ArticlePDF Available

Abstract and Figures

Current views on value creation emphasize the role of the customer, mutual investments, and value co-creation. Nevertheless, at present the customer-focused research concentrates on value expectations and value experiences as outcomes but disregards the analysis of potential value that is dependent on the customer’s activity and learning in the process. The present study explores customer perceived value as a multidimensional phenomenon incorporating expected, realized, and potential dimensions. Using a real-life experiment, the study shows the role of customer learning particularly in realizing the potential value of novel technological services. To understand and achieve the potential value, customers need first to unlearn their current practices, second, to learn how to use the novel service, and third, to envision the best ways to use the novel service. Hence, a sacrifice made in the present day (i.e. learning efforts) will increase the potential value-in-use in the future.
Content may be subject to copyright.
RESEARCH ARTICLE
J Bus Mark Manag (2013) 1: 1–21
URN urn:nbn:de:0114-jbm-v6i1.400
Published online: 29.03.2013
----------------------------------------
© jbm 2013
----------------------------------------
H. Komulainen · Tuija Mainela · Jaana Tähtinen
University of Oulu, Oulu, Finland
e-mail: hanna.komulainen@oulu.fi; tuija.mainela@oulu.fi; jaana.tahtinen@oulu.fi
* The authors have contributed equally
Customer’s Potential Value: The Role of Learning
Hanna Komulainen · Tuija Mainela · Jaana Tähtinen*
Abstract: Current views on value creation emphasize the role of the customer,
mutual investments, and value co-creation. Nevertheless, at present the customer-
focused research concentrates on value expectations and value experiences as
outcomes but disregards the analysis of potential value that is dependent on the
customer’s activity and learning in the process. The present study explores customer
perceived value as a multidimensional phenomenon incorporating expected, realized,
and potential dimensions. Using a real-life experiment, the study shows the role of
customer learning particularly in realizing the potential value of novel technological
services. To understand and achieve the potential value, customers need first to
unlearn their current practices, second, to learn how to use the novel service, and
third, to envision the best ways to use the novel service. Hence, a sacrifice made in
the present day (i.e. learning efforts) will increase the potential value-in-use in the
future.
Keywords: Value co-creation · Interaction · Resource integration · Many-to-many
networks · Service-dominant (S-D) logic · Relationship marketing
Acknowledgements: The financial support of the Academy of Finland is gratefully
acknowledged. The authors wish to thank the organizations whose invaluable
collaboration has made this study possible.
Customer’s Potential Value: The Role of Learning
2
Introduction
The current views on service business, such as service logic (Grönroos, 2008; 2011)
and the service dominant logic (Vargo & Lusch, 2004; 2008), emphasize need for
mutual investments and the active roles of both parties in value creation, since that
process determines the value-in-use for the customer (Edvardsson et al., 2005;
Kowalkowski, 2011; Macdonald et al., 2011). Research has approached value as
either a static concept (e.g., Liu et al. 2005, Menon et al. 2005; Ulaga 2003) or when
temporal, focused on consumers’ past expectations and present experiences (e.g.,
Flint et al., 2002; Parasuraman, 1997; Woodall, 2003; Woodruff, 1997). However,
recent research (Möller, 2006; Möller & Rajala, 2007) emphasizes the need to take
into account the future orientation, too. Currently, little is known about the creation of
potential value that may be realized only in the future. The present study explores
customer perceived value as a multidimensional phenomenon incorporating expected,
realized, and potential dimensions and focuses on that very dimension of potential
value.
The exploration will take place in the context of novel technological services for the
following reasons. Firstly, the novel technological features of a business service make
the value not only difficult to assess before the actual consumption of the service, but
even during and after it, meaning that high levels of uncertainty are involved (Hogan,
2001). This emphasizes the need to envision the future and to conceive the potential
value of the service. Secondly, such services are often launched while still under
development, and they remain subject to near constant change as new versions are
introduced throughout the lifecycle (e.g., Curran & Meuter, 2005). This means that
once launched the service itself has not reached its full potentials yet and the
customer needs to keep up with the development of technology and learn to use (i.e.,
operate) and utilize (i.e., fully exploit) new versions of the service. Hence, customer
perceived value (CPV) might be very different at different points in time (see e.g.,
Green et al., 1996; Parasuraman, 1997). This makes the value of novel technological
services dynamic, future-oriented, and dependent on learning. However, research has
only recently begun to connect value creation and learning. Sanchez, Vijande and
Gutierrez (2010) state that a supplier’s learning is a direct antecedent of its customer’s
value creation capability, but customer’s learning efforts still await dedicated research
on them.
Although both benefits and sacrifices are commonly noted as playing important
roles in customer value perception (see Ulaga & Eggert, 2005), sacrifices have been
studied far less than benefits. Learning requires time and effort and therefore is a
significant sacrifice. Moreover, this study explores learning related to its role in the
temporality of CPV, in particular in the realization of potential value. Learning is viewed
as an investment. Its form changes over time: today’s sacrifices in learning, although
reducing the present net value of the service, may produce benefits tomorrow (see
Woodall, 2003). Hence, we argue that value is a dynamic phenomenon that may be
temporally past, present, or future oriented (see Stanley & Tyler, 2002) and that
learning is an investment-type sacrifice that largely determines the potential value
derived in the future.
Some research has been conducted on the value of technological consumer
services (e.g., Pura 2005, Heinonen 2004), but the research in business services
Customer’s Potential Value: The Role of Learning
3
context is underdeveloped. The present study thus extends the exploration of
temporality of value to the context of novel technological business services.
The study contributes to research on value creation in two specific ways. First, the
study conceptualizes CPV as a temporally changing phenomenon with expected,
realized, and potential value dimensions. The introduction of the potential value
concept adds future orientation to the current conceptualizations that focus primarily
on the past and present. Second, the study discusses learning as a sacrifice that
increases potential value achieved in the future. This questions the straightforward
analysis of benefits as increasing value and sacrifices as decreasing value.
Furthermore, the examination of the role of learning reveals the connectedness of the
expected, realized, and potential value dimensions.
The following theoretical section reviews value research, placing specific emphasis
on time-sensitivity and the role of learning. The empirical setting of the study, the
introduction and use of a novel technological business service, was chosen as it brings
out the future-oriented, potential value dimension that remains under-researched. The
methodological section describes a real-life experiment in which 40 companies using a
novel technological service were observed and the representatives of 17 of the
companies were interviewed on their experience. The findings from the empirical
analysis are then presented as a learning-driven three-dimensional conceptualization
of customer value. The final section discusses the theoretical and managerial
implications and limitations of the study.
Value Creation in Novel Technological Business Service
Value in the Service Context
Scholarly interest in value has shifted from an early focus on product-oriented value-in-
exchange to value-in-use, in other words, onto customers’ value creation processes
(e.g., Grönroos, 2008; Vargo & Lusch, 2004; Vargo et al., 2008). Accordingly, a
service provider can create a value proposition, but the value is determined by the
customer (Kowalkowski, 2011; Ulaga, 2011, Vargo & Lusch, 2008). This study adopts
the value-in-use perspective and, following Lapierre (2000), Ulaga and Eggert (2006),
and Woodall (2003), defines CPV as a subjective perception of the trade-off between
multiple benefits and sacrifices, relative to the competition. Benefits and sacrifices
stem from all service and relationship dimensions that customers perceive as
facilitating or blocking attainment of their goals in the value creation processes (see
Blocker, 2011; Woodruff, 1997).
