Abstract
Objectives
To investigate the factors affecting employees' knowledge sharing intention, knowledge sharing behavior, and innovation behavior of the four top-ranked university hospitals in South Korea.
Methods
Data were collected from employees at three university hospitals in Seoul, Korea and one university hospital in Gyeonggi-Do, Korea through self-administered questionnaires. The survey was conducted from May 29, 2013 to July 17, 2013. A total of 779 questionnaires were analyzed by SPSS version 18.0 and AMOS version 18.0.
Results
Factors affecting hospital employees' knowledge sharing intention, knowledge sharing behavior, and innovation behavior are reciprocity, behavioral control, and trust.
Conclusion
It is important to select employees who have a propensity for innovation and continuously educate them about knowledge management based on trust.
Keywords: innovation behavior, knowledge sharing, knowledge sharing behavior, knowledge sharing intention
1. Introduction
In our knowledge–information society, organizations regard knowledge as a core resource to identify their competitiveness. Furthermore, organizations try to create added value through sustainable knowledge sharing and innovation.
Recently, the opening of the medical market, the development of medical technology and information, and the introduction of new high-tech medical equipment has intensified competition in both the domestic and international medical markets. Dalkir [1] pointed out that the more uncertain and dynamic the environment is, the more important innovation becomes. Therefore, innovation behavior is a key factor in the survival and growth of hospital organizations in the long run. The public health and health care fields are well positioned to leverage knowledge throughout the world [1]. Organizations that differentiate their processes or products and services have been shown regularly to outperform their competitors in terms of profitability, market share, and growth [2]. Hospital organizations can promote knowledge sharing culture, not only by directly incorporating knowledge in their business strategy, but also by changing employees' attitudes and behavior by promoting consistent knowledge sharing [3]. Hospital organizations attempt to set up knowledge management to implement their knowledge more effectively. In particular, knowledge sharing in hospital organizations is for the management of intellectual resources and employee's hospital work styles by providing new ideas, tools, services and processes, which results in innovative behavior in the organization.
Beginning in industrialized nations in the 1990s, knowledge management began by considering knowledge as the intellectual assets of organization. Recently, it has been adopted as the main management technique or strategy within certain companies. Knowledge management is the process of attaining intellectual and social capital. This process will lead to core competencies and higher levels of organizational performance unique to the organization [4]. In particular, hospital organizations realize that knowledge management can help them to use their current competencies or develop new and innovative ideas, services, products, processes, and solutions. Hospital organizations should take knowledge management in order to enhance knowledge creation, knowledge sharing, and application. In this way, effective knowledge management will turn hospitals into fast-learning organizations with sustained and competitive advantages [5]. The Mayo Clinic established an Innovation Center to identify and share examples of innovative patient-centered services in 2008. It is now regarded as a global innovator in medical services. Lee and Choi [6] stressed that hospitals in South Korea ask for innovation behavior from their employees. To do this, hospital organizations must build and develop knowledge by stimulating the employees' knowledge sharing and continually fostering innovation in their organizations. However, culture and systems of hospital organizations have not been set up for successful knowledge management.
One of the reasons is that hospital organizations consist of professional groups such as medical specialists, nursing specialists, clinical technicians, and administrative staff who have differing roles and skills. Therefore, the different departments within a hospital organization need to obtain new knowledge and various techniques to encourage employees in several ways. Moreover, unlike other organizations, hospital organizations are the most complex organizations in our society. They have a lot of information, skills, knowledge, and complicated decision-making processes and networks. This causes hospital organizations to require the rapid, accurate, systematic and long-term sharing of technology, information and knowledge. Furthermore, those systems also require immediate feedback mechanisms [7].
Overall, in order to have successful knowledge sharing, hospital organizations need to understand organizational factors such as systems, organizational structure, and organizational culture. Also, it is necessary to identify individual factors such as the characteristics of the employee's knowledge sharing intention and behavior. However, the studies about the relationships between knowledge sharing and innovation behavior are still rare in the medical field.
