Scholarly Article
Journal of Service Research
2023, Vol. 0(0) 1–16
© The Author(s) 2023
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DOI: 10.1177/10946705231173116
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Micro-Level Mechanisms to Support Value
Co-Creation for Design of Digital Services
Tuure Tuunanen1,2, Juuli Lumivalo1, Tero Vartiainen3, Yixin Zhang4,
and Michael M. Myers5
Abstract
This study identifies micro-level value co-creation mechanisms that support the design of digital services. As services are now
becoming digital—or at least digitally enabled—how to design digital services that enable value co-creation between a service
provider and customers has become an increasingly important question. Our qualitative research study provides one answer to this
question. Based on 113 in-depth laddering interviews analyzed using interpretive structural modeling, our study shows that value
co-creation mechanisms differ between business-to-business and customer-to-customer digital service types. We identify five
mechanisms to support value co-creation in the design of digital services: (1) Social use, (2) Customer orientation and decision
making, (3) Service experience, (4) Service use context, and (5) Customer values and goals. We claim that firms can readily utilize
these mechanisms to improve their customers’ service experiences.
Keywords
value co-creation, micro-level mechanisms, theory, design of digital services, qualitative research, laddering interview, interpretive
structural modeling
Introduction
Most services are now digital—or at least digitally enabled. This
is because of a fundamental change in the nature of our world—
a world that has been described as digital first (Baskerville,
Myers, and Yoo 2020). In this digital-first world, digital services
have become just as, if not more important than, traditional
services. As digital services differ significantly from traditional
services, there is an urgent need to understand how design may
help digital services reach their full value co-creation potential
(Cˇaic´, Odekerken-Schro¨der, and Mahr, 2018).
We propose that a way to understand the design of digital
services is to focus on how the value received by the service
customer is co-created with the service provider and customer
(Vargo, Maglio, and Akaka 2008). Although much research has
investigated aspects such as resource integration, roles in value
co-creation, value outcomes in different contexts, engaging
customers in value co-creation, and its managerial implications
(see, for example, Alves, Fernandes, and Raposo 2016; Vargo,
Koskela-Huotari, and Vink 2020), we do not yet understand the
micro-level mechanisms of value co-creation that enable and
constrain the design of a service (Storbacka et al. 2016; Vargo,
Koskela-Huotari, and Vink 2020). Whereas the activity, pro-
cess, or practice of service design has been the subject of inquiry
in the literature, the design of a service has not. The design of a
service refers to “a collection of elements or components that are
organized for a common purpose as a system.”1
Given the current digital-first nature of our world
(Baskerville, Myers, and Yoo 2020), we believe there is a need
to understand how to enable—and enhance—value co-creation
between a service provider and its customers through the design
of digital services. Therefore, this study focuses on micro-level
value co-creation mechanisms in the design of digital services
by investigating the perspective of customers interacting with
the service. We define digital services (plural) as a particular
type of output of service (singular) (Vargo, Koskela-Huotari and
Vink 2020) that are “obtained and/or arranged through a digital
transaction (information, software modules, or consumer
goods) over Internet Protocol” (Williams, Chatterjee, and Rossi
2008, 506).
Most previous research on value co-creation in service
design has focused on the activity, process, and practice of
service design. The literature often focuses on involving
1Faculty of Information Technology, University of Jyva¨skyla¨, Finland
2Department of Informatics and Media, Uppsala University, Sweden
3School of Technology and Innovations-Vaasa, University of Vaasa, Finland
4Swedish Center for Digital Innovation, Department of Applied IT, Division of
Informatics-Go¨teborg, University of Gothenburg, Sweden
5University of Auckland Business School, Auckland, New Zealand
Corresponding Author:
Tuure Tuunanen, Faculty of Information Technology, University of Jyva¨skyla¨,
Mattilanniemi 2, Agora, P.O. Box 35, Jyva¨skyla¨ 40014, Finland.
Email: tuure@tuunanen.fi
customers in the service design process (cf., Yu and Sangiorgi
2018). Others have looked at value co-creation activities by
different actors in service systems (cf., Vargo et al. 2008) or
service platform ecosystems (cf., Storbacka et al. 2016).
However, researchers have called for research on the “black
box”2 design of services (see, for example, Tuunanen et al.,
2018), especially when technological innovations are con-
stantly changing the digital services landscape (Leimeister,
O¨sterle, and Alter, 2014). Thus, we are interested in the opaque
nature of the design of a service, and how we can apply the
concept of micro-level mechanism to “white box”3 the design
to understand how we can enable value co-creation between a
service provider and a customer.
Consequently, this study adopts a qualitative research ap-
proach and identifies micro-level mechanisms for explaining the
value co-creation process between digital service providers and
their customers. More specifically, we follow Gro¨nroos and
Voima (2013) and argue that value co-creation happens in a joint
sphere where customers use a digital service provided by a
service provider. We define mechanisms as “entities and ac-
tivities organized such that they are productive of regular
changes from start or set-up to finish or termination conditions”
(Machamer, Darden, and Craver 2000, 3). We build on the
earlier work of Tuunanen, Myers, and Cassab (2010), who
presented a framework consisting of two key aspects for the
design of digital services to support value co-creation: (1) value
propositions offered by the digital service—that is, the designed
features, and (2) value drivers of customers. Thus, the actors in
this joint sphere (Gro¨nroos and Voima 2013) are the service
provider and their customers. Consequently, this study seeks to
answer the following research question: What micro-level
mechanisms of value co-creation support the design of digi-
tal services and how can they be identified?
Our study contributes to the literature by identifying micro-
level value co-creation mechanisms for the design of digital
services: (1) Social use, (2) Customer orientation and decision
making, (3) Service experience, (4) Service use context, and (5)
Customer values and goals. We believe our research findings are
relevant to managers in all kinds of industries who are trying to
figure out how their organizations can be digitally transformed.
We suggest that practitioners can use the identified mechanisms
and the depicted research approach to better design digital
services that enable value co-creation between a service pro-
vider and customers. Furthermore, our findings show how the
mechanisms differ between business-to-business (B2B) and
customer-to-customer (C2C) digital service types. This finding
has implications for the design of digital services if a service
provider desires to leverage the value co-creation potential
between its customers and the digital service offered. The
proposed mechanisms were identified based on our analysis of
113 laddering interviews (Reynolds and Gutman 1988). The
resulting dataset was analyzed using the interpretive structural
modeling approach (Guo, Li, and Stevens 2012) to develop
linkages between the model constructs.
The structure of this paper is as follows. First, we review the
literature, explaining different approaches to conceptualize
value co-creation. We then argue that there is a need to enable
value co-creation between customers and the digital service
offered to improve the design of digital services. Next, we
describe our research methodology, data collection, and analysis
methods. This is followed by the presentation of our findings.
We then discuss the implications of our study for future re-
search. For service managers and designers, we exemplify the
use of the findings in a scenario that applies the developed
conceptual model for designing a digital service for the mining
industry. We conclude by acknowledging some limitations of
the research and suggesting future research avenues.
Toward Micro-Level Value
Co-Creation Mechanisms
Traditionally, value creation has been viewed as an action in
which firms sacrifice resources by exchanging value with
customers (Gro¨nroos 2006) to pursue benefits (Zeithaml 1988).
