference could be recognized from the means of their
0 5 10 15 20 25 30 35 40 45 50
Strongly disagree
Partially disagree
Slightly disagree
Slightly agree
Partially agree
Strongly agree
INTC1
INTC2
INTC3
33
sub-dimensions. The means of three sub-dimensions under consumer learning value are
around 4.6 out of 6.0 comparing with 4.0 out of 6.0 on social integrative value and 4.3
out of 6.0 on hedonic value. It is easy to be recognized consumer most agree they
perceived consumer learning value through the interaction in fashion brand sites,
following with hedonic value, then social integrative value.
Table 4. Responses of attitude scales toward participation benefits.
� Strongly Disagree
Partially Disagree
Slightly Disagree
Slightly Agree
Partially Agree
Strongly Agree Mean
CLV1 3.12% 5
4.38% 7
14.37% 23
22.50% 36
18.12% 29
37.50% 60 4.61
CLV2 3.12% 5
1.88% 3
12.50% 20
28.12% 45
21.25% 34
33.12% 53 4.62
CLV3 3.12% 5
1.88% 3
15.00% 24
24.38% 39
21.88% 35
33.75% 54 4.61
SIV1
4.38% 7
9.38% 15
24.38% 39
25.00% 40
16.25% 26
20.62% 33 4.01
SIV2
6.88% 11
9.38% 15
24.38% 39
22.50% 36
15.00% 24
21.88% 35 3.95
SIV3
5.00% 8
8.12% 13
18.75% 30
27.50% 44
18.75% 30
21.88% 35 4.13
HEV1
1.25% 2
6.25% 10
26.88% 43
19.38% 31
18.12% 29
28.12% 45 4.31
HEV2
3.75% 6
7.50% 12
20.62% 33
29.38% 47
11.88% 19
26.88% 43 4.19
HEV3
2.50% 4
10.00% 16
15.00% 24
25.00% 40
20.00% 32
27.50% 44 4.33
Number of participants: 160
Starting with an overview of personal improvement in Table 5, most of the responses on
the personal improvement section are distributed in “slightly disagree” and three “agree”
options. The responses on “strongly disagree” and “partially disagree” can be ignored
because few of answer are founded. Hence, the mean of personal improvement are
around 4.4 out of 6.0 which illustrate young Chinese consumers accepted the interaction
in fashion social media motivated their creative and sharing activity and inspired their
innovative idea on personal style. In other words, the responses partially answered the
third research questions “social media interaction help to change the role of young
34
Chinese consumers in fashion market place” immediately in general idea.
Table 5. Responses of attitude scales toward personal improvement.
� Strongly Disagree
Partially Disagree
Slightly Disagree
Slightly Agree
Partially Agree
Strongly Agree Mean
PSIP1
3.75% 6
5.00% 8
16.88% 27
26.88% 43
21.88% 35
25.62% 41 4.47
PSIP2
1.88% 3
1.25% 2
23.75% 38
21.88% 35
23.12% 37
28.12% 45 4.35
Number of participants: 160
5.1.3.1 Consumer learning value
With respect to attitudes toward three sub-dimensions of consumer learning value
(Figure 6), there is not significant attitudinal divergence among three sub-dimensions.
The important information is that almost 60 participants responded “strong agree” in all
three sub-dimensions. The responses on “strongly disagree” and “partially disagree” can
be ignored because few of answer are founded. It means a large percentage of people
make sure they learned more from interaction in fashion brand social network.
Figure 6. The comparison attitudes based on 160 participants toward three items involved in
consumer learning value dimension.
0
10
20
30
40
50
60
70
Strongly disagree
Partially disagree
Slightly disagree
Slightly agree
Partially agree
Strongly agree
CLV1
CLV2
CLV3
35
5.1.3.2 Social integrative value
Focus on attitudes toward three sub-dimensions of social integrative value, Figure 7
expresses a unique way comparing with the figures are mentioned before. Most of
responses centralize at two middle options, even though the responses on “agree” side
are more than “disagree” side, the data distribution illustrate participants are not very
approve the idea that they perceived social integrative value during interaction in fashion
brand social network.
Figure 7. The comparison attitudes based on 160 participants toward three items involved in social
interactive value dimension.
5.1.3.3 Hedonic value
Putting sights on attitudes toward three sub-dimensions of hedonic value (Figure 8), only
HEV3 at a predict level. Most of young Chinese consumers drive enjoyment from
problem solving and fashion idea generation. However, HEV1 received similar
0 5 10 15 20 25 30 35 40 45 50
Strongly disagree
Partially disagree
Slightly disagree
Slightly agree
Partially agree
Strongly agree
SIV1
SIV2
SIV3
36
responses on “slightly disagree” and “strongly agree”. A significant amount of people
cogitate interactions on fashion sites are enjoyable and relaxing. Moreover, HEV2 has
some “strongly disagree” or “partially disagree” answers and the most answers in the
middle “slightly” level. Hence, A great deal of participants did not believe interactions
entertained and stimulated their mind. It has the same situation with social integrative
value.
