Purpose
This study aims to analyze the effects of cultural orientations (performance and sociality) on the trajectories of innovation inputs and their results in different countries worldwide between 2011 and 2021.
Design/methodology/approach
As a technique for data analysis, one of the spatial Bayesian models and Gray forecasting methods is used. This technique is adequate to achieve the objectives of the investigation because it allows analyzing how the variables move in time ranges and allow the generation of forecasts. This model also allows knowing if there are spills, which investing in a country can positively affect countries with geographical proximity. The databases used were the Global Innovation Index with data from 131 nations and the Globe Project with data from 157 countries between 2011 and 2021. The variables analyzed are institutions, human capital, research infrastructure, market sophistication and business sophistication. On the other hand, regarding moderations of cultural orientations, The Globe Project developed two factors: performance orientation (high degree of masculinity, avoidance of ambiguity, power distance and future orientation) and humane orientation (high-level of femininity, institutional and societal collectivism).
Findings
The results reveal that all inputs grow at different rates over time. In the case of institutions, it is the most difficult to generate changes over time. However, human capital, market sophistication and business sophistication are the ones that have grown the most over time, regardless of the country’s cultural orientation.
Research limitations/implications
Among the main limitations is the set of data used because it only considers one approach to culture, especially the one considered by Hofstede. However, other approaches could help evaluate the results of this research. Considering the results obtained, the study attempts to provide a different view of the effects of cultural variables on companies’ innovation performance in different countries in the world. In the same way, evaluating these effects allows firms to consider variables associated with the country that will affect the strategies and performance of the firm.
Practical implications
The results achieved make it possible to strengthen the analysis of the countries’ strategies when it comes to innovation, especially in the permanent evaluation of the results that allow to encourage changes in the execution of innovative activities to maintain their performance over time.
Social implications
The contributions allow us to understand the dynamics of innovation in the knowledge and creative outputs of countries over time.
Originality/value
The trajectory analysis used in the data analysis is perhaps one of the most robust techniques that makes a time series analysis. This allows identifying trajectories for the independent variables of the study and their influence on the innovation of the country.