A number of studies (e.g., Eggert & Ulaga 2002, Lapierre 2000, Menon et al. 2005)
categorize and classify CPV using the benefit-sacrifice approach. Within business
services, value has been categorized by Lapierre (1997) into exchange and in-use
elements, and in technological consumer services, Heinonen (2004) refers to two very
similar dimensions as the outcome of the service interaction and functional aspects of
the service delivery. However, these context-related categorizations do not discuss the
relationship between benefits and sacrifices longitudinally. Grönroos (2009), in turn,
divides sacrifices into short- and long-term variants. Short-term sacrifices include the
Customer’s Potential Value: The Role of Learning
4
price paid for the service and long-term sacrifices refer to investments made in the
relationship. Hence, this refers to the inevitable dynamism of value, which we will
examine next and thereafter, proceed to examine learning as a primary type of long-
term sacrifice.
Value as a Time-Sensitive Concept
Studies on CPV could be split into two types: static and temporal. Static studies lack
explicit consideration of value evaluated at different times (e.g., Menon et al., 2005; Liu
et al., 2005; Ulaga, 2003) whereas in temporal studies (e.g., Flint et al., 1997; Woodall,
2003; Woodruff, 1997) as well as service quality studies (e.g. Parasuraman et al.,
1985) the evaluation takes place at the time of the purchase decision, during use, and
afterwards. Hence, decision-making is based on a prediction of value, and only during
(or after) use can a customer experience the value. Adding more detail, Parasuraman
(1997) suggests that both the attributes customers use to judge value and the relative
importance of those attributes may change soon after the purchase, but also during
long-term use. This study adopts the temporal view and thus argues that both the
benefits and sacrifices have past, present, and future dimensions. They may be
expected, realized and/or potential and they change when evaluated at different points
of time.
Past, present, and future time act as reference frames for each other (Medlin
2004). Past time holds the memories and interpretations of events that are
remembered. What we remember is likely to be based on what we need in order to
understand the present and its attendant future possibilities (Mead 1932). Conversely,
future time is full of many possible alternatives, of which only one can become the
present (Luhmann 1979). However, these views of past and future as continuously
changing contexts can only be interpreted in the present, thus making it a complex
structure that relies on the existence of the past, in the form of learning, and the
existence of the future, as intentions and expectations (Luhmann 1979).
Next, the past, present and future aspects of time are considered against the
expected, realized, and potential dimensions of value. First, expected value, i.e., the
benefits and sacrifices customers expect to occur during the service use, even before
they start using it, strongly influences the customer’s willingness to try a novel service
(Komulainen et al., 2007). Parasuraman et al. (1985, 1991) suggest that customers
have an implicit range of expectations for the service based on a “standard”. In the
present study the service is, however, totally new and thus the customer has no real
“standard” on which to base the expectations. Instead, the closest similar service is
likely to be used as a point of comparison; in the case of m-advertising, that can be
traditional mass-market advertising. As a result, the traditional point of comparison
guides the expectations instead of the actual characteristics of the novel service. Thus,
customer’s potentially distorted and unrealistic value expectations need to be taken
into account specifically in the context of novel technological services. Flint et al.
(1997) use a concept of desired value, referring to what customers want to happen
and the benefits they seek. Here the concept of expected value is used to highlight
that there are both expected benefits and expected sacrifices.
Customer’s Potential Value: The Role of Learning
5
Second, the realized CPV refers to actual benefits and sacrifices customers
perceive when evaluating the service during and after its use. The evaluation of the
realized value takes place in the present time, although the target of the evaluation is
what happened in the past. Similarly, Flint et al. (1997) write of a value judgment that
reflects an assessment of what has happened in a specific use situation (in terms of
benefits and sacrifices).
Finally, as novel technological services are subject to continuous change and
development, customers can picture the optimal and improved service in the future.
This potential value is here seen as the trade-off between the benefits and sacrifices
the customers expect from the service in the future, when it will provide the best
possible value for them. Potential value thus refers not only to the improved future
releases of the technological service that may provide even more benefits, but also the
wide-spread use of the technology by other actors in the future. The latter may either
increase the value for the customer or it may migrate, if the actor has not adopted the
technological services with others (see Sharma 2002).
The realization of potential value is thus influenced by the actions of the service
provider, the customer, and the network actors instead of depending simply on the
passing of time. At the core of these actions are complex learning processes (Möller
2006; Möller & Rajala 2007) that form an investment-type sacrifice required to realize
the conceived potential value. Accordingly, if the customer sacrifices time and effort to
learn to use the novel service skillfully, the benefits are expected to increase more
than the sacrifices decrease the short term value. This follows the logic of Transaction
Cost Analysis (TCA) (see Rokkan, Heide & Wathne, 2003; Gosh & John, 1999).
Although TCA has more often been applied to the specific investments made by a
supplier to create value for the customer, this study suggests that customer
investments in learningwhich are sacrifices made today may increase or improve
benefits derived in the future, and so result in higher CPV. Therefore, we will next take
a closer look at learning and its role in CPV.
Organizational Learning in Customer Perceived Value
Learning refers to doing something better than before (Lewin, 1975 p. 65). It is a
mechanism and a process that improves organizational understanding and
performance (Bell et al., 2002; Senge, 1990) and thus represents a highly sought-
after, appreciated, and studied activity. Apart from at the individual level, learning can
take place at intra-organizational (e.g., Senge, 1990; Slater & Narver, 1995), dyadic
(e.g., Kodama, 2001), inter-organizational (e.g., Lane & Lubatkin, 1998), and network
levels (e.g., Powell, Koput & Smith-Doerr, 1996). This study focuses on company-level
learning and applies the concept of organizational learning.
Organizational learning could be adaptive and/or generative (Slater and Narver
1995).The adaptive type is the most basic form of learning and occurs within a set of
constraints both recognized and unrecognized that reflect the organization’s
assumptions about its environment and itself. As a result, learning is focused on
opportunities that are within the traditional scope of the organization’s activities.
Generative learning occurs when an organization is willing to question its long-held
Customer’s Potential Value: The Role of Learning
6
traditions or assumptions and focus on interrelationships and dynamic processes (see
also, Senge, 1990).
Learning is time-dependent as it refers to change (Lewin, 1975). It draws on
experiences and affects future action. Although temporality is always implicitly present
in the learning concept, existing research has not focused on the issue. An exception
is the study of Styhre (2006) who sees workplace learning as taking place through
continuous interaction, recollection, and anticipation of the past, present and future.
Without a full understanding of how a certain practice is dependent on previous
experiences and potential future events, learning (and changing the practice) becomes
very difficult. This highlights the importance of active unlearning in situations when the
organizational memory constrains generative learning (Slater & Narver, 1995; Bhatt,
2000). Organizational unlearning is viewed as “the discarding of old routines to make
way for new ones, if any” (Tsang & Zahra, 2008). Without unlearning new effective
routines are rejected within the organization, and the familiar ways of operating remain
in place.
To summarize, learning changes thoughts, attitudes and/or processes, requires
effort and is based on experience. In addition, learning is firmly linked to value
creation. Sanchez et al. (2010) suggest that learning by a supplier increases its
capability for customer value creation. Taking a customer view, customer learning
required to use a novel service and utilize its special features is a sacrifice made today
that increases the benefits derived tomorrow. CPV inherently includes temporal
dimensions that are here labeled expected value, realized value, and potential value.
Previous research has discussed them as separate concepts and focused on the past
and present (i.e., expected and realized) dimensions. In the context of novel
technological business services, the importance of the future dimension (i.e., potential
value) is heightened due to the novelty and constantly developing nature of the
service. As the value changes over time, it is likely that learning will also take different
forms. Specifically in terms of potential value, the role of learning is accentuated since
learning in the two previous time dimensions (i.e. expected and realized value)
influences the realization of the potential value in the future. Thus, it is important to
empirically explore the role of learning in temporal value dimensions, its influence on
the customer’s value perceptions over time and its connecting role for, and
embeddedness in, the expected, realized, and potential value dimensions.