Figure 8. The comparison attitudes based on 160 participants toward three items involved in
hedonic value dimension.
5.1.3.4 Personal improvement
Particularly, recording to the responses on PSIP1, there are 43 (Figure 9) participants
answered “slightly agree”, which only got two more responses than “strongly agree”. In
general, people almost agree with interaction motivated his or her creative and sharing
activity. Moving to the data on PSIP2, the responses of “slightly disagree”, “slightly
agree” and “partially agree” seem on a closed percentage between 35 and 38 (Figure 9).
0 5 10 15 20 25 30 35 40 45 50
Strongly disagree
Partially disagree
Slightly disagree
Slightly agree
Partially agree
Strongly agree
HEV1
HEV2
HEV3
37
Comparing with PSIP1, PSIP2 obtained less agreement on interactions inspired
consumers’ innovative idea on personal style.
Figure 9. The comparison attitudes based on 160 participants toward two items involved in personal
improvement after interaction in online social network.
5.1.4 Attitudes toward intention of future co-creation (Response)
Table 6. Responses of attitude scales toward intention of future co-creation.
� Strongly Disagree
Partially Disagree
Slightly Disagree
Slightly Agree
Partially Agree
Strongly Agree Mean
IFCC1
5.00% 8
8.12% 13
26.25% 42
20.62% 33
17.50% 28
22.50% 36 4.05
IFCC2
6.25% 10
6.25% 10
20.62% 33
21.25% 34
21.25% 34
24.38% 39 4.18
Number of participants: 160
Turning attention to intention of future co-creation participation, the means of IFCC1
and IFCC2 are 4.05 out of 6.0 and 4.18 out of 6.0 (Table 6) that are both significant
lower than the preceding sectors. This might reveals the participants slightly intend to
0 5 10 15 20 25 30 35 40 45 50
Strongly disagree
Partially disagree
Slightly disagree
Slightly agree
Partially agree
Strongly agree
PSIP1
PSIP2
38
participate in future co-creation in fashion brand sites. The responses moderately
answered the last research questions “To what degree are young Chinese consumers
willing to participate for co-creation in social media” on some level.
Figure 10. The comparison attitudes based on 160 participants toward two items involved in
intension of further co-creation.
As can be seen from the bar chart, the numbers of responses on “slightly disagree”,
“slightly agree”, “partially agree” and “Strongly agree” on IFCC2 are similarly around
35 (Figure 10). Most of participants are moderately interested in participating in further
interactions on fashion site. However, even though the agreement answers occupied the
main part of responses, “slightly disagree” earned the most supporters which amount is
42 (Figure 10). It illustrates there are weighty amount of young Chinese consumers
would not join into the fashion brand online interactions in the future.
0
5
10
15
20
25
30
35
40
45
Strongly disagree
Partially disagree
Slightly disagree
Slightly agree
Partially agree
Strongly agree
IFCC1
IFCC2
39
5.2 Bivariate analysis results
5.2.1 Crosstabs
In order to find the answers to the research question, the responses on self-identify need
to be combinative analyzed with other control varieties.
Figure 11. The self-identify based on gender.
In particular, Figure 11 reflects the female participants have more awareness on
collecting fashion photos and websites in online social network. There is no obvious
relationship between participants’ gender and self-identify, because the answer from
male participants distributed at both ends, but the answer from female participants
distributed in the middle. To be interesting, the group of male consumer who chose
“creator” to be their self-identify occupies unexpected percentages on 42.9%, which is
40
significant higher than the other roles. It might reveal Chinese male consumers have
more innovative power on fashion idea than the female.
Figure 12. The self-identify based on education background.
On education geographic aspect (Figure 12), the data are expressing in a ladder-shaped
situation. It is easy to be found that the self-identify, from the spectator as fashion
follower to the creator as fashion leader, has a positive relationship on participants’
educational background on some degree. It might be seen as the higher educational
background they have, the more they act as fashion leader. Nonetheless, this description
only depends on the responses from participants who have highest or lowest educational
background. The responses from participants in undergraduate educational background
are at a flexible level.
41
Figure 13. The self-identify based on work employment.
As similar as dropping educational factors into self-identify, it can be simply deemed
work employment of participants has positive relationship on fashion innovation on a
certain degree (Figure 13). The responses from unemployed participants centralize on
more follower side and the percentage of these people expresses as a decreasing trend
when the participative activities in fashion brand sites shift to more creative. However,
this assumption is not totally reliable due to the responses from working people and
student involving an irregular and fluctuant nature.
