Spatial and Non-spatial Proximities in Inter-firm Relations: An Empirical Analysis

Aguiléra, Anne; Lethiais, Virginie; Rallet, Alain

doi:10.1080/13662716.2012.669609

Cited by 59 publications

(64 citation statements)

References 28 publications

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“…2012),Balland et al (2014),Boschma (2005), D'Este et al (2013),Hong and Su (2013), Huber (2011), Mattes (2012,Rosenkopf and Almeida (2003),Slavtchev (2013),Aguiléra et al (2012),Autant et al (2007),Broekel and Boschma (2012), Hoekman et al (2010) Organizational Similarity in routines, regulations, and incentives between organizations Heringa et al (2014), Knoben and Oerlemans (2006), Capaldo and Petruzzelli (2014), Balland (2012), Balland et al (2014), Boschma (2005), Bruneel et al (2010), D'Este et al (2013), Hong and Su (2013), Huber (2011), Mattes (2012), Aguiléra et al (2012), Broekel and Boschma (2012) Social Degree of common relationships (personal relationships between actors involving trust, friendship, and previous collaborations) Heringa et al (2014), Knoben and Oerlemans (2006), Balland (2012), Balland et al (2014), Boschma (2005), Bruneel et al (2010), Hong and Su (2013), Huber (2011), Mattes (2012), Aguiléra et al (2012), Autant et al (2007), Broekel and Boschma(2012)…”

mentioning

confidence: 96%

How intermediary organizations facilitate university–industry technology transfer: A proximity approach

Villani

Rasmussen

Grimaldi

2017

Technological Forecasting and Social Change

256

143

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mentioning

confidence: 96%

How intermediary organizations facilitate university–industry technology transfer: A proximity approach

Villani

Rasmussen

Grimaldi

2017

Technological Forecasting and Social Change

256

143

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“…Typically, non-spatial proximity is conceptualised in terms of the similarities between agents based on: shared knowledge bases or skills (cognitive proximity); shared methods and procedures (organisational proximity); shared relationships (social proximity); and shared culture (institutional proximity) (Aguilera et al 2012). In addition, the importance of epistemic communities has also been highlighted as an important determinant of collaborative links (Cowan et al 2000) as well as shared codebooks (Pinch et al 2003;Henry & Pinch 2001).…”

Section: Organisational Proximitymentioning

confidence: 99%

Drivers of University–Industry Links: The Case of Knowledge-Intensive Business Service Firms in Rural Locations

Johnston

Huggins

2015

Regional Studies

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The process of establishing collaborative links with university partners is potentially accompanied by uncertainties with respect to both the process and expected outputs. Partner selection is a difficult task influenced by a multitude of factors including location, geographic distance, compatibility of interests, shared understanding and prior experience of collaboration. Drawing on an analysis of Knowledge Intensive Business Service Firms (KIBS) firms located in predominantly rural districts of the UK, this paper examines the influences on partner selection when developing university links through knowledge transfer partnerships. The main focus of the paper is the extent to which geographic and organisational proximity influence the choice of university partner. The paper examines rural KIBS firms, which are generally less likely to be in close geographic proximity to a university. In the case of these firms, organisational proximity potentially has a strong role to play in partner selection. Indeed, the empirical analysis finds that both geographic and organisational proximity are significantly associated with partner choice, indicating that the formation of university-industry links are not only the result of locational factors, but also prior experience of collaboration. The findings indicate that partner choice is a complex process influenced by both geographic and organisational proximity, alongside university research prowess. The paper concludes by considering the policy implications of these findings and possible avenues for future research in this area

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“…Aguiléra et al 2012;Broekel and Boschma, 2012;Crescenzi et al 2016;Feldman et al 2015;Marrocu et al 2013;Nooteboom et al 2007;Rigby 2015). However, as discussed below, it is often the case that empirical tests rely on rather crude indicators, which, in turn, make strong assumptions about the relationships between sectors, places, and organisations.…”

Section: Introductionmentioning

confidence: 99%

“…By contrast, very few papers (e.g. Broekel and Boschma 2011;Aguiléra et al 2012) have so far used survey data to capture how the firms interpret their proximity to the partner in a more direct way. Very few studies (e.g.…”

mentioning

confidence: 99%

Not too close, not too far: testing the Goldilocks principle of ‘optimal’ distance in innovation networks

Fitjar

Huber

Rodríguez‐Pose

2016

Industry and Innovation

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This paper analyses how the formation of collaboration networks affects firm-level innovation by applying the 'Goldilocks principle'. The 'Goldilocks principle' of optimal distance in innovation networks postulates that the best firm-level innovation results are achieved when the partners involved in the network are located at the 'right' distance, i.e. 'not too close and not too far' from one another, across non-geographical proximity dimensions. This principle is tested on a survey of 542 Norwegian firms conducted in 2013, containing information about firm-level innovation activities and key innovation partners. The results of the ordinal logit regression analysis substantiate the Goldilocks principle, as the most innovative firms are found amongst those that collaborate with partners at medium levels of proximity for all non-geographical dimensions. The analysis also underscores the importance of the presence of a substitution-innovation mechanism, with geographical distance problems being compensated by proximity in other dimensions as a driver of innovation, whilst there is no support for a potential overlap-innovation mechanism.

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Spatial and Non-spatial Proximities in Inter-firm Relations: An Empirical Analysis

Cited by 59 publications

References 28 publications

How intermediary organizations facilitate university–industry technology transfer: A proximity approach

How intermediary organizations facilitate university–industry technology transfer: A proximity approach

Drivers of University–Industry Links: The Case of Knowledge-Intensive Business Service Firms in Rural Locations

Not too close, not too far: testing the Goldilocks principle of ‘optimal’ distance in innovation networks

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