Content uploaded by Andreas Hein
Author content
All content in this area was uploaded by Andreas Hein on Oct 03, 2022
Content may be subject to copyright.
The Interdependencies between Customer Journey, Business Model, and
Technology in Creating Digital Customer Experiences – A Configurational
Analysis at the Example of Brick-and-Mortar Retail
Timo Phillip Böttcher
Technical University of Munich
timo.boettcher@tum.de
Tanja Kersten
Technical University of Munich
tanja.kersten@tum.de
Jörg Weking
Queensland University of
Technology
joerg.weking@qut.edu.au
Andreas Hein
Technical University of Munich
andreas.hein@tum.de
Helmut Krcmar
Technical University of Munich
helmut.krcmar@tum.de
Abstract
As brick-and-mortar retail increasingly disappears
while online retail flourishes, the customer experience
(CX) becomes a critical source of competitive
advantage. Customers expect the same information,
personalization, and availability in a brick-and-mortar
store as they do online. While digital technology enables
such CXs and enhances the advantage of the physical
experience, brick-and-mortar retailers struggle with the
complexity of these digital transformations. We analyze
38 cases of retailers implementing digital
transformations to create digital CXs by conducting a
qualitative comparative analysis. In eight expert
interviews, we refine our understanding of CX in retail
and discuss the validity and generalizability of the three
resulting configurations: value chain innovation,
seamless purchase experience, and personal
experience. They provide actionable pathways to digital
CX representing individual transformation initiatives.
Since the configurations overlap strongly, we discuss
the necessity to combine the three configurations to
implement digital CX across all phases of the customer
journey and business model.
Keywords: customer experience, digital
transformation, retail, QCA.
1. Introduction
Digital marketplaces such as Alibaba or Amazon
are overtaking brick-and-mortar retailers, causing
disruptions in the retail industry. Artificial intelligence,
the internet of things, mobile commerce, and extended
reality have become ubiquitous and eventually
unavoidable for retail (Grewal et al., 2020). The
question has long since ceased to be whether brick-and-
mortar retailers need to undergo a digital transformation
but how to do it.
Digital technology, for example, implemented to
create digitally augmented stores, can help attract,
support, and engage customers in their customer
journey. Digital mirrors that, for example, virtually
change the color of a shirt or personalize prices and
complementary products, rather than just buying and
consuming the product or service, create a digital
customer experience (DCX) that ensures customers
move through the various stages of this journey (Lemon
& Verhoef, 2016; Roggeveen & Sethuraman, 2020).
DCX is about fulfilling the customer's desire for an
experience supported by digital technology. Since
customers want different experiences at different stages
of their customer journey, the business model (BM),
which describes all company activities to create and
capture value for and from customers, must fulfill these
desires. DCX thus emerges at the intersection of digital
support for the customer journey and digital innovation
of the BM (Lemon & Verhoef, 2016).
The ways digital technology can be used to create
DCXs have become a significant source of competitive
advantage in retail (Keiningham et al., 2020). However,
firms struggle to create DCX because they do not view
DCX as an integrated construct of the customer journey
and BM that takes into account changing customer
expectations along their journey and the experience
offered across the various BM elements. For example,
Procter & Gamble wasted great investments in their
digital distribution systems to have their products
available to the customer at all the times, thus ensuring
the transition from the pre-purchase to the purchase
stage. However, as part of the BM, their key partners
and retail customers were not ready for these systems,
which then failed (Grewal et al., 2020). From a different
perspective, Macy's once rejected the TV shopping BM
idea that spawned QVC and a significant competitor
because they did not understand the customer journey of
willingly buying a product that was just comfortably
presented to customers on the couch.
The literature already selectively addresses these
challenges, such as the benefits of digital technologies
and their usage along the customer journey (Roggeveen
& Sethuraman, 2020) or in BMs (Böttcher, Li, et al.,
2021). Thus, we know how digital technology can
innovate either the customer or the firm perspective on
DCX. Although both sides are necessary, one of the two
implementations may not achieve the desired result of
improving DCX, as the example of Procter & Gamble
shows, and convince customers to continue their
journey satisfied or return because of the positive DCX.
Such focused research does not provide integrated
recommendations for creating DCX that coherently
addresses the two-sided challenge of creating a digital
customer journey and digital BM innovation (Grewal et
al., 2020; Keiningham et al., 2020).
To make such recommendations that address the
interactions between the customer journey, the BM, and
digital technology, we seek to find configurations that
explain what experiential value represented in the BM
is presented to the customer along the customer journey
when using digital technology that creates such DCX in
retail. These configurations demonstrate how retailers
digitally transformed their customer journey and BM in
alignment to create DCX. We propose the following
research question: What are the configurations of using
digital technology across the customer journey and the
BM to create digital customer experiences? Brick-and-
mortar retail provides an appropriate research context
because changes in consumer behavior impact retailers
early on, requiring an early response from retailers who
are now using digital technologies to create DCX
(Hagberg et al., 2017). As such, the industry serves as a
pathfinder for other consumer-facing industries. Brick-
and-mortar retail is of particular interest because
consumers are increasingly shopping online, and offline
retailers need to counteract this trend by offering
experiences that convince consumers to shop in offline
stores (Brynjolfsson et al., 2013).
