DISCUSSION PAPER SERIES
February 2014

No.2014-03

The Growth of End User Innovators and Changing
Precedent Factors: A Case Study of the Comics Industry
Sotaro Katsumata
Takeyasu Ichikohji

The Growth of End User Innovators and Changing
Precedent Factors: A Case Study of the Comics Industry

Sotaro Katsumata
Faculty of Economics, Nagasaki University
Takeyasu Ichikohji
Faculty of Business Administration, Toyo University

Abstract
In this study, we examine the motivation structure for individuals’ consumption, purchase, andinnovation behaviors. In particular, we divide innovation into three stages: privatized, publicized,
and profitable innovation. These three stages are determined by whether individuals share theirworks with others and whether they obtain monetary rewards for selling their works. To examine this
topic, we carry out an empirical survey focusing on the Japanese comics industry. We find that there
are substantial differences in the motivation involved in the three stages. In privatized innovation,
users are motivated by intrinsic pleasure. On the other hand, in publicized and profitable stages, theeffect of pleasure becomes negative, while userness becomes a main precedent factor for creators.
Our results suggest that firms and industry groups need to better understand users’ internal changes
in motivation, so that they can address related issues.

Keywords: user innovation, consumer behavior, content industry, information goods

11. Introduction
In the modern market, firms are often interested in the innovations of end users and consumers.
Since many users become connected to interactive media on the Internet, they can easily transmit,
receive, and share any content that they create. The transmission of content is no longer exclusively
controlled by large organizations such as firms, industry groups, and governments, and much content
is created and transmitted by consumers in a manner that is not connected to large organizations in
any way, creating a large market.
In economic models, consumers, as end users, are seen as economic entities that exclusively
consume products and services, while producers are economic entities that produce them. However,even long before the advent of the Internet, some users have been both producers and consumers.
Toffler (1980) refers to these individuals as “prosumers,” who innovate for themselves. These
prosumers are characterized by a DIY (“do it yourself”) approach, which is most evident in the home.
Current prosumers can use the Internet to interact, thus acquiring easy access to the knowledge andinnovations of others. Von Hippel (1996) and Chesbrough (2003) have reported the adoption of
external innovations in a business-to-business market. In the recent years, end users have exchanged
innovations through the Internet, and firms have utilized these innovations. Information goods are
particularly easy to copy and transmit through the Internet, and users can share their content withothers worldwide (Shapiro and Varian, 2000). In recent years, the objectives of innovation haveshifted away from simply developing innovations and toward developing innovations that are
adoptable by others.
As more innovative users appear, so do new businesses in the ICT (information communication
technology) industry, such as YouTube and Twitter. For these businesses, user participation andcontent submission are vital to success. These firms provide only “empty boxes” for users, which
they have to encourage users to fill. Some of these innovative users create particularly valuable
content, while others are less valuable in this regard. Firms thus have to identify users’ values anddetermine their motivations in order to encourage their creation.
However, many studies have focused only on the creation or innovation activities of users,
without examining the value of created content. Furthermore, few studies have revealed thedifferences in motivations between users who create valuable content and those who do not. With
this in mind, our research aims to classify three stages of innovation and examine the relationships
between creative activity and motivations in the information goods industry.

2. User Innovations and Consumer Motivations
Research on innovative users has been carried out in a number of fields. In this section, we
present an overview of relevant studies and propose research objectives based on a synthesis ofprevious findings.
2

2.1.

User Innovation Studies
The concept of the lead user was originally proposed by von Hippel (1986), in a study based on

von Hippel’s (1976, 1977) earlier observations of innovative users who have more ideas for products
than developers in the B-to-B (business-to-business) industry. Von Hippel (1986) defines lead users
as having the following two properties:(1) Lead users face needs that will be general in a marketplace——but face them months or years
before the bulk of that marketplace encounters them.
(2) Lead users are positioned to benefit significantly by obtaining a solution to those needs.

Urban and von Hippel (1988) then empirically demonstrated the existence of lead users throughcluster analysis. In the early years of research on lead users, they were mainly the subject of efficient
market research, but user innovation studies also discussed how to adapt user innovations to firms’
product development (e.g., von Hippel, 2001a; Ogawa, 1998; von Hippel, 2005). User innovation
studies mainly focused on B-to-B industries, although some later studies addressed B-to-C(business-to-customer) industries (e.g., Franke and von Hippel, 2003; Franke and Shar, 2003;
Jeppesen and Frederiksen, 2006). Von Hippel, Ogawa, and de Jong (2011) conducted a survey of end
user innovation in the USA, the UK, and Japan, and their results suggested that millions ofconsumers acted as sources of innovation. Within the field of user innovation studies, many papers
have demonstrated consumers’ innovation activities.
To measure the “lead userness” of individuals, Morrison (1995) and Morrison, Roberts, and vonHippel (2000) have proposed a measurement scale that uses the LES (leading edge status),
consisting of 7 measurement items, to measure lead userness. Morrison et al. (2000) havedemonstrated that the reliability of the construct is good. Morrison, Roberts, and Midgley (2004)
have also presented a distribution of LES scores. Morrison et al. (2000) focus on a library
information system and the innovation behaviors of librarians; their findings suggest that librarians
who have high LES scores tend to use the system proactively. In particular, they tend tocommunicate with vendors to express their needs or develop and configure the system. Jeppesen andFrederiksen (2006) have focused on a digital synthesizer product to show that high LES users tend to
modify software.
2.2.

