Dynamic capability, ambidexterity and social network—empirical evidence from SMEs in China

PurposeThe investigation of organization's ambidextrous innovation is a challenge in the research studies of management sciences. As existent literature showed a positive relation between dynamic capability (DC) and innovation, few empirical studies are conducted to explain how DC impacts on the balanced and combined dimension of ambidexterity and still less on how social network moderates this relation. As a result, this paper aims to investigate and provide empirical evidence on DC’s influence on ambidexterity in the context of China.Design/methodology/approachBy a relational model of DC, ambidextrous innovation and social network, this study has conducted multiple regression analysis on the data collected from 350 small and medium enterprises (SMEs) in mainland China.FindingsThe results show that, DC has positive influence on both the combined and balanced dimension of ambidexterity; and both the relational network and structural network play an inverted U moderating role, where the moderation of relational network is stronger than that of structural network.Originality/valueThis study provides empirical support on DC's influence on ambidexterity together with the moderation of social network.

Evaluating borrowers’ default risk with a spatial probit model reflecting the distance in their relational network

Potential relationship among loan applicants can provide valuable information for evaluating default risk. However, most of the existing credit scoring models either ignore this relationship or consider a simple connection information. This study assesses the applicants’ relation in terms of their distance estimated based on their characteristics. This information is then utilized in a proposed spatial probit model to reflect the different degree of borrowers’ relation on the default prediction of loan applicant. We apply this method to peer-to-peer Lending Club Loan data. Empirical results show that the consideration of information on the spatial autocorrelation among loan applicants can provide high predictive power for defaults.

A Relational Approach to Lexical Borrowings in the Discourse of Romanian Bilingual Immigrants in Spain

A Relational Approach to Lexical Borrowings in the Discourse of Romanian Bilingual Immigrants in Spain. This paper is a neurocognitive analysis of idiosyncratic lexical borrowings recorded in the discourse of bilingual Romanian immigrants living in Spain. The neurocognitive approach, also known as Relational Network Theory (RNT), conceives language as an interconnected relational network composed of nodes and lines, part of and connected to the general cognitive system. Linguistic processing is a result of spreading activation through the network and of interaction of the system with other biological systems. The model elegantly describes real and inferred linguistic behaviors, both well-formed and erroneous. We use this approach to explore the underlying mechanisms that trigger the emergence of linguistic interference in the discourse of bilingual speakers. We focus on several lexical borrowings selected from corpora of Romanian spoken in Spain, and we model them, using the NeuroLab tool, in relational network terms. The network modeling of these hybrid forms pinpoints new ways of understanding the differences between adapted and non-adapted, and between necessary and luxury borrowings. We conclude that the RNT model is well suited for explaining bilingual processing and, arguably, one of the few models that can account for the hybrid forms emerging in the discourse of bilingual speakers. Keywords: Relational Network Theory, lexical borrowing, Romanian, Spanish, Rumañol, neurocognitive linguistics.

Researching public art and public space

This special issue is devoted to research on the changing paradigms of public art, and of public spaces. Today all art can be characterized as public since it is mediated via relational networks. The shift of paradigm from modernist art to contemporary art coincides with this shift of paradigm – from consumption to communication – in the sense that advanced art practices had already absorbed the change from individual mediation to relational networks. In the communication network of relations, artists and works are constitutive elements. Without the works and the artists, the relational network does not exist, and vice versa: Without the network of relations, neither artists nor works are made visible. This constitutive reciprocity of relations is decisive both for theorists doing research on public art and art in public spaces, as well as for artists who are doing research in public spaces.

ImmunAL: a frame to identify the immunological markers for Mild Moderated Alzheimer's Disease applying Multiplex Network Model

Identification of immunological markers for neurodegenerative diseases resolve issues related to diagnostic and therapeutic. Neuro-specific cells experience disruptive mechanisms in the early stages of disease progression. The autophagy mechanism, guided by the autoantibodies, is one of the prime indicators of neurodegenerative diseases. Identifying autoantibodies can show a new direction. Detecting influential autoantibodies from relational networks viz., co-expression, co-methylation, etc. is a well-studied area. However, none of the studies have considered the functional affinity among the autoantibodies while selecting them from a relational network. In this regard, a two-layered multiplex network based framework has been proposed,whereby the layers consist co-expression and co-semantic scores. The networks have been formed using three distinct cases viz., diseased, controlled, and a combination of both. Subsequently, a random walk with restart mechanism has been applied to identify the influential autoantibodies, where layer switching probability and restart probability are 0.5 and 0.4 respectively. Next, pathway semantic network has been formed considering the autoantibody associated pathways. EPO and IL1RN, associated with a maximum number of pathways, are identified as the two most influential autoantibodies. The network also provides insights into possible molecular mechanisms during the pathogenic progression. Finally, MDPI and CNN3 are also identified as important biomarkers.

