PROMOTING UNCOMMON KNOWLEDGE USE WITHIN IS
DEPARTMENT: HUMAN RESOURCE MANAGEMENT
PERSPECTIVE
Shih-Yu Wang, Department of Information Management, National Sun Yat-Sen University,
Kaohsiung, Taiwan, R.O.C., [email protected]
Jack Shih-Chieh Hsu, Department of Information Management, National Sun Yat-Sen
University, Kaohsiung, Taiwan, R.O.C., [email protected]
Tung-Chin Lin, Department of Information Management, National Sun Yat-Sen University,
Kaohsiung, Taiwan, R.O.C., [email protected]
Yu-Wen Hung, Department of Information Management, National Sun Yat-Sen University,
Kaohsiung, Taiwan, R.O.C., [email protected]
Abstract
Employing new IT to react to external changes and developing IS effectively and efficiently are
critical for IS department in contemporary business environment. In order to solve wicked problems
that are never faced before, IS department needs to use knowledge uncommonly through twisting
current knowledge slightly or analogizing from other areas. In addition to understand its impact on
performance, this study also explores the antecedents of uncommon knowledge use from a human
resource management perspective. Specifically, we hypothesize that uncertainty avoidance culture,
communication, shared decision making, team style work design, and human resource policies are
critical antecedents of knowledge augmentation and adaptation, which in turns lead to better IS
performance. The results show that while knowledge adaptation can be enhanced by uncertainty
avoidance culture and communication, knowledge augmentation is a function of shared decision-
making, use of team, and innovation-based policies. The results serve as guidance for managers to
choose needed HRM practices to boost desired uncommon knowledge use style.
Keywords: Uncommon knowledge use, Human resource management practices, Information system
department.
1 INTRODUCTION
Nowadays technology and business environment changes rapidly. Organizations have to change their
business strategies, process, and structure frequently so that they can effectively use knowledge and
utilize decision-making strategies to cope with the changing environment (Jones & Mahon 2012).
External changes in the business context often lead to changes in user requirements of the information
system that developed by information system (IS) department (Lee & Xia 2005). Therefore, the IS
department has to have sufficient capability to respond to changing needs and help firms to achieve
their goals. For example, IS department should be able to employ new information technology (IT) to
react to external changes and develop IS effectively and efficiently. Given that IS development is a
knowledge intensive process, the final performance of ISD is a function of effective knowledge
management (Joshi et al. 2007; Ko et al. 2005; Patnayakuni et al. 2007; Pee et al. 2010).
Indeed, previous knowledge management studies have demonstrated that performance is related to the
extent to which organization can create, acquire, and apply knowledge effectively (Chang Lee et al.
2005; Choo 1996; Gold et al. 2001; Janz & Prasarnphanich 2003; Lee & Choi 2003). Early literatures
in knowledge management area emphasize the importance to store knowledge effectively and be able
to retrieve it when needed. However, under a turbulent environment, being able to retrieve and apply
existing knowledge may not be sufficient. Solutions generated through simply applying accumulated
experiences in the same way may not be sufficient to solve problems never facing before. Researchers
suggest that organizations need to acquire new knowledge from external (Cohen & Levinthal 1990;
Matusik & Hill 1998; Tsai 2001). The following studies therefore shift their focus to clarify the role
of knowledge acquisition, such as absorptive capacity (Jansen et al. 2005; Lichtenthaler 2009; Zahra
& George 2002). However, simply applying existing knowledge, accumulated within organization or
acquired from external, is not sufficient for organizations in such a turbulent environment. Recently,
researchers further highlight the need to utilize existing knowledge uncommonly, through twisting
current knowledge slightly or analogizing from other areas, in order to solve wicked problems to gain
advantage. Nag and Gioia (2012) classify the way to adopt uncommon knowledge use into two types:
knowledge adaption and knowledge augmentation. While the former refers to applying knowledge to
modify and improve specific operational activities the later is defined as criticizing what are known so
as to generate new understandings on problem solving.
Nag and Gioria (2012), through case studies, demonstrate the critical role of uncommon knowledge
use under a turbulent environment. Analogizing the same concept to IS area, IS department may also
need to use knowledge uncommonly to improve the development process and to create innovative
information systems. However, a lack of systematic analysis leaves this question unanswered.