Attitude of Users for a Certain Product Category
As mentioned above, many studies examine the behavioral aspects of innovative users in thefield of innovation management. In contrast, in the field of consumer behavior, many studies focus
on intrinsic motivation structures or processes. In this paper, we focus on involvement as a construct3

that controls behaviors concerning or attitudes toward specific product or service categories.
The concept of involvement was first addressed in terms of “ego-involvement” by Sherif and
Cantril (1947) and Sherif and Hovland (1961) within the field of social psychology. In these earlyyears, the concept of involvement was typically applied to examine responses to advertisements(Krugman, 1965). Since there are many types of involvement, Mitchell (1981), Park and Mittal(1985), and Laaksonen (1994) have tried to classify them. According to Peter and Olson (2010),
involvement can be classified into two groups: situational and enduring involvement. Enduring
involvement is deeply related to the attitudes of consumers toward a certain product category orindustry. Higie and Feick (1989) argue that enduring involvement is a factor that affects individual
attitudes to and behaviors concerning a product. In addition, they explain that enduring involvement
is intrinsically motivated by consumers’ experiences of self-image and the delight given by anobjective product.
Many studies indicate that involvement, and especially enduring involvement, affects
consumption behavior with regard to objective product categories such as the size of consideration
or reject sets of consumers (Divine and Page, 1994; Brisoux and Cheron, 1990), routes of
information processing (Petty and Caciopoo, 1986), and entire information processing behaviors(Peter and Olson, 2010). In this study, we find that consumers with high involvement actively search
for information on products and, as a result, tend to have higher levels of consumption.
Involvement affects more than consumption; some empirical studies indicate that a relationshipexists between involvement and other behaviors. For example, Ichikohji and Katsumata (2013) showthat content generators tend to have high levels of involvement, while Chang and Chung (2011)indicate that involvement affects information sharing on the Internet. These studies imply thatinvolvement affects consumers’ entire behaviors related to an objective product.
Higie and Feick (1989) also show that that enduring involvement, which affects the motivation
to relate to certain products, contains two sub-constructs, the “hedonic” factor and the“self-expression” factor. Some previous studies, such as those of Zaichkowsky (1985) andMcQuarrie and Munson (1987, 1991) also imply that there are two different sub-constructs ofenduring involvement. Higie and Feick (1989) examine the relationship between these two
sub-constructs and particular items. They argue that the hedonic factor measures the degree to whicha product is related to one’s pleasure, while the self-expression factor measures a product’s
relationship to one’s identity. These two factors may affect users’ behaviors and attitudes in different
ways. Therefore, in this study, we divide enduring involvement into these two sub-constructs to
examine the structure of motivation.
2.3.

Research Objectives
We define the objectives of this paper based on the previous studies of user innovation behavior
4and consumer motivation that are described above. The purpose of this study is to examine therelationships between generation/consumption behavior and the intrinsic motivations of users. In it,
we focus on the motivation structure of users who generate content. We aim to reveal the precedentfactors for generating valuable content that can be exchanged for money in the market. Using asimilar approach, Ghose and Han (2011) have empirically analyzed the information transmission andreception of users. In contrast, we focus on the quality or market value of generated information.
In addition, we examine the effects of users’ individual characteristics, such as lead userness
and involvement level, on their generation and consumption behaviors. In generation behavior, themotivation structure for generating valuable content may be different from that for generating
non-valuable content. As Deci (1975) indicates, monetary rewards may alter the motivation structure
involved in content generation.
In the next section, we define the objective variables of generation and consumption andpropose our hypotheses.

3. Research Design and Hypotheses
3.1.

Definition of Objective Variables
In this study, we focus on users’ behavioral aspects in both consumption and innovation(content generation). We divide consumption and innovation behaviors into two and three aspects(respectively) and examine the relationships between them.
First, we divide consumption into frequency of use and purchase amount. In the content market,
many users do not pay for their content. Although they are still consumers, they do not contribute to
the profits of firms. With this in mind, we examine the structural differences between thesenon-valuable consumers and valuable consumers. Table 1 provides a more detailed description ofuser aspects.