Methodology
Empirical Research Setting
The technological business service that this study explores empirically is a mobile
advertising (m-advertising) service through which retailers send advertisements (ads)
to their customers’ mobile phones. The service enables sending unique, personalized,
and customized mobile ads (m-ads) cost-effectively as well as engaging customers in
personal real-time discussions and transactions with the retailer (Salo & Tähtinen,
2005). M-advertising is very different from traditional one-way advertising as it
efficiently identifies the receiver of the message. Hence, it should be used in a
Customer’s Potential Value: The Role of Learning
7
radically different way (see e.g., Choi, Stahl & Whinston, 1997; Salo & Tähtinen,
2005). Retailers cannot design and use m-ads in the same way as they might
newspaper ads, and that presents a learning challenge. They need to change their
ways of thinking about advertising and their practice to learn how best to apply m-
advertising. As such, the service offers a rich empirical setting to extend the theory of
CPV.
Research Method and Data Collection
Due to the new, complex, and context-dependent nature of the phenomenon, a case
study design (the m-advertising service being the case) and qualitative data collection
methods were chosen. A case study is particularly useful in situations where the
phenomenon is new and unknown and where current theories seem inadequate
(Easton, 1995; Eisenhardt, 1989). It offers a means of developing theory by utilizing in-
depth insights on empirical phenomena and their contexts (Dubois & Gadde, 2002).
The chosen research strategy follows an abductive theory-building approach (Peirce,
1957; Dubois & Gadde, 2002). The conceptualization presented is a result of a
continuous interplay between theory and empirical observation and a research
process that requires being open to new insights from either side to combine them
systematically into the research findings (see Dubois & Gadde, 2002).
The examination of value creation in m-advertising took place within a 7-week long
field trial. In it, a research project organized an m-advertising service system (for SMS
and MMS ads) and recruited 40 retailers to use it in the course of their daily business.
The method placed the focus on the retailer’s views of value before, during, and after
using the novel m-advertising service. The main data was gathered through thematic
interviews with 17 retailers (see Table A1). The selection of the interviewees was a
multi-stage process, in which all 40 m-advertisers were first interviewed by phone.
Based on their willingness to use the service in the future the advertisers were
categorized into ‘enthusiastic’, ‘doubtful’, ‘negative’, and ‘non-user’. The non-users had
signed up for the trial but never sent a single m-ad. Second, to increase variety,
retailers from each of the four categories were interviewed in person. The interviewees
were selected to represent three usage types; users themselves, those enlisting the
help of an advertising agency to use the service, and those who involved the research
team. Thus, the 17 retailers represent a large variety of experience and attitudes
towards m-advertising, and also various fields of retailing. This theoretical sampling
aimed to maximize the differences between the interviewees’ perceptions of value
(Glaser & Strauss, 1967; Spiggle, 1994).
Two researchers conducted the interviews after the seven-week trial period. The
thematic interviews covered five general areas: 1) Background information on the
company 2) Objectives for and expectations of / assumptions about mobile advertising
3) Experience of mobile advertising (including quality of training and guidance, design
and implementation of mobile ads, and use of the mobile advertising tool) 4)
Effectiveness and utility of mobile advertising 5) Suggested improvements to the
service. In addition, the specific experiences of each retailer were elicited by posing
additional questions. The audiotaped interviews were transcribed verbatim, resulting in
171 pages. In addition, being involved in the recruitment and initial training of the
Customer’s Potential Value: The Role of Learning
8
retailers and addressing their day-to-day problems during the trial allowed the
researchers to observe and take notes on discussions, which also developed an
understanding of the phenomenon.
Data Analysis
The interview transcripts formed the raw data of the analysis. The unit of analysis was
the retailers’ perceptions and conceptions of the value of the novel technological
service. The first interpretations of the data were based on multiple readings of each
transcript. Thereafter, the original verbatim interview data were imported to the QSR
N’Vivo software. The software facilitated the storing of the text, coding, searching, and
retrieving of text segments and stimulated the researchers’ interaction with the data
(see Dembkowski & Hanmer-Lloyd, 1995). The first multi-authored coding was based
on the researchers’ theoretical and empirical pre-understanding using two basic
coding categories; perceptions of value and learning. The concept of value was soon
divided into temporal dimensions of expected, realized and potential value, since a
single concept was insufficient to explain the variety in the retailers’ views.
The analytical question of what connects and influences the temporal value
perceptions led us to analyze retailers’ learning in greater detail. At this point, research
on organizational learning was reviewed to create a basis for a multidimensional
conceptualization. The concepts of adaptive learning, generative learning, and
unlearning were thereafter used to approach the data. During the coding process, free
nodes and memos were also created to store ideas that seemed to give meaning to
the data. The refined definitions and interpretations of the concept were tied to specific
words and lines within the transcripts, thus opening up the process to the scrutiny of all
the researchers involved. Interpretations of parts (whether segments of a transcript or
entire transcripts) were compared to each other following the constant comparative
analysis method (see Glaser & Strauss, 1967; Spiggle, 1994; Strauss & Corbin, 1998).
Finally, the categories describing value were crosschecked with categories of learning
to create a temporal picture of value in relation to types and objects of learning.
Findings
Dynamic Nature of Customer Perceived Value
Expected Value Dimension
The expected value refers to the difference between the benefits and sacrifices that
the retailer expects to experience when the service is used. The expected value
influences a customer’s willingness to use a novel service.
We had already requested offers, to find out what m-advertising would cost and
how it can really be done, like in practice. And then your project came along, and
we, kind of, could do that without paying, and with your help and all that. So things,
Customer’s Potential Value: The Role of Learning
9
well, became easier, so we decided to throw in our lot with you [joint the project]. Art
museum
Expected value is related to past events, i.e. the retailer’s previous experiences, as
it has the potential to contribute to its future performance (La & Kandampully, 2004). In
the case of a new service there can be no previous experience of the service, so
experiences of similar services in the past, or where available, knowledge of other
customers’ experience of the novel service are used. Therefore, in this case
unlearning (see e.g., Bhatt, 2000) previous experience from traditional mass
advertising is important.
Most of the retailers in the focal case based their expectations on their experience
of newspaper advertising, commonly used by local retailers. That experience led the
retailers to expect, among other things, mass marketing value. In other words, they
expected m-advertising to have the potential to reach thousands of consumers. The
specific benefits of m-advertising such as providing personalized ads to their existing
loyal customers or to a hungry family searching for a restaurant were seldom foreseen.
The following quotation illustrates that even though some retailers noted that m-
advertising is different, they still formed their expectations from experience of mass-
market advertising and acted upon them:
[I was interested in] how many [consumers] it [m-advertising] reaches and what the
reasons are that make people come, if it attracts them to visit us. If we, for example,
place an ad in a local newspaper on specially priced holiday flights to Europe [] does
the mobile advertising have the same effect? Does it attract as many customers?
Travel agency
On the other hand, expected value is directed towards events in the near future
thus illustrating the future orientation of the concept. As already discussed, the future
as it comes to pass is only one alternative of many potential uncertain futures. In the
present case, to the uncertainty that is always present in future time is added the
uncertainty of the novel technological service. Because of the lack of previous
experience of a similar service, the novelty of the service amplifies the uncertainty of
the expected benefits and sacrifices (see Hogan, 2001; Hibbard et al., 2003) as well
as the lack of clear comparison standard (cf. Parasuraman et al., 1985, 1991).
The difficult part was at the beginning, when you did not know where to, sort of
anchor it. Like, what does this [m-advertising] resemble? Like, what is the starting
point for revising or modifying? Advertising agency
Evaluation of the expected value is thus related to both experience and future
events. In perceiving an expected value of the novel m-advertising service both the
lack of experience and uncertainty connected to the usage of the novel service were
evident.
Customer’s Potential Value: The Role of Learning
10
Realized Value Dimension
Realized value refers to a comparison of the expected value and the experiences
gathered during the use of the m-advertising service. The dimension of the realized
value refers to the actual benefits and sacrifices customers perceive when they
evaluate the service experience.
