Comparative analysis of innovation management between ANZ (Australia, New Zealand) and TMSV (Thailand, Malaysia, Sri Lanka and Vietnam) regions

Purpose: The main aim of this study was to determine the scope of application for an innovation management assessment framework (IMAF) within innovation management. Two distinct geographical regions: ANZ (Australia and New Zealand) and TMSV (Thailand, Malaysia, Sri Lanka and Vietnam) were chosen to identify and analyse significant comparative differences. Design/methodology/approach: A quantitative research approach was used using empirical data collected through an online questionnaire-based survey. Statistical data analysis, including descriptive statistics, univariate analysis of variance (ANOVA) and Hsu's MCB (multiple comparisons with/to the best) post-hoc test results, was carried out to identify significant differences and similarities in innovation management capabilities within the two regions. Findings: The descriptive statistics analysis reveals areas for potential enhancement in all the model constructs within both regions under investigation. Significant differences in innovation management capabilities between the two regions are identified, specifically in the design for lean six sigma (DFLSS) and the operation function commercial (COMM). However, when considering the remaining constructs of the IMAF, no significant differences in innovation management capabilities are observed between the regions. Research limitations/implications: The research is limited by the relatively small size of survey questionnaire responses from the targeted population. Future studies could be conducted on a global scale to increase responses. Practical implications: The research findings serve as valuable insights into the development of important and useful guidelines for managers and innovation practitioners engaged in innovation planning and management. Originality/value: The critical analysis conducted in this research, focusing on innovation management capabilities by region, represents a significant advancement in the existing body of work that utilises the IMAF model.