Analysis of Maximization Strategy Intangible Assets through the Speed of Innovation on Knowledge-Driven Business Performance Improvement
Abstract
:1. Introduction
2. Methodology
2.1. Financial Performance
2.2. Human Capital
2.3. Structural Capital
2.4. Consumer Capital
2.5. Speed of Innovation
3. Results
3.1. The Effect of Human Capital on Improving Financial Performance
3.2. The Effect of Structural Capital on Improving Financial Performance
3.3. The Effect of Consumer Capital on Improving Financial Performance
3.4. Speed of Innovation Moderates the Effect of Human Capital on Improving Financial Performance
3.5. Speed of Innovation Moderates the Effect of Structural Capital on Improving Financial Performance
3.6. Speed of Innovation Moderates the Effect of Consumer Capital on Improving Financial Performance
- Y = γ1X + γ2M + γ3XM + ε
- Description:
- Y: Endogenous variables;
- X: Exogenous variable;
- γ: The influence coefficient of the exogenous on the endogenous latent variable;
- M: Moderating variables;
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Sample Criteria | Number of Observations |
---|---|
Total questionnaires distributed | 401 |
Complete questionnaires that were not returned | (9) |
Total returned questionnaires | 392 |
Complete questionnaires that cannot be processed | 0 |
Total questionnaires that can be processed | 392 |
Variable | Definition | Data Source |
---|---|---|
Improved Financial Performance | A company’s financial condition in a certain period regarding aspects of fundraising and its distribution is presented in the financial statements (Frias-Aceituno et al. 2014) | Questionnaire |
Human Capital | Value is added in the form of knowledge, expertise, abilities and skills possessed by humans and then makes humans capital or assets of an organization to achieve strategic goals (Pasban and Nojedeh 2016) | Questionnaire |
Structural Capital | Supporting infrastructure, organizational databases, and organizational design structures that enable human capital to carry out its functions for better performance (Sumedrea 2013) | Questionnaire |
Consumer Capital | The knowledge possessed in aspects of marketing channels and relationships that occur with outside parties such as customers, suppliers, communities and governments that develop in the organization through operational activities (Kim et al. 2012). | Questionnaire |
Speed of Innovation | The pace of progress manifests a bold appearance in innovating and commercializing new products, which means the company can accelerate its operational activities in developing new products (Engel 2015). | Questionnaire |
Variable | Indicator | X1 | X2 | X3 | Z | Y | p-Value | Description |
---|---|---|---|---|---|---|---|---|
Human Capital (X1) | X1.1 | 0.631 * | > | <0.001 | Valid | |||
X1.2 | 0.663 * | <0.001 | Valid | |||||
X1.3 | 0.677 * | <0.001 | Valid | |||||
X1.4 | 0.709 * | <0.001 | Valid | |||||
X1.5 | 0.741 * | <0.001 | Valid | |||||
X1.6 | <0.001 | Valid | ||||||
Structural Capital (X2) | X2.1 | 0.973 * | <0.001 | Valid | ||||