This firm-centric view of service orchestration considers that
companies ultimately determine what is of value to customers
(Prahalad and Ramaswamy 2004b). Accordingly, the literature
often focuses on creating business value for a firm (Kohli and
Grover 2008) and measuring value as value-in-exchange.
However, divergent measures have emerged that define
value, for instance, through an extrinsic-intrinsic or hedonic-
utilitarian division (see, for example, Holbrook 1999; Van der
Heijden 2004) and service experience (see, for example,
Helkkula 2011; Prahalad and Ramaswamy 2004a). Customer-
centric views see value as being cooperatively produced by
customers in firms’ processes (Prahalad and Ramaswamy 2002;
2004b). Service-Dominant (S-D) logic, in turn, posits that value
co-creation emerges from the use of service offerings (Vargo
and Lusch 2004; Vargo, Koskela-Huotari, and Vink 2020).
Consequently, firms should consider customer interactions as
key to value co-creation (Prahalad and Ramaswamy 2004b). In
the same vein, Vargo and Lusch (2004) suggest that firms
merely offer customers value propositions and that customers
derive value-in-use through such service exchange.
Vargo and Lusch (2004) position service as the foundation
for all exchange between firms and customers, where customers
as beneficiaries determine value in using the service. S-D logic
holds that the value of a service or a good does not exist by itself
but is rather derived from the customers’ perceived contextual
experiences that it enables (Flint and Woodruff 2014; Prahalad
and Ramaswamy 2004b). Companies are regarded as offering
value propositions to customers who may accept the proposi-
tions by integrating their resources, thus co-creating value.
Accordingly, service is explained as applying possessed re-
sources to benefit the entity or another entity, and value co-
creation is regarded as a collaborative process (Prahalad and
Ramaswamy 2004a) of resource integration between benefit-
pursuing entities (Vargo and Lusch 2004). Evolving toward a
general theory of value co-creation (Vargo and Lusch 2017), S-
D logic captures generic actors (entities taking part in the co-
creation process) connected by value propositions. Accordingly,
Vargo and Lusch (2004) and Lusch and Nambisan (2015)
2 Journal of Service Research 0(0)
emphasize the importance of incorporating different actors in
value co-creation to facilitate the generation of value-in-use
(Vargo and Lusch 2004; Vargo, Koskela-Huotari, and Vink
2020).
The literature has attempted to make sense of the value co-
creation process in various contexts, such as B2B (e.g., Lenka,
Parida, and Wincent 2017), business-to-consumer (B2C) (e.g.,
Echeverri and Ska˚le´n 2011), and networks of consumers and
businesses (e.g., Singaraju et al. 2016). For instance, Lenka,
Parida, and Wincent (2017) explicate how digitalization ca-
pabilities provide mechanisms for a company to co-create value
with customers through an improved ability to perceive cus-
tomers’ needs and changing demands. Alexander and Jaakkola
(2015), in turn, construct an understanding of resource inte-
grations occurring between network actors and depict four
prerequisites for a successful value co-creation process, namely,
the provision of access and the nature of that access, the level of
ownership taken by adopters, user empowerment, and an in-
creased level of support from other actors.
While a plethora of research has examined the effects of
value co-creation, such as for economic gain (Ostrom et al.
2010), only a few studies have considered the underlying
structures, mechanisms, and relationships of a value co-creation
process (Vargo, Koskela-Huotari, and Vink 2020). Drawing
from a systematic literature review, Saarija¨rvi (2012) outlines
“value co-creation mechanisms” as those that support the focal
firm in delivering its value propositions to customers.
Saarija¨rvi’s (2012) value co-creation mechanisms manifest
as particular ways in which value co-creation is initiated to
customers, such as co-production (e.g., Etgar 2008), co-
development (e.g., Payne, Storbacka, and Frow 2008), and
co-design (e.g., Sanders and Stappers 2008). However, the
conceptual understanding of value co-creation and its process
should not be limited solely to the co-production or co-
development of the core offering, which is involved in the
design or development phases (Cova, Dalli, and Zwick 2011).
Such approaches often focus on the implementation of cus-
tomers’ labor and related value implications (Etgar 2008) and
on the labeling conditions that lead to such benefits
(Kristensson, Matthing, and Johansson 2008).
Delving deeper, the value co-creation process is linked to the
individual customer’s service experience (Helkkula 2011;
Vargo and Lusch 2008) and the intangible nature of services—
that is, the service occurs at a certain time, in a designated place,
and cannot be stored in situ (Bitner 1990; Shostack 1977).
According to Heinonen et al. (2010), value-in-use may emerge
at three temporal points: prior to, during, and after a purchase.
Thus, the co-creation of value stems not merely from con-
sumption but also from the experience of the process (Frow and
Payne 2007). Thus, customers’ past, present, and future ex-
periences with multiple actors in multiple service occurrences
influence the co-creation of value and thus should be considered
when making sense of the value co-creation process (Heinonen
et al. 2010).
Gro¨nroos and Voima (2013) state that value can only be co-
created in a joint co-creation sphere between the involved
parties, indicating that the initiative to co-create value stems
from the customer’s rather than the company’s side. Here, the
customer is seen as the value creator who invites the service
provider into direct interaction with them to co-create value.
Thus, the service provider may be offered an opportunity to
become an active co-creator of value. Such value co-creation
activities may strengthen customers’ motivations for further
engaging in similar processes and foster engagement (Hsieh and
Chang, 2016). In a similar vein, Storbacka et al. (2016) identify
particular social mechanisms that connect micro-, meso-, and
macro-level analytical concepts, complementing the micro-
level foundational understanding of how the value co-
creation process unfolds.
However, although there is an emerging strand of research
investigating how customers take part in value co-creation, such
as Payne, Storbacka, and Frow (2008) and McColl-Kennedy
et al. (2012), the literature has tended to focus on enterprises as
service providers (actors) interacting with similar entities. Less
attention has been paid to other types of networks, such as those
in which customers interact with other customers. The structures
underlying the described value co-creation events and the nature
of the entire process remain largely unknown. We argue that to
understand value co-creation between a digital service provider
and customer(s) in a joint sphere (Gro¨nroos and Voima 2013),
we need to understand the interaction mechanisms of such
behavior at a design level. To provide such an understanding, an
in-depth inspection at the micro-level of the individual end
customer needs is required. Hence, in this paper, we intend to
focus on the micro-level mechanisms involved in the design of
digital services.
Enabling Value Co-Creation for Design of
Digital Services
Today, as new digital technologies emerge, distributed service
exchange networks are created and entered by multiple actors
(Blaschke et al. 2019; Breidbach and Maglio 2016). Along with
the shift from “co-located contexts into dynamic, distributed,
and technology-enabled ones” (Breidbach and Maglio 2016,
83), a shift is also needed in designing digital services. Although
user interaction has been underscored as an important aspect of
digital service design processes (Williams, Chatterjee, and
Rossi 2008), supporting value co-creation is still poorly un-
derstood (Lusch and Nambisan 2015).
