University of Wollongong

Research Online
Faculty of Informatics - Papers (Archive) Faculty of Engineering and Information Sciences

2011

Improving knowledge sharing behaviour within

organizations: towards a model
Marion Zalk
University of Melbourne

Rachelle Bosua
University of Melbourne

Rajeev Sharma
University of Wollongong, rajeev@uow.edu.au

Publication Details
Zalk, M., Bosua, R. & Sharma, R. (2011). Improving knowledge sharing behaviour within organizations: towards a model. ECIS 2011:
European Conference on Information Systems (pp. 1-6). AIS Electronic Library (AISeL): AISeL.

Research Online is the open access institutional repository for the University of Wollongong. For further information contact the UOW Library:
research-pubs@uow.edu.au
Improving knowledge sharing behaviour within organizations: towards a
model
Abstract
Knowledge management is the process of capturing, storing, sharing and using organizational knowledge with
the aim of improving organizational performance. A necessary precursor for successful knowledge
management initiatives is knowledge exchange between employees. This exchange is voluntary and highly
dependent on an individual’s willingness to share his/her knowledge. It thus becomes important to identify
the factors motivating employees to share their knowledge. This research in progress draws on Locke and
Latham’s Goal Setting Theory (1990) to propose a model explaining knowledge sharing behavior.

Keywords
era2015

Disciplines
Physical Sciences and Mathematics

Publication Details
Zalk, M., Bosua, R. & Sharma, R. (2011). Improving knowledge sharing behaviour within organizations:
towards a model. ECIS 2011: European Conference on Information Systems (pp. 1-6). AIS Electronic Library
(AISeL): AISeL.

This conference paper is available at Research Online: http://ro.uow.edu.au/infopapers/3854

 IMPROVING KNOWLEDGE SHARING BEHAVIOUR
WITHIN ORGANIZATIONS: TOWARDS A MODEL

Zalk, Marion, Dept of Information Systems, The University of Melbourne, Melbourne, VIC,
3010, Australia, m.zalk@pgrad.unimelb.edu.au

Bosua, Rachelle, Dept of Information Systems, The University of Melbourne, Melbourne,

VIC, 3010, Australia, rachelle.bosua@unimelb.edu.au

Sharma, Rajeev, School of Information Systems and Technology, University of Wollongong,

NSW 2500, Australia, rajeevs@unimelb.edu.au

Abstract
Knowledge management is the process of capturing, storing, sharing and using organizational
knowledge with the aim of improving organizational performance. A necessary precursor for
successful knowledge management initiatives is knowledge exchange between employees. This
exchange is voluntary and highly dependent on an individual’s willingness to share his/her
knowledge. It thus becomes important to identify the factors motivating employees to share their
knowledge. This research in progress draws on Locke and Latham’s Goal Setting Theory (1990) to
propose a model explaining knowledge sharing behavior.

Keywords: Knowledge Management, Motivation, Goal Setting Theory, Goal Commitment, Feedback,
Task Complexity, Social Cognitive Theory, Job Design Theory
1. Introduction
Knowledge sharing can be considered as one of the most important knowledge management processes
in organizations (Alavi, 2001; Bock et al, 2005). As such, mechanisms should be introduced to
encourage and motivate individuals and groups to improve knowledge sharing activities and behavior
in organizational settings. Organizations often attempt to motivate knowledge sharing behavior
(KSB) using extrinsic motivators such as monetary incentives (e.g. performance-related pay or
bonuses); promotions (Bock et al., 2005); better work assignments; job security (Kankanhalli et al.,
2005); training opportunities (Franco et al., 2002) or combinations of motivators (Bock et al., 2005,
Franco et al., 2002). Even when it is not explicit that financial incentives are used to promote higher
productivity, the underlying philosophy of many organizations is that these highly individualistic
tournament incentive systems are significant determinants of an individual’s behavior, resulting in
intense competition among employees (Lai, 2009, Von Krogh, 1998, Menton and Pfeffer, 2003). In
this instance, an individual’s unique knowledge may provide increased influence and power (Von
Krogh, 1998) and/or secure his/her position in the organization (Zack, 1999). Consequently, there is a
reluctance to share knowledge (Lai, 2009) and the company becomes increasingly dependent on
individual expertise (Von Krogh, 1998). This dependence on individual expertise is often undesirable
for the organization’s overall performance (Von Krogh, 1998) as strategically the ability to share
knowledge is required for problem solving and exploiting opportunities (Zack, 1999).