Yes, we got [benefits for the sacrifices]but we were also looking for other things
beside commercial value: I wrote two articles for our national magazine []. I used the
m-ad service both as a consumer and as an advertiser and that way got my own
viewpoint. We got communications and a high-tech image value when we told our
customers that we are using thisand we got first-hand experiencebut the
commercial benefit was not significant. [] But there were other elements. We made
the most of it. Telecommunications shop
The evaluation of the realized value takes place in the present time, although the
target of the evaluation is what happened in the past. However, realized value also
encompasses a future dimension by providing a basis for evaluating a potential value
created in the future.
It was nice to do something new and a bit differentand it was great to learn new
things. Hopefully, we can utilize this experience later in our business. Advertising
agency
I monitored our own sales and what happened during the whole field trial.
However, it was about the same as print media, in other words weak, weak signals.
Nevertheless, I still believe that this particular way to reach consumers, [to offer]
mobile content directly to mobile phones by using m-advertising is the right way.
Mobile applications retailer
Many of the m-advertisers perceived benefits arising from the learning opportunity,
which was reflected in their perceptions of the potential value of the service system in
the near future.
Our objective was maybe more like gaining experiences and testing it [m-
advertising service] [] On the other hand, it is nicely connected to our own products
and we want to be a kind of a forerunner and tester in the field. Telecommunication
devices
Potential Value Dimension
Potential value is the best possible net value that the retailer can imagine will be
realized, not now but at some time in the uncertain future and not even necessarily for
itself. Hibbard et al. (2003) discuss future value as the result of future prices, benefits,
or investments, which is difficult to evaluate because of the inherent uncertainty
involved. This is the case also in the context of a novel technological service.
However, here the concept of potential value extends to whichever uncertain future
Customer’s Potential Value: The Role of Learning
11
can be imagined at the moment, but though it is pictured, it is known that: 1) it has not
existed in the past 2) it does not exist in the present 3) it will not exist in the near future
4) it might never exist 5) but if all goes well, it might exist in the imaginable future.
Therefore, it encompasses, at least implicitly, all the three time concepts past,
present, and future. The excerpt below illustrates the situation:
If it [the m-advertising] someday provides something that the other media do not
better price-quality relations, better targeting [of messages] or something else and it
has proved its effectivenessaccording to market rules anyone would be willing to
pay for a medium that provides benefits that other media do notbut now it is far from
that. Shoe shop
The retailers also pointed out that the potential value of the service is highly
dependent on consumers and other network actors. Consumers need to accept mobile
advertising as an everyday, effective medium for communication with retailers. The
major uncertainties that the retailers associate with future usage are spam/junk
messages and the personalized nature of mobile phones. At the same time, they see
new opportunities to interact with loyal customers, as illustrated in the following:
If we think about the people that have bought our annual pass, belonging in a way
to our club, we could serve them better. In a way it would not just be marketing, but it
could really serve them. In that sense it could be kind of personalized interaction. Art
museum
There are problems with the implementation of the new media, both from the
content provider and consumer perspectives. In the future, it will be very important and
I believe that for us it will be the media [with which] to reach consumers. However, we
still have a lot of learning to do, and the consumers’ habits also have to change and
that is a long-term task. It does not happen overnight, we still have quite a lot [to learn]
in designing the ads and implementing them, as well as targeting and utilizing the
media. Mobile applications retailer
To be realized in the future, potential value requires investments from both the
customer and the other actors in the network who produce the novel technological
business service. The network actors will have to apply their expertise, skills, and
knowledge as well as learn new ones in order to create an optimal service that delivers
its potential value.
The Role of Learning in Customer Perceived Value
The concepts of expected, realized, and potential value are connected to each other
through customer learning. However, the type of learning varies in different time
dimensions. First, unlearning previous experiences that are not relevant is a
prerequisite for the customer to be able to set the expected value to be related to the
novel service (instead of some existing standard). The expected value is related to the
retailers’ previous experiences on one hand, and is also directed towards events in the
near future on the other. In novel technological services, the experiences from
Customer’s Potential Value: The Role of Learning
12
traditional services form the basis for comparison. However, in the case of m-
advertising this comparison with traditional media directs the retailers’ to expect mass
marketing value. This distracts them from seeing and utilizing the advantages of m-
advertising, i.e. the novel service. This view is supported by Folkes (1994) who
suggests that memories of past service experiences can bias expectancy.
Hence, in
the case of expected value, the type of learning is unlearning. The targets of
unlearning are misleading expectations of value. If the expectations are unlearned and
new understanding and ideas about the service are learned they can lead to new
routines needed for their realization (see Bhatt, 2000; Tsang & Zahra, 2008). Thus,
unlearning provides a basis for customers to increase the perceived realized value.
Secondly, perceiving realized value in a novel technological service requires
sacrifices from the retailer in the form of learning. Only by learning to use the technical
features of the service, can the customer fully utilize the special features of the
service, and thus derive value from it. It was noticed from the empirical data, that the
retailers’ motivation to invest in this type of learning varied considerably. When a
retailer did not invest in learning how to use the service, even on a purely technical
level, its value remained low. This was related to the novel and technical nature of the
service as the following interviewee reveals:
The initial uncertainty was a bit irritating, it all was so confusing. We do not have
the time or the interest to examine it in detail and read all the stuff; those technical
things and others. It was such a new thing for us. [] So we put just a few sentences
there [m-ad]. We did not have any pictures or anything. We thought that it would be
more suitable for us if it were simplified. Just a few words and contact information.
Because I do not even know what you could put in [an m-ad]. Furniture shop
When a firm was willing to invest in learning, the value perceived was greater. The
retailer had invested in learning, and learned not only to use the service but also to
utilize its special features, which enhanced the perception of value. Hence, the
perceived realized value varied significantly depending on the firm’s willingness to
invest in learning. The following quotation demonstrates that some retailers also
understood the need to make sacrifices to gain benefits.
I think it was up to us to make time to familiarize ourselves with [the m-advertising
service] and to think how we are going to use itbut I can say that we got multiple
benefits in return for what we invested. In my opinion, it was clear to all the participants
that this is pioneering work, also for the retailers. We must invest and make sacrifices
at this phase so that it will bear fruit in the future. Gifts and interior decoration shop
The type of learning, adaptive or generative (Slater & Narver 1995) seems to have
a bearing on how effectively customers learn to use the service (i.e. the technical
aspects of the service) and whether they learn to utilize the service (here, the special
features of m-advertising). When retailers engaged in generative learning and
consciously searched for new opportunities, the trial seemed to be more successful:
Customer’s Potential Value: The Role of Learning
13
I think everything depends on your willingness and ability to adopt new things. That
is the starting point. We are ready to try new things and not always to choose the well-
known, easy traditional solution. We kind of like to jump from the comfort zone And
we tried to do this better than the ‘average advertiser’ and really think what we do. I
mean, we used animations and these kinds of advertising elements. We did not just
repeat the print media [adverts]. Co-operative
I knew something about this [m-advertising] already before this test. So, I was
aware that it is possible to advertise like thisfor me it was easy to use and it
workedand we got new customers while using it. Health store
We suggest that only when firms can effectively both use and utilize the service will
they be fully capable of visualizing the optimal future version of the service, and then in
turn be able to perceive the greatest possible potential value. Thus, generative
learning in the realized value dimension forms the basis for perceiving the potential
value. However, the unlearning of old expectations and routines is also important, to
keep them from hindering the generative learning.
Finally, the perception of potential value involves learning that must take place
between the present time and an uncertain future time before the potential value can
even be expected, let alone realized. To be able to imagine possible utilization
scenarios for the novel service and to have a vision of its potential value requires the
customer to have learned to use it. Without understanding the essence of the current
service, it is impossible to envision an improved, optimal version of the service.