Previous research has mostly focused on selecting suitable
service design methods and techniques for involving customers
in the design process in certain situations (see, for example,
Maguire 2001; Zomerdiik and Voss 2010; Tuunanen and Peffers
2018). Such studies tend to take a unilateral view, focusing on
specific design objectives rather than holistically on co-creating
value with or among individual customers throughout the life
cycle of the developed digital service (Gro¨nroos and Voima
2013). Such approaches usually do not focus on the design of
digital services. Grotherr, Semmann, and Bo¨hmann (2018)
argue for a need to understand value co-creation in the pro-
cess of designing digital services by different actors involved in
Tuunanen et al. 3
their design. Grenha Teixeira et al. (2017) offer another ap-
proach to modeling a service using different service design
methods. Others have studied how to involve different actors in
a service design process (Pinho et al. 2014; Yu and Sangiorgi
2018), service systems (Vargo et al. 2008; Jaakkola and
Alexander 2014), or service platform ecosystems (Storbacka
et al. 2016; Hein et al., 2019) enabling value co-creation. The
literature has, therefore, examined different actors in a service
design process, service systems, or service platform ecosystems
and their context and social practices, translating these into
service design knowledge of activities, processes, and practices.
Morelli (2002) highlights the importance of understanding
the customers’ service experience and the interactions between
the customer and the service provider. A need to understand
customers’ perceived service experiences has also been em-
phasized (Flint and Woodruff 2014; Prahalad and Ramaswamy
2004b), as without active customer participation, value-in-use
cannot emerge (Gro¨nroos and Voima 2013). While we agree that
interaction with customers is particularly important for the
design of digital services, where transactions are technology-
mediated (Williams, Chatterjee, and Rossi 2008), we also see
that the literature currently lacks guidance on the design of a
digital service so that it supports the co-creation of value for
customers. There is a need to investigate the “black box”2
design of digital services, not only the activities, processes, and
practices of service design when considering value co-creation.
Thus, we follow Ostrom et al.’s (2015) argument that we
should consider the ideas from the design of information sys-
tems to better accommodate the design that enables value co-
creation for digital service customers. Lusch and Nambisan
(2015) state that digital technologies can be catalysts for co-
creating value by the customer(s) and the service provider.
Consequently, paying attention to individual customers’ needs
and wants becomes important in facilitating value co-creation in
digital services.
Digital services are constantly updated and continuously
maintained. New features often become available weekly or
monthly, which increases the challenges that firms and cus-
tomers experience. Sjo¨din et al. (2020) call this a digitalization
paradox, where increasing revenues from digital services fail to
deliver greater profits because of rising costs. Facebook, for
example, updates its digital services several times a day (e.g.,
Savor et al. 2016). Such progressiveness, which is virtually
impossible with physical services, is enabled by the digital
delivery of services (Yoo, Henfridsson, and Lyytinen 2010).
Tuunanen, Myers, and Cassab (2010) have proposed a way
to enable value co-creation with the design of digital services.
They propose taking an individual customer perspective to
investigate value co-creation, arguing that value co-creation is
an interplay of at least two different kinds of micro-level in-
teraction mechanisms with the digital service by the individual
customer. First, the system offers value propositions to cus-
tomers, and second, the customers possess values or goals that
drive their behavior. Lamb and Kling (2003) argue that cus-
tomers can potentially have an identity (e.g., Creed, Scully, and
Austin 2002) attached to their systems and that actors use these
systems to form and construct identities. Orlikowski et al. (1995)
also suggest that the context of system use is important, as is the
cultural context for influencing customer needs (Myers and Tan
2003; Tuunanen and Kuo 2015).
Tuunanen, Myers, and Cassab (2010) further posit that value
is co-created and determined by customers’ three key value
drivers: (1) customer participation (e.g., co-production activi-
ties, Von Hippel and Katz 2002); (2) service process experience,
such as hedonic benefits (Kahneman, Diener, and Schwarz
2003), and the experience of flow (Agarwal and Karahanna
2000; Csikszentmihaly 1991); and (3) customers’ goals for use,
such as desired features (Jacobs and Ip 2003) and perceived
usefulness (Venkatesh et al. 2003). Customers’ goals may be
hedonic (i.e., the use itself as aspired to) or utilitarian (i.e.,
productivity-oriented) (Tuunanen, Myers, and Cassab 2010),
and they may vary between different and similar types of
systems (i.e., work vs. leisure-oriented), which should be
considered in the design of such services (Tuunanen, Lintula,
and Auvinen 2019).
Consequently, we argue that the dynamic service charac-
teristics unleashed by digital technologies may be harnessed to
create engagement between the service provider and the cus-
tomers, enabling the digital service to retain and gain new
customers. We posit that digitally enabling and enhancing a
joint sphere of value co-creation (Gro¨nroos and Voima 2013)
between a service provider and its customers is key to
leveraging the value co-creation potential of digital services.
Accordingly, our study aims to identify micro-level mechanisms
that can enable and enhance value co-creation through the
design of digital services.
Research Methodology
This study adopts a qualitative research approach. In a field
study of five digital services, we attempted to identify the
mechanisms that enable value co-creation in the design of
digital services. We used the interpretive structural modeling
(ISM) approach to analyze the relationships among the iden-
tified constructs. We employed system value propositions and
customer value drivers (Tuunanen, Myers, and Cassab 2010) as
lenses for deriving constructs for value co-creation. The ISM
method is particularly suitable for extracting structures within
complex relationships among system elements and for devel-
oping a graphical representation of a given network of pairwise
connections (Malone 1975). We employed the constructs
emerging from the ISM analysis to derive mechanisms that can
be regarded as enablers of events (Wynn and Williams 2012).
Scrutinizing the emerging mechanisms and their interdepen-
dencies helped explain how the value co-creation process un-
folds in digital services.
Data Collection
We used the laddering interview technique to collect data based
on personal construct theory (PCT) (Kelly 1955). Personal
construct theory enables us to understand how and why people
4 Journal of Service Research 0(0)
see the world differently. Kelly (1955) argues that by under-
standing the relationships between the states of the universe, the
consequences of the states, and the impact of the consequences
on individuals’ values, we can infer how individuals observe
and interpret things and events in life. Personal constructs
describe the properties and operation of the connected things
and events, their consequences, and their effect on the indi-
vidual’s values. These personal constructs (Pervin 1993) result
from individuals’ observations and interpretations of events.
Individuals have multi-dimensional constructs that describe the
attributes and behavior of objects and events, their conse-
quences, and their effect on their personal values. The laddering
interviewing technique operationalizes PCT by providing a
means to investigate people’s values and/or goals that drive their
use of technology (Peffers, Gengler, and Tuunanen 2003;
Reynolds and Gutman, 1988).
The laddering technique can be used to study participants’
means-end structures of a product (Reynolds and Gutman 1988).
A complete description of a sequence of attribute–consequence–
value associations is referred to as a means-end chain. In lad-
dering, the interview participants are typically given a choice or
decision task within a service or product category. They are then
asked to describe what service or product attributes were the basis
for their decisions (Modesto Veludo-de-Oliveira, Akemi Ikeda,
and Cortez Campomar 2006). Subsequently, participants are
questioned to uncover the relevant consequences derived from
the service or product use (Reynolds and Gutman 1988). Probing
questioning continues until the participants describe their final
personal values when consuming the service or product. We
followed the examples of Reynolds and Gutman (1988), Peffers,
Gengler, and Tuunanen (2003), and Tuunanen and Peffers (2018)
for our laddering interview process. The data collection process is
further described in Online Appendix 1.
