RESUMEN
Developing nations have motivated contemporary manufacturing companies to embrace green innovation and focus on smart technology that is sustainable to harness the growing economy and uplift the people. Although, scientific research in this direction has been neglected, and at the same time there are challenges to the attainment while meeting the need of the people. This study aims to investigate the impact of Industry 4.0, open innovation and green innovation performance on green innovation behaviour. To this end, a theoretical model was established. A quantitative research approach was applied in which survey data were utilized to capture 247 responses from different manufacturing companies in Malaysia. The model was tested using SmartPLSver3.0 to measure the structural relationship between variables. The findings indicate that Industry 4.0 and green innovation performance positively impact green innovation behaviour, compared to open innovation which has no impact. The impact of green innovation performance is found to be stronger when compared to Industry 4.0 and open innovation. Likewise, green innovation performance exhibits a substantial mediating impact between the exogenous variables and green innovation behaviour. The policy implication and conclusions are further discussed in the last section of the study.
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Introduction: Depression and obesity are the main threat among women which have been considered by many research scholars in psychology studies. In their analysis for measuring and estimating obesity and depression they were involving statistical functions. Methods: Regression, Analysis of Variance (ANOVA), and in the last two decades Structural Equation Modeling are the most familiar statistical methods among research scholars. Taguchi algorism process is one the statistical methods which mostly have been applying in engineering studies. In this study we are looking at two main objectives. The first one is to introduce Taguchi algorism process and apply it in a case study in psychology area. The second objective is challenging among four statistical techniques include ANOVA, regression, SEM, and Taguchi technique in a same data. To achieve those aims we involved depression and obesity indices with other familiar indicators contain socioeconomic, screen time, sleep time, and usage fitness and nutrition mobile applications. Results and discussion: Outputs proved that Taguchi technique is able to analyze some correlations which are not achieved by applying ANOVA, regression, and SEM. Moreover, SEM has a special capability to estimate some hidden correlations which are not possible to evaluate them by using ANOVA, regression, and even Taguchi method. In the last, we found that some correlations are significant by SEM, however, in the same data with regression those correlation were not significant. This paper could be a warning for psychology research scholars to be more careful with involving statistical methods for measuring and estimating of their research variables.
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PURPOSE: The purpose of this paper is to advance healthcare service quality research using hierarchical component models. DESIGN/METHODOLOGY/APPROACH: This study used a quantitative approach with cross-sectional design as a survey method, combining cluster and convenience sampling and partial least square structural equation modelling (PLS-SEM) to validate the research model and test the hypotheses. FINDINGS: The study extends health service quality literature by showing that: patient satisfaction (PS) is dominant, significant and indirect determinant of behavioural compliance (BC); perceived service quality has the strongest effect on BC via PS. RESEARCH LIMITATIONS/IMPLICATIONS: Only one hospital was evaluated. PRACTICAL IMPLICATIONS: The study provides managers with a service quality model for conducting integrated service delivery systems analysis and design. ORIGINALITY/VALUE: Overall, the study makes a significant contribution to healthcare organizations, better health outcomes for patients and better quality of life for the community.