Potential value entails generative learning targeted towards the future and involves
searching for new opportunities and knowledge. In the case of m-advertising, the
retailers were enthusiastic about finding new ways of advertising, and that led them to
perceive value in being among the first to test the service.
I believe we got a kind of communicational, high-tech value from this as we can tell
our customers that we are using this [m-advertising service] and also have experience
with it. I think it is good for our corporate image that we were involved. Yes, it is a very
positive thing for us. Telecommunication devices
The most important thing was gaining a general awareness of this thing [m-
advertising], to be prepared in advance for the future. This probably will not be our
main business field at any point but it is very likely that in some projects there will be
mobile advertising involved. Advertising agency
In this case, learning is related to the most important actors in the m-advertising
network: the consumers as receivers of m-ads, the m-advertisers themselves, and the
advertising agencies, as well as to the convergence of technology. The actors need to
unlearn old routines and learn how to use the novel service and the technology needs
to advance so as to be available to a wider range of actors and so that different
technologies can work together.
Finally, in the potential value dimension generative learning was again evident.
Similarly, the retailers’ willingness to invest in learning in order to find new ways to
advertise and to develop their businesses was also stressed. Furthermore, learning
not only concerned the individual firm using m-advertising, but was also closely related
Customer’s Potential Value: The Role of Learning
14
to the other important actors in the m-advertising network. Only by making mutual
investments in learning, is it possible to create an optimal service providing potential
value in the future.
To conclude, learning plays a significant role in the CPV of a novel technological
business service. In the short term, learning can be seen as a sacrifice that decreases
the CPV, but in the longer term, its resulting in changed behavior is a benefit that
enhances the CPV. Furthermore, learning connects the different value dimensions to
each other. In the expected value dimension, unlearning forms a basis for customers
to perceive realized and potential value. Then in the realized value dimension,
customer learning may be either adaptive or generative. The type of learning
influences the effectiveness of the learning concerning the use of the novel service
(e.g., its technological features) and utilization of the specific service features. This
kind of learning, in turn, is the basis for how the potential value of the optimal service
in the future is pictured.
Discussion
Theoretical Contribution
This study aimed to explore the role of a business customer’s learning in value
creation and especially in customer perceived potential value. The role of learning is
twofold. Firstly, as a sacrifice, learning facilitates customer value creation and
secondly, it connects expected, realized, and potential value, facilitating the realization
of the highest potential value. To fulfill this role, two aspects of learning are influential:
the type of learning and the learners. Customer’s learning changes from being
unlearning, to the adaptive type, and then to the generative type. The learners change
as well; initially the firms as customers are the learners, and later the group of learners
grows to encompass all the network actors involved in the creation of the potential
value. Figure 1 sums up the results of this study.
Fig. 1: Temporality and learning in CPV
Customer perceived value of
novel technological business service
Expected value
dimension
Potential value
dimension
Realized value
dimension
Type of learning:
Unlearning
Type of learning:
Adaptive/
generative
Type of learning:
Generative
-Firm level
- Network level
Past Present Future
Customer’s Potential Value: The Role of Learning
15
The study makes two exciting theoretical contributions to the customer value
discussion. These theoretical insights are connected to the context of the study: a
novel technological business service. Taken together, the dimensions of expected,
realized, and potential value help us to include the temporally loaded perceptions of
customers assessing value. The concepts are connected to each other through the
learning that varies at different points of time. Understanding the important role of
temporality and learning in CPV enhances theory development and has implications
for the providers of technological business services regarding how to manage the
learning processes of their customers with the aim of improving the perceived value of
a novel technological business service.
As far as the authors are aware, this is the first study to connect learning in its
different forms to a temporal view of CPV. In the area of customer expected value,
customers distinguish certain elements of value that they look for in the service. Then
they compare the new service to prior experiences and base the expectations of the
service on those experiences. A type of learning that has a major role in expected
value is unlearning the old attitudes and expectations. This is an innovative finding that
adds to the value discussion and receives support from studies on learning
organizations (Bhatt 2000, Slater & Narver 1995), which see unlearning as critical to
the learning of any new process. In the case of expected value, the objects of
unlearning are the prior expectations and attitudes based on an understanding of a
different kind of service that is no longer relevant. In this study, m-advertising
represents a novel service that enables more innovative and personal advertising. If
the customer company is able to unlearn the prior experiences formed by using
traditional advertising, it is possible to view a more realistic expected value of the novel
service. If unlearning, however, does not take place it may distort both realized and
potential value.
In terms of the present, the expectations relate to the customer’s perceptions of
realized value. Customers assess the value compared both to their past expectations,
and to their experience of the use of the novel service. Extant studies have generally
taken the view that benefits increase and sacrifices decrease CPV (e.g., Ravald &
Grönroos, 1996), but we suggest that in order to perceive greater realized value, the
customer must make sacrifices in the form of learning. The reason for this is that a
customer who learns to use the service (i.e., the technical features of the service) can
also learn to utilize the service (i.e., the special features of mobile advertising) and
thus perceive the highest possible realized value. It follows that if the customer does
not learn to use and then utilize the novel service, the value perceived is likely to be
diminished. Therefore, we suggest that learning as a key sacrifice, is required from the
customer if they are to perceive realized value. This follows the logic of value creation
in TCA presented by Gosh and John (1999) and adds to Flint et al. (1997) and Ravald
& Grönroos (1996) by raising the variable role of sacrifices; not only decreasing CPV
but through their outcome, also increasing it.
Finally, the potential value concept moves the realized value closer to what could
be realized in the uncertain future but not yet. It is the best possible value the
customer can imagine will be realized in future. The object of learning in the case of
realized value is related, first, to the technological skills needed to use the service and
second, to the specific features of the novel m-advertising service that must be
Customer’s Potential Value: The Role of Learning
16
mastered to utilize the service effectively. The investments made in generative
learning in the present, enable the customer to envisage the optimal service that would
create potential value in the future. Related to potential value, learning is explorative
and targets discovering new knowledge and ensuring future viability. Furthermore, we
agree with Möller’s (2006) emphasizing the importance of learning by the entire
network. For the potential value to become realized value in a novel technological
business service context, it is essential that both customers and service providers are
willing to invest in learning. Customers need to learn a new way of doing things and
service providers need to listen to their customers and improve the service so that
customers’ new ideas are incorporated into the service. Therefore, in a technological
business service, potential value is achieved by mutual learning and adaptations
undertaken by all parties (e.g., customers’ customers, content providers, and
technology providers) in the network related to the service. Furthermore, it is important
for the service provider to understand the expectations their customers hold for the
service in the future. Only with such critical information, will they be able to develop the
service and their customer relationships in a way that will ensure that a technological
business service becomes a profitable business.
Managerial Implications
For managers working in the field of technological business services, the main
implications of the study are as follows. First, it is important for service providers
involved in a novel service development to get across to the first customers that they
will need to make some sacrifices in order to learn to use the service, and in turn to
derive significant value from that service. It is also crucial that the service provider
helps customers to learn use the service. Customers should be encouraged to unlearn
past expectations and assisted in absorbing the technological aspects and special
features of the novel service. This requires that the service provider is aware of the
customers’ absorptive capacity and other characteristics (e.g., technical resources,
knowhow). Such awareness would help them recognize the specific needs of their
customers and to adjust the support offered accordingly. If the service provider can
manage the expectations of the customers, those customers will realize a greater
value from the service and the chances of their continuing to use the service will
improve.
Understanding whether the customer’s learning is adaptive or generative is also
important from the value creation perspective. In the case of adaptive learning,
motivating the customers is more challenging since they will tend to utilize existing
knowledge instead of actively pursuing new opportunities, which often results in a
reduced perceived value. These types of customers also demand more effort of the
service provider. Overall, understanding customers’ learning processes is vital to the
service provider, since that understanding can determine whom its key customers are,
how to serve different types of customers and how to motivate them to invest in their
learning.