The purpose of this study was to provide a better understanding of the phenomenon. The focus was to test whether employees' knowledge sharing influences innovation behavior through the knowledge sharing process. We investigated how employees' knowledge sharing affected knowledge sharing behavior and innovation behavior. A further purpose of this study was to investigate the effect of individual factors (incentives, reciprocity, subjective norms, and behavioral control) and organization factors [organizational structure, chief executive officer (CEO) support, learning climate, information technology systems, rewards systems, and trust] relevant to knowledge sharing or innovation behavior through knowledge sharing intention and knowledge sharing behavior.
2. Materials and methods
2.1. Data collection
Hospitals mainly focus on medical and administrative areas, thus, it is difficult to answer knowledge sharing and innovation questions. Therefore, this survey only focused on large hospitals that have a vision and mission about hospital management, medical care, research and development, education, hospital culture and systems, and employees' mind for “Medical Innovation”, and “Administration Innovation” strategy.
The sample of employees included nurses, administrative staff, and medical technicians who were randomly selected from the top four university hospitals in Seoul, Korea and Gyeonggi-Do, Korea. The survey was conducted from May 29, 2013 to July 17, 2013. Of the 820 questionnaires distributed, 779 were completed and usable questionnaires were returned, representing a response rate of 95%.
2.2. Research model
The research model is illustrated in Figure 1.
Figure 1.
Research model.
2.3. Measurement of variables
There were two groups of factors related to knowledge sharing: individual factors (incentives, reciprocity, subjective norms, and behavioral control) and organizational factors (organizational structure, CEO support, learning climate, information technology systems, rewards systems, and trust). The factors connected to knowledge sharing performance are employees' knowledge sharing intention, knowledge sharing behavior, and innovation behavior. The operational definition and sources of constructs in the model are described in Table 1.
Table 1.
Survey instrument.
| Classification | Definition | Sources | ||
|---|---|---|---|---|
| Independent | Individual | Incentives | Perception to obtain a better work assignment, promotion, and many education chances | Kankanhalli et al [8], Bock et al [9] |
| Reciprocity | Perception to respond for my knowledge needs, the emergency situation, and mutual intimacies | Kankanhalli et al [8], Wasko and Faraj [10] | ||
| Subject norms | Social pressure which CEO, boss, and colleagues should share knowledge with my colleagues | Bock et al [9] | ||
| Behavioral control | Perception and ability to share knowledge with my colleagues by myself | Kankanhalli et al [8], Wasko and Faraj [10] | ||
| Organization | Organizational structure | Ability of the structure such as delegation of authority for decision-making, systematic methods and procedures | Chandler et al [11], Lin [12] | |
| CEO support | CEO's strong will, environment aid, and physical support for knowledge sharing | Hsu [13], Tan and Zhao [14] | ||
| Learning climate | Regular training and programs about new knowledge | Lee and Choi [6], Yeh et al [15] | ||
| IT systems | Efficiently building, management, and use of IT system | Bock et al [9], Kankanhalli et al [8] | ||
| Rewards systems | Extrinsic and intrinsic incentives, fairness about rewards | Ross and Weiland [16] | ||
| Trust | Interaction openly among colleagues about hospital policy, colleagues' knowledge and experience | Bock et al [9] | ||
| Dependent | Knowledge sharing intention | Motivation about actual knowledge, formal document, know-how, and expert knowledge | Bock et al [9] | |
| Knowledge sharing behavior | Action to share knowledge and actually use knowledge | Bock et al [9] | ||
| Innovation behavior | Action to create new and innovative ideas, technical tool and method | Scott and Bruce [17] | ||
The questionnaires were divided into demographic characteristics, including the individual and organization factors of knowledge sharing, sharing intention, knowledge sharing behavior, and innovation behavior. The items were measured using a seven-point Likert-type scale (ranging from 1 = strongly disagree to 7 = strongly agree). In the questionnaires, negative items were set up to inhibit insincere answers and then normalized. A score closer to 7 was interpreted as positive, whereas a score closer to 1 was negative.
