# 20.58 Hops, Skip & a Jump: The Regional Uniqueness of Beer Styles

Ryan M. Hynes, Bernardo S. Buarque, Ronald B. Davies & Dieter F. Kogler

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Abstract:

Perhaps more than any other product, beer evokes the place it was made. Weißbier and Germany, dubbels and Belgium, and most of all, Guinness and Ireland. Part of what makes these beers so memorable is what sets them apart and gives them their ‘taste of place’. Many studies have tried to place that taste, and due to a lack of detailed data, have relied largely on qualitative methods to do so. We introduce a novel data set of regionalized beer recipes, styles, and ingredients collected from a homebrewing website. We then turn to the methods of evolutionary economic geography to create regional ingredient networks for recipes within a style of beer, and identify which ingredients are most important to certain styles. Along with identifying these keystone ingredients, we calculate a style’s resiliency or reliance on one particular ingredient. We compare this resiliency within similar styles in different regions and across different styles in the same region to isolate the effects of region on ingredient choice. We find that while almost all beer styles have only a handful of key ingredients, some styles are more resilient than others due to readily available substitute ingredients in their region.

# 20.43 Improvement on the association strength: implementing a probabilistic measure based on combinations without repetition

Mathieu P.A. Steijn

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Abstract:

The use of co-occurrence data is common in various domains. Co-occurrence data often needs to be normalised to correct for the size-e↵ect. To this end, van Eck and Waltman (2009) recommend a probabilistic measure known as the association strength. However, this formula is based on combinations with repetition, even though in most uses self-co-occurrences are non-existent or irrelevant. A more accurate measure based on combinations without repetition is introduced here and compared to the original formula in mathematical derivations, simulations, and patent data, which shows that the original formula overestimates the relation between a pair and that some pairs are disproportionally more overestimated than others. The new measure is available in the EconGeo package for R by Balland (2016).

# 20.28 Anatomy of a techno-creative community – the role of places and events in the emergence of videomapping in Nantes

Etienne Capron, Dominique Sagot-Duvauroux & Raphaël Suire

 

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Abstract:

This article aims to study the role of places and events in the structuring of a community of innovation whose practice is at the crossroads of art and tech – videomapping. Based on an exploratory case study, we observe the relationships between the different actors who form subgroups, sharing a common interest in a techno-creative practice – but whose collective innovation dynamic is only in its beginnings. We also document the usage of places and events in their intermediation role for these subgroups. This reveals preferential circulations – patterns of moves among a set of focal locations in the city for a community – and the crucial role of these locations in creative communities emergence.

# 20.15 Related variety, recombinant knowledge and regional innovation. Evidence for Sweden, 1991-2010

Mikhail Martynovich and Josef Taalbi

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Abstract:

This study investigates how related variety in the regional employment mix affects the innovation output of a region. Departing from the idea of recombinant innovation, previous research has argued that related variety enhances regional innovation as inter-industry knowledge spillovers occur more easily between different but cognitively similar industries. This study combines a novel dataset and related variety measures based on network theory, which allows a more nuanced perspective on the relationship between related variety and regional innovation. The principal novelty of the paper lies in employing new data on product innovations commercialised by Swedish manufacturing firms between 1970 and 2013. In this respect, it allows a direct measure of regional innovation output as compared to patent measures, usually employed in similar studies. The second contribution of this paper is that we employ network-topology based  measures of related variety that allow us to measure relatedness as the recombination rather than direct flow of knowledge. We argue that this measure comes closer to the notion of innovation as spurred by recombination and show that this measure is a superior predictor of innovation activity.

# 19.27 A shot in the dark? Policy influence on cluster networks

Holger Graf & Tom Broekel

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Abstract: Cluster policies are often intended and designed to promote interaction in R&D among co-located organisations, as local knowledge interactions are perceived to be underdeveloped. In contrast to the popularity of the policy measure little is known about its impact on knowledge networks, because most scientific evaluations focus on impacts at the firm level. Using the example of the BioRegio contest, we explore cluster policy effects on local patent co-application and co-invention networks observed from 1985 to 2013, in 17 German regions. We find that the initiative increases network size and innovation activities during the funding period but not afterwards. The impact of the BioRegio contest on network cohesion is moderate. In contrast, general project-based R&D subsidisation is found to support cohesion more robustly.