Table 1: The two aspects of users
Classification

Profitability

Frequency of Use

Non-profitable

Purchase Amount

Profitable

Degree of activeness in using content,
which includes free content use.
Degree of activeness in purchasing
content.

We divide innovation behavior into three stages, based on a study by Katsumata and Ichikohji(2011) that defines the stages of creation of innovative consumers. The first stage is that of“privatized innovators,” who develop innovations to solve their individual problems that are
exclusively used by them. This is also one of the characteristics of the “prosumers” proposed by5

Toffler and Toffler (2007). The second stage is that of “publicized innovators,” who develop
innovations and share their outcomes with other users, as has been reported by von Hippel (2005)
and other user innovation studies. The third stage is that of “profitable innovators,” who obtainmonetary rewards from other users by selling their outcomes. In terms of use and purchase behaviors,
we also assume that profitable innovators develop privatized and publicized innovations. In otherwords, the three stages of innovation are not exclusive. Table 2 presents a summary of the threestages of innovation.

Table 2: The 3 classifications of end user innovation
Classification

Profitability

Privatized innovation

Socialization
Non-socialized

Non-profitablepurposes and use them by themselves.
Share innovations that they develop

Publicized innovation

with other users but do not receive any
Socialized

Profitable innovation

Develop innovation for their own

Profitablemonetary rewards.
Developinnovations

andreceivemonetary rewards for sharing themwith other users.

3.2.

Hypotheses
In this section, we present our hypotheses on the relationship between intrinsic constructs andbehavioral aspects. First, as many studies indicate (e.g., Peter and Olson, 2010), we hypothesize theeffect of enduring involvement on consumption behavior as follows:

H1: There is a positive relationship between enduring involvement and consumption behavior.

Second, we formulate the relationship between enduring involvement and lead userness. Users
who are characterized by high involvement actively search for information, and so may recognize
new problems and needs earlier than low-involvement users. According to Higie and Feick (1989),
users who have high enduring involvement want to relate to objective products. Therefore, we can
expect that they also have high lead userness, as shown in Katsumata and Ichikohji (2011), and thus
hypothesize the following:

H2: There is a positive relationship between enduring involvement and lead userness.

Next, we formulate the relationship between consumption behavior and lead userness. In
6general, lead users are also frequent users (Morrison et al., 2000; Jeppesen and Frederiksen, 2006).
We can expect that these users have greater knowledge of objective products and therefore
hypothesize the following:

H3: There is a positive relationship between consumption behavior and lead userness.

The enduring involvement construct has already been applied to consumption behavior issues,
but as Katsumata and Ichikohji (2011) indicate, this construct also affects innovation behavior.
Therefore, we hypothesize the following:

H4: There is a positive relationship between enduring involvement and innovative behavior.

As user innovation studies show (Morrison et al., 2000a; Jeppesen and Frederiksen, 2006), leaduserness plays a vital role in innovation behavior. The construct of lead userness includes both
motivation and capability to innovate. As such, we propose the following hypothesis:

H5: There is a positive relationship between lead userness and innovation behavior.

In addition, we expect that users gradually step up their innovation. Thus, we offer thefollowing hypothesis:

H6: Innovation behavior gradually moves from the privatized to the publicized and then to the
profitable stage.

We also expect that the direct effect of moving from privatized to profitable innovation is not
significant or is smaller than the effect of moving from publicized to profitable innovation.

This paper examines the above six hypotheses. However, we have defined consumption
behavior as having two different aspects and innovation as comprising three stages. Therefore, wehave to examine the relationships between these aspects and stages. Also, since we can expect that
consumption and innovation behaviors are correlated with each other, we assume that correlations
between them exist. Figure 1 depicts a rough structure of our model.

7Figure 1: Rough Description of the Model
Enduring
Involvement

H2 (+)

H1 (+)

Lead
Userness

H3 (+)

Consumer
AspectFrequency ofUse

H5 (+)

H4(+)

Innovator Aspect
PurchaseAmountPrivatized
Innovation

Profitable
Innovation

H6(+)
Publicized
Innovation(+)

Expected relationships are shown in the brackets

In addition, as Higie and Feick (1989) have mentioned, the enduring involvement construct canbe divided into two sub-constructs. Therefore, we estimate and compare the following two models:the first (Model 1) assumes one involvement construct, while the second (Model 2) assumes two
involvement constructs. Table 2 shows the corresponding relationships between hypotheses andpaths. In this table, lead userness is referred to as “LES,” while enduring involvement is referred toas “EIS,” after the names of the measurements. In Model 2, EIS is divided into EIS (hedonic) andEIS (self-expression).
In the next section, we describe our process of data collection.