Sample Description
Our study is based on analyzing interview data collected in a
study of five different digital services. We used an identical
research methodology for collecting and analyzing the data,
applying theoretical sampling to both B2B and C2C digital
services. The rationale for choosing both B2B and C2C digital
services was twofold. First, we aimed to adapt Tuunanen, Myers,
and Cassab’s (2010) framework to different digital service
contexts. The original framework was developed for targeted
digital services for business to consumer (B2C). Second, we
hypothesized that having the contrasting perspective of having
either business-only oriented digital services or customer-only
oriented digital services would enable us to identify differences
more easily between the value co-creation mechanisms.
For each digital service, we sought lead user representatives (von
Hippel 1986) of the target user population (Tuunanen and Peffers
2018). The participants in each study were chosen to represent the
key stakeholders for each study. The demographics of the study
participants are described in Online Appendix 2. For example, to
study an intelligent cyber-physical system for mining, we worked
with the client company to find an initial set of 10 lead users of the
system. Subsequently, the snowball sampling technique was
adopted to recruit additional participants. The recruitment of people
continued until the required number of individuals was achieved;
see, for example, Tuunanen and Peffers (2018) for further details on
how to apply this technique in non-representative sample generation.
Similar participant recruitment processes were used for each study.
The study contexts were (1) an intelligent cyber-physical
system for mining, (2) an online customer relationship man-
agement (CRM) system, (3) an online event organizing and
planning system, (4) an online system for supporting a metal
detecting hobby, and (5) an online system for the geocaching
hobby. We provide short descriptions of the study contexts
below. The intelligent cyber-physical system for mining is
discussed in more detail in Section Implications for the Service
Design Practice.
· Intelligent cyber-physical system for mining: The com-
pany is a part of a global engineering group specializing
in high-technology equipment. The company provides
tools, equipment, and components, such as drills and
crushers, for the mining and construction industry. The
manufactured equipment and tools of the company
represent high technology and are industry-specific
(Ha¨nninen, Tuunanen, and Vartiainen 2015).
· Online CRM: The company is a specialized pulp and
paper production firm and consists of three business
divisions: services, pulp, and energy and papers. The
technology offerings include pulp mills, tissue, board,
and paper production lines, and power plants for bio-
energy production. The study focused on the services
division, including product life-cycle management and
related services. Its service portfolio includes everything
from individual spare parts to complete maintenance
outsourcing solutions.
· Event planning and organizing system: The company is a
start-up in the business event industry. The company
focuses on how event organizers can digitalize the
business by applying networking tools, video and picture
materials, newsletter subscriptions, and an organizer
dashboard to update the digital materials conveniently.
Their objective is to develop a marketplace with search
functionality that uses different event categories, areas, or
cities where the events are being held, similar to the way
in which Ticketmaster.com has digitalized the purchase of
concert tickets.
· Metal detecting: Metal detecting is a hobby where people
search for buried metallic objects and artifacts using a metal
detector. Our study focused on a Nordic country with an
estimated one to two thousand hobbyists who submit several
thousand finds to the local authority that handles archeo-
logical finds (https://www.kulttuuriymparistomme.fi).
· Geocaching: Geocaching is an outdoor treasure hunting
game that combines physical activity and technology.
Geocachers use global position system (GPS)-enabled
devices, and they navigate to specific GPS coordinates to
find the geocache (container) hidden at that location. In
Tuunanen et al. 5
2021, there were over five million active geocachers
worldwide (www.geocaching.com).
Three study contexts were identified as B2B digital services,
while the other two primarily operated on a C2C basis. With
respect to the two C2C digital services, the hobbyists’ activity—
that is, the number of years of activity within the metal detecting
hobby or the number of found geocaches—was used as a proxy
for indicating a participant’s activity. The number of laddering
interview chains (data units), interviewees per study, the av-
erage number of chains per interview, and the average interview
durations per study are depicted in Table 1. Examples of lad-
dering interviews are described in Peffers, Gengler, and
Tuunanen (2003), Tuunanen and Kuo (2015), and Tuunanen
and Peffers (2018).
Data Coding
After the data collection phase of each study, the laddering in-
terview chains were aggregated into matrices. The researchers
developed codes one by one for the attribute, consequence, and
value/goal items of the chains (Peffers, Gengler, and Tuunanen
2003). Emerging attribute (A), consequence (C), and value (V)
codes were transcribed. In cases wheremultiplemeanings emerged
from a single chain, the chains were divided into multiple threads
for coding. Although most chains were coded with all three codes
(A, C, and V), in some chains, no A and/or C and/or V codes
emerged from the chain in question. Once all studies were coded,
the entire dataset totaled 1038 codes: 440 A codes represented the
triggering system features or circumstances, 317 C codes repre-
sented the reasons for customers’ perceptions, and 281 V codes
represented customers’ personal goals or values.
The derived codes were later used for clustering analysis in
each study, as depicted in Tuunanen and Peffers (2018). For the
meta-analysis for this study, we did not employ the previous
clustering analysis results of the individual studies. Instead, we
revised and meta-coded the original coding of each study in two
phases. Previous laddering researchers have advocated using
multiple coders to reach a high degree of agreement (Klenosky,
Gengler, and Mulvey 1993; Peffers, Gengler, and Tuunanen
2003; Reynolds and Gutman 1988). Therefore, two researchers
first revised all codes of the dataset and the coherence of the
laddering chains’ A, C, and V codes. Thus, we aimed to ensure
consistency and a suitable level of precision and abstraction
without an excess loss of detail. In cases of conflicting
assessments between the two researchers, conflicts were re-
solved via consensus. Both coders mutually suggested most of
the concluded changes (64–79%).
Subsequently, the paper’s first author evaluated the final
codes, concluding that the differences between the propositions
of the two individual coders were insubstantial and that the final
codes were consistent and representative. In total, 196 changes
were made in the original dataset, but only 48 of the changes
were proposed by a single coder. The high agreement level
reflects the overall high quality of the dataset, the coding
process, and the protocol used.
In the second phase, two researchers meta-coded the final
codes with system value propositions and customer value
drivers, as proposed by Tuunanen, Myers, and Cassab (2010).
The goal of the meta-coding was to apply the framework as a
lens for attaining a unified means of analyzing value co-creation
with service customers over the entire dataset. Thus, the final C
and V codes were classified by the six framework constructs
(i.e., meta-coding themes), namely, (1) social nature of use, (2)
construction of identities, (3) context of use, (4) participation in
service production, (5) service experience, and (6) goals and
outcomes. We started by aggregating and standardizing the data
from all five study contexts so that the headings and contents
were identical in spreadsheet format. Subsequently, the two
researchers reviewed the dataset, meta-coding each C and V
code item by item in a 3-day workshop. New themes were
derived in cases in which the existing framework constructs
(Tuunanen, Myers, and Cassab 2010) were identified as inap-
plicable. If a theme could not be explicitly concluded for an
item, information from the original chain was reviewed to
provide more elaborate insight into the use context of the code
in question. As a result, the data were meta-coded with 11
themes. The original construct, goals and outcomes, were di-
vided into two themes: (6) hedonic values and (7) utilitarian
values. Furthermore, four new themes were identified: (8)
decision making and support, (9) reliability and credibility, (10)
customer orientation, and (11) access to information. Table 2
depicts the final meta-coding themes 1–11 along with
exemplars.