5.2.2 Reliability and validity
In order to continue the analysis, the reliability and validity of the collected data should
be primarily tested.
42
Table 7. Results of reliability and validity tests.
Variables Indicator Standard loading CR AVE Cronbach's
Alpha Information content INFC1
INFC2 INFC3
0.876 0.870 0.876
0.907 0.764 0.910
Brand expression BREP1 BREP2 BREP3
0.877 0.903 0.859
0.911 0.774 0.912
Interactive communication INTC1 INTC2 INTC3
0.797 0.790 0.823
0.845 0.646 0.909
Consumer learning value CLV1 CLV2 CLV3
0.895 9.918 0.750
0.892 0.735 0.869
Social integrative value SIV1 SIV2 SIV3
0.851 0.922 0.914
0.924 0.803 0.931
Hedonic value HEV1 HEV2 HEV3
0.899 0.869 0.865
0.910 0.771 0.932
Personal improvement PSIP1 PSIP2
0.965 0.859 0.910 0.835 0.926
Intention of co-creation IFCC1 IFCC2
0.896 0.841 0.860 0.755 0.891
Cronbach's Alpha coefficient is also known as internal consistency coefficient. When the
coefficient is greater than 0.7, it could indicate that the reliability of questionnaire data is
in good order and condition. The Alpha coefficients of all variables’ sub-dimensions in
Table 7 are greater than 0.7, so all the collected data have sufficient reliability to be
analyzed in the following process. The coefficient in CR section reflects all the items in
each latent variable whether consistently explained the latent variable. In other words,
the CR coefficient reveals the reliability of questionnaire data. As same as Cronbach's
Alpha coefficient, the coefficients of all variables’ sub-dimensions in CR section are
greater than 0.7 in Table 7. It demonstrates the latent variables have a good composite
reliability. AVE reflects the amount of variations that are explained by each latent
43
variable immediately come from all the problems. When AVE are greater than 0.50, the
latent variable has good convergent validity. AVE coefficients in Table 7 are sufficient
to meet the criteria, so the convergent validity of the collected data is approved.
The values shown in Table 7 reveals that the survey to fashion sites followers in this
research satisfied the requirements of reliability and validity. The data from web
questionnaires could be studied continually.
5.2.3 Bivariate correlation
Table 8. Results of bivariate correlation analysis.
INFC BREP INTC CLV SLV HEV PSIP IFCC
INFC Pearson Correlation 1 .779** .760** .708** .682** .730** .691** .695** Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000 N 160 160 160 160 160 160 160 160
BREP Pearson Correlation .779** 1 .768** .768** .673** .714** .678** .697** Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000 N 160 160 160 160 160 160 160 160
INTC Pearson Correlation .760** .768** 1 .721** .809** .820** .781** .723** Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000 N 160 160 160 160 160 160 160 160
CLV Pearson Correlation .708** .768** .721** 1 .738** .754** .674** .747** Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000 N 160 160 160 160 160 160 160 160
SLV Pearson Correlation .682** .673** .809** .738** 1 .856** .833** .757** Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000 N 160 160 160 160 160 160 160 160
HEV Pearson Correlation .730** .714** .820** .754** .856** 1 .815** .795** Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000 N 160 160 160 160 160 160 160 160
PSIP Pearson Correlation .691** .678** .781** .674** .833** .815** 1 .765** Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000 N 160 160 160 160 160 160 160 160
IFCC Pearson Correlation .695** .697** .723** .747** .757** .795** .765** 1 Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000 N 160 160 160 160 160 160 160 160
**. Correlation is significant at the 0.01 level (2-tailed).
44
In Table 8, ** means correlation is significant at the 0.01 level. When the correlation
coefficient is positive, the relationship between two variables is positive. When the
correlation coefficient is negative, the relationship between two variables is negative.
The larger absolute value of the coefficient shows in the table, the higher correlation
exists between two variables. As we can see in the table, all the correlation coefficients
of the nine dimensions in research model are greater than 0.6, and is positive, which
indicates all the relationships between each two variables express as highly or
moderately positive correlation. In other words, while one variable increase, the other
one will also increase, and vice versa.
5.3 Multivariate analysis results
5.3.1 Research model testing
Table 9. Fit index of research model.
Index name Value Ideal standard
Absolute index
641.6
2.333 <3
GFI 0.795 >0.8
RMSEA 0.092 <0.08
Relative index TLI 0.892 >0.9
IFI 0.910 >0.9
CFI 0.909 >0.9
PGFI 0.623 >0.5
Parsimony index PCFI 0.769 >0.5
2χ
2 / dfχ
45
Absolute index partially reveals data interpretation capacity of the research model.
