3. Research method
This study uses quantitative research with the explanatory survey method. In this method, hypotheses are tested by a relevant statistical analysis technique. The explanatory survey method is applied to find cause-effect relationships and test influence of independent variables on dependent variables (Sekaran & Bougie, 2016). The sample is all SOEs, which are 113 companies in Indonesia. Samples are taken by using simple random sampling. This study collected questionnaires from company directors and commissioners. The study data are collected from questionnaires using Likert Scale 1-5 with such grades, which are 1= strongly disagree to 5= strongly agree. Data are analysed by the descriptive analysis of respondent characteristics and the Partial Least Square (PLS) analysis. The descriptive analyses of respondent characteristics are conducted by applying SmartPLS 3rd version (Indriyanto & Supomo, 2002).

4. Results
To test the validity and reliability, the outer model involves tests of discriminant validity, and composite reliability. Table 1 reveals that all indicators have loading factor values >0.7 and all constructs have AVE >0.5. Therefore, convergent validity is accepted as required. Second, the discriminant validity is tested by the square root of AVE, the Fornell-Larcker Criterion (Garson, 2016). As AVE square root values of all latent variables are higher than those of all correlations with other variables. Furthermore, the composite reliability test by Cronbach's alpha results shows that all constructs meet criteria of composite reliability. Table 1 discloses the Cronbach’s alpha of 0.991 >0.7 and composite reliability of 0.991 >0.7. All measures confirm that the model is valid and reliable.
Table 1
Discriminant Validity and Cronbach’s alpha
Variable SCG PERF BE BS Cronbach’s alpha
SCG 0.901 0.990
PERF 0.834 0.923 0.991
BE 0.795 0.871 0.898 0.986
BS 0.670 0.832 0.697 0.936 0.984
Valid: √AVE>r; √AVE PERF=0.923; √AVE SCG>0.901; √AVE BE=0.898; √AVE BS=0.936

To examine Goodness of Fit, this study uses the R Square, Q Square, and Standardized Root Mean Square Residual (SRMR) values to assess the goodness of fit. Chin (1998) argues that the R square value of 0.67 shows a strong model; 0.33 moderate, and 0.19 weak. Q square value is categorized by small, moderate, and big. Q square value is 0.02, it is small, Q square is 0.15 medium, Q square is 0.35, big. SRMR explains good fit, with perfect fit model if SRMR0.10. Table 2 reveals the goodness of fit of this research supported by strong and moderate endogen variables (R Square) big Q Square and fit (SRMR 0.08 – 0.10).
Table 2
Goodness of Fit
Endogen Variable Goodness of Fit Model Parameter
R Square Q Square SRMR
KIN 0.882 0.743 0.045
SB 0.522 0.451
R-Square: 0.67 strong; 0.33 moderate; 0.19 weak. Q-square: 0.02 small; 0.15 medium; 0.35 big. SRMR: <0.10 fit

Moreover, adjusted R-Square shows the determination coefficient which describes contributions of all exogen and endogen variables. Table 2 reveals that the adjusted R-Square of the performance is 0.878. This means that 87,8% the Company performance is affected by business environment, supply chain governance, and business strategy, and the rest 12,8% the Company performance is influenced by other variables. Furthermore, the business environment and supply chain governance contribute 51.1% to the business strategy, and the rest of 48.9% affected by other variables as represented by the value of the adjusted R-square.
Table 3
Direct Effect
Path Path Coefficient T statistics (|O/STDEV|) p-values
SCG → PERF 0.266 3.624 0.000
SCG → BS 0.317 2.808 0.005
BE → PERF 0.397 4.898 0.000
BE → BS 0.445 3.494 0.001
BS → PERF 0.377 4,873 0.000
Significance Level 5%; significant path coefficient if p-value1.96

As to examine the direct effects, Table 3 shows direct effect and significance test results. The analysis with path found the influence of business environment on business performance (BE  PERF, p-value is 0.000 with T-stat. = 4.898 and positive path coefficient of 0.397. Because the results showed the value is acceptable by using the criteria of p-value1.96, and positive path coefficient, so that business environment has positive influence and significance on the business performance. Thus, the first hypothesis was accepted. Path analysis also showed the influence of supply chain governance on business performance (SCG  PERF), p-value is 0.000. with T-stat. = 3.624, and positive path coefficient (0.266). The path analysis results confirmed that the value is acceptable by using the criteria of p-value1.96, and positive path coefficient. Thus, the second hypothesis stating that supply chain governance has positive influence and significance on the business performance was accepted. Regarding the influence of the business environment on business strategy (BE  BS), the results showed that p-value is 0.001 (1.96), and a positive path coefficient of 0.445. This confirms that the business environment has a positive influence and significance on the business strategy. Thus, the third hypothesis was accepted. Moreover, path analysis showed the influence of supply chain governance on business strategy (SCG  BS), p-value is 0.005 with T-stat. = 2.808, path coefficient is 0.317. Compared with the acceptance limit by using the criteria of p-value 1.96, and positive path coefficient, the results confirmed that supply chain governance has positive influence and significance on business strategy. Therefore, the fourth hypothesis was accepted. Lastly, the path results showed the influence of business strategy on company performance (BS  PERF), indicated by p-value is 0.000 (1.96), and path coefficient (+)0.377. Thus, the fifth hypothesis stating that business strategy has positive influence and significance on the business performance was accepted.