Data Analysis – Interpretive Structural Modeling
We adopted the interpretive structural modeling (ISM) approach
to analyze the data. ISM is a qualitative method used to reveal
the structure of complex relationships among elements of a
Table 1. Dataset.
Study Laddering Chains Interviews Average Chains per Interview Average Interview Time
Online CRM 287 21 13.6 45 mins
Intelligent cyber-physical system for mining 266 20 13.3 30 mins
Event organizing and planning system 321 22 14.6 50 mins
Metal detecting 478 24 19.9 75 mins
Geocaching 336 26 12.9 35 mins
Total 1688 113
6 Journal of Service Research 0(0)
system (Malone 1975). A structural model of the elements
emerges within the context of the ISM, depending on the
connections of the elements to each other (Warfield 1994). In
recent years, ISM has been widely adopted in various contexts.
The studies vary from assessing information systems quality
(Kanungo and Bhatnagar 2002) and the agility of the supply
chain (Singh et al. 2003), to web interface design (Lee, Chao,
and Lin 2010). ISM constructs can be derived by combining a
literature review and expert interviews or can be solely based on
a literature review. The steps involved in the ISM approach are
depicted in Online Appendix 3.
We derived the ISM constructs from previous literature and
a meta-analysis of our laddering interviews (Guo, Li, and
Stevens 2012), that is, the meta-coded constructs (cf. Table 2).
We established contextual relationships between each of these
constructs by performing a pairwise comparison between each
construct and developing adjacency matrices with multiple
thresholds. After analyzing the meta-coded dataset, we
identified 3006 relationships between the consequence and
value codes. Preparing an ISM structure involves many steps
and details, as described in Online Appendix 3. The final set of
constructs in the ISM analysis was as follows: (1) social nature
of use, (2) construction of identities, (3) context of use, (4)
service experience, (5) customer participation, (6) utility
values and goals, (7) hedonic values and goals, (8) decision
making and support, (9) reliability/credibility, (10) customer
orientation, and (11) access to information. These were labeled
as S1 to S11, respectively.
We derived the following matrix based on all five digital
services: Each entry in the original matrix indicates how many
times the relationship from one construct (at a row) to another
(at a column) was mentioned in the interviews. Some rela-
tionships were substantially weaker than others (fewer hits), and
thus could be removed. To focus only on relevant connections,
we tested several thresholds to remove weaker connections
while uncovering important hierarchical relationships. This was
done to ensure that the resulting hierarchy was not overly
cluttered. We obtained the adjacency matrix for the threshold we
set to be 11; those mentioned less than 11 times were considered
weak relationships and were thus removed. Table 3 summarizes
the threshold tests for each case and the merged cases. As the
threshold increases, the number of connections between nodes
drops. In general, during a specific threshold range, the model
stabilizes in terms of having the same number of hierarchical
levels and similar patterns of connections.
We then performed the calculation for the reachability matrix
in RStudio, calculating (A + I)≠ [(A + I)]^2≠(A + I)^3≠…≠(A +
I)^(n-1)=(A + I)^n, and we get (A + I)^3 = (A + I)^4, and
produced the reachability matrix. Lastly, a level partition is
performed based on the reachability matrix. Here, four iterations
of four levels were derived: level 1 contains constructs 6 and 7;
level 2 contains constructs 3, 4, 8, and 9; level 3 contains
constructs 2 and 10; and level 4 contains constructs 1, 5, and 11.
The ISM graphs were then derived. All the above matrixes are
available in Online Appendix 4.
Findings
This section presents our findings about micro-level value co-
creation mechanisms that support the design of a joint digital
value co-creation sphere between a service provider and cus-
tomers (Table 4). We describe newly found constructs and how
to extend earlier findings regarding the goals and outcomes
construct. We also show how the digital service type affects
mechanism interdependencies. Lastly, we present a model that
summarizes the micro-level value co-creation mechanisms,
which we operationalize as propositions.
Our study reveals new constructs related to B2B digital
services, contrary to the findings of Tuunanen, Myers, and
Cassab (2010). These are (1) access to information, (2) cus-
tomer orientation, (3) decision making and support, and (4)
reliability/credibility. We define “access to information” as
related to the availability of information and the ability to follow
up on the information continuously; “customer orientation”
pertains to customer satisfaction and understanding the cus-
tomer’s needs; “decision making and support” are related to
making prompt and correct decisions; and “reachability and
credibility” are associated with the digital service’s trust,
Table 2. Constructs and Exemplars of Meta-coded Items.
Construct Example Consequence Codes Example Value Codes
1) Social nature of use Getting more contacts Social relationships and identification
2) Construction of identities Developing profile Status value
3) Context of use Going/finding new places —
4) Participation in service production Making participation easier Real-time awareness
5) Service experience Making it possible to attain goals together Motivating users
6) Utilitarian values Making current processes more efficient and easier Economic gains
7) Hedonic values Challenging oneself Enjoyment, gratification, and satisfaction
8) Decision making and support Can advise in real-time Quick and right decisions
9) Reliability and credibility Personal feedback is more reliable Common trust, reliability, safety, and
appropriateness
10) Customer orientation Understand the customer’s needs Customer satisfaction
11) Access to information Continuous/Real-time follow up Availability of information
Tuunanen et al. 7
reliability, safety, and appropriateness, which enable reliable
personal feedback.
Our findings also show that the original “goals and out-
comes” construct should be split into “utilitarian values and
goals” and “hedonic values and goals.” The context of the
digital service in each case affected the nature of the emerging
values and goals construct. Although there were more utilitarian
values and goals in the B2B digital services, we also found them
in the C2C digital services and vice versa (see Table 5).
The findings show how the digital service type (B2B or C2C)
affects mechanism interdependencies and how the weights
differ. We analyzed the complete dataset to assess the inter-
dependencies between mechanisms and how these vary be-
tween B2B and C2C digital service types. These findings are
summarized in Table 5, including a description of the generated
event. More specifically, whereas interdependencies such as the
“social nature of use–construction of identities” or “access to
information–customer orientation” are straightforward and
emphasized in B2B or C2C digital service types, the interde-
pendencies are more mixed. An example is “access to
information–service experience,” which shows a heavier em-
phasis on B2B but still holds a 15% weight on C2C.
We also observe that hedonic values and goals are more
visible with C2C digital service types among the mechanism
interdependencies; conversely, utilitarian values and goals drive
behavior in B2B digital service types. However, the results are
interesting when hedonic and utilitarian values and goals affect
the interdependencies of the mechanisms. First, there are in-
terdependencies between the two values. Second, the mecha-
nism interdependencies related to the service experience
construct are reported with either a balanced weight of 50/50
(service experience–hedonic values and goals) or a nearly
balanced weight of 62/38 (utilitarian values and goals–service
experience). Figure 1 depicts the pathways that we identified
and how these interdependencies are organized.
Figure 1 conceptualizes our findings regarding micro-level
value co-creation mechanisms and the propositions listed in
Table 5. The figure presents the interdependencies between the
depicted mechanisms and how these infer the design of digital
services. It also shows the linkages (arrows between constructs
in the figure) between the constructs and the value co-creation
process (a sequence of value co-creation activities). In what
follows, we operationalize the proposed mechanisms as a set of
propositions.
