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Little research focuses on the conditions under which companies open up to co-develop knowledge with external actors. Spatial proximity has been proved insufficient to generate successful open innovation processes: socio-economic proximity also seems required. This paper aims at better understanding how this new form of proximity can be organized and investigates the role of third parties or tertius iungens in this process.

This paper is based on an exploratory case of successful open innovation between a software editor and a systems integrator located in the same cluster, relying on 50 face-to-face in-depth interviews, documentation and analysis of physical artifacts.

It confirms that socio-economic and in particular coordination proximity favors open innovation processes. This proximity is facilitated by a third party acting as a sustained iungens to initiate contact between development partners and key customers, and to practically organize knowledge transfer. The paper suggests that to be effective this tertius iungens needs to occupy a central position in the local network and to exhibit the characteristics of an epistemic community.

Due to its exploratory design, the authors' research exhibits several limitations in terms of generalization. It does not fully appreciate the specific interaction between the various dimensions of proximity and in what respect spatial proximity positively influences or reinforces the development of socioeconomic proximity. Further research is needed to analyze the relationships between these various forms of proximity and understand whether spatial proximity is required in a context where new information technologies ease up relationship and coordination mechanisms. Another limitation is linked to the character of the open innovation project analyzed which focused on an innovation of exploitation.

This paper suggests that territorial engineering should favor the emergence of organizations playing the role of tertius iungens in the local network. Such organizations need to have the technical expertise and image of benevolence and integrity to manage knowledge transfer.

Little research analyzes the role of third parties or tertius iungens in the emergence and management of open innovation processes. The literature on clusters has mostly highlighted that inter-organizational cooperation emerges from spatial proximity and can be organized by public authorities whereas most of the open innovation literature on software describes cooperation patterns that do not require any third party.

This study aims to explore the overlap between symptoms of depression, anxiety, irritability and aggressiveness in autism spectrum disorder (ASD), to measure specific and idiosyncratic emotional responses.

A total of 42 high functioning adolescents and adults, between 12 and 39 years old, meeting the diagnostic and statistical manual of mental disorders – 5 criteria for ASD were selected from the InFoR Autism cohort. Data were analyzed in an exploratory way using Hill and Smith and K-medoids cluster analysis.

The authors found an aggregation of anxiety, depression, aggressive behaviors and irritability. Cluster analysis was maximized for two groups with 17 and 25 participants, respectively. The first group was characterized by high levels of symptoms of irritability, aggressiveness, hyperactivity and intermediate levels of anxiety and depression. In the first group, participants had significantly higher levels of autistic symptoms considering the social responsiveness scale and repetitive behavior scale-revised scales (relatives’ reports) suggesting that a particular group of subjects with a high level of ASD specific symptoms may express anxiety and depression in a specific way based on externalizing behaviors in addition to the common mood and anxiety symptoms.

Improved understanding of the aggregation of externalized symptoms with symptoms of anxiety and mood disorders in ASD should lead to a better understanding of the underlying mechanisms related to emotion dysregulation in ASD.

Improved knowledge of the symptoms could lead to enhanced detection of psychiatric comorbidities in ASD.

The study was based on a transdiagnostic approach of psychiatric symptoms in individuals with ASD. Aggregation and clustering analysis was used to explore naive patterns of these psychiatric symptoms.