Search results

Nature’s evolution has shaped intelligent behaviors in creatures like insects and birds, inspiring the field of Swarm Intelligence. Researchers have developed bio-inspired algorithms to address complex optimization problems efficiently. These algorithms strike a balance between computational efficiency and solution optimality, attracting significant attention across domains.

Bio-inspired optimization techniques for feature engineering and its applications are systematically reviewed with chief objective of assessing statistical influence and significance of “Bio-inspired optimization”-based computational models by referring to vast research literature published between year 2015 and 2022.

The Scopus and Web of Science databases were explored for review with focus on parameters such as country-wise publications, keyword occurrences and citations per year. Springer and IEEE emerge as the most creative publishers, with indicative prominent and superior journals, namely, PLoS ONE, Neural Computing and Applications, Lecture Notes in Computer Science and IEEE Transactions. The “National Natural Science Foundation” of China and the “Ministry of Electronics and Information Technology” of India lead in funding projects in this area. China, India and Germany stand out as leaders in publications related to bio-inspired algorithms for feature engineering research.

The review findings integrate various bio-inspired algorithm selection techniques over a diverse spectrum of optimization techniques. Anti colony optimization contributes to decentralized and cooperative search strategies, bee colony optimization (BCO) improves collaborative decision-making, particle swarm optimization leads to exploration-exploitation balance and bio-inspired algorithms offer a range of nature-inspired heuristics.

In the last two decades, risk reporting has followed a normative and calculative culture rather than the “materiality” of data. Although integrated reporting (IR) has become flooded with extra information, it does not adequately disseminate material information to stakeholders. In addition, the poor tone from the top diminishes creativity. This study aims to investigate how companies creatively address issues of the materiality of risk information in IR and how IR can be aligned with enterprise risk management.

Qualitative research was conducted via interviews with 50 chief risk officers and senior management executives in the Indian and UK insurance markets.

Overall, five institutions were observed to exhibit elements of being early adopters of institutional creativity. This confirmed the present study’s theoretical contribution of five divergent types of early adopters. The motivations for creativity are reflected in the resources available to these institutions.

To the best of the authors’ knowledge, this study provides a new insight into IR from internal mechanisms to deal with issue of materiality.