First, we recognize value co-creation mechanisms related to
the sociality of digital service use and access to information
(P1a–d). We define this as the “social service use” pathway. We
propose that the social nature of use is linked to the construction
of identities (P1a) in C2C digital services. Furthermore, the
construction of identities is linked to reliability/credibility (P1b)
in B2B digital services, and access to information is linked to
reliability/credibility (P1c) in B2B and C2C services. The P1a–c
mechanisms are linked to values and goals constructs (P1d).
Reliability/credibility is linked to utilitarian value and goals
Table 3. Summary of Threshold Tests.
Study Threshold Tested
1: Online CRM Threshold = 1, 2, 3, … 8
2: Intelligent cyber-physical system for mining Threshold = 1, 2, 3, … 8
3: Event planning and organizing system Threshold = 1, 2, 3, … 6
4: Metal detection Threshold = 3, 4, 5, … 9
5: Geocaching hobby Threshold = 2, 3, 4, …14
Studies 1, 2, and 3 Threshold = 2, 3, 4, … 17
Studies 4 and 5 Threshold = 3, 4, 5, … 60
All five studies Threshold = 5, 6, 7, … 52
Table 4. Key Findings of the Study.
Key Findings Description
New constructs Earlier findings by Tuunanen, Myers, and Cassab (2010) extended with new constructs related to
B2B services, design of digital services, and value co-creation.
Utilitarian and hedonic goals and outcomes
constructs
Our findings show that Tuunanen, Myers, and Cassab (2010) original “goals and outcomes”
constructs do not fully reflect the reality of B2B and C2C services. These have been divided into
“utilitarian values and goals” and “hedonic values and goals.”
Digital service type affects mechanism
interdependencies
Hedonic values and goals are more visible with C2C digital service types among the mechanism
interdependencies, whereas utilitarian values and goals drive the behavior with B2B digital service
types. Further, hedonic and utilitarian values and goals affect the mechanisms’ interdependencies
between the digital service types.
Value co-creation mechanisms and
propositions
Interdependencies between the depicted mechanisms infer the design of digital services and
represent the linkages between the constructs and the value co-creation process. We
operationalize the proposed mechanisms as a set of propositions (P1a–P5).
8 Journal of Service Research 0(0)
with B2B digital services and C2C digital services. Reliability/
credibility is linked to hedonic values and goals in C2C digital
services. Access to information is linked to utilitarian values and
goals in B2B digital services and hedonic values and goals in
C2C digital services. Lastly, the social nature of use is linked to
hedonic values and goals in C2C digital services.
Second, we identify value co-creation mechanisms related to
access to information, customer participation, and decision
making and support (P2a–d). We define this as the “customer
decision-making” pathway. Here, we propose that “access to
information” is linked to customer orientation (P2a) in B2B
digital services, such as customer participation (P2b). Customer
Table 5. Value Co-creation Mechanism Pathways, Propositions (Prop.), Interdependencies, Weights, and Total Hits.
Pathway Prop Interdependency B2B, % C2C, %
P
“Social use” P1a Social nature of use–Construction of identities 0 100 17
P1b Construction of identities–Reliability and credibility 100 0 16
P1c Access to information–Reliability and credibility 83 17 18
P1d Reliability and credibility–Hedonic values and goals 3 97 33
Social nature of use–Hedonic values 6 94 85
Access to information–Utilitarian values 93 7 90
Access to information–Hedonic values 8 92 66
“Customer orientation and decision making” P2a Access to information–Customer orientation 100 0 23
P2b Customer participation–Customer orientation 100 0 16
P2c Customer orientation–Decision making and support 100 0 12
Access to information–Decision making and support 100 0 23
P2d Decision making and support–Utilitarian values and goals 100 0 52
Customer orientation–Utilitarian values 100 0 23
Customer participation–Utilitarian values 94 6 17
Customer participation–Hedonic values 0 100 17
Access to information–Utilitarian values 93 7 90
Access to information–Hedonic values 8 92 66
“Service experience” P3a Access to information–Service experience 85 15 47
P3b Service experience–Utilitarian values and goals 62 38 29
Service experience–Hedonic values and goals 50 50 103
Access to information–Utilitarian values 93 7 90
Access to information–Hedonic values 8 92 66
“Service use context” P4 Context of use–Utilitarian values and goals 96 4 23
Context of use–Hedonic values 4 96 23
“Customer values and goals” P5 Utilitarian values and goals–Hedonic values and goals 5 95 66
Hedonic values–Utilitarian values and goals 16 84 19
Figure 1. Value co-creation mechanisms and propositions.
Tuunanen et al. 9
orientation, in turn, is linked to decision making/support (P2c)
in B2B digital services. The P2a–c mechanisms are linked to
values and goals constructs (P2d). Decision-making support
links to both utilitarian and hedonic values and goals in B2B
digital services. Customer orientation similarly links to both
utilitarian and hedonic values and goals in B2B digital services.
Customer participation and access to information are linked to
utilitarian values and goals in B2B digital services. However,
customer participation and access to information are also linked
to hedonic values and goals in C2C digital services. Access to
information is linked to utilitarian values and goals in B2B
digital services and hedonic values and goals in C2C digital
services.
Third, we recognize value co-creation mechanisms related to
access to information and service experience (P3a-b). We define
this as the “service experience.” Namely, access to information
is linked to the service experience (P3a) in B2B and C2C digital
services. Service experience is strongly linked to utilitarian and
hedonic values and goals (P3b) in both B2B and C2C digital
services. We also identify a value co-creation mechanism re-
lated to the context of use and its linkage to the values and goals
construct (P4). We define this as the “service use context”
pathway. Here, utilitarian values and goals are linked to B2B
digital services and hedonic values and goals to C2C digital
services. Lastly, we identify a linkage between utilitarian and
hedonic values and goals, as well as between hedonic values and
goals and utilitarian values goals in C2C digital services (P5),
which we define as the “customer values and goals” pathway.
Next, we discuss the implications of the findings for both
research and practice.
Implications for Research and Practice
Our study contributes to the literature in several ways. First, our
study is one of the first to focus on the micro-level mechanisms
that support the co-creation of value in the design of digital
services. Given the digital-first world in which we now live in,
digital services have become just as, if not more important than,
physical services. With digital transformation being the priority
for many managers, we need to better understand how to le-
verage the value co-creation potential of digital services through
their design. Our findings provide a concrete way to analyze
how different aspects of digital service use may impact cus-
tomers’ value co-creation behavior.
Our primary theoretical contribution is the identification
of a set of micro-level value co-creation mechanisms
(Figure 1) and propositions (Table 5). Our findings explicate
the connection between high-level digital service features—
that is, the ISM constructs (cf. Table 5). Furthermore, the
depicted mechanisms and interdependencies indicate how
value co-creation may be enabled and enhanced for digital
services. Furthermore, we propose a set of pathways for the
interdependencies between the recognized mechanisms and
how these affect the co-creation of value for B2B or C2C
digital services. Some of these pathways are more impactful
for B2B digital services than for C2C. For example, the
customer decision-making pathway affects only B2B digital
services. However, the affiliated customer participation–
hedonic values and goals interdependency has an impact
only on C2C digital services. Access to information–hedonic
values and goals interdependency similarly leans toward a
C2C emphasis, although there is some impact on B2B digital
services.
