MAIN STUDY FINDINGS - The Effect between UN Global Compact, CSR and Business Performance of Mu

This chapter presents the main findings of the study. The data was empirically analysed by using SPSS 21 and SmartPLS 2 tools. This chapter contains correlation analysis, reliability and validity analysis result of the main study and lastly, regression analysis and SEM using SmartPLS with findings and discussion.

Correlations Analysis

Pearson’s coefficient correlation analysis was established to test whether multicollinearity problem exists in the model, this test was also conducted to examine the direction and the strength of linear relationship between variables. This research need to proceed this test because if the correlation exceed the threshold .75 is considered as problematic (Kennedy, 1989). The correlation table 5.1 shows there are five values that are greater than .75 (CSR-M with CSR-V, CSR-M with CSR-P, CSR-C with CSR-S, BP-PF with BP-PC and BP-PP with BP-PL). Therefore multicollinearity exists in the model, but the data has been validated by factor analysis, it can be assumed the data can still be used and the Pearson’s correlations values can be accepted. Researchers point out that multicollinearity does not affect the predictive power of equation of a model as a whole; it only affects the calculations regarding individual predictors (Khalaf, Månsson, & Shukur, 2013).

57 Table 5.1

Correlation Analysis (Main Study, N=154)

Note. GC-HR = Global Compact Human Rights; GC-L = Global Compact Labour; GC-E=

Global Compact Environment; GC-C = Global Compact Anti-corruption; CSR-M = Management systems, organization and processes; CSR-V = Vision, values and strategy;

CSR-P = Products and services; CSR-R = Resource and environmental management; CSR-S

= Stakeholder management; CSR-C = Communication, Reporting; BP-PF = Performance from financial perspective; BP-PC = Performance from customer perspective; BP-PP = Performance from internal business process perspective; BP-PL = Performance from learning and growth perspective.

Validity and Reliability Analysis

After refining the instrument through reliability and validity procedures in pilot study (refer to chapter 4), the researcher needs to run again the reliability and validity for the entire sample (n=154). For statistical validity the KMO and Bartlett’s test for Sphericity was conducted, refer to Table 5.2. KMO, the higher the value is to 1.0 the better will be data accounted variance explained. For Bartlett’s test for Sphericity, the smaller p-value is, the less likely that correlation between variables happened by chance. All KMO and Bartlett’s test values are provided below, all the values meet with minimum requirements for validity of the sample.

Table 5.2

KMO and Bartlett’s Test of Sphericity Values (Main Study N=154) Constructs Number of

Items KMO Variance

Explained Bartlett’s Test of Sphericity

UNGC 18 .840 67.43% 1620.392***

CSR 27 .923 73.28% 2930.786***

BP 15 .920 73.74% 1386.279***

Note. *** p < .001

UNGC= UN Global Compact; CSR= Corporate Social Responsibility; BP= Business Performance.

Table 5.3 below gives the reliability of scales found by analysis of the main sample.

Cronbach’s Alpha for each construct as follows: global compact (0.940); corporate social responsibility (0.903) and business performance (0.933) All reliabilities dimensions in this survey were higher than 0.900 (see Table 5.3); indicating that they all are higher that the acceptable level of 0.70 (Nunnally, 1978). Therefore, it indicates that the all constructs have a high level of internal consistency and reliability.

Table 5.3

Cronbach’s Alpha results for all dimensions (Main Study N=154) Constructs Number of items Cronbach’s Alpha

UNGC 18 0.909

CSR 27 0.903

BP 15 0.933

Next Cronbach’s Alpha for each individual variable in the dimensions observed in this study was conducted. The individual variables ranges between 0.933 to 0.695 in this study;

however, the researcher noted that Cronbach’s Alpha above 0.6 was also acceptable (see Table 5.4); indicating that they all are higher that the acceptable level of 0.6). Thus, it can be concluded that the scales for all constructs have a high level of internal consistency and reliability.

Table 5.4

Cronbach’s Alpha results for all variables (Main Study N=154)

Note. UNGC= UN Global Compact; CSR= Corporate Social Responsibility; BP= Business Performance

Dimensio

ns Variables No. of

Items Cronbach's alpha

UNGC Human Rights 3 0.695

Labour 5 0.728

Environment 5 0.891

Anti-Corruption 5 0.903

Total 18 0.909

CSR Management systems, organization and

processes 6 0.873

Resource and environmental management 2 0.811

Stakeholder management 5 0.861

Products and services 2 0.697

Vision, values and strategy 6 0.892

Communication, Reporting 6 0.933

Total 27 0.903

BP Performance from financial perspective 4 0.902

Performance from customer perspective 4 0.860 Performance from internal business process

perspective 3 0.757

Performance from learning and growth

perspective 4 0.806

Total 15 0.933

Partial Least Square (PLS) Analysis

This study uses The SmartPLS software to analyse and explain the result. SmartPLS is used for the assessment of reliability and validity of the measurement model, and the assessment of the path coefficients of structural model of the main study. After comparing the pilot study and the main study result, the researcher found there is difference in results. Thus for further investigation researcher decide to separate the data according to industries to two groups: the IT industry and other industries. The difference of PLS analysis within these two groups are then presented.

