Description
Base on the social network theory, this study attempts to investigate whether the network centrality will
affect the user participation in ERP system post-implementation or not. In aspects of network centrality,
we used degree, closeness, betweenness and eigenvector as indicators to investigate the relationships
between individual network centrality and user participation. Thenwe further explore the impact of user
participation on system use and user satisfaction. We adopted the ERP post-implementation of TSC
Company as an example. The sample data has 211 questionnaires. Our empirical results show that
network centrality positively affects the three dimensions of user participation; hands-on activity and
communication activity positively affect system use; usereIS relationship, hands-on activity, and
communication activity positively affect user satisfaction. Through the lens of social network, we argued
that ERP user network plays an important role to influence user participation in post-implementation
period, which is critical for system use and user satisfaction.
Model of post-implementation user participation within ERP advice network
Pei-Hung Ju
a
, Hsiao-Lan Wei
b, *
, Chung-Che Tsai
c
a
Department of Business Administration, School of Management, National Kaohsiung University of Applied Science, Kaohsiung, Taiwan, ROC
b
Department of Information Management, School of Management, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC
c
Department of Software Application Development, ASUSTeK Computer Inc., Taipei, Taiwan, ROC
a r t i c l e i n f o
Article history:
Received 9 March 2015
Accepted 2 November 2015
Available online xxx
Keywords:
User participation
Social network
ERP post-implementation
Network centrality
a b s t r a c t
Base on the social network theory, this study attempts to investigate whether the network centrality will
affect the user participation in ERP system post-implementation or not. In aspects of network centrality,
we used degree, closeness, betweenness and eigenvector as indicators to investigate the relationships
between individual network centrality and user participation. Then we further explore the impact of user
participation on system use and user satisfaction. We adopted the ERP post-implementation of TSC
Company as an example. The sample data has 211 questionnaires. Our empirical results show that
network centrality positively affects the three dimensions of user participation; hands-on activity and
communication activity positively affect system use; usereIS relationship, hands-on activity, and
communication activity positively affect user satisfaction. Through the lens of social network, we argued
that ERP user network plays an important role to in?uence user participation in post-implementation
period, which is critical for system use and user satisfaction.
© 2016 College of Management, National Cheng Kung University. Production and hosting by Elsevier
Taiwan LLC. All rights reserved.
1. Introduction
Many researchers study the key factors of how to implement
enterprise resource planning (ERP) system successfully (Chou &
Chang, 2008; Chung, Skibniewski, & Kwak, 2009; Morton & Hu,
2008). These successful factors may broadly be classi?ed as hu-
man/organizational, technical, and economic ones (Chen, 2001;
Sarker & Lee, 2003). While each set of factors is important, there
appears to be a growing consensus among researchers that human
factors, more than technical or economic, are critical to the success
of ERP projects (Alvarez, 2008; Sarker & Lee, 2003). Sarker and Lee
(2003) suggest that empowering the team-members for self-
management and communication issues are seen as central to
success of an ERP implementation project. Salmeron and Lopez
(2010) indicate that encouraging the active participation of all
users involved in the process of post-implementation ERP systems
is essential in the success of the ERP maintenance. To deal with
technical complexity and overambitious demands associated with
ERP systems, user participation is important to mitigate risk (Amrit,
van Hillegersberg, & van Diest, 2013). Therefore, user participation
is an important factor when implementing the ERP system.
User participation refers to the favorable behaviors and activ-
ities that users perform in the systems development process to
promote ef?cient and effective implementation of ERP systems
(Bagchi, Kanungo, & Dasgupta, 2003; Barki & Hartwick, 1989; Ives
& Olson, 1984; Kawalek & Wood-Harper, 2002). When organiza-
tions plan to use an ERP system, a number of user representatives
participated in software package con?guration and there might
have a conceptual gap between developers and users (Barki, Rivard,
& Talbot, 2001; Kappelman, 1995; Markus & Ji-Ye, 2004). To close
the gap to ensure ERP systemimplementation success, it's essential
for organizations to handle user participation carefully (Dong-Gil,
Kirsch, & King, 2005; Markus, Axline, Petrie, & Tanis, 2000). User
participation can improve system quality by giving developers the
information they need to produce a high-quality design (Barki et al.,
2001; Byrd, Cossick, & Zmud, 1992; Markus & Ji-Ye, 2004). Besides,
user participation in change management activities such as plan-
ning or conducting training is much more likely to affect system
acceptance and use outcomes (Kappelman, 1995; McKeen &
Guimaraes, 1997; Yetton, Martin, Sharma, & Johnston, 2000). ERP
system is an integrated solution in an enterprise, which involves
internal work?ow within inter-departmental cooperation. The
* Corresponding author. Tel.: þ886 2 27303226; fax: þ886 2 27376777.
E-mail address: [email protected] (H.-L. Wei).
Peer review under responsibility of College of Management, National Cheng
Kung University.
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Asia Paci?c Management Review xxx (2016) 1e10
Please cite this article in press as: Ju, P.-H., et al., Model of post-implementation user participation within ERP advice network, Asia Paci?c
Management Review (2016),http://dx.doi.org/10.1016/j.apmrv.2015.11.001
communication and coordination in related users are extremely
important as well as the communicationwith consultants. With the
efforts in both sides, the implementation can be ensured to corre-
spond to the entire work?ow in the enterprise.
The timing issue of user participation over ERP lifecycle is
highlighted as an important but ignored dimension recently
(Wagner & Newell, 2007). As post-implementation success of ERP
is critical for adopting organizations in order to fully bene?t from
system's potential, user participation is extremely important at this
stage. During the implementation stage, only limited key users are
participated in the con?guration of ERP to help the system go live.
After the installation of an ERP system, a critical mass of users start
the exploitation and evaluation of the system and some uncon-
trolled problems may also appear. Post-implementation phase
including the stabilization, operation and extension of the ERP
system involves a large number of different users from different
functions and previously silent users may express their dissatis-
faction with the system, which will in?uence the acceptance of the
ERP system (Markus & Ji-Ye, 2004; Wagner & Newell, 2007).
Therefore, investigating post-implementation participation is crit-
ical for the system's survival and assimilation in the organization
because users themselves need situated learning through use to
?gure out what is best from ERP system for existing practices.
A person's behavior intention is in?uenced by his/her personal
relationship network in an organization (Sykes, Venkatesh, &
Gosain, 2009; Zagenczyk & Murrell, 2009). This impacts the
result of learning and knowledge exchange during the ERP post-
implementing process. Therefore, a concept of social network is
proposed to study the in?uences in different network relationship.
How to use the network to achieve the enterprise target has been
highly valued by the management because understanding an em-
ployee's network relationship is bene?cial to ?nd out the in?uen-
tial users during the process of ERP post-implementation. The
potential users have greater in?uences in drawing the participation
of other users and thus they indirectly enhance the possibility of
successful post-implementation. Many researches show that the
social network has signi?cantly in?uence in individual job perfor-
mance (Ahuja, Galletta, & Carley, 2003; Sparrowe, Liden, Wayne, &
Kraimer, 2001). More and more studies reveal the behavior in?u-
ence impacted by individual's network relationship (Sykes et al.,
2009; Zagenczyk & Murrell, 2009). The network relationship in
an organization has certain impact on user participation. Sykes
et al. (2009) indicated that the counseling network relationship
has signi?cant in?uence on system usage. Meanwhile, the network
relationship in?uences one's job involvement (Zagenczyk &
Murrell, 2009). Individual's network relationship is a key variable
in one's participation. During the post-implementation, the rele-
vant users will be impacted by the social network, and the
following behavior changes are key factors of successful post-
implementation.
As studies on the ERP post-implementation phase are still un-
derrepresented (Esteves & Boh orquez, 2007; Grabski, Leech, &
Schmidt, 2011) and the call for investigating post-implementation
user participation (Markus & Ji-Ye, 2004; Wagner & Newell,
2007), this research explains the in?uence of user participation and
the relationship of the successful ERP post-implementation, based
on the social network theory (Bonacich, 1972; Freeman, 1979) and
the user participation theory (Barki & Hartwick, 1994a; Hartwick &
Barki, 2001). It intends to understand the relationship of social
network, user participation and the success of system post-
implementation and to discover the role of social network in
post-implementation and in the enhancement of user participation
to accomplish the system post-implementation successfully.
Section one covers the relevant background literature. This is
followed by theoretical framework and hypotheses section and
then the methodology one. We then analyze the results and we
draw conclusions in the ?nal section.
2. Conceptual background
2.1. Social network
A social network can be de?ned as a relationship comprising a
series of persons, objects, and events; different networks can be
formed with the same elements because of different types of
relationship. In social network theory, these persons, objects, and
events are de?ned as actors or nodes. The relationships between
actors in a structural relationship and an individual actor in a
network have a strong in?uence on the behavior, perception, and
attitude of an individual or an entire organization (Knoke &
Kuklinski, 1982).
When a corporation introduces an IS system, network centrality
is one of the crucial elements; the corporation must invest
considerable resources during the introduction, which makes the
transmission and control of these resources highly valuable. The
knowledge, intentions, and behavior of using the newsystemis also
affected by the network (Sykes et al., 2009). Network centrality is
de?ned as “the scope of individual participation in the network
which facilitates information exchange among colleagues”
(Sparrowe et al., 2001). Knoke and Kuklinski (1982) indicated that
the interactions of numerous relationships, including the trans-
mission and receipt of information, exist in the process of contact
among individuals, and that the level of individual involvement can
be judged by the number of relationships.
Researchers consider network centrality an essential structural
attribute in social networks. Individuals situated in the network
center can control the ?ow of resources and related knowledge. An
individual is not affected by others; instead, he or she has in?uence
on individual power in an organization, as well as resource control
(Ibarra, 1993; Ibarra &Andrews, 1993). However, if the individual is
situated at a lower level of network centrality, he or she must rely
on others to pass on resources and knowledge and is subsequently
easily in?uenced by the environment (Freeman, 1979). Freeman
(1979) and Bonacich (1972) analyzed network centrality by using
four dimensions: degree, closeness, betweenness, and
eigenvectors.
In 1974, researchers started to apply social network concepts to
the technology innovation diffusion model of an organization
(Czepiel, 1974) and discovered that an informal communication
network within an organization can ease the adoption of a new
system. The network is also crucial to the IS system post-
implementation, as well as the transmission and transfer of
related resources and knowledge in the organization. Some studies
have indicated that the structures of a social network can affect the
transmission of valuable resources in an organization (Brass, 1984;
Ibarra, 1993). Work-related resources, such as work counseling and
strategic information, can be transmitted through a social network,
as can social recognition, discipline, and support (Sykes et al.,
2009). How knowledge and usage methods can be transferred to
users during the post-implementation process of an ERP system is
crucial. Informal personal networks play a key role in transferring
the knowledge about a new system. Hence, Sykes et al. (2009)
considered it dif?cult to accomplish the absorption and trans-
mission of professional knowledge about a new system within a
short timeframe; transferring knowledge among people with
similar training, backgrounds, and work characteristics is easier.
When an organization introduces a new IS system, it is more
effective to share and transmit knowledge of the new system by
using staff in the same department of the organization. In
P.-H. Ju et al. / Asia Paci?c Management Review xxx (2016) 1e10 2
Please cite this article in press as: Ju, P.-H., et al., Model of post-implementation user participation within ERP advice network, Asia Paci?c
Management Review (2016),http://dx.doi.org/10.1016/j.apmrv.2015.11.001
summary, the social network perspective in IS implementation has
become a prominent topic in recent years (He, Qiao, & Wei, 2009).
2.2. User participation
In the development of information systems, user participation
and user involvement are key success factors. Early studies have
indicated that user participation or involvement has positive effects
on the success of systems (Swanson, 1974). However, these early
studies did not clearly differentiate between user participation and
user involvement. Ives and Olson (1984) proposed that participa-
tion, including board behavior, activities, and responsibilities, refers
to users or system developers. Barki and Hartwick (1994a) de?ned
user participation as a series of operations and activities conducted
by users or their representatives during system development.
