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Given the general consensus that creativity is a crucial driving force for innovation and progress, understanding how to promote it would benefit individuals, companies, society and academia. Therefore, this paper aims to analyze the independent and contingent impact of individuals’ personality traits, team-member exchange (TMX) and gender on stimulating creativity.

The study uses a survey-sample of 639 university students (51.96% women) between the ages of 17 and 50. Confirmatory factor analysis (CFA) demonstrated reliability and validity of its measures. To test hypotheses, using structural equation modeling, hierarchical regression analyses were performed.

Results show that four of the five personality traits (extraversion, agreeableness, conscientiousness and openness to experience) and TMX positively influence creativity. There are no significant differences between men’s and women’s creativity. High TMX reinforces the influence of extraversion on creativity, while low TMX harms this relationship. High extravert women are more creative than high extravert men, while low extravert men are more creative than low extravert women. Low emotionally stable women are more creative than low emotionally stable men, while high emotionally stable men are more creative than high emotionally stable women. There are differences in how women and men take advantage of their openness to experience when TMX is considered. That is, while women take advantage of openness to experience for any value of TMX, men only increase their creativity as openness to experience increases for low values of TMX.

Like all studies, ours has some limitations that provide opportunities for future research. First, care should be taken when generalizing these findings to other contexts. We use data from Spanish individuals, specifically university students. While they are suitable for testing our hypotheses, future studies should establish whether the general tendencies that we observe hold true for other kinds of people from Spain and other countries. Even more, this paper’s perspective might be biased by the authors’ country of origin (south Europe) in terms of gender. According to Hofstede (2001) south European and South American countries are more masculine than other cultures (Mensa and Grow, 2022). Therefore, analyzing these questions in different cultures (countries and settings) would facilitate the generalization of the results. Second, the data we use is mainly cross-sectional so strict causality cannot be inferred. The theory we use assumes specific causal directions, but alternative causal relationships cannot be ruled out. Finally, ideally, we should have controlled for additional variables that might influence the relationships in our model.

This paper has practical implications, as it demonstrates that neither gender is more creative than the other. It goes a step further, explaining how men and women can leverage their personality traits to be more creative. Moreover, since TMX could reinforce the impact of personality traits on creativity, this paper could help managers better organize teams and companies that want to be more innovative by taking into account the personality traits of their employees and how to get the best out of women and men.

Traditionally, women have considered creativity to be a man’s thing. The results of this work favor society, demonstrating that women are just as creative as men and that through personality traits and TMX, both men and women can be more creative. These results help to reduce the gender gap and may favor women’s place in today’s society.

This work offers academic and practical implications. The main contributions to the creativity and gender literatures are the following: (1) Women are as creative as men. (2) High extravert and low emotionally stable women are more creative than men. (3) High open to experience women with high TMX are more creative than men at any level of TMX. For practitioners, the understanding of what personality traits have higher impact on creativity depending on the levels of TMX for women and men could help companies and politicians in hiring the most suitable people, especially for those positions where creativity is needed. This would increase the quality of their human capital, allowing them to get the most out of their human resources, from the very beginning of the employment relationship.

This work presents a novel approach by considering teaching learning based optimization (TLBO) and radial basis function neural networks (RBFNs) for building a classifier for the databases with missing values and irrelevant features. The least square estimator and relief algorithm have been used for imputing the database and evaluating the relevance of features, respectively. The preprocessed dataset is used for developing a classifier based on TLBO trained RBFNs for generating a concise and meaningful description for each class that can be used to classify subsequent instances with no known class label. The method is evaluated extensively through a few bench-mark datasets obtained from UCI repository. The experimental results confirm that our approach can be a promising tool towards constructing a classifier from the databases with missing values and irrelevant attributes.