Evaluating Innovation Levels based on Standard Deviation of Parameters and MCDM Methods

Do Duc Trung; Branislav Dudic; Dinh Mai Huong; Nguyen Thi Tham; Aleksandar Ašonja

doi:10.31181/sems41202666

Authors

Do Duc Trung Hanoi University of Industry, Hanoi, Vietnam Author https://orcid.org/0000-0002-3190-1026
Branislav Dudic Comenius University Bratislava, Faculty of Management, Bratislava, Slovakia Author
Dinh Mai Huong Hanoi University of Industry, Hanoi, Vietnam Author https://orcid.org/0000-0002-1876-8662
Nguyen Thi Tham Hanoi University of Industry, Hanoi, Vietnam Author https://orcid.org/0000-0002-8366-8449
Aleksandar Ašonja Faculty of Economics and Engineering Management, University Business Academy, Novi Sad, Serbia Author https://orcid.org/0000-0001-6667-1024

DOI:

https://doi.org/10.31181/sems41202666

Keywords:

Minimum three keywords, Avoid too general and too specific keywords, Innovation, Weights, Standard deviation, SD method, LOPCOW method, LOPCOW-SD method

Abstract

Innovation is the process of implementing novel ideas into practice to generate solutions, products, or enhanced procedures that deliver value. Comparing innovation efforts across provinces within a nation is essential, as it clarifies the specific strengths and weaknesses of each locality, providing a comprehensive overview of development capacity rooted in science and technology. This study was conducted to evaluate the innovation performance of several Vietnamese provinces, utilizing data sourced from the Vietnam Economy and Forecast Magazine. Seven parameters were employed to characterize innovation efforts: institutions (C1), human capital and research (C2), infrastructure (C3), market sophistication (C4), business sophistication (C5), knowledge, creativity, and technology outputs (C6), and impacts on production, business, and society (C7). The weights of these parameters were determined by analyzing their standard deviations using the LOPCOW weighting method, the SD weighting method, and the LOPCOW-SD method—an integration of the two primary approaches. The results indicated that the institutional parameter (C1) was identified as the most significant factor, whereas the impact on production, business, and society (C7) was the least significant. The ranking of provinces regarding innovation performance was executed using eight distinct MCDM methods, including MOORA, MARCOS, COCOSO, ROV, PIV, RAM, TOPSIS, and CRADIS. The findings demonstrated that, regardless of the methodology applied, the study consistently highlighted the same high-ranking and low-ranking provinces. Finally, Spearman and WSPE coefficients were utilized to compare the weighting methods, revealing that SD and LOPCOW-SD exhibit higher efficiency compared to the LOPCOW method.

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