Compared with user participation, which is demonstrated by
the user's external behavior and activities, user involvement rep-
resents a user's inner subjective state of mind. According to early
studies, a user's state of mind affects his or her attitudes, satisfac-
tion, and intention to use a system. Furthermore, user participation
has an obvious positive in?uence on user involvement. Therefore,
actual participation in the form of behavior or activities during a
system's development may improve a user's state of mind; this in
turn affects the user's satisfaction and the extent of his or her
intention to use the system.
In the activities of user participation, some scholars have pro-
posed that participation should not be limited to only before sys-
tem implementation, but also afterwards. Before system
implementation, if the user clearly understands the relevance of
the system to him or her, it may increase the user's eagerness to
participate in the process of system development. After system
implementation, user satisfaction must be improved. The system
and its ?tness can be modi?ed through user participation to
improve user satisfaction (Wagner & Newell, 2007).
Recently, ERP studies have emphasized the importance of post-
implementation concerns and have suggested that user participa-
tion plays a critical role for the assimilation and business bene?ts of
ERP (Liu, Feng, Hu, & Huang, 2011; Staehr, Shanks, & Seddon, 2012;
Wagner & Newell, 2007). Wagner and Newell (2007) indicated
several factors inhibiting user participation during the initial
implementation phase, such as legacy thinking, pseudo participa-
tion, and motivation. Aligning ERP software with existing practices
is easier after actual implementation and through situated learning.
The sustained use of an ERP system is a critical component for
realizing its anticipated bene?ts. Liu et al. (2011) argued that the
business value of ERP cannot be fully realized until it is extensively
assimilated into business processes and individual-level assimila-
tion focuses on the understanding of ERP and the ability to use ERP
for non-routine tasks. Therefore, post-implementation engagement
is an effective method of increasing user interest and enhancing the
ability to exploit ERP, leading to increased system use and assimi-
lation (Wagner & Newell, 2007).
3. Theoretical framework and hypotheses
In this study, individuals in the network of relations within an
enterprise were the focal point of howan enterprise implements its
ERP system and how participation behavior arising from personal
network relationships in?uences the success of enterprise system
implementation. The four indicators of degree, closeness,
betweenness, and eigenvectors were used to de?ne the individual
within the enterprise network centrality. User participation was
divided into three parts: the relationship between users and in-
formation technology (IT) staff, actual participation in activities,
and communication activities. Finally, user satisfaction and system
use were used to measure the success of post-ERP implementation.
The theoretical research model is depicted as Fig. 1.
3.1. Network centrality and user participation
Network centrality is an essential aspect of research on social
networks (Ahuja et al., 2003; Sparrowe et al., 2001; Sykes et al.,
2009). It is de?ned as the scope of individual participation that
helps working partners exchange information (Sparrowe et al.,
2001). Network centrality is measured by the number of rela-
tional connections in an individual network. One study showed
that if individuals within an organization's network center, which
has more links, may have a high impact capacity (Freeman, 1979).
Scholars also believe that the degree of network centrality affects
individual performance within the organization (Ahuja et al.,
2003), work involvement (Zagenczyk & Murrell, 2009) and
resource control (Ibarra, 1993).
The relationship between users and IT staffs is de?ned as
development activities that re?ect the communication and in?u-
ence among users and IT staffs (Barki & Hartwick, 1994a). Some
studies have indicated that when the implementation of an infor-
mation system faces a problem, individuals search their network of
relations for a solution, not only to enhance their job performance
but also to have a major in?uence on the degree of participation in
information system implementation (Sparrowe et al., 2001; Sykes
et al., 2009). Thus, network centrality is key to the relationship
between users and IT staff. The degree of network centrality rep-
resents the linkage level for an individual in relation to others
within the organization, and shows the communication relation-
ship between the individual and related IT staff (Ahuja et al., 2003;
Sparrowe et al., 2001), as well as personal power within the orga-
nization (Ibarra, 1993; Ibarra & Andrews, 1993). It can in?uence
relationship building within an organization. Therefore, the
following hypothesis was proposed.
H
1
: Network centrality is positively associated with the rela-
tionship between users and IT staff in post-ERP implementation.
Brass and Burkhardt (1993) stated that employees with a higher
degree of network centrality have increased power within the or-
ganization. In addition, the personal closeness of network cen-
trality can represent the power of individuals within an
organization, and the power affects other people's views and per-
spectives in the network (Ibarra, 1993; Ibarra & Andrews, 1993;
Sparrowe et al., 2001). The in?uence or drive from center mem-
bers of the network affects whether an individual actually partici-
pates in decision-making in the new system (Sykes et al., 2009). In
addition, network centrality positively in?uences individual
Fig. 1. Research model.
P.-H. Ju et al. / Asia Paci?c Management Review xxx (2016) 1e10 3
Please cite this article in press as: Ju, P.-H., et al., Model of post-implementation user participation within ERP advice network, Asia Paci?c
Management Review (2016),http://dx.doi.org/10.1016/j.apmrv.2015.11.001
behaviors, and enhances the degree of participation for related
work (Zagenczyk & Murrell, 2009). Network centrality can affect
the actual behavior of users to pay for the process of information
system post-implementation. Therefore, the following hypothesis
was proposed.
H
2
: Network centrality is positively associated with actual
participation in hands-on activity in post-ERP implementation.
Communication activities are regarded as an essential part of
the process of information system implementation; the interactive
communication between users and the project team allows the
functions of information systems to ?t with individual daily work.
Hartwick and Barki (2001) explored the various dimensions of user
participation and de?ned communication activities as a crucial
aspect. Users exchange information through formal or informal
communication with other participants. As such, communication
activities have become a factor in post-implementation ERP.
Following social networks theory, an individual's degree of network
centrality can be regarded as an indicator for potential communi-
cation activities (Freeman, 1979). Through the degree of network
centrality, the interaction between individuals and other people in
organizations can be understood; it also represents the degree to
which individuals will participate in projects or related communi-
cation activities (Ahuja et al., 2003; Sparrowe et al., 2001). Users
related through an interactive network of communication within
an organization answer questions about information systems and
assist in the implementation process. Members with a high
network centrality act as a valuable bridge for promoting the use of
the system by others (Sykes et al., 2009) and the degree of work
participation (Zagenczyk & Murrell, 2009).
We present the following hypothesis:
H
3
: Network centrality is positively associated with the
communication activities in post-ERP implementation.
3.2. User participation and system use
Effective use of an information system is considered the main
determinant for enhancing organizational competitiveness and
productivity. System use is included in the six categories of IS
success in the model by DeLone and McLean (1992). It is mainly
used to determine the level of actual use of information system.
Studies have indicated that user participation can help users
develop ownership feelings for the ERP system, which strongly
in?uences their acceptance of the system(Barki &Hartwick, 1994b;
Barki, Pare, & Sicotte, 2008).
The relationship between users and developers is one of the
factors that affect the result of system implementation (Cavaye,
1995). This relationship is crucial because ERP systems may cause
comprehensive changes to the business process. Users review or
evaluate the work completed by information system staff such that
the system can meet actual work processes (Hartwick & Barki,
2001). This enhances their feelings of control, intimate knowl-
edge, and ownership of the ERP (Barki et al., 2008; Pierce, Kostova,
& Dirks, 2001). The feelings of possession toward an ERP can
effectively improve the willingness of users to use the system for
their work. Therefore, the following hypothesis was proposed.
H
4
: The relationship between users and IT staff is positively
associated with ERP system use in post-ERP implementation.
Studies have shown that actual participation in implementation
activities has a signi?cantly positive effect on the willingness to use
the system in the future (Wu & Marakas, 2006). Users with work-
related knowledge obtained through actual participation in
implementation activities can effectively reduce the gaps between
users and IS staff and increase the possibility to develop user-
friendly solutions. By participating in design activities, users
perceive the ERP system as much more relevant, useful, and
essential for their job (Barki et al., 2008). The literature on tech-
nology acceptance has suggested that a system with a higher level
of perceived usefulness leads to a higher degree of use; hence, users
that help design the ERP systemcan enhance the willingness to use
ERP after introducing the system(Kositanurit, Ngwenyama, &Osei-
Bryson, 2006; Saleem, 1996). Therefore, the following hypothesis
was proposed.
H
5
: Actual participation in hands-on activity is positively asso-
ciated with ERP system use in post-ERP implementation.
A successful ERP system must be reworked and continuously
improved to satisfy new or changed business processes, through a
series of post-implementation projects (McGinnis & Huang, 2007;
Rajagopal, 2002). In the post-implementation process, system-
related knowledge and information must be conveyed through
communication activities. Communication and learning among
users after implementation is critical. The knowledge created dur-
ing the implementation process is a valuable resource and should
be shared for the ultimate success of ERP (McGinnis & Huang,
2007). Education and training after the system goes live is one of
the channels of communication; however, this can distribute only
explicit knowledge. Tacit knowledge could be exchanged through
meetings, chat, discussion, and other socialization activities.
Communication activities allow users to absorb and learn ERP-
related knowledge, which can facilitate the willingness and abil-
ity to actively use the new system. Therefore, the following hy-
pothesis was proposed.
H
6
: Communication activities are positively associated with ERP
system use in post-ERP implementation.
3.3. User participation and user satisfaction
Previous studies have suggested that user participation in the
information system implementation process can improve user
satisfaction (Hwang & Thorn, 1999; Wu & Marakas, 2006). By
incorporating the expectancy discon?rmation, equity, and needs
theories, Au, Ngai, and Cheng (2008) indicated that user satisfaction
is a function of IS performance, IS performance expectations,
equitable work performance ful?llment, equitable relatedness
ful?llment, and equitable self-development ful?llment. Participa-
tion in the formal approval of speci?cations and the continuous
review of the system can improve control in the outcome of ERP in
the post-implementation stage and obtain the desired information
and system quality. After the daily situated learning of using the
ERP system, users gain con?dence with their outcome control to
obtain improved system performance. Participation activities may
also enhance psychological ownership of the ERP, thereby creating
feelings of control and power, and ful?lling the needs of relatedness
for end users (Au et al., 2008; Barki et al., 2008). In summary, user
participation should lead to a greater commitment to and a higher
value of resultant systems, ultimately leading to greater satisfaction
(McKeen, Guimaraes, & Wetherbe, 1994). Therefore, the following
hypothesis was proposed.
H
7
: The relationship between users and IT staff is positively
associated with user satisfaction in post-ERP implementation.
P.-H. Ju et al. / Asia Paci?c Management Review xxx (2016) 1e10 4
Please cite this article in press as: Ju, P.-H., et al., Model of post-implementation user participation within ERP advice network, Asia Paci?c
Management Review (2016),http://dx.doi.org/10.1016/j.apmrv.2015.11.001
User participation in activities related to system development
can improve the information systemto ?t the organization or work,
which has a signi?cant in?uence on user satisfaction (McKeen et al.,
1994; Wagner & Newell, 2007). In the post-implementation stage,
users explore ERP as implemented to identify the functionality
necessary for performing daily tasks and de?cient functionalities.
This exploration is a learning process that allows users to be more
competent with ERP features (Gallagher, Worrell, & Mason, 2012).
As users participate in activities to design extended functionality of
the system to align ERP with business needs, the experiential
knowledge of the system is enriched. Therefore, actual participa-
tion may increase user motivations to make the ERP system useful
for their jobs and enhance user absorptive capacities, leading to
higher levels of ERP assimilation during the post-implementation
stage (Liu et al., 2011). Satisfaction with the ERP system is
improved as it becomes more closely aligned with business needs.
We present the following hypothesis:
H
8
: Actual participation in hands-on activity is positively asso-
ciated with user satisfaction in post-ERP implementation.
