This research follows a positivist paradigm, employing a quantitative methodology. The population of this study is ICT employees working in Malaysia Digital (MD) Status active companies based on the Malaysia Digital Economy Corporation (MDEC). For this study, only 10 companies were selected by generating random numbers in an Excel spreadsheet using the randbetween(x,y) function. According to Teddlie and Yu (2007), "probability samples aim to achieve representativeness, which is the degree to which the sample accurately represents the entire population." The company names on the list will match the numbers from x to y. Data collection is carried out through onsite-administered questionnaires featuring close-ended questions. Responses were measured using a 5-point Likert scale, a method recognized for its ease of use and clarity for respondents (Drumm, et al., 2022). Table 1 outlines the research design elements utilized in this study.
Table 1: Research design elements.
DATA ANALYSIS
SmartPLS 4.0 was utilized in this study to develop and analyze the proposed model. The data analysis process in SmartPLS comprises of the measurement model evaluation and structural model evaluation (Hair et al., 2020; Urbach & Ahlemann, 2010).
Measurement Model Evaluation
Prior to investigating the relationships among the constructs, it is essential to evaluate the measurement model to confirm its reliability and validity (Cheung et al., 2023; Hair et al., 2020). Indicator reliability is evaluated by examining the factor loading values. According to Hair et al. (2011), a general rule is to consider factor loadings of 0.7 or higher acceptable. However, for exploratory research designs, Chin (2010) suggests that factor loadings between 0.5 and 0.6 are deemed satisfactory. In this research, the initial evaluation showed that several constructs did not achieve the recommended levels for average variance extracted (AVE), which should be above 0.5. To address this, items with low factor loadings were eliminated to improve both internal consistency reliability and convergent validity (Hair et al., 2021). Table 2 depicts the factor loadings that meet the recommended threshold, thereby confirming the reliability of the indicators. As for internal consistency reliability, it is deemed to be adequate when the composite reliability (CR) is valued above 0.7. Convergent validity, on the other hand, is deemed to be satisfactory when the AVE is valued above 0.5. Table 2 confirms that both internal consistency reliability and convergent validity are satisfactory. Figure 2 depicts the measurement model of the study.
Table 2: Factor loadings of items, CR, and AVE values.
To assess discriminant validity, the Fornell-Larcker criterion was applied. Discriminant validity is determined by examining correlations between overlapping measures to identify the degree to which items distinguish between constructs (Ramayah et al., 2018). Table 3 confirms that discriminant validity is adequate.
Table 3: Fornell-Larcker criterion in assessing discriminant validity.
Structural Model Evaluation
Figure 3 depicts the structural model generated using SmartPLS 4 after performing a non-parametric bootstrapping with a sample size of 5000.
Table 4 shows the path coefficients of the structural model. For the beta value to significantly influence the research model, it needed to be at least 0.1, while the t-statistic value had to exceed 1.645. Optimism, innovativeness, and insecurity showed significant relationships with attitude. However, discomfort did not show a significant relationship with attitude. The same goes to the relationship between PBC and intention. However, attitude and subjective norm both showed significant relationships with intention.
Table 4: Path coefficients.
The study also examined whether attitude mediated the relationship between the independent variables and intention to implement Green IS. The results of the mediation testing are presented in Table 5. The analysis suggests that attitude mediates the relationship between optimism, insecurity, and innovativeness and intention to implement Green IS. However, discomfort was not supported in mediation testing.
Table 5: Mediation analysis.