Relative index implies the advantage of research model comparing with the virtual
model. Parsimony index consider the absolute index and relative index of model
complexity.
By the influence of the complex model structure, the estimated coefficients and the
small sample size, the GFI = 0.795 (Table 9) is slightly lower than the ideally standard
indicator. However, the simple index PGFI goes beyond the ideal standard, and other
indices are also reach or close to the ideal standards. Taking into account the GIF index
is not the only principle to judge the value of research model, driving for perfect GIF
index might occur over fitting problem, so that the model is recognized to be acceptable.
5.3.2 Hypothesis testing
In Table 10, “estimate” reflect the estimated value of the path coefficients, the arrows
symbol reflects the influence direction, the absolute value of the coefficient reflects the
influence size, and SE reflects the estimated standard error, CR reflects the results of
significance test on T value (similar to the T value in regression coefficient test), P
reflects the critical probability of coefficient significance test. When P <0.01, it shows as
*** in the table, it indicates that the coefficient on the significance level 0.01 is
significantly different from zero. When P <0.05, it means the coefficient on the
significant level of 0.05 is significantly different from zero. When P < 0.1, it indicates
that the coefficient on the significance level 0.1 is significantly different from zero.
When P> 0.1, it means the coefficient has no meaning in the statistics. In the other words,
there is no evidence to prove it is significantly different from zero.
46
Table 10. Standardized path coefficient.
Estimate S.E. C.R. P
Consumer learning value <--- Information content .108 .111 .891 .373 Social integrative value <--- Information content .254 .114 2.180 .029 Hedonic value <--- Information content .348 .110 2.911 .004 Personal improvement <--- Information content .316 .120 2.637 .008 Consumer learning value <--- Brand expression .532 .113 4.245 *** Social integrative value <--- Brand expression -.135 .110 -1.170 .242 Hedonic value <--- Brand expression -.034 .106 -.291 .771 Personal improvement <--- Brand expression -.130 .116 -1.107 .268 Consumer learning value <--- Interactive communication .454 .060 6.966 *** Social integrative value <--- Interactive communication .926 .079 11.607 *** Hedonic value <--- Interactive communication .875 .070 11.506 *** Personal improvement <--- Interactive communication .882 .081 11.090 *** Intention of co-creation <--- Consumer learning value .235 .069 3.394 *** Intention of co-creation <--- Social integrative value .010 .125 .073 .942 Intention of co-creation <--- Hedonic value .459 .147 3.117 .002 Intention of co-creation <--- Personal improvement .270 .112 2.194 .028 Intention of co-creation <--- Gender .097 .120 1.892 .058 Intention of co-creation <--- Education -.031 .093 -.600 .549 Intention of co-creation <--- Occupation -.079 .091 -1.554 .120 Intention of co-creation <--- Self-identify .013 .051 .255 .799 *** p<0.01.
According to above description, information content has no significantly effect on
consumer learning value due to the coefficient is 0.108 which is closed to be zero.
Therefore, except hypotheses H1a, the approved hypotheses are H1b, H1c and H1d.
Moreover, Brand expression only has significant impact on consumer learning value,
because the other three coefficients are negative. As a result, only hypothesis H2a is
approved in this section. Meanwhile, the impacts of interactive communication to the
four variables are all to be seemed significantly. Accordingly, all hypotheses, H3a, H3b,
H3c and H3d, are approved in this dimension. To intention of future co-creation, the
greatest impact is Hedonic value, whose coefficient is 0.459. However, the impact of
social integrative value to the intention of further co-creation is almost at zero level.
47
Hence, the hypotheses H4, H6 and H7 are approved. In control variables, only gender
has a significant impact on the Intention future co-creation. All the significant influences
are showed in Figure 14 below.
Figure 14. The results of the research model.
* p<0.1, ** p<0.05, *** p<0.01; ns: non-significant at 0.1 level
48
6. Discussion
6.1 Discussion of attitudes
Based on 160 online questionnaires with followers of Weibo.com fashion brand sites
embedded on social media, this study developed a general view on the consumers’
online interaction participation of value co-creation in the context of fashion brand
social network, building on the stimuli-organism-response model with dimensions from
historical participation framework.
Consumers who participate in fashion brand social network included a numerous of
young consumers, in which female occupied more than three fifth proportion. Although
man’s fashion trend is making a big issue in globalization, female consumers are still the
main force of fashion market in China (Law et al., 2004). Within those young
participants, more than nine out of ten people identified themselves as a fashion follower
(Foster, 2013), who just collect and browse fashion information online (Li & Bernoff,
2008), only less than 10% people believed they act as a fashion leader in social media
interaction. Most of the participants showed a great agreement on the performance of
fashion brand sites, but some of them were slightly unsatisfied during interactive process.