To measure the variables, we used a multiple-item scale derived from existing studies. Table 2 shows the reliability of the scale questions that can be used using Cronbach's α to measure internal coincidence. All variables except organizational structure (0.602) ranged from 0.801 to 0.948, exceeding the recommended value of >0.80.
Table 2.
Results of reliability coefficients.
| Classification | Items | Cronbach's α | |
|---|---|---|---|
| Individual | Incentive | 3 | 0.834 |
| Reciprocity | 3 | 0.889 | |
| Subjective norms | 3 | 0.829 | |
| Behavioral control | 3 | 0.801 | |
| Organizational | Organizational structure | 3 | 0.602 |
| CEO support | 3 | 0.897 | |
| Learning climate | 3 | 0.876 | |
| IT systems | 3 | 0.900 | |
| Rewards system | 3 | 0.903 | |
| Trust | 3 | 0.907 | |
| Dependent | KS intention | 4 | 0.931 |
| KS behavior | 4 | 0.885 | |
| Innovation behavior | 4 | 0.948 | |
CEO = chief executive officer; IT = information technology; KS = knowledge sharing.
2.4. Statistical analysis
The data were analyzed using Structural Equation Modeling in SPSS version 18.0 (SPSS Inc., Chicago, IL, USA) to validate the research model. We conducted frequency analysis to measure the demographic characteristics. We used the t test and analysis of variance to compare mean differences for sharing intention, knowledge sharing behavior, and innovation behavior according to the demographic characteristics. Finally, we used confirmatory analysis and completed maximum likelihood estimation using Analysis of Moment Structure (AMOS) in SPSS version 18.0 (SPSS Inc., Chicago, IL, USA). Fit indices indicated χ², Normal Fit Index (NFI),Tucker–Lewis Index (TLI), Comparative Fit Index (CFI), and Root Mean Square Error of Approximation (RMSEA). To improve the fit of the model, modification indices were used.
3. Results
3.1. Sociodemographic characteristics
The respondents' characteristics are shown in Table 3. Among the 779 respondents, 499 (64.1%) were female and 280 (35.9%) were male. Three hundred and fifty-four (45.4%) participants were aged 30–39 years, 295 (37.9%) participants were >40 years, and 130 (16.7%) participants were 20–29 years. There were 600 (77.0%) respondents who had graduated from university, 164 (21.1%) respondents had masters degrees, and 15 (1.9%) employees only graduated from high school. In terms of work experience, 274 (35.2%) respondents had worked in the organization for 6–10 years, 203 (26.0%) respondents had worked for >16 years, 176 (22.6%) respondents had worked for ≤5 years, and 126 (16.2%) had worked for 11–15 years. With regard to job type, 274 (35.2%) respondents were administrative staff, 261 (33.5%) participants were medical technicians, and 244 (31.3%) participants were nurses. The positions were grouped into three categories. That is, 340 (43.6%) people were classed as general employees, 232 (29.8%) people as junior managers, and 207 (26.6%) people as middle managers.
Table 3.
Respondent characteristics.
| Classification | Frequency | % | |
|---|---|---|---|
| Sex | Female | 499 | 64.1 |
| Male | 280 | 35.9 | |
| Age (y) | 20–29 | 130 | 16.7 |
| 30–39 | 354 | 45.4 | |
| ≥40 | 295 | 37.9 | |
| Education level | High school | 15 | 1.9 |
| University | 600 | 77.0 | |
| Graduate school | 164 | 21.1 | |
| Work experience (y) | ≤5 | 176 | 22.6 |
| 6–10 | 274 | 35.2 | |
| 11–15 | 126 | 16.2 | |
| ≥16 | 203 | 26.0 | |
| Occupation type | Nursing staff | 244 | 31.3 |
| Technical staff | 261 | 33.5 | |
| Administrative staff | 274 | 35.2 | |
| Position | General employee | 340 | 43.6 |
| Junior manager | 232 | 29.8 | |
| Middle manager | 207 | 26.6 | |
| Total | 779 | 100.0 | |
3.2. Knowledge sharing intention, knowledge sharing behavior, and innovation behavior according to sociodemographic characteristics
According to sociodemographic characteristics, knowledge sharing intention, knowledge sharing behavior, and innovation behavior of men seemed to be stronger than those of women. The higher the respondents' education level, the stronger their knowledge sharing intention became. As workers' age, education level, position, and work experience increased, innovation behavior tended to be higher. Respondents who were older and had a higher position had greater knowledge sharing behavior (Table 4).