Therefore, the first purpose of this study is to understand the impact of uncommon knowledge use on
the outcomes of IS department. Furthermore, if using knowledge uncommonly does allow IS
department to perform better, we are also interested in knowing the ways to encourage members to
use knowledge uncommonly within IS department. The drivers of behavior include motivation or
capability (Vroom 1964). Human Resource Management (HRM) practices are frequently adopted to
motivate or provide employees sufficient capability (Bowen & Ostroff 2004). For example, HRM
practices can foster innovation and improve firm’s ability to sustain competitive advantage
(Beugelsdijk 2008; Gupta & Singhal 1993). However, even though past studies have demonstrated the
relationship between HRM practices and outcome variables, how effectively HRM practices can lead
to better outcomes (such as innovation) in such a turbulent environment is not clear. We suspect that
HRM practices may motivate or provide employees capability to use knowledge uncommonly.
Therefore, the second purpose of this study is to understand what HRM practices can enhance the
performance of IS department, through promoting uncommon knowledge use within the department.
Through achieving the above purposes, this study contributes to knowledge management literature by
highlighting the importance of uncommon knowledge use and illustrating ways to enhance it.
Furthermore we also contribute to HRM literatures by showing how effective HRM practices can
enhance unit performance indirectly through promoting uncommon knowledge use.
This paper is organized as follows. In the next section, we introduce uncommon knowledge use and
the role of HRM practice to two modes of uncommon knowledge use. In the third section, we describe
the method used to collect data and examine the proposed model. The fourth section presents the
analysis results. Last, conclusion and implication are provided.
2 LITERATURE REVIEW
2.1 Effectiveness of IS department
Contemporary business environment requires effective IS department to be innovative while
maintaining sufficient performance. One the one hand, the dramatic change of information technology
and economic make being innovative as a critical factor for organizations to success in the
competitive environment (Cardozo et al. 1993; Frambach & Schillewaert 2002). IS department often
need to introduce new technology quickly to accommodate the turbulent environment. Since
organizations often need to employ new technologies to empower their business function and increase
their competitive capability (Dewett & Jones 2001; Sambamurthy et al. 2003), being innovative
therefore refers to implementing new IT, adopting new methodology, or developing new IS to enable
new product or service or improve business operation.
On the other hand, the performance of IS department is defined as the extent to which IS department
can plan, develop, and operate information system effectively and efficiently. IS department is
responsible for developing or implementing information system to support organization operation, e.g.
to provide useful information that can solve organization’s business problem and improve the
efficiency and effectiveness of decision-making. However, the variation in the business context often
leads to changes in user requirements of the information system that is developed or implemented by
IS department. High failure rate of IS/IT projects is one significant issue in IS area and enhancing IS
department’s performance is therefore cannot be neglected.
2.2 From Common to Uncommon Knowledge Use
Insufficient knowledge has been identified as one critical problem in information system (IS)
development (Sakthivel 2007). IS department performance suffers when needed capability cannot be
constructed because of lacking sufficient knowledge resources (Nelson & Cooprider 1996).
Effectively acquiring, storing, and retrieving knowledge has been emphasized by knowledge
management literatures (Alavi & Leidner 2001; Nemati et al. 2002). Recent studies further highlight
the need to acquire needed knowledge from external (Cohen & Levinthal 1990; Matusik & Hill 1998;
Tsai 2001). However, Nag and Gioia (2012) pointed out that many firms feel no interest in generate
novel knowledge generally, but only focus on following what they used to do in the past and
maintaining the status quo. For example, firms prefer to continue with current approach even though
there are other more efficient ways to do things. Those firms value knowledge mainly for maintaining
responsiveness to current customers. Nag and Gioia referred this situation as common knowledge use.
According to Nag and Gioia (2012), strategic leaders have to transform common knowledge into
uncommon knowledge to create distinctive capabilities and sustain competitive advantage. They
further proposed two modes of uncommon knowledge use: knowledge augmentation and knowledge
adaptation. Knowledge adaptation emphasizes on utilize existing knowledge to figure out new
solution to modify or improve the process of specific operational activities. Knowledge augmentation
encourages employees to question existing knowledge to generate new understanding for future
activities. The process of information system development is knowledge intensive and it is critical to
acquire knowledgeable IS developers for effective system development and implementation (Tesch et
al. 2009). In addition, there is no two identical projects within IS department. Members need to
generate effective solutions for various problems. Since many problems are unique, IS department
therefore need to use knowledge uncommonly to improve the development process and to create
innovative information systems. However, limited efforts in IS area have been entered to understand
the role of uncommon knowledge use. The goal of this study is therefore to introduce two types of
uncommon knowledge use and explore their impact on the outcomes of IS department.
