VALUE CO-CREATION AND INDUSTRY 4.0- A COMPARATIVE CROSS-CASE STUDY OF LUXURY VS. FAST-FASHION BRANDS - DIVA
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VALUE CO-CREATION AND INDUSTRY 4.0
– A COMPARATIVE CROSS-CASE STUDY OF LUXURY VS. FAST-FASHION BRANDS
Thesis for Two year Master, 30 ECTS
Textile Management
Dumitru Lopusneac
Thesis number: 2020.5.11
I
Title: Value co-creation and Industry 4.0: A comparative cross-case study of luxury vs. fast-
fashion brands
Publication year: 2020
Author: Dumitru Lopusneac
Supervisor: Olga Chkanikova
Acknowledgements
I would like to express my deepest gratitude to:
My supervisor, OLGA CHKANIKOVA, for her valuable advice and guidance without which this
project would have not succeeded.
My dearest family and friends, who supported me and helped me carry on with discipline in such
extraordinary times.
To my colleagues for their undivided attention during our seminars.
To the University of Borås who made sure that the research process is smooth and well-organised.
And at last, to myself, for everything else that was needed to get the job done.
IIAbstract: Consumers have changed their behaviour from passive roles to active ones,
demanding their beloved brands to be integrated into long-lasting customer-brand
relationships. With this ideology, which is the basis for the S-D logic, there is an on-going
scientific debate on the value co-creation phenomenon and its effects on sustaining long-term
brand-customer relationships in the context of the fashion industry. These effects are
considered to have the potential to sustain a competitive advantage and affect not only the
marketing of the fashion brands, but also other facets of such enterprises, including their
value and supply chains. Additionally, the world has been experiencing a steep increase in
technological innovation under the name of Industry 4.0, where machinery and human
labour become integrated into smart systems and consumers have the ability to influence
parts of brands which were not available before. Within this context, the interest of this
research is to explore the value co-creation phenomenon in relation to the I4.0 dimension in
the setting of two generic business models characteristic of the fashion industry (luxury vs.
fast-fashion). In exploring the interconnectivity of these two phenomena, this study takes on
the digital strategies of Burberry, Louis Vuitton, UNIQLO and Zalando, and assesses their
co-creative processes targeted towards their consumers. In doing so, this study is also aiming
at identifying the approaches of the chosen brands towards the I4.0 dimension and its
relevance towards the process of value co-creation.
In order to illuminate the co-creative processes within the digital strategies of the selected
brands and to accomplish the research goal, this study takes on a comparative cross-case
study methodology synthesising secondary data on both value co-creation and I4.0 as
separate phenomena. The secondary data on the digital strategies of the selected brands is
used within an existing model called “the Co-creation mix” which assesses the co-creative
processes of the brands based on six different criteria: co-creator, purpose, locus, intimacy,
time, and incentives. Interpreting the secondary data through such a model resulted in the
identification of two different approaches to co-creation and I4.0.
The findings indicate that the luxury case companies approach co-creation from a traditional
marketing perspective where digital consumer engagement is the main co-creative process,
whereas the fast-fashion case companies initiate co-creative processes designed to
accomplish goals that are more supply-chain related. This result also brings several
intriguing implications. First, the fast-fashion case companies are more technology-driven
and are more open towards the implementation of innovative I4.0 technologies within the
co-creative processes than the luxury case companies. Second, the consumer role in the co-
creation process seems to become less central the more the I4.0 dimension is involved. Third,
the model shows that the fast-fashion examples outperform the luxury examples at the
dimensions where the latter perform the weakest, such as intimacy and time. And fourth, the
study findings confirm the new research opinion that both industry segments have weak
areas which can be handled by taking on a mix of the two identified approaches, rather than
focus on the traditional one alone. Yet, these findings are not generalizable but only
illustrative, meaning that the study provides plausible hypothesis and future research
directions concerning value co-creation and I4.0 within the fashion industry context.
Keywords: co-creation; industry 4.0; fashion; luxury; fast-fashion.