We follow a three-step research approach,
combining a case survey with qualitative comparative
analysis (QCA) and refining the resulting configurations
with expert interviews. Based on 38 case studies on
digital transformations of brick-and-mortar retailers, we
identify three set-theoretic configurations creating
DCX. We refine our understanding of these
configurations, namely digitally innovated supply
chains, seamless purchase experiences, and personal
experiences, with eight expert interviews. The findings
propose three individual DCX initiatives to transform
the customer journey and the BM digitally. Besides the
interdependencies between the customer journey, the
BM, and digital technology, the QCA also reveals
interdependencies between the three configurations.
Hence, all three configurations must be combined to
create a holistic DCX. This guides practice to implement
digital technology to effectively create DCX by digitally
transforming the customer journey and the BM in
alignment with each other.
2. Theoretical Background
2.1. Digital Customer Experience
Holbrook and Hirschman (1982) introduced the
idea that consumer consumption involves experience
factors rather than viewing consumers as purely rational
actors. Experiences employ hedonic, symbolic, and
aesthetic characteristics of the customer journey. Later,
Pine and Gilmore (1998) referred to the emergence of
the Experience Economy as the next step in economic
value progression, replacing the agricultural, industrial,
and service economies. Building on these initial
findings, the existing literature describes customer
experience (CX) as the interplay between a company's
physical performance and the aroused emotions of
customers, intuitively measured at each contact with
customer expectations (Shaw & Ivens, 2002).
Therefore, CX is a “multidimensional construct
focusing on a customer’s cognitive, emotional,
behavioral, sensorial, and social responses to a firm’s
offerings during the customer’s entire [customer]
journey” (Lemon & Verhoef, 2016). Due to the holistic
nature of CX, this endeavor is also notably challenging
to replicate, in contrast to various product or service
improvements (Berry et al., 2002).
To provide an immersive CX and enhance and
promote competitive advantage, retailers must leverage
today's digital technologies. We refer to CX as the
overall concept of experiences provided to the customer
and to DCX if this CX is created by using digital
technology, thus digital technology is critical for the
CX. However, the sole use of technology is no longer a
fascination point for consumers but a base expectation
(Stephens & Pine, 2017). Technological stimuli are
increasingly becoming essential to creating a
memorable CX (Bustamante & Rubio, 2017). Creating
DCXs, for example, by guiding a customer in the store
using augmented reality or smart monitors is becoming
a prerequisite for competitiveness as retail is rapidly
evolving due to changes in consumer behavior (Grewal
et al., 2020; Piccinini et al., 2015). DCX provides value
for retailers by either attracting customers who value
such experiences and are willing to pay more for a DCX
or digitizing human services such as customer
consultations or self-checkout payments (Sethuraman &
Parasuraman, 2005).
To assess how digital technology creates value in
DCXs, firms must consider when technology is used in
the customer’s journey (Roggeveen & Sethuraman,
2020). The customer journey refers to “a series of
touchpoints, involving all activities and events related to
the delivery of the service from the customer’s
perspective” (Patrício et al., 2011) and is considered an
integrative and vital part of CX (Voorhees et al., 2017).
These touchpoints (i.e., interactions) are divided into the
three stages, pre-purchase, purchase, and post-purchase,
and into direct and indirect interactions (Lemon &
Verhoef, 2016). For example, intelligent warehouses
create value pre-purchase by providing customers
information about how many product items are available
in a particular store or by enabling data analytics for
improved stock levels. They also add value after the
purchase, such as handling customer returns, offering
follow-up services, or making new purchases based on
the previous CX. Direct interactions mainly happen
during the purchase stage, the use, and the receipt of
goods and services. The indirect contact consists of
interactions pre-and post-purchase, such as depicting a
company's product, reviewing recommendations or
criticism, services, brands, advertising, reports, or news
(Meyer & Schwager, 2007).
2.2. Business Models
To fully leverage the potential of digital technology
for DCX, the technology must also be embedded in the
BM. Firms need to gauge the impact of technologies on
DCX in terms of additional revenue when new BMs are
enabled or cost savings when a given BM can be
optimized (Böttcher & Weking, 2020; Jocevski et al.,
2019).
The term “BM” is defined as the “logic, the data,
and other evidence that support a value proposition for
the customer, and a viable structure of revenues and
costs for the enterprise delivering that value” (Teece,
2010, p. 179). Thus, the BM is the architecture linking
interdependent activities to create, deliver, and capture
value (Zott & Amit, 2010). It consists of three main
components: the value proposition (i.e., the offered
products and services), the value chain (i.e., all
processes and activities and the necessary resources,
capabilities, and coordination to achieve the value
proposition), and the revenue model (i.e., cost structure
and revenue streams) (Zott & Amit, 2010). Digital
technology is relevant for all these elements. Once it
fundamentally alters the elements, the BM is considered
a digital BM (Veit et al., 2014).
Consciously integrating DCX in the BM offers new
perspectives for firms in renewing their BMs. Firms
frequently conduct BM changes based on their
perception of what the market will accept and believe
will achieve their business objectives. Nevertheless, the
literature has ignored DCX’s implications for BMs
(Keiningham et al., 2020). Both topics overlap strongly
since a new BM typically influences customer
perceptions of their experiences with a company. DCX
can also be viewed as a potential enabler for creating
new digital BMs by capitalizing on opportunities that
customers want and are willing to alter their category
spending (Weill & Woerner, 2018). Digital technology
is the catalyst for bringing these concepts together.