2.3 Human Resource Management Practices
The importance of employing effective HRM practices has long been emphasized in organization
studies. For example, many studies investigate the relationship between HRM practices and firm
performance (e.g. Becker & Huselid 2006; Boselie et al. 2005; Collins & Clark 2003; Evans & Davis
2005) or innovative outcome (e.g. Beugelsdijk 2008; Chen & Huang 2009; Oke et al. 2012). Some
scholars also explore the impact of HR practices on knowledge sharing (e.g. Cabrera & Cabrera 2005;
Collins & Smith 2006). While few studies attempt to explore the link between HRM practices and
performance or innovative outcome (Laursen & Foss 2003), limited effort has been entered to
understand what transfers the effect of HRM to outcome variables. Wright et al. (2001) suggested that
people management practices impact the knowledge creation, transfer, and integration of firms. We
believe that effective HRM practices can improve the performance of IS department through
promoting uncommon knowledge use. Managers can use effective HRM practices to create an
environment that encourage members to use knowledge uncommonly. In this study, we introduce
common HRM practices, including uncertainty avoidance culture, communication, shared decision-
making, work design (e.g. use of team), and innovation-based policies as the factors impacting
uncommon knowledge use.
Given the importance of being innovative and having high performance, this study addresses these
issues from a knowledge perspective. Specifically, we propose that different modes of uncommon
knowledge use can help IS department to utilize their expertise creating more effective performance
and innovative solutions. The research model is shown in Figure 1.
Figure 1. Research Model
HRM Practices Uncommon
Knowledge Use
IS Department
Effectiveness
Innovation-based
Policy
Communication
Shared DM
Work Design
(Use of Team)
Uncertainty
avoidance
Adaptation
Augmentation
Performance
Innovation
3 HYPOTHESIS DEVELOPMENT
3.1 From Uncommon Knowledge Use to Outcome
3.1.1 Knowledge Adaptation
Knowledge adaptation is a way to use knowledge which can be described as an ability to apply
knowledge to modify and improve specific operational activities (Nag & Gioia 2012). Knowledge
adaptation emphasizes “tweaking” knowledge already known to create novel solutions to specific
problems but not innovation. According to literature, with accumulated knowledge, an IS department
can draw from its experiences to quickly figure out what need to do to match organization’s objective
as firm’s strategy changing. However, performance remains the same if only applying the same
solution on the same problems. Therefore, Nag and Gioia proposed that, strategic leaders should focus
on how to tweak existing knowledge so as to improve operational efficiency. This implies that, by
keeping tweaking existing knowledge (knowledge adaptation), IS department continuously refines its
existing resources and processes of daily work. As an outcome, better performance can be expected.
Thus, we hypothesized:
H1: Knowledge adaptation has a positive impact on performance.
3.1.2 Knowledge Augmentation
Different from knowledge adaptation focuses on solving the same problem with slightly tweaked
knowledge, knowledge augmentation style uncommon knowledge use encourages members of a firm
to reflect upon, criticize, questioning what they have known, and generate new understandings to
solve problems (Nag & Gioia 2012). Knowledge augmentation style uncommon knowledge use
doesn’t focus on a particular problem but analyse problems to figure out how these solutions apply to
other problems. It emphasizes on using existing expertise and skills of the firm to develop new
understandings and principles for future action to benefit the firm’s competitiveness. Based on these
experience, the members of IS department can quickly apply the solution to similar situation. Then,
they can solve problem more effectively and efficiently during the development or implementation.
Therefore, we proposed:
H2a: Knowledge augmentation has a positive impact on performance.
For example, managers who choose knowledge augmentation as their strategy for developing
uncommon knowledge believe that new technological knowledge enabled them to find new insights
and develop a richer understanding of customer needs. In a rapidly changing environment, IS
department has to respond to the changing business strategy and user requirements effectively. While
some problems are predictable, some problems are wicked and unpredictable at all. It is not likely for
IS department to only tweak existing knowledge slightly to solve those problem never faced before.
Instead, innovative approaches are needed. Members should challenge what have known and develop
unique insights. They can apply these ideas to other problems in the future and meet changing user
needs more easily. Since members are encouraged to challenge existing knowledge, they are more
likely to generate some novel insights during this process and also be more willing to adapt new
technologies or new ways to perform work. With effective knowledge augmentation, IS department
can then be able to improve the ability to support the organizational strategy. Therefore, we proposed:
H2b: Knowledge augmentation has a positive impact on innovation.
