Purpose: While the Malaysian government proposed the "Industry4ward" approach to enhance technological adoption, there is scarce empirical evidence in the literature that validates SMEs for Industry 4.0. Using Dynamic Capability View (DCV), this study proposes a framework that includes core determinants like top management commitment, supply chain integration, and IT infrastructure, that can significantly influence Industry 4.0 implementation toward achieving TBL sustainability.
Design/methodology/approach: Employing simple random sampling, the study adopted a quantitative approach based on 199 useable respondent's feedback collected through a survey questionnaire of 900 employees from Malaysian SMEs. The statistical analysis was performed using Structural Equation Modeling (Partial Least Square, SmartPLS 3.3.2).
Findings: The results show that top management and IT infrastructure significantly impact Industry 4.0 implementation and sustainability. In contrast, the analysis also demonstrates that supply chain integration is insignificant to Industry 4.0 implementation in SMEs. The findings also indicate that the relationship between the determinants of Industry 4.0 and TBL sustainability can be mediated by the "effective implementation" of Industry 4.0.
Recommendations: The study highlights the practical consequences of the role and use of the determinants in Industry 4.0 implementation. Its findings help managers and policy-makers to optimize value creation to achieve sustainable development goals.
Limitations and future research: Focusing only on Malaysian manufacturing SMEs may restrict the generalization of the study; thus, a benchmarking analysis from other industrial settings is encouraged. The questionnaire-based survey is a further limitation of the study.
SETTING: Kelantan, Malaysia.
PARTICIPANTS: All breast cancer cases diagnosed in 2007 and 2011 identified from Kelantan Cancer Registry.
DESIGN: This retrospective cohort study used a relative survival approach to estimate the net survival of patients with breast cancer. Thus, two data were needed; breast cancer data from Kelantan Cancer Registry and general population mortality data for Kelantan population.
PRIMARY AND SECONDARY OUTCOME MEASURES: Net survival according to stage and age group at diagnosis at 1, 3 and 5 years following diagnosis.
RESULTS: The highest net survival was observed among stage I and II breast cancer cases, while the lowest net survival was observed among stage IV breast cancer cases. In term of age at diagnosis, breast cancer cases aged 65 and older had the best net survival compared with the other age groups.
CONCLUSION: The age at diagnosis had a minimal impact on the net survival compared with the stage at diagnosis. The finding of this study is applicable to other populations with similar breast cancer profile.