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This paper aims to explore the complexity of the “leaky pipeline” of women in science, technology, engineering and maths (STEM) in the intriguing contexts where there are a high number of STEM graduates but a low number of women working in these fields.

The authors conducted in-depth interviews with eight STEM “leavers” and eight “persisters” in Turkey to understand the multi-level influences on their career paths.

The behavioural ecological model is applied to enrich the understanding of women’s attrition from STEM. The authors found a complex system of actors, relationships and influences that impact the negotiations of women’s felt misfit/love of their STEM career and changing self-actualisation.

The authors highlight that social marketers should consider the complex influences on even the most individualistic-looking decisions to produce systemic change.

This paper deepens the use of the behavioural ecological model in the ways that the layers of motivator and demotivator influences interact with women’s internal negotiations of career choice. The paper integrates classic theories (self-actualisation (Maslow, 1943) and two-factor model (Herzberg et al., 1959)) within systems social marketing.

Locating disaster response centers is one of the key elements of efficient relief operations. The location and infrastructure of the candidate facilities usually conform to the required criteria at different levels. This study aims to identify the criteria for the main and local distribution center location problem separately and prioritize each candidate distribution center using a hybrid multiple criteria decision-making approach.

The proposed model incorporates analytic hierarchy process (AHP) and Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) under interval type-2 fuzzy sets (IT2FSs) to overcome the uncertainty of experts` judgments and expressions in the evaluations of candidate distribution centers. In the proposed approach, weights of the criteria are determined using type-2 fuzzy AHP and the candidate distribution centers are prioritized using type-2 fuzzy TOPSIS.

Transportation, cost, infrastructure and security are determined as the main criteria for the main distribution center location criteria. Cost, warehouse facilities and security are the main criteria for local distribution center location selection. Prioritization enables decision-makers to assess each alternative accordingly to be able to select the best locations/facilities for efficient disaster response operations.

This study proposes new multi-criteria decision support models for prioritizing disaster response distribution centers. IT2FSs are used to be able to reflect both the complexity and vagueness of disaster environment and expert opinions. Different support models are suggested for main and local distribution centers considering their different missions. The proposed methodology is applied in Istanbul city, Turkey, where a high-magnitude earthquake is expected.