3.2 From Human Resource Management Practices to Uncommon Knowledge Use
3.2.1 Uncertainty avoidance culture
Members in a society with uncertainty avoidance culture prefer to work through rules, budgets, and
standard operating procedures (Shane et al. 1995). The company with high uncertainty avoidance
culture invest more time and effort on planning and designing their program (Javidan et al. 2005). In
our context, culture of department has significant impact on the intention to change. If an IS
department has clear norm and procedure for employees to follow, employees are constrained with
standard operational procedure to avoid risks. The members of IS department will focus on the
existing process, hence, we proposed:
H3a: Uncertainty avoidance culture is positively related to knowledge adaptation.
On the other hand, members are more willing to break the rules and norms to innovation in the society
with uncertainty accepting culture (Shane et al. 1995). Javidan et al. (2005) also indicated that the
company with low uncertainty avoidance culture is more willing to explore opportunities to adapt
quick changes and develop new ideas. In other words, employees in the IS department with
uncertainty avoidance culture are not allowed to question existing knowledge and unlikely to change
and innovate as well. Therefore, we proposed:
H3b: Uncertainty avoidance culture is negatively related to knowledge augmentation.
3.2.2 Communication
Smith and Rupp (2002) define communication as “human interaction through oral conversations and
the use of body language” and considered that communication is fundamental in encouraging
knowledge transfer. Communication can be classified into two types: formal and informal
communication. Formal communication refers to communication that flows through written modes,
like official meetings, manuals and procedure and rule books. On the other hand, informal
communication is based on social relationship among employees. Employees can share work-relevant
information and create collaboration opportunities outside the formal channels (Mohr & Nevin 1990;
Smith et al. 1994). In this study, we primarily focus on informal communication among IS department
members. Informal communication can facilitate the knowledge flows among members (Smith et al.
1994). Frequent informal communication between department members enables members to learn
from others and exchange ideas and information with each other. Moreover, informal communication
can facilitate the collaborative work between members and further figure out more effective solution.
Therefore we proposed:
H4a: Communication is positively related to knowledge adaptation.
Through the process of communication, the members of the IS department can build a sharing belief
and express new ideas to increase the quality of knowledge creation (Henderson et al. 1997;
Patnayakuni et al. 2007). Senge (1997) also proposed that organizational knowledge is created
through communication of individual learning among co-workers. The communication among
members can arouse them to find the problem of process and generate new ideas. Therefore, we
proposed:
H4b: Communication is positively related to knowledge augmentation.
3.2.3 Shared-decision making
Shared decision making refers to “seeking team members’ input in decision making” (Patnayakuni et
al. 2007). Shared decision making has effect on uncommon knowledge use for the following two
reasons. First, previous studies have indicated that employees are more like to accept the decision if
they are involved in the decision making process. Employees feel that they are recognized by the
organization when involving in decision making. Employees also sense more responsibilities toward
the outcomes if they are included in the decision making process (Driscoll 1978). By viewing
themselves as critical members in the department, employees are more willing to spend efforts and,
more importantly, adjust themselves to reach a better outcome. So they may pay more attention on
how to improve operational efficiency. Therefore, we proposed:
H5a: Shared-decision making is positively related to knowledge adaptation.
Second, in the process of shared-decision making, members have to collect various perspectives in
order to make more comprehensive decision and get better performance. This action would encourage
members to understand others’ expertise and share their knowledge with each other (Patnayakuni et al.
2007). Thus, empowering the members of department to make decision increase opportunities and
need of knowledge sharing to solve problems (Srivastava et al. 2006). They need to expand their
knowledge and acquire new skills. Knowledge creation and innovation are more likely to result if
team members are allowed to make decision, solve problem, and identify opportunities by themselves
(Bligh et al. 2006). Therefore we proposed:
H5b: Shared-decision making is positively related to knowledge augmentation.
3.2.4 Teamwork Design
Teamwork design refers to use teams for performing activities of information system development
(Patnayakuni et al. 2007). Using team as work design provides members of department opportunities
to work closely with others. Teamwork is a process to integrate individual knowledge into collective
knowledge and realize the value of integrated knowledge (Okhuysen & Eisenhardt 2002). An
information system team usually includes members from different department or expertise, such as
users, programmers, and project managers. Since each member has different background, they have
their own opinion and viewpoint to understand the existing process. They may find different problems
that should be solved based on their unique background. Therefore, we proposed:
H6a: Teamwork design is positively related to knowledge adaptation.