8

Table 3: Models and summary of hypotheses
Model 1: One-Factor Model
←

H1

H2

H3

H4

H5

H6

LU

LU

Innovation

Innovation

Innovation

←

←

←

←

←

Involvement

Involvement

Usage

Involvement

LU

Innovation

Model 2: Two-Factor Model

H1a

Consumption

←

EIS

H1a

Consumption←

EIS (Hedonic)

H1b

Purchase

←

EIS

H1b

Purchase←

EIS (Hedonic)

H1c

Use

←

EIS (Self-Expression)

H1d

Purchase←

EIS (Self-Expression)

H2a

LES

←

EIS (Hedonic)

H2b

LES

←

EIS (Self-Expression)

H2

LES

←

EIS

H3a

LES

←

Consumption

H3a

LES

←

Consumption

H3b

LES

←

Purchase

H3b

LES

←

Purchase

H4a

Privatized

←

EIS

H4a

Privatized←

EIS (Hedonic)

H4b

Publicized

←

EIS

H4b

Publicized←

EIS (Hedonic)

H4b

Profitable

←

EIS

H4b

Profitable←

EIS (Hedonic)

H4c

Privatized←

EIS (Self Expression)

H4c

Publicized←

EIS (Self Expression)

H4d

Profitable←

EIS (Self Expression)

H5aPrivatized

←

LES

H5a

Privatized

←

LES

H5a

Publicized

←

LES

H5a

Publicized

←

LES

H5b

Profitable

←

LES

H5b

Profitable

←

LES

H6a

Publicized←Privatized

H6a

Publicized←Privatized

H6bProfitable←

Privatized

H6bProfitable←

Privatized

H6cProfitable←

Publicized

H6cProfitable←

Publicized

Note: LU = Lead Userness, LES = Leading Edge Status, EIS = Enduring Involvement Scale

4. Empirical Analysis
4.1.

Object Industry
In this study, we focus on the Japanese comics (manga) industry. Since there are many active

innovative users in the comics industry, it is a suitable focus for examining the research objective. In
addition, it has the following useful features.
First, the market size of the comics industry is larger than those of other content industries. In
Japan, the market volume of the comics industry in 2012 was 376 billion yen (The All Japan
Magazine and Book Publisher’s and Editor’s Association, 2013). Although the size of the comics
market is gradually decreasing with the increase in digital media, its volume is still large. In addition,
as Aoyama and Izushi (2003) have explained, the Japanese comics industry has a substantial effecton other content industries, such as the TV animation, TV drama, movie, and video game industries.
Since comics have a large derivative market, the value of the comics content industry is larger than9

its market size. For example, in the 2012 movie market, six of the top 10 Japanese movies (in termsof box-office sales) were based on comics works. Their box office sales accounted for 67% of thetotal sales of the top 10 Japanese movies (31 billion yen). Aoyama and Izushi (2003) call the comics
industry the “creative foundation” of Japanese content industries, and comic works play a vital roleeven in neighbor industries, which the Japanese government has recently been supporting. The “CoolJapan” initiative, planned by the MIETI (Ministry of Economy, Trade, and Industry) aims todramatically increase the spread of Japanese creative products on a worldwide scale.1 The comics
industry is one of the initiative’s focus industries.
The second useful feature of the Japanese comics industry is that it includes large amateur
markets and many amateur distributors. One of the most famous distribution events is the “Dojin-Shi
Sokubai Kai,” at which fan art and amateur works are sold. Some of these distribution events arevery large. For example, at the “Comic Market,” or “Comiket,” the largest event in Japan, over
30,000 amateur groups sell their own works, and over 500,000 buyers visit the three-day event.2
Amateur works are also available in bookstores that deal exclusively in these non-commercial works.
Since these bookstores have e-commerce sites, consumers are able to purchase their comics throughthe Web, even if they live far from a bookstore. These prepared events and other means of
distribution encourage amateur comic artists, and many professional comic artists get their start as
sellers at events. In recent years, amateur artists have also begun uploading their comics and movies
through applications such as pixiv, an image sharing SNS, and nico-nico doga, a movie sharing site.
The number of visitors to nico-nico doga make it the 12th most visited in Japan (and the 111th
worldwide), while pixiv is the 28th in Japan (and the 402nd worldwide), according to Alexa.com.3
We have chosen the comics industry as an objective case because of (1) its market size and theeffect of neighbor markets, and (2) its organized amateur distribution channels.
4.2.

Measurement of Behavioral Variables
In this section, we explain our measurement of behavioral variables in detail.