Research has suggested that communication relations between
users and developers have a signi?cant in?uence on user satisfac-
tion (McKeen et al., 1994). Saleem(1996) con?rmed that users have
expertise relevant to the work. The interaction and the ability to
exchange information between users and IT staff can affect system
satisfaction through knowledge exchange and learning. Commu-
nication activities can transmit relevant knowledge and needs,
improve the quality of system outputs, and improve the ability to
meet user needs. To successfully manage the knowledge of ERP,
organizations must establish a knowledge-sharing community to
provide a common frame of reference for all ERP activities
(McGinnis & Huang, 2007). This common frame of reference is
exchanged, assimilated, and distributed through communication
activities among users, IS staff, and managers. As such, users and IS
developers can have a shared understanding of an ERP system,
leading to reasonable user expectations for the system (Saeed,
Abdinnour, Lengnick-Hall, & Lengnick-Hall, 2010). The increased
realization of expected bene?ts of ERP use has a great in?uence on
user satisfaction (Bhattacherjee, 2001). Therefore, we present the
following hypothesis:
H
9
: Communication activities are positively associated with user
satisfaction in post-ERP implementation.
4. Methodology
4.1. Data collection
The subject of this study is based on personal social networks
within an organization, users in the information system, and the
successful implementation of a system. A well-known domestic
company (hereinafter referred to as TSC) with an ERP system
implementation project was thus chosen for this study. TSC
developed a new WebERP system in 2006, which included the
following modules: distribution, production management, ?nance,
human resources management, and project management. This
new generation of online WebERP was expected to reduce paper
work, achieve fully electronic processes, and streamline ERP to
improve the ef?ciency of the enterprise. The ERP system imple-
mentation project is still undergoing maintenance and
improvement.
The total number of employees in TSC was approximately 400.
Through our contact with the relevant authorities to identify and
obtain ERP system implementation information, we initially
identi?ed approximately 300 people in TSC as users for the ERP
system implementation project, to whom we issued question-
naires. Out of 300 questionnaires, a total of 243 were returned,
leading to a return rate of 81%. Some respondents did not want to
disclose information for the personal networking questions, lead-
ing to 32 invalid or incomplete questionnaires. The total number of
valid questionnaires was 211, and the effective rate was 70.33%. The
respondents covered various departments and job functions, and
had worked for more than one year; thus, all respondents had a
certain degree of understanding of the ERP systemimplementation
(Table 1).
4.2. Measures
To measure network centrality, we used Freeman (1979) and
Bonacich's (1972) four-measure index: degree, closeness,
betweenness, and eigenvectors. Degree was the extent of inter-
action with other members of the network. Closeness represented
a person's freedom from dependence on other members of the
network. Betweenness gauged the extent which an employee is a
key intermediary, i.e., in a position to control communication or
information exchange. Eigenvector was associated with greater
network in?uence because it was highly depending on the con-
nections to well-connected employees. It is a recursive measure
in which a user's centrality is proportional to the sum of cen-
tralities of the users to which they are connected, weighted by
the strength of connection (Bonacich, 1972). An open-question
survey was used to ask each ERP user the following question
adapted from Sykes et al. (2009) and Zagenczyk and Murrell
(2009): “when implementing/using ERP, who will you get
advice and help for your system problems?” We asked re-
spondents to list one to ten persons including their name,
department, and weight (interaction degree, 1 ¼ low, 5 ¼ high).
These data were used to compute the four network centrality
aspects discussed earlier.
The user participation constructs were measured with items
developed by Hartwick and Barki (2001). We only indicated that
the project/system was ERP project/system. The relationship be-
tween users and IT staffs was de?ned as the interaction between
users and IT staffs during the information system implementation
project; eight questions were used to assess this measure. Actual
involvement in activities was de?ned as activities related to the
case actually involved during the information system imple-
mentation project; nine questions were used to assess this mea-
sure. Communication activity was de?ned as communication
circumstances among all relevant members during the informa-
tion system implementation project; 12 questions were used to
assess this measure (Hartwick & Barki, 2001). System usage was
de?ned as the performance changes caused by users actually
using the system after the information system went into pro-
duction; ?ve questions were used to assess this measure using
item developed by Park, Suh, and Yang (2007). User satisfaction
was de?ned as the user views and evaluation of the system after
the information system went into production; 12 questions were
used to assess this measure adapted from Doll and Torkzadeh
(1989).
5. Result
This study used social network and structural equation
modeling (SEM) analysis for data analysis. The study divided
analyzing process into three parts: the ?rst part calculated TSC
personal network centrality; second part assessed the reliability,
convergent validity and discriminant validity for measurement
model; the third part evaluated an overall structural model.
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Please cite this article in press as: Ju, P.-H., et al., Model of post-implementation user participation within ERP advice network, Asia Paci?c
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5.1. Network centrality analysis
This study collected data of the advice network when the TSC
implement ERP to build up personal social networks. Table 2 de-
scribes the top twenty users' network centrality data sorting by
degree centrality. In the TSC ERP implementation process, the high
degree of network centrality were dominated by members of IS
department which is responsible for important related work (such
as: demand planning, database design, training …etc.) during the
information system implementation process and play as an
important role in consulting relation network. Other members of
non-IT departments also have high network centrality, such as
members in C Business Group, D Business Group, ?nancial
department, and operating administration Department. Fig. 2
shows the get-help ties centered on employee WCM, who is staff
of C business group. It indicates that many users get advice from
WCM when they encounter some ERP related problems. The ERP
implementation should not ignore these key persons' position in
the corporate network. Through their in?uence in the network, the
related knowledge of ERP systems or operating procedures may
spread to all departments easily within the enterprise.
By the analysis of Network Centrality, we can further under-
stand members who have important in?uences in the ERP system
implementation process. Using UCINET 6, this study calculated
degree of centrality, closeness-centrality, betweenness centrality
and eigenvector centrality. Through these four values calculated by
this analysis, we understand high and low level of network cen-
trality, and to explore its in?uence on user participation in ERP
system implementation.
5.2. Measurement model
The measurement model was analyzed by SmartPLS. The psy-
chometric properties of the scales were assessed in terms of item
loadings, discriminant validity, and internal consistency. Item
loadings and internal consistencies (also known as composite
reliability) greater than 0.70 are considered acceptable (Fornell &
Larcker, 1981). From the factor analysis results, all the items
loaded highly (>0.70) on their respective construct (see Appendix
A). All the constructs also exhibited good internal consistency as
evidenced by their composite reliability scores, which were all
greater than 0.90 (see Table 3).
Discriminant validity was assessed by two criteria (Chin,
1998): (1) items should load more highly on the construct that
they are intended to measure than on other constructs (i.e.
loadings should be higher than cross-loadings) and (2) the square
root of the average variance extracted (AVE) should be larger than
the inter-construct correlations. Cross-loadings were computed
by calculating the correlations between latent variable's compo-
nent scores and the manifest indicators of other latent constructs
(Agarwal, Gupta, & Kraut, 2008; Chin, 1998). Without exception,
all items loaded more highly on their own construct than on
other constructs (see Appendix A). Also, by comparing the inter-
construct correlations and the square root of AVE (shaded lead-
ing diagonal), the square root of the AVE for each construct was
greater than 0.707 (i.e., AVE > 0.50) and also greater than the
correlations between the construct and other constructs, indi-
cating that all the constructs share more variance with their in-
dicators than with other constructs. Overall, the self-report
measurement instrument exhibited suf?ciently strong psycho-
metric properties to support our subsequent test of the proposed
structural model.
Table 1
Respondents background.
Background variables No. of samples Percentage
Sex Male 123 58.29%
Female 88 41.71%
Seniority Under 1 y 15 7.11%
1e3 y 66 31.28%
3e5 y 42 19.91%
5e7 y 40 18.96%
7e9 y 10 4.74%
Over 9 y 36 17.06%
Age 20e29 45 21.33%
30e39 116 54.98%
40e49 47 22.27%
50e59 3 1.42%
Job ExecutivesMid. Mgr. 18 8.53%
Low Mgr. 11 5.22%
Eng. 48 22.75%
Secretary 33 15.64%
Sales 34 16.11%
IT staff 49 23.22%
17 8.06%
Table 2
Top twenty users with high network centrality sorting by degree centrality.
Name Sex Age Department Work year Network centrality
Degree Closeness Betweenness Eigenvector
CYL F 30e39 IS Over 9 y 33.21 26.39 16.66 43.80
LLC M 30e39 IS 3e5 y 31.73 26.21 16.35 42.16
CCJ F 20e29 IS 1e3 y 30.63 26.08 16.82 40.69
YSC1 M 30e39 IS 1e3 y 25.46 26.06 11.51 38.44
TCH M 30e39 IS 1e3 y 23.25 25.26 6.26 36.63
TTP M 40e49 IS Over 9 y 21.40 25.00 12.11 24.28
HYT M 40e49 IS Over 9 y 20.30 25.47 6.81 32.14
CSW M 30e39 Operation 3e5 y 17.71 24.66 13.77 17.46
SWF M 30e39 IS 7e9 y 14.39 23.16 10.39 12.10
CJJ M 30e39 IS 5e7 y 12.18 23.44 4.04 16.87
KPC M 40e49 IS 3e5 y 10.70 23.92 3.17 17.53
CPS M 20e29 IS 3e5 y 10.70 23.34 2.92 11.98
WCC F 20e29 BG D 5e7 y 9.23 24.11 6.01 15.96
HWW F 20e29 Operation 3e5 y 8.12 23.40 2.58 14.18
CHH M 20e29 IS Under 1 y 7.01 23.48 1.60 16.17
WCM F 30e39 BG C 5e7 y 6.64 22.42 0.79 11.83
HKF F 30e39 Operation 5e7 y 5.90 23.57 0.85 12.68
LCC2 F 30e39 Finance Over 9 y 5.90 22.57 0.96 13.03
LSJ F 30e39 Operation Over 9 y 5.54 22.72 1.00 8.38
HCY1 F 20e29 IS 3e5 y 5.17 22.29 1.03 9.89
P.-H. Ju et al. / Asia Paci?c Management Review xxx (2016) 1e10 6
Please cite this article in press as: Ju, P.-H., et al., Model of post-implementation user participation within ERP advice network, Asia Paci?c
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5.3. Structural model
The PLS structural model and hypotheses were assessed by
examining path coef?cients (similar to standardized beta weights
in regression analysis) and their signi?cance levels. All of the con-
structs were modeled as re?ective. Following Chin (1998), boot-
strapping (with 500 resamples) was performed to obtain the
estimates of standard errors for testing the statistical signi?cance of
path coef?cients using t test.
Fig. 3 and Table 4 summarize the model-testing results. As for
Hypothesis 1, we ?nd that network centrality is positively
associated with usereIS relationship (t ¼3.67, p < 0.01). Hypothesis
2, which posits that network centrality would in?uence hands-on
activity, is supported (t ¼ 6.19, p < 0.01). As for Hypothesis 3, we
?nd that, network centrality is positively associated with commu-
nication activity (validating H
3
, t ¼7.11, p < 0.01). Hypotheses 4, 5, 6
posit that user participation would positively in?uence system use.
Hypothesis 4, which posits that usereIS relationship would in?u-
ence systemuse, is not supported (t ¼0.81). As for Hypothesis 5, we
?nd that hands-on activity is positively associated with system use
(t ¼2.58, p < 0.01). Hypothesis 6, which posits that communication
activity would in?uence system use, is supported (t ¼ 2.56,
p < 0.01). Hypotheses 7, 8, 9 posit that user participation would
positively in?uence user satisfaction. As for Hypothesis 7, we ?nd
that usereIS relationship is positively associated with user satis-
faction (t ¼2.11, p < 0.05). Hypothesis 8, which posits that hands-on
activity would in?uence user satisfaction, is supported (t ¼ 2.07,
p < 0.05). Hypothesis 9, which posits that communication activity
would in?uence system use, is supported (t ¼ 1.99, p < 0.05).
Network centrality explains 3%, 17% and 13% of the variances in
usereIS relationship, hands-on activity and communication activity
respectively. Explained variances for system use and user satisfac-
tion are 21% and 20%.