2.3. An Integrated Perspective on DCX
Based on the overlap of the presented elements of
DCX, customer journey, digital technologies, and BMs,
we propose an integrated socio-technical perspective on
DCX presented in Figure 1 (Bostrom & Heinen, 1977).
This socio-technical perspective highlights the
integrated and interdependent nature of the concepts
related to DCX.
Figure 1. A socio-technical perspective on CX
As the value of technology increases when
embedded in a salient BM, retailers need to consider the
opportunities that digital technology offers to innovate
the BM (Teece, 2010). The BM presents a technical
system articulating “the processes, tasks, and
technology needed to transform inputs to outputs”
(Bostrom & Heinen, 1977, p. 17), or the activities to
create, deliver, and capture value (Zott & Amit, 2010).
It creates affordances to use digital technologies to
introduce novel activities that add customer value and
incorporate part of that value as profit (Teece, 2010).
The integration of DCX provides possibly more than
just an incremental improvement in a firm’s current
BM; it can help organizations innovate, allocate
resources, and transition from an old BM to a new one
based on newly created customer demand (Norton &
Pine, 2013).
Customer journey
Business modelCustomers
Digital
technology
Social system Technical system
Digital customer experience
Further, DCX can be captured in the three stages of
the customer journey and its touchpoints between the
retailer and the customer. Roggeveen and Sethuraman
(2020) argue that digital technology provides value in
the different stages of the customer journey and creates,
changes, or enhances the associated touchpoints. Firms
need to acknowledge the affordances related to
implementing digital technology in the different
customer journey stages and assess how, why, and when
it can create value for the customer, thus improving the
DCX.
In summary, firms’ affordances to create a DCX are
the potential technology implementations to support the
customer journey (i.e., activities in the pre-purchase, the
purchase, or the post-purchase stage) and to change the
BM (i.e., the value proposition, or the value chain).
3. Methodology
We conducted a three-step research method
depicted in Figure 2. In step one, we followed the case
survey method (Larsson, 1993) to collect a case sample
on retailers implementing DCX initiatives. We coded
these cases using a coding scheme grounded in theory
from a structured literature review. In step two, we
analyzed this coded case sample with crisp-set QCA
(csQCA) to derive configurations of DCX initiatives
(Rihoux & De Meur, 2009). In step three, we refined our
understanding of these configurations with industry
experts in semi-structured interviews and developed a
model of effective use. This combination of methods
allowed us to benefit from the advantages of each of the
three methods while compensating for their
disadvantages through the combination of methods.
3.1. Case collection
We scanned the extant literature to identify cases
for our case sample (Larsson, 1993). To identify a
comprehensive set of case studies about DCX in retail,
we searched for case studies about digital
transformation initiatives in retail. We can include cases
that present DCX initiatives (i.e., transformation
projects creating or changing DCX) but do not focus on
DCX explicitly but on digital transformation, digital
BMs, or digital retail in general. We included peer-
reviewed academic, practitioner- and education-
oriented outlets. We did not filter for publication date,
research method, or publication type. Also, we did not
exclude any retail sectors (e.g., food, fashion, and
furniture). Initially, we identified 80 case studies
relevant to our research. We analyzed these case studies
using inclusion and exclusion criteria to ensure quality,
relevance, and topic fit for our research purpose. We
included cases if (1) the case context was brick-and-
mortar retail and (2) the case narrative provided a
detailed description of the firm and its digital
transformation efforts. We excluded cases if (1) we
could not identify any instances of technology and BM
consistent with our research purpose and (2) if too little
information was reported. After the application of
selection and rejection criteria, 38 cases remained. For
non-anonymous case studies, we triangulated the
information with publicly available information, such as
the firm websites and news articles.
Figure 2. Three-step research method
3.2. Coding scheme
We developed a coding scheme grounded in theory.
It is based on the literature review and our socio-
technical view of DCX. Thus, the coding scheme is
organized in the three meta-characteristics digital
technology implementation along the customer journey,
BM change through the implementation, and improved
DCX as the outcome. For the meta-characteristic digital
technology implementation, we used the framework by
Roggeveen and Sethuraman (2020). The framework
categorizes digital technology along the three customer
journey stages based on their primary influence. We
could combine the information about which of the three
customer journey stages uses digital technology and the
information about which digital technology is used.
The BM change refers to the BM element whose
change was enabled or supported by the technology
implementation. Initially, we used four variables to
describe the BM elements: value proposition, customer,
value chain, and profit mechanism (Gassmann et al.,
2019). However, during the coding process, we
summarized the value proposition and customer and the
value chain and profit mechanism since we could not
differentiate the two aggregated variables (e.g., value
Case collection (n = 38)
Development of coding scheme
Case coding
(1) Case survey(2) csQCA
(3)
Theorizing
Necessity check
Truth table construction
Minimization and robustness check
Semi-structured interviews (n = 5)
Development of model of effective use
proposition and customers). The reason for this was
either limited availability of information or double
coding where both variables were coded as present, for
example, when digital technology was introduced to
change the value proposition and target a new customer
segment. DCX served as an outcome variable and was
therefore described by one variable expressing whether
or not the changes enabled by digital technology along
the customer journey or in the BM improved DCX.