Table 4.
Mean difference of KS intention, KS behavior, innovation behavior by sociodemographic characteristics.
| Classification | Level of KS Intention | F-test/t-test | Level of KS Behavior | F-test/t-test | Level of IB | F-test/t-test | |
|---|---|---|---|---|---|---|---|
| Sex | Female | 5.42 ± 0.91 | −2.98** | 4.93 ± 0.84 | −2.02 | 4.48 ± 1.00 | −7.22*** |
| Male | 5.62 ± 0.89 | 5.06 ± 0.89 | 5.01 ± 0.96 | ||||
| Age (y) | 20–29 | 5.43 ± 0.93 | 11.17*** | 4.82 ± 0.84 | 14.21*** | 4.27 ± 0.96 | 27.41*** |
| 30–39 | 5.36 ± 0.91 | 4.86 ± 0.85 | 4.56 ± 1.00 | ||||
| ≥40 | 5.69 ± 0.86 | 5.18 ± 0.85 | 4.98 ± 0.98 | ||||
| Education level | High school | 5.05 ± 0.95 | 4.79** | 4.92 ± 0.74 | 2.14 | 4.48 ± 0.68 | 7.21** |
| University | 5.46 ± 0.92 | 4.95 ± 0.87 | 4.60 ± 1.03 | ||||
| Graduate school | 5.65 ± 0.84 | 5.10 ± 0.84 | 4.93 ± 0.97 | ||||
| Work experience (y) | ≤5 | 5.50 ± 0.93 | 3.86** | 4.89 ± 0.87 | 2.33 | 4.43 ± 1.05 | 6.40*** |
| 6–10 | 5.38 ± 0.88 | 4.94 ± 0.82 | 4.67 ± 0.98 | ||||
| 11–15 | 5.46 ± 0.91 | 4.99 ± 0.81 | 4.68 ± 0.94 | ||||
| ≥16 | 5.66 ± 0.91 | 5.10 ± 0.93 | 4.88 ± 1.04 | ||||
| Occupation type | Nursing staff | 5.53 ± 0.90 | 0.42 | 4.97 ± 0.88 | 0.20 | 4.57 ± 1.07 | 1.74 |
| Technical staff | 5.50 ± 0.93 | 5.00 ± 0.88 | 4.72 ± 1.00 | ||||
| Administrative staff | 5.46 ± 0.90 | 4.96 ± 0.82 | 4.71 ± 0.98 | ||||
| Position | Employee | 5.41 ± 0.93 | 11.49*** | 4.87 ± 0.85 | 17.15*** | 4.47 ± 0.99 | 26.49*** |
| Junior manager | 5.39 ± 0.89 | 4.88 ± 0.89 | 4.59 ± 0.99 | ||||
| Middle manager | 5.75 ± 0.84 | 5.27 ± 0.87 | 5.09 ± 0.98 | ||||
IB = innovation behavior; KS = knowledge sharing.
*p < 0.05.
**p < 0.01.
***p < 0.001.
3.3. Results of research model
The research model investigated whether the individual and organizational factors influenced innovation behavior through knowledge sharing intention and knowledge sharing behavior.
Based on Table 5, the final research model (RMSEA = 0.048) is better than the null model (RMSEA = 0.081).
Table 5.
Evaluation of fit measurement: research model.
| χ² | d.f. | NFI | TLI | CFI | RMSEA | |
|---|---|---|---|---|---|---|
| Null model | 4757.927 | 787 | 0.815 | 0.826 | 0.841 | 0.081 |
| Research model | 2101.702 | 762 | 0.918 | 0.939 | 0.946 | 0.048 |
| Recommended value | – | >0.9 | >0.9 | >0.9 | <0.08 |
CFI = Comparative Fit Index; d.f. = degrees of freedom; NFI = Normal Fit Index; RMSEA = Root Mean Square Error of Approximation; TLI = Tucker–Lewis Index.