IIITable of Contents
1 Introduction ........................................................................................... 1
1.1 Background .............................................................................................................. 1
1.2 Purpose and study structure ................................................................................. 2
1.3 Research question .................................................................................................... 3
1.4 Research scope and delimitations ......................................................................... 3
2 Industry 4.0 and its technologies ....................................................... 4
2.1 Front-end technologies ........................................................................................... 5
2.1.1 Smart Manufacturing .......................................................................................... 5
2.1.2 Smart Supply Chain ............................................................................................ 6
2.1.3 Smart Working ..................................................................................................... 6
2.2 Base Technologies.................................................................................................... 6
2.2.1 Internet of Things (IoT)....................................................................................... 7
2.2.2 Cloud Computing ............................................................................................... 7
2.2.3 Big Data Analytics ............................................................................................... 8
3 Value co-creation .................................................................................. 8
3.1 The origins ................................................................................................................ 8
3.2 The co-creating customer ....................................................................................... 9
3.3 Types of value co-creation ................................................................................... 11
3.3.1 Co-ideation and co-innovation ........................................................................ 11
3.3.2 Co-manufacturing and social manufacturing ............................................... 12
3.3.3 Co-design ............................................................................................................ 13
4 Research Methodology ...................................................................... 14
4.1 Research design ..................................................................................................... 14
4.1.1 Case study design.............................................................................................. 15
4.1.2 Method of case study analysis ......................................................................... 15
4.2 Method for secondary data collection ................................................................ 16
4.2.1 Case study sampling ......................................................................................... 16
4.2.2 Case study data collection ................................................................................ 17
4.2.3 The model ........................................................................................................... 17
4.3 Case study presentation: main co-creative strategies/practices of the chosen
luxury and fast-fashion brands ....................................................................................... 18
5 Results................................................................................................... 21
5.1 The luxury brands ................................................................................................. 21
5.1.1 Burberry .............................................................................................................. 21
5.1.2 Louis Vuitton ..................................................................................................... 24
5.2 Fast-fashion brands ............................................................................................... 27
5.2.1 UNIQLO ............................................................................................................. 27
5.2.2 ZALANDO SE ................................................................................................... 30
IV6 Analysis ................................................................................................ 32
6.1 Cross-industry segment analysis ........................................................................ 33
6.1.1 Co-Creator Type ................................................................................................ 33
6.1.2 Purpose ............................................................................................................... 34
6.1.3 Locus ................................................................................................................... 35
6.1.4 Intimacy .............................................................................................................. 36
6.1.5 Time ..................................................................................................................... 37
6.1.6 Incentives ............................................................................................................ 38
6.2 Industry 4.0 dimension ......................................................................................... 39
7 Discussion ............................................................................................ 40
7.1 Luxury case companies ........................................................................................ 40
7.2 Fast-fashion case companies ................................................................................ 41
7.3 Summarizing conceptual framework ................................................................. 43
8 Conclusion ........................................................................................... 46
8.1 Managerial implications ....................................................................................... 47
8.2 Limitations of the study ....................................................................................... 48
8.3 Suggestions for future research ........................................................................... 50
9 References ............................................................................................ 52
10 Appendices .......................................................................................... 64
10.1 Burberry digital campaigns (extensive description) ........................................ 64
10.1.1 My Burberry My Fragrance ........................................................................... 64
10.1.2 Burberry Kisses ................................................................................................ 64
10.1.3 Burberry Acoustic............................................................................................ 65
10.1.4 Burberry Bespoke ............................................................................................ 65
10.1.5 The art of the Trench ....................................................................................... 66
10.2 The BIQ study ........................................................................................................ 67
10.3 Profile information on brand case examples ..................................................... 67
Table of Figures
Figure 1: Model figure for luxury case brands.................................................................. 33
Figure 2: Model figure for fast-fashion case brands ......................................................... 33
Figure 3: Conceptual framework on luxury vs. fast-fashion towards value co-creation
and I4.0 .................................................................................................................................... 43
Figure 4: My Burberry My Fragrance ................................................................................. 64
Figure 5: Burberry Kisses ..................................................................................................... 64
Figure 6: Burberry Acoustic ................................................................................................. 65
Figure 7: Burberry Bespoke .................................................................................................. 66
Figure 8: Art of the Trench ................................................................................................... 66
V1 Introduction
1.1 Background
With the appearance of the Internet phenomenon and its aggressive integration in the day-to-
day life, the marketing landscape has changed dramatically, transitioning itself to the digital
realm and becoming a more of a socio-commercial activity (Hughes, Bendoni & Pehlivan,
2016). Together with the Internet, social media is another term that became so important in
the lives of companies and consumers, that it is now almost a synonym to “the Internet” term.
According to See-To & Ho (2014), the term social media is explained as being “a group of
Internet-based applications […] that allow the creation and exchange of user-generated
content”. Social media platforms, propelled by the Internet and digitalization, changed
consumer preferences and gave birth to a new phenomenon, digital consumer engagement,
which is a participatory social process. Nowadays, customer interactions with the brands are a
form of brand value, whereas digitalized platforms of engagements have become essential to
brand equity. Trough customer participation on the digital platforms, they now are
empowered to influence different facets of the brands and their offering, such as customizing
the initial design and opting for individualized deliveries of goods and services, among the
many other opportunities (Ramaswamy & Ozcan, 2016).
Due to the permanent impact that the Internet and Social Media had made on the current
society, a new direction of marketing had been given birth, the experiential one. It is based on
the new service dominant logic, abbreviated in the research literature as the S-D model,
according to which there is a continuous exchange of value between the brand and the
customers as long as both parties are interacting, while the product/service offering serves as
the starting point for the future brand-customer relationship (Payne, Storbacka & Frow, 2008).
In other words, companies are no longer simply producing goods and delivering them to the
marketplace, but they are creating a conversation with their environment and their customer,
providing a different, a more enhanced, special, and experiential shopping experience
(Occhiocupo & Friess, 2013).
Starting from the previous idea that the relationship between the buyer and the seller has
shifted from a commercial transaction to a personal connection, the consumers are now
becoming an integrated part of the brands they love/purchase/follow due to their associations
they have with the brands, which as a consequence motivates consumers to contribute to the
brand image and actively create value (especially in the context of online marketing) (Hughes,
Bendoni & Pehlivan, 2016). This phenomenon is now called “value co-creation”, which is the
process where the consumer and the brand are intimately involved in a relationship in which
they jointly create value that is unique for the consumer and sustainable in the long-term
perspective for the brand (See-To & Ho, 2014).
Additionally, the Internet has allowed for the society to transition to the Forth Industrial
Revolution, or I4.0, which enables creating a cyber-physical environment where multiple
elements are operating in a synchronized manner. More specifically, I4.0 technologies enable
an environment where a system of machines is interconnected via the Internet and where
these machines communicate with each other synchronically. In other words, a manufacturing
system with I4.0 technologies is able to monitor its physical processes by creating a so-called
“digital twin” of its physical world, where the system makes smart decisions through real-
time communication and real-time cooperation between all parties involved (Zhong, Xu,
Klotz & Newman, 2017). Moreover, the Internet of Things, or IoT, is the digital technology
1that binds a manufacturing system together through a single Internet connection and enables
I4.0 in itself, this way connecting devices, machines, humans, sensors, services, and other
technologies in a single entity. Such an entity brings intelligence to physical machines and
devices, making them smarter through the connection they all share and the exchange of
information that takes place (Nguyen & Simkin, 2017).
