Table 1 Measurement constructs of environmental management control tools. Focus Operational level Strategic level Environmental management control tools (9 factors) ° environmental management accounting (EMA) ° the eco products-related costing (Eco-products) °the use of environmental indicators (UEI) °Action controls° Results controls ° Cultural controls °Personnel controls °Environmental decision making (EDM) ° Supply chain management (Suppliers) “Personnel controls,” “EDM” and “suppliers” as mentioned above are separate environmental management control tools (factors) in the analytical model. The framework of the questionnaire was designed from these nine factors (see Table 1). The specific questions included for each factor were mainly cited from the following eight empirical studies: Ferreira et al. (2010), Goebel and Weissenberger (2017), Henri and Journeault (2010), Journeault (2016), Journeault et al. (2016), Perego and Hartmann (2009), Pondeville et al. (2013) and Widener (2007) on a five-point Likert scale (see Table 2). following two steps. Regarding the measurement of SCP, to represent the SCP variable, the questionnaire asked about the status of SCP, i.e., whether the company had incorporated or was planning to incorporate sustainable consumption and production into its business activity targets (1: yes, 2: no). We employed companies’ self-evaluation on waste reduction as their environmental-performance-related SCP. The analysis conducted in this study consisted of the In Step 1 we tested whether our data replicated the elements environmental management tools. We then conducted exploratory factor analysis (EFA) to assess the elements of EMCS. from EMCS In Step 2, to investigate whether the elements of the EMCS and other environmental management tools verified in Step 1 could support the implementation of SCP and improve environmental performance, we employed MGSEM. Structural equation modeling (SEM) is a powerful statistical technique that combines a measurement model, or confirmatory factor analysis, and a structural model into a simultaneous statistical test (Hoe, 2008). It is particularly valuable in inferential data analysis and hypothesis testing where the pattern of inter-relationships among the study constructs are specified a priori and grounded in established theory. It has the flexibility to model relationships among multiple predictor and criterion variables, and statistically tests a priori theoretical assumptions against empirical data through CFA (Chin, 1998). In most cases, SEM is applied to the testing of causal relationships among variables Environmental Management Control Tools for Promoting SCP in Thai and Vietnamese Companies Categories of environmental management Environmental management accountingEnvironmental management control systemEnvironmental management systemincluded as nine and other in Vietnam. Regarding the 53 2.2 Analytical Methods (Hoe, 2008). It is also possible to estimate and compare models that come from two or more samples, called MGSEM (Sörbom, 1974). To compare Thai and Vietnamese companies, MGSEM was performed to examine the differences between the countries’ models using AMOS (Ver. 27.0). EFA (principal components with promax rotation) was performed on the questionnaire items. Hair et al. (1995) assumed the following multiple extraction rules with an eigenvalue ≥ 1.0, Kaiser-Meyer-Olkin (KMO) index > 0.5 (Cerny & Kaiser, 1977), and communality > 0.5 to determine factor extraction. The eigenvalue measures how much of the variance of the observed variables a factor explains. The value ≥1.0 explains more variance than a single observed variable. The KMO index ranges from 0 to 1, with 0.5 considered suitable for factor analysis. The communality is a definition of common variance that ranges between 0 and 1. Values closer to 1 suggest that the extracted factors explain more of the variance of an individual item. The acceptance of each item was decided based on a factor loading of 0.5 or more and a difference in cross-loadings of greater than 0.2 (Kaiser & Rice, 1974). As a result, eight factors were successfully extracted. Table 2 presents final descriptive statistics for each item. To clarify the impact of each EMCS element on SCP and the impact of SCP on environmental performance, MGSEM was performed with SCP and waste reduction as the dependent variable. The independent variables were the individual EMCS elements, Action controls, Results controls, Cultural controls, Personnel controls, EMA, supplier, EDM and UEI. The results are shown in Fig. 1. The model’s fitting showed a sufficient value (χ2 = 1.758, p < 0.001, df = 1362, CFI = 0.928, RMSEA = 0.040). Towards the implementation of SCP in Thailand, action controls are negatively significant and result controls are positively significant. There are no significant EMCA elements the other elements, only EMA is significantly positive for SCP in 3.2 MGSEM Results 3. Results and Discussion 3.1 EFA Results
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