نشریه مطالعات زیست بوم اقتصاد نوآوری
سال چهارم شماره 1 (پیاپی 13، بهار 1403)

Innovation is widely recognized as a crucial driver of modern economic and social progress. This research aims to investigate the relationship between economic freedom and its components on innovation. A review of the literature indicates that economic freedom can either positively influence innovation (Arrow effect), negatively impact it (Schumpeter effect), or produce a combination of both effects (Scherer effect). To investigate this issue, two groups of countries—developed and developing—were examined. Econometric panel data analysis was conducted for the period 2011-2022 using two models: one based on the overall index of economic freedom and the other on its components. The research findings indicate a positive and significant relationship between economic freedom and innovation in developed countries. However, a deeper analysis reveals that only the rule of law and government size positively and significantly impact innovation within this group. Regulatory efficiency and market openness did not exhibit significant effects, suggesting a partial confirmation of the Arrow effect. In contrast, economic freedom's impact on innovation in developing countries was found to be negative, though not statistically significant. Among the components, only the rule of law showed a negative and significant relationship, aligning with Schumpeter's theories. Additionally, control variables such as GDP per capita, research and development expenditures, information and communication technology, and corruption levels significantly influenced innovation in both groups of countries.

The concept and importance of collective interactions and moral virtues in the structure of society and economy are rooted in the ages of history. The explanation of this issue in the history of science has led to the production of an important concept called social capital. This concept has important effects on economic and social variables. Theoretical foundations show that social capital can be effective on variables such as knowledge and innovation. This study investigates the factors influencing innovation across countries worldwide, with a particular focus on the role of social capital. Social capital can enhance the business environment and reduce transaction costs, thereby fostering knowledge dissemination and innovation. To achieve the research objectives, data from 113 countries over the period 2013-2022 were analyzed using the quantile panel regression method. To facilitate comparison, countries were categorized into four income groups: low-income, lower-middle-income, upper-middle-income, and high-income. Separate estimates were provided for each category. The findings indicate that population, democracy, and government expenditure are significant determinants of innovation, with their impact being more pronounced in high-income countries. Population has a positive effect on innovation for countries that have been able to provide appropriate infrastructure. The analysis reveals that social capital exerts a positive and significant effect on innovation. This effect is stronger in high-income countries. Furthermore, quantile estimates demonstrate that the impact of social capital on innovation varies significantly across different quantiles. Consequently, external factors in each country play a crucial role in determining the extent to which social capital influences innovation.

The main goal of this research is to investigate the impact of innovation indicators on macroeconomic efficiency. For this purpose, the information of OECD member countries was used in the period of 2012 to 2021. In this research, in order to identify the method of choosing the appropriate model for model estimation, Limer and Hausman's F test was used, and the results of the tests show the use of Panel data with fixed effects as the appropriate model for model estimation. In the following, the macroeconomic inefficiency factor is estimated by using the frontier stochastic analysis method, and finally the obtained inefficiency factor is considered as a dependent variable in the final model. Finally, the effect of three indicators, the number of patent license applications, the export of advanced technologies, and the number of research articles as indicators of innovation and independent variables; Also, the inflation variable was measured as a control variable on macroeconomic inefficiency. The findings of the research indicate that among the three indicators mentioned as innovation indicators, two indicators of patent license requests, export of advanced technologies were not significant on macroeconomic efficiency. Meanwhile, the coefficient related to the number of research articles shows the number 0.163, which shows the positive and significant effect of this variable on macroeconomic inefficiency at the 5% error level. In fact, it can be said that the factor of the number of research articles had a negative and significant effect on economic efficiency, which means that an increase in the number of research articles causes a decrease in economic efficiency. The inflation factor also has a positive and significant control variable on economic inefficiency, or in other words, the inflation factor has a negative and significant effect on the macroeconomic efficiency, which is in line with expectations.

The current research provides new evidence regarding the impact of innovation and creative industries on the process of economic wellbeing. In this context, a smooth transition panel regression approach has been utilized for the period from 2013 to 2020. The optimal model for developed countries was estimated with two threshold levels and two transition functions, while for developing countries, it was estimated with two threshold levels and one transition function. In developed countries, the speed of transition from the first limit regime to the second limit regime was equal to 14.0361 and the speed of transfer from the second limit regime to the third regime was equal to 28.2824, which shows that the transition from the first regime to second regime smoother than the transition from the second to the third regime. In developing countries, the speed of transition from the first regime to the second is equal to 25.6488, which indicates a smooth transition from the first regime to the second regime. The results indicate that innovation in developed countries has a significant negative impact on economic welfare in the first regime, but this impact turns positive and significant in the second and third regimes. In developing countries, innovation does not significantly affect economic wellbeing in the first regime, but it has a positive and significant effect in the second regime.

In today's business world, organizations face dynamic and competitive environments that require continuous innovation to survive and grow. Organizational innovation is recognized as a key factor in improving company performance. However, there are several challenges for the successful implementation of innovation, one of the most important of which is the effective coordination between different organizational units. Coordination mechanisms can play a vital role in facilitating innovation. These mechanisms include formal and informal structures, management processes and communication tools that strengthen cooperation and coordination between different units of the organization. This study examines the relationship between the coordination mechanism and organizational innovation on the performance of the company with regard to the role of mediator in multidisciplinary knowledge sharing. The current research is applied in terms of purpose and descriptive-composite in terms of method. In order to collect information from library and field methods, and the data collection tool was a closed questionnaire. To determine the validity of the questionnaire, the content method was used with the opinion of experts in the field of knowledge management, and to determine the reliability of the questionnaire, two criteria of composite reliability and the extracted average variance were used. The population under investigation was all the employees of the Golestan Tax Affairs Organization, the statistical sample was determined to be 220 people based on the Karajesi and Morgan formula. While reviewing the theoretical foundations and selecting the members of the statistical sample with a simple random method, the researchers evaluated the research hypotheses with the structural equation modeling method. The results of structural equation analysis by Lisrel 8/8 software showed that: 1) coordination mechanisms have an effect on multidisciplinary knowledge sharing. 2) multidisciplinary knowledge sharing has an effect on performance and 3) organizational innovation has an effect on performance.

The advancements in the field of information and communication technology have paved the way for economic and societal progress and development. The penetration of technology into various aspects of life and society has led to the emergence of the concept and method of the digital economy, which has increased economic productivity. In this research, the Digital Economy Infrastructure Index (DEII) has been used to examine the position and performance of the digital economy. The performance of this index in the provinces of Iran is composed of components such as the number of fixed telephone users, the number of mobile phone users, the number of internet users, and internet bandwidth, considered for the period from 2013 to 2023. This research has been conducted using an analytical-descriptive method, and the ranking of the Digital Economy Infrastructure Index (DEII) in the provinces of Iran has been completed using the method of principal component and cluster analysis. According to the research findings, the provinces of Tehran, Isfahan, and Razavi Khorasan ranked first to third, respectively , while the provinces of North Khorasan, Ilam, and Kohgiluyeh and Boyer Ahmad ranked twenty eighth to thirtieth, respectively. Additionally, the performance of the provinces in the field of the digital economy was divided and categorized into three clusters: very suitable, suitable , and very unsuitable. Based on the examination of the digital economy performance of the provinces and the categorization of the provinces, the path for digital economy policy making and planning in the country can be facilitated.