Entrepreneur: Do social capital and culture matter?

[Abstract]: This paper analyzes the effect of the individual perceptions of social capital and culture in entrepreneurial aspirations before and after the economic crisis in Western Europe. Following the approach of the Theory of Planned Behavior (Ajzen, 1991), we advance the analysis of the effect of the perception of subjective norms in the entrepreneurial intentions. We studied the Total Early-Stage Entrepreneurial Activity (TEA) of twelve countries in 2006 and 2010. The results reveal that the perception of having social networks is significant for the TEA, and it increases after the economic crisis. However, the cultural factors do not have a significant impact, except the one related with the perception of social equality. The results obtained through the double perspective of this analysis (individual´s social capital vs cultural factor of individualistic perspective) offers a certain dilemma when we try to understand the entrepreneurial intention through the individual´s perception of subjective norms, following the Ajzen´s model. The more individualist is a person, the lower the weight of its social capital. However, the more a person has access to social networks, the greater his entrepreneurial intention will be. This result opens future lines of research focused on understanding the value of the individual´s social capital for different countries and groups of entrepreneurs

DancingLines: An Analytical Scheme to Depict Cross-Platform Event Popularity

Nowadays, events usually burst and are propagated online through multiple modern media like social networks and search engines. There exists various research discussing the event dissemination trends on individual medium, while few studies focus on event popularity analysis from a cross-platform perspective. Challenges come from the vast diversity of events and media, limited access to aligned datasets across different media and a great deal of noise in the datasets. In this paper, we design DancingLines, an innovative scheme that captures and quantitatively analyzes event popularity between pairwise text media. It contains two models: TF-SW, a semantic-aware popularity quantification model, based on an integrated weight coefficient leveraging Word2Vec and TextRank; and wDTW-CD, a pairwise event popularity time series alignment model matching different event phases adapted from Dynamic Time Warping. We also propose three metrics to interpret event popularity trends between pairwise social platforms. Experimental results on eighteen real-world event datasets from an influential social network and a popular search engine validate the effectiveness and applicability of our scheme. DancingLines is demonstrated to possess broad application potentials for discovering the knowledge of various aspects related to events and different media

Take it personally - A Python library for data enrichment for infometrical applications

Like every other social sphere, science is influenced by individual characteristics of researchers. However, for investigations on scientific networks, only little data about the social background of researchers, e.g. social origin, gender, affiliation etc., is available. This paper introduces ”Take it personally - TIP”, a conceptual model and library currently under development, which aims to support the semantic enrichment of publication databases with semantically related background information which resides elsewhere in the (semantic) web, such as Wikidata. The supplementary information enriches the original information in the publication databases and thus facilitates the creation of complex scientific knowledge graphs. Such enrichment helps to improve the scientometric analysis of scientific publications as they can also take social backgrounds of researchers into account and to understand social structure in research communities

A Techno-Social Approach for Achieving Online Readership Popularity

Understanding what drives readership popularity in online interactive media has important implications to individual practitioners and net-enabled organizations. For instance, it helps generate a success “formula” for designing potentially popular websites in the increasingly competitive online world. So far, research in this area lacks a unified approach in guiding the design of online interactive media as well as in predicting their successful adoption and use, from both technological and social orientations. Drawing upon the media success literature and related social cognition theories, we establish a techno-social model for achieving online readership popularity, accounting for the impacts of technology-dependent and media-embedded characteristics. The proposed model and hypotheses will be tested by a content analysis of 100+ very popular weblogs and survey of 2000+ active weblog readers. This research carries significant value for sustaining community- and firm-based user networks that have been recognized as an important source of social and knowledge capitals

ERP project’s internal stakeholder network and how it influences the project’s outcome