The use of teams can not only bring better use of local knowledge, but also be positively related to
innovation performance (Laursen & Foss 2003). Integrating individual’s perspectives and unique
skills of team members into collective knowledge of team can contribute to team creativity – using
different ways to develop information systems (Tiwana & Mclean 2005). So the use of team can
integrate knowledge of team members to create more value and innovation. Thus, we hypothesized:
H6b: Teamwork design is positively related to knowledge augmentation.
3.2.5 Innovation-based Policies
Empirical studies have shown that including “being innovative” as a requirement in recruitment,
compensation, and promotion of employees are important to promote innovations in firms (Atuahene‐Gima 1996; Khazanchi et al. 2007). In this study, we move further and argue that innovation-based
policies, such as hiring creative employees and rewarding innovative initiates, are expected to have
positive impacts on uncommon knowledge. The policies allow organization to successfully hire
employees who have required expertise to solve difficult problems and find novel ideas (Amabile
1998; Seijts & Latham 2005). Therefore, we proposed:
H7a: Innovation-based Policies is positively related to knowledge adaptation.
Rewarding and recognizing being innovative encourage employees to generate new ideas, break rules
(Khazanchi et al. 2007), and also motivate employees’ willingness to achieve innovative outcomes
(Seijts & Latham 2005). The innovation-based HR policies are also likely to facilitate an innovative
organizational culture (Oke et al. 2012). Specific policies foster the climate, such as psychological
safety, that drives employees to learn and be innovative (Edmondson 1999). Individuals are more
willing to challenge existing process and try out new ideas. Therefore, we proposed:
H7b: Innovation-based Policies is positively related to knowledge augmentation.
4 RESEARCH METHOD
4.1 Data Collection
We conducted a survey to examine the proposed hypotheses. The target sample of this study is the
manager of IS department. The data were collected from the members of the Information
Management Association (IMA) in Taiwan. IMA is an association aims to improving IT usage and
enhancing communication among IS professionals. Members of this organization are either IS seniors
or IS manager. First, we contacted members of the IMA to introduce the purpose of this study and
obtain their willingness to participate. A total of 750 survey packages were then sent to managers who
agree to participate. We received 133 survey packages, yielding a valid response rate of 17.73%.
Table 1 provides the detailed information.
Variables Categories # % Variables Categories # %
Industry type Information
Technology
47 35.3 # of company
employee
<30 15 11.3
Financial 2 1.5 30-50 7 5.3
Manufacturing 39 29.3 50-100 11 8.3
Service 8 6.0 100-500 26 19.5
Medical 13 9.8 500-1000 15 11.3
Hospitality 1 0.8 1000-5000 26 19.5
Retailing 1 0.8 >5000 33 24.8
Government 10 7.5 # of IS employee <5 21 15.8
School 9 6.8 5-10 18 13.5
Others 3 2.3 10-15 15 11.3
Position Senior member 62 46.6 15-20 14 10.5
Manager 20 15 20-50 14 10.5
Senior manager 12 9 50-100 12 9
Administrator 38 28.6 >100 39 29.3
Others 1 0.8
Table 1. Sample demographics (N=133)
4.2 Constructs and Measurement
All constructs of our research model were measured using multiple items. Most of measurement items
were adapted from past studies. Due to the research of Nag and Gioia (2012) was conducted by
interview, the measurement items of adaptation and augmentation were developed by the authors. The
questionnaire adopted Likert scales ranging from 1 (strongly disagree) to 7 (strongly agree). The
definitions of the constructs are shown in Table 2.
