The Influence of Knowledge Sharing on Sustainable Performance: A Moderated Mediation Study
Abstract
:1. Introduction
RQ 1: How does knowledge sharing contribute to the sustainable performance of banking institutions?RQ 2: What is the magnitude of indirect effects, if there is any, of knowledge hiding and employees’ ambidexterity in turning knowledge sharing into sustainable performance?
2. Theoretical Model and Hypothesis Development
2.1. Knowledge Sharing and Sustainable Performance
2.2. Knowledge Sharing, and Employees’ Ambidexterity
2.3. Employees’ Ambidexterity and Sustainable Performance
2.4. Moderating Effect of Knowledge Hiding
2.5. Research Framework
3. Research Design and Methods
3.1. Sampling and Data Collection Procedure
3.2. Participants’ Information
3.3. Measurement Tools
4. Results
4.1. Common Method Bias and Multicollinearity
4.2. Model Evaluation
4.2.1. Measurement Model Evaluation
4.2.2. Structural Model Evaluation
5. Findings
5.1. Hypothesis Testing
5.2. Mediation Effect
5.3. Moderating Effect of Knowledge Hiding
6. Discussion
7. Conclusions
7.1. Theoretical Contributions
7.2. Managerial Implications
7.3. Research Limitations and Further Research Directions
Author Contributions
Funding
Conflicts of Interest
References
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Gender | Age Category of Participants | ||||
Male | Female | Above 25 Years | Above 35 Years | Above 35 Years | Above 55 Years |
210 (73.20%) | 77 (26.80%) | 42 (14.6%) | 115 (40.10%) | 92 (32.10%) | 38 (13.20%) |
Educational Qualifications | Job Experience | ||||
Graduate | Master | Others | Below 10 Years | Above 15 Years | Above 20 Years |
27 (9.40%) | 147 (51.20%) | 113 (39.40%) | 92 (32.10%) | 163 (56.80%) | 32 (11.10%) |
Bank Category and Number of Respondents | Foreign Bank | Islamic Bank | State Bank | Private Bank | |
46 (16.02) | 59 (20.56) | 40 (13.94) | 142 (49.48) | ||
Employee Size in Branches | Below 20 | Below 30 | Below 40 | Below 50 | |
24 | 84 | 112 | 67 |
Models | CMIN/DF | RMSEA | RMR | GFI | TLI | CFI | Alternative Models |
---|---|---|---|---|---|---|---|
7-Factor Model | 1.126 | 0.029 | 0.021 | 0.913 | 0.979 | 0.982 | EPI, EPO, KS, KH, SP, EP, FP |
6-Factor Model | 2.433 | 0.071 | 0.034 | 0.802 | 0.873 | 0.889 | EPI + EPO, KS, KH, SP, EP, FP |
5-Factor Model | 4.682 | 0.113 | 0.072 | 0.673 | 0.673 | 0.709 | EPI + EPO, KS + KH, SP, EP, FP |
4-Factor Model | 5.413 | 0.124 | 0.077 | 0.649 | 0.605 | 0.608 | EPI + EPO, KS + KH, SP + EP, FP |
3-Factor Model | 6.040 | 0.133 | 0.077 | 0.622 | 0.552 | 0.593 | EPI + EPO, KS + KH, SP + EP + FP |
2-Factor Model | 6.856 | 0.143 | 0.066 | 0.581 | 0.479 | 0.524 | EPI + EPO, KS + KH + SP + EP + FP |
1-Factor Model | 7.120 | 0.146 | 0.065 | 0.583 | 0.456 | 0.501 | EPI + EPO + KS + KH + SP + EP + FP |
Threshold limit | <0.050 | <0.050 | <0.050 | >0.90 | >0.90 | >0.90 |
Latent variable | CR | AVE | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
---|---|---|---|---|---|---|---|---|---|
1. FP | 0.802 | 0.582 | 0.763 | ||||||
2. EPI | 0.891 | 0.577 | 0.353 | 0.759 | |||||
3. EPO | 0.880 | 0.595 | 0.424 | 0.620 | 0.771 | ||||
4. KH | 0.895 | 0.682 | −0.203 | −0.341 | −0.447 | 0.826 | |||
5. KS | 0.818 | 0.530 | 0.176 | 0.426 | 0.486 | −0.024 | 0.728 | ||
6. EP | 0.849 | 0.655 | 0.419 | 0.488 | 0.386 | −0.166 | 0.204 | 0.809 | |
7. SP | 0.863 | 0.759 | 0.269 | 0.387 | 0.373 | −0.134 | 0.288 | 0.284 | 0.871 |
Hypotheses | Path Relations | Estimate | C.R. | p | ||
---|---|---|---|---|---|---|
H1 | SP | <--- | KS | −0.03 | −0.396 | 0.692 |
H2 | EA | <--- | KS | 0.45 | 3.726 | *** |
H3 | SP | <--- | EA | 0.54 | 3.966 | *** |
95% Confidence Interval | |||||
---|---|---|---|---|---|
Path | Estimate | T-statistics | Lower | Upper | Standard Error |
KS→EA→SP | 0.184 | 3.309 | 0.084 | 0.302 | 0.055 |
KS→SP (c/) | −0.127 | 0.3102 | −0.0681 | 0.0935 | 0.041 |
Variables | β | SE | T-Value | p-Value | LLCI | ULCI |
---|---|---|---|---|---|---|
Constant | 2.8053 | 0.4836 | 5.6829 | 0.0000 | 1.8336 | 3.7765 |
KS | 0.4671 | 0.1173 | 3.9833 | 0.0001 | 0.2363 | 0.6979 |
KH | −0.1985 | 0.2672 | −0.7427 | 0.4583 | −0.7245 | 0.3275 |
KS×KH | −0.0336 | 0.0638 | −0.5261 | 0.5992 | −0.1591 | 0.0920 |
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Jilani, M.M.A.K.; Fan, L.; Islam, M.T.; Uddin, M.A. The Influence of Knowledge Sharing on Sustainable Performance: A Moderated Mediation Study. Sustainability 2020, 12, 908. https://doi.org/10.3390/su12030908
Jilani MMAK, Fan L, Islam MT, Uddin MA. The Influence of Knowledge Sharing on Sustainable Performance: A Moderated Mediation Study. Sustainability. 2020; 12(3):908. https://doi.org/10.3390/su12030908
Chicago/Turabian StyleJilani, Munshi Muhammad Abdul Kader, Luo Fan, Mohammad Tazul Islam, and Md. Aftab Uddin. 2020. "The Influence of Knowledge Sharing on Sustainable Performance: A Moderated Mediation Study" Sustainability 12, no. 3: 908. https://doi.org/10.3390/su12030908
APA StyleJilani, M. M. A. K., Fan, L., Islam, M. T., & Uddin, M. A. (2020). The Influence of Knowledge Sharing on Sustainable Performance: A Moderated Mediation Study. Sustainability, 12(3), 908. https://doi.org/10.3390/su12030908