These two concepts, value co-creation and I4.0, are considered together for several reasons,
the major one being the fact that while co-creation as a strategy promotes a consumer-centric
view to business within brands, I4.0 is believed to facilitate innovative methods of co-creation
and sustain its consumer-centricity. According to Adamik & Nowicki (2018), I4.0
technologies drive innovation to the level where brands discover new ways of co-creating
value with different stakeholders, including their customers. Moreover, the brands who strive
for efficient co-creative strategies need to know the consumers’ expectations, needs, and
tastes as precisely as possible, and in times as digital as now, such external information can
only be provided by a correct use of I4.0 technologies (ibid.). Knowing that the modern
consumers have a much more participatory character and expect from brands more than just
their product offerings, Ross (2017) claims that the currently available digital technologies
have the potential of offering several types of co-creative values customers expect, such as co-
design, better body-fit and personalized choices of fabrics, trims, shapes, and styles.
Similarly, Ross (2017) acknowledges the relationship between the co-creative habits of the
modern consumers and their permanent usage of mobile devices, apps, and tablets, claiming
that the latter are enabled by digital technologies to serve as co-creative platforms. Moreover,
the omni-channel experience, which is more and more expected from the brands, is achievable
only through innovative I4.0 technologies (ibid.).
Therefore, this study builds upon the comparative cross-case qualitative methodology and
identifies common approaches to value co-creation and I4.0 based on the two types of
business models the four studied brands represent. Several studies such as Rai et al. (2012)
and Ross (2017) claim that a positive progression in the implementation of I4.0 technologies
within the fashion industry is observed, however, a big part of studies continue to highlight
the gap in research regarding I4.0 in the context of the fashion industry and its slowness of
implementation by the traditional brands of the industry (Bertola & Teunissen, 2018). Hence,
with these two paradigms together, value co-creation and I4.0, this study expects to contribute
to their scientific exploration and a more up-ward practical implementation within the fashion
industry.
1.2 Purpose and study structure
The purpose of this thesis is to qualitatively explore the concepts of value co-creation and I4.0
in the context of the fashion industry. As both concepts are relatively unexplored in the
fashion setting and remain to be under-researched even outside this particular industry
(Cossio-Silva et al., 2016), the luxury and fast-fashion brands used as case companies in this
thesis will facilitate a better understanding of the current stance and of the current progress
when it comes to value co-creation and I4.0 implementation in the fashion industry. This
industry in particular is known to be hesitant towards innovative technologies, and therefore,
looking at value co-creation in combination with I4.0, the latter being a synonym or a direct
referral to “innovation”, this thesis plans to provide insights into how these two concepts
influence each other and how they are currently implemented jointly by the case companies
(Bertola & Teunissen, 2018). By assessing the current approaches to these two constructs by
the chosen fashion brands, the study plans to find and develop new insights in regards to value
co-creation and I4.0 which will contribute to the current scientific debate on the subject.
2Moreover, the findings are expected to provide a clearer understanding in regards to these two
constructs for the industry practitioners and brand executives, a fact that is expected to
facilitate a better implementation of I4.0 and co-creation strategies within this industry.
To successfully accomplish the goals of this study, it is structured as follows: section 2 will
introduce the concept of Industry 4.0 in detail, will present its major technologies and all the
relevant literature covering them; section 3 will go further and will add another level of
complexity as value co-creation will be considered. In these two sections, value co-creation
and Industry 4.0 technologies will be analysed through a more targeted perspective, namely in
the context of the fashion industry, and the types of values created will be differentiated, as
well as the mechanisms of co-creating each of the values. Lastly, the study will empirically
analyse Burberry and LV (from the luxury side) and UNIQLO with Zalando (from the fast-
fashion side) with the help of an existing model in terms of value co-creative strategies and
I4.0 implementation degrees so that both differences and similarities are retrieved and
analysed.
1.3 Research question
As specified in the previous two sections, this research focuses on two constructs: value co-
creation and I4.0 technologies, and aims at qualitatively assessing the approaches towards
these two constructs by the chosen case-companies representing two major types of fashion
business models: luxury and fast-fashion. Therefore, the research question whose answer will
help achieve the purpose of the study is: How are value co-creation strategies and I4.0
technologies implemented by the chosen luxury and fast-fashion brands?
1.4 Research scope and delimitations
The scope of this study is limited to exploring approaches to value co-creation given two
dimensions: I4.0 with its technologies and the fashion industry. In regards to the first
dimension, its scope is determined by all the technologies described in the literature review
sections. The second dimension, the fashion industry, is defined by the two different fashion
business models, luxury vs. fast-fashion, and the 4 brands chosen as case companies
representing one of the two fashion business models. The research specifically focuses on
comparing implementation approaches of value co-creation in the fashion industry and to
learn the extent and the way in which I4.0 is currently employed in regards to value co-
creation within this context. By implementing a comparative cross-case study approach, the
findings are expected to be generalizable to the industry segments explored, namely, luxury
and fast-fashion. These specific two groups, luxury and fast-fashion, were chosen with the
idea that they are the most wide-spread and generic grouping criteria in the industry, a fact
that will not restrict but potentially enforce the generalizability of the findings.
