=Paper=
{{Paper
|id=Vol-2518/paper-SOLEE4
|storemode=property
|title=Prototyping a Taxonomy of Value Types
|pdfUrl=https://ceur-ws.org/Vol-2518/paper-SOLEE4.pdf
|volume=Vol-2518
|authors=Satoshi Nishimura,Ken Fukuda
|dblpUrl=https://dblp.org/rec/conf/jowo/NishimuraF19
}}
==Prototyping a Taxonomy of Value Types==
https://ceur-ws.org/Vol-2518/paper-SOLEE4.pdf
Prototyping a Taxonomy of Value Types
Satoshi NISHIMURAa,1 and Ken FUKUDA a
a
National Institute of Advanced Industrial Science and Technology (AIST), Tokyo,
Japan
Abstract. Service industry is a dominant industrial discipline among developed
countries. The structure of service activities is recognized to be complex because
interactions among a producer, a customer and an environment are intrinsically
occurred in the service system. Value is an important concept for understanding of
services itself, decision making for business strategy etc. However, the concept
tends to be used as economic value even though there are many types of value. This
paper provides prototype taxonomy of value types to describe what kinds of value
types exist. We extract value concepts from a literature and then organize the
concepts into a prototype taxonomy.
Keywords. Value, Service, Taxonomy of value types
1. Introduction
1.1. Background
Service industry is a dominant industrial discipline among developed countries including
Japan. The structure of service activities is recognized to be complex because co-creation
is intrinsic part of the service system. There are some research efforts to describe it clear.
Vargo and Lusch proposed "value co-creation" to clarify the importance of the
interaction among customers and employees for value creation [21]. Ueda et al, provided
three value creation model from a production engineering viewpoint [19, 20].
Those two research efforts tackled to make the concept “value co-creation” clear,
however the notion of “value”, which is an important component of value co-creation, is
still used as various meanings [1, 2, 15]. The notion of XaaS (X as a service such as
Mobility as a Service) and sharing economy are broadening the boundary between value
creator and value receiver even further. It causes difficult to clarify value further.
From a practical viewpoint, quality of service activities should be measured to
improve quality of service effects. The clarification of “value” is important in this context
because the value can be interpreted from various viewpoints. Nishimura and Fukuda
provided a prospect to make the indicator of value by clarifying value types [13]. We
focus on clarifying value types from an engineering viewpoint and our goal is not
clarifying detailed value types in any domain, such as religious value, ethical value, etc.
but clarifying value types which related to economic activities. The detailed motivation
is described in section 1.2.
1
Corresponding Author: Satoshi Nishimura, National Institute of Advanced Industrial Science and
Technology (AIST), Tokyo, Japan; E-mail: satoshi.nishimura@aist.go.jp. Copyright © 2019 for this paper by
its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
1.2. Motivation
Companies tend to evaluate the prospect of new business from economical viewpoints.
This strategy is simple and good to choose beneficial business activities for the company.
However, the strategy might be harmful from a sustainability viewpoint. For instance,
some jobs may help the company to increase employees’ satisfaction, some jobs may
help their customers to gain understanding and loyalty toward the company, some jobs
may help the company to get customers information. And it can happen that all these
jobs do not contribute to make money directly. An example is servitization of
manufacturing, which tends to fail without proper non-economical KPIs (Key
Performance Indicators) during the investment phase when profit is very low.
We provide a case scenario as follows. Company A decides to provide more
hospitable maintenance service. The company should collect customer data for efficient
after-support services to the customer. The data collection may be operated by
salespeople who usually promote to sell products of the company A. Therefore, the data
collection job does not contribute to increase profit of the company A. In this case, a
business manager should be aware of not only profit (as economical value) but also
customers’ data (as non-economical value). The former one become beneficent soon and
the latter one contributes to the company in the future. It is difficult decision-making for
the manager without the indicator of value.
There is no standard notion of value yet [1]. This should prevent the managers of the
company decide what value they should increase. Therefore, we will classify types of
value in appropriate manner based on ontological engineering method. Then, we will
investigate what measurement indicator is measurable and suitable for each type of value.
For the first step, we prototype a taxonomy of value types.
1.3. Structure of paper
In this paper, we provide data collection about concepts related to value from literature
and prototyped taxonomy of value types. In section 2, we show how we collect concepts
related to value. In section 3, we describe the prototype of taxonomy of value types and
some definitions of value. In section 4, we describe related work about the notion of
value. In section 5, we summarize our paper.