Customer’s Potential Value: The Role of Learning
17
Limitations and Suggestions for Future Research
When evaluating any study certain shortcomings can always be found. This paper
draws heavily on interview data that has been acquired from retailers that used a novel
m-advertising service for a relatively short time without making a monetary sacrifice.
However, the aim of the paper was to conceptualize CPV, not to measure it or
determine how valuable the service was for the retailers. Therefore, we feel that the
cost issue and the field trial nature of the service setting do not significantly threaten
the validity of the study. The rather short duration of the service use is an issue that
might prompt calls for more longitudinal studies.
In future, it would be interesting to explore expected, realized and potential value
longitudinally at different stages of novel service development and compare how they
change and relate to each other. This requires longitudinal research strategies, which
of course are time and resource consuming. However, there may be a potential for
such settings within large research projects.
As this study deals with a novel m-advertising service that is was not in commercial
use, it would be important to conduct research on CPV in commercialized
technological services. That would enable a more comprehensive assessment of the
role of sacrifices in the perception of value. It is also important to explore the dynamics
of value in other empirical contexts, such as existing non-technological services.
Moreover, it can be expected that in long-term relationships the temporal
conceptualization of value suggested in this paper, would help us to understand the
dynamics of the relationships as well.
References
Bell, Simon J., Gregory J. Whitwell and Bryan A. Lukas (2002), “Schools of thought in
organizational learning,” Journal of the Academy of Marketing Science, 30 (1), 70-
86.
Bhatt, Ganesh D. (2000), “Information dynamics, learning and knowledge creation in
organizations,” The Learning Organization, 7 (2), 89-99.
Blocker, Chistopher (2011), “Modeling customer value perceptions in cross-cultural
business markets,” Journal of Business Research, 64 (5), 533540.
Choi, Soon-Yong, Dale O. Stahl and Andrew B. Whinston (1997), The Economics of
Electronic Commerce. Indianapolis: Macmillan Technical Publishing.
Cohen, Wesley and Daniel Levinthal (1990), “Absorptive capacity: a new perspective
on learning and innovation,” Administrative Science Quarterly, 35 (1), 128-152.
Curran, James M. and Matthew L. Meuter (2005), “Self-service technology adoption:
comparing three technologies,” Journal of Services Marketing, 19 (2), 103-113.
Dembkowski, Sabine and Stuart Hanmer-Lloyd (1995), “Computer applications A
new road to qualitative data analysis?,” European Journal of Marketing, 29 (11)
5062.
Dubois, Anna and Lars-Erik Gadde (2002), “Systematic combining: An abductive
approach to case research,” Journal of Business Research, 55 (7), 553560.
Customer’s Potential Value: The Role of Learning
18
Easton, Geoffrey (1995), “Methodology in industrial networks,” in Business Marketing:
An Interaction and Network Perspective, Kristian Möller and David Wilson, eds.
Dordrecht: Kluwer Academic Publishers Group, 411-492.
Edvardsson, Bo, Anders Gustafsson and Inger Roos (2005), “Service portraits in
service research: a critical review,” International Journal of Service Industry
Management, 16 (1), 107-121.
Eggert, Anders and Wolfgang Ulaga (2002), “Customer perceived value: a substitute
for satisfaction in business markets?,” Journal of Business and Industrial
Marketing, 17 (2/3), 107-118.
Eisenhardt, Kathleen M. (1989), “Building theories from case study research,”
Academy of Management Review, 14 (4), 532 - 550.
Flint, Daniel J., Robert B. Woodruff and Sarah F Gardial (1997), “Customer value
change in industrial marketing relationships. A call for new strategies and
research,” Industrial Marketing Management, 26 (2), 163175.
---, ---, and --- (2002), “Exploring the phenomenon of customers’ desired value change
in a business-to-business context,” Journal of Marketing, 66 (4), 102-117.
Folkes, Valerie (1994), “How consumers predict service quality,” in Service Quality,
Roland T. Rust and Richard L. Oliver, eds. Thousand Oaks, CA: Sage, 108122.
Gosh, Mrinal and George John (1999), “Governance value analysis and marketing
strategy,” Journal of Marketing, 63 (4), 131-145.
Glaser, Barney G. and Anselm L. Strauss (1967), The Discovery of Grounded Theory.
Chicago: Aldine.
Green, Linda V., Donald R Lehmann and Bernd H. Schmitt (1996), “Time perceptions
in service systems: an overview of the TPM framework,” in Advances in Services
Marketing and Management, Theresa A. Swarzt, David E. Bowen and Stephen W.
Brown, eds. London: JAI Press Inc., 85-107.
Grönroos, Christian (2008), “Service logic revisited: who creates value? And who co-
creates?,” European Business Review, 20 (4), 298-314.
--- (2011), “A service perspective on business relationships: the value creation,
interaction and marketing interface,” Industrial Marketing Management, 40 (2),
240-247.
Heinonen, Kristiina (2004), “Reconceptualizing customer perceived value: the value of
time and place,” Managing Service Quality, 14 (2/3), 205-215.
Hibbard, Jonathan D., John E Hogan and Gerald R. Smith (2003), “Assessing the
strategic value of business relationships: the role of uncertainty and flexibility,”
Journal of Business and Industrial Marketing, 18 (4/5), 376387.
Hogan, John E. (2001), “Expected relationship value. A construct, a methodology for
measurement, and a modelling technique,” Industrial Marketing Management, 30
(4), 339351.
Kodama, Mitsuru (2001), “Customer value creation business through learning
processes with customers: case studies of venture business in Japan,” Managing
Service Quality, 11 (3), 160-174.
Komulainen, Hanna, Tuija Mainela, Jaana Tähtinen and Pauliina Ulkuniemi (2007),
“Retailers’ different value perceptions of mobile advertising service,” International
Journal of Service Industry Management, 18 (4), 368393.
Customer’s Potential Value: The Role of Learning
19
Kowalkowski, Christian (2011), “Dynamics of value propositions: insights from service-
dominant logic,” European Journal of Marketing, 45 (1/2), 277-294.
La, Khanh V. and Jay Kandampully (2004), “Market oriented learning and customer
value enhancement through service recovery management,” Managing Service
Quality, 14 (5), 390-401.
Lane, Peter J. and Michael Lubatking (1998), “Relative absorptive capacity and
interorganizational learning,” Strategic Management Journal, 19 (5), 461-477.
Lapierre, Jozée (1997), “What does value mean in business-to-business professional
services?,” International Journal of Service Industry Management, 8 (5), 377-397.
--- (2000), “Customer perceived value in industrial contexts,” Journal of Business and
Industrial Marketing, 15 (2/3), 122-145.
Lewin, Kurt (1975). Field Theory in Social Science: Selected theoretical papers,
Dorwin Cartwright, eds. Westport: Greenwood.
Liu, Annie H., Mark P. Leach and Kenneth L Bernhardt (2005), “Examining customer
value perceptions of organizational buyers when sourcing from multiple vendors,”
Journal of Business Research, 58 (5), 559568.
Luhmann, Niklas (1979), Trust and Power. New York: Wiley.
Macdonald, Emma K., Hugh Wilson, Veronica Martinez and Amir Toossi (2011),
“Assessing value-in-use: a conceptual framework and exploratory study,” Industrial
Marketing Management, 40 (5), 671-682.
Mead, George H. (1932), The Philosophy of the Present. Chicago: University of
Chicago Press.
Medlin, Christopher J. (2004), “Interaction in business relationships: A time
perspective,” Industrial Marketing Management, 33 (3), 185193.
Menon, Ajay, Christian Homburg and Nikolas Beutin (2005), “Understanding customer
value in business-to-business relationships,” Journal of Business-to-Business
Marketing, 12 (2), 1-35.
Möller, Kristian (2006), “Role of competences in creating customer value: a value-
creation logic approach,” Industrial Marketing Management, 35 (8), 913-924.