Construct Definition Source of items
Performance of IS
department
the efficiency of IS department to develop and
implement information system
Adapted from DeLone and
McLean (1992);
Ravichandran and
Lertwongsatien (2005)
Innovation the extent to innovation activities of IS
department
Song et al. (2006)
Knowledge adaptation the mode of uncommon knowledge use that
focuses on applying knowledge to modify and
improve specific operational activities
Developed by authors
Knowledge augmentation the mode of uncommon knowledge use that
represents an orientation toward using existing
expertise and skills to reflecting upon, critiquing,
and questioning for problem solving and
generating new insights
Developed by authors
Uncertainty avoidance the extent that the members of a culture feel
threatened by uncertain or unknown situations
Hwang (2005)
and try to avoid them
Communication the extent of informal interaction among members
of IS department
Patnayakuni et al. (2007)
Shared decision-making sharing of decision-making authority among IS
employee
Patnayakuni et al. (2007)
Work design use of teams for ISD activities Patnayakuni et al. (2007)
Innovation-based policy the extent to which a firm adopts people-focused
policies including recruitment and selection, and
reward systems that foster the development of
innovation
Oke et al. (2012)
Table 2. Construct definition and source of items
4.3 Common Method Variance
Common method variance (CMV) might be a concern in this study, because both independent and
dependent variables are collected simultaneously from the same respondent. We implemented the
Harman’s single factor to ensure there was no significant method effect on the predefined causal
relationship. The result shows that the first factor explains 16.52% of variance through the exploratory
factor analysis process. Besides, we followed Liang et al. (2007) to test the impact of common method
variance in the PLS model. There are 33 indicators and only 6 method factor loadings are significant.
The summation of substantively explained variance of the indicators is 25.1, while the average
method based variance is 0.46. The ratio of substantive variance to method variance is approximately
54:1. Therefore, CMV is unlikely to be a problem in this study.
4.4 Reliability and Validity
We used PLS (Partial Least Squares) to evaluate the item reliability, convergent validity, and
discriminant validity of measurement model. The reliability was ensured through composite reliability,
Cronbach’s alpha and factor loading. Convergent validity should be examined by item-to-total
correlation (ITC), composite reliability, and average variance extracted (AVE) by constructs (Fornell
& Larcker, 1981). For discriminant validity, the correlation between construct pairs should be lower
than 0.90 and the square root of AVE should be higher than the inter-construct correlation coefficients
(Fornell & Larcker 1981). All validity requirements are met, as shown in Tables 3 and 4. Table 4
shows the descriptive statistics.
Constructs Items Loadings ITC Uncertainty
avoidance
culture
Alpha: 0.91 ;
AVE:0.84 ;
CR:0.94
It is important to have job requirements and instructions spelled
out in detail so that employees always know what they are
expected to do.
0.930 0.828
Rules and regulations are important because they inform
employees what the organization expects of them.
0.910 0.807
Standard operating procedures are helpful to employees on the
job.
0.912 0.802
Communication
Alpha: 0.85 ;
AVE:0.76 ;
CR:0.91
There is extensive informal communication among IS employees
at the same level.
0.865 0.675
There is extensive informal communication among IS employees
at different level.
0.908 0.773
There is extensive informal communication between IS
employees and employees in other departments.
0.848 0.691
Shared decision
making
Alpha: 0.87 ;
AVE:0.80 ;
CR:0.92
Participative decision-making is broadly used in these
development projects.
0.916 0.769
Decision-making authority rests with managers as opposed to
development staff. (R)
0.878 0.744
Joint-decision making by managers and analysts/programmers is
the norm in our ISD.
0.884 0.758
Work design - All projects are managed by autonomous teams. 0.832 0.594
team
Alpha: 0.78 ;
AVE:0.69 ;
CR:0.87
System development is team based. 0.873 0.678
Project team performance is evaluated rather than individual
performance.
0.794 0.576
Innovation-
based Policies
Alpha: 0.94 ;
AVE:0.80 ;
CR:0.95
Our human resource policies support a culture of innovation. 0.870 0.784
The rewards and recognition systems encourage innovation. 0.877 0.811
Innovation is a key criterion in our recruitment and selection
process.
0.939 0.899
Innovation forms part of our training and development programs. 0.907 0.851
Clear innovation targets are set for all employees. 0.868 0.801
Knowledge
augmentation
Alpha: 0.84 ;
AVE:0.76 ;
CR:0.91
We encourage everyone to question what they think they know,
to generate new understanding.
0.897 0.680
We analyze problems to figure out how solutions apply to other
problems.
0.875 0.756
We use new technical knowledge to find unique insights. 0.844 0.690
Knowledge
adaptation
Alpha: 0.78 ;
AVE:0.61 ;
CR:0.86
We capable of refining and extending our existing knowledge
and technologies to enhance the efficiency of firm.
0.743 0.476
We usually change the operation processes (development,
implementation, maintenance process) we use slightly to gain
better performance.
0.870 0.694
We regularly recombine and integrate existing technologies in
new products or services process.