As shown in Table 6, the individual and organizational factors influenced knowledge sharing intention. Individual factors (reciprocity, subjective norms, and behavioral control) and an organizational factor, trust, had a significant effect of knowledge sharing intention. Next, individual factors [behavioral control, reciprocity(−)] and organizational factors (CEO support, IT systems, and trust) significantly influenced knowledge sharing behavior. Moreover, individual factors [behavioral control and reciprocity(−)] and organizational factors [organization structure, CEO support, and trust(−)] significantly influenced innovation behavior. However, reciprocity and trust in particular had a negative influence on innovation behavior.
Table 6.
Path result of research model.
| Paths | Standardized path coefficient | p |
|---|---|---|
| Incentives → knowledge sharing intention | −0.013 | |
| Reciprocity → knowledge sharing intention | 0.174 | *** |
| Subject norms → knowledge sharing intention | 0.164 | *** |
| Behavioral control → knowledge sharing intention | 0.288 | *** |
| Organization structure → knowledge sharing intention | −0.036 | |
| CEO support → knowledge sharing intention | 0.048 | |
| Learning climate → knowledge sharing intention | 0.069 | |
| IT systems → knowledge sharing intention | 0.008 | |
| Rewards systems → knowledge sharing intention | −0.029 | |
| Trust → knowledge sharing intention | 0.288 | *** |
| Incentives → knowledge sharing behavior | 0.066 | |
| Reciprocity → knowledge sharing behavior | −0.123 | * |
| Subject norms → knowledge sharing behavior | 0.028 | |
| Behavioral control → knowledge sharing behavior | 0.404 | *** |
| Organization structure → knowledge sharing behavior | 0.010 | |
| CEO support → knowledge sharing behavior | 0.118 | * |
| Learning climate → knowledge sharing behavior | 0.012 | |
| IT systems → knowledge sharing behavior | 0.146 | * |
| Rewards systems → knowledge sharing behavior | −0.027 | |
| Trust → knowledge sharing behavior | 0.110 | * |
| Incentives → innovation behavior | 0.060 | |
| Reciprocity → innovation behavior | −0.113 | * |
| Subject norms → innovation behavior | −0.015 | |
| Behavioral control → innovation behavior | 0.248 | *** |
| Organization structure → innovation behavior | 0.054 | * |
| CEO support → innovation behavior | 0.156 | ** |
| Learning climate → innovation behavior | −0.071 | |
| IT systems → innovation behavior | 0.032 | |
| Rewards systems → innovation behavior | 0.017 | |
| Trust → innovation behavior | −0.125 | ** |
| Knowledge sharing intention → KS behavior | 0.275 | *** |
| Knowledge sharing behavior → innovation behavior | 0.557 | *** |
*p < 0.05.
**p < 0.01.
***p < 0.001.
4. Discussion
The main findings of this study were as follows. First, according to mean differences in knowledge sharing intention, knowledge sharing behavior, and innovation by sociodemographic characteristics, knowledge sharing intention, knowledge sharing behavior, and innovation in men seems to be stronger than in women. The higher the education level, the stronger knowledge sharing intention becomes. As workers' education level, position, and work experience increase, innovation behavior also tends to be higher. The older and higher position one achieves, the better knowledge sharing behavior becomes. Based on these results, a hospital organization should suggest systematic solutions. Therefore, the efficient knowledge management is based on understanding sociodemographic characteristics, in particular age, sex, and cultural and educational differences. Second, this study examined the factors affecting hospital employees' knowledge sharing intention, knowledge sharing behavior, and innovation behavior. Three individual factors (reciprocity, subjective norms, and behavioral control) and one organizational factor (trust) significantly influenced knowledge sharing intention. Two individual factors [reciprocity(−), and behavioral control] and three organizational factors (CEO support, IT system, and trust) had a significant influence on knowledge sharing behavior. Two individual factors [behavioral control and reciprocity(−)] and three organizational factors (organizational structure, CEO support, and trust(−))] significantly influenced innovation behavior through knowledge sharing intention and knowledge sharing behavior. However, two factors (reciprocity and trust) in particular had a negative influence on innovation behavior. Individual factors [behavioral control and reciprocity(−)] and organizational factors (organizational structure, CEO support, and trust(−))] significantly influenced innovation behavior. However, reciprocity and trust had a negative influence on innovation behavior.