Validity and Reliability

This research uses Cronbach’s alpha in SPSS and PLS approach to assess the measurement model (outer model). Individual item reliabilities were evaluated by examining the loadings of the measures with their corresponding construct. The model was again tested the validity and reliability using SmartPLS tool in order to observe convergent validity, composite reliability and average variance extracted were examined. For composite reliability, a minimum value of .70 is recommended (Nunnally & Bernstein, 1994). The study showed that the composite reliabilities values exceed the threshold value, as could be seen in table 5.5 next page.

Average variance extracted (AVE) determines the variance captured by the indicators relative to the measurement error. According to Hair, Tatham, & Anderson (2006) AVE values should be greater than the .50 minimum necessary to justify the use of a construct.

Given that all the values are greater than .50, it can be concluded that the data meet the convergent validity. Individual item reliabilities were computed by examining the loadings.

Loadings of 0.5 or greater are acceptable if there exists additional indicators for describing the latent construct (Chin, 1998). Therefore, items with loadings of 0.5 or greater are maintained. From Table 5.6, all loadings were greater than 0.713. According to results from SPSS and PLS tests, all the minimum requirement of reliability and validity tests were met.

61 Table 5.5

Measurement Model Results (Main Study N=154)

Constructs Number of items Composite Reliability R² (%) AVE

UNGC 18 0.8589 0.6045

CSR 27 0.9388 0.613 0.7198

BP 15 0.9227 0.323 0.7495

Note. UNGC= UN Global Compact; CSR= Corporate Social Responsibility; BP= Business Performance.

Table 5.6

PLS Loadings (Main Study, N=154)

Items Loadings Items Loadings Items Loadings

Note. GC-HR = Global Compact Human Rights; GC-L = Global Compact Labour; GC-E=

Global Compact Environment; GC-C = Global Compact Anti-corruption; CSR-M = Management systems, organization and processes; CSR-V = Vision, values and strategy;

CSR-P = Products and services; CSR-R = Resource and environmental management; CSR-S

Testing Measurement Model

Through the use of PLS tools, the researcher can compute the path coefficients. Hair et al. (2006) indicate that the individual path coefficients in the PLS structural model can be interpreted as the standardized beta coefficient in ordinary regressions. In addition, each of the path coefficients significance value can be determined by means of the bootstrapping procedures, using the t-value. The casual relationship between variables can thus be assessed. In order to evaluate the statistical significance of the loadings and the path coefficients (standardized betas), the bootstrapping 40x method was used to test the significance of the path coefficients.

The results of the multivariate test of the structural model are presented in Table 5.7 and clearly configured in Figure 5.1. The structural model as whole explained 61% and 32%, of the variance in UNGC, CSR and business performance, refer to Figure 5.1.

For the explanatory power (R²) researcher can conclude that this model explained a substantial percentage of the variance in which all the independent variables can explain the dependent variables (Nunnally & Bernstein, 1994). UNGC can explain 63% of CSR and CSR can explain 35% of business performance. These numbers are large enough to have the relevance in the model.

Table 5.7 demonstrates the result of PLS testing and it also shows that all path coefficients for variables are significant. Hair, Ringle, & Sarstedt (2011) state that critical t-values for the two-tailed test are 1.65, 1.96 and 2.58, representing weak, moderate and strong.

The casual relationship between variable=s can thus be assessed. Therefore to the effects of each variable, the results showed that there is a positive significant effect between UNGC to CSR (ß = .783, t = 13.373, p < .001). Thus null hypothesis 1 was rejected. CSR has positive significant effects towards business performance (ß = .608, t = 7.475, p < .001) therefore null hypotheses 2 was rejected. The results show that all of dimensions have positive influences that rejected the null hypotheses.

Table 5.7

PLS Path Analysis Results (Main Study N=154)

Note. * p < .1, ** p < .05, *** p < .001

UNGC= UN Global Compact; CSR= Corporate Social Responsibility; BP= Business Performance.