The result in univariate also revealed participants’ educational background and
employment situation had positive relationship with their self-identify, but these
relationships have not successfully been tested in SEM program (Blunch, 2008). The
fashion leaders were commonly found in the group of people who was higher educated
and employed, this might be related the concept of groundswell. Groundswell was
happened from people’s desire to connect and online economic (Li & Bernoff, 2008).
49
The higher educated and employed group within young Chinese consumer had more
percipient (Law et al., 2004) and money (Chan, 2015) to accept global fashion news and
go shopping in abroad online store. Furthermore, the results expressed there was no
obvious relationship between participants’ gender and self-identify, but female were
more like a collector, male liked to be a pure follower or a creator.
Consumers’ attitudes revealed the participants partially agreed with the statements of the
attractive factors involved in fashion brand sites. Particularly, information content and
brand expression in fashion brand sites were more acclaimed than interactive
communication as the environmental stimuli. The result firstly proved participants had
positive reaction, because they thought the fashion sites got balance on sponsored
content and useful information (Kulmala et al., 2013). It also indirectly certified
interesting to the brand might be most significant reason for participating in a brand
social network (Chen et al., 2014; Baird and Parasnis, 2011). Moreover, the results
supported influence from interaction is less efficient than brand-image-related attributes
(Carlson et al., 2008). Additionally, participants slightly disagreed the communication
was responded and helpful, so brand should passively participate into the interaction in
order to potentially impact consumer participation (Sloan et al., 2015). From the above,
it is significant that enhances the quality of the sties’ attribution according to participants’
attitudes to stimulate participation in consumer engagement.
The participants also expressed their perceptions about the perceived value from
interaction in fashion brand social network. They were almost sure that they obtained
learning value (Gummerus et al., 2012; Nambisan & Baron, 2009; Zhang et al., 2015)
from interaction in fashion brand sites, and then was hedonic value (Gummerus et al.,
50
2012; Nambisan & Baron, 2009; Zhang et al., 2015) that involved the sense of
entertainment and pleasure. Some of them did not believe they could gain social
interactive value (Gummerus et al., 2012; Nambisan & Baron, 2009; Zhang et al., 2015)
from online interaction. Hence, the result, what average attitudes on social integrative
value expressed weaker than consumer learning value and hedonic value did,
demonstrated consumer desired more personal benefits than engage with organization
and other consumers on the platform (Verhagen et al., 2015). Furthermore, the finding
discovered the agreement on hedonic value might due to brand page are ease to use and
free to share (Chen et al., 2014; Verhagen et al., 2015). However, the similar attitudes on
three sub-dimensions of consumer learning value revealed the previous finding, what
consumer had more awareness on getting suggestion than getting discounts (Baird &
Parasnis, 2011), could not be accepted in this study. In conclusion, studying consumer
perceived value allows the environmental stimuli link to intention of future participation
in value co-creation.
Understanding consumers’ perceptions of their personal improvement after they
participate in the brand online interaction enrich the effectiveness of consumer
engagement. Most participants believed they had different degree of personal
improvement when they interacted in fashion brand sites. However, more of them
agreed the interaction motivate their activity which was also known as social media
influenced consumer behavior (Constantinides, 2013), less of them agreed the
improvement on cultural generating unique idea and fashion styles.
The young Chinese consumers’ attitudes on intention of future participation in fashion
brand online social network was lower than expected, but many participants expressed
51
they were interested in participating in further interactions.
6.2 Discussion of research model and hypothesis
Our findings extended the view of consumer participation in brand social network as a
multi-dimensional concept with fashions site attributes as stimuli, participation value as
organism and intension of future participation in co-creation as response. This is due to
consumer engagement (Verhagen et al., 2015) is the technique to deal with eWOM
(Ashley & Tuten, 2015; Tsimonis & Dimitriadis, 2014; Kulmala et al., 2013; Verhagen
et al., 2015) and value co-creation with brand (Gyrd-Jones, 2015; Sawhney et al., 2005;
Verhagen et al., 2015; Zwass, 2010) through consumer-to-consumer communication
(Kulmala et al., 2013) and consumer-to-corporate interaction (Shao et al., 2015).
Additionally, personal improvement on fashion concept and interactive activity was
considered into the organism for looking at the social media motivation on consumer
role in fashion diffusion and the influence of personal improvement on co-creation
participation, based on recent individualization trends and increasingly significant role
of consumer (Hodkinson, 2007). Relationships between different dimensions and sectors
were conducted in groups of hypotheses in this study. The results of hypotheses test
revealed the impacts between fashion sites attributes (Martins & Patrício, 2013),
participation benefits (Zhang et al., 2015) from online interaction, and intention of
co-creation participation.