Most importantly, this study limits the interpretative ability of the value co-creation process
only to those settings that directly involve consumer interaction. Such a co-creative setting
(operating on the brand-customer relationship) is extensively studied by the likes of Prahalad
& Ramaswamy (2004), Ind & Coates (2013), Choi et al. (2016). Therefore, the study looks
only at those value co-creative projects undertaken by the selected brands that directly involve
the brand customers. For the correct representation of such delimitation and study scope, the
study references to the 3-M framework developed by Gallaugher & Ransbotham (2010)
which considers three types of brand-customer interaction: firm-to-customer, customer-to-
firm, and customer-to-customer (ibid.). The co-creative relationship between the selected
brands and their suppliers falls out of scope as it would give the study a more technical
3approach (more characteristic of supply chain studies), whereas the current study looks at
value co-creation from a viewpoint pertaining to consumer behaviour and marketing research.
2 Industry 4.0 and its technologies
The world of business is changing fast and simultaneously from many perspectives. From the
one hand, global competition and market volatility is steadily increasing and customers are
demanding highly customised products while the product life cycles are known to be
dramatically decreased. The previous factors represent some problems of the current market,
showing that the existing ways of generating value and the traditional business models do not
suffice in meeting the current demands. From the other hand, the world is now experiencing a
dramatic technological progress that opens a wide range of new possibilities and opportunities
(Balaji & Roy, 2017; Hofmann & Rusch, 2017). When it comes to this technological
progress, the scholars associate it with the term of Industry 4.0, which gained so much
attention from scholars that it has registered under 1000 queries on scientific databases such
as Scopus, according to Chiarello et al. (2018).
As mentioned in the previous section, the Forth Industrial Revolution, or Industry 4.0 (also
abbreviated I4.0), is directly connected with a radical digital transformation. The
manufacturing/industrial progress brought about by these emerging digital technologies is
revolutionizing the traditional systems into smart ones. The smartness in this equation is
attributed to the cyber-physicality of the digital systems connected with each other via an
Internet connection and which are controlled by software integrating computers, networks and
physical processes (Kerin & Pham, 2019). The concept of Smart Manufacturing can be
explained as “an adaptable system where flexible lines automatically adjust production
processes for multiple types of products and changing conditions” (Frank, Dalenogare &
Ayala, 2019).
Additionally, I4.0 represents a system that transitioned from a computer controlled automated
facility into one capable of gathering and analysing data from the manufacturing process and
use it to make intelligent decision-making in an automated manner. This data, which was
unavailable before, now makes the traditional automated machines and processes more
intelligent as they are controlled by digital systems that track, analyse, and manage their
performance continuously (Ahuett-Garza & Kurfess, 2018). Chiarello et al. (2018) claim that
Industry 4.0 is not an entirely new technology, and not an old one either, but rather an
emerging one because it encompasses a combination of partly existing and partly new
technologies that together bring about an innovative system (ibid.).
When it comes to value co-creation and to this collaborative process between different
stakeholders motivated to generate additional value, Industry 4.0 technologies can be used in
this context in different departments or areas, such as Supply Chain Management (SCM),
Product Research and Development (R&D), and Marketing, in each case using different
technologies or different features they provide (Rai et al., 2012).
To introduce the main Industry 4.0 technologies, the framework developed by Frank et al.
(2019) will be used. According to it, an I4.0 system is separated in two categories: the “front-
end” technologies and the “base” technologies. The former category includes the technologies
that are responsible for the process of transforming the manufacturing activities based on the
emerging new technologies. The base technologies, however, have the main aim of enabling a
virtual connection between traditional and innovative technologies through the Internet of
4Things (IoT). To correctly set up an I4.0 system, the two categories should be given equal
importance so that their mechanisms work continuously and with joint support (ibid.).
Lastly, the fashion companies that incorporate I4.0 in their supply chains can also be
considered to have revolutionized their business models to the new one, called Apparel 4.0.
Gokalp et al. (2018) analyse the I4.0 paradigm specifically in the context of the fashion
industry and articulate that the Apparel 4.0 paradigm should be handled from two
perspectives: the production system and the managerial viewpoint (ibid.). Moreover, the main
benefits of an Apparel 4.0 business model are agility, transparency, increased quality,
productivity, and customer satisfaction, reduced operational costs and reduced order delivery
time (Jayatilake & Peter, 2016). The current challenges of implementing such a business
model is the high initial investment cost, privacy and security issues, technical challenges, the
lack of a global standard due to the newness of this concept, and lastly, social difficulties
related to the labour force (Gokalp et al., 2018; Barbu & Militaru, 2019; Barbu et al., 2019;
Gonzalo et al., 2020).
2.1 Front-end technologies
As mentioned in the previous sub-section, the front-end technologies are responsible for the
process of transforming the manufacturing activities based on the emerging technologies.
Smart Manufacturing, for instance, is the front-end technology that stays at the foundation of
all the other technologies. The base technologies, however, is the category that comprises the
technologies that create connectivity and give intelligence to the front-end technologies.
Hence, the front-end technologies also enable new ways the products can be offered (smart
products), the way raw materials and products can be delivered (smart supply chain), and the
way workers go through new functions and new roles acquired due to these technologies
(smart working). The base technologies are the ones that enable the concept of Industry 4.0
through system connectivity and create a fully integrated manufacturing system using the IoT
concept (Frank et al., 2019). Additionally, Apparel 4.0 and Smart Manufacturing changes all
of its departments by enabling new approaches to cutting, sewing, designing, quality control,
with innovative processes such as Digital Information Transfer, Predictive Maintenance, and
Human-Robot Technology Collaboration in the Cutting Department (Gokalp et al., 2018).