2. Collection of concepts related to value
Ueda et al. [20] surveyed papers in axiology from a viewpoint of production engineering.
Their focal point is value creation and decision-making in sustainable society, and they
proposed models to describe value creation in a complex service system as the
consequence of the survey. We collected concepts related to value from the paper.
Hereafter, we write names of value types in Italics.
First, we extracted the terms including a word “value” by using a text mining tool,
which is called as KH Coder [6]. 87 terms were collected by the automatic extraction
step and we selected 26 terms which represent specific values, such as Sustainable value
and Economic value. Second, we also extracted concepts related to value not containing
a word “value” by manual surveying. Some value types, which do not have their names
explicitly, were conceptualized in this step and 12 concepts were extracted, such as Value
of human knowledge and Value as intersubjective phenomena.
After the extraction steps, we selected meaningful concepts from the extracted terms.
The definitions of 15 terms are lack in the literature therefore we decide to exclude these
terms in this research. According to the previous works [15, 18] and reviewers’
comments to the first version of this paper, we made distinction of these concepts into
value, value object which the value inheres in, and amount of value. For example, Value
as the volume of net products and Surplus value are interpreted as the amount of value.
These values can be described as the summation of value and additive value respectively.
However, if the value is regarded as quality, such calculation is difficult. Therefore, we
interpreted these values as not value type but the amount of value. Sustainability and
Fundamental value (nature) are interpreted as value object on the other hand. For
example, Ueda et al. explained the latter value as “nature is regarded as the object of
study and investigation by science and not as the field of manifestation of divine forces.”
The sentence denotes that nature has utility for the scientists to investigate, therefore it
can be interpreted as not value type but value object.
The results of the selection show on table 1 and 2. We got 8 meaningful concepts at
the result. Table 1 shows the concepts which we included in a taxonomy and table 2
shows the concepts which we excluded in this paper.
Table 1. Considered concepts including in a prototype taxonomy
Use value Value of human knowledge
Exchange value Economic value
Surplus value Marginal utility
Ordinal utility Cardinal utility
Table 2. Excluded concepts in a prototype taxonomy
Knowledge value Pragmatic value
Cognitive value Psychological value
Subjective notion of good Meta-knowledge value
Human natural value Sustainable value
Value from cognitive development Bland value
Behavioural Value Synthetic value
Functional value Utility value
Ecological value Non-objective value
Provided value Adaptive value
Co-creative value Value in value engineering
Value as the volume of net products Value as intersubjective phenomena
Maximization of pleasure Minimization of pain
Protection, safety and peace Objective Value
Subjective value Absolute value
Natural value Sustainability
Fundamental value (nature)
Class restriction
represents a class of its Is-a link represents an Red-colored role
player is-a relation concept represents
(=rdfs:subClassOf) an inherited slot This part
Orange node (=owl:allValuesFrom) represents from
represents a what the slot is
Concept inherited.
(=rdfs:Class)
Cardinality
(=owl:cardinality)
Role concept
p/o slot represents a (? property name)
part-of relation
(=rdf:Property)
Link between slots
represents a relation between
a/o slot represents an parts/attributes
attribute-of relation Role holder (=some axiom)
(=rdf:Property) (= Class restriction
which is playing a
Role concept)
Figure 1. Overview of ontology representation in Hozo [9]
3. Prototyping a taxonomy of value types
3.1. Hozo ontology editor
We use Hozo [9] to prototype the taxonomy of value types. Hozo is an ontology editor
which is widely used in various domains, such as clinical domain [12], sustainability
domain [10], education domain [5] and manufacturing domain [8]. Figure 1 shows an
overview of representation of class definition in Hozo. Orange nodes represent concepts
which can be interpreted as whole thing, such as Bike. Each concept has properties and
they are represented as slots in Hozo. There are two types of slots (p/o and a/o). A p/o
slot represents a part-of relation and an a/o slot represents an attribute-of relation. The
property is represented as Role concept which has Class restriction as its player. The
Role concept with its player is interpreted as Role holder. In this example, Wheel is a
concept and it is called as Front wheel when it plays Front wheel role, on the other hand,
it is called as Rear wheel when it plays Rear wheel role. The properties are inherited to
the specified concepts which is linked by is-a link as same as other ontology
representation tools.
3.2. Overview of a taxonomy of value types
Figure 2 shows a prototype taxonomy of value types. We added some concepts to clarify
classification criteria in the taxonomy. First, Value of knowledge is added as an abstract
concept of Value of human knowledge. Value of explicit knowledge is added for opposite
concept of Value of human knowledge. The detail description of these concepts is shown
in section 3.3 with their classification criteria.
