The defining of knowledge in industry

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This chapter is devoted to literature on knowledge sharing. This chapter begins with a review on the concept of knowledge, knowledge management and knowledge sharing and the importance of knowledge sharing. Finally, a theoretical framework and hypotheses are presented to show the relationships between the study variables.

2.2 What is Knowledge?

Defining knowledge precisely is difficult, due to its formless and unclear. Bhatt (2002) defines what is considered knowledge for one person can be information for the other. Therefore, valuation of knowledge is uncertain since productivity gain from untried knowledge cannot be guaranteed. Furthermore, knowledge can be a liability if it does not provide the expected result. Regardless of difficulties in defining knowledge, it is well agreed that knowledge is an organized combination of ideas, rules, procedures, and information. Only through the organizations that information can find its life and become knowledge. It can be associated with professional intellect. According to this point of view, organizational knowledge at its best is a metaphor and the organization does not create knowledge. Knowledge is also defined as acceptable belief, where beliefs are used to justify self-interests. This concept of knowledge is matched with the "constructionist perspective", where actors are considered to perform and construct realities based on their mental models, which are shaped through interpretations and discourse between different members. Bhatt (2002) also divided knowledge in different types. A part of knowledge become public goods and is continually reexamined and reinterpreted by different social members, but other part of the knowledge still remains exclusively in the domain of individual. This knowledge cannot be fully communicated, but only perceived by the individual.

Knowledge belongs to the family of progressively increasing corporate assets, like management systems, brand identity, customer information and corporate reputation. Smith (2001) concludes that knowledge is a human highly personal asset and represents the pooled expertise and efforts of networks and alliances. Based on the published reports, 99% of work people actions are knowledge based. Knowledge seems invisible but it clearly drives the end result, and the value of knowledge is increased when it has a key purpose and focuses on mission, core values and strategic priorities. Knowledge assets like money or equipment, exits and are worth cultivating only in the context of the strategy used to apply them. When organizations merge, downsize, reorganize, or organizational culture changes, priceless knowledge is lost or buried under new information. Employees who leave their jobs take their valuable knowledge, resources, skills and experiences with themselves. While those who stay may be assigned new jobs and never use their wealth of accumulated knowledge. Unless managers recognize the inventive ways people get thing done, tacit knowledge, in particular, will be lost.

2.2.1 Tacit and Explicit Knowledge

Spencer (1997) categorizes knowledge into two types; there are tacit knowledge and explicit knowledge. Tacit knowledge is subjective and experience based. It is often cannot be expressed in words or sentences, described in numbers or formulas, due to its nature which is context specific based. Tacit knowledge also includes cognitive skills such as beliefs, images, intuition, mental models, and technical skills like craft and know-how. In contrast, explicit knowledge is objective and rational. It can be expressed in words, sentences, numbers or formulas, and it is context free. It includes theoretical approaches, problem solving, manuals and databases.

2.2.1.1 Tacit knowledge

It is difficult to estimate the level of knowledge tacitness, but knowledge can be evaluated in a spectrum. In this spectrum, one extreme end is associated with completely tacit and unconscious knowledge and at the other end represents completely explicit, structured and coded knowledge. Haldin-Herrgard(2000), discusses the associated issues with tacit knowledge. This paper indicates that tacit and explicit coexist in a synergetic relationship in such a dualist framework. We can find many epitomes of tacit knowledge such as intuition, rule-of-thumb, gut feeling and personal skills in our working life. These can be categorized into two dimensions, the technical and the cognitive dimension. The technical dimension includes information and expertise in relation to know-how and the cognitive dimension consists of mental models, belief and values.

Tacit knowledge is mainly saved in individuals and it is difficult to exchange due to its transparent characteristics. We can understand tacit knowledge as when one has released oneself from the technical formulas for action. We can refer to a person is able to cook without a recipe or to have an intuitive feeling of the right decision. Tacit knowledge is obtained by internal individual processes like experience, reflection, internalization, or individual talents. Therefore, it cannot be managed and taught in the same manner as explicit knowledge. In contrast explicit knowledge is possible to store in a mechanical or technological way, like in handbooks or information systems, while tacit knowledge is mostly stored only in human beings. Tacit knowledge cannot be given in lectures, and it cannot be found in database, textbooks, manuals or internal newsletters for diffusion. It has to be internalized in the human body and soul. Different methods like apprenticeship, direct interaction, networking and action learning that include face to face social interaction and practical experiences are more suitable for supporting the sharing of tacit knowledge. We should consider that relying on personal tacit knowledge in organizations is usually risky, and conversion of tacit knowledge to explicit or at least ability to share it offers greater value to the organization (Haldin-Herrgard, 2000)