2.1.1 Smart Manufacturing
Smart manufacturing is considered to be the core of Industry 4.0 as it enables all other
technologies associated with I4.0 and is regarded as being a revolutionary manufacturing
system that connects the digital with the physical in Cyber-Physical systems (Zhong et al.,
2017; Ahuett-Garza & Kurfess, 2018; Xiong & Zhou, 2018). While the definitions of I4.0 and
its technologies are not described solely on their fundamental engineering principles, but
rather on the specific applications to various manufacturing and engineering operations
(Chiarello et al., 2018), this set of technologies is believed to greatly upgrade the design,
production, management, and integration of the whole life cycle of a product. The positive
impact of I4.0 paradigm on the numerous departments of a business is realized through smart
sensors, adaptive decision-making models, intelligent devices, data analytics, and advanced
materials (Pramatari, 2007; Zhong et al., 2017). Specifically with the help of smart sensors, a
smart factory is able to monitor and control equipment, conveyors and all the other parts of a
factory because the sensors record and send feedbacks containing an enormous amount of
continuously-flowing data. This data then is being processed and analysed by Big Data
Analytics tools, which in turn, updates the virtual models with the up-to-date information
about the physical processes taking place (Dalenogare et al., 2018). Due to the fact that Smart
5Manufacturing, or Smart Factory, uses service-oriented architecture via an Internet
connection, it makes it possible for companies to update their business models which can
provide collaborative, customizable, flexible, and reconfigurable services to their customers,
this way transforming their supply chains into highly integrated human-machine production
systems (Zhong et al., 2017).
2.1.2 Smart Supply Chain
This category of front-end technologies is meant to increase the efficiency and support the
complementary operational activities, especially those that are connected to the supply chains
of companies. While internal logistics is revolutionized under the concept of Smart
Manufacturing, external logistics can follow this process with the help of the Smart Supply
Chain dimension. According to Frank et al. (2019), Smart Supply Chain as a concept provides
efficiency to the relations outside the factory through a platform that shares all the relevant
information about manufacturing, warehousing, and transportation, which in the end, is the
same as horizontally integrating the company. Moreover, Hofmann & Rusch (2017) expect
three types of customer value to be achieved out of a correct implementation of the Smart
Supply Chain dimension. Firstly, if autonomous delivery is enabled by I4.0, it makes it
possible to make products and services available to customers at the desired time and place.
Secondly, it enables digital integration due to the transparency and full traceability provided
by the innovative technologies. And thirdly, the value of digital servitization extends the
length of the supply chain of a company. In other words, due to the innovative IT-
technologies that can retrieve customer post-purchase information that was unavailable
before, the sale of a product is not the ending point in the company-customer relationship
anymore (ibid).
2.1.3 Smart Working
When it comes to this dimension, its technologies aim at providing better working conditions
for the workers and enhance their productivity. Moreover, the access to the real-time shop
floor information takes humans and machines into an integrated socio-technical mechanism,
while the usage of digital and mobile devices provides the opportunity of remote control over
operations, improved decision-making and enhanced information visibility and transparency.
The augmented and virtual technologies are also included in this dimension because they
accelerate workers’ trainings with virtual simulations of maintenance routines, while
augmented reality also provides additional interactive guidance for different important tasks
with an increased complexity level. Product development stage is also positively influenced
through the opportunity of creating virtual models of products before starting the production,
omitting the constant need of creating physical prototypes (Frank et al., 2019).
2.2 Base Technologies
The base technologies, on the other hand, have the purpose of sustaining the virtual
connection between the physical and virtual technologies in one integral concept: cyber-
physical spaces (Ahuett-Garza & Kurfess, 2018; Frank et al., 2019). Moreover, the base
technologies such as IoT, Big Data and Cloud Computing have a big impact on the
managerial perspective. As part of the Apparel 4.0 paradigm, these technologies make it
possible for the retail businesses to enable new features such as End-to-end Digital
Integration, Wireless Sensor Networks, 3D Product Design, and multiple features enabling
real-time information registration and tracking within numerous business departments (ibid.).
62.2.1 Internet of Things (IoT)
If Smart Manufacturing was introduced as the concept which represents the essence of
Industry 4.0, Internet of Things, abbreviated as IoT, can be considered to represent the
operational principle of Smart Manufacturing and I4.0, respectively. In other words, IoT is
what enables Smart Manufacturing to operate. As Rupasinghe (2017) puts it, the process of
connecting objects and machines in a network with continuously-shared information makes
the system intelligent in the on-going decision making process. Lampropoulos, Siakas &
Anastasiadis (2019) provide a precise definition of what IoT is, claiming that “IoT can be
regarded as a dynamic and global network infrastructure based on standard and
interoperable communication protocols and with self-configuring capabilities” (ibid).
Frank et al. (2019) claim that IoT, Cloud Computing, and Big Data Analytics are base
technologies that support the front-end technologies and are categorized as being information
and communication technologies (ICTs) (ibid.). Nguyen & Simkin (2017) claim that although
IoT is a novel concept as the I4.0 itself (ibid.)., its developments will touch all industries and
fields, including the fashion context. Hence, it will directly affect the logistics department
because it will be revolutionized through real-time tracking of material flows, improved
transport handling, and more accurate risk management (Hofmann & Rusch, 2017).
Additionally, Bertola & Teunissen (2018) argue that the IoT technology finds its application
in retailing as well, where sensors placed in shopping spaces enable communication with
customers on multiple levels via their mobile devices (ibid.).