# 19.05 The network effects of NGOs on social capital and innovation of smallholder farmers. A case study in Peru

D. Hartmann and A. Arata and M. Bezerra and F.L. Pinheiro

 

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Abstract: The impact of Non-Government Organizations (NGOs) on the local development of rural areas has rarely been explored empirically. Here we employ methods from network science to evaluate the impact of an NGO’s activities on the social capital and innovation of three Peruvian farming communities between 2003 and 2018. Data was collected from in-depth interviews with farmers, including information about the farmers’ socioeconomic characteristics, types of interactions with the NGO, and innovations in processes, products, marketing, and organization. Our findings show that the NGO had a significant impact on the local social cohesion and innovation performance of the farmers. The NGO helped to connect farmers from different villages, provided access to external knowledge, and facilitated the establishment of a local productive organization. Yet, the NGO also changed the local power structure by becoming the most central agent in the local innovation system. The NGO’s centrality declined, though, at later stages of the development project as local agents took over the role of the NGO. Moreover, econometric results show that having a link with the NGO is associated with a significantly more central role of the farmers in the local network. However, only close cooperation with the NGO, such as membership in the local productive organization or active participation in technical training workshops was associated with a significantly higher innovation performance. Finally, our study demonstrates that methods from network science can help to empirically evaluate and monitor the effects of NGOs on local development at different stages of their development interventions.

# 15.04 Proximity, knowledge base and the innovation process: The case of Unilever’s Becel diet margarine

Mila Davids & Koen Frenken

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The proximity concept refers to types of inter-organizational relationships that are expected to facilitate interactive learning and collaborative innovation. Different forms of proximity include geographical, cognitive, social, institutional and organizational proximity. Following an extensive case study of a new diet margarine developed by Unilever, we extent the proximity framework by theorizing how the relative importance of each proximity dimension depends on the type of knowledge being produced, where we distinguish between analytical, synthetic and symbolic knowledge. We argue that our theoretical framework in principle applies to product innovations in all science-based industries.

# 15.02 The geography and evolution of complex knowledge

Pierre-Alexandre Balland & David L. Rigby

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There is consensus among scholars and policy makers that knowledge is one of the key drivers of long-run economic growth. It is also clear from the literature that not all knowledge has the same value. However, too often in economic geography and cognate fields we have been obsessed with counting knowledge inputs and outputs rather than assessing the quality of knowledge produced. In this paper we measure the complexity of knowledge across patent classes and we map the distribution and the evolution of knowledge complexity across U.S. cities from 1975 to 2004. We build on the 2-mode structural network analysis proposed by Hidalgo and Hausmann (2009) to develop a knowledge complexity index (KCI) for Metropolitan Statistical Areas (MSAs). The KCI is based on more than 2 million patent records from the USPTO, and combines information on the technological structure of 366 MSAs with the 2-mode network that connects cities to the 438 primary (USPTO) technology classes in which they have Relative Technological Advantage (RTA). The complexity of the knowledge structure of cities is based on the range and ubiquity of the technologies they develop. The KCI indicates whether the knowledge generated in a given city can be produced in many other places, or if it is so sophisticated that it can be produced only in a few select locations. We find that knowledge complexity is unevenly distributed across the U.S. and that cities with the most complex technological structures are not necessarily those that produce most patents.

# 11.07 Explaining the structure of inter-organizational networks using exponential random graph models: does proximity matter?

Tom Broekel and Matté Hartog

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A key question raised in recent years is which factors determine the structure of inter-organizational networks. While the focus has primarily been on different forms of proximity between organizations, which are determinants at the dyad level, recently determinants at the node and structural level have been highlighted as well. To identify the relative importance of determinants at these three different levels for the structure of networks that are observable at only one point in time, we propose the use of exponential random graph models.

Their usefulness is exemplified by an analysis of the structure of the knowledge network in the Dutch aviation industry in 2008 for which we find determinants at all different levels to matter. Out of different forms of proximity, we find that once we control for determinants at the node and structural network level, only social proximity remains significant.