2.2.1.2 Explicit knowledge

Explicit knowledge is mainly in form of technical or academic data or information that is described in formal language, like manuals, mathematical expressions, copyright and patents. Smith (2001), believe that this "know-what" or systematic knowledge is readily communicated and shared through print, electronic methods, and other formal means. Explicit knowledge is technical and requires a level of academic knowledge or understanding. These skills can be gained through formal education, or structured study.

Explicit knowledge is carefully codified, stored in a hierarchy of databases and can be accessed with high quality, reliable, fast information retrieval systems, Once explicit knowledge assets are codified, it can be reused to solve many similar types of problem or connect people with valuable and reusable knowledge. Knowledge sharing processes often require major monetary investments in the infrastructure needed to support and fund information. In the process of gathering and using explicit knowledge, we assume a predictable and relatively stable environment. However, marketplace competition and changing customer needs, among other factors, reduce the stability (smith, 2001).

2.3 Knowledge Management

Unfortunately, there is no general definition of Knowledge Management, just as there is no agreement as to what constitutes knowledge in the first place. For this reason, it is best to think of knowledge management in the broadest context. Succinctly put, knowledge management is the process through which organizations generate value from such assets involves sharing them among employees, departments and even with other companies in an effort to devise best practices. It is important to note that the definition says nothing about technology; while knowledge management is often facilitated by information technology, technology by itself is not knowledge management.

Knowledge management is the management of corporate knowledge that can improve a range of organizational performance characteristics by enabling an enterprise to be more "intelligent acting" (Wiig, 1993). It is not a new movement per se, as organizations have been trying to harness their internal processes and resources that have resulted in various movement over the years as total quality management, expert systems, business processes re-engineering, the learning organization, core competencies, and strategy focus (Shukla, 1997). Good managers in organizations have been using the know-how of people they hired with skills and experience, and processes for effective management on an ad-hoc, casual basis. However, only recently have organizations begun to focus their interest on this aspect in more systematic and a formal manner.

Most organizations already have a vast reservoir of knowledge in a wide variety of organizational processes, best-practices, know-how, customer trust, management information system, culture and norms. However, this is knowledge is diffused, and mostly unrecognized. Often, organizational culture itself prevents people from sharing and disseminating their know-how in an effort to hold onto their individual powerbase and viability. Determining who knows what in an organization itself could be a time consuming and daunting task. This, in itself, justifies the need for a knowledge management system for organizations to allow them to identify and access workers' skill and expertise.

2.4 Knowledge Sharing

Davenport (1997) defined sharing as a voluntary act and distinguished it from reporting. Reporting involves the exchange of information based on some routines or structured formats. Sharing, on the other hand, implies a conscious act by an individual who participates in the knowledge exchange even though there is no compulsion to do so. Hendriks (1999) suggested that knowledge sharing implies a relationship between at least two parties one that possesses the knowledge and the other that acquires the knowledge. This article makes a distinction between knowledge sharing between individuals and the concept of knowledge transfer used predominantly to describe the movement of knowledge between larger entities within organizations, such as between departments or divisions and between organizations themselves (e.g., Chakravarthy et al., 1999; Lam, 1997).

Knowledge sharing is important because it provides a link between the individual and the organization by moving knowledge that resides with individuals to the organizational level, where it is converted into economic and competitive value for the organization (Hendriks, 1999). Cohen and Levinthal (1990) proposed that interactions between individuals who possess diverse and different knowledge enhance the organization's ability to innovate far beyond what any one individual can achieve. Boland and Tenkasi (1995, p.358) concurred with this idea and contended that competitive advantage and product success in organizations results from individuals with diverse knowledge collaborating synergistically toward common outcomes. According to these authors, the creation of an organization's knowledge base requires "a process of mutual perspective taking where distinctive individual knowledge is exchanged, evaluated, and integrated with that of others in the organization". Knowledge sharing also leads to the dissemination of innovative ideas and is considered critical to creativity and subsequent innovation in organizations (Armbrecht, Chapas, Chappelow, & Farris, 2001). However, in practice, the lack of knowledge sharing has proved to be a major barrier to the effective management of knowledge in organizations (Davenport & Prusak, 1998; Hendriks, 1999).

