©15-ICIT 26-28711 in Malaysia
ST-4: Green Energy Management Paper :
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Reliability concerns the extent to which an experience, test or any measuring procedure yields the same results on repeated trials. The reliability of the factors needs to be determined to support any measures of
validity that may be employed. Both reliability tests and item analysis were recalculated without those seven items. Table. II lists the new Cronbach’s alpha values, ranging 0.867 to 0.912, after the seven items were
dropped. Generally, Cronbach’s alpha values in this study are greater than 0.6, revealing the high internal consistency.
Table 2: Factor Analysis Result: Green Practices
Dimension GSC practices
Item loading
range Eigenvalues
Cumulative percentage
Cronbach’s alpha
1. Helping suppliers to establish their own EMS PR1
0.829 2.
Use of alternative sources of energy PR2 0.810
3. Recovery of the companys end-of-life products PR3
0.806 4.
Use of waste of other companies PR4 0.737
5. Taking back packaging PR5
0.723 Product
recycling PR
6. Eco-labeling PR6
0.667 8.507
40.510 0.891
1. Taking environmental criteria into consideration EC1
0.761 2.
Choice of suppliers by environmental criteria EC2 0.727
3. Substitution of environmental questionable materials
EC3 0.723
4. Environment-friendly raw materials EC4
0.704 5.
Use of cleaner technology processes to make savings energy, water, wastes EC5
0.676 Environmental
compliance EC
6. Urgingpressuring suppliers to take environmental
actions EC6 0.602
2.465 52.247
0.867
1. Optimization of processes to reduce water use OPT1
0.891 Optimization
OPT 2.
Optimization of processes to reduce air emissions OPT2
0.856 1.809
60.862 0.912
3.3 Performance of the Manufacturing System MP
A measure of success in implementing any manufacturing systems or supply chain management can be defined along a few performance parameters. The companies were requested to indicate the performance of
their manufacturing system. The measures used were: 1= very poor, and 4 = very good. The results are summarized in Table 3. It can be deduced from the table that, in general, the respondents were satisfied with
the achievement of most of the objectives of the manufacturing systems implementation. On average above half of the respondents considered the performance of their systems to be good or very good. Product quality
improvement is the performance measures that were considered to be most satisfactory, whereas flexibility improvement was considered poor. Cronbach’s alpha values 0.843 of the manufacturing performances are
greater than 0.7, revealing the high internal consistency.
Table 3: Performance of manufacturing system
Relative Performance 1
2 3
4 Mean
sd
1. Product quality improvement
- 10
58 32
3.22 0.616
2. Work-in-progress reduction
- 6
80 14
3.08 0.444
3. Throughput time reduction
- 8
80 12
3.04 0.450
4. Lead time reduction
2 10
70 18
3.04 0.605
5. Machine utilization improvement
- 14
70 16
3.02 0.553
6. Manufacturing cost reduction
- 12
76 12
3.00 0.495
7. Flexibility improvement
- 16
74 10
2.94 0.512
N= 50, Cronbach’s Alpha = 0.843 Table 4 show the factor analysis result for manufacturing performance. The results of KMO show that the
compared value is 0.774, significantly exceeding the suggested minimum standard of 0.5 required for conducting factor analysis. The three variables were eliminated because their factor loadings were less than
0.5. The remaining 4 items, therefore, were re-analyzed which represented at least 66.935 percent of variances that can be denominated into two different factors. However, the correlation value 0.57 between
©15-ICIT 26-28711 in Malaysia
ST-4: Green Energy Management Paper :
04-07 P-
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the two groups is considered strong relationship and the 4 items were just extracted into one factor. With the new Cronbach’s alpha values 0.747, it was revealing the high internal consistency.
Table 4: Factor Analysis result: Manufacturing Performance
Dimension GSC practices
Item loading
range Eigenvalues
Cumulative percentage
Cronbach’ s alpha
1. Work-in-progress reduction MP1
0.883 2.
Throughput time reduction MP2 0.789
3. Product quality improvement MP3
0.754 3.676
52.518 Manufacturing
Performance MP
4. Flexibility improvement MP4
0.910 1.009
66.935 0.747
4.0 Structural Equation Modeling SEM
