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1 – 3 of 3Asieh Bakhtiar, Seyed Sepehr Ghazinoory, Alireza Aslani and Vahid Mafi
The purpose of this paper is to present and evaluate the performance of innovation systems by considering two indicators of efficiency and effectiveness. The scope of the…
Abstract
Purpose
The purpose of this paper is to present and evaluate the performance of innovation systems by considering two indicators of efficiency and effectiveness. The scope of the evaluation is globally and due to the situation of each country, the suggested strategies are proposed to maintain the status quo or move toward the desired situation for countries.
Design/methodology/approach
The approach is to compare and benchmark the countries in terms of the efficiency and effectiveness of their innovation system. The Global Innovation Index report’s input-to-output ratio and the global competitiveness report are used for the assessment.
Findings
The findings indicate that countries such as China, Switzerland and the USA have an efficient and effective innovation system. However, the innovation systems in countries such as Brazil and Zimbabwe are not only inefficient but also ineffective. The findings also indicate that the innovation systems of countries such as Iran, Armenia and Egypt are efficient but ineffective. Finally, the authors can name Australia, Qatar and Russia as countries with effective but inefficient innovation systems.
Originality/value
Assessment of national innovation system using efficiency and effectiveness performances is done for the first time at the global stage.
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Keywords
Zeinab Zamani, Ameneh Khadivar, Hamid Padash, Javad Shekarkhah and Morteza Akbari
This chapter recognizes and ranks the factors that impact the adoption of mobile commerce (MC) by users. The results showed that compatibility, perceived usefulness (PU)…
Abstract
This chapter recognizes and ranks the factors that impact the adoption of mobile commerce (MC) by users. The results showed that compatibility, perceived usefulness (PU), perceived risk (PR), mobility, and perceived cost (PC) have a significant effect on the adoption of MC by users. The results of multilayer perceptron (MLP) showed that mobility, among other model variables, had the greatest impact on the adoption of MC, and PC had the lowest effect on the adoption of MC. The comparison of the MLP model with linear regression illustrates that the predictive power of MLP outperforms the linear regression model in predicting MC adoption.
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