According to the findings above, important factors relevant to hospital employees' knowledge sharing behavior and innovation behavior are reciprocity, behavioral control, and trust. Finally, hospital managers should analyze individual factors and organizational factors to enhance workers' knowledge sharing behavior and innovation behavior. Hospital managers should build an organizational culture and system and develop practical strategies. In addition, it is important to select workers who have a propensity for innovation and continuously educate them about knowledge management based on trust.
In the case of trust, an organization maintains rapport through reciprocity and mutual trust among members in the innovation process. Furthermore, organizations need to actively encourage innovative behavior through social interaction among their members [18]. However, our results indicate that mutual trust and reciprocity have a negative impact on innovation behavior. According to Aziz et al [19], because workers perceive their expertise, skill and knowledge and new ideas as sources of power, workers are reluctant to share and create their knowledge. That could be the reason knowledge sharing behavior and innovation behavior are hindered. Thus, in order to achieve knowledge sharing and innovation behavior, hospitals need to set targets and goals, and workers should be instructed and encouraged to share their expertise and innovation with their counterparts.
Krogh et al [20] indicated that some other barriers include organizational structural barriers such as authority and status hierarchies. There are factors that affect knowledge sharing and innovation in organizations, such as lack of time to share knowledge and innovation, concern about job security, lack of awareness, inadequate evaluation and communication of previous mistakes that may improve the individual and organizational learning influences, differences in experience level, lack of interaction, social network, poor communications and interpersonal skills, sociodemographic characteristics (age, sex, and cultural and educational differences), and little trust in the accuracy and credibility of knowledge.
Therefore, Kim and Kim [21] have emphasized that the ultimate goal of knowledge management for innovation and creativity through knowledge sharing is that hospitals need diversity and autonomy of members or departments, decentralization and leadership for rapid responses, internal and external networks to share and exchange information and knowledge, open communication for exchanging high-quality information and face-to-face contact, cohesion for communication and teamwork, and surplus resources for challenges and opportunities.
Consequently, hospitals should employ and educate new employees who have innovative tendencies. Also, hospitals need to recognize that the diversity in an organization is good and to educate experts in various occupations for innovation and creativity, by organizing task force teams. In addition, hospitals should try to build inter- and intra-departmental mutually reciprocal trust, and use innovation behavior to seek work-related changes.
The limitations and suggestions for future research are as follows. First, only four university hospitals were investigated. Hence, in order to compensate for this limitation, research should be conducted using samples from other hospitals, because cultural differences among hospital organizations influence employees' perception regarding knowledge sharing and innovation. Second, this study focused only on nurses, medical technicians, and administrative staff. So, it does not represent the entire hospital. Future research should consider a broader sample of workers such as CEOs, doctors, and medical personnel. Also, further study can examine how individual traits and organizational characteristics may moderate the relationship between knowledge receivers and providers based on trust. Finally, these data were based on subjective responses and used a cross-sectional approach. Therefore, future studies should gather longitudinal data to examine the causality and inter-relationships between variables that are important to knowledge sharing. In addition, further research considering these factors could enhance our understanding of critical determinants for knowledge sharing and innovation.
Conflicts of interest
The authors declare no conflicts of interest.