A large part of the knowledge sharing literature focuses on people-to-people sharing of knowledge
(Chiu et al., 2006, Swan et al., 1999, Wasko and Faraj, 2000) while there is a gap in terms of research
that investigates knowledge sharing behavior through codification. Knowledge codification is an
inherently complex activity and Cohendet and Steinmueller (2000) claim that much higher priority
needs to be assigned to mechanisms and processes that extend and improve individual knowledge
codification efforts. As extrinsic motivators can place the organization in an unattractive position, it is
important to consider other factors that influence an individual’s degree of willingness to exert and
maintain an effort towards achieving organizational goals (Franco et al., 2002). This research explores
knowledge sharing goals by investigating the influence of goal commitment, feedback and task
complexity on KSB through codification. It draws on the existing theories of Job Design Theory
(JDT), Social Cognitive Theory (SCT) and Goal Setting Theory (GST). Section 2 discusses these
theories and introduces the KSB model followed by a discussion of contributions of the model in
Section 3.

2. A Model of Knowledge Sharing Behaviors in Organizations

Literature suggests that the effectiveness of an organization is increasingly dependent on the
organization’s ability to facilitate the utilization and sharing of knowledge (Nonaka and Takeuchi,
1995). There is a growing body of research that suggests that organizations are more productive if
successful conditions for knowledge sharing are created. A deeper examination of these conditions
has highlighted the critical role of motivation on knowledge sharing and utilization processes (Alavi
and Leidner, 2001, Hansen et al., 1999, Szulanski, 1996, 2000). It is therefore important to further
explore motivation and unpack the motivational factors that underpin knowledge sharing behavior.
Motivational factors are usually categorized into intrinsic and extrinsic. Intrinsic (intangible)
motivation refers to the inherent pleasure and satisfaction derived from performing an action
(Venkatesh and Speier, 1999). Situationalists such as Job Design Theorists (JDT) believe that the job
and the organization design are the primary determinants of employee behavior and by focusing on
the social and psychological influences on individuals in a job, factors that contribute to motivation to
perform a job (Oldham and Hackman, 2010) can be identified.

In a similar vein, Latham (2007:162) states that “… to believe that motivation is solely a function of
the person or solely a function of the job is naïve…”. Rather it is a combination of many factors,
including the employee’s environment (the job and organization) and the interaction this environment
has with the individual that affects and is in turn affected by a person’s needs, personality and values
(Franco et al., 2002). A theory that explains behavior based on the interaction of different factors is
Social Cognitive Theory (SCT) which explains behavior as a triadic, dynamic and reciprocal
interaction of the person, the environment and the behavior. SCT has been widely used in
Information Systems (IS) literature to improve computer use and internet behavior (Hsu et al., 2007)
and recently several studies have drawn upon SCT in order to explain knowledge sharing behavior
(e.g. Chiu et al., 2006, Lin and Huang, 2008).

On the basis of these previous studies, this research proposes a model based on Locke and Latham’s
(1990) Goal Setting Theory (GST). GST is highly compatible with SCT and became popular towards
the end of the 20th century both in the literature and as a valid and practical theory of employee
motivation within an organization (Latham, 2007). “A goal is the object or aim of an action” (Locke
and Latham, 2002:705). This theory asserts that there is a linear relationship between degree of goal
difficulty and performance. The function is linear until the subjects reach the limits of their ability (at
high difficulty goals) and then the function plateaus (Locke and Latham, 1990). Goals affect action
through three direct mechanisms; an energizing function, persistence and a direction of both
behavioral and cognitive attention and effort toward goal related activities. Goals also indirectly
influence action by leading to the discovery, arousal and/or use of task relevant knowledge and
strategies.

The objective of this research is to investigate how KSBs can be increased in organizations.
Knowledge sharing can either occur via codification or via person-to-person contact (Hansen et al.,
1999). Codification refers to the persistence of knowledge by means of documentation (Alavi and
Leidner, 2001). It entails individuals contributing knowledge to populate document databases and
individuals seeking knowledge from these databases for reuse (Hansen et al., 1999). The aim is to put
organizational knowledge into a form that makes it accessible to those who need it and give
permanence to knowledge that may otherwise only exist in the individual’s mind (Davenport and
Prusak, 1998). Organizations that adopt a codification strategy obtain a competitive advantage via the
reuse of this high quality and reliable knowledge (Hansen et al., 1999).