Interestingly enough, such sensors placed in the shopping spaces, which mainly operate on the
IoT technology, have also the potential to enable co-creation processes with the customers
present in such stores. According to Schuler, Maier & Liljedal (2019), in-store co-creation
through customers using their mobile devices to communicate their preferences, give
feedback, and eventually create new engagement opportunities, is all enabled by the sensors
operating on the IoT technology. Regardless of the vast ramifications of IoT in the fashion
segment which are broad and highly beneficial, their implementation is still staggering and
one reason explaining this is poor familiarity and knowledge of the fashion executives on the
I4.0 paradigm (Vass, Shee & Miah, 2018; Schuler et al., 2019)
2.2.2 Cloud Computing
Cloud computing is a technology that stores a big amount of data in an internet server
provider and makes it available for retrieval or use through remote access. The possibility of
remote access is specifically enabled by cloud computing technologies due to the integration
of different devices that make information easily accessible without the need to be
geographically present (Polyviou, Pouloudi & Pramatari, 2014). Lampropoulos et al. (2019)
state that cloud computing services are considered to be a type of “outsourcing that combines
large numbers of compute servers and resources with a view to offering computer programs,
high-level services and resources on an on-demand or pay-per-cycle basis”. Moreover,
enterprises of any sizes can cut costs by avoiding owning their own IT infrastructure and
invest in other resources by paying for the usage of Cloud Computing services on a “pay-as-
you-go” method (ibid). Lastly, cloud infrastructure allows companies to create a virtual copy
of their physical environment, this way ensuring data and information to be accessible and
manageable by administrative systems such as enterprise resource planning (ERP) and
production systems continuously (Damodaram & Ravindranath, 2010; Gokalp et al., 2018).
72.2.3 Big Data Analytics
Frank et al. (2017) state that while the combination of IoT and Cloud Computing permits
different devices to be connected with each other, the huge amount of data that is collected in
this process requires another technology to process it all. This I4.0 technology is known under
the name of Big Data Analysis. It is comprised of different tools such as machine-learning
and data mining enabling brands to keep track of real-time information and making sure that
all processes operate correctly. This, in turn, allows them to perform better at decision-
making, plan for future projects, develop predictive capacity and identify events that can
affect production before them taking place (ibid.).
When it comes to the nature of this big data, the previously mentioned article identifies four
characteristics that differentiate big data from traditional data, those being volume, veracity,
velocity, and variety (Frank et al., 2019). Regarding the “variety” characteristic of big data,
Acharya, Singh, Pereira & Singh (2018) and Liu & Zhang (2019) state that companies
implementing Big Data Analytics tools analyse different types of information, such as data
about products and/or services, people (such as customers and employees), and transactions.
Moreover, from analysing high volumes of data, companies can discover important insights
and data patterns that reveal customer tastes and preferences, which in turn, make calculated
enticement possible (ibid.).
Moreover, Big Data Analytics spans as an important element in the fashion industry too, and
fast-fashion is the concept that enforces the relevance of such technologies as data is growing
and changing at rates higher than in any other industry. Concerning the types of big data in
this industry, Jain et al. (2017) classify 5 of them: material-related data, fashion design data,
body data, colour data, and technical/production data. As one can intrinsically understand, and
as Chen & Luo (2016) and Acharaya et al. (2018) mention, the majority of big data
information is related to the preferential behaviour of customers, hence, material-related,
fashion design, body and colour data types are all related to what specific customer groups
prefer.
Besides understanding the preferences of customers and their ethnographic patterns, Big Data
Analytics enhances organizational capabilities in terms of decision-making efficiency and
correctness. For example, technologies such as RFID-enabled tags attached to garments allow
a systematic and serialized identification of manufactured and/or transferred goods, which in
turn, generates real-time operational and strategic data across the whole value chain. Hence,
Big Data Analytics provides an opportunity for knowledge co-creation in the sense that all the
generated and analysed data about customers, personnel, and other stakeholders, can be
exchanged between the whole value chain, facilitating better operational, organizational, and
economic value for businesses (Chen & Luo, 2016; Zaki et al., 2017; Acharaya et al., 2018;
Barbu & Militaru, 2019).
3 Value co-creation
3.1 The origins
The traditional marketing model, also called the producer-consumer model, or the goods-
dominant logic (Payne et al., 2008) is explained by the old-fashioned situation in which the
business activity is centred on the company producing, providing and pushing goods and
services to consumers solely to be consumed (Occhiocupo & Friess, 2013). However, with the
Internet and the social media channels, a new logic of marketing had been given birth and has
been implemented by an increasing number of companies, including fashion brands.
8According to this service-dominant model, abbreviated in the research literature as the S-D
model, there is the centrally focused idea that the service provided by the product and the
company is the common denominator in exchange between these two parties (Payne et al.,
2008). In other words, companies are no longer simply producing goods and delivering them
to the marketplace, but they are creating a conversation with their environment and their
customer, providing a different, more enhanced and more special, shopping experience
(Occhiocupo & Friess, 2013; Fernandes & Remelhe, 2015). Payne et al. (2008) argue that the
co-creating customers are not only active, but permanent generators of value, both to
themselves and to the enterprises they are interacting with. Moreover, value creation can
either be instrumentally created with the help of intentionally-used technologies and tactics, or
it can emerge organically and continuously from customers’ experiences (Gronroos, 2012).
Consequently, with this change in perspectives and a development of a new paradigm, value
co-creation served as a means to not only create new competitive advantage, but also see
customers as active participants in value creation (ibid.). This enables an enormous amount of
new business opportunities and long-term brand growth (Payne et al., 2008).