4.2.1. Usage
To measure usage variables, we asked questions on usage and then summarized the items.
We measured consumption with two items: “frequency of reading comic books,” and“frequency of reading comic magazines,” because comic books and magazines are the two major
distribution forms in the comics industry. In addition, we asked respondents to indicate whether the
comic books and magazines they read included those borrowed from friends, because many comics
1

Ministry of Economy, Trade, and Industry’s “Cool Japan/Creative Industries Policy”(http://www.meti.go.jp/english/policy/mono_info_service/creative_industries/creative_industries.html, retrieved on Dec, 18, 2013)2
The Official Comic Market Site (http://www.comiket.co.jp/, retrieved on Feb. 22, 2013)3
Alexa (http://www.alexa.com/, retrieved on Feb. 22, 2013)10

consumers, especially young ones, frequently lend comic books to and borrow them from each other.
Furthermore, we asked about the “frequency of viewing comics and illustrations on the web” tomeasure activity related to comics on the Internet. These three questions were measured in terms offrequency on an 11-point scale. We obtained data for an overall consumption variable in terms ofstandardized values. The details of the items and anchors are listed in the appendix.
Just as with our questions on frequency of consumption, we asked about “purchase amount ofcomic books” and “purchase amount of comic magazines” to measure purchase behavior. In theJapanese comics industry, comic magazines are commonly sold for 200-400 yen and comic books
are sold for 400-500 yen. Therefore, we can roughly estimate the monetary value of a user’s comics
purchases from the number of purchases. In addition, we asked about “purchase amount of fan
publications.” Although it is not possible to purchase fan publications in ordinary bookstores, someconsumers purchase them through the amateur market or the Internet. Generally, fan publications sellfor 500 yen. Some experimental studies and previous surveys have implied that the market size of
paid internet distribution is small (The All Japan Magazine and Book Publisher’s and Editor’s
Association, 2013). Therefore, we did not ask about the purchase amount of internet comics. Ourpurchase volume variable was obtained from the aforementioned three measurements just as theconsumption variable was based on three measurements. The items and anchors are also listed in the
appendix.
4.2.2. Innovation behavior
Our measurements of innovation behavior were based on the three-stage innovation processdescribed in the previous section.
First, to measure their degree of privatized innovation, we asked respondents about comics andillustration innovation activities. We asked them “do you draw comics/illustrations for yourself?” towhich they responded “yes” or “no.” We obtained 0- , 1- , and 2-point scores for privatized
innovation by summing up the two measures.
Next, to measure respondents’ degree of publicized innovation, we asked them whether theyshared comics or illustrations that they drew through the Internet or in other traditional media, suchas paper, CDs, and DVDs. There were four questionnaire items, for what the respondents shared(comics or illustrations) and how they shared it (through the Internet or through other traditional
media). Items could be answered with a “yes” or “no,” and we obtained a 0 to 4 score on publicizedinnovation by summing up the four measures.
Finally, to measure profitable innovation, we asked whether users sold their own works andwhether they received enough revenue to have a surplus. As with the items on publicized innovation,
since we asked about both comics and illustrations, there were four questionnaire items. For each
item, we collected “yes” or “no” answers. Therefore, we were able to obtain a 0 to 4 score for11

profitable innovation by summing up the four measures.
In our analysis, we standardized these three variables and estimated the coefficients. All items
are listed in the appendix.
4.3.

Measurement of Lead Userness and Involvement
In this study, we measure the two constructs of lead userness and involvement. To measure leaduserness, we adopted the LES, consisting of seven items, as proposed by Morrison et al. (2000). We
collected answers with a 5-point Likert scale. We also employed the EIS, as proposed by Higie andFeick (1989), to measure the enduring involvement construct. The EIS consists of 10 items, and wecollected answers with a 5-point Likert scale.

5. Results
5.1.

Data Collection
We collected data from February 15 to 17, 2013, through an internet survey. The 1,747

respondents in our sample were all under 40 years old.
The reliability coefficients for our constructs are as follows: LES is 𝛼 = 0.97 (six items, withthe last item omitted), and one-factor EIS is 𝛼 = 0.94 (10 items). In EIS, to check the number offactors, we calculated the eigenvalues of the correlation matrix. From the matrix, we got two
eigenvalues above one; therefore, it was reasonable to assume that there were two factors involved.
From the two-dimensional exploratory factor analysis, we found that the first “hedonic” factor wascontributed to by the first to fifth item, and the second “self-expression” factor was contributed to by
the seventh to tenth item. This corresponds to the results of Higie and Feick (1989). Since the sixth
item was not contributed to by either factor, we omitted it. As a result, we obtained results on thehedonic factor from the first to fifth item and results on the self-expression factor from the seventh totenth item. The Cronbach’s alpha coefficients for the hedonic factor and self-expression factor were
𝛼 = 0.97 and 𝛼 = 0.94, respectively.
5.2.

