Diego Suárez

Bio: Diego Suárez is an academic researcher. The author has contributed to research in topics: Rural area & Risk management. The author has an hindex of 1, co-authored 1 publications receiving 2 citations.

Risks Identification and Management Related to Rural Innovation Projects through Social Networks Analysis: A Case Study in Spain

Abstract: Risk identification and management are essential in innovation projects in the rural context, where cultural differences and relations between actors are decisive for assuring a project success. Risk management is especially important when considering innovation processes in rural areas that experience conflict or are lagging in development. Although there are studies focusing on the interaction of actors, there are only a few that approach the risks associated with stakeholders. This research aims to identify the risks and the associated stakeholders and draws on a risk map in order to develop effective risk management and action plans to mitigate risk. A rural project optimizing irrigation in Spain was taken as a case study and conduct semi-structural interviews with key actors were conducted. Social Network Analysis (SNA) was applied to recognize and investigate the network of stakeholder-associated risk factors. The main risks identified in the project were associated with technical, economic, and time problems and with irrigation communities and project developers. These findings offer a new visual perspective of risk management in rural innovation projects, improving the ability to assess and efficiently mitigate the risks.

Research on the network connection mode of logistics economy in Guangdong province based on social network analysis

Abstract: PurposeThis paper aims to clarify the spatial connection characteristics and organization mode of logistics economy of 21 cities in Guangdong Province under the background of the integrated development of Guangdong, Hong Kong and Macao Bay area, and explore the spatial development characteristics and influencing factors of logistics economy in Guangdong Province.Design/methodology/approachThis paper constructs the development level model of urban logistics economy in Guangdong Province from three aspects: demand level, supply level and support level, and uses the entropy weight method to measure the development level index of urban logistics economy in Guangdong Province. Then, the traffic accessibility index model is used to measure the traffic accessibility index between cities in Guangdong Province. Finally, using the social network analysis method, combined with the development level index of urban logistics economy in Guangdong Province and the urban traffic access index in Guangdong Province, this paper analyzes the spatial connection characteristics and influencing factors of logistics economy network in Guangdong Province.FindingsThere are regional differences in the development level of logistics economy in Guangdong Province; The overall network density of its logistics economic connection is large, but there is an imbalance in the network structure, and the core edge phenomenon is obvious; Logistics economic space presents the characteristics of double core development.Research limitations/implicationsBecause the research object is the spatial connection characteristics of logistics economy in Guangdong Province, the research results may lack universality. Therefore, researchers are encouraged to put forward further tests.Practical implicationsBy studying the spatial connection mode of logistics economy in 21 cities in Guangdong Province, China, this paper promotes the original methods and empirical contributions, and constructs the research framework of spatial relationship of logistics economy. This research framework is universal to a certain extent.Social implicationsThis paper is conducive to promoting the integrated development of logistics economy in Guangdong Province and improving the balance of regional development of logistics economy.Originality/valueFirstly, this study provides a new perspective to understand the spatial relationship and spatial spillover of logistics economy from relational data rather than attribute data. Secondly, This study enriched and broadened the research topic of spatial correlation of logistics economy. Thirdly, this research aims to promote the original methods and empirical contributions. Specifically, this study establishes a comprehensive research framework on the spatial network structure of logistics economy.

The main risk factors for rural innovation in Europe: an analysis of 200 case studies

Abstract: PurposeEuropean rural development programmes are driving multi-actor interactive innovation initiatives and alliances to create an environment in which innovation acts as a tool for accelerating rural development processes. In Europe, where rural areas are facing many challenges, identifying which challenges, difficulties, obstacles or risk factors that interactive innovation projects have had to face in rural areas while being planned and set up would be interesting. The objective of this research work was to, therefore, identify and analyse the risk factors of 200 rural projects and initiatives that were selected as case studies from the whole of Europe.Design/methodology/approachThe employed methodology consisted in conducting interviews to subsequently perform statistical independence analyses of the qualitative variables characterising the found projects and risk factors.FindingsThe findings indicated that most of the risks that rural projects and initiatives faced were related to the social domain which was, in turn, the fundamental pillar of interactive innovation. Dependence was found between social risk factors appearing and the innovation type carried out; the risk factors corresponding to the political–legal risks category and the project or initiative coordinating country; and the economic–technical risks category and the initiatives' geographic magnitude.Originality/valueThis paper exposes the main risks identified within various rural innovation initiatives and projects around Europe. For this purpose, a statistical analysis of independence was performed, allowing us to generate reliable and accurate results of the main risks associated with certain descriptive characteristics (coordinating region, domain, innovation type, gender balance and geographic magnitude) of the initiatives studied.

From social networks to knowledge graphs: A plea for interdisciplinary approaches

Abstract: Contextual information is a crucial factor in interdisciplinary research on social networks. At the same time, missing linked data and missing methods for large-scale knowledge networks are a serious limitation. Only few researches have addressed the questions between data science, graph theory and social network analysis. This paper seeks to discuss how this gap can be closed. For this, we use an interdisciplinary approach trying to improve the interdisciplinary exchange and method exchange. We investigate how new methods from computer science, in particular knowledge graphs, can be used within the field of SNA. The contributions of this paper are (1) a knowledge graph model representation of a multi-layer social network, (2) the showcase of examples from different domains and (3) a perspective for more interdisciplinary discussion. We present an innovative solution to discuss coming challenges in SNA with methods from the digital humanities, in particular computer science.