0.798 0.639
Our innovation comes through small steps rather than giant
leaps.
0.691 0.542
Performance
Alpha: 0.92 ;
AVE:0.76 ;
CR:0.94
Information quality providing by our IT department has met our
firm’s objectives
0.865 0.772
The quality of information system developing or implementing
by our IT department has met our firm’s objectives.
0.883 0.816
The efficiency of developing or implementing information
system by our IT department has been successful.
0.876 0.806
The efficiency of introducing information system by our IT
department has been successful.
0.855 0.786
The efficiency of maintaining information system by our IT
department has been successful.
0.866 0.776
Innovation
Alpha: 0.89 ;
AVE:0.76 ;
CR:0.93
The overall performance of developing innovative information
system program has met our objectives.
0.819 0.703
From an overall profitability standpoint, implementing new
information system program has been successful.
0.888 0.779
We successfully use innovative method to plan and manage
information systems and launch novel development process.
0.855 0.748
We successfully use innovative information technology to
support business operations.
0.911 0.814
Note: ITC-Item-Total Correlation
Table 3. The results of factor analysis
Correlation matrix
Mean Std M3 M4 INN IBP SDM PE WD AD AUG COM UAC
INN 4.19 1.404 -0.291 -0.647 0.87
IBP 4.21 1.370 -0.282 -0.253 0.56 0.89
SDM 4.25 1.317 -0.308 -0.276 0.44 0.61 0.89
PE 4.62 1.013 -0.590 0.412 0.54 0.35 0.26 0.87
WD 4.83 1.250 -0.390 0.403 0.39 0.64 0.59 0.40 0.83
AD 5.13 0.988 -0.213 -0.273 0.34 0.40 0.43 0.53 0.45 0.78
AUG 4.34 1.224 -0.297 -0.049 0.63 0.65 0.57 0.42 0.57 0.53 0.87
COM 4.71 1.205 -0.128 -0.325 0.36 0.65 0.55 0.46 0.59 0.55 0.48 0.87
UAC 5.35 1.195 -0.634 0.607 0.24 0.43 0.40 0.37 0.54 0.59 0.36 0.57 0.92
Note: INN-innovation; IBP-Innovation-based Policies; SDM-Shared decision making; PE-Performance; WD-
Work design; AD-Adaptation; AUG-Augmentation; COM-Communication; CUL- Uncertainty avoidance
culture.
The boldfaced data on diagonal of the correlation matrix represent the squared root of AVE.
Table 3. Descriptive statics and correlation matrix
5 RESULTS
Test results are shown in Figure 2. The path coefficients from knowledge adaptation to department
performance and from knowledge augmentation to innovation are positively significant (β = 0.430, p
< 0.001; β = 0.630, p < 0.001; respectively). Therefore, H1 and H2a are supported. But knowledge
augmentation was partially related to department performance (β = 0.193, p < 0.1). Knowledge
adaptation and knowledge augmentation total explains a 31.3% variance of performance. Knowledge
augmentation explains a 39.7% variance of innovation. The path coefficients from uncertainty
avoidance culture and communication to knowledge adaptation are positively significant (β = 0.378, p
< 0.001; β = 0.268, p < 0.01; respectively), indicating that uncertainty avoidance culture and
communication contribute to knowledge adaptation. The path coefficient from shared decision
making to knowledge adaptation is partially significant (β = 0.135, p < 0.1, but from shared decision
making, work design, and innovation-based policy to knowledge adaptation are not significant (β =
0.036, p > 0.1; β = -0.046, p > 0.1; respectively). Thus, H3a and H4a are supported but H5a, H6a, and
H7a are not. The path coefficients from uncertainty avoidance culture and communication to
knowledge augmentation are not significant (β = 0.009, p < 0.1; β = -0.023, p > 0.1; respectively), but
from shared decision making, work design, and innovation-based policy are all positively significant
(β = 0.216, p < 0.05; β = 0.191, p < 0.05; β = 0.411, p < 0.001; respectively). Therefore, H5b, H6b,
H7b are all supported, but H3b and H4b are not. There five HR practices in total explain the 42.6%
and 49.2% variance of knowledge adaptation and knowledge augmentation respectively.
