Abstract
Although in line with the resource-based view (RBV), the impact of different HPWS practices on the innovation success of SMEs has been approved by researchers, investigating the previous studies indicates that the relation between these two areas has been more widely considered and less attention has been paid to the impact mechanism. Lack of real data and focus of analysis on respondents’ opinions, lack of process perspective and focus on innovation output criteria, lack of attention to uncertainty in the impact chain, and most importantly lack of a method to prioritize HPWS practices are among the most important constraints identified. So, this study proposes a framework for prioritizing innovation-oriented high-performance human resource practices by combining fuzzy DEA and fuzzy ARAS methods. This paper also presents an objective approach to investigate the impact of High-Performance Work system (HPWS) practices on innovation performance of small and medium size enterprises (SMEs) by considering organizational innovation as a process. After preparing the list of HPWS practices and innovation performance criteria through reviewing the literature and obtaining expert opinions, the fuzzy DEA method was used to model the innovation process performance and calculate the weight of each innovation input criteria. Then, considering the impact of HPWS practices on these input criteria, HPWS practices were ranked using the fuzzy ARAS method. The results of applying this framework to SMEs in the field of nanotechnology in Iran show that top management support is the most important input criteria and the financial results of innovation are the most important output of organizational innovation criteria. In addition, based on the results of this study, the most important effective HPWS practices for SME innovation can be considered as: employee training and development, information sharing and employee participation. The consistency of final ranking of practices and criteria importance with the findings of previous research, the results of sensitivity analysis and comparison of the results of proposed framework and four other multi-attribute decision-making (MADM) methods show the robustness and reliability of the findings of this research.
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Heidary Dahooie, J., Estiri, M., Zavadskas, E.K. et al. A Novel Hybrid Fuzzy DEA-Fuzzy ARAS Method for Prioritizing High-Performance Innovation-Oriented Human Resource Practices in High Tech SME’s. Int. J. Fuzzy Syst. 24, 883–908 (2022). https://doi.org/10.1007/s40815-021-01162-2
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DOI: https://doi.org/10.1007/s40815-021-01162-2