We coded all variables binary, indicating whether
the variable applies to a specific case. For example,
Home Times has implemented digital walls that allow
customers to see their desired furniture and décor in a
virtual home setting. This supports the decision-making
of which furniture to buy. Thus, we coded the pre-
purchase stage to "1." The coding was performed in
collaboration by two of the authors.
Besides the variables in our coding scheme, we
recorded additional control variables. These control
variables include the firms' retail sector, age, size,
headquarter location, and internationalization. We used
these variables in the data analysis to check if one or
more control variables bias any configurations.
3.3. Configurational analysis
To analyze the coded case sample, we applied
csQCA. QCA was first introduced by Ragin (1987) and
has been further developed and refined into multiple so-
called "flavors," such as fuzzy-set QCA, csQCA, or
multi-value QCA. As our coding was binary or "crisp,"
we applied csQCA. QCA bridges qualitative and
quantitative research methodologies, increasing
confidence in the results (Duşa, 2007). QCA identifies
combinations of conditions that are sufficient to achieve
the outcome. Based on the socio-technical perspective
on DCX, the customer journey and BM changes are
interdependent. Thus, they need to be assessed in
combination. Hence, the configurational approach of
QCA is a suitable method for our research since we aim
to find the combinations of when (customer journey)
and how (BM) digital technology is used to improve
DCX in brick-and-mortar retail.
The csQCA comprises four main steps: First, a data
set is constructed that summarizes whether the causal
conditions and outcome are present or absent for each
case. We did this step in coding our cases, coding
whether a variable is present for every case. Second,
conditions are tested for necessity. Necessary conditions
are conditions that are always present if the outcome is
observed. We tested for necessity using a minimum
coverage threshold of 0.6, a consistency threshold of
0.95, and a relevance for necessity of 0.5 (Schneider &
Wagemann, 2012). No combinations were found with
the specified cut-off thresholds for both the presence
and the absence of the outcome. Hence, we assume no
necessary conditions for the outcome. Third, the coded
data table is converted into a truth table. The truth table
lists all logically possible combinations of conditions.
Fourth, the truth table is minimized using Boolean
minimization to identify sufficiency relations that
explain the observed outcome. We derived the
intermediate and the parsimonious solution to identify
core and peripheral conditions (Fiss, 2011). Based on
our medium sample size, the coverage threshold, which
determines how many cases must be included in a
configuration as a minimum, was set to 1. We set the
consistency threshold, which determines how consistent
the configuration is with the input data, to 0.8 to ensure
empirically valid configurations.
3.4. Refinement and interpretation
The final step in QCA is to interpret and theorize
from the resulting configurations (Park et al., 2020). We
conducted semi-structured interviews to refine our
understanding of the csQCA results . We interviewed
five retail experts from a global technology consultancy
to understand the context of the configurations in retail.
We selected the experts based on their experience with
digital technology and DCX, particularly in retail. To
validate the generalizability of our findings, we
interviewed three CX experts from a global software
firm that operates more than fifteen CX centers
worldwide to support their sales process. By validating
the configurations with these experts, we could ensure
their practical relevance and empirical reasoning . Also,
it allowed us to add in-depth practical insights to our
analysis. Thereby, we address a limitation of the case
survey method: the case studies analyzed were not
initially written for our specific research purpose. To
avoid bias in the validation, we did not present the
results of our csQCA to the interviewees. Our questions
targeted the technology trends in the retail and the
software industry, experiences in technology
implementation, and the success factors of DCX
implementations.
4. Results
4.1. Case sample
Our final case sample consists of 38 retail firms.
The sample contains primarily large and established
companies rather than start-ups or small and medium-
sized firms. All retail sectors contain a reasonable
proportion of cases, although Fashion and Food &
Grocery are more strongly represented. The firms are
equally distributed around the USA, Europe, and Asia.
The sample also contains an equal amount of
international and locally operating retailers.
4.2. Configurations
Table 1. Configurations for enhancing CX
Solution
Configuration
[1]
[2]
[3]
Customer
journey
PREP
⊗
PUR
⊗
POST
BM
VPROP
VCHAIN
Unique consistency
1.000
1.000
1.000
Unique coverage
0.273
0.152
0.091
Solution consistency
1.000
Solution coverage
0.788
Table 1 displays the results of the csQCA. The
analysis revealed three configurations, leading to a
DCX. Following the notation of Fiss (2011), black
circles indicate the presence of a condition; crossed
circles indicate the absence of a condition. Large circles
indicate core conditions; small ones indicate peripheral
conditions. Blank spaces indicate irrelevance to the
outcome. The overall solution indicates consistency of
1.000. Thus, the configurations fully explain the
outcome. The solution coverage of 0.788 indicates an
explained variance of 78.8% of our analyzed cases.
Thus, our solution is a good fit for our cases, similar to
other applications of QCA in information systems
research (e.g., Park & Mithas, 2020). The unique
consistency and coverage indicate each configuration's
consistency and coverage individually. The unique
coverage reveals how much variance of the solution
coverage is explained solely by this configuration. Since
the sum of the individual coverages does not equal the
solution coverage, there is an overlap in explained
variance between the three configurations, as illustrated
in Figure 3. The dark areas in the middle of Figure 3
illustrate the overlap of the configurations.
4.2.1. Configuration 1 "Value chain innovation."
Solution 1 represents technology implementation in the
pre-purchase stage and changes the BM's value chain.