X2.2 | 0.992 * | <0.001 | Valid | |||||
X2.3 | 0.978 * | <0.001 | Valid | |||||
X2.4 | 0.981 * | <0.001 | Valid | |||||
Consumer Capital (X3) | X3.1 | 0.638 * | <0.001 | Valid | ||||
X3.2 | 0.768 * | <0.001 | Valid | |||||
X3.3 | 0.745 * | <0.001 | Valid | |||||
X3.4 | 0.718 * | <0.001 | Valid | |||||
X3.5 | 0.823 * | <0.001 | Valid | |||||
Speed of Innovation (Z) | >Z1 | >0.832 * | ><0.001 | >Valid | ||||
Z2 | 0.776 * | <0.001 | Valid | |||||
Z3 | 0.807 * | <0.001 | Valid | |||||
Z4 | 0.797 * | <0.001 | Valid | |||||
Improvement of financial performance (Y) | Y1 | 0.646 * | <0.001 | Valid | ||||
Y2 | 0.786 * | <0.001 | Valid | |||||
Y3 | 0.844 * | <0.001 | Valid | |||||
Y4 | 0.913 * | <0.001 | Valid |
Z × X1 | Z × X2 | Z × X3 | p-Value | Description | |||
---|---|---|---|---|---|---|---|
Z1 × X1.1 | 0.596 | Z1 × X2.1 | 0.977 | Z1 × X3.1 | 0.867 | <0.001 | Valid |
Z1 × X1.2 | 0.876 | Z1 × X2.2 | 0.997 | Z1 × X3.2 | 0.852 | <0.001 | Valid |
Z1 × X1.3 | 0.831 | Z1 × X2.3 | 0.977 | Z1 × X3.3 | 0.688 | <0.001 | Valid |
Z1 × X1.4 | 0.829 | Z1 × X2.4 | 0.985 | Z1 × X3.4 | 0.716 | <0.001 | Valid |
Z1 × X1.5 | 0.934 | Z2 × X2.1 | 0.978 | Z1 × X3.5 | 0.852 | <0.001 | Valid |
Z1 × X1.6 | 0.792 | Z2 × X2.2 | 0.988 | Z2 × X3.1 | 0.838 | <0.001 | Valid |
Z2 × X1.1 | 0.892 | Z2 × X2.3 | 0.972 | Z2 × X3.2 | 0.932 | <0.001 | Valid |
Z2 × X1.2 | 0.704 | Z2 × X2.4 | 0.957 | Z2 × X3.3 | 0.760 | <0.001 | Valid |
Z2 × X1.3 | 0.866 | Z3 × X2.1 | 0.984 | Z2 × X3.4 | 0.721 | <0.001 | Valid |
Z2 × X1.4 | 0.823 | Z3 × X2.2 | 0.986 | Z2 × X3.5 | 0.827 | <0.001 | Valid |
Z2 × X1.5 | 0.808 | Z3 × X2.3 | 0.991 | Z3 × X3.1 | 0.798 | <0.001 | Valid |
Z2 × X1.6 | 0.780 | Z3 × X2.4 | 0.990 | Z3 × X3.2 | 0.943 | <0.001 | Valid |
Z3 × X1.1 | 0.861 | Z4 × X2.1 | 0.962 | Z3 × X3.3 | 0.794 | <0.001 | Valid |
Z3 × X1.2 | 0.932 | Z4 × X2.2 | 0.992 | Z3 × X3.4 | 0.728 | <0.001 | Valid |
Z3 × X1.3 | 0.744 | Z4 × X2.3 | 0.953 | Z3 × X3.5 | 0.937 | <0.001 | Valid |
Z3 × X1.4 | 0.897 | Z4 × X2.4 | 0.964 | Z4 × X3.1 | 0.868 | <0.001 | Valid |
Z3 × X1.5 | 0.852 | Z4 × X3.2 | 0.837 | <0.001 | Valid | ||
Z3 × X1.6 | 0.791 | Z4 × X3.3 | 0.730 | <0.001 | Valid | ||
Z4 × X1.1 | 0.850 | Z4 × X3.4 | 0.779 | <0.001 | Valid | ||
Z4 × X1.2 | 0.800 | Z4 × X3.5 | 0.953 | <0.001 | Valid | ||
Z4 × X1.3 | 0.851 | <0.001 | Valid | ||||
Z4 × X1.4 | 0.795 | <0.001 | Valid | ||||
Z4 × X1.5 | 0.848 | <0.001 | Valid | ||||
Z4 × X1.6 | 0.844 | <0.001 |
Correlations among l. vs. with sq. rts. of AVEs | ||||||||
---|---|---|---|---|---|---|---|---|
X1 | X2 | X3 | Z | Y | Z × X1 | Z × X2 | Z × X3 | |
Human Capital (X1) | 0.634 * | |||||||
Structural Capital (X2) | 0.902 * | |||||||
Consumer Capital (X3) | 0.603 * | |||||||
Innovation Speed (Z) | 0.739 * | |||||||
Improvement of financial performance (Y) | 0.613 * | |||||||
Z × X1 | 0.588 * | |||||||
Z × X2 | 0.708 * | |||||||
Z × X3 | 0.520 * |
X1 | X2 | X3 | Z | Y | Z × X1 | Z × X2 | Z × X3 | |
---|---|---|---|---|---|---|---|---|
R-squared coefficients | 0.393 | |||||||
Adjusted R-squared coefficients | 0.311 | |||||||