In aspect of stimuli, the influences of three dimensions, which were information content
(Martins & Patrício, 2013), brand expression (Brogi et al., 2013; Dessart et al., 2015;
Martins & Patrício, 2013) and interactive communication (Dessart et al., 2015; Martins
52
& Patrício, 2013), to three dimensions of participation benefits and personal
improvement has been analyzed in the study. Firstly, information content had significant
influence on social integrative value (Kohler et al., 2011; Nambisan & Baron, 2009;
Zhang et al., 2015), hedonic value (Kohler et al., 2011; Nambisan & Baron, 2009; Zhang
et al., 2015) and personal improvement, but the influence on consumer learning value
was not been proved as well as the previous studies (Kohler et al., 2011; Nambisan &
Baron, 2009; Zhang et al., 2015) in young Chinese participants. Secondly, brand
expression in fashion social network merely took significant impact on consumer
learning value. The relationships between it and other three organism dimensions were
not founded. Thirdly, the results showed interactive communication not only affected
consumer learning value, social integrative value and hedonic value, but also influenced
personal improvement.
On organism side, participation benefits and personal improvement were considered as
the bridge between sites’ attributes and intention of participation in co-creation. Initially,
the result indicated consumer learning value had influence on consumers’ decision to
participate in future (Kohler et al., 2011; Zhang, et al., 2015). It might due to consumer
knowledge had the most significant impact on innovation (Kohler et al., 2011; Sawhney
et al., 2005). Coincidentally, hedonic value also could make young Chinese consumers
intent to join into online value co-creation (Tsimonis & Dimitriadis, 2014; Kohler et al.,
2011; Zhang, et al., 2015). Then, perceived personal improvement still could promote
consumer to have the will to further co-create with brand together. However, this study
get inconsistent results what the social integrative value had no significant impact on
intention of future participation with the previous study (Kohler et al., 2011; Zhang, et
53
al., 2015).
Putting sight into control variables, only gender had significantly invisible relationship
with young Chinese consumers’ intention of future co-creation participation.
6.3 Discussion of implications
The study findings had several theoretical and practical implications. For theoretical
implications, the study set self-identify to be one of control variables, to understand
young Chinese fashion consumers’ activities in social media, in order to optimize the
research construction. Moreover, this study combined information content, brand
expression and interactive communication as three main attributes of fashion brand
social media (Martins & Patrício, 2013), in order to perfectly find the results with
matching the characteristics of brand page in a certain social media which is the most
popular type of corporate-generated content, such as Weibo.com company sites,
Facebook pages, Instagram official account, and so on. Furthermore, personal
improvement was considered as an acquisition of consumer participation so as to
understand social media force on changing consumers’ role in fashion market place and
to investigate the impact of a practical fashion benefit on intention of future co-creation.
For practical implications, the recent interactive communication in fashion sites was
slightly weaker than its content and brand expression enlighten that providing and
sharing more tips and advices on fashion style as well as fashion bloggers do (Kulmala
et al., 2013; Pihl, 2014) will be a good choice for fashion brand in consumer
engagement.
54
7. Conclusion
7.1 Goal fulfillment
The study aimed to conduct a quantitative research for understand young Chinese
consumer’s perception on online social network and intention of co-creation. For the
research objectives, we tried to understand the self-identify of young Chinese consumers
in social media interaction; investigate young Chinese consumers attitudes on
participation in online social network; examine the influence of social media interaction
on the role of young Chinese consumer in fashion market place; examine young Chinese
consumer awareness on further co-creation; and examine the relationships between
online social network attributes and co-creation participation.
To respond to these objectives, deductive research has been taken with the structural
equation model in statistics is used to test hypotheses and analyze quantitative data from
160 young participants by web survey.
After mix-approached data analysis, all research goals are achieved after the research
has completed. Firstly, around three quarters young Chinese consumers identified
themselves as fashion followers who read and watch information only in online social
network. Secondly, young Chinese consumers attitudes are slightly satisfactory on
interactive communication. They also expressed slightly agree with they perceived
social integrative value from interaction. The attitudes on other sectors are well. Thirdly,
three environmental stimuli reflected significant influence on personal improvement. It
means social media interaction could help to change the role of young Chinese
consumers in fashion area. Fourthly, the responses reflected young Chinese consumers
55
slightly intent to participate in future online co-creation. Finally, according to the
relationship between intention of future co-creation and the four perceived value from
interaction, recent Chinese fashion brand sites could assist intention of co-creation
through consumer learning value, hedonic value and personal improvement on certain
degree. However, minority hypotheses have not been successfully tested such as H1a,
H2b, H2c, H2d and H5.