Although the emerging mechanisms vary across digital
service types (B2B and C2C), our analysis reveals that access to
information is a foundational mechanism for co-creating util-
itarian and hedonic values and goals, particularly in the B2B
context. Each distinct interdependency between mechanisms
emerging across digital service contexts is depicted and de-
scribed in Table 5.With the depicted interdependencies between
mechanisms, we investigated the empirical phenomenon of
value co-creation from the perspective of digital service users.
We argue that by exploring such processes and activities, the
mechanisms and interdependencies we have identified reveal
how and why digital service customers experience the emer-
gence of value in the joint digital co-creation sphere with the
service provider. This offers a new approach to studying and
understanding value co-creation, which builds on the joint co-
creation sphere argument by Gro¨nroos and Voima (2013).
Our findings also suggest that, for the service experience
pathway, utilitarian and hedonic values and goals have nearly an
equal impact on B2B and C2C digital services. This finding
contrasts with what was previously proposed in the literature
(e.g., Prebensen and Rosengren 2016). In other words, we argue
that when considering how to enable value co-creation with/
among digital service customers, biases toward either a focus on
hedonic or utilitarian values and goals are not supported. In-
stead, the impact of these two is nearly equal for both digital
service types, contrary to many of the other interdependencies
between the emerging mechanisms. Here, we see a difference
compared to what, for example, Sandstro¨m et al. (2008) pro-
pose, with a filtering effect of situational factors affecting how
digital service customers perceive value outcomes. We do not
argue that the context of digital service is irrelevant—as our
findings also show that it does have an impact—but instead, we
posit that both hedonic and utilitarian values and goals of digital
service customers should receive equal focus in the design of
both B2B and C2C digital services.
Second, instead of taking a service design process, service
systems, or platform ecosystem perspective, which is common
in the extant literature (see, for example, Vargo et al. 2008; Yu
and Sangiorgi 2018; Vargo, Koskela-Huotari, and Vink 2020),
our study has examined value co-creation mechanisms at the
micro-level (Storbacka et al. 2016) that have an impact on using
digital services at a design level. Specifically, we examined the
level of groups or types of digital services or a single service,
that is, how customers derive value from digital service in-
teractions. Hence, we have not focused on the firm perspective
in service exchange but on the customers’ perspective of using
the service. The depicted mechanisms and their interdepen-
dencies explain how value co-creation occurs in digital service
contexts. The implications of the derived mechanisms are linked
10 Journal of Service Research 0(0)
to the implementation of value co-creation, as enforcing and
improving the highlighted mechanisms through the design of
digital services may continuously enhance and enable value co-
creation with customers.
Finally, our study offers a methodological contribution. We
identified the mechanisms that generate value co-creation
events using the ISM analysis of the laddering interview
data. Focusing on how the occurrence of mechanisms varies
across different digital service contexts, we demonstrated that
the type and context of a digital service impact the mechanisms
of value co-creation. Our findings underscore that customers’
hedonic and utilitarian values and goals are connected to the
other emerging constructs via the three lower hierarchical
levels. In their ISM study, Guo, Li, and Stevens (2012) describe
such emerging high-level constructs as outcome constructs or
dependent variables, which we describe as hedonic and utili-
tarian values and goals. In the next section, we illustrate how
service managers and designers can use this methodology to
support the practice of service design.
Implications for the Service Design Practice
Our study provides applicable tools for service designers and
managers to improve the design of their digital services. Below
we provide a scenario of using value co-creation mechanisms
to design a digital service and use one of the digital services
included in the study as an exemplar: an intelligent cyber-
physical system for mining (Ha¨nninen, Tuunanen, and
Vartiainen 2015).
We used the same recruitment protocol for the study par-
ticipants, as reported earlier in the research methodology sec-
tion. We recruited 20 industry experts (demographic
information is available in Online Appendix 2). The data
collection followed the approach described earlier of first de-
veloping a stimuli list that fits the study context, and then
laddering interviews were conducted with the study partici-
pants. The full dataset included 1420 individual statements by
the interviewees. The data analysis included coding the lad-
dering interview data and a thematic cluster analysis (Ha¨nninen,
Tuunanen, and Vartiainen 2015), which followed Tuunanen and
Kuo’s (2015) procedure.
The outputs of the data analysis were several thematic maps
(Ha¨nninen, Tuunanen, and Vartiainen 2015) that depicted how
different service features (attributes) were connected to the
values and goals (values) of the system users and the reasoning
behind the connections (consequences). Service designers and
managers can, therefore, use these thematic maps to understand
how the service is perceived by their customers. Figure 2 depicts
an exemplar map of the “sharing and receiving information
related to intelligent equipment” theme. The numbers on the
Figure 2. Sharing and receiving information related to intelligent equipment, adapted from Ha¨nninen, Tuunanen, and Vartiainen (2015).
Tuunanen et al. 11
map indicate the frequency of a code in the dataset. For ex-
ample, the attribute code “data collection” was mentioned 41
times. From the map, we observe that the “data collection”
attribute (including features related to “Equipment health,”
“User,” “Process,” and “Environment”) is linked to several
reasons, for example “Interpret conditions real-time,” and why
it was considered important for the “Real-time awareness” and
“Reliability” goals of the company. The map also shows that
several reasonings can be connected to an attribute, like in the
case of “data collection,” and the reasonings can be connected.
Similarly, values and goals may be interconnected as described
in the example chain of attributes–consequences–values.
The number of times a code is mentioned in the data can be
used for prioritizing service features as suggested by Tuunanen
and Kuo (2015). Tuunanen and Peffers (2018) later reported that
a daily newspaper, at the time the largest Newspaper in the
Nordic countries, developed a 3-year development roadmap for
their digital service based on similar thematic maps and pri-
oritization information of service features. The firm successfully
followed the roadmap to develop the digital service operating
the newspaper’s ad trafficking system. This showcases the
utility that service managers and designers can achieve with
laddering interviews and analysis of the data. Based on our
experience with undergraduate and graduate students, the ap-
proach can be taught with two 2-hour workshops. The first
workshop focuses on the laddering interviewing technique, and
the second on the coding and thematic analysis of the data. We
have trained hundreds of students to use the approach over the
past 15 years.
While these maps inform the company regarding important
service features and their rationales, they do not explain how
their customers co-create value with the digital service.
Therefore, in this study, we developed several ISM graphs with
different thresholds by performing an ISM analysis. Note that
the earlier thematic maps are not required for the ISM analysis
or vice versa, but both offer additional utility for the practice of
service design. Figure 3 shows the value co-creation mecha-
nisms and their interdependencies for the intelligent cyber-
physical system for mining with a threshold of 7. The figure
also includes references to the propositions (see Table 5 for the
interdependencies). We recognize that the “customer orientation
and decision making” mechanism is fully presented in the in-
telligent cyber-physical system for mining (propositions P2a-d);
similarly, we see that “service use context” is present (propo-
sition P4). However, “service experience” is only partly im-
pacting the use of this digital service (proposition P3a).
Consequently, based on the model, the company can now
visualize which laddering interview chains, corresponding
values and goals, and service features are affecting the micro-
level value co-creation mechanisms for its customers. For ex-
ample, by studying Figure 2, we observe that laddering chains,
including “camera system” and “remote monitoring,” link to the
system’s reliability. The full interview dataset, in turn, includes
detailed descriptions of the service features under each attribute
code, such as the “camera system.” Tuunanen, Salo, and Li
(2022) provide further insights into how laddering interview
data can be used to design modular digital services. By applying
this approach, service designers and managers of the company
can understand the value the system provides to their customers
and how they co-create value while using the system.