--- and Arto Rajala (2007), “Rise of strategic nets New modes of value creation,”
Industrial Marketing Management, 36 (7), 895-908.
Parasuraman, A. (1997), “Reflections on gaining competitive advantage through
customer value,” Journal of the Academy of Marketing Science, 25 (2), 154-61.
Parasuraman, A., Valaria Zeithaml and Leonard L. Berry (1985), “A conceptual model
of service quality and its implications for future research,” Journal of Marketing, 49,
41-50.
Parasuraman, A., Valaria Zeithaml and Leonard L. Berry (1991), “SERVQUAL: a
multiple-item scale for measuring of consumer perceptions of service quality,”
Journal of Retailing, 64 (1), 12-37.
Peirce, Charles S. (1957), Essays in the Philosophy of Science. New York: The Liberal
Arts Press.
Powell, Walter W., Kenneth W. Koput and Laurel Smith-Doerr (1996),
“Interorganizational collaboration and the locus of innovation: networks of learning
in biotechnology,” Administrative Science Quarterly, 41 (1), 116-145.
Pura, Minna (2005), “Linking perceived value and loyalty in location-based mobile
services,” Managing Service Quality, 15 (6), 509-538.
Customer’s Potential Value: The Role of Learning
20
Ravald, Annika and Christian Grönroos (1996), “The value concept and relationship
marketing,European Journal of Marketing, 30 (2), 19-30.
Rokkan, Akseli I., Jan B. Heide and Kenneth H. Wathne (2003), “Specific investments
in marketing relationships: expropriation and bonding effects,” Journal of Marketing
Research, 40 (2), 210-224.
Salo, Jari and Jaana Tähtinen (2005), “Retailer use of permission-based mobile
advertising,” in Advances in Electronic Marketing, Irvine Clarke III and Theresa B.
Flaherty, eds. Hershey: Idea Publishing Group, 139-155.
Sanchez, José, María Vijande and Juan Gutierrez (2010), “Organisational learning and
value creation in business markets,” European Journal of Marketing, 44 (11/12),
1612-1641.
Senge, Peter M. (1990), The Fifth Discipline: The Art and Practice of the Learning
Organization. London: Century.
Sharma, Arun (2002), “Trends in Internet-based business-to-business marketing,
Industrial Marketing Management, 31 (2), 77-84.
Slater, Stanley F. and John C. Narver (1995), “Market orientation and the learning
organization,” Journal of Marketing, 59 (3), 63-74.
Spiggle, Susan (1994), “Analysis and interpretation of qualitative data in consumer
research,” Journal of Consumer Research, 21 (3), 491503.
Stanley, Edmund and Katherine Tyler (2002), “The problem of time in financial
services business markets: a conceptual approach,” The International Journal of
Bank Marketing, 20 (5), 227-241.
Strauss, Anselm L. and Juliet Corbin (1998), Basics of Qualitative Research:
Grounded Theory Procedures and Technique. Newbury Park: Sage Publications.
Styhre, Alexander (2006), “Peer learning in construction work: virtuality and time in
workplace learning,” Journal of Workplace Learning, 18 (2), 93-105.
Tsang, Eric W.K. and Shaker A. Zahra (2008), Organizational unlearning,” Human
Relations, 61 (10), 1435-1462.
Ulaga, Wolfgang (2003), “Capturing value creation in business relationships: a
customer perspective,” Industrial Marketing Management, 32 (8), 677693.
--- and Eggert, Anders (2005), “Relationship value in business markets: The construct
and its dimensions,” Journal of Business-to-Business Marketing, 12 (1), 7399.
--- and --- (2006), “Value-based differentiation in business relationships: gaining and
sustaining key supplier status,” Journal of Marketing, 70 (1), 119-136.
Vargo, Stephen L. and Robert F. Lusch (2004), “The four service marketing myths.
Remnants of a goods-based, manufacturing model,” Journal of Service Research,
6 (4), 324-35.
--- and--- (2008), “Service-dominant logic: continuing the evolution,” Journal of the
Academy of Marketing Science, 36 (1), 1-10.
---., Paul P. Maglio and Melissa A. Akaka (2008), “On value and value co-creation: a
service systems and service logic perspective,” European Management Journal,
26 (3), 145152.
Woodall, Tony (2003), “Conceptualising ‘value for the customer’: An attributional,
structural and dispositional analysis,” Academy of Marketing Science Review, 2003
(1), 142.
Customer’s Potential Value: The Role of Learning
21
Woodruff, Robert B. (1997), “Customer value: the next source of competitive
advantage,” Journal of the Academy of Marketing Science, 25 (2), 139153.
Appendix
Table A1: Interview data
Duration
Interviewee(s) position
45 min
Communications Manager
45 min
Manager
35 min
Press Officer and Assistant
30 min
Assistant
30 min
Shop Manager
15 min
Shop Manager
30 min
Shop Manager
30 min
Shop Manager
25 min
Customer Service Manager
40 min
Shop Manager
30 min
Owner
25 min
IT-support
30 min
Owner
40 min
Office Manager
25 min
Advertising Manager
30 min
Administrative Manager
60 min
Owners (two persons)
8 h 5 min
19 interviewees
... Value has been argued to be multidimensional (Macdonald et al., 2011) and context-specific, and therefore determined by an actor's experience in the social system (Gummerus, 2013). It has different temporal forms ranging from value expectations to value experiences and imagined future value (Komulainen et al., 2013;Möller, 2006). Along these lines, Eggert et al. (2018) present a continuum of value involving the dimensions of valuein-exchange and value-in-use. ...
... It shows how the healthcare sector's notion of collaboration influences the nature of value capture from value creation activities that aim at innovations. The findings corroborate that value is a multivariant concept that requires careful delineation in healthcare context with actors creating value differently (Komulainen et al., 2013;Reypens et al., 2016); value capture also has various timeframes for different parties engaged in innovation collaboration. In particular, the theoretical and empirical findings indicate that value capture practices in healthcare innovation emerge from the situational motivations and goals of the parties, but also from their inherent properties (see Clarke & Crane, 2018). ...
Article
Healthcare is a challenging field for innovation: it is characterised by complex regulation and needs for enhanced collaboration between public and private actors who differ in terms of their motivations, innovation needs, and institutional logics. These complexities relate to multiple ways of approaching value capture in terms of securing financial or non-financial benefits from value creation in innovation collaboration. At the same time, existing scholarly knowledge offers limited help to understand or manage value capture practices in public-private collaborations. Exploring the specific practices of value capture is needed not only to understand how the returns from shared value creation activities are secured but also to understand why public and private organisations should invest their limited resources in collaboration in the first place. Applying insights from the innovation management and industrial marketing literatures, the present case study explores value capture practices in public-private collaborations for healthcare technological innovation. Empirically, it draws from twelve collaborations between a public hospital and private firms providing insight into both private firms and a public hospital organization. As a result, the study suggests a categorisation of value capture practices emerging in innovation collaboration in healthcare, thereby explicating how such practices incorporate approaches of both public and private sector participants.
... An actor's personal history and past experiences are an essential part of value perception (Heinonen et al., 2010). They shape the actor's expectations of future value, and therefore temporality is seen to be an important aspect of value, which is discussed here as a time-sensitive concept with past, present, and future dimensions (see Flint et al., 1997;Komulainen et al., 2013;Woodall, 2003). Actors' value perceptions change over the course of a relationship (e.g., Beverland and Lockshin, 2003;Flint et al., 2002). ...
... As suggested by a phenomenological view on value, individuals' iterative sense-making is not a linear process as current value in the experience is constructed based on previous and imaginary future experiences (Helkkula et al., 2012). Individual actors' current interpretations of value are shaped by their intentions (Corsaro and Snehota, 2012), and currently perceived value is dependent on past experiences (see also Komulainen et al., 2013). Therefore, value perceptions take place in the present time, even though the past and future value influence perceived value at each moment. ...