Knowledge can also be viewed as closely tied to the person who developed it and within this view it is
shared mainly through direct person-to-person contact. A personalization strategy emphasizes the
linkage among people and the transfer of knowledge via this relationship. The organization that
adopts this strategy obtains competitive advantage through inventive and analytic advice on high-level
strategic problems through the channeling of individual expertise (Hansen et al., 1999). According to
GST, behavioral performance is moderated by goal commitment, feedback and task complexity.
These together with a set of corresponding hypotheses are described in the sections that follow.
2.1. Goal commitment

When individuals are committed to their goals, the goal-performance relationship is strongest (Locke
and Latham, 2002). Goal commitment is influenced by two factors namely importance and self
efficacy. Importance refers to those factors that make goal attainment important to an individual such
as the outcomes that are expected and can be influenced by increasing the importance of the task
including participation in decision making and goal setting (Locke and Latham, 2002). It is also
suggested that an increase in an individual’s self efficacy will increase goal commitment. Self-
efficacy refers to the belief that one can attain his/her goal. Organizations can influence an
individual’s self-efficacy by providing training; role modeling and through positive communications
that the goal is achievable (Locke and Latham, 2002). In previous studies where self-efficacy was
considered, a positive relationship between self-efficacy and KSB was found (e.g. Hsu et al., 2007).
Therefore we expect that:

Hypothesis 1: Goal commitment positively influences the effect of knowledge sharing goals on
knowledge sharing behavior

2.2. Feedback
Feedback can be defined as “...a special case of the general communications process in which some
sender (hereafter referred to as a source) conveys a message to a recipient (Ilgen et al., 1979:350). In
this instance, the message comprises of information about the recipient and feedback can be
considered as information about the recipient’s past performance. The value of the information is
dependent on the incremental increase in knowledge about performance that it provides (Annett,
1969). Feedback in itself does not have the power to motivate but rather through its relationship with
goal setting. For goals to be effective, individuals need summary feedback that reveals progress in
relation to their goals. If the individual has no information on his/her performance, it is difficult or
impossible to adjust their level of or direction of performance and performance strategies in order to
achieve the goal. Feedback can cognitively affect performance by revealing what the individual is
doing correctly or incorrectly or what task strategies are helping or hindering (Locke and Latham,
1990). Therefore we predict that:

Hypothesis 2: Feedback positively influences the effect of knowledge sharing goals on knowledge
sharing behavior

2.3. Task Complexity

Task complexity influences the amount of knowledge, skill and effort required to perform the task
(Wood, 1986). There are numerous tools and technologies developed to foster collaboration, the
sharing of knowledge (Alavi and Leidner, 2001) and an increase in organizational learning by
capturing internal knowledge and making it available to employees for reuse (Lin and Huang, 2008).
As there are many different ways of creating artifacts and as each is different, their complexity may
impact KSB.

There are different ways of classifying tasks. Locke and Latham (1990) use Wood’s (1986) definition
of task complexity to classify tasks. Wood’s (1986) definition describes tasks based on three types of
complexities, specifically compontent complexity, coordinative complexity and dynamic complexity.
Component complexity is a function of the number of distinct acts that are required to be performed
and the number of information cues that need to be processed in order to complete the task. The
nature of the relationship between task inputs and task products is captured in coordinative
complexity and at a more specific level will influence the timing, frequency, location and intensity
requirements for performing a given task. Dynamic complexity refers to the changes in the states of
the world that in turn affect the coordinative and component complexities. These changes can affect
skills and knowledge required to complete the task (Wood, 1986) therefore we predict that.

Hypothesis 3: Task complexity negatively influences the effect of knowledge sharing goals on
knowledge sharing behavior

Based on the preceding hypotheses, the KSB model therefore is

Feedback
Goal
Task
Commitment
Complexity

H1 H3

H2
Knowledge Knowledge
Sharing Goal Sharing Behaviour

Figure 1 Model of knowledge sharing behavior

3. Contributions
Organizations implementing knowledge management initiatives face a critical hurdle of finding ways
to encourage employees to share knowledge (Nahapiet and Ghoshal, 1998, Hansen et al., 1999, Zack,
1999). KSB cannot be controlled or enforced as this behavior is essentially voluntary and the sharer
has the option of passing on the knowledge that he/she possesses (Davenport and Prusak, 1997).
Therefore there is a requirement to consider the factors that positively and negatively influence KSB.
Drawing on a well developed theory of motivation described by Locke and Latham (1990), a model of
KSB is presented. This model describes the effects of goal commitment, feedback and task
complexity on KSB (Locke and Latham, 1990).

Practically, this research aims at enabling organizations to more effectively promote worker
motivation and to identify managerial interventions that can foster KSB. This has implications for
organizational resources including human resources and technology. Within the organizational
system, human resource management (HRM) is responsible for mobilizing and motivating employees
(Franco et al., 2002) and therefore motivating KSB would fall under the responsibilities of HRM.
Furthermore, results of this research may provide key insights to team and unit managers on how
tasks should be designed and managed to promote KSB. Technology also plays a role in KSB
(Hansen et al., 1999) as it is used to capture and disseminate knowledge. This has implications for the
designers and implementers of knowledge management systems. The next stage of this research in
progress will involve the testing of the hypotheses by conducting a series of experiments.
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