6. Conclusion
We theorized that the social network construct of network
centrality would in?uence individual system use and system
satisfaction through enhanced user participation in the post-
implementation of an ERP system. The empirical results sup-
ported the proposed model, with the social network construct
positively in?uencing user participation and thus leading to
improved system use and user satisfaction. This is the ?rst empir-
ical study to investigate post-implementation user participation
based on the majority of ERP users' network relationships. In
Fig. 2. Partial advice network diagram of employee WCM.
Table 3
Correlation analysis and composite factor reliability scores.
a
Variables Mean Std. C.R a NC UIS HOA COM USE SAT
NC N/A N/A 0.94 0.91 0.89
UIS 2.58 1.01 0.95 0.94 0.16* 0.84
HOA 2.12 1.01 0.97 0.96 0.40** 0.50** 0.88
COM 2.90 0.99 0.96 0.95 0.38** 0.40** 0.56** 0.81
USE 3.44 0.65 0.95 0.93 0.25** 0.27** 0.40** 0.37** 0.88
SAT 3.45 0.59 0.95 0.95 0.26** 0.29** 0.37** 0.39** 0.57** 0.80
NC ¼ Network Centrality; UIS ¼ UsereIS Relationship; HOA ¼ Hands-on Activity; COM ¼ Communication Activity; USE ¼ System Use; SAT ¼ User Satisfaction.
Signi?cant level: **p < 0.01.
a
Items on diagonal (shaded) represent the square root of the AVE scores.
Fig. 3. PLS results of path model.
P.-H. Ju et al. / Asia Paci?c Management Review xxx (2016) 1e10 7
Please cite this article in press as: Ju, P.-H., et al., Model of post-implementation user participation within ERP advice network, Asia Paci?c
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contrast to the participation of key users in the ERP implementation
stage, a greater number of users engaged in the modi?cation and
customization of ERP in the post-implementation period. Encour-
aging user participation during the post-implementation period is
a key to facilitating the exploitation and adaptation of ERP (Wagner
& Newell, 2007). For large numbers of users, it is bene?cial to un-
derstand the in?uence of social networks on user participation.
The results indicated that network centrality had signi?cant and
positive effects on user participation in the usereIS relationship,
hands-on activity, and communication activity. Previous studies
have suggested that a high degree of network centrality indicates
stronger power, and that such power can control resource ?ow in
the organization (Brass, 1984; Ibarra, 1993; Ibarra & Andrews,
1993), as well as affect an individual's willingness to participate
in the IS system post-implementation. In addition, when an IS
system is implemented, the power an individual possesses in
allocating and controlling resources represents the overall re-
sponsibility he or she bears for the project. A higher degree of
network centrality means stronger connections between the indi-
vidual and others; such a connection can become an effective
communication channel during post-implementation (Ahuja et al.,
2003; Sparrowe et al., 2001). Consequently, this study revealed that
the higher the degree of network centrality is, the closer the rela-
tionship the individual has with others; a person with a high
network centrality can effectively change and improve the behav-
iors of other people in the surrounding environment brought about
by the IS system and subsequently promote their willingness to
participate in the post-implementation stage. In addition, because
members with a high network centrality can effectively control
knowledge and resources, related knowledge can be disseminated
and transferred through these members' communication activities.
Hence, this study revealed that network centrality can substantially
facilitate user participation during the post-implementation pro-
cesses of an IS system.
Furthermore, the results also suggested that hands-on activities
and communication activities have considerable and positive ef-
fects on system use and user satisfaction. Some studies indicated
that user participation and communication in various stages of
system implementation could familiarize users with knowledge
about the system and facilitate the improvement of system quality
(McKeen & Guimaraes, 1997; Wagner & Newell, 2007). Further-
more, users do not truly understand the relevance and value of a
system in relation to themselves without having participated in or
communicated about the process (Cavaye, 1995), which in turn
promotes their motivation to actually use the system. Hence the
results of this analysis are consistent with previous studies in
?nding that hands-on participation and the communications of
associated users in an organization can effectively increase system
use and user satisfaction.
In improving business processes and work ef?ciency to create
strategically competitive advantages, many corporations have
started to implement ERP to assist with their daily business activ-
ities. However, as much as 90% of IS projects could not be
completed to the expected standard or within the expected time-
frame, particularly the introduction of an ERP system (Martin,
1998). IS system implementation may change original business
processes or organizational structures of a company, and conse-
quently it is prone to user resistance, which could lead to failure.
Hence, reducing user resistance and promoting user participation
in IS system implementation is crucial. This study found that per-
sonal networks in an organization could affect an individual's de-
cision to participate in IS system implementation. Users in the
network center play an essential role as a communication bridge in
an organization, and they possess more knowledge and power
related to the system's introduction. Therefore, corporations must
value users with a high degree of network centrality and use their
status in personal networks to disseminate the knowledge and
strengths of the ERP system. By doing so, other users can be
in?uenced to change their attitudes or behaviors toward the ERP
system, which can improve participation and promote the chance
of system success. According to a social network analysis, corpo-
rations can identify users who have strong in?uence in personal
networks, and then train them to become key users in the ERP
system's implementation. This can help solve the problems of other
users during the system's introduction and effectively extend
knowledge of system use to associated users, which in turn makes
other users willing to accept and use the system. Therefore, this
study suggests that corporations should effectively manage the
personal network in an organization to enhance the degree of user
participation during ERP system implementation.
Numerous studies have indicated that user participation
behavior is a crucial element in IS system implementation (Barki &
Hartwick, 1994a; McKeen & Guimaraes, 1997; Saleem, 1996; Wu &
Marakas, 2006). This study suggests that corporations must be able
to improve associated users' attitudes and opinions of the ERP
system during implementation, and promote user motivation to
participate in implementation. Effective communication can be
achieved only through the participation of associated users, and
such participation enhances the effects of the optimal use of the
new system and the daily work in an organization.
IS systems must be implemented through continuous commu-
nication and coordination among the project team and associated
users, and only in this way can an ERP system truly be integrated
with corporate processes. This study mainly considers strong tie
aspect of the social network theory for studying ERP post-
implementation. As individuals have diverse skills and knowledge
to implement and use ERP system, it is crucial to exchange knowl-
edge in this situation. However, Granovetter (1973) asserts that
strong ties among individuals facilitate information ?ows but weak
ties increase the likelihood of ?nding novel ideas. The innovative
aspect of weak ties may be another important issue to study ERP
implementation in future research. Besides, an increase in aptitude
Table 4
PLS results of path signi?cance.
Hypothesis Coef?cient t-Value Signi?cance R
2
Network centrality /usereIS relationship (H
1
) 0.18 3.67** Yes 0.03
Network centrality /hands-on activity (H
2
) 0.41 6.19** Yes 0.17
Network centrality /communication activity (H
3
) 0.36 7.11** Yes 0.13
UsereIS relationship /system use (H
4
) 0.06 0.81 No 0.21
Hands-on activity /system use (H
5
) 0.24 2.58** Yes
Communication activity /system use (H
6
) 0.22 2.56** Yes
UsereIS relationship /user satisfaction (H
7
) 0.15 2.11** Yes 0.20
Hands-on activity /user satisfaction (H
8
) 0.21 2.07** Yes
Communication activity /user satisfaction (H
9
) 0.17 1.99** Yes
Signi?cant level: **p < 0.05.
P.-H. Ju et al. / Asia Paci?c Management Review xxx (2016) 1e10 8
Please cite this article in press as: Ju, P.-H., et al., Model of post-implementation user participation within ERP advice network, Asia Paci?c
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enhances the willingness touse the system, andinturnreduces user
resistance. If corporations want toincrease the probability of system
success, they must focus on the degree of user participation and the
opinions raised by users after their participation.
Acknowledgments
This research is partially supported by the Ministry of Science
and Technology of R.O.C., Taiwan, under research grant 99-2410-H-
151-014-MY3. We are grateful to the comments provided by two
anonymous reviewers for their helpful comments on an earlier
version of this manuscript.
Appendix A
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Factor loadings and cross-loadings table.
Centrality UIS HOA COM System usage SAT
Betweenness 0.90 0.13 0.37 0.27 0.19 0.20
Closeness 0.74 0.13 0.30 0.31 0.24 0.18
Degree 0.97 0.17 0.40 0.32 0.26 0.25
Eigenvector 0.96 0.20 0.40 0.39 0.29 0.29
UIS1 0.15 0.75 0.42 0.38 0.22 0.24
UIS2 0.11 0.80 0.46 0.36 0.16 0.20
UIS3 0.06 0.84 0.41 0.34 0.19 0.27
UIS4 0.09 0.88 0.44 0.36 0.23 0.26
UIS5 0.15 0.87 0.41 0.33 0.24 0.33
UIS6 0.15 0.89 0.53 0.44 0.29 0.29
UIS7 0.22 0.89 0.51 0.42 0.29 0.30
UIS8 0.22 0.81 0.49 0.44 0.32 0.36
HOA1 0.39 0.51 0.91 0.58 0.37 0.36
HOA2 0.36 0.48 0.89 0.55 0.35 0.36
HOA3 0.37 0.54 0.92 0.60 0.39 0.38
HOA4 0.40 0.48 0.91 0.56 0.35 0.34
HOA5 0.35 0.55 0.92 0.59 0.39 0.41
HOA6 0.36 0.47 0.71 0.59 0.26 0.28
HOA7 0.37 0.48 0.91 0.54 0.42 0.39
HOA8 0.32 0.44 0.89 0.51 0.36 0.33
HOA9 0.34 0.39 0.84 0.48 0.38 0.31
COM1 0.28 0.29 0.43 0.74 0.24 0.22
COM2 0.25 0.31 0.50 0.84 0.34 0.37
COM3 0.32 0.32 0.47 0.85 0.34 0.31
COM4 0.34 0.30 0.50 0.86 0.33 0.32
COM5 0.28 0.35 0.47 0.79 0.25 0.25
COM6 0.37 0.44 0.54 0.87 0.38 0.37
COM7 0.38 0.47 0.54 0.88 0.38 0.35
COM8 0.40 0.45 0.55 0.83 0.40 0.39
COM9 0.17 0.36 0.53 0.73 0.26 0.19
COM10 0.19 0.37 0.55 0.76 0.28 0.22
COM11 0.17 0.39 0.53 0.75 0.30 0.26
COM12 0.23 0.41 0.56 0.77 0.32 0.25
USE1 0.25 0.22 0.33 0.32 0.90 0.55
USE2 0.20 0.27 0.36 0.33 0.92 0.56
USE3 0.32 0.24 0.39 0.37 0.83 0.54
USE4 0.20 0.28 0.33 0.28 0.88 0.50
USE5 0.23 0.30 0.41 0.43 0.87 0.56
SAT1 0.20 0.31 0.34 0.36 0.49 0.75
SAT2 0.15 0.25 0.30 0.30 0.44 0.82
SAT3 0.15 0.24 0.33 0.32 0.53 0.79
SAT4 0.09 0.18 0.23 0.23 0.42 0.78
SAT5 0.16 0.19 0.25 0.20 0.42 0.76
SAT6 0.18 0.24 0.27 0.21 0.45 0.78
SAT7 0.23 0.30 0.29 0.25 0.48 0.78
SAT8 0.31 0.27 0.35 0.34 0.53 0.84
SAT9 0.20 0.30 0.42 0.33 0.50 0.80
SAT10 0.18 0.30 0.34 0.24 0.46 0.76
SAT11 0.25 0.32 0.31 0.33 0.55 0.86
SAT12 0.33 0.33 0.35 0.38 0.58 0.85
The bold and italic numbers indicate the factor loadings on each construct.
UIS ¼ UsereIS Relationship; HOA ¼ Hands-on Activity; COM ¼ Communication
Activity; USE ¼ System Use; SAT ¼ User Satisfaction.