Article
Co-innovation often occurs in trustful long-term relationships when a fruitful match is found. Evaluating the value of those relationships is difficult but necessary for their management. Discussions of business-to-business relationship value have been revolving more around utilitarian elements even though experiential value aspects have gained increasing research interest. Here, the concept of experiential value is applied to understand the value of long-term co-innovation relationships. An exploratory case study of such a relationship between a supplier, its customer, and a university was built on in-depth interviews with key informants from each party. The study provides a multi-level framework of experiential value in the context of co-innovation relationships that encompasses the subjective, temporal, and contextual aspects of value as well as personal relationships and projects as devices that transfer individuals' value experiences between individuals and organisations, and through time. This study contributes to relationship value and co-innovation research by elaborating on the experiential aspects of relationship value.
... An actor's personal history and past experiences are an essential part of value perception (Heinonen et al., 2010). They shape the actor's expectations of future value, and therefore temporality is seen to be an important aspect of value, which is discussed here as a time-sensitive concept with past, present, and future dimensions (see Flint et al., 1997;Komulainen et al., 2013;Woodall, 2003). Actors' value perceptions change over the course of a relationship (e.g., Beverland and Lockshin, 2003;Flint et al., 2002). ...
... As suggested by a phenomenological view on value, individuals' iterative sense-making is not a linear process as current value in the experience is constructed based on previous and imaginary future experiences (Helkkula et al., 2012). Individual actors' current interpretations of value are shaped by their intentions (Corsaro and Snehota, 2012), and currently perceived value is dependent on past experiences (see also Komulainen et al., 2013). Therefore, value perceptions take place in the present time, even though the past and future value influence perceived value at each moment. ...
Article
Co-innovation often occurs in trustful long-term relationships when a fruitful match is found. Evaluating the value of those relationships is difficult but necessary for their management. Discussions of business-to-business relationship value have been revolving more around utilitarian elements even though experiential value aspects have gained increasing research interest. Here, the concept of experiential value is applied to understand the value of long-term co-innovation relationships. An exploratory case study of such a relationship between a supplier, its customer, and a university was built on in-depth interviews with key informants from each party. The study provides a multi-level framework of experiential value in the context of co-innovation relationships that encompasses the subjective, temporal, and contextual aspects of value as well as personal relationships and projects as devices that transfer individuals’ value experiences between individuals and organisations, and through time. This study contributes to relationship value and co-innovation research by elaborating on the experiential aspects of relationship value.
... In order to provide new or improved digital services to customers, it is crucial to understand their total value experience. Value experience is not usually rational or objective but rather very personal and bounded in time and context (Corsaro and Snehota, 2010;Helkkula et al., 2012), yet customers' past experiences and future expectations also have a significant impact (Komulainen et al., 2013). Taking the customer-oriented perspective on value experience suggests that value is created by either the company, by the customer and company together, or by the customer alone (Heinonen et al., 2013). ...
Article
Purpose The purpose of this paper is to examine how the customer value experience conveys the restructuring of the service network in the banking industry. The banking sector has often been one of the early adopters of IT in terms of connecting their services and customers. While developing digital services, however, banks are also concerned that they are losing contact with their customers. At the same time, fast developing technologies enable new companies to enter the industry to offer their services. As a result, the service supply chains in the banking industry appear to be restructured. Design/methodology/approach The empirical data were collected by using a qualitative method of focus groups and interviews with end-users of banking services. Findings According to findings, customers value a holistic approach to the services, and such a holistic value cannot necessarily be provided by a single banking service provider because the ecosystem around such services is becoming more complex. Practical implications Service supply chains need to be restructured based on the end-customer value experience. Originality/value This study contributes to value research and especially to the discussion in service experiences by addressing some of the disruptions happening at the industry level. The paper shows that the focus should be on customer value because banks should understand that their services are not enough for the customers—they are only seen as banks, not as providers of the holistic value that is required from the customer’s point of view.
Article
Purpose - Since agencies play a pivotal role in operationalising marketing strategy, this relationship is central to marketing theory, management and practice. This article presents the first systematic review of the literature relating to the relationships between organisations and their marketing agencies, the agency-client relationship, and presents a concept matrix that identifies the key areas of investigation, and topics where further research would be beneficial. Design/methodology/approach - A systematic review of the literature was performed using key databases and search terms, and filtering on the basis of criteria relating, for example, to relevance and format, to create a core set of refereed articles on the agency-client relationship in the marketing and advertising domains. Bibliographic and thematic analysis was used to profile the literature in the dataset, and to draw out key themes. Findings: The article provides an analysis of the extant knowledge base, including key themes, journals, and research methods. The following themes emerged from the literature, and are used to elaborate further on the existing body of knowledge: conflict, client account management, contracts and agency theory, cultural and international perspectives and co-creation. An agenda for future research is proposed that advocates a focus on theoretical foundations, research strategies, and research topics and themes. Originality/value: This is the first systematic review of the literature on agency- client relationships, which is scattered across disciplines and informed by several theoretical perspectives. Given the increasing complexity of agency-client relationships in the digital age, and increasing need to understand ‘marketing-as- practice’, the coherent overview offered by this article is of particular value for guiding future research. Keywords Agency-client relationship, Agency Theory, Relationship management, Marketing management, Co-creation, Marketing-as-practice.
Article
Full-text available
Much of the prior research on interorganizational learning has focused on the role of absorptive capacity, a firm's ability to value, assimilate, and utilize new external knowledge. However, this definition of the construct suggests that a firm has an equal capacity to learn from all other organizations. We reconceptualize the Jinn-level construct absorptive capacity as a learning dyad-level construct, relative absorptive capacity. One firm's ability to learn from another firm is argued to depend on the similarity of both firms' (1) knowledge bases, (2) organizational structures and compensation policies, and (3) dominant logics. We then test the model using a sample of pharmaceutical-biotechnology RED alliances. As predicted, the similarity of the partners' basic knowledge, lower management formalization, research centralization, compensation practices, and research communities were positively related to interorganizational learning. The relative absorptive capacity measures are also shown to have greater explanatory power than the established measure of absorptive capacity, R&D spending. (C) 1998 John Wiley & Sons, Ltd.
Article
Full-text available
Since the introductory article for what has become known as the “service-dominant (S-D) logic of marketing,” “Evolving to a New Dominant Logic for Marketing,” was published in the Journal of Marketing (Vargo, S. L., & Lusch, R. F. (2004a)), there has been considerable discussion and elaboration of its specifics. This article highlights and clarifies the salient issues associated with S-D logic and updates the original foundational premises (FPs) and adds an FP. Directions for future work are also discussed. KeywordsService-dominant logic-New-dominant logic-Service
Article
This chapter shows how retailers - without any previous experience or education - utilize a new mobile advertising channel. The chapter focuses on permission-based mobile advertising and the specific features that should be considered when designing and targeting mobile advertising. The empirical part of the chapter analyzes data from a field trial where Finnish retailers were able to use mobile advertising. The empirical data is obtained through the use of content analysis. Data analysis explores whether the retailers positioned the m-adverts to target either individuals or groups and whether the content of the m-adverts reflected and utilized the medium's specific features. The results of this analysis suggest that both retailers and advertising agencies have to learn how to use m-advertising as a new media. Conclusions of the chapter suggest ways to fully utilize the potential of mobile advertising.
Article
Managing collaborative business-to-business relationships demands an understanding of how relationships create value for the firm and a method to accurately assess that value. The purpose of this research is to propose a new construct, expected relationship value, and an innovative method for its measurement. The proposed methodology relies on qualitative research techniques to gather dispersed organizational knowledge about the relationship. The results of the interviews then serve as input to a quantitative model using a Monte-Carlo simulation to operationalize expected relationship value as a probability distribution of the net present value of current and future relationship outcomes.