Knowledge sharing between individuals is a process that contributes to both individual and organizational learning (Andrews & Delahaye, 2000; Nidumolu, Subramani, & Aldrich, 2001). Organizational knowledge is recognized as a key component of organizational learning (Dodgson, 1993; Huber, 1991). Huber (1991) further identified four knowledge concepts that contribute to organizational learning knowledge acquisition, information distribution, information interpretation, and organizational memory. The concept of knowledge sharing as it is presented in this article is linked to both knowledge distribution and knowledge acquisition. The voluntary act of sharing knowledge by an individual contributes to knowledge distribution, and the process of sharing may result in knowledge acquisition by other individuals within the organization. Knowledge sharing between individuals thus results in individual learning, which in turn may contribute to organizational learning.

Knowledge management calls for managing organizational knowledge as a corporate asset and harnessing knowledge creation and sharing as key organizational capabilities (Nonaka & Takeuchi, 1995). A possible concern in this approach to managing knowledge is that much of organizational knowledge is controlled at the level of individuals (Staples & Jarvenpaa, 2001). Individuals use the knowledge they have in their daily activities at work (Lam, 2000), and unless the organization can facilitate the sharing of this knowledge with others, it is likely to lose this knowledge when individual employees leave (Gupta & Govindarajan, 2000). Even if individuals stay with the organization, the full extent of their knowledge may not be realized and utilized unless there are opportunities for the individual to share that knowledge with others in the organization (Weiss, 1999).

Understanding the process of knowledge sharing between individuals is one step toward a better understanding of knowledge sharing as a whole in organizations.

2.5 The Importance of Knowledge Sharing

Gurteen (1999) found four importance values of knowledge sharing:

Knowledge is an intangible product which includes ideas; processes and information .These intangible products are taking a growing share of global trade from the traditional, tangible goods of manufacturing economy.

Knowledge sharing is important for creating a new knowledge in order to achieve competitive advantage.

Knowledge sharing is important because of the increasing turnover of staff. People do not keep the same job for life any more. When someone leaves an organization their knowledge walks out of the door with them. Therefore, sharing has the power to carry on the knowledge.

Many organizations have problem of "we don't know what we know". Expertise learnt and applied in one part of the organization is not leveraged in another.

Accelerating change in technology, business and social "50 percent of what we knew 5 years ago in probably obsolete today".

Sharing knowledge allows both parties not only to retain information but also to amplify and expands it through the exchange process. However sharing of knowledge within organizations provides the opportunity to discuss know-what and know-how practices, to direct the organization towards future development and growth. The act of it transfers knowledge from one person to another or among many people adding value to organizational activities (Mitchell, 2008).

2.6 Culture of work environment

Organizational cultures are increasingly being recognized as a major barrier to effective knowledge creation, sharing, and use (De Long & Fahey, 2000; Leonard Barton, 1995; Pan & Scarbrough, 1999). Organizations are essentially cultural entities (Cook&Yanow, 1993), and therefore, regardless of what organizations do to manage knowledge, the influences of the organization's culture are much stronger (McDermott & O'Dell, 2001).

Schein (1985, p.9) defined culture as a "pattern of basic assumptions" that is developed by a group as they grapple with and develop solutions to everyday problems. When these assumptions work well enough to be considered valid, they are taught to new members as the appropriate way to approach these problems. Schein (1985, p.89) further added that a key part of every culture is a set of assumptions about how to determine or discover what is real and "how members of a group take an action, how they determine what is relevant information, and when they have enough of it, to determine whether to act and what to do". Culture is therefore reflected in the values, norms, and practices of the organization, where values are manifested in norms that in turn shape specific practices (De Long & Fahey, 2000).