We suggest the proposed micro-level value co-creation
mechanisms can guide design efforts to support new service
development and to revise or update extant digital service
offerings. Although this higher-level view may be sufficient
for the practice of service design, the insights may be
complemented by a more detailed analysis of inherent value
co-creation mechanisms and their interdependencies through
a research endeavor, as described above. The custom-made
study with data laddering and the ISM analysis approach
provides a more detailed view. However, although the higher-
level view offered by the theory may be sufficient for the
practice of digital service design, Figure 3 shows an inter-
dependency between decision making/support and
reliability/credibility that is not explained by our theory. This
finding is not unexpected, as the threshold for analyzing a
single digital service differs from the threshold used to
Figure 3. Value co-creation mechanisms and their interdependencies for the intelligent cyber-physical system for mining (threshold 7).
12 Journal of Service Research 0(0)
analyze the entire dataset. In other words, the interdepen-
dency between these two mechanisms is important for this
digital service, but this was not the case for the entire dataset.
This finding was specific only to the intelligent cyber-
physical system in the mining context in our dataset.
This alternative result shows the importance of under-
standing the context in which digital services are used. Al-
though most of the interdependencies are explained by the
theory, we recommend that designers and managers use
existing data or collect new data to understand how value is
co-created by their customers while using their digital ser-
vices. We expect that the theory will explain most interde-
pendencies for other digital services, but not all of them.
Applying the obtained insights should lead to better design of
digital services while not adding significant new resource
needs or costs to the company.
Concluding Remarks and Limitations
Given that most services are now digital—or at least digitally
enabled—this study has focused on identifying micro-level
value co-creation mechanisms to support the design of digital
services. Our findings show that the context of a digital service
significantly impacts the value co-creation mechanisms of
digital services. We propose a set of micro-level value co-
creation mechanisms and their interdependencies, showing
how value co-creation may be enabled and enhanced for de-
signing digital services (see Figure 1). We also depict a set of
propositions for conceptualizing the mechanisms (see Table 5).
As with any study, the findings of this study are subject to certain
limitations. We acknowledge that our study is based on five digital
services only. Hence, our findingsmight not be fully generalizable to
the design of all digital services. Further, the thresholdwe used in the
analysis of our results impacts the generalizability of the findings.
However, as our exemplar digital service describes (Figure 3), the
theory explainsmost of the interdependencies.We suggest that more
research is needed to understandwhy andwhether newmechanisms
emerge from studying other digital services and their interdepen-
dencies. This will most likely suggest new propositions to depict the
value co-creation mechanisms. Our findings offer a foundation for
such research.
Additionally, we acknowledge that we did not include B2C-
type digital services in our study. We suggest that future studies
could investigate the applicability of the proposed theory to
B2C digital services. Another limitation is that our dataset
included respondents from only one European country. Thus,
further studies in other regions and cultural settings should be
considered. Lastly, although we think that a laddering interview
with an ISM analysis approach provides a robust way to un-
derstand value co-creation mechanisms and their interdepen-
dencies in the design of digital services, other research methods
could be considered in the future.
Despite these limitations, we believe that this study offers a novel
contribution to the literature regarding the design of digital services.
We contribute to the conceptualization and theorization of value co-
creation (Breidbach and Maglio 2016; Gro¨nroos and Voima 2013;
Grotherr, Semmann, and Bo¨hmann 2018; Lusch and Nambisan
2015; Payne, Storbacka, and Frow 2008; Prahalad and Ramaswamy
2004b; Vargo, Maglio, and Akaka 2008; Vargo and Lusch 2017;
Vargo, Koskela-Huotari, and Vink 2020). In contrast to previous
contributions that have focused on value co-creation at the eco-
system level (see, for example, Vargo, Koskela-Huotari, and Vink
2020), we have focused more narrowly on individual and micro-
level service customer perspectives (Storbacka et al. 2016). This
said, we recognize the need to study value co-creation mechanisms
at a meso-level. When considering value co-creation for designing
services, Ghotherr et al. (2018) define the meso-level as the service
platform where resource integration is done by different actors.
Consequently, based on our findings, we argue that studying meso-
level value co-creation mechanisms can offer novel insights, es-
pecially on how to design a digital service platform (De Reuver,
Sørensen, and Basole 2018).
Finally, we believe our findings should be of interest to re-
searchers and practitioners in designing and developing digital
services. A better understanding of the micro-level value co-creation
mechanisms of their customers may lead firms to design better
service experiences and, consequently, increase their revenues.
Firms may utilize the proposed theory and methodological insights
to enhance their current digital services and/or the design of new
services. We suggest future research should consider how to use
micro-level value co-creation mechanisms in the service design
process and/or specific service design activities, especially in de-
signing digital services. This research can lead to the development of
new digital service designmethods that would incorporate tool-level
support for the application(s) of the value co-creation sphere
(Gro¨nroos and Voima 2013).
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to
the research, authorship, and/or publication of this article.
Funding
We thank Foundation for Economic Education for the financial support
for this research.
ORCID iDs
Tuure Tuunanen  https://orcid.org/0000-0001-7119-1412
Juuli Lumivalo  https://orcid.org/0000-0001-7458-7869
Michael M. Myers  https://orcid.org/0000-0001-8525-6395
Supplemental Material
Supplemental material for this article is available online.
Notes
1. https://en.wikipedia.org/wiki/System
2. A black box is a system which can be viewed in terms of its inputs
and outputs (or transfer characteristics), without any knowledge of
its internal workings. Its implementation is “opaque” (black).
https://en.wikipedia.org/wiki/Black_box
3. Awhite box is a system, which can be viewed in terms of its inputs and
outputs (or transfer characteristics), but whose internals can be viewed.
Tuunanen et al. 13
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Author Biographies
Tuure Tuunanen is Chair Professor of Information Systems at
Uppsala University, and Professor of Information Systems at
University of Jyva¨skyla¨. Tuure is also Global Faculty Fellow at
Center for Service Leadership, Arizona State University. His
current research interests include digitalization of services,
digital service design and cyber-physical service innovations.
Juuli Lumivalo Postdoctoral researcher in Faculty of Infor-
mation Technology, University of Jyva¨skyla¨ (Finland). Her
current research interests include smart services for sustainable
transition, understanding service users and requirements, con-
tinuous digital/cyber-physical service innovation, technology as
an actor, and the service-dominant logic lens for viewing value
co-creation and co-destruction.
Tero Vartiainen is Professor of Information Systems in the
Department of Computing Sciences at the University of Vaasa,
Finland. His research interests lie in the areas of cybersecurity,
IT services, energy informatics, IT project management, and
computer ethics.
Yixin Zhang is Senior Lecturer in the Department of Applied
Information Technology, University of Gothenburg in Sweden.
Her research interests include social media, empowerment,
digital innovation, and digital resilience. She has published in
journals such as Information Systems Journal, Information and
Management, and International Journal of Information
Management.
Michael D Myers is Professor of Information Systems at the
University of Auckland Business School, Auckland, New
Zealand. He is a Fellow and LEO award winner of the Asso-
ciation for Information Systems. Michael currently serves as
Editor-in-Chief of European Journal of Information Systems.
16 Journal of Service Research 0(0)