Path Hypothesis β-path Adj.

t-value Sig. Direction Reject Null Hypotheses

UNGCàCSR H1 0.783 13.373 *** + Reject

CSRàBP H2 0.608 7.475 *** + Reject

Performance from financial perspective (PF) .805***(8.709)

Performance from customer perspective (PC) .875***(15.618)

Performance from internal business process perspective (PP) .851***(12.401)

Performance from learning and growth perspective (PL) .857***(18.325)

Figure 5.1 PLS structural model (main study, N=154).

Note: * p < .1, ** p < .05, *** p < .001

The result of PLS findings shows that UNGC have a significant positive effect on CSR, in which corporate social responsibility also has a significant positive effect on business performance. This research can conclude that all null hypotheses proposed in the beginning chapter are rejected. Table 5.8 summarizes the research results.

Table 5.8

Research Hypotheses Results

Null Hypotheses Outcome

H1 Global compact have no effect on CSR. Rejected

H2 CSR have no effect on Business Performance. Rejected

Focus only at the UNGC dimension, the dominant factor of the global compact in terms of context that affect this dimension most is environmental principle. It follows by anti-corruption, human rights and the last labour principle. The dominant factor of CSR is vision, values and strategy. It followed by products and services; management systems, organization and processes; Communication, reporting; stakeholder management and resource and environmental management. Within business performance variable, performance from customer perspective is the dominant factor, which is followed by performance from learning and growth perspective, performance from internal business process perspective and the last performance from financial perspective.

Comparisons Study of IT industry and Other Industries

By comparing the PLS results from pilot study and main study, there are some noteworthy points between the results. Within build GCSR model the UNGC and business performance dimensions have same results. On the other hand, within the CSR variable, the dominant factors between two results are different. In pilot study, the dominant factor is management systems, organization and processes, while in the main study the dominant factor is vision, values and strategy. Moreover, within corporate social responsibility the second dominant factor is communication, reporting in pilot study, where in main study it is products and services. Since these two results are not consistent like the other factors, it is important to investigate further in order to give a whole understanding of CSR in this study.

The data gathered in pilot and main study has different main characteristics that may explain the differences in results. The pilot study has balanced number of respondents in industry category. On the contrary, the total of 154 the majority of respondents were from IT industry with 33% and the rest consist in total 67%. The researcher separate the data according to the findings, the data are then being analyzed again by using PLS method.

IT industry

Table 5.9 showed the result for the PLS testing for main study IT industry. The result shows that within CSR variable, the dominant factor is vision, values and strategy. It followed by products and services. In terms of UNGC, the dominant factor is environment, followed by anti-corruption. Within business performance variable, performance from learning and growth perspective is the dominant factor, which followed by performance from financial perspective.

Table 5.9

PLS Path Analysis Result (IT industry, N=51)

Note. * p < .1, ** p < .05, *** p < .001

UNGC= UN Global Compact; CSR= Corporate Social Responsibility; BP= Business Performance.

Path Hypothesis β-path Adj.

t-value Sig. Direction Reject Null Hypotheses

UNGCàCSR H1 0.768 12.988 *** + Reject

CSRàBP H2 0.597 6.171 *** + Reject

66 Table 5.10

PLS Loadings (IT industry, N=51)

Items Loadings Items Loadings Items Loadings

GC-HR 0.752 CSR-V 0.841 BP-PF 0.836

GC-L 0.716 CSR-M 0.771 BP-PC 0.912

GC-E 0.823 CSR-P 0.833 BP-PP 0.858

GC-C 0.767 CSR-R 0.679 BP-PL 0.858

CSR-S 0.814 CSR-C 0.821

Note. GC-HR = Global Compact Human Rights; GC-L = Global Compact Labour; GC-E=

Global Compact Environment; GC-C = Global Compact Anti-corruption; CSR-M = Management systems, organization and processes; CSR-V = Vision, values and strategy;

CSR-P = Products and services; CSR-R = Resource and environmental management; CSR-S

Performance from financial perspective (PF) .805***(13.023)

Performance from customer perspective (PC) .875***(26.797)

Performance from internal business process perspective (PP) .851***(17.277)

Performance from learning and growth perspective (PL) .857***(26.421)

Figure 5.2 PLS structural model (IT industry, N=51).

Note: * p < .1, ** p < .05, *** p < .001

68 Other Industries

Table 5.11 showed the result for the PLS testing for main studies other industries. The result shows that within CSR variable, the dominant factor is management systems, organization and processes. It followed by vision, values and strategy. In terms of UNGC, the dominant factor is environment; followed by anti-corruption, therefore in this dimension it has same result as in IT industry. However, within business performance dimension, performance from learning and growth perspective is the dominant factor, which followed by performance from customer perspective.