P.-H. Ju et al. / Asia Paci?c Management Review xxx (2016) 1e10 9
Please cite this article in press as: Ju, P.-H., et al., Model of post-implementation user participation within ERP advice network, Asia Paci?c
Management Review (2016),http://dx.doi.org/10.1016/j.apmrv.2015.11.001
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doc_165864917.pdf
Base on the social network theory, this study attempts to investigate whether the network centrality will
affect the user participation in ERP system post-implementation or not. In aspects of network centrality,
we used degree, closeness, betweenness and eigenvector as indicators to investigate the relationships
between individual network centrality and user participation. Thenwe further explore the impact of user
participation on system use and user satisfaction. We adopted the ERP post-implementation of TSC
Company as an example. The sample data has 211 questionnaires. Our empirical results show that
network centrality positively affects the three dimensions of user participation; hands-on activity and
communication activity positively affect system use; usereIS relationship, hands-on activity, and
communication activity positively affect user satisfaction. Through the lens of social network, we argued
that ERP user network plays an important role to influence user participation in post-implementation
period, which is critical for system use and user satisfaction.
Model of post-implementation user participation within ERP advice network
Pei-Hung Ju
a
, Hsiao-Lan Wei
b, *
, Chung-Che Tsai
c
a
Department of Business Administration, School of Management, National Kaohsiung University of Applied Science, Kaohsiung, Taiwan, ROC
b
Department of Information Management, School of Management, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC
c
Department of Software Application Development, ASUSTeK Computer Inc., Taipei, Taiwan, ROC
a r t i c l e i n f o
Article history:
Received 9 March 2015
Accepted 2 November 2015
Available online xxx
Keywords:
User participation
Social network
ERP post-implementation
Network centrality
a b s t r a c t
Base on the social network theory, this study attempts to investigate whether the network centrality will
affect the user participation in ERP system post-implementation or not. In aspects of network centrality,
we used degree, closeness, betweenness and eigenvector as indicators to investigate the relationships
between individual network centrality and user participation. Then we further explore the impact of user
participation on system use and user satisfaction. We adopted the ERP post-implementation of TSC
Company as an example. The sample data has 211 questionnaires. Our empirical results show that
network centrality positively affects the three dimensions of user participation; hands-on activity and
communication activity positively affect system use; usereIS relationship, hands-on activity, and
communication activity positively affect user satisfaction. Through the lens of social network, we argued
that ERP user network plays an important role to in?uence user participation in post-implementation
period, which is critical for system use and user satisfaction.
© 2016 College of Management, National Cheng Kung University. Production and hosting by Elsevier
Taiwan LLC. All rights reserved.
1. Introduction
Many researchers study the key factors of how to implement
enterprise resource planning (ERP) system successfully (Chou &
Chang, 2008; Chung, Skibniewski, & Kwak, 2009; Morton & Hu,
2008). These successful factors may broadly be classi?ed as hu-
man/organizational, technical, and economic ones (Chen, 2001;
Sarker & Lee, 2003). While each set of factors is important, there
appears to be a growing consensus among researchers that human
factors, more than technical or economic, are critical to the success
of ERP projects (Alvarez, 2008; Sarker & Lee, 2003). Sarker and Lee
(2003) suggest that empowering the team-members for self-
management and communication issues are seen as central to
success of an ERP implementation project. Salmeron and Lopez
(2010) indicate that encouraging the active participation of all
users involved in the process of post-implementation ERP systems
is essential in the success of the ERP maintenance. To deal with
technical complexity and overambitious demands associated with
ERP systems, user participation is important to mitigate risk (Amrit,
van Hillegersberg, & van Diest, 2013). Therefore, user participation
is an important factor when implementing the ERP system.
User participation refers to the favorable behaviors and activ-
ities that users perform in the systems development process to
promote ef?cient and effective implementation of ERP systems
(Bagchi, Kanungo, & Dasgupta, 2003; Barki & Hartwick, 1989; Ives
& Olson, 1984; Kawalek & Wood-Harper, 2002). When organiza-
tions plan to use an ERP system, a number of user representatives
participated in software package con?guration and there might
have a conceptual gap between developers and users (Barki, Rivard,
& Talbot, 2001; Kappelman, 1995; Markus & Ji-Ye, 2004). To close
the gap to ensure ERP systemimplementation success, it's essential
for organizations to handle user participation carefully (Dong-Gil,
Kirsch, & King, 2005; Markus, Axline, Petrie, & Tanis, 2000). User
participation can improve system quality by giving developers the
information they need to produce a high-quality design (Barki et al.,
2001; Byrd, Cossick, & Zmud, 1992; Markus & Ji-Ye, 2004). Besides,
user participation in change management activities such as plan-
ning or conducting training is much more likely to affect system
acceptance and use outcomes (Kappelman, 1995; McKeen &
Guimaraes, 1997; Yetton, Martin, Sharma, & Johnston, 2000). ERP
system is an integrated solution in an enterprise, which involves
internal work?ow within inter-departmental cooperation. The
* Corresponding author. Tel.: þ886 2 27303226; fax: þ886 2 27376777.
E-mail address: [email protected] (H.-L. Wei).
Peer review under responsibility of College of Management, National Cheng
Kung University.
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Asia Paci?c Management Review xxx (2016) 1e10
Please cite this article in press as: Ju, P.-H., et al., Model of post-implementation user participation within ERP advice network, Asia Paci?c
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communication and coordination in related users are extremely
important as well as the communicationwith consultants. With the
efforts in both sides, the implementation can be ensured to corre-
spond to the entire work?ow in the enterprise.
The timing issue of user participation over ERP lifecycle is
highlighted as an important but ignored dimension recently
(Wagner & Newell, 2007). As post-implementation success of ERP
is critical for adopting organizations in order to fully bene?t from
system's potential, user participation is extremely important at this
stage. During the implementation stage, only limited key users are
participated in the con?guration of ERP to help the system go live.
After the installation of an ERP system, a critical mass of users start
the exploitation and evaluation of the system and some uncon-
trolled problems may also appear. Post-implementation phase
including the stabilization, operation and extension of the ERP
system involves a large number of different users from different
functions and previously silent users may express their dissatis-
faction with the system, which will in?uence the acceptance of the
ERP system (Markus & Ji-Ye, 2004; Wagner & Newell, 2007).
Therefore, investigating post-implementation participation is crit-
ical for the system's survival and assimilation in the organization
because users themselves need situated learning through use to
?gure out what is best from ERP system for existing practices.
A person's behavior intention is in?uenced by his/her personal
relationship network in an organization (Sykes, Venkatesh, &
Gosain, 2009; Zagenczyk & Murrell, 2009). This impacts the
result of learning and knowledge exchange during the ERP post-
implementing process. Therefore, a concept of social network is
proposed to study the in?uences in different network relationship.
How to use the network to achieve the enterprise target has been
highly valued by the management because understanding an em-
ployee's network relationship is bene?cial to ?nd out the in?uen-
tial users during the process of ERP post-implementation. The
potential users have greater in?uences in drawing the participation
of other users and thus they indirectly enhance the possibility of
successful post-implementation. Many researches show that the
social network has signi?cantly in?uence in individual job perfor-
mance (Ahuja, Galletta, & Carley, 2003; Sparrowe, Liden, Wayne, &
Kraimer, 2001). More and more studies reveal the behavior in?u-
ence impacted by individual's network relationship (Sykes et al.,
2009; Zagenczyk & Murrell, 2009). The network relationship in
an organization has certain impact on user participation. Sykes
et al. (2009) indicated that the counseling network relationship
has signi?cant in?uence on system usage. Meanwhile, the network
relationship in?uences one's job involvement (Zagenczyk &
Murrell, 2009). Individual's network relationship is a key variable
in one's participation. During the post-implementation, the rele-
vant users will be impacted by the social network, and the
following behavior changes are key factors of successful post-
implementation.
As studies on the ERP post-implementation phase are still un-
derrepresented (Esteves & Boh orquez, 2007; Grabski, Leech, &
Schmidt, 2011) and the call for investigating post-implementation
user participation (Markus & Ji-Ye, 2004; Wagner & Newell,
2007), this research explains the in?uence of user participation and
the relationship of the successful ERP post-implementation, based
on the social network theory (Bonacich, 1972; Freeman, 1979) and
the user participation theory (Barki & Hartwick, 1994a; Hartwick &
Barki, 2001). It intends to understand the relationship of social
network, user participation and the success of system post-
implementation and to discover the role of social network in
post-implementation and in the enhancement of user participation
to accomplish the system post-implementation successfully.
Section one covers the relevant background literature. This is
followed by theoretical framework and hypotheses section and
then the methodology one. We then analyze the results and we
draw conclusions in the ?nal section.
2. Conceptual background
2.1. Social network
A social network can be de?ned as a relationship comprising a
series of persons, objects, and events; different networks can be
formed with the same elements because of different types of
relationship. In social network theory, these persons, objects, and
events are de?ned as actors or nodes. The relationships between
actors in a structural relationship and an individual actor in a
network have a strong in?uence on the behavior, perception, and
attitude of an individual or an entire organization (Knoke &
Kuklinski, 1982).
When a corporation introduces an IS system, network centrality
is one of the crucial elements; the corporation must invest
considerable resources during the introduction, which makes the
transmission and control of these resources highly valuable. The
knowledge, intentions, and behavior of using the newsystemis also
affected by the network (Sykes et al., 2009). Network centrality is
de?ned as “the scope of individual participation in the network
which facilitates information exchange among colleagues”
(Sparrowe et al., 2001). Knoke and Kuklinski (1982) indicated that
the interactions of numerous relationships, including the trans-
mission and receipt of information, exist in the process of contact
among individuals, and that the level of individual involvement can
be judged by the number of relationships.
Researchers consider network centrality an essential structural
attribute in social networks. Individuals situated in the network
center can control the ?ow of resources and related knowledge. An
individual is not affected by others; instead, he or she has in?uence
on individual power in an organization, as well as resource control
(Ibarra, 1993; Ibarra &Andrews, 1993). However, if the individual is
situated at a lower level of network centrality, he or she must rely
on others to pass on resources and knowledge and is subsequently
easily in?uenced by the environment (Freeman, 1979). Freeman
(1979) and Bonacich (1972) analyzed network centrality by using
four dimensions: degree, closeness, betweenness, and
eigenvectors.
In 1974, researchers started to apply social network concepts to
the technology innovation diffusion model of an organization
(Czepiel, 1974) and discovered that an informal communication
network within an organization can ease the adoption of a new
system. The network is also crucial to the IS system post-
implementation, as well as the transmission and transfer of
related resources and knowledge in the organization. Some studies
have indicated that the structures of a social network can affect the
transmission of valuable resources in an organization (Brass, 1984;
Ibarra, 1993). Work-related resources, such as work counseling and
strategic information, can be transmitted through a social network,
as can social recognition, discipline, and support (Sykes et al.,
2009). How knowledge and usage methods can be transferred to
users during the post-implementation process of an ERP system is
crucial. Informal personal networks play a key role in transferring
the knowledge about a new system. Hence, Sykes et al. (2009)
considered it dif?cult to accomplish the absorption and trans-
mission of professional knowledge about a new system within a
short timeframe; transferring knowledge among people with
similar training, backgrounds, and work characteristics is easier.
When an organization introduces a new IS system, it is more
effective to share and transmit knowledge of the new system by
using staff in the same department of the organization. In
P.-H. Ju et al. / Asia Paci?c Management Review xxx (2016) 1e10 2
Please cite this article in press as: Ju, P.-H., et al., Model of post-implementation user participation within ERP advice network, Asia Paci?c
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summary, the social network perspective in IS implementation has
become a prominent topic in recent years (He, Qiao, & Wei, 2009).
2.2. User participation
In the development of information systems, user participation
and user involvement are key success factors. Early studies have
indicated that user participation or involvement has positive effects
on the success of systems (Swanson, 1974). However, these early
studies did not clearly differentiate between user participation and
user involvement. Ives and Olson (1984) proposed that participa-
tion, including board behavior, activities, and responsibilities, refers
to users or system developers. Barki and Hartwick (1994a) de?ned
user participation as a series of operations and activities conducted
by users or their representatives during system development.