Thus, digital technology implemented in the pre-
purchase stage is not sufficient to increase DCX but
needs to be combined with an optimized value chain,
bridging the gaps between the customer journey stages.
The value chain is specifically relevant because it
consists of the processes and activities and the involved
resources and capabilities to build and distribute the
value proposition. Saving cost, enabling fast logistics,
managing and storing data to streamline internal
processes, and forecasting to ensure product availability
seem to be a success factor for companies. An
innovative supply chain can manage peak times and
ensure availability, which significantly impacts DCX.
Figure 3. Venn Diagram of the QCA Solution
For example, the beauty retailer Sephora enabled its
supply chain to provide free two-day shipping. This
improved supply chain is essential to convince
customers to move from the pre-purchase stage to the
purchase stage. Otherwise, if the product they want is
not available in the store or cannot be delivered to their
home immediately, the customer might enjoy the DCX
Sephora created with chatbots, personalized alerts,
digital screens, and augmented reality, but then buy
online from any other online retailer to deliver the
product quickly.
Stock and inventory management and forecasting
are critical elements for a fast value chain, ensuring
availability in-store or enabling quick deliveries.
Therefore, data analytics plays a key role as retailers
such as Target and Walmart implement to improve
planning accuracy and forecasting. This also reduces
supply chain costs, augments productivity, and ensures
the availability of products that will, in turn, serve the
customer and enhance the DCX.
Based on the digital optimization of supply chains,
the retailers can create omnichannel experiences
combining the benefits of online and offline
experiences. The offline experience of touching and
feeling is still valuable to customers. Thus, many online-
first retailers, such as Warby Parker or Bonobos, are
opening showrooms to enter the offline world.
However, sold products are fulfilled via home delivery
just as online sales, improving both realized demand and
operational efficiency. As an outcome, the retailers
created DCXs by “providing assistance by stylists for
better customer interaction” (Bhatnagar, 2018, p. 2). On
the other side, brick-and-mortar retailers are moving
online, thus changing their value chain. J.C. Penney, for
example, has realized the potential of their stores also
becoming distribution points for their online retail.
Moreover, Home Times uses gamification, digital
catalogs, digital walls, and virtual showrooms to attract
customers in the pre-purchase stage. Besides the DCX
in offline stores, an omnichannel experience creates
awareness and brand legitimacy to attract customers to
the online channel and transfer them to the purchase
stage.
4.2.2. Configuration 2 "Seamless purchase
experience." Solution 2 combines technology
implementation in the pre-purchase stage and the
purchase stage. We find no link to the BM elements in
this solution. Pre-purchase technology engages
customers and encourages them to interact with
businesses before committing to any purchases. The
technology inspires potential customers, enabling them
to experiment with the idea of transacting with a
business. Once committed to the purchase, technology
invested in the purchasing phase makes the journey
from commitment to exchange seamless. For example,
the McDonald’s digital kiosk goes beyond reducing the
time spent waiting in a line to order; it allows customers
to interact with the menu and create customized burgers.
Once customers found the right combination, it enabled
the creation to become a real burger. The combination
of pre-purchase and purchase technology complement
each other to bring greater customer engagement and
convenience, thus creating DCX through the digital
interface.
In the fashion industry, Nordstrom, for example,
invested in pre-purchase technology such as digital self-
service kiosks to find products quickly and digitally.
Tablets in changing rooms can be used to call for
personal assistance or pay directly via mobile payment.
Moreover, Nordstrom deploys technology such as cloud
computing and endless aisle and uses a store app for
geotargeting (e.g., routing the customers to the nearest
store).
Overall, the DCX decreases the barriers between
the pre-purchase stage and the actual purchase. It helps
addressing individual customers more personalized,
create a convenient experience in brick-and-mortar
stores that is known from online retail, and ensures a
personal connection between customers and sales
assistants.
4.2.3. Configuration 3 "Personal experience."
Solution 3 indicates low technology need to create CX
due to the combined absence of technology
implementations in the pre-purchase and purchase
phases. However, the retailers used other means to
enhance the value proposition to create CXs. Instead of
DCXs, these retailers focus on the strengths of offline
retail: the personal, physical CX.
For example, Casper Sleep, a retailer selling sleep
products, attracts “more traditional shoppers who would
not purchase a mattress without trying it out” (Tangirala
& Purkayastha, 2018, p. 7) by demonstrating
mattresses’ cooling functionality and simulating
bedrooms to test and experience the products before
buying. Nike flagship stores create happenings with DJs
causing customers to stay longer in the store just to
enjoy the musical experience. By increasing the value of
the retailers’ bundle of products and services to the
customer, thus the value proposition, a better CX can be
achieved. Other opportunities to create personal CXs are
marketing campaigns, such as giveaways included with
the purchase, or attractions in the store, such as the DJ,
with positive word-of-mouth effects.
5. Discussion
In the wake of the digital transformation, customers
expect a memorable experience in brick-and-mortar
retail that provides some benefits compared to online
retail (Grewal et al., 2020). Digital technology provides
one way to achieve a superior DCX. However, both the
customer journey and the BM need to be considered to
maximize the benefits of DCX (Keiningham et al.,
2020; Lemon & Verhoef, 2016). We conducted a case
survey of 38 retailers to address the resulting challenge
of complex interdependencies and analyzed their
initiatives to create DCXs. The csQCA revealed three
configurations to create DCX with strong overlaps. We
refined and validated the configurations with eight
expert interviews from a technology consultancy and a
software firm.
