The Role of the Perceived Justice in the Relationship between Human Resource Management Practices and Knowledge Sharing: A Study of Malaysian Universities Lecturers
Bibliographic record
Abstract
Knowledge sharing is one of the important factors in knowledge-based industries due to the fact that knowledge sharing can result in knowledge creation (Noanaka, Umemoto, & Seonoo, 1996) and innovation (Kamsak & Bulutlar, 2010; Wang & Wang, 2012). Thus, by considering that innovation can impact different dimensions of performance (financial and non-financial), (Cohen, 2010), increasing knowledge sharing is one of the necessities in any type of company. Knowledge sharing can be relevant to individual tendency for donating and collecting knowledge (Van Den Hoof & De Ridder, 2004) Different researches have been conducted about influential factors on knowledge sharing. Such researches have emphasized on environmental factors, motivational factors, individual factors, etc. (Wang & Noe, 2010; Li & Poon, 2011) that among such factors, many different theories such as social capital, resource-based review (RBV) and social exchange can be observed. Through narrowing these factors according to available concepts in human resource management (HRM) and organizational behavior, HRM practices have key role on increasing knowledge sharing. HRM practices have strategic contribution (Lengnick-Hall, Lengnick-Hall, Andrade, & Drake, 2009) as well as previous researches (Huselid, 1995; Wright, Gardner, & Moynihan, 2003; Chen & Huang, 2009) regarding RBV theory have the capability to impact employee behavior in case of sharing knowledge. Fong, Ooi, Tan, and Lee (2011), studied impact of HRM practices (training, staffing, performance appraisal, team work and reward) on knowledge sharing as gap of previous researches. Results demonstrated that HRM practices have a key role on improving knowledge sharing. If we consider talent as one of the knowledge resources or as a scope for dependent researches to impact of talent on sharing knowledge, so according to conducted research by Gelen et al. (2013) role of justice will be highlighted in case of relationship between HRM practices and knowledge sharing. It will result to the fact that existed interaction between equity theory (Pritchard, 1969) and underlying theories of researches will become important. There was little focus about this subject in previous researches. However, Khanmohammdi (2014) also emphasized on moderating role of justice in case of relationship between IT, management support, training and reward and knowledge sharing. Universities of Malaysia currently attempt to improve their position in global ranking. One of the helpful aspects for improving scientific level of universities is utilizing of high potential of lecturers. In this regard, improving knowledge sharing level among lecturers results in science creation (Khanomohammadi, 2014). Through considering lecturers as talents and also importance of knowledge sharing among them, it is necessary to clarify role of HRM practices and justice. Hence, this research aims to examine what is the relationship between HRM practices, perceived justice, and knowledge sharing in the Malaysian universities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".