Model ComparisonFirst, we compared the results for the one-factor involvement model (Model 1) and thetwo-factor involvement model (Model 2). We compared the RMR, GFI, RMSE, AIC, and BIC
obtained from the estimation results. Table 4 shows that the indicators of Model 2 were better thanthose of Model 1. In Model 1, RMR, GFI, and RMSE are not high (low) enough, while in Model 2,
these indicators exceed the threshold value. Furthermore, AIC and BIC show that Model 2 is better
than Model 1. Therefore, in the following sections, we examine the results obtained from Model 2.

12

Table 4: Comparison of model fitness indicators
Model 1Model 2One-factor involvement modelTwo-factor involvement model

RMR

0.234

0.068

GFI

0.669

0.905

RMSE

0.165

0.078

AIC

7,578.5

1,849.0BIC

7,884.6

2,193.3

N

1747

Note: Values are bold if RMR and RMSE < 0.1 or GFI > 0.9.
5.3.

Test of Hypotheses
Table 5 shows the results of Model 2, which we used to test our hypotheses.
The first hypothesis, H1, addresses the effect of involvement on consumption behaviors. Since

there are two usage variables and two involvement factors, we divide the hypothesis into four
sub-hypotheses. From table 4, we find that both hedonic and self-expression involvement factors
positively affect consumption and purchase amount. The coefficients of hedonic involvement for
consumption behaviors are larger than those for self-expression. Thus, hypotheses H1a to H1d aresupported.
H2a and H2b concern the relationships between involvement and LES. We find that these two
factors have opposite directions. The self-expression factor positively affects LES, while the hedonic
factor negatively affects it. The negative affect of the hedonic factor is significant, at less than the
1% level. These results support H2b, but reject the validity of H2a. This implies that a user who feels
only pleasure from a product will not become an innovator. It is also in line with von Hippel’s (1986)
findings that a user’s dissatisfaction or problem recognition concerning a product encourages
innovation.
We examine the effect of usage behavior on LES in H3. Table 5 shows our findings that bothconsumption and purchase behavior positively affect LES. Users who actively create user content
tend to have high LES. This supports both H3a and H3b. Furthermore, we find that purchase’s
coefficient value to LES is larger than that of consumption.
Our results concerning H4, which addresses the relationship between involvement factors andinnovation behavior, are relatively complex. First, we find that only H4a, which concerns thehedonic factor in privatized innovation, is significantly positive. Hypotheses on the relationships
between the hedonic factor and publicized and profitable innovation are significantly negative. On
the other hand, we find that the self-expression factor does not affect any innovation behaviors.
13

Therefore, we find that only H4a is supported. In section 5.4, we discuss the indirect effect of theself-expression factor in more detail. In addition, we further examine the negative effect in thediscussion section.
The effects of LES on the three stages of innovation behaviors are all positively significant.
This supports hypotheses H5a to H5c. However, the effects of privatized and publicized innovation
are significant at the 10% level, while publicized innovation is significant at the 5% level. Thisimplies that LES’s main role is as a precedent of profitable innovation.
Finally, we tested the hypotheses for staged innovation growth. We found that the paths fromprivatized to publicized innovation and publicized to profitable innovation are positively significant,but could not find a significant relationship between privatized and profitable innovation. This resultshows that users gradually move through the three innovation stages, which fully supports H6.

Table 5: Estimated parameters
Model 2: Two-factor model
H1

H2

H3

H4

H5

H6

Estimate

Std. Est.

Std. Err.

t-value

H1a

Consumption←

EI (Hedonic)

0.312

0.433

0.018

16.92

***

H1b

Purchase←

EI (Hedonic)

0.170

0.236

0.019

8.80

***

H2c

Consumption←

EI (Self-Expression)

0.041

0.054

0.019

2.13

**

H2d

Purchase←

EI (Self-Expression)

0.110

0.146

0.020

5.45

***

H2a

LES

←

EI (Hedonic)-0.154-0.245

0.018

-8.63

***

H2b

LES

←

EI (Self-Expression)

0.254

0.387

0.018

14.37

***

H3a

LES

←

Consumption

0.061

0.070

0.030

2.05

**

H3b

LES

←

Purchase

0.201

0.231

0.028

7.20

***

H4a

Privatized←

EI (Hedonic)

0.101

0.140

0.020

4.94

***

H4b

Publicized←

EI (Hedonic)-0.081-0.113

0.017

-4.79

***

H4c

Profitable←

EI (Hedonic)-0.066-0.091

0.016

-4.19

***

H4d

Privatized←

EI (Self-Expression)-0.001-0.001

0.023

-0.02

H4e

Publicized←

EI (Self-Expression)

0.028

0.037

0.019

1.46

H4f

Profitable←

EI (Self-Expression)

