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Erscheinungsjahr: 
2018
Quellenangabe: 
[Journal:] European Journal of Management and Business Economics (EJM&BE) [ISSN:] 2444-8451 [Volume:] 27 [Issue:] 2 [Publisher:] Emerald [Place:] Bingley [Year:] 2018 [Pages:] 198-214
Verlag: 
Emerald, Bingley
Zusammenfassung: 
Purpose: The purpose of this paper is to identify factors promoting innovation in the framework of R&D based on surveys conducted on firms in five ASEAN countries, Indonesia, Laos, Thailand, the Philippines, and Vietnam. Design/methodology/approach: The analytical method divided sample firms into two categories, namely, "the R&D group" and "non-R&D group." The analysis attempts to identify which of the internal capabilities, consisting of technology, human factors and organization factors, promote innovation. Ordered probit analysis is employed. Findings: Findings from the estimations indicate that the two groups pursue product innovation differently. The R&D group promotes innovation by cross-functional teams of production, engineering, and marketing and IT use, whereas the non-R&D group promote product innovation by HRD programs for workers, group awards for suggestions or QC, and ISO9000 series. Research limitations/implications: The number of samples related to the non-R&D group is too small to conduct statistical analysis. External linkages played an important role in the authors' previous studies. The introduction of external linkages into the model may yield different results, though the analysis would become more complex. Practical implications: The results of this paper provide the solid basis of policy to promote innovation and upgrading SMEs in the region. Social implications: Many ASEAN SMEs successfully achieve innovation without owning specified in-house departments or sections to conduct R&D. Originality/value: The features of this paper lie in the original firm-level survey data and rigorous estimation method using ordered probit analysis, which are new to this literature.
Schlagwörter: 
MNCs
HRD
Learning process
Cross-functional team
Ordered probit analysis
QC
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