Table 5.11

PLS Path Analysis Result (other industries, N=103)

Note. * p < .1, ** p < .05, *** p < .001

UNGC= UN Global Compact; CSR= Corporate Social Responsibility; BP= Business Performance.

Table 5.12

PLS Loadings (other industries, N=103)

Items Loadings Items Loadings Items Loadings

GC-HR 0.708 CSR-V 0.857 BP-PF 0.755

GC-L 0.569 CSR-M 0.869 BP-PC 0.839

GC-E 0.780 CSR-P 0.776 BP-PP 0.807

GC-C 0.726 CSR-R 0.662 BP-PL 0.842

CSR-S 0.729 CSR-C 0.808

Note. GC-HR = Global Compact Human Rights; GC-L = Global Compact Labour; GC-E=

Global Compact Environment; GC-C = Global Compact Anti-corruption; CSR-M = Management systems, organization and processes; CSR-V = Vision, values and strategy;

CSR-P = Products and services; CSR-R = Resource and environmental management; CSR-S

Path Hypothesis β-path Adj.

t-value Sig. Direction Reject Null Hypotheses

UNGCàCSR H1 0.769 11.664 *** + Reject

CSRàBP H2 0.513 5.257 *** + Reject

Performance from financial perspective (PF) .756***(4.501)

Performance from customer perspective (PC) .840***(6.651)

Performance from internal business process perspective (PP) .806***(9.046)

Performance from learning and growth perspective (PL) .843***(12.367)

Figure 5.3 PLS structural model (other industries, N=103).

Note: * p < .1, ** p < .05, *** p < .001

PLS Findings Discussion

Results obtained from this chapter suggest several important characteristics. First, the highest path coefficient in the GSCR Model is between UNGC and CSR (ß = .783). The dominance of this path in the overall model implies that UNGC principles are the key factor to CSR and business performance. The more a is company aware of UNGC principles and apply them in terms of environment and anti-corruption principles, the more effective can be company in tackling CSR. According to the result, it will then make a positive contribution to the business performance.

Second, looking only at the UNGC variable, the dominant factor of the UNGC dimension is environment principle. In comparison between IT industry and the other industries the dominant factor remain same for both of them. It is followed by anti-corruption principle. This suggests that the best way to follow the UNGC principles is to increase the effort focused on environmental principles and issues within companies. This means, in concrete terms that managers should be counseled to promote company’s commitment and responsibility in terms of environment and anti-corruption principles order to build up CSR awareness. Environmental principle is also important these days, because society has now high demand for environmental behavior from firms and it is more apparent now than it was in Taiwan’s industrial period. Results also showed that multinational companies have high priority on anti-corruption principles so Taiwan policy makers should be aware to improve regulations in terms of anti-corruption. Two other principles (human rights and labour) have lower impact but it’s for discussion why are these two principles less important for companies. Therefore Taiwan companies should more work on human rights principles and labour principle awareness.

Looking at CSR dimension the study can perceive that biggest priority for organizations are vision, values and strategy; followed by management systems, organization and processes within and organization products and services. This result suggests that in order to have higher CSR, companies should be aware of their vision, values and strategy.

With importance of management systems, organization and processes as second highest priority companies researcher can imply that organizations have high priority to have sustainability responsibilities defined and there is visibility and integration of sustainability in core processes within companies. This creates competitive advantage than can be achieved through internal resources or a group of internal resources from the firm. Products and services also effect corporate social responsibility in high manner. Results also showed that

organizations lack in resource and environmental management reporting, that should be in focus for companies.

Third, there is a positive and highly significant relationship between CSR and business performance. To have higher business performance, company should look to improve vision, values and strategy in CSR performance. For business performance, the performance from customer perspective has the highest influence among four aspects measuring business performance. This indicates that customer satisfaction; ability to gain contracts and market share has highest influence for organizational performance.

Fourth, looking at the comparisons between IT industry and other industries, the result implied that for IT industry is more important vision, values and strategy followed by products and services. CSR of IT industry has also higher impact on business performance than other industries. For other industries within CSR variable, the dominant factor is management systems, organization and processes, then followed by vision, values and strategy. In business performance for IT industry is more important performance from learning and growth perspective and financial perspective. In other industries performance from learning and growth perspective is the dominant factor, which followed by performance from customer perspective. We can conclude that for both groups the productivity, freedom, satisfaction and motivation for employees are very important, but for IT is also financial perspective very important.

CHAPTER VI CONCLUSIONS AND

在文檔中 The Effect between UN Global Compact, CSR and Business Performance of Multinational Companies in Taiwan (頁 63-79)