So far little effort has been put into researching the importance of internal ERP project stakeholders’ mutual interactions, realizing the project’s complexity, influence on the whole organization, and high risk for a useful final outcome. This research analyzes the stakeholders’ interactions and positions in the project network, their criticality, potential bottlenecks and conflicts. The main methods used are Social Network Analysis, and the elicitation of drivers for the individual players. Information was collected from several stakeholders from three large ERP projects all in global companies headquartered in Finland,together with representatives from two different ERP vendors, and with two experienced ERP consultants. The analysis gives quantitative as well as qualitative characterization of stakeholder criticality (mostly the Project Manager(s), the Business Owner(s) and the Process Owner(s)) , degree of centrality, closeness , mediating or bottleneck roles, relational ties and conflicts (individual, besides those between business and project organizations) , and clique formations. A generic internal stakeholder network model is established as well as the criticality of the project phases. The results are summarized in the form of a list of recommendations for future ERP projects to address the internal stakeholder impacts .Project management should utilize the latest technology to provide tools to increase the interaction between the stakeholders and to monitor the strength of these relations. Social network analysis tools could be used in the projects to visualize the stakeholder relations in order to better understand the possible risks related to the relations (or lack of them).ERP; Social networks ; Enterprise resource planning; Stakeholders

DEVELOPMENT OF THE CITTASLOW NETWORK IN POLAND AND IN CHINA

ABSTRACT: The purpose of this article has been to present the genesis and development of the Polish National Cittaslow Network and China National Cittaslow Network and to draw the attention to the differences in the Polish and Chinese ‘slow city’ model. The period of analysis is 2007 to 2021. The research methods included a critical analysis of the literature and source materials (statutes, regulations and other strategic documents of the association), comparative analysis and case study. The main differences between the Polish and Chinese Cittaslow Network are related to cultural differences between these countries, with the different political system and administrative division. The model of development of Cittaslow in Poland is closer to the European ‘slow city’ model.  The Chinese network is at the stage of searching for individual solutions adequate to the social, cultural and economic realities of the country.The purpose of this article is to present the genesis and development of the Polish National Cittaslow Network and the Chinese National Cittaslow Network, as well as to draw attention to differences between the two ‘slow city’ models, respectively. The period of analysis spans the years 2007-2021. The research methods included a critical analysis of the relevant literature and source materials (statutes, regulations and other strategic documents of the association) and a comparative analysis. The main differences between the Polish and Chinese Cittaslow networks are related to cultural differences between these countries, with the dissimilar political systems and administrative divisions. The model of Cittaslow development in Poland is closer to the European ‘slow city’ model. The Chinese network is at the stage of searching for individual solutions corresponding to social, cultural and economic realities of the country

Network Effects on Learning during Disasters: The Case of Australian Bushfires

Understanding factors that enhance or diminish learning levels of individuals and teams is significant for achieving both individual (low level) and organisational (high level) goals. In this study, the effect of social network factors at all levels of analysis (actor level, dyadic level and network level) on learning attitudes of emergency personnel in emergency events is investigated. Based on social network concepts of structural holes and strength of weak ties, and the social influence model of learning, a conceptual model is developed. To test and validate the model, data was collected from the transcripts of the 2009 Victorian Bushfires Royal Commission reports in conjunction with the 2008 Australian Inter-Service Incident Management System (AIIMS) survey. Secondly, network measures were applied for exploring the association with learning from a sample of people working within Incident Management Teams, combat roles and coordination centres across Australia and New Zealand. Empirical results suggest that social network factors at all levels of analysis (actor, dyadic and network levels) of emergency personnel play a crucial role in individual and team learning. The contextual implication from the quantitative and qualitative findings of this research is that when approaches for improving the emergency response at an interpersonal level are contemplated, the importance of social structure, position and relations in the networks of emergency personnel needs to be considered carefully as part of the overall individual and organisation-level goals. With this model of learning-related work activity, based on network connectedness, emergency staff members can strengthen their capacity to be flexible and adaptable. The findings of this study may be appreciated by emergency managers or administrators for developing an emergency practice culture to optimise individual and team learning and adaptability within an emergency management context

Older Adults in Nursing Homes: Assessing Relationships Between Multiple Constructs of Social Integration, Facility Characteristics, and Health