7.2 Contributions
This study has some contributions on the previous research. Initially, it considers
co-creation in online social network in the initial stage of consumer information system
design form interactive participation value perspective. Due to this study is set into
Chinese fashion market, the co-creation strategy in social media is developing in the
initial stage of consumer information management. This study, which found the general
ideas in consumer perspective, is significant on a certain degree to fashion brands’
online social media marketing plan. Furthermore, there is no studies link the interactive
communication to consumer perceived participation value. The study paid attention to
the influence of interactive communication on the value obtained from the interaction in
fashion brand sites. In other words, this study emphasized the importance of interactive
communication to co-creation with the content and brand expression in fashion brand
sites. Moreover, no studies considered personal improvement as an acquisition of
consumer participation. The study found the three dimensions of fashion sites attributes
all have significant influence on consumer personal improvement. This new finding
proved and extended our knowledge on function of social media. At the end, no study
56
researched the online social network interaction in fashion marketplace as a technique to
change the role of Chinese consumer. In the beginning of the research design, young
Chinese consumers were recognized as a force which break “more follower” ice in
Chinese fashion market. Considering social media to be the tool to train young
consumers could be a significant idea for the fashion brands in China.
7.3 Limitation
Admittedly, this study involves several limitations due to the limited time period and
acceptable lack of knowledge. Firstly, the quantitative research has some criticisms for
this research. For example, the determined dimensions with hypotheses develop a
non-natural and designed consciousness of accuracy (Bryman, 2008). The participant’s
real attitudes are supposed to be restricted into the structured survey. It might cause the
result of this research is artificial rather than real. Secondly, the most possible limitation
could be predicted in sampling. When non-probability sampling type was used, the
sample would be limited to represent the general idea of young Chinese consumer
(Weisberg & Bowen, 1977). Additionally, Human judgment will be accepted using
non-probability sampling method (Bryman and Bell, 2011). Moreover, the sample size
seemed a bit small. To avoid unreliability, the larger sample size relates to the smaller
sample error (Weisberg & Bowen, 1977). Conversely, only 160 responses received were
not enough to reflect research model perfectly, or in other words, the research model
could not be perfectly acceptable to explain the acquired data. Thirdly, the model on
co-creation is not very suitable for Chinese participants, because the Chinese people do
not well understand the co-creation strategy from their basic knowledge. Besides, the
57
social media is a kind of innovative tool for fashion brand use in China, co-creation is a
newborn concept in Chinese fashion marketplace.
7.4 Recommendation and future research
Avenues for further research in co-creation might also need utilization of the S-O-R
model and the framework of online social network participation to test the relationship
between the cause and value of consumer participation. This research only focuses on
the relationships among certain dimensions of online interaction participation. The
hypotheses are been tested to illustrate the influences. However, what extent the
influences are and how de different sectors impact on the co-creation should be
continually examined in future researches. Moreover, the reason why Chinese
consumer’s intention of participating in co-creation is not as expected can be further
investigated. The knowledge on fashion social media marketing in China are poor,
researchers need make more efforts on deepening and expending the comprehension on
the mentioned area. It requires more qualitative research for this topic.
For practical implication, fashion brands should be aware of the importance of creating a
social network interaction to value co-creation. How to use social networking sites to
please fashion brand’s consumers, has become a must be considered marketing strategy
in Web2.0. Particularly in China, the fashion brands marketers should pay more
attentions to online social marketing for developing online value co-creation strategy, in
order to design a more applicative consumer information system.
