Validity Test Behavior of Reading Nutrition Fact Label on Undergraduate Students of Bogor Agricultural University, Indonesia
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Private employee Additional
35 3
22,2 1,89
5 Income
1 million 1 million - 2,5 million
2,5 million - 5 million 34
63 61
21,5 39,8
38,6
Futhermore, There has been a lot of product purchase such as electronic equipment with the number of respondent was 25 at 15,8, Cosmetic with number of respondent 21 respondent
with 13,3 , CD 22 at 13,9, Book 27 at 17,1, souvenir 28 at 17,7 and bag, watch, dress 35 at 22,2. Based on the result research have also been know to visit the online
site name is rakuten .co.id with the number of respondent by 18 at 11,4, kaskus.com with
number of respondent by 25 at 15,8, tokobagus.com with number of respondent by 36 at 22,7,
berniaga.com. with number of respondent by 30 at 18,9, lazada.co.id with the number respondent by 21 at 13,3 and also bhinneka.com the number of respondent 28 by at
17,7.
Testing Hypothesis Multiple Linear Reggresion
In statistic, multiple linear regression analysis is a method used to draw a linear relationship between few independent variables and dependent variables.
Table 4. Coefficients of Multiple Regressions Model
Coefficients
a
Model Unstandarized
Coefficients Standarized
Coefficients B
Std Error Beta
T Sig.
Constant .251
.303 .386
.314 1.935
.148 .179
.135 .270
.302 .286
.130 2.051
2.162 2.342
.898 .047
.036 .025
In table 4, the unstandardized beta coefficient is used for the values of the numbers in the linear regression equation. Theory explains that a higher beta value indicates a greater impact of the
independent variable on the dependent variable. The independent variable Perceived Usefulness, Perceived Ease of Use, Purchase Intention, and Consumer Trust can be ranked according to the
magnitude of the beta coefficient to determine which component has the most significant . Therefore, the multiple regressions equation of this study is:
Y = 0,251+ 0.303 X
1
+ 0.386X
2
+ 0,314X
3
Based on the result obtained, that using behavioral online of the most significant impact on customer trust , as it has the highest beta value, followed by perceived ease of use, purchase
intention, and perceived usefulness.
Table 5. Model Summary of Multiple Regression Model Summary
Model R
R Square Adjusted
R Square
Std.Error of The Estimate
1 0,434
0,454 0,540
0,07106
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The R square or coefficient of determination is a portion of the total variation in the dependent variable that is explained by the variation in the independent variables.
Additionally, it helps to determine the percentage of variance in three dimensions Perceived Usefulness, Perceived Ease of Use, Purchase Intention which can significantly explain customer
trust. The values of multiple correlation coefficients R can lie only within the range from
–1 to +1. A perfect positive association will be reflected by the correlation of +1; a perfect negative
association will be reflected by the correlation of –1; and the absence of association will produce
a correlation of approximately zero. According to the model summary, R square is equal to 0.454, which is less than 1. This indicates
that there is a weak linear relationship between perceived ease of use, purchase intention, and perceived usefulness and customer trust. Approximately 45.4 of variance in all can
significantly explain to create customer trust. The finding suggests that aside from components, there are many other factors that might also effect customer trust. Because multiple R is positive
in value, it shows that there is positive linear relationship between perceived ease of use, purchase intention, and perceived usefulness and customer trust. Coefficients adjusted R square
shows how much the variable perceived ease of use, purchase intention, and perceived usefulness have effect on customer trust at shopping online. Adjusted R
2
is 54 while the remaining amount of 46 is the contribution of other variables.
Table 6. Anova
b
of Multiple Regressions F Test Anova
b
Model Sum of
Square Df
Mean Square
F Sig.
1 Regression
Residual Total
13.863 20.104
33.967 4
116 120
3.465 .173
18.270 ,0000
An analysis of variance ANOVA is used to test whether there is a significant linear relationship between the combination of the using behavioral intention and customer trust. Therefore, we can
see Table 6, the p-value is .000, indicating that the components significantly effect in consumer trust.
CONCLUSION Based on the analysis, conclusions as the following: variable perceived usefulness, perceived ease
of use, and purchase intention have a significant effect. However, if it views the results of hypothesis testing using the f test. Variable perceived usefulness, perceived ease of use, purchase
intention have effect and significance simultaneously on customer trust at business retail online. This is indicated by the value of F calculated by 18,270 and the significance level of 0.000, it
can be concluded that the regression model can be used to predict customer trust. Therefore, Ho is rejected and Ha accepted.
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The Impact of Transformational Leadership Dimensions on Organizational Innovation: A Case of Higher Education in
Iraq
HUSSAIN K. HUSSAIN
1
, NORAINI ABU TALIB
2
, ISHAK BIN MAD SHAH
3
Faculty of Management, Universiti Teknologi Malaysia, Johor Bahru, Malaysia
123
Scholarship cultural Relations Directorate, MOHESR, Baghdad, Iraq
1
Corresponding Author hussaink763yahoo.com
Abstract This research was carried out with the intention of examining the impact of transformational
leadership dimensions Idealized Influence Attribute, Idealized Influence Behavioral, Inspirational Motivation, Intellectual Stimulation, and Individualized Consideration on
organizational innovation in higher education in Iraq. The study used survey design to collect the data. The sample targeted 50 academic staff members from one university in Iraq selected
through random sampling technique to participate in this study. The statistic results found significant strong relationships between the transformational leadership dimensions and the
organizational innovation. More importantly, there are significant impacts of the transformational leadership on organizational innovation. In addition, transformational leadership plays important
roles in determining the organizational innovation. Leaders should consider in matching both leadership behaviors based on the situation of their subordinates. Thus, the study contributes to
the existing pool of knowledge on the empirical impact of transformational leadership dimensions on organizational innovation. Different aspects of these variables were tested, so as to provide a
wider and more comprehensive understanding of the factors that affect higher education in Iraq.
Keywords:
Transformational Leadership Dimensions, Organizational Innovation, and Higher Education