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This paper aims to inform the promotion of sustainable modes of transport. For this purpose, it deploys a means-ends framework as a type of second-order cybernetics and uses it to explore cognitive transport mode choice structures.

The empirical study relies on a purposive sample and a qualitative research methodology known as laddering. It is aimed at the identification and comparative analysis of the cognitive means-ends structures of transport users.

The results reveal more positive and complex associations for the car than for public transport. Two main positive means-ends structures are identified for public transport, one related with the relaxation and the other with doing useful things while travelling. Dominant positive structures for the car are related with self-confidence, satisfaction and personal freedom. Negative means-ends structures in addition reveal important justifications and rationalizations for car use.

Based on the identified distinct means-ends elements and structures, this study holds important implications for developing a communications strategy and policy interventions seeking to promote public transport.

Means-ends theory is proposed as an integrative cybernetic framework for the study of stakeholders’ (customers’) mental models. The empirical study is the first to concurrently and comparatively examine positive and negative means-ends chains for the car and for the public transport modes.

The purpose of the paper is to propose an effective approach of artificial intelligence (AI) addressing social-humanitarian reality comprising non-formalizable representation. The new task is to describe processes of integration of AI and humans in the hybrid systems framework.

Social-humanitarian dynamics contradict traditional characteristics of AI. Suggested methodology embraces formalized and non-formalized parts as a whole. Holonic and special convergent approaches are combined to ensure purposefulness and sustainability of collective decision-making. Inverse problem solving on topology spaces, control thermodynamics and non-formalizable (considering quantum and relativistic) semantics include observers of eigenforms of reality.

Collective decision-making cannot be represented only by formal means. Thus, this paper suggests the equation of hybrid reality (HyR), which integrates formalizable and non-formalizable parts conveying and coalescing holonic approaches, thermodynamic theory, cognitive modeling and inverse problem solving. The special convergent approach makes the solution of this equation purposeful and sustainable.

The suggested approach is far reaching with respect of current state-of-the-art technology; medium-term limitations are expected in the creation of cognitive semantics.

Social-humanitarian events embrace all phenomena connected with individual and collective human behavior and decision-making. The paper will impact deeply networked experts, groups of crowds, rescue teams, researchers, professional communities, society and environment.

New possibilities for advanced AI to enable purposeful and sustainable social-humanitarian subjects. The special convergent information structuring during collective decision-making creates necessary conditions toward the goals.