De Long and Fahey (2000) identified certain aspects of organizational culture that influence knowledge sharing-culture shapes assumptions about which knowledge is important, it controls the relationships between the different levels of knowledge (organizational, group, and individual), and it creates the context for social interaction. It is also culture that determines the norms regarding the distribution of knowledge between an organization and the individuals in it (Staples & Jarvenpaa, 2001). Norms and practices that advocate individual ownership of knowledge severely impede the process of knowledge sharing within the organization, as the "organizational culture orients the mindset and action of every employee" (Nonaka & Takeuchi, 1995, p. 167). Culture suggests what to do and what not to do regarding knowledge processing and communication in organizations (Davenport, 1997). An important component of culture in organizations is corporate vision (Gold, Malhotra, & Segars, 2001; Leonard-Barton, 1995). Gold et al. (2001) pointed to the fact that a corporate vision not only pro vide a sense of purpose to the organization but also helps to create a system of organizational values. Organizational values that influence knowledge sharing include the creation of a sense of involvement and contribution among employees (O'Dell & Grayson, 1998), the types of knowledge that are valued (Leonard-Barton, 1995), and knowledge-related values such as trust and openness (Eisenberg & Riley, 2001; von Krogh, 1998).

An organization's culture also shapes the perceptions and behaviours of its employees (De Long & Fahey, 2000), and one way it does this is by establishing the context for social interactions within the organization (Gold et al., 2001; Trice & Beyer, 1993). According to De Long and Fahey (2000), the impact of culture on the context for social interaction can be assessed along three dimensions-vertical interactions (interactions with senior management), horizontal interactions (interactions with individuals at the same level in the organization), and special behaviours that promote knowledge sharing and use (sharing, teaching, and dealing with mistakes).

Cultures are not homogenous across an organization (McDermott & O'Dell, 2001). Within organizations, there are also subcultures that are characterized by a distinct set of values, norms and practices, often resulting in their members valuing knowledge differently from other groups within the same organization (Pentland, 1995). Subcultures and their influence on knowledge sharing add even more complexity to determining those practices and norms that create the right environment to facilitate the sharing of knowledge.

2.7 The Importance of Knowledge Sharing Culture in Organization

Many organizations have intranets to enable employees to share, exchange, and access knowledge but if non-sharing culture exist there will be little benefit for the organization or its employees. It is possible that employees may not find the intranets user friendly, therefore there is likely to be resistance to sharing knowledge through that system, or for some it may simply be too much of a hassle to try find what is being sought. Where resistance to sharing knowledge attitudes exist, organizations need to consider undertaking an approach to implementing behavioral patterns amongst staff that are helpful to knowledge sharing.

Organizational culture has connection with knowledge sharing and knowledge transfer. Knowledge transfer and knowledge sharing is a concept and can be formal and informal. Formal knowledge sharing however is more common among staff's in organization (Naaranoja & Sandhu, 2007).

Studies show that culture can make or crack hard work to manage knowledge effectively within an organization (Choo & Bontis, 2002). Lawson's research study included the test of studies to understand what cultural types or cultural values were found to be most important to the implementation of effective Knowledge Management practices. One study Lawson(2004) described was by Lesser and Storck (2001) study concluded that communities of practices provided value to an organization and can be used as a means to enhance performance and improve quality within any organization or company.

According to Nonaka and Takeuchi (1995), knowledge sharing culture consists of collection and combination of ordinary expectation, share experience, tacit roles and social standard and norms that create our attitude and behaviors. Gold et al. (2001) pointed out that knowledge sharing culture in organization should support and motivate their employee in any knowledge sharing activities during interaction and relations building to overcome the barriers for implementing the KM. According to O'Dell and Grayson (1998), people like to share partly because they wanted to let other people know of what knowledge they hold. The people like a kind of respect they earned from others. If for any specific reason they cover up knowledge, it was organizational environment, political setting or reward system that caused them to prevent from sharing and collaboration (O'Dell and Grayson, 1998).

Culture, according to Vijay Sathe is the set of important understandings (often unstated) that members of a community share in common. These shared understandings consist of our norms, values, attitudes, beliefs and paradigms. Another definition given in Webster's New Collegiate Dictionary "culture is the integrated pattern of human behavior that includes thought, speech, action, and artifacts and depends on man's capacity for learning and transmitting knowledge to succeeding generations". This second definition is an exciting one as increasing our capacity for learning and transmitting knowledge is one of the prime aims of knowledge management (Gurteen.com, 2009).

2.8 Theoretical Framework and Model Development

Based on the fact of knowledge sharing in Malaysia is still in the infancy stage the following theoretical model was developed to study acceptance of knowledge sharing in Malaysia. Knowledge self-efficacy, Trust, Top management support, Organizational rewards, Subjective norm and Information and Communication Technology (ICT) use are independent variables in this study. Knowledge donating and collecting have been chosen to be intervening variables and knowledge sharing intention has been chosen as dependent variable.

