12 (1), 2023
Eyüp Çalık
Analytical Approach to Innovation Processes: Innovation AnalyticsPurpose: In this study, it is aimed to understand the concept of innovation analytics by examining what innovation analytics is and to show what kind of models will find application areas for analytical levels.
Methodology: Modeling was done for innovation analytics and widely used data analytics and machine learning algorithms were used as well as basic inferential statistical methods for data analysis.
Findings: It has been shown that many different types of innovation analytics can be modeled and applied to increase efficiency in innovation processes which are from idea selection to commercialization.
Practical Implications: Demonstrating the applicability of innovation analytics types will offer a different perspective to researchers, corporate innovation practitioners, and leaders.
Originality: In addition to being the first Turkish study to handle the concept of innovation analytics, it also includes applications for 3 different levels of innovation analytics.
Keywords: Innovation Analytics, Innovation Process, Data Analytics, Machine Learning, Artificial Intelligence
DOI : 10.15659/jeim.12.1.001 [PDF]
Determination of Features Used in The Global Entrepreneurship Monitor Through Artificial IntelligencePurpose: To determine the items that need to be concentrated in order to increase the development levels of the countries in the GEM report with artificial intelligence techniques. At the same time, it is aimed to examine the situation of Turkey.
Methodology: The data were taken from the GEM report and the Adaptive Neuro-Fuzzy Classifier with Linguistic Hedges method was used.
Findings: The most important factor affecting the level of development in terms of entrepreneurship was determined as "Government policies: Taxes and bureaucracy".
Practical Implications: Countries that want to develop in terms of entrepreneurship should first give priority to developments within the scope of "Government policies: Taxes and bureaucracy".
Originality: In this study, artificial intelligence techniques, which are very popular today, were used rather than the methods commonly used in the field of social sciences.
Keywords: The Global Entrepreneurship Monitor, Entrepreneurship Ecosystem, Artificial Intelligence, Adaptive Neuro-Fuzzy Classifier with Linguistic Hedges
DOI : 10.15659/jeim.12.1.002 [PDF]
From The EditorDear colleagues,
Bringing the each issues on to your screen is both very tiring and exiting period and it requires allot of joint effort from all sides. Now we are so happy to bring our new issues to you and we hope you will enjoy reading our issue.
We are thankful for those who supporting us either by sending their research results. Despite receiving number of article, we could only finalize two of them to be ready for the issue. Although the number of the publish article is law, the spent effort is more and quality of the paper is very good. We congratulate all the authors and the reviewers who help us to improve the quality of the papers. Without their support it would not be possible to bring the Journal to this level.
In this new issue, we have different well-addressed two research papers about innovation analytics which is introduced the literature recently. The second paper is about how to increase the level of entrepreneurship of countries in GEM reports by using artificial intelligence techniques.
We hope this issue will also provide useful information both researchers, professionals as well as it will also provide useful information for policy makers.
Finally, I like to remind you that you can access all our past and current issues with no charge. I strongly recommend you to read our publications and I believe this will be helpful for your current research and professional business.
Best Regards
Cevahir UZKURT
Editor-in Chief
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