Figure 2. Prototype taxonomy of value types
3.3. Classification of intrinsic value types
3.3.1. Economic value, Emotion value, and Value of knowledge
According to Toya’s notion of value [18], we classified values into three types. The first
one is Economic value. We defined that Economic value is measurable by using money.
If the value object to which Economic value is inhered is able to exchange with money,
then the value is defined as Exchange value. Use value is defined as usefulness of a
product/service or its utility. It is also able to be exchanged so that we classified Use
value as a subclass of Exchange value. The second branch of value is Emotion value.
Emotion value is defined that a value is related to emotion. The third branch of value is
Value of knowledge. Value of knowledge is defined that a value inheres in knowledge.
The details of subclasses of the Value of knowledge is described in section 3.3.2.
3.3.2. Value of knowledge
There is Value of human knowledge which is defined as “(Omitted) the word
"Embodiment" represents a similar aspect of values of human knowledge.” In this
context, the term Value of human knowledge means only knowledge which is inherent to
human body, such as skill. However, there is other type of knowledge, i.e. explicit
knowledge which is written in a concrete media and interpretable by other people.
Therefore, we added Value of explicit knowledge as an opposite concept of Value of
human knowledge and Value of knowledge as an abstract concept of them. As shown in
figure 2 a), Value of human knowledge depends on human and the human has some
proposition as knowledge and the knowledge is indescribable. On the other hand,
knowledge which Value of explicit knowledge refers is describable. That is a
classification criterion among them.
4. Related work
4.1. Service management viewpoint
Toya provides three types of value from a service management viewpoint [18].
Economical value is chosen as a measurement indicator to decide business plan in many
cases as we mentioned in section 1. She also consists that there are considerable other
types of value when the management sector develops long-term business plan, such as
expertise knowledge of employees and customers’ loyalty and emotion toward products,
employees or brands, etc. Toya defines Knowledge Value (KV) as the accumulated
knowledge held by co-creators and Emotion Value (EV) as the affective value associated
with customer and employee moods and perceptions in [18]. However, there are not
enough discussion what is the differences among the value types and the other value
types which are discussed in literatures.
4.2. Value modeling viewpoint
There are also research efforts from value modeling viewpoint. Hruby [7] and da Silva
Reis [3] discuss components related to value. Proper et al. try to construct a modeling
framework focusing on value co-creation [14]. Andersson et al. propose a model of value
ascription [2].
Hruby provided a model focusing on coalition [7]. Coalitions can be dealt as a kind
of context in which people who want to exchange something valuable in the value
exchange processes. Such a model helps us clarify the notion of value exchange and it
can be a component of describing value types.
da Silva Reis et al. proposes a notion to configure value networks based on
subjective business value [3]. The interest is also realizing sustainable economy as same
as Ueda et al. [20]. They also put subjectivity as key concept to configure a value network.
However, the scope of the subjectivity is only assurance, privacy and trust and it is not
comprehensive.
Proper et al. are constructing a modeling framework about value co-creation [14].
The framework is based on a notion of [4]: potential value in production context and real
value in the context of interactive value creation and independent value creation. The
distinction of value in this context seems to be based on phases of value creation not
characters of the value types.
Andersson et al. focuses on value ascription [2]. They also mentioned subjectivity
of value as same as other research [3, 7, 14]. Additionally, in the paper, the context is
key notion. Ascribed value to different value objects can be comparable in the same
context. For the comparison, they introduce “value structure.” However, the component
of value structure is not discussed well, and they do not clarify whether the value includes
only fundamental value or other types of value.
5. Summary
As the first step to understand value, we prototype a taxonomy of value types. We
extracted terms related to value from a literature [20] and got 87 terms. Then, we selected
8 meaningful concepts from the extracted terms. After that, we clarify the classification
criteria among the concepts and prototype the taxonomy of value types.
As a future work, we will integrate other contribution provided in related work. We
will also try to make other scenarios rather than we mentioned in the section 1 according
to the proposed taxonomy because the scenarios we mentioned in the section 1 refer to
limited types of value. Such concretization of the scenarios can contribute to improve
decision making for services industry.
Acknowledgement
The part of this paper is based on results obtained from a project supported by Council
for Science, Technology and Innovation, “Cross-ministerial Strategic Innovation
Promotion Program, Big-data and AI-enabled Cyberspace Technologies”. (funding
agency: NEDO) We are also grateful for many valuable comments to the reviewers.
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