Key Node Discovery Algorithm Based on Multiple Relationships and Multiple Features in Social Networks

The key nodes play important roles in the processes of information propagation and opinion evolution in social networks. Previous work rarely considered multiple relationships and features into key node discovery algorithms at the same time. Based on the relational networks including the forwarding network, replying network, and mentioning network in a social network, this paper first proposes an algorithm of the overlapping user relational network to extract different relational networks with same nodes. Integrated with these relational networks, a multirelationship network is established. Subsequently, a key node discovery (KND) algorithm is presented on the basis of the shortest path, degree centrality, and random walk features in the multirelationship network. The advantages of the proposed KND algorithm are proved by the SIR propagation model and the normalized discounted cumulative gain on the multirelationship networks and single-relation networks. The experiment’s results show that the proposed KND method for finding the key nodes is superior to other baseline methods on different networks.

Geographical Relationships between Long-Tailed Goral (Naemorhedus caudatus) Populations Based on Gut Microbiome Analysis

The long-tailed goral (Naemorhedus caudatus) is an endangered species found in the mountains of eastern and northern Asia. Its populations have declined for various reasons, and this species has been designated as legally protected in South Korea. Although various ecological studies have been conducted on long-tailed gorals, none have investigated the gut microbiome until now. In the present study, we compared the diversity and composition of the gut microbiome of seven populations of Korean long-tailed gorals. By analyzing the gut microbiome composition for each regional population, it was found that four phyla—Firmicutes, Actinobacteriota, Bacteroidota, and Proteobacteria—were the most dominant in all regions on average. The alpha diversity of the gut microbiome of the goral population in the northern regions was high, while that in the southern regions was low. Through the analysis of beta diversity, the seven long-tailed goral populations have been divided into three groups: the Seoraksan population, the Samcheock population, and the Wangpicheon population. It was possible to confirm the regional migration of the animals using the gut microbiome based on the site-relational network analysis. It was found that the most stable population of long-tailed gorals in Korea was the Seoraksan population, and the closely related groups were the Samcheok and Wangpicheon populations, respectively. Wangpicheon appeared to be a major point of dispersal in the migration route of Korean long-tailed gorals.

Convergence of City Relational Network, Production Sector Structure, and Regional Development

There is a strong correlation between government intervention and urban production structure in China. Particularly, the outputs of the cities partly come from the economic rent of city relational network (CRN), which is a unique regional policy and administrative hierarchy. In order to analyze the gravity flows of CRN under the nonmarket mechanism, we attempt to build a new gravity model that adopts the production sector. The new gravity produces relational data with direction, which makes it possible to use social network analysis (SNA) and overcome the endogeneity of the linear model. The empirical results show that (1) modified new gravity model can effectively capture the distribution of CRN gravity flows and the convergence of regional development in China, (2) the CRN, which especially stems from the government financial intervention, increases the share of nontradable sectors in cities, and (3) adjustment of the production sector leads to the difference of CRN gravity flows, so asymmetric flows distribution leads to the heterogeneity of regional economic performance. Cities with higher share of nontradables have relatively slower productivity growth in long-term.

Are Spanish TTOs Prepared to Innovation in a COVID Context?

The analysis of the characteristics of Technology Transfer Offices (TTOs) is particularly important as they constitute mediating units in the relationship between the market and university research. They are responsible for the transfer and exploitation of knowledge arising in the university context. Previous studies have been inconclusive as to the importance that the size, professionalisation or age of TTOs might have on the transfer process. However, the need to explore new markets, recognise new opportunities and identify potential customers points to the importance of TTOs having a dual exploitative and exploratory orientation and an extensive relational network. More recent research in the literature, based on ambidexterity and network theory, points to the impact that these variables could have on change management and innovation in uncertain and changing environments, such as those faced by TTOs in the current pandemic context. Therefore, the aim of this paper is to analyse whether Spanish TTOs, due to their ambidextrous orientation at the organisational and individual level, and their relational network with academic and market actors, are prepared to promote innovation in a COVID-19 context. Based on a cluster analysis of 29 Spanish TTOs, our results show that just a few of the Spanish TTOs surveyed would be prepared, from the perspective of ambidexterity and their relational capital, to promote innovation in a COVID-19 context. In conclusion, Spanish TTOs and their employees should focus more on ambidexterity and building extensive relational capital so that, through mentoring, training, incubation or the provision of various resources, they can help academics take advantage of the innovation opportunities offered by the changing and uncertain environment.