Table 4
Indirect Effect
Indirect Path Indirect Path Coefficient T-statistics p-values
BE → BE → PERF 0.168 2.638 0.009
SCG → BS → PERF 0.119 2.250 0.025
Significance level 5%; significant path coefficient if p-value1.96

Furthermore, to examine the indirect effect, in this study, the business strategy is the intervening variable, which mediates influence of business environment and supply chain governance on the company performance. To test the contribution of this business strategy in mediating those variables, indirect influence is tested by specific indirect effect PLS analysis. Table 4 reveals that the indirect effect p-value business environment and supply chain governance on the company performance through business strategy. First on the path of business environment indirect effect to the company performance through the business strategy, the test results in p-value is 0.0091.96. This concludes that business strategy is significant in mediating indirect influence of the business environment on the company performance. Thus, the seventh hypothesis highlighting the mediating effect of business strategy on business environment and the performance is accepted. Second, on the indirect effect of supply chain governance on the Company performance through the business strategy, p-value is 0.0251.96. This means that the business strategy significantly mediates indirect supply chain governance on the performance. Thus, the seventh hypothesis highlighting the mediating effect of business strategy on supply chain governance and the performance is accepted.

Table 5
Hypothesis Test Results
No Hhypotheses Results Conclusions
1 Business environment has a significant effect on business strategy Path coefficient= 0.445; t-stat.= 3.494; p-value= 0.001 Accepted
2 Supply chain governance has a significant effect on business strategy Path coefficient= 0.317; t-stat.= 2.808; p-value= 0.005 Accepted
3 Business strategy has a significant effect on company performance Path coefficient= 0.397; t-stat.= 4.898; p-value= 0.000 Accepted
4 Supply chain governance has a significant effect on company performance Path coefficient= 0.266, t-stat.= 3.624; p-value= 0.000 Accepted
5 Business strategy has a significant effect on company performance Path coefficient= 0.377, t-stat.= 4.873; p-value= 0.000 Accepted
6 Business strategy mediates the relationship of business environment on company performance Path coefficient= 0.168, t-stat.= 2.638; p-value= 0.009 Accepted
7 Business strategy mediates the relationship of supply chain governance on company performance Path coefficient= 0.119; t-stat.= 2.250; p-value= 0.025 Accepted
Significance Level 5%; hypothesis is accepted if p-value1.96 (two tail test)


Fig. 1. Estimated Result of PLS Model – Bootstrapping
5. Conclusion
The study concludes that the business environment has a positive and significant effect on business strategy, and supply chain governance has a positive and significant effect on business strategy. Moreover, the results showed that the business environment influences corporate performance, and supply chain governance influences corporate performance. Business strategy influences corporate performance, and business strategy can mediate the influence of the business environment on corporate performance. Lastly, business strategy can mediate the influence of supply chain governance on corporate performance. Statistically, the the results showed that the path coefficient measuring influence of business environment on performance is 0.397, and that of supply chain governance on performance is 0.266; and that of business strategy on performance is 0.377. This means that the most influenced variables on the company performance are business environment and business strategy, besides supply chain governance. Furthermore, business environment affects strongly relative to supply chain governance on business strategy as path coefficient of business environment on business strategy is greater (0.445) that of supply chain governance on business strategy (0.317). This study suggests company management and governments to improve performance of SOEs. First, regarding the business environment, the company should have qualified human resources who meet competence standards, a consistent reward and punishment system, commitment, and quick response to latest technologies. In the supply chain governance, company management should develop risk-management and effective internal controls to create more agile supply chain management. In terms of the business strategy, quick response of emerging market changes, new product development, new brand development, and cost efficiency of production must be considered as the business strategy. Regarding company performance, the management needs to estimate, do best, monitor periodically on sales growth, net profit, return on equity (ROE), return on asset (ROA), and return on investment (ROI). As one of the specific items in supply chain governance, particularly for state companies, government and regulators are advised to restructure the organizations to make the companies more agile in doing their businesses, to measure burden and costs of the companies in conducting public service obligations required by the government. For future research, it is hoped that next research examines different models of research which can be developed by considering other independent and intervening variables which may affect company performance. Some variables such as company capabilities and transformational leadership can be considered to have influence on the business strategy and performance.

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