First, digital technology enables value chain
innovation to create superior DCX in the pre-purchase
stage, which helps convince the customer to proceed to
the purchase stage. Second, digital technology innovates
the customer journey and creates a seamless purchase
experience from the very beginning when a customer
identifies a need until the purchase is completed. Third,
retailers should look outside digital technology and
consider the personal experience and the non-digital
interactions with customers that create a superior DCX.
However, while the configurations are sufficient to
create DCX in set-theoretic terms, neither of the
configurations alone is enough to create a holistic DCX
that should be targeted. As the overlaps in Figure 3
show, all three configurations and all elements of the
customer journey and the BM are needed. The sweet
spot is right in the middle of Figure 3. For example,
intelligent mirrors suggesting matching pants to a shirt
(i.e., configuration 2) do not create a beneficial DCX if
these pants are unavailable in this store (i.e.,
configuration 1). Personal experiences, such as in-store
events (i.e., configuration 3), do not create additional
benefits if the customers are not convinced to buy
anything, a process supported by DCX (i.e.,
configurations 1 and 2).
The creation of DCX thus needs to address the
entire customer journey and the BM. It needs to merge
online and offline experiences. In retail, customers have
nearly complete information about products and prices.
The DCX in offline environments, such as brick-and-
mortar retail but also in business-to-business
relationships like enterprise software, needs to provide
a benefit (i.e., the experience) customers cannot obtain
from the internet or from looking at publicly available
presentations, reviews, or price lists (Piccinini et al.,
2015). In online retail, customers are used to product
recommendations based on previous purchases or the
current shopping cart. Combining digitally innovated
value chains and seamless purchase experiences makes
similar DCXs possible in brick-and-mortar retail. For
example, augmented reality makes it easier to identify
vegan or organic food in a grocery store. Interactive
displays or smart mirrors can inform the customer about
the farm the meat comes from or match shirts to selected
pants. Again, this also translates to other industries. For
example, based on a firm’s current enterprise software
architecture, or the usage thereof, software firms can
suggest optimal additions to the architecture improving
business processes or enabling new BMs.
During the customer journey, brick-and-mortar
retailers need to find ways to support customers by
digitalizing the value chain. Implementing digital
technology in the value chain improves the DCX by
bridging the gap between online and offline. The store
is no longer the only point of interaction as customers
start the customer journey already at home online
(Brynjolfsson et al., 2013; Jocevski et al., 2019). For
example, if the customer knows a product is available
in-store, it is more likely they will go to the store to buy
the product there. Similarly, if a firm knows a new
software is compatible with its existing architecture,
chances are it is open to implementing it. Digital
technologies support the connection between the pre-
purchase and the purchase stage. The technology eases
the transition between the two stages and increases the
chances of customers buying the product or service
(Roggeveen & Sethuraman, 2020).
Besides all benefits of digital technology, the third
configuration highlights social interactions. This builds
on the notion that a DCX includes emotional and social
components (Lemon & Verhoef, 2016). In retail, these
DCX are created through event-like experiences such as
live music, pop-up stores, or social reputation.
Customers plan to visit a store not because they want to
buy something first but because they want to enjoy the
experience. In other industries, such as enterprise
software, social experiences are created through
personal meetings, such as customized workshops
demonstrating the software's potential for a customer,
meeting the board members of the software vendor, or
invitations to events at unique locations. These social
experiences are beneficial not in the way that it helps to
transition customers through the customer journey
stages but in the way it creates a customer engagement
effect. Customers will remember the experience and
eventually return based on past experiences.
5.1. Contributions to research and practice
The theoretical contributions of this research are
threefold. First, we demonstrate three configurations of
initiatives creating DCX. These configurations
represent individual and separate elements of DCX.
However, our analysis also reveals that these three
elements must be combined to create a holistic DCX.
Thus, we find support for previous research arguing that
CX needs to be considered across the customer journey
and the BM. We extend this argument by drilling it
down to the three identified configurations presenting
pathways to implement DCX. Thereby, we address
several calls for research to provide actionable
guidelines to implement the potential of digital
technology in retail (Grewal et al., 2020; Lemon &
Verhoef, 2016; Roggeveen & Sethuraman, 2020).
Combining the case survey method with the
configurational approach of csQCA shows how digital
technology can be effectively used to create DCXs. The
configurational approach enables us to acknowledge the
complexity and interdependencies of the socio-technical
model in retail, comprising digital technology, the
customer journey, and the BM.
Second, we find personal experiences (i.e.,
configuration 3) creating social and emotional
experiences as a relevant element even for DCX. While
digital technologies support the customer journey and
help transition the customer from one stage to the
following, personal experiences, not relying on digital
technology, are a critical element of the CX.
Third, our findings based on 38 cases of brick-and-
mortar retailers are generalizable to many industries.
We use examples from the enterprise software context
we learned during our interviews to demonstrate how
DCX supports software vendors' sales and consulting
process. This applies to almost any industry, such as
hospitality and tourism, automotive and logistics, or
government services.