DEPENDENT VARIABLES

INTERVENING VARIABLES

INDEPENDENT VARIABLES

Figure 2.1 Theoretical framework

2.8.1 Knowledge Self-efficacy

Self-efficacy is defined as the judgments of individuals regarding their capabilities to organize and execute courses of action required to achieve specific levels of performance (Bandura, 1986). Self-efficacy can help motivate employees to share knowledge with colleagues (Wasko and Faraj, 2005). Researchers have also found that employees with high confidence in their ability to provide valuable knowledge are more likely to accomplish specific tasks (Constant et al., 1994). Knowledge self-efficacy typically manifests in people believing that their knowledge can help to solve job-related problems and improve work efficacy (Luthans, 2003). Employees who believe that they can contribute organizational performance by sharing knowledge will develop greater positive willingness to both contribute and receive knowledge.

H1a: Knowledge self-efficacy positively influences employee willingness to donate knowledge.

H0: There is no relationship between knowledge self-efficacy and knowledge donating.

Hypothesis 1b: Knowledge self-efficacy positively influences employee willingness to donate knowledge.

H0: There is no relationship between knowledge self-efficacy and knowledge collecting.

2.8.2 Trust

Numerous definitions of the term trust have been given from a number of different perspectives and research disciplines (Doney and Cannon, 1997; Sahay, 2003). As a multidimensional construct, trust is a belief, sentiment or expectation about an exchange partner that results from the partner's expertise, reliability and intentionality (Ganesan, 1994), or from the partner's honesty and benevolence (Kumar et al., 1995). In this study, to reflect the co-opetition relationship between supply chain members in the research model, trust refers to a firm's belief to have confidence in its partner's reliability and integrity that lead to positive outcomes (Anderson and Narus, 1990; Morgan and Hunt, 1994). For all levels of analysis, trusting parties must be vulnerable to some extent for trust to become operational (Doney and Cannon, 1997). In operational terms, trust implies the belief that the other partner is honest and sincere (Claro et al., 2006).

It is evidenced in knowledge management that trust is a necessary condition for interorganizational knowledge learning (Davenport and Prusak, 1998; Dyer and Nobeoka, 2000). Trust plays a critical role in facilitating a deeper exchange relationship such as knowledge sharing (Morgan and Hunt, 1994; Davenport and Prusak, 1998; Dyer and Nobeoka, 2000; Soekijad and Andriessen, 2003; Moller and Svahn, 2004). Without trust during the collaborative process, information exchanged or knowledge shared between the partners may be low in accuracy (Currall and Judge, 1995). In the context of supply chains, trust is seen as a phenomenon, which contributes to the strength of inter-organizational relationships (Sahay, 2003; Wu et al., 2004). Trust is an important precondition in supply chain management (Halldorsson et al., 2007) and information sharing is a prerequisite for trust in supply chains (Henriott, 1999; Kwon and Suh, 2005). As such trust facilitates inter-organizational knowledge sharing (Mentzer et al., 2000). In particular, if the knowledge sharing process involves sharing vital and confidential information, the process not only helps build trust but also grows with the presence of trust (Sahay, 2003). Without trust, supply chain members will not share confidential information, as it risks a substantial investment (Sahay, 2003). With trust, partners are able to engage in more open and effective knowledge sharing (Panteli and Sockalingam, 2005).

Hypothesis 2a: Trust positively influences employee willingness to donate knowledge.

H0: There is no relationship between trust and knowledge donating.

Hypothesis 2b: Trust positively influences employee willingness to collect knowledge.

H0: There is no relationship between trust and knowledge collecting.

2.8.3 Top management Support

Organizational rewards indicate what the organization values shape employee behaviors (Cabrera and Bonache, 1999). Organizational rewards can range from monetary incentives such as increased salary and bonuses to non-monetary awards such as promotions and job security (Davenport and Prusak, 1998; Hargadon, 1998). Several organizations have introduced reward systems to encourage employees to share their knowledge. For example, Buckman Laboratories recognizes its 100 top knowledge contributors through an annual conference at a resort. Moreover, Lotus Development, a division of IBM, bases 25 per cent of the total performance evaluation of its customer support workers on the extent of their knowledge sharing activities (Bartol and Srivastava, 2002). This study thus expects that if employees believe they can receive organizational rewards by offering their knowledge, they would develop greater positive willingness to both donate and receive knowledge.

Hypothesis 3a: Top management support positively influences employee willingness to donate knowledge.