0.016

0.022

0.017

0.93

H5a

Privatized

←

LES

0.049

0.042

0.030

1.65

*

H5b

Publicized

←

LES

0.046

0.040

0.025

1.82

*

H5c

Profitable

←

LES

0.049

0.042

0.024

2.07

**

H6a

Publicized←Privatized

0.574

0.574

0.020

28.91

***

H6b

Profitable←

Privatized-0.005-0.005

0.022

-0.22

H6c

Profitable←

Profitable

0.652

0.652

0.022

29.67

***

Note: Std. Est. = Standardized Estimates, Std. Err. = Standard Error, * = p < 0.1, ** = p <0.05, *** =p < 0.01
14

In summary, the LES directly encourages innovation behaviors. The LES directly affects three
innovation behaviors as a precedent-encouraging factor. Although the hedonic factor positively
affects privatized innovation, its effect on profitable innovation is negative. Usage behaviors affectthe LES positively. In particular, the effect of purchase amount is larger than the frequency of
consumption. In involvement, the effects of hedonic and self-expression factors on the LES are
opposite to each other.
5.4.

Indirect Effects
In this section, we examine the indirect effects of involvement factors on innovation behaviors

through the LES. To test indirect effects, Sobel (1982) proposes a procedure of statistic examination.
Based on Sobel’s approach, Baron and Kenney (1986) and Mallinckrodt et al. (2006) also examine
methods for testing indirect effects. We apply these methods to test indirect effects. As Mallinckrodt
et al. (2006) mentions, the results of measurements of indirect effects are not reliable when thesample involved is small. However, since the sample in this study involves more than 1,700
respondents, we were able to obtain reliable results.
Table 6 shows the results on indirect effects. We find that the indirect effects of the hedonic
factor on innovation behaviors are negative. In contrast, the indirect effects of the self-expression
factor on innovation behaviors are positive. Although we cannot observe the direct effects of theself-expression factor, this factor indirectly affects innovations via the LES.

Table 6: Indirect effects
Estimate

Std. Est.

Std. Err.

z-value

Prob.

Privatized

←

LES

←

EI (Hedonic)-0.0075-0.0103

0.0047

-2.17

0.030

**

Publicized

←

LES

←

EI (Hedonic)-0.0071-0.0098

0.0040

-2.47

0.013

**

Profitable

←

LES

←

EI (Hedonic)-0.0075-0.0103

0.0038

-2.69

0.007

***

Privatized

←

LES

←

EI (Self-expression)

0.01240.01630.0077

2.11

0.035

**

Publicizes

←

LES

←

EI (Self-expression)

0.01170.01550.0064

2.41

0.016

**

Profitable

←

LES

←

EI (Self-expression)

0.01240.01630.0062

2.63

0.008

***

Note: Std. Est. = Standardized Estimates, Std. Err. = Standard Error, * = p < 0.1, ** = p <0.05, *** =p < 0.01

In this study, we initially expected that involvement would be a direct source of motivation, but
our results show different relationships. In particular, we find that the self-expression factor does notdirectly affect innovations. We assume that this result is caused by the characteristics of comics
production. In the Japanese comics industry, comics are mainly drawn by a single person; therefore,15

a certain level of drawing and construction technique is needed by comics artists. Some users do nothave enough skills, even if they have high levels of involvement with comics.

6. Discussion
6.1.

Rewards and Innovations
Our findings show that there are substantial differences among the motivation structures ofprivatized, publicized, and profitable innovation. This is particularly true for the effects of thehedonic factor, which is a sub-construct of enduring involvement but moves in a direction opposite
to its effects. In this section, we discuss the background of our results.
First, the difference between pleasure (hedonic factor) and dissatisfaction (problem recognition)is important. In the consumer information processing model (e.g., Bettman, 1979; Blackwell,
Miniard, and Engel, 2010), the first step in a behavior is “problem (or need) recognition.”
Consumers recognize the gap between an ideal and actual state and try to fill it. In our study,
innovative users seem to face similar problems or needs. This causality fits in with the first definitionof a lead user proposed by von Hippel (1986). Consumers who have high hedonic factor scores do
not feel any problems or needs in the comic industry, and therefore do not tend to create. The
exception to this is that the hedonic factor positively affects privatized innovation. Although, wehave to examine this result in further detail, private drawings are only for the pleasure of users. Ifthey feel any dissatisfaction, they can publicize their own solutions, in the form of their own comics.
Dissatisfaction with the present state of an industry is one of the motivations of innovation,
especially in the socialized stage, in forms such as publicized and profitable innovation.
Second, it should be kept in mind that there are differences among the rewards of privatized,
publicized, and profitable innovation. Users do not receive monetary rewards for the first two stagesof innovation but do for the third stage. Deci (1975) discusses how intrinsic motivation tends to becontrolled by more concrete extrinsic motivations such as money. Generally, this change ofmotivation is irreversible. This implies that, at first, users’ private generation is motivated byintrinsic factors such as involvement, which is mainly a hedonic factor, but that, once they begin
sharing their works and gaining recognition from other consumers, their motivations shift toward
peer recognition and away from intrinsic motivation. At the profitable stage, monetary rewards
become a central motivation, making intrinsic motivation unnecessary. It should be noted that, since
the shift in motivation is irreversible, users who are at the profitable stage have to receive monetary
rewards to continue to generate content.
6.2.

