Limitations of Our Technological Convergence Analysis and Future Work

Table of Links

Abstract and 1. Introduction

2 Related Work and 2.1 Technology Convergence Approaches

2.2 Technology Convergence Measurements

2.3 Technology Convergence Models

3 Data

4 Method and 4.1 Proximity Indices

4.2 Interpolation and Fitting Data

4.3 Clustering

4.4 Forecasting

5 Results and Discussion and 5.1 Overall Results

5.2 Case Study

5.3 Limitations and Future Works

6 Conclusion and References

Appendix

5.3 Limitations and Future Works

While our research offers valuable insights, it also has limitations and suggests areas for future work. One limitation of our proposed method is its reliance on a single data source, OpenAlex, without integrating or comparing it to other similar datasets. This could potentially result in our proposed method being overfitted towards OpenAlex. Additionally, our approach lacks a normalization strategy for various calculations of proximity indices. As a result, index comparisons may be influenced by predominant values, such as the high number of publications in a specific technology domain. To address this issue, we propose index normalization by averaging monthly publications relevant to the technologies or using a weighted factor based on available variables.

Introducing a normalized index as an additional graph edge could enhance the computation of different proximity indices. This additional edge, forming 5-dimensional edges instead of our quintet of distinct indices, could contribute to establishing a more improved convergence threshold. Subsequently, leveraging community detection algorithms might provide insights into technological convergence by identifying clusters of converging technologies. This avenue holds promise for further exploration.