Composite reliability coefficients | 0.798 | 0.946 | 0.732 | 0.828 | 0.693 | 0.876 | 0.941 | 0.806 |
Cronbach’s alpha coefficients | 0.696 | 0.923 | 0.547 | 0.722 | 0.513 | 0.854 | 0.933 | 0.749 |
Average variances extracted | 0.401 | 0.813 | 0.364 | 0.547 | 0.363 | 0.238 | 0.501 | 0.177 |
Full collinearity VIFs | 2.893 | 1.035 | 1.732 | 2.181 | 1.448 | 1.506 | 1.013 | 1.264 |
Q-squared coefficients | 0.335 |
No. | Model Fit and Quality Indices | Fit Criteria | Indeks | Description |
---|---|---|---|---|
1 | Average path coefficient (APC) | p < 0.05 | 0.169 | Fulfilled |
2 | Average R-squared (ARS) | p < 0.05 | 0.311 | Fulfilled |
3 | Average adjusted R-squared (AARS) | p < 0.05 | 0.293 | Fulfilled |
4 | Average block VIF (AVIF) | acceptable if ≤5, ideally ≤3.3 | 1.341 | Fulfilled |
5 | Average full collinearity VIF (AFVIF) | acceptable if ≤5, ideally ≤3.3 | 1.634 | Fulfilled |
6 | Tenenhaus GoF (GoF) | small ≥0.1, medium ≥0.25, large ≥0.36 | 0.364 | Fulfilled, Categori Large |
7 | Sympson’s paradox ratio (SPR) | acceptable if ≥0.7, ideally = 1 | 0.767 | Fulfilled |
8 | R-squared contribution ratio (RSCR) | acceptable if ≥0.9, ideally = 1 | 0.951 | Fulfilled |
9 | Statistical suppression ratio (SSR) | acceptable if ≥0.7 | 0.833 | Fulfilled |
10 | Nonlinear bivariate causality direction ratio (NLBCDR) | acceptable if ≥0.7 | 0.833 | Fulfilled |
Variable | Criteria | Description | |
---|---|---|---|
Path Coefficients | p Values | ||
Human Capital (X1) | 0.205 | <0.001 *** | Highly Significant |
Structural Capital (X2) | 0.157 | 0.007 *** | Highly Significant |
Consumer Capital (X3) | 0.362 | <0.001 *** | Highly Significant |
Innovation Speed× Human Capital (Z × X1) | 0.054 | 0.202 | Not significant |
Innovation Speed× Structural Capital (Z × X2) | 0.119 | 0.031 ** | Significant |
Innovation Speed× Consumer Capital (Z × X3) | −0.113 | 0.038 ** | Significant |
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Purnamawati, I.G.A.; Jie, F.; Hong, P.C.; Yuniarta, G.A. Analysis of Maximization Strategy Intangible Assets through the Speed of Innovation on Knowledge-Driven Business Performance Improvement. Economies 2022, 10, 149. https://doi.org/10.3390/economies10060149
Purnamawati IGA, Jie F, Hong PC, Yuniarta GA. Analysis of Maximization Strategy Intangible Assets through the Speed of Innovation on Knowledge-Driven Business Performance Improvement. Economies. 2022; 10(6):149. https://doi.org/10.3390/economies10060149
Chicago/Turabian StylePurnamawati, I Gusti Ayu, Ferry Jie, Puah Chin Hong, and Gede Adi Yuniarta. 2022. "Analysis of Maximization Strategy Intangible Assets through the Speed of Innovation on Knowledge-Driven Business Performance Improvement" Economies 10, no. 6: 149. https://doi.org/10.3390/economies10060149
APA StylePurnamawati, I. G. A., Jie, F., Hong, P. C., & Yuniarta, G. A. (2022). Analysis of Maximization Strategy Intangible Assets through the Speed of Innovation on Knowledge-Driven Business Performance Improvement. Economies, 10(6), 149. https://doi.org/10.3390/economies10060149