Compared with user participation, which is demonstrated by
the user's external behavior and activities, user involvement rep-
resents a user's inner subjective state of mind. According to early
studies, a user's state of mind affects his or her attitudes, satisfac-
tion, and intention to use a system. Furthermore, user participation
has an obvious positive in?uence on user involvement. Therefore,
actual participation in the form of behavior or activities during a
system's development may improve a user's state of mind; this in
turn affects the user's satisfaction and the extent of his or her
intention to use the system.
In the activities of user participation, some scholars have pro-
posed that participation should not be limited to only before sys-
tem implementation, but also afterwards. Before system
implementation, if the user clearly understands the relevance of
the system to him or her, it may increase the user's eagerness to
participate in the process of system development. After system
implementation, user satisfaction must be improved. The system
and its ?tness can be modi?ed through user participation to
improve user satisfaction (Wagner & Newell, 2007).
Recently, ERP studies have emphasized the importance of post-
implementation concerns and have suggested that user participa-
tion plays a critical role for the assimilation and business bene?ts of
ERP (Liu, Feng, Hu, & Huang, 2011; Staehr, Shanks, & Seddon, 2012;
Wagner & Newell, 2007). Wagner and Newell (2007) indicated
several factors inhibiting user participation during the initial
implementation phase, such as legacy thinking, pseudo participa-
tion, and motivation. Aligning ERP software with existing practices
is easier after actual implementation and through situated learning.
The sustained use of an ERP system is a critical component for
realizing its anticipated bene?ts. Liu et al. (2011) argued that the
business value of ERP cannot be fully realized until it is extensively
assimilated into business processes and individual-level assimila-
tion focuses on the understanding of ERP and the ability to use ERP
for non-routine tasks. Therefore, post-implementation engagement
is an effective method of increasing user interest and enhancing the
ability to exploit ERP, leading to increased system use and assimi-
lation (Wagner & Newell, 2007).
3. Theoretical framework and hypotheses
In this study, individuals in the network of relations within an
enterprise were the focal point of howan enterprise implements its
ERP system and how participation behavior arising from personal
network relationships in?uences the success of enterprise system
implementation. The four indicators of degree, closeness,
betweenness, and eigenvectors were used to de?ne the individual
within the enterprise network centrality. User participation was
divided into three parts: the relationship between users and in-
formation technology (IT) staff, actual participation in activities,
and communication activities. Finally, user satisfaction and system
use were used to measure the success of post-ERP implementation.
The theoretical research model is depicted as Fig. 1.
3.1. Network centrality and user participation
Network centrality is an essential aspect of research on social
networks (Ahuja et al., 2003; Sparrowe et al., 2001; Sykes et al.,
2009). It is de?ned as the scope of individual participation that
helps working partners exchange information (Sparrowe et al.,
2001). Network centrality is measured by the number of rela-
tional connections in an individual network. One study showed
that if individuals within an organization's network center, which
has more links, may have a high impact capacity (Freeman, 1979).
Scholars also believe that the degree of network centrality affects
individual performance within the organization (Ahuja et al.,
2003), work involvement (Zagenczyk & Murrell, 2009) and
resource control (Ibarra, 1993).
The relationship between users and IT staffs is de?ned as
development activities that re?ect the communication and in?u-
ence among users and IT staffs (Barki & Hartwick, 1994a). Some
studies have indicated that when the implementation of an infor-
mation system faces a problem, individuals search their network of
relations for a solution, not only to enhance their job performance
but also to have a major in?uence on the degree of participation in
information system implementation (Sparrowe et al., 2001; Sykes
et al., 2009). Thus, network centrality is key to the relationship
between users and IT staff. The degree of network centrality rep-
resents the linkage level for an individual in relation to others
within the organization, and shows the communication relation-
ship between the individual and related IT staff (Ahuja et al., 2003;
Sparrowe et al., 2001), as well as personal power within the orga-
nization (Ibarra, 1993; Ibarra & Andrews, 1993). It can in?uence
relationship building within an organization. Therefore, the
following hypothesis was proposed.
H
1
: Network centrality is positively associated with the rela-
tionship between users and IT staff in post-ERP implementation.
Brass and Burkhardt (1993) stated that employees with a higher
degree of network centrality have increased power within the or-
ganization. In addition, the personal closeness of network cen-
trality can represent the power of individuals within an
organization, and the power affects other people's views and per-
spectives in the network (Ibarra, 1993; Ibarra & Andrews, 1993;
Sparrowe et al., 2001). The in?uence or drive from center mem-
bers of the network affects whether an individual actually partici-
pates in decision-making in the new system (Sykes et al., 2009). In
addition, network centrality positively in?uences individual
Fig. 1. Research model.
P.-H. Ju et al. / Asia Paci?c Management Review xxx (2016) 1e10 3
Please cite this article in press as: Ju, P.-H., et al., Model of post-implementation user participation within ERP advice network, Asia Paci?c
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behaviors, and enhances the degree of participation for related
work (Zagenczyk & Murrell, 2009). Network centrality can affect
the actual behavior of users to pay for the process of information
system post-implementation. Therefore, the following hypothesis
was proposed.
H
2
: Network centrality is positively associated with actual
participation in hands-on activity in post-ERP implementation.
Communication activities are regarded as an essential part of
the process of information system implementation; the interactive
communication between users and the project team allows the
functions of information systems to ?t with individual daily work.
Hartwick and Barki (2001) explored the various dimensions of user
participation and de?ned communication activities as a crucial
aspect. Users exchange information through formal or informal
communication with other participants. As such, communication
activities have become a factor in post-implementation ERP.
Following social networks theory, an individual's degree of network
centrality can be regarded as an indicator for potential communi-
cation activities (Freeman, 1979). Through the degree of network
centrality, the interaction between individuals and other people in
organizations can be understood; it also represents the degree to
which individuals will participate in projects or related communi-
cation activities (Ahuja et al., 2003; Sparrowe et al., 2001). Users
related through an interactive network of communication within
an organization answer questions about information systems and
assist in the implementation process. Members with a high
network centrality act as a valuable bridge for promoting the use of
the system by others (Sykes et al., 2009) and the degree of work
participation (Zagenczyk & Murrell, 2009).
We present the following hypothesis:
H
3
: Network centrality is positively associated with the
communication activities in post-ERP implementation.
3.2. User participation and system use
Effective use of an information system is considered the main
determinant for enhancing organizational competitiveness and
productivity. System use is included in the six categories of IS
success in the model by DeLone and McLean (1992). It is mainly
used to determine the level of actual use of information system.
Studies have indicated that user participation can help users
develop ownership feelings for the ERP system, which strongly
in?uences their acceptance of the system(Barki &Hartwick, 1994b;
Barki, Pare, & Sicotte, 2008).
The relationship between users and developers is one of the
factors that affect the result of system implementation (Cavaye,
1995). This relationship is crucial because ERP systems may cause
comprehensive changes to the business process. Users review or
evaluate the work completed by information system staff such that
the system can meet actual work processes (Hartwick & Barki,
2001). This enhances their feelings of control, intimate knowl-
edge, and ownership of the ERP (Barki et al., 2008; Pierce, Kostova,
& Dirks, 2001). The feelings of possession toward an ERP can
effectively improve the willingness of users to use the system for
their work. Therefore, the following hypothesis was proposed.
H
4
: The relationship between users and IT staff is positively
associated with ERP system use in post-ERP implementation.
Studies have shown that actual participation in implementation
activities has a signi?cantly positive effect on the willingness to use
the system in the future (Wu & Marakas, 2006). Users with work-
related knowledge obtained through actual participation in
implementation activities can effectively reduce the gaps between
users and IS staff and increase the possibility to develop user-
friendly solutions. By participating in design activities, users
perceive the ERP system as much more relevant, useful, and
essential for their job (Barki et al., 2008). The literature on tech-
nology acceptance has suggested that a system with a higher level
of perceived usefulness leads to a higher degree of use; hence, users
that help design the ERP systemcan enhance the willingness to use
ERP after introducing the system(Kositanurit, Ngwenyama, &Osei-
Bryson, 2006; Saleem, 1996). Therefore, the following hypothesis
was proposed.
H
5
: Actual participation in hands-on activity is positively asso-
ciated with ERP system use in post-ERP implementation.
A successful ERP system must be reworked and continuously
improved to satisfy new or changed business processes, through a
series of post-implementation projects (McGinnis & Huang, 2007;
Rajagopal, 2002). In the post-implementation process, system-
related knowledge and information must be conveyed through
communication activities. Communication and learning among
users after implementation is critical. The knowledge created dur-
ing the implementation process is a valuable resource and should
be shared for the ultimate success of ERP (McGinnis & Huang,
2007). Education and training after the system goes live is one of
the channels of communication; however, this can distribute only
explicit knowledge. Tacit knowledge could be exchanged through
meetings, chat, discussion, and other socialization activities.
Communication activities allow users to absorb and learn ERP-
related knowledge, which can facilitate the willingness and abil-
ity to actively use the new system. Therefore, the following hy-
pothesis was proposed.
H
6
: Communication activities are positively associated with ERP
system use in post-ERP implementation.
3.3. User participation and user satisfaction
Previous studies have suggested that user participation in the
information system implementation process can improve user
satisfaction (Hwang & Thorn, 1999; Wu & Marakas, 2006). By
incorporating the expectancy discon?rmation, equity, and needs
theories, Au, Ngai, and Cheng (2008) indicated that user satisfaction
is a function of IS performance, IS performance expectations,
equitable work performance ful?llment, equitable relatedness
ful?llment, and equitable self-development ful?llment. Participa-
tion in the formal approval of speci?cations and the continuous
review of the system can improve control in the outcome of ERP in
the post-implementation stage and obtain the desired information
and system quality. After the daily situated learning of using the
ERP system, users gain con?dence with their outcome control to
obtain improved system performance. Participation activities may
also enhance psychological ownership of the ERP, thereby creating
feelings of control and power, and ful?lling the needs of relatedness
for end users (Au et al., 2008; Barki et al., 2008). In summary, user
participation should lead to a greater commitment to and a higher
value of resultant systems, ultimately leading to greater satisfaction
(McKeen, Guimaraes, & Wetherbe, 1994). Therefore, the following
hypothesis was proposed.
H
7
: The relationship between users and IT staff is positively
associated with user satisfaction in post-ERP implementation.
P.-H. Ju et al. / Asia Paci?c Management Review xxx (2016) 1e10 4
Please cite this article in press as: Ju, P.-H., et al., Model of post-implementation user participation within ERP advice network, Asia Paci?c
Management Review (2016),http://dx.doi.org/10.1016/j.apmrv.2015.11.001
User participation in activities related to system development
can improve the information systemto ?t the organization or work,
which has a signi?cant in?uence on user satisfaction (McKeen et al.,
1994; Wagner & Newell, 2007). In the post-implementation stage,
users explore ERP as implemented to identify the functionality
necessary for performing daily tasks and de?cient functionalities.
This exploration is a learning process that allows users to be more
competent with ERP features (Gallagher, Worrell, & Mason, 2012).
As users participate in activities to design extended functionality of
the system to align ERP with business needs, the experiential
knowledge of the system is enriched. Therefore, actual participa-
tion may increase user motivations to make the ERP system useful
for their jobs and enhance user absorptive capacities, leading to
higher levels of ERP assimilation during the post-implementation
stage (Liu et al., 2011). Satisfaction with the ERP system is
improved as it becomes more closely aligned with business needs.
We present the following hypothesis:
H
8
: Actual participation in hands-on activity is positively asso-
ciated with user satisfaction in post-ERP implementation.