The Role of the Publication Stage
In information industries, and especially content industries, user-generated content plays a vitalrole in supporting the market. In these industries, firms have to find new creators among the16consumers of content. Some innovative consumers become professionals, and their products are soldthrough commercial distribution. Firms have to deal with consumers not only for monetary income
but also in order to foster the development of new creators.
To maintain this reproduction system, the publication (sharing) stage is especially important. As
shown by the results of H6, users gradually move through innovation stages. Privatized innovators
do not directly become profitable innovators but do so via a stage in which they are publicizedinnovators. The comics industry has long featured many means of amateur distribution, butpublishing an amateur comic book is difficult for low-level innovative users. Recently, as a middle
stage, many users upload their works free on the Internet. These means of sharing are important
contact points that allow them to obtain feedback from readers. Based on comments and evaluationsof their work, innovative users are able to understand the needs of the market. Innovative users
become market-oriented by sharing their innovations and communicating with other users. All
innovative users can access Internet distribution systems from anywhere, which encourages future
professional creators. Some papers in the field of user innovation mention that toolkits andinformation-sharing communities encourage user innovation (e.g., Jeppesen, 2005; von Hippel,
2001a; von Hippel and Katz, 2002). Through the middle stage, users can easily achieve their
purposes, which maintains their levels of motivation.

7. Conclusion
In this study, we examine the usage and innovation behaviors of end users in the informationindustry. We divide usage and innovation into two aspects and three stages, respectively, and propose
a model of user behavior. Based on this model, we examine differences in the motivation structuresof non-profitable and profitable innovation. Our study has made contributions to the existing
literature and raised the following issues for future exploration.
The first contribution of our study is its findings on the relationships between the innovation
behaviors and usage behaviors of consumers/users. Users are basically economic entities who pay
money in exchange for products provided by firms. In our research, we focus on content generation(not only for consumption) and propose a comprehensive model of user behavior. Although, in thisstudy, we discuss the comics industry, our findings are applicable to other industries. Future researchshould apply the model to other industries, such as the software development or music industries,and examine any points of difference.
The second contribution of our work is that it reveals the motivation structure involved in bothusage and innovation behaviors among users. Previous studies have focused on lead userness and its
precedent factors. However, our research incorporates the involvement construct to examine further
intrinsic properties of users. In particular, we divide enduring involvement into two sub-constructs,
hedonic and self-expression factors, and find many beneficial implications. This also allows us to17

demonstrate substantial changes in motivation structures as users grow through innovation stages. In
the future, we need to further consider precedent factors and transitions in motivation as innovative
users step up, as well as our measurement scales and model.

18

Appendix: Measures
Table A1. Measures of usage behaviors
Items

Anchors

Consumption
How many comic magazines do you read in a month?

1) Never; 2) 1; 3) 2; 4) 3; 5) 4; 6) 5; 7) 6 to 10;

How many comic books do you read in a month?

8) 11 to 30; 9) 21 to 50; 10) 51 to 100; 11) Over 101

How often do you browse illustrations and comics on1) Never; 2) Less than once a year;

the Internet?

3) Several times a year; 4) Once a month;5) Several times a month; 6) Once a week;7) Several times a week; 8) Once a day;9) Several times a day; 10) More than 10 times a day

Purchase
How many manga magazines do you purchase in a1) Never; 2) 1; 3) 2; 4) 3; 5) 4; 6) 5; 7) 6 to 10;

month?

8) 11 to 30; 9) 21 to 50; 10) 51 to 100; 11) Over 101

How many manga books do you purchase in a month?
How many manga fun publications do you purchase ina year?

Table A2. Measures of innovation behaviors
Items

Anchors

Privatized Innovation
Do you draw illustrations for yourself?

0) No; 1) Yes

Do you draw comics for yourself?
Publicized Innovation
Do you share illustrations that you drew on the Internet?

0) No; 1) Yes

Do you share comics that you drew on the Internet?
Do you share illustrations that you drew in other traditional media such as papers, CDs,
and DVDs?
Do you share comics that you drew in other traditional media, such as paper, CDs, andDVDs.
Profitable Innovation
Do you sell illustrations that they drew to others?

0) No; 1) Yes

Do you sell comics that you drew to others?
Do you sell illustrations that you drew and receive enough revenue to have a surplus?
Do you sell comics that you drew and receive enough revenue to have a surplus?

19

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