3.2 The co-creating customer
The new marketing wave of research focuses on the “empowered” consumer who demands
brands to provide more than just the product, but to provide intimate and unique experiences
through cooperation and most importantly, through inclusion (Payne et al., 2009; France et
al., 2015; Millspaugh, 2016). Hoyer et al. (2010) identifies four different types of motivation
customers have for co-creation: financial, social, technical and psychological. On the one
side, the financial motivation is triggered solely by a monetary prize during or after the
completion of the co-creation process, while the technical motivation revolves around the
expected information and skills to be gained as a result of co-creation. On the other hand, the
social motivations are triggered by the desire to enhance personal reputation, social esteem,
and build relationships with other community members, whereas the psychological
motivations, which are much harder to determine, are related to the intrinsic value in the form
of pride, self-expression, and the desire to contribute creatively (Etgar (2007); Nambisan &
Baron, 2009; and Hoyer et al. (2010), cited in Ochiocupo & Friess (2013)).
In this sense, Romero & Molina (2011) define value co-creation as a collaborative or
cooperative process in which there is a relationship between two or more entities which have
an extensive access to each other’s resources and are committed to work for a common cause.
Consequently, the consumers are now becoming an integrated part of the brands they
love/purchase/follow due to their associations with the brands, which as a consequence
motivates consumers to contribute to the brand image and actively create value (especially in
the context of online marketing) (Hughes, Bendoni & Pehlivan, 2016). Moreover, engaging
consumers is considered to be an imperative factor in enabling a continuous dialogue and the
consequent co-creation of value, which in fact, brings hedonic and experiential benefits to
consumers on the one hand, and strengthens the brand equity from multiple perspectives on
the other hand. For example, if brands successfully maintain brand-customer co-creative
relationships with consistent engagement, then they can capitalize through sales growth, cost
reductions, brand referrals, enhanced collaborative product development processes, enhanced
co-creative experiences, and overall, superior profitability and sustainable competitive
advantage (Hollebeek et al., 2016).
Similarly, the collective identities of consumers resulted within such a virtual community can
influence the brand identity and shape a certain behavioural attitude towards a brand. This is a
process, a result, or even a consequence, that revolves around cognitive activities of
9developing social links, collectively building cultural worlds, and partaking in brand rituals
and tradition in the process of co-creation and brand-customer engagement. This way, co-
creative customers have some control over the identity of a brand which is co-developed
during the co-creation process (Black & Veloutsou, 2017).
According to Barbu & Militaru (2019), the most common motive customers have when it
comes to the desire to collaborate with a brand is triggered by dissatisfaction with the current
offering and hence the motivation to give feedback and suggestions so that the company
improves it (ibid.). Companies even use consumer groups to co-create a brand’s ideology and
help develop the correct brand persona (Black & Veloutsou, 2017), and even more, the co-
creating customers create “communities” to draw attention on core brand competences by
participating in new product development (NPD), where their feedback, preferences,
suggestions and solutions are taken into consideration (Romero & Molina, 2011). Such co-
created value is considered to be of product-related nature because customers interact with the
motivation and interest surrounding the product within any moment of its value chain
(Nambisan & Baron, 2009).
In this sense, Black & Veloutsou (2017) introduce the concept of “working consumers” who
voluntarily allocate their time, talent, immaterial labour, experience and information to create
value for brands and organizations, this way contributing with cultural and affective value to
market offerings. Regarding co-creating brand meaning in form of identity and reputation,
these active and working consumers are believed to contribute in two main ways. First, by
either expressing their opinions, assessments and experiences with the brands, this way
becoming an uncontrolled source of information effecting brand reputation, or second, by
becoming more involved in the development of the brand and its products, this way producing
signals that “wider audiences perceive as originating from the brand” (ibid.).
Additionally, keeping the brand audience engaged through a two-way communication on
social media, Kim & Ko (2012) believe that brands stay relevant among their competitors and
most importantly, they create an opportunity to strengthen their relationship with customers,
reach new and younger audiences, and even reduce misunderstanding and prejudice towards
them if previously created (ibid.). Brand experience has become an imperative type of value
that customers expect and demand (Gentile et al., 2007), and digital consumer engagement
and social media interaction can provide such value through engagement- and consumer-
driven brand content and dialogue (Kim & Ko, 2012; Godey et al., 2016; Kim & Sullivan,
2019).
Similarly, Godey et al. (2016) claim that brands group social media into two groups
depending on the content their customers expect to receive and on the type of connection and
interaction: profile-based and content-based. The former group focuses on its members by
creating information and topics that strike common interest, create engagement surrounding
such content and provide an opportunity for the members to connect with each other. The
latter social media group, the content-based one, deals with providing consumers a more
entertaining content on which discussions and dialogue are provoked by the positive feelings
emerged from the content (ibid.). Such an example is co-creation in the context of luxury
fashion brands, where Choi et al. (2016) claim that one of the favourite types of content
luxury consumers react to is the art-inspired one, such as art-related activities or events and
art-inspired products, artistically constructed store facilities, and artist collaborations (ibid.).