58
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Brodie, R. J., Ilic, A., Juric, B. & Hollebeek, L. (2013). Consumer engagement in a
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9. Appendix
9.1 Questionnaire
1. My gender
¨ Male ¨ Female
2. My educational background
¨ High school or below ¨ Undergraduate school ¨ Graduate school and higher
3. My occupation
¨ Student ¨ Working ¨ Unemployment
4. My self-identify of interactive activity in fashion sites
¨ I act as a spectator (read and watch information only) ¨ I act as a joiner (aware to maintain my online profile) ¨ I act as a collector (add tags to photos or web sites) ¨ I act as a critics (comment on blog and contribute to experience sharing) ¨ I act as a creator (publish a blog and upload video you created)
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5. Information content
The content is adequacy on balance in quality and update frequency
Strongly Disagree Strongly Agree
1 2 3 4 5 6
The content is informative and supportive for my needs
Strongly Disagree Strongly Agree
1 2 3 4 5 6
The content is chic and unique
Strongly Disagree Strongly Agree
1 2 3 4 5 6
6. Brand expression
The fashion sites is expressively interesting and excellent on products
Strongly Disagree Strongly Agree
1 2 3 4 5 6
The fashion sites is expressively excellent on brand image and fashion concept
Strongly Disagree Strongly Agree
1 2 3 4 5 6
The fashion sites is expressively excellent on brand culture and history
Strongly Disagree Strongly Agree
1 2 3 4 5 6
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7. Interactive communication
The communication on fashion site is easy and free
Strongly Disagree Strongly Agree
1 2 3 4 5 6
The communication on fashion site is responded and helpful
Strongly Disagree Strongly Agree
1 2 3 4 5 6
The interactive atmosphere on fashion site is positive and harmonious
Strongly Disagree Strongly Agree
1 2 3 4 5 6
8. Consumer learning value
My interactions enhance my knowledge about the products
Strongly Disagree Strongly Agree
1 2 3 4 5 6
My interactions enhance my knowledge about the firm and brand culture
Strongly Disagree Strongly Agree
1 2 3 4 5 6
My interactions facilitate me to obtain deal and event information
Strongly Disagree Strongly Agree
1 2 3 4 5 6
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9. Social integrative value
My interactions expand my social network
Strongly Disagree Strongly Agree
1 2 3 4 5 6
My interactions enhance the strength of my affiliation with this community
Strongly Disagree Strongly Agree
1 2 3 4 5 6
My interactions enhance my sense of belongingness with this community
Strongly Disagree Strongly Agree
1 2 3 4 5 6
10. Hedonic value
My interactions are enjoyable and relaxing
Strongly Disagree Strongly Agree
1 2 3 4 5 6
My interactions entertain and stimulate my mind
Strongly Disagree Strongly Agree
1 2 3 4 5 6
I drive enjoyment from problem solving, idea generation, and so on
Strongly Disagree Strongly Agree
1 2 3 4 5 6
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11. Personal improvement
My interactions inspired my innovative idea on personal style
Strongly Disagree Strongly Agree
1 2 3 4 5 6
My interactions motivate my creative and sharing activity
Strongly Disagree Strongly Agree
1 2 3 4 5 6
12. Intention of future co-creation participation
I intend to further participate in interactions on fashion site
Strongly Disagree Strongly Agree
1 2 3 4 5 6
I am interested in participating in further interactions on fashion site
Strongly Disagree Strongly Agree
1 2 3 4 5 6
Completed
Thanks for your participation and support ^_^
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9.2 Consent form
The University of Sheffield. Information School
Young Chinese consumer’s perception of fashion website
co-‐creation interaction.
Researchers Lili Gu
Information School
The University of Sheffield
E-‐mail: [email protected]
Tel: 07739864938
Purpose of the research This study aims to examine young Chinese consumers perception on fashion websites
co-‐creation strategies within social media interaction. In addition, it drives to analyze the
finding of the research to understand Young Chinese consumers’ perception for further
customer information system use.
Who will be participating? We are inviting Chinese fashion consumers between 18-‐30 who have used Social Media to track
and diffuse fashion trends.
What will you be asked to do? We will ask you to complete a brief demographics questionnaire so that we have a profile of our
participant group. Then we will conduct a 20 questions survay about how you think about
fashion content on social media.
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What are the potential risks of participating? The risks of participating are the same as those experienced in everyday life.
What data will we collect? We are digital data recording the questionnaire answer via Google form.
What will we do with the data? We will be analyzing the data for inclusion in my master dissertation. After that point, the data
will be destroyed.
Will my participation be confidential? We are anonymising the data and coding the computer files with a random number. No
identifying information will be retained.
What will happen to the results of the research project? The results of this study will be included in my master’s dissertation which will be publicly
available. Please contact the School in six months.
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I confirm that I have read and understand the description of the research project, and that I
have had an opportunity to ask questions about the project.
I understand that my participation is voluntary and that I am free to withdraw at any time
without any negative consequences.
I understand that I may decline to answer any particular question or questions, or to do any of
the activities. If I stop participating at all time, all of my data will be purged.
I understand that my responses will be kept strictly confidential, that my name or identity will
not be linked to any research materials, and that I will not be identified or identifiable in any
report or reports that result from the research.
I give permission for the research team members to have access to my anonymised responses.
I give permission for the research team to re-‐use my data for future research as specified
above.
I agree to take part in the research project as described above.
Do you agree to participate in this academic survey?
¨ Yes
¨ No
If Yes – The questionnaire is showing
If No – “I am sorry you could not participate in this survey”
Note: If you have any difficulties with, or wish to voice concern about, any aspect of your participation
in this study, please contact Dr. Angela Lin, Research Ethics Coordinator, Information School, The
University of Sheffield ([email protected]), or to the University Registrar and Secretary.
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9.3 Ethic form
73
74
75
76
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9.4 Ethic approval letter