Footnotes
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
References
- 1.Dalkir K. 2nd ed. Boston: Massachusetts Institute of Technology; 2011. Knowledge management in theory and practice. [Google Scholar]
- 2.Tidd J. Innovation management in context: environment, organization and performance. Int J Management Rev. 2001;3(3):169–183. [Google Scholar]
- 3.Connelly C.E., Kelloway E.K. Predictors of employees’ perceptions of knowledge sharing cultures. Leadersh Organ Dev J. 2003;24(5):294–301. [Google Scholar]
- 4.Rigby D.K. 2011. Management tools 2011: an executives' guide. Boston: Bain & Company. [Google Scholar]
- 5.Edna P., Tuvya R. New York: Wiley; 2011. The complete guide to knowledge management: a strategic plan to leverage your company's intellectual capital. [Google Scholar]
- 6.Lee H.S., Choi B.G. Knowledge management enablers, processes, and organizational performance: an integrative view and empirical examination. J Manag Inf Syst. 2003;20(1):179–228. [Google Scholar]
- 7.Kim T.S., Jang I.S. The influence of knowledge management strategy of hospitals and HIS characteristics on their management performance. Korea Manag Educ Inst. 2009;56:205–225. [Google Scholar]
- 8.Kankanhalli A., Tan B.C.Y., Wei K.K. Contributing knowledge to electronic knowledge respositories: an empirical investigation. MIS Quarterly. 2005;29(1):113–145. [Google Scholar]
- 9.Bock G.W., Zmud R.W., Kim Y.G. Behavioral intention formation in knowledge sharing: examining the roles of extrinsic motivators, social-psychological forces, and organizational climate. MIS Quarterly. 2005;29(1):1–26. [Google Scholar]
- 10.Wasko M.M., Faraj S. Why should I share examining knowledge contribution in networks of practice? MIS Quarterly. 2005;29(1):35–57. [Google Scholar]
- 11.Chandler G.N., Keller C., Lyon D.W. Unraveling the determinants and consequences of an innovation-supportive organizational culture. Entrepreneurship Theory Pract. 2000;25(1):59–76. [Google Scholar]
- 12.Lin W.B. The effect of knowledge sharing model. Expert Syst Appl. 2008;34(2):1508–1521. [Google Scholar]
- 13.Hsu I.C. Knowledge sharing practices as a facilitating factor for improving organizational performance through human capital: a preliminary test. Expert Syst Appl. 2008;35(3):1316–1326. [Google Scholar]
- 14.Tan H.H., Zhao B. Individual and perceived contextual-level antecedents of individual technical information inquiry in organizations. J Psychol. 2003;137(6):597–621. doi: 10.1080/00223980309600637. [DOI] [PubMed] [Google Scholar]
- 15.Yeh Y.J., Lai S.Q., Ho C.T. Knowledge management enablers: a case study. Indust Manag Data Syst. 2006;106(6):793–810. [Google Scholar]
- 16.Ross W.H., Weiland C. Effects of interpersonal trust and time pressure on managerial mediation strategy in a simulated organizational dispute. J Appl Psychol. 1996;81(3):228–248. [Google Scholar]
- 17.Scott S.G., Bruce R.A. Determinants of innovative behavior: a path model of individual informativeness in the workplace. Acad Manag J. 1994;37:580–607. [Google Scholar]
- 18.Brandes P., Dharwadkar R., Wheatley K. Social exchange within organization and work outcomes: the important of local and global relationships. Group Organ Manag. 2004;29(3):276–301. [Google Scholar]
- 19.Aziz N., Gleeson D., Kashif M. 2012. Barriers and enablers of knowledge sharing: a qualitative study of ABB, Bombardier. Ericsson and Siemens. School of Sustainable Development of Society and Technology, Bachelor Thesis in Business Administration. [Google Scholar]
- 20.Krogh G., Ichijo K., Nonaka I. Oxford University Press; Oxford: 2000. Enabling knowledge creation: how to unlock the mystery of tacit knowledge and release the power of innovation. [Google Scholar]
- 21.Kim K.S., Kim G.S. JIPMUNDANG; Asan Social Welfare Foundation, Seoul: 2003. Organizational design for business plan for knowledge management. [Google Scholar]