10Additionally, luxury consumers are known to engage with their luxury brands in co-creation
in the form of user-generated content created by them on social media channels. By sharing
brand-related media content such as photography and video with each other, luxury
consumers co-construct brand meaning as they share their personal brand experience. This
way, the brands are only indirectly involved in such a process whereas the engaged consumers
are driven by the motivation to associate with their beloved luxury brands for self-
presentation and self-acclamation. Moreover, other reasons to co-create with luxury brands by
sharing user-generated content on social media are information dissemination, intrinsic
enjoyment, community participation, and social interaction, which in turn, extend the brand
experience temporarily and spatially into the virtual environment (Occhiocupo & Friess,
2013; Koivisto & Mattila, 2018). Furthermore, storygiving is another innovative
communication strategy used by luxury brands wishing to establish meaningful relationships
with their customers by revealing the history of the brand or an important event in a narrative
tone that expresses the brand’s point-of-view. Interestingly enough, and compared to the
storytelling strategy, storygiving is operating on the basis of user-generated content resulted
from the interaction of consumers within branded digital communities. In other words,
consumers share content that expresses the brand’s identity seen from their own eyes, which
is an opportunity to share the experiential dimension of the brand with the rest of the
community that co-creates the symbolic meaning of the brand (Hughes, Bendoni & Pehlivan,
2016; Kim & Sullivan, 2019).
3.3 Types of value co-creation
Because value is a term whose definition is still debated over for the reason of it being diverse
in nature, value co-creation, in its original form, is equivalently diverse. As the research on
the definition of value argues that it can be of different types and nature and that customers
can create different types of value simultaneously, be it tangible, intangible, or a mix of both,
there are several terms that are directly related to this process, such as “co-ideation”, “co-
innovation” (in Romero & Molin (2011);), “co-designing”, “co-manufacturing” and “social
manufacturing” (in Hirscher, Niinimaki & Armstrong (2017); Nachtigall et al. (2019)). As
this project focuses on the value co-creation process and its types, this sub-section will
provide a literature review on the main types of value that are generated as a result of co-
creation activities.
3.3.1 Co-ideation and co-innovation
These two types of value are considered together due to one similarity that they have in
common: the fact that both involve a process of idea generation and the type of value co-
created is in the form of new ideas, be them related to a certain product or to the business
model of a brand. With the help of co-ideation and co-innovation, the brands can offer their
customers a co-creative platform where the generated ideas can lead to restructuring and
innovation of the company’s business model. Therefore, by having customers who enhance
the capabilities of each other through sharing the same risks, resources, responsibilities and
rewards in the efforts of co-producing unique value propositions, a company enhances its
innovative ability over time. The continuous exchange of information between a company and
its community of co-creating consumers is what motivates the brands to continuously
innovate so that the correct co-creation mechanisms are provided (Romero & Molina, 2011).
In regards to the need for business model restructuring, Thomke & v.Hippel (2002) argue that
the difficulty in realizing an efficient co-creation process lies in the difficulty of knowing
what exactly the consumers want and prefer. Therefore, by Thomke & v.Hippel, co-
innovation can be achieved through the realization of two major steps. Firstly, instead of
11using resources to solely understand consumers, businesses can switch to customer
innovation, where the innovation process is not withheld internally, but a part of it is
transferred to the customers. Secondly, once the first step is achieved, the co-creating
customers need to be provided with all the necessary user-friendly tools which would make
the innovation process easy and enjoyable, otherwise, customers will not collaborate with the
company and will go to the competitors. If the co-creation platform is correctly set up, than
the brand department that is being co-created can become more efficient and less expensive.
This is a consequence from the fact that the innovating customers participate in designing and
developing their own products or generate business ideas which facilitate brand innovation
(ibid).
3.3.2 Co-manufacturing and social manufacturing
When it comes to the co-creation process in the manufacturing stage, the researchers came up
with terms such as co-manufacturing, social manufacturing, intelligent manufacturing (in the
case of I4.0 technologies) to relate to the collaborative aspect of manufacturing. This
innovative approach to manufacturing implies that companies partially or integrally shift the
manufacturing capabilities to their consumers and other stakeholders, enabling them to
customize production according to the current market and individual needs. This type of co-
created value can be seen as a democratic approach to manufacturing, where everyone has
access to different phases of the process (Shamsuzzoha et al., 2013; Hirscher et al., 2018).
Moreover, if smart manufacturing (introduced in the context of I4.0 in the previous section),
relates to the manufacturing system that is revolutionized and embedded solely by the I4.0
dimension, co-manufacturing, or social manufacturing, is still a smart-manufacturing system,
but one that puts collaboration and co-creation forefront.
It is co-manufacturing and co-design types of co-created value where I4.0 technologies come
into play as enabling counterparts in this equation. The collaborative aspect of a supply chain
is the fundamental step in creating a co-manufacturing production. Its power lies in the fact
that it uses I4.0 technologies such as information sharing, Point-of-Sale data, forecasts,
promotion plans, and even more advanced tools, such as radio frequency identification
(RFID), all for one common goal: to create and sustain an efficient collaborative relationship
between all the stakeholders of a supply chain (Pramatari, 2007).
In the context of the fashion industry, I4.0 technologies are believed to enable the transition
from mass-production and mass-customization to social manufacturing, a term that
encompasses a production system enabled by IoT, Cloud Computing, Cyber-physical systems
and Knowledge-based intelligent systems. Exclusively due to these technologies, social
manufacturing brings social networks into the system, according to which different
stakeholders can take part simultaneously and jointly in different activities, like product
design, communication and data exchange, and product evaluation, to name a few. The ability
of these technologies to create and sustain a dynamically networked crowd leads to the
opportunity to provide personalized product design for companies (Carneiro et al., 2014;
Xiong et al., 2018). Moreover, Satam, Liu & Lee (2011) and Zhong et al. (2017) argue that
these technologies in the context of social manufacturing enable co-creation in the form of
smart-design, smart machines, smart monitoring, smart control and smart scheduling.
Especially in the case of smart-design, I4.0 provides customers with the personalization
opportunity by using Virtual/Augmented Reality, design software like computer-aided design
(CAD), and computer-aided manufacturing (ibid.).
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