Research has suggested that communication relations between
users and developers have a signi?cant in?uence on user satisfac-
tion (McKeen et al., 1994). Saleem(1996) con?rmed that users have
expertise relevant to the work. The interaction and the ability to
exchange information between users and IT staff can affect system
satisfaction through knowledge exchange and learning. Commu-
nication activities can transmit relevant knowledge and needs,
improve the quality of system outputs, and improve the ability to
meet user needs. To successfully manage the knowledge of ERP,
organizations must establish a knowledge-sharing community to
provide a common frame of reference for all ERP activities
(McGinnis & Huang, 2007). This common frame of reference is
exchanged, assimilated, and distributed through communication
activities among users, IS staff, and managers. As such, users and IS
developers can have a shared understanding of an ERP system,
leading to reasonable user expectations for the system (Saeed,
Abdinnour, Lengnick-Hall, & Lengnick-Hall, 2010). The increased
realization of expected bene?ts of ERP use has a great in?uence on
user satisfaction (Bhattacherjee, 2001). Therefore, we present the
following hypothesis:
H
9
: Communication activities are positively associated with user
satisfaction in post-ERP implementation.
4. Methodology
4.1. Data collection
The subject of this study is based on personal social networks
within an organization, users in the information system, and the
successful implementation of a system. A well-known domestic
company (hereinafter referred to as TSC) with an ERP system
implementation project was thus chosen for this study. TSC
developed a new WebERP system in 2006, which included the
following modules: distribution, production management, ?nance,
human resources management, and project management. This
new generation of online WebERP was expected to reduce paper
work, achieve fully electronic processes, and streamline ERP to
improve the ef?ciency of the enterprise. The ERP system imple-
mentation project is still undergoing maintenance and
improvement.
The total number of employees in TSC was approximately 400.
Through our contact with the relevant authorities to identify and
obtain ERP system implementation information, we initially
identi?ed approximately 300 people in TSC as users for the ERP
system implementation project, to whom we issued question-
naires. Out of 300 questionnaires, a total of 243 were returned,
leading to a return rate of 81%. Some respondents did not want to
disclose information for the personal networking questions, lead-
ing to 32 invalid or incomplete questionnaires. The total number of
valid questionnaires was 211, and the effective rate was 70.33%. The
respondents covered various departments and job functions, and
had worked for more than one year; thus, all respondents had a
certain degree of understanding of the ERP systemimplementation
(Table 1).
4.2. Measures
To measure network centrality, we used Freeman (1979) and
Bonacich's (1972) four-measure index: degree, closeness,
betweenness, and eigenvectors. Degree was the extent of inter-
action with other members of the network. Closeness represented
a person's freedom from dependence on other members of the
network. Betweenness gauged the extent which an employee is a
key intermediary, i.e., in a position to control communication or
information exchange. Eigenvector was associated with greater
network in?uence because it was highly depending on the con-
nections to well-connected employees. It is a recursive measure
in which a user's centrality is proportional to the sum of cen-
tralities of the users to which they are connected, weighted by
the strength of connection (Bonacich, 1972). An open-question
survey was used to ask each ERP user the following question
adapted from Sykes et al. (2009) and Zagenczyk and Murrell
(2009): “when implementing/using ERP, who will you get
advice and help for your system problems?” We asked re-
spondents to list one to ten persons including their name,
department, and weight (interaction degree, 1 ¼ low, 5 ¼ high).
These data were used to compute the four network centrality
aspects discussed earlier.
The user participation constructs were measured with items
developed by Hartwick and Barki (2001). We only indicated that
the project/system was ERP project/system. The relationship be-
tween users and IT staffs was de?ned as the interaction between
users and IT staffs during the information system implementation
project; eight questions were used to assess this measure. Actual
involvement in activities was de?ned as activities related to the
case actually involved during the information system imple-
mentation project; nine questions were used to assess this mea-
sure. Communication activity was de?ned as communication
circumstances among all relevant members during the informa-
tion system implementation project; 12 questions were used to
assess this measure (Hartwick & Barki, 2001). System usage was
de?ned as the performance changes caused by users actually
using the system after the information system went into pro-
duction; ?ve questions were used to assess this measure using
item developed by Park, Suh, and Yang (2007). User satisfaction
was de?ned as the user views and evaluation of the system after
the information system went into production; 12 questions were
used to assess this measure adapted from Doll and Torkzadeh
(1989).
5. Result
This study used social network and structural equation
modeling (SEM) analysis for data analysis. The study divided
analyzing process into three parts: the ?rst part calculated TSC
personal network centrality; second part assessed the reliability,
convergent validity and discriminant validity for measurement
model; the third part evaluated an overall structural model.
P.-H. Ju et al. / Asia Paci?c Management Review xxx (2016) 1e10 5
Please cite this article in press as: Ju, P.-H., et al., Model of post-implementation user participation within ERP advice network, Asia Paci?c
Management Review (2016),http://dx.doi.org/10.1016/j.apmrv.2015.11.001
5.1. Network centrality analysis
This study collected data of the advice network when the TSC
implement ERP to build up personal social networks. Table 2 de-
scribes the top twenty users' network centrality data sorting by
degree centrality. In the TSC ERP implementation process, the high
degree of network centrality were dominated by members of IS
department which is responsible for important related work (such
as: demand planning, database design, training …etc.) during the
information system implementation process and play as an
important role in consulting relation network. Other members of
non-IT departments also have high network centrality, such as
members in C Business Group, D Business Group, ?nancial
department, and operating administration Department. Fig. 2
shows the get-help ties centered on employee WCM, who is staff
of C business group. It indicates that many users get advice from
WCM when they encounter some ERP related problems. The ERP
implementation should not ignore these key persons' position in
the corporate network. Through their in?uence in the network, the
related knowledge of ERP systems or operating procedures may
spread to all departments easily within the enterprise.
By the analysis of Network Centrality, we can further under-
stand members who have important in?uences in the ERP system
implementation process. Using UCINET 6, this study calculated
degree of centrality, closeness-centrality, betweenness centrality
and eigenvector centrality. Through these four values calculated by
this analysis, we understand high and low level of network cen-
trality, and to explore its in?uence on user participation in ERP
system implementation.
5.2. Measurement model
The measurement model was analyzed by SmartPLS. The psy-
chometric properties of the scales were assessed in terms of item
loadings, discriminant validity, and internal consistency. Item
loadings and internal consistencies (also known as composite
reliability) greater than 0.70 are considered acceptable (Fornell &
Larcker, 1981). From the factor analysis results, all the items
loaded highly (>0.70) on their respective construct (see Appendix
A). All the constructs also exhibited good internal consistency as
evidenced by their composite reliability scores, which were all
greater than 0.90 (see Table 3).
Discriminant validity was assessed by two criteria (Chin,
1998): (1) items should load more highly on the construct that
they are intended to measure than on other constructs (i.e.
loadings should be higher than cross-loadings) and (2) the square
root of the average variance extracted (AVE) should be larger than
the inter-construct correlations. Cross-loadings were computed
by calculating the correlations between latent variable's compo-
nent scores and the manifest indicators of other latent constructs
(Agarwal, Gupta, & Kraut, 2008; Chin, 1998). Without exception,
all items loaded more highly on their own construct than on
other constructs (see Appendix A). Also, by comparing the inter-
construct correlations and the square root of AVE (shaded lead-
ing diagonal), the square root of the AVE for each construct was
greater than 0.707 (i.e., AVE > 0.50) and also greater than the
correlations between the construct and other constructs, indi-
cating that all the constructs share more variance with their in-
dicators than with other constructs. Overall, the self-report
measurement instrument exhibited suf?ciently strong psycho-
metric properties to support our subsequent test of the proposed
structural model.
Table 1
Respondents background.
Background variables No. of samples Percentage
Sex Male 123 58.29%
Female 88 41.71%
Seniority Under 1 y 15 7.11%
1e3 y 66 31.28%
3e5 y 42 19.91%
5e7 y 40 18.96%
7e9 y 10 4.74%
Over 9 y 36 17.06%
Age 20e29 45 21.33%
30e39 116 54.98%
40e49 47 22.27%
50e59 3 1.42%
Job ExecutivesMid. Mgr. 18 8.53%
Low Mgr. 11 5.22%
Eng. 48 22.75%
Secretary 33 15.64%
Sales 34 16.11%
IT staff 49 23.22%
17 8.06%
Table 2
Top twenty users with high network centrality sorting by degree centrality.
Name Sex Age Department Work year Network centrality
Degree Closeness Betweenness Eigenvector
CYL F 30e39 IS Over 9 y 33.21 26.39 16.66 43.80
LLC M 30e39 IS 3e5 y 31.73 26.21 16.35 42.16
CCJ F 20e29 IS 1e3 y 30.63 26.08 16.82 40.69
YSC1 M 30e39 IS 1e3 y 25.46 26.06 11.51 38.44
TCH M 30e39 IS 1e3 y 23.25 25.26 6.26 36.63
TTP M 40e49 IS Over 9 y 21.40 25.00 12.11 24.28
HYT M 40e49 IS Over 9 y 20.30 25.47 6.81 32.14
CSW M 30e39 Operation 3e5 y 17.71 24.66 13.77 17.46
SWF M 30e39 IS 7e9 y 14.39 23.16 10.39 12.10
CJJ M 30e39 IS 5e7 y 12.18 23.44 4.04 16.87
KPC M 40e49 IS 3e5 y 10.70 23.92 3.17 17.53
CPS M 20e29 IS 3e5 y 10.70 23.34 2.92 11.98
WCC F 20e29 BG D 5e7 y 9.23 24.11 6.01 15.96
HWW F 20e29 Operation 3e5 y 8.12 23.40 2.58 14.18
CHH M 20e29 IS Under 1 y 7.01 23.48 1.60 16.17
WCM F 30e39 BG C 5e7 y 6.64 22.42 0.79 11.83
HKF F 30e39 Operation 5e7 y 5.90 23.57 0.85 12.68
LCC2 F 30e39 Finance Over 9 y 5.90 22.57 0.96 13.03
LSJ F 30e39 Operation Over 9 y 5.54 22.72 1.00 8.38
HCY1 F 20e29 IS 3e5 y 5.17 22.29 1.03 9.89
P.-H. Ju et al. / Asia Paci?c Management Review xxx (2016) 1e10 6
Please cite this article in press as: Ju, P.-H., et al., Model of post-implementation user participation within ERP advice network, Asia Paci?c
Management Review (2016),http://dx.doi.org/10.1016/j.apmrv.2015.11.001
5.3. Structural model
The PLS structural model and hypotheses were assessed by
examining path coef?cients (similar to standardized beta weights
in regression analysis) and their signi?cance levels. All of the con-
structs were modeled as re?ective. Following Chin (1998), boot-
strapping (with 500 resamples) was performed to obtain the
estimates of standard errors for testing the statistical signi?cance of
path coef?cients using t test.
Fig. 3 and Table 4 summarize the model-testing results. As for
Hypothesis 1, we ?nd that network centrality is positively
associated with usereIS relationship (t ¼3.67, p < 0.01). Hypothesis
2, which posits that network centrality would in?uence hands-on
activity, is supported (t ¼ 6.19, p < 0.01). As for Hypothesis 3, we
?nd that, network centrality is positively associated with commu-
nication activity (validating H
3
, t ¼7.11, p < 0.01). Hypotheses 4, 5, 6
posit that user participation would positively in?uence system use.
Hypothesis 4, which posits that usereIS relationship would in?u-
ence systemuse, is not supported (t ¼0.81). As for Hypothesis 5, we
?nd that hands-on activity is positively associated with system use
(t ¼2.58, p < 0.01). Hypothesis 6, which posits that communication
activity would in?uence system use, is supported (t ¼ 2.56,
p < 0.01). Hypotheses 7, 8, 9 posit that user participation would
positively in?uence user satisfaction. As for Hypothesis 7, we ?nd
that usereIS relationship is positively associated with user satis-
faction (t ¼2.11, p < 0.05). Hypothesis 8, which posits that hands-on
activity would in?uence user satisfaction, is supported (t ¼ 2.07,
p < 0.05). Hypothesis 9, which posits that communication activity
would in?uence system use, is supported (t ¼ 1.99, p < 0.05).
Network centrality explains 3%, 17% and 13% of the variances in
usereIS relationship, hands-on activity and communication activity
respectively. Explained variances for system use and user satisfac-
tion are 21% and 20%.