For practice, our model provides guidelines to
create DCXs in retail and other industries, leveraging
digital technology. The three configurations can serve
as guidelines to structure DCX projects and drill them
into more manageable and focused initiatives. Firms can
refer to these configurations when making strategic
decisions about digital technology implementations. In
combination with the framework by Roggeveen and
Sethuraman (2020), the actualizations provide
practicable guidelines on how digital technology can be
implemented to create a superior DCX throughout the
customer journey and the BM.
5.2. Limitations and Future Research
Despite its contributions, our research faces some
limitations. First, our primary data sources are published
case studies about digital transformation in retail. While
we employed a rigorous case selection procedure to
select information-rich and purposeful publications, the
case studies were not written for our research purpose
(Larsson, 1993). Thus, the information provided in the
individual case studies may not be complete. However,
we tried to address this limitation by validating the
configurations with expert interviews that supported our
case analysis. Second, the reliance on these case studies
does not allow us to quantify the effect of the changes
on the improved DCX. As reflected in the binary coding
of the case data, we only collected data if a customer
journey stage or a BM element were changed by digital
technology. However, we cannot differentiate if
changing the pre-purchase stage influences the DCX
stronger than the value proposition.
In future research, scholars can build on our
findings to quantify the effects of the three
configurations. Through quantitative surveys, scholars
can assess the retailers' and customers' perspectives on
the effect of digital technology on DCX throughout the
customer journey. A large sample and differentiated
item scales allow for fuzzy-set QCA, which can further
differentiate the importance of individual elements in
the configurations leading to improved DCX. This could
also validate our claim for generalizability if such large-
n studies include multiple industries despite retail.
Additionally, COVID-19 heavily impacted the
retail industry (Böttcher et al., 2022). In our interviews,
the experts highlighted the increasing demand of
retailers for digital technologies, especially cloud
computing, that serves as a base for further technology
implementations. Hence, the pandemic may be a trigger
to kick-start digital transformations in retail (Böttcher et
al., 2022). For research, this provides a unique setting to
analyze the digital transformation of the retail
ecosystem (Böttcher, Rickling, et al., 2021) after a
shock, to analyze the digital transformation of late
movers or small and medium-sized retailers that did not
engage in digital technology before COVID-19, or to
look into the implementation and usage of digital
technology, such as virtual reality or digital platforms,
to provide digital DCX.
6. Conclusion
Creating and improving the DCX is a significant
competitive advantage in retail and other customer-
focused industries. Customers want to enjoy the
shopping experience. Firms create DCXs by
implementing unique, enjoyable experiences so that
customers like to spend time in the store or make it as
convenient as possible, eliminating unpleasant activities
in the customer journey. Digital technologies enable
both types of DCX, thus providing great potential for
retailers. However, DCX is a multidimensional
construct. To effectively create a digitally augmented
DCX, firms must consider the entire customer journey
from the pre-purchase stage to the post-purchase stage.
Also, the BM is necessary for DCX, as it articulates how
value is created, captured, and delivered to the customer.
This research proposes a socio-technical perspective on
DCX. It identifies three configurations, value chain
innovation, seamless purchase experience, and personal
experience, leading to the creation of DCXs and
highlighting the interdependencies of the
aforementioned customer journey, BM, and digital
technology.
7. Acknowledgments
The authors would like to thank the track chairs,
editors and all anonymous reviewers for their helpful
comments and suggestions. This work was funded by
the German Federal Ministry for Economic Affairs and
Energy as part of the project 01MK20001B
(Knowledge4Retail) and the Deutsche
Forschungsgemeinschaft (DFG, German Research
Foundation) – project no. 464594907.
8. References
Berry, L. L., Carbone, L. P., & Haeckel, S. H. (2002).
Managing the Total Customer Experience. Mit Sloan
Management Review, 43(3), 85-89.
Bhatnagar, M. (2018). Bonobos Acquisition by WalMart:
Setting a New Benchmark in Multichannel Experience?
(318-0015-1). https://www.thecasecentre.org/
Bostrom, R. P., & Heinen, J. S. (1977). MIS problems and
failures: A socio-technical perspective. Part I: The causes.
MIS Quarterly, 17-32.
Böttcher, T., Li, W., Hermes, S., Weking, J., & Krcmar, H.
(2021). Escape from Dying Retail by Combining Bricks
and Clicks: A Taxonomy of Digital Business Models in
Retail. 25. Pacific Asia Conference on Information
Systems, Virtual.
Böttcher, T., Rickling, L., Gmelch, K., Weking, J., & Krcmar,
H. (2021). Towards the Digital Self-Renewal of Retail:
The Generic Ecosystem of the Retail Industry 16.
International Conference on Wirtschaftsinformatik,
Virtual.
Böttcher, T., & Weking, J. (2020). Identifying Antecedents &
Outcomes of Digital Business Model Innovation. 28.
European Conference on Information Systems, Virtual.
Böttcher, T., Weking, J., & Krcmar, H. (2022). THE GOOD,
THE BAD, AND THE DYNAMIC: CHANGES TO
RETAIL BUSINESS MODELS DURING COVID-19 35th
Bled eConference, Bled, Slovenia.
Brynjolfsson, E., Hu, Y., & Rahman, M. (2013). Competing
in the Age of Omnichannel Retailing. MIT Sloan
Management Review, 54, 23-29.
Bustamante, J. C., & Rubio, N. (2017). Measuring customer
experience in physical retail environments. Journal of
Service Management, 28(5), 884–913.