H0: There is no relationship between top management support and knowledge donating.

Hypothesis 3b: Top management support positively influences employee willingness to collect knowledge.

H0: There is no relationship between top management support and knowledge collecting.

2.8.4 Organizational reward

Organizational rewards indicate what the organization values shape employee behaviors (Cabrera and Bonache, 1999). Organizational rewards can range from monetary incentives such as increased salary and bonuses to non-monetary awards such as promotions and job security (Davenport and Prusak, 1998; Hargadon, 1998). Several organizations have introduced reward systems to encourage employees to share their knowledge. For example, Buckman Laboratories recognizes its 100 top knowledge contributors through an annual conference at a resort. Moreover, Lotus Development, a division of IBM, bases 25 per cent of the total performance evaluation of its customer support workers on the extent of their knowledge sharing activities (Bartol and Srivastava, 2002). This study thus expects that if employees believe they can receive organizational rewards by offering their knowledge, they would develop greater positive willingness to both donate and receive knowledge.

Hypothesis 4a: Organizational reward positively influences employee willingness to donate knowledge.

H0: There is no relationship between organizational reward and knowledge donating.

Hypothesis 4b: Organizational reward positively influences employee willingness to collect knowledge.

H0: There is no relationship between organizational reward and knowledge collecting.

2.8.5 Subjective norm

Subjective norm is often measured directly by asking respondents to indicate whether "important others" (that is, self-selected referents) would approve or disapprove of their performing a particular behavior (Ajzen, 1991). Studies using TPB have often found subjective norms significantly impact in predicting behavioral intentions than the other factors of the models (Kurland, 1995; Chang, 1998). For example, Ajzen and Fishbein (1980) proposed that the significance of the factors in their model would vary with the behavioral intentions tested and the subgroup or population investigated. Chang (1998) found that subjective norm significantly affected moral behavioral intention. Ruy et al., (2003) indicated that individual professional groups, physician subject norms regarding knowledge sharing have affected knowledge-sharing intentions.

Hypothesis 5a: Subjective norm positively influences employee willingness to donate knowledge

H0: There is no relationship between subjective norm and knowledge donating.

Hypothesis 5b: Subjective norm positively influences employee willingness to collect knowledge

H0: There is no relationship between subjective norm and knowledge collecting.

2.8.6 Information and communication technology (ICT) use

Information and communication technology (ICT) use and knowledge sharing are closely linked, because ICT can enable rapid search, access and retrieval of information, and can support communication and collaboration among organizational employees (Huysman and Wulf, 2006). Within knowledge sharing, the use of ICT development facilitate new methods and applications (such as groupware, online databases, intranet, virtual communities, etc.), and allow firms to expand available social networks by overcoming geographical boundaries and thus achieving more effective collaborative activities (Pan and Leidner, 2003

Moreover, according to Yeh et al. (2006), effective knowledge management requires employees sharing their knowledge through ICT facilities, because ICT can provide communication channels for obtaining knowledge, correcting flow processes, and identifying the location of knowledge carriers and requesters.

Hypothesis 6a: ICT support positively influences employee willingness to donate knowledge.

H0: There is no relationship between ICT support and knowledge donating.

Hypothesis 6b: ICT support positively influences employee willingness to collect knowledge.

H0: There is no relationship between ICT support and knowledge collecting.

2.8.7 Knowledge donating

Knowledge donating aims to see individual knowledge become group and organizational knowledge over time, which in turn improves the stock of knowledge available to the firm. A firm that promotes employees to contribute knowledge within groups and organizations is likely to generate new ideas and develop new business opportunities, thus facilitating innovation activities (Darroch and McNaughton, 2002).

Hypothesis 7: Employee willingness to donate knowledge positively influences knowledge sharing intentions.

H0: There is no relationship between knowledge donating and knowledge sharing intention.

2.8.8 Knowledge collecting

Knowledge collecting consists of processes and mechanisms for gathering information and knowledge from internal and external sources. The process of knowledge collecting in which organizational knowledge becomes group and individual knowledge, involves the internalization and socialization of knowledge. Hansen (1999) suggested that knowledge collecting represents a key aspect of successful project completion, especially for organizations heavily involved in innovation projects.

Hypothesis 8: Employee willingness to collect knowledge positively influences knowledge sharing intentions.

H0: There is no relationship between knowledge collecting and knowledge sharing intention.

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