CHAPTER 1 INTRODUCTION
3.8 Measurement of the Variable
30 C Competitive advantage (DV)
1. I need to prepare myself with a competitive advantage in order to be more confident, dedicated, and able to improve my performance.
2. I acknowledge that competitive advantage will have a positive effect on myself because of efficiency and opportunities that are better used.
3. I believe that the competitive advantage can overcome others in the competition if I master some skills.
4. I need to improve my competitive advantage to achieve marketability in the employment industry.
5. Hard skills and soft skills can increase the competitive advantages of a person.
5 Chen and Chang (2013)
condition of an independent variable (IV). In a study, variables are measured at four different levels. According to Cohen et al. (2000), the type of measurement a researcher employs is crucial in deciding the kind of analyses to be performed. Researchers can include nominal, ordinal, interval, and ratio level measures. As for our research, our team will only utilize two measurement variables: nominal level and interval level.
3.8.1 Nominal level
The nominal measurement level categorizes variables according to qualitative labels or names. These labels and groupings have no order or hierarchy to them (Stevens, E., 2022). For instance, by offering respondents the choice of M (male) or F (female), the researcher can recognize the respondent's gender. In addition, the researcher can learn the respondent's details by simply including the option in the questionnaire.
3.8.2 Interval level
Interval scale is a numerical scale that labels and orders variables, with a known, evenly spaced interval between each of the values (Stevens, E., 2022). The interval scale's most challenging feature is likely the absence of a true zero. For example, when evaluating temperatures in Celsius, such as 20–40 and 40–60 degrees, there is order, and the difference between the variables has significance;
however, zero occurrences are meaningless.
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32 3.9 Procedure for Data Analysis
Using a questionnaire for our research, we will collect the data from the respondents.
The information will be examined utilizing Statistical Package for the Social Sciences (SPSS) program. Most researchers use SPSS, a popular software, to examine data and execute statistical tests. Because it is user-friendly, SPSS software enables researchers to be more versatile when studying the research plan (D'Amico, Neilands & Zambarano, 2001). Additionally, SPSS allows researchers to create calculated reports, diagrams, distribution graphs, frequency tables, and advanced statistical analyses using their gathered data. Additionally, SPSS software aids researchers with data calculations, allowing them to handle the data they have collected expeditiously and to do so without making any errors due to confusion.
3.9.1 Descriptive Analysis
Descriptive studies are conducted to comprehend the profile of any company that corresponds to a particular standard of conduct (Verma, J. P., 2015). The researchers can quickly and easily review the respondents' demographic data thanks to this analysis. Using SPSS, the information gathered from respondents via a questionnaire can be examined and evaluated.
3.9.2 Reliability Test and Validity Test
Validity test is concerned with a measure's correctness, while reliability test is concerned with its continuity (Middleton, F., 2019). How consistently a technique assesses something is referred to as its reliability. The measurement is regarded as trustworthy when the same results can be repeatedly obtained by using the same
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techniques under the same conditions. How well a technique assesses what it is supposed to assess is known as its validity. High consistency is one sign of reliable measurement. A technique is probably invalid if it is not trustworthy.
3.9.3 Pearson Correlation Analysis
The intensity and direction of a link between two variables are indicated by a correlation coefficient, which is a number between -1 and 1. It assigns a number between -1 and 1, with 0 indicating no correlation, 1 indicating a total positive correlation, and -1 indicating an absolute negative correlation (Nettleton, D.,2014).
To evaluate correlation strength from the value of the correlation coefficient, use the table below as a general guideline.
Table 3.1: General guideline for correlation coefficient evaluation.
Correlation coefficient Correlation strength Correlation type
-0.7 to -1 Very strong Negative
-0.5 to -0.7 Strong Negative
-0.3 to -0.5 Moderate Negative
0 to -0.3 Weak Negative
0 None Zero
0 to 0.3 Weak Positive
0.3 to 0.5 Moderate Positive
0.5 to 0.7 Strong Positive
0.7 to 1 Very strong Positive
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Pearson's correlation coefficient (r) determines the degree to which the independent and dependent variables are correlated. While a negative correlation indicates a negative link, a positive correlation denotes a favorable relationship between the independent factors and dependent variables. There is a stronger association between independent factors and dependent variables when the correlation coefficient (r) is more significant.
3.9.4 Regression Analysis
Regression analysis is a group of statistical techniques employed to calculate associations between a dependent variable and one or more independent variables (C. Angelini, 2019). It can be used to simulate the long-term link between variables and gauge how strongly their relationships are related. Regression analysis comes in a variety of forms, including multiple linear, nonlinear, and linear. Simple linear and multiple linear models are the most prevalent and useful models. For more complex data sets where the connection between the dependent and independent variables is nonlinear, non-linear regression analysis is frequently used.
3.9.5 Pilot Test
According to Porta (2008), a pilot study is, “A small-scale test of the methods and procedures to be used on a larger scale”. In the Pilot study, George and Gordon (2010) suggested 10 to 30 participants for the pilot in the survey. Therefore, in this study, the researcher decides to use 30 participants in the pilot study.