Fiss, P. C. (2011). Building Better Causal Theories: A Fuzzy
Set Approach to Typologies in Organization Research.
Academy of Management Journal, 54(2), 393-420.
Gassmann, O., Frankenberger, K., & Csik, M. (2019). The St.
Gallen Business Model Navigator [Working Paper].
University of St. Gallen.
Grewal, D., Noble, S. M., Roggeveen, A. L., & Nordfalt, J.
(2020). The future of in-store technology. Journal of the
Academy of Marketing Science, 48(1), 96–113.
Hagberg, J., Jonsson, A., & Egels-Zandén, N. (2017). Retail
Digitalization: Implications for Physical Stores. Journal
of Retailing and Consumer Services, 39, 264-269.
Holbrook, M. B., & Hirschman, E. C. (1982). The
Experimental Aspects of Consumption: Consumer
Fantasies, Feelings and Fun. Journal of consumer
research, 9(2), 132-140.
Jocevski, M., Arvidsson, N., Miragliotta, G., Ghezzi, A., &
Mangiaracina, R. (2019). Transitions towards omni-
channel retailing strategies: a business model perspective.
International Journal of Retail & Distribution
Management, 47(2), 78-93.
Keiningham, T., Aksoy, L., Bruce, H. L., Cadet, F., Clennell,
N., Hodgkinson, I. R., & Kearney, T. (2020). Customer
experience driven business model innovation. Journal of
Business Research, 116, 431-440.
Larsson, R. (1993). Case Survey Methodology: Quantitative
Analysis of Patterns Across Case Studies. Academy of
Management Journal, 36(6), 1515-1546.
Lemon, K. N., & Verhoef, P. C. (2016). Understanding
Customer Experience Throughout the Customer Journey.
Journal of Marketing, 80(6), 69-96.
Meyer, C., & Schwager, A. (2007). Understanding customer
experience. Harvard Business Review, 85(2), 116-126.
Norton, D. W., & Pine, B. J. (2013). Using the customer
journey to road test and refine the business model.
Strategy & Leadership.
Park, Y., Fiss, P., & Sawy, O. (2020). Theorizing the
Multiplicity of Digital Phenomena: The Ecology of
Configurations, Causal Recipes, and Guidelines for
Applying QCA. MIS Quarterly, 44, 1493-1520.
Park, Y., & Mithas, S. (2020). Organized Complexity of
Digital Business Strategy: A Configurational Perspective.
MIS Quarterly, 44(1), 85-127.
Patrício, L., Fisk, R. P., Cunha, J. F., & Constantine, L. (2011).
Multilevel service design: from customer value
constellation to service experience blueprinting. Journal
of Service Research, 14(2), 180-200.
Piccinini, E., Gregory, R., & Kolbe, L. (2015). Changes in the
Producer-Consumer Relationship – Towards Digital
Transformation. Wirtschaftsinformatik, Osnabrück,
Germany.
Pine, B. J., & Gilmore, J. H. (1998). Welcome to the
experience economy. Harvard Business Review, 76(4),
97-105.
Ragin, C. (1987). The comparative method: Moving beyond
qualitative and quantitative methods. Berkeley:
University of California.
Rihoux, B., & De Meur, G. (2009). Crisp-set qualitative
comparative analysis (csQCA). Configurational
comparative methods: Qualitative comparative analysis
(QCA) and related techniques, 51, 33-68.
Roggeveen, A. L., & Sethuraman, R. (2020). Customer-
Interfacing Retail Technologies in 2020 & Beyond: An
Integrative Framework and Research Directions. Journal
of Retailing, 96(3), 299–309.
Schneider, C. Q., & Wagemann, C. (2012). Set-theoretic
methods for the social sciences: A guide to qualitative
comparative analysis. Cambridge University Press.
Sethuraman, R., & Parasuraman, A. (2005). Succeeding in the
Big Middle through technology. Journal of Retailing,
81(2), 107–111.
Shaw, C., & Ivens, J. (2002). Building great customer
experiences. Palgrave.
Stephens, D., & Pine, J. (2017). Reengineering Retail: The
Future of Selling in a Post-Digital World. Figure 1
Publishing.
Tangirala, V. K., & Purkayastha, D. (2018). Casper:
Employing Innovative Marketing Strategies to Engage
Consumers (518-0155-1).
https://www.thecasecentre.org/
Teece, D. J. (2010). Business Models, Business Strategy and
Innovation. Long Range Planning, 43(2-3), 172-194.
Veit, D., Clemons, E., Benlian, A., Buxmann, P., Hess, T.,
Kundisch, D., Leimeister, J. M., Loos, P., & Spann, M.
(2014). Business Models. Business & Information
Systems Engineering, 6(1), 45-53.
Voorhees, C. M., Fombelle, P. W., Gregoire, Y., Bone, S.,
Gustafsson, A., Sousa, R., & Walkowiak, T. (2017).
Service encounters, experiences and the customer
journey: Defining the field and a call to expand our lens.
Journal of Business Research, 79, 269-280.
Weill, P., & Woerner, S. (2018). What's your digital business
model?: six questions to help you build the next-
generation enterprise (1 ed.). Harvard Business Press.
Zott, C., & Amit, R. (2010). Business Model Design: An
Activity System Perspective. Long Range Planning,
43(2-3), 216-226.