Figure 2. Results of hypotheses testing
Innovation-
based Policy
Communication
Shared DM
Work Design
(Use of Team)
Uncertainty
avoidance
Adaptation
R2=0.426
Augmentation
R2=0.492
Performance
R2=0.313
Innovation
R2=0.397
***: p < 0.001; **: p < 0.01; *: p < 0.05; +: p < 0.1
0.378***
0.268**
0.135+
0.216*
0.191*
0.411***
0.430***
0.193+
0.630***
-0.023
0.036
-0.046
0.009
6 DISCUSSION
The results show that (1) knowledge adaptation has a significant effect on department performance,
and knowledge augmentation is more important to innovation than department performance; (2)
uncertainty avoidance and communication can enhance knowledge adaptation, and shared decision
making, work design (use of team), and innovation-based policy are important to promote knowledge
augmentation.
First, two types of uncommon knowledge use have different impact on performance and innovation.
Knowledge augmentation is more important for innovation than for performance of the department.
The relationship from knowledge augmentation to performance is not significant. We suspect that
augmentation focuses on generating new understandings to solve problems for future actions. Hence
the effects of improving performance probably are not obvious immediately. Second, we found that
uncertainty avoidance and communication do not have effect on knowledge augmentation. For
uncertainty avoidance culture, although we argue that employees are less creative under this condition,
it is also reasonable that member may be able to apply one procedure to different problems after
having clearly understanding toward the detail parts. For communication, although members
communicate with each other and come out some creative ideas, but how to implement these ideas
might be another problem. It probably needs to break rules or make some changes. Third, work team
design and innovation-based policy were found to affect augmentation but have limited effects on
adaptation only. Team is a combination of individuals with diversified expertise. Information
exchange in problem analysis stage allows members to generate novel insight. However, many
activities in IS department are not in teamwork style, especially those routines works. Since
adaptation focuses on change the current way of doing things, it is then reasonable that teamwork
style has limited effect on adaptation. In addition, innovation-based policy leads to strong innovative
culture in which critical innovation is emphasized more than incremental innovation. Therefore,
augmentation is highlighted instead of adaptation.
6.1 Implications to Academia
Nag and Gioia (2012) proposed the concept of uncommon knowledge use and illustrate the idea with
several cases. This study introduces these two modes of uncommon knowledge use into the discipline
of project management and empirically validates its antecedents and consequences. In addition to
showing its effect on IS department outcomes, we also explore possible ways can be used to foster
uncommon knowledge use from the HRM perspective. We contribute to HRM literature by
introducing possible mediators that transfer the effect of HRM practices to innovation and
performance. While most of past studies investigated the relationship between HRM practices and
outcome variable, we further demonstrate that knowledge adaptation and knowledge augmentation
might be important mediators of HRM practices and performance or innovation.
6.2 Implications to Practitioners
According to the result of this study, knowledge adaptation is associated with performance positively
and knowledge augmentation leads to innovation. More important, this study identifies possible
antecedents from a HRM perspective. Based on our results, managers of IS department can choose
appropriate HRM practices to achieve the desired style of uncommon knowledge use. To promote
knowledge adaptation, managers should pay attention on fostering open department culture and
encourage communication between members. To boost augmentation, managers can empower
members to make decision, form teams to integrate different expertise to promote creative ideas of
members. In addition, managers should pay attention on member selection to select members with
innovative characteristic. They may provide adequate reward to promote uncommon knowledge use
or offer needed training to encourage members to think differently.
7 CONCLUSION
The objectives of our study are (1) examine the relationship of uncommon knowledge use between IS
performance and innovation and (2) explore the factors that are important to foster uncommon
knowledge use from the HRM perspective. Performance and innovation outcome represent the work
result of IS department. To achieve organization’s goal and meet user’s need, IS department have to
apply new method of knowledge use, which includes two modes of uncommon knowledge use. The
results indicate that uncertainty avoidance culture and communication have significant impact on
adopting knowledge adaptation; shared-decision making, work design (use of team), and innovation-
based policy impact the use of knowledge augmentation. Some limitations of this study should be
mentioned. First, the generalizability of the result might be limited because the sample pool of this
study is only in Taiwan. Thus, the future study may collect western-culture based data to verify the
generalizability of our results. Second, we validated our proposed model through cross-sectional data.
It is very likely that poor performance may reversely drive IS department to use knowledge
commonly in order to promote their performance. Finally, to maintain the parsimonious of our
research model, we explored the antecedents of uncommon knowledge use from an HRM practices
perspective only. We believe that exploring factors other than HRM practices allow us to know the
way to boost uncommon knowledge use, given its positive impact on IS performance.
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