6. Conclusion
We theorized that the social network construct of network
centrality would in?uence individual system use and system
satisfaction through enhanced user participation in the post-
implementation of an ERP system. The empirical results sup-
ported the proposed model, with the social network construct
positively in?uencing user participation and thus leading to
improved system use and user satisfaction. This is the ?rst empir-
ical study to investigate post-implementation user participation
based on the majority of ERP users' network relationships. In
Fig. 2. Partial advice network diagram of employee WCM.
Table 3
Correlation analysis and composite factor reliability scores.
a
Variables Mean Std. C.R a NC UIS HOA COM USE SAT
NC N/A N/A 0.94 0.91 0.89
UIS 2.58 1.01 0.95 0.94 0.16* 0.84
HOA 2.12 1.01 0.97 0.96 0.40** 0.50** 0.88
COM 2.90 0.99 0.96 0.95 0.38** 0.40** 0.56** 0.81
USE 3.44 0.65 0.95 0.93 0.25** 0.27** 0.40** 0.37** 0.88
SAT 3.45 0.59 0.95 0.95 0.26** 0.29** 0.37** 0.39** 0.57** 0.80
NC ¼ Network Centrality; UIS ¼ UsereIS Relationship; HOA ¼ Hands-on Activity; COM ¼ Communication Activity; USE ¼ System Use; SAT ¼ User Satisfaction.
Signi?cant level: **p < 0.01.
a
Items on diagonal (shaded) represent the square root of the AVE scores.
Fig. 3. PLS results of path model.
P.-H. Ju et al. / Asia Paci?c Management Review xxx (2016) 1e10 7
Please cite this article in press as: Ju, P.-H., et al., Model of post-implementation user participation within ERP advice network, Asia Paci?c
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contrast to the participation of key users in the ERP implementation
stage, a greater number of users engaged in the modi?cation and
customization of ERP in the post-implementation period. Encour-
aging user participation during the post-implementation period is
a key to facilitating the exploitation and adaptation of ERP (Wagner
& Newell, 2007). For large numbers of users, it is bene?cial to un-
derstand the in?uence of social networks on user participation.
The results indicated that network centrality had signi?cant and
positive effects on user participation in the usereIS relationship,
hands-on activity, and communication activity. Previous studies
have suggested that a high degree of network centrality indicates
stronger power, and that such power can control resource ?ow in
the organization (Brass, 1984; Ibarra, 1993; Ibarra & Andrews,
1993), as well as affect an individual's willingness to participate
in the IS system post-implementation. In addition, when an IS
system is implemented, the power an individual possesses in
allocating and controlling resources represents the overall re-
sponsibility he or she bears for the project. A higher degree of
network centrality means stronger connections between the indi-
vidual and others; such a connection can become an effective
communication channel during post-implementation (Ahuja et al.,
2003; Sparrowe et al., 2001). Consequently, this study revealed that
the higher the degree of network centrality is, the closer the rela-
tionship the individual has with others; a person with a high
network centrality can effectively change and improve the behav-
iors of other people in the surrounding environment brought about
by the IS system and subsequently promote their willingness to
participate in the post-implementation stage. In addition, because
members with a high network centrality can effectively control
knowledge and resources, related knowledge can be disseminated
and transferred through these members' communication activities.
Hence, this study revealed that network centrality can substantially
facilitate user participation during the post-implementation pro-
cesses of an IS system.
Furthermore, the results also suggested that hands-on activities
and communication activities have considerable and positive ef-
fects on system use and user satisfaction. Some studies indicated
that user participation and communication in various stages of
system implementation could familiarize users with knowledge
about the system and facilitate the improvement of system quality
(McKeen & Guimaraes, 1997; Wagner & Newell, 2007). Further-
more, users do not truly understand the relevance and value of a
system in relation to themselves without having participated in or
communicated about the process (Cavaye, 1995), which in turn
promotes their motivation to actually use the system. Hence the
results of this analysis are consistent with previous studies in
?nding that hands-on participation and the communications of
associated users in an organization can effectively increase system
use and user satisfaction.
In improving business processes and work ef?ciency to create
strategically competitive advantages, many corporations have
started to implement ERP to assist with their daily business activ-
ities. However, as much as 90% of IS projects could not be
completed to the expected standard or within the expected time-
frame, particularly the introduction of an ERP system (Martin,
1998). IS system implementation may change original business
processes or organizational structures of a company, and conse-
quently it is prone to user resistance, which could lead to failure.
Hence, reducing user resistance and promoting user participation
in IS system implementation is crucial. This study found that per-
sonal networks in an organization could affect an individual's de-
cision to participate in IS system implementation. Users in the
network center play an essential role as a communication bridge in
an organization, and they possess more knowledge and power
related to the system's introduction. Therefore, corporations must
value users with a high degree of network centrality and use their
status in personal networks to disseminate the knowledge and
strengths of the ERP system. By doing so, other users can be
in?uenced to change their attitudes or behaviors toward the ERP
system, which can improve participation and promote the chance
of system success. According to a social network analysis, corpo-
rations can identify users who have strong in?uence in personal
networks, and then train them to become key users in the ERP
system's implementation. This can help solve the problems of other
users during the system's introduction and effectively extend
knowledge of system use to associated users, which in turn makes
other users willing to accept and use the system. Therefore, this
study suggests that corporations should effectively manage the
personal network in an organization to enhance the degree of user
participation during ERP system implementation.
Numerous studies have indicated that user participation
behavior is a crucial element in IS system implementation (Barki &
Hartwick, 1994a; McKeen & Guimaraes, 1997; Saleem, 1996; Wu &
Marakas, 2006). This study suggests that corporations must be able
to improve associated users' attitudes and opinions of the ERP
system during implementation, and promote user motivation to
participate in implementation. Effective communication can be
achieved only through the participation of associated users, and
such participation enhances the effects of the optimal use of the
new system and the daily work in an organization.
IS systems must be implemented through continuous commu-
nication and coordination among the project team and associated
users, and only in this way can an ERP system truly be integrated
with corporate processes. This study mainly considers strong tie
aspect of the social network theory for studying ERP post-
implementation. As individuals have diverse skills and knowledge
to implement and use ERP system, it is crucial to exchange knowl-
edge in this situation. However, Granovetter (1973) asserts that
strong ties among individuals facilitate information ?ows but weak
ties increase the likelihood of ?nding novel ideas. The innovative
aspect of weak ties may be another important issue to study ERP
implementation in future research. Besides, an increase in aptitude
Table 4
PLS results of path signi?cance.
Hypothesis Coef?cient t-Value Signi?cance R
2
Network centrality /usereIS relationship (H
1
) 0.18 3.67** Yes 0.03
Network centrality /hands-on activity (H
2
) 0.41 6.19** Yes 0.17
Network centrality /communication activity (H
3
) 0.36 7.11** Yes 0.13
UsereIS relationship /system use (H
4
) 0.06 0.81 No 0.21
Hands-on activity /system use (H
5
) 0.24 2.58** Yes
Communication activity /system use (H
6
) 0.22 2.56** Yes
UsereIS relationship /user satisfaction (H
7
) 0.15 2.11** Yes 0.20
Hands-on activity /user satisfaction (H
8
) 0.21 2.07** Yes
Communication activity /user satisfaction (H
9
) 0.17 1.99** Yes
Signi?cant level: **p < 0.05.
P.-H. Ju et al. / Asia Paci?c Management Review xxx (2016) 1e10 8
Please cite this article in press as: Ju, P.-H., et al., Model of post-implementation user participation within ERP advice network, Asia Paci?c
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enhances the willingness touse the system, andinturnreduces user
resistance. If corporations want toincrease the probability of system
success, they must focus on the degree of user participation and the
opinions raised by users after their participation.
Acknowledgments
This research is partially supported by the Ministry of Science
and Technology of R.O.C., Taiwan, under research grant 99-2410-H-
151-014-MY3. We are grateful to the comments provided by two
anonymous reviewers for their helpful comments on an earlier
version of this manuscript.
Appendix A
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Factor loadings and cross-loadings table.
Centrality UIS HOA COM System usage SAT
Betweenness 0.90 0.13 0.37 0.27 0.19 0.20
Closeness 0.74 0.13 0.30 0.31 0.24 0.18
Degree 0.97 0.17 0.40 0.32 0.26 0.25
Eigenvector 0.96 0.20 0.40 0.39 0.29 0.29
UIS1 0.15 0.75 0.42 0.38 0.22 0.24
UIS2 0.11 0.80 0.46 0.36 0.16 0.20
UIS3 0.06 0.84 0.41 0.34 0.19 0.27
UIS4 0.09 0.88 0.44 0.36 0.23 0.26
UIS5 0.15 0.87 0.41 0.33 0.24 0.33
UIS6 0.15 0.89 0.53 0.44 0.29 0.29
UIS7 0.22 0.89 0.51 0.42 0.29 0.30
UIS8 0.22 0.81 0.49 0.44 0.32 0.36
HOA1 0.39 0.51 0.91 0.58 0.37 0.36
HOA2 0.36 0.48 0.89 0.55 0.35 0.36
HOA3 0.37 0.54 0.92 0.60 0.39 0.38
HOA4 0.40 0.48 0.91 0.56 0.35 0.34
HOA5 0.35 0.55 0.92 0.59 0.39 0.41
HOA6 0.36 0.47 0.71 0.59 0.26 0.28
HOA7 0.37 0.48 0.91 0.54 0.42 0.39
HOA8 0.32 0.44 0.89 0.51 0.36 0.33
HOA9 0.34 0.39 0.84 0.48 0.38 0.31
COM1 0.28 0.29 0.43 0.74 0.24 0.22
COM2 0.25 0.31 0.50 0.84 0.34 0.37
COM3 0.32 0.32 0.47 0.85 0.34 0.31
COM4 0.34 0.30 0.50 0.86 0.33 0.32
COM5 0.28 0.35 0.47 0.79 0.25 0.25
COM6 0.37 0.44 0.54 0.87 0.38 0.37
COM7 0.38 0.47 0.54 0.88 0.38 0.35
COM8 0.40 0.45 0.55 0.83 0.40 0.39
COM9 0.17 0.36 0.53 0.73 0.26 0.19
COM10 0.19 0.37 0.55 0.76 0.28 0.22
COM11 0.17 0.39 0.53 0.75 0.30 0.26
COM12 0.23 0.41 0.56 0.77 0.32 0.25
USE1 0.25 0.22 0.33 0.32 0.90 0.55
USE2 0.20 0.27 0.36 0.33 0.92 0.56
USE3 0.32 0.24 0.39 0.37 0.83 0.54
USE4 0.20 0.28 0.33 0.28 0.88 0.50
USE5 0.23 0.30 0.41 0.43 0.87 0.56
SAT1 0.20 0.31 0.34 0.36 0.49 0.75
SAT2 0.15 0.25 0.30 0.30 0.44 0.82
SAT3 0.15 0.24 0.33 0.32 0.53 0.79
SAT4 0.09 0.18 0.23 0.23 0.42 0.78
SAT5 0.16 0.19 0.25 0.20 0.42 0.76
SAT6 0.18 0.24 0.27 0.21 0.45 0.78
SAT7 0.23 0.30 0.29 0.25 0.48 0.78
SAT8 0.31 0.27 0.35 0.34 0.53 0.84
SAT9 0.20 0.30 0.42 0.33 0.50 0.80
SAT10 0.18 0.30 0.34 0.24 0.46 0.76
SAT11 0.25 0.32 0.31 0.33 0.55 0.86
SAT12 0.33 0.33 0.35 0.38 0.58 0.85
The bold and italic numbers indicate the factor loadings on each construct.
UIS ¼ UsereIS Relationship; HOA ¼ Hands-on Activity; COM ¼ Communication
Activity; USE ¼ System Use; SAT ¼ User Satisfaction.
P.-H. Ju et al. / Asia Paci?c Management Review xxx (2016) 1e10 9
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