An extensive body of research has examined connections between older adults' social worlds and health and well-being, particularly for community-dwelling older adults. Yet, little is known about the social worlds of older adults living in nursing homes because of this population's exclusion from many studies and national databases. Further, the influence of social workers and culture change practices on the social lives of nursing home residents is not well-documented. This research assessed the relationships between multiple social integration (i.e., social networks, social capital, social support, and social engagement) and health (i.e., depression, functional health and well-being) constructs, and examined the influence of facility characteristics (i.e., culture change, role of social workers) on these variables. This study drew on a model based on social network theory developed by Berkman, Glass, Brissette, and Seeman (2000). Data were collected at 30 nursing homes in Northeast Kansas using a cross-sectional, quantitative, planned missing data design with random sampling techniques. Data collection occurred at the individual-level through in-person structured interviews with older adult nursing home residents (N = 140) and at the facility-level (N = 30) with social service directors and nursing home administrators. Data were imputed using multiple imputation, and multilevel confirmatory factor analysis was used to verify measurement properties. Multilevel structural equation modeling (MSEM) was used to answer the research questions and test hypotheses. Findings revealed that the data did fit the proposed model supporting social network theory, showing that social networks and social group participation indirectly influence depression and functional health and well-being primarily via social engagement. Social capital had a direct influence on both health constructs. Further, the relationships sub-scale of culture change involvement significantly influenced between-level differences in residents' social networks, and the number of social workers in a nursing home was positively associated with between-level differences in residents' social support. These findings inform social integration strategies for reducing social isolation and related declines in physical and mental health for older adults in nursing homes as well as nursing home and health care policies for improving quality of life of those utilizing long term care services

Exploring and Predicting Online Collective Action on Patients’ Virtual Communities: a Multi-method Investigation in France

Virtual patients’ communities are developing on the Internet. These communities allow frequent interactions among patients, who can share health-related information within an interactive environment. However, we know very little about what determines patients’ online collective action on Web 2.0 social networks. Accordingly, this research-in-progress examines why patients interact with others and communicate on topics related with their disease through these virtual communities. Drawing on goal-directed behavior (MGB) and the expectancy-value (EVT) theories, we have developed a model for examining patients’ interactions with virtual communities. This multi-method, qualitative and quantitative approach enables one to explore patients’ interactions and measure the determinants of online collective action on virtual spaces. The results from the qualitative analysis of 54 interviews conducted with patients, patient’s relatives, health 2.0 professionals, doctors and caregivers are discussed herein. This research is expected to increase our knowledge regarding the individual dynamics and interactions that surround online patients’ communities

Social Network Analysis using Cultural Algorithms and its Variants

Finding relationships between social entities and discovering the underlying structures of networks are fundamental tasks for analyzing social networks. In recent years, various methods have been suggested to study these networks efficiently, however, due to the dynamic and complex nature that these networks have, a lot of open problems still exist in the field. The aim of this research is to propose an integrated computational model to study the structure and behavior of the complex social network. The focus of this research work is on two major classic problems in the field which are called community detection and link prediction. Moreover, a problem of population adaptation through knowledge migration in real-life social systems has been identified to model and study through the proposed method. To the best of our knowledge, this is the first work in the field which is exploring this concept through this approach. In this research, a new adaptive knowledge-based evolutionary framework is defined to investigate the structure of social networks by adopting a multi-population cultural algorithm. The core of the model is designed based on a unique community-oriented approach to estimate the existence of a relationship between social entities in the network. In each evolutionary cycle, the normative knowledge is shaped through the extraction of the topological knowledge from the structure of the network. This source of knowledge is utilized for the various network analysis tasks such as estimating the quality of relation between social entities, related studies regarding the link prediction, population adaption, and knowledge formation. The main contributions of this work can be summarized in introducing a novel method to define, extract and represent different sources of knowledge from a snapshot of a given network to determine the range of the optimal solution, and building a probability matrix to show the quality of relations between pairs of actors in the system. Introducing a new similarity metric, utilizing the prior knowledge in dynamic social network analysis and study the co-evolution of societies in a case of individual migration are another major contributions of this work. According to the obtained results, utilizing the proposed approach in community detection problem can reduce the search space size by 80%. It also can improve the accuracy of the search process in high dense networks by up to 30% compared with the other well-known methods. Addressing the link prediction problem through the proposed approach also can reach the comparable results with other methods and predict the next state of the system with a notably high accuracy. In addition, the obtained results from the study of population adaption through knowledge migration indicate that population with prior knowledge about an environment can adapt themselves to the new environment faster than the ones who do not have this knowledge if the level of changes between the two environments is less than 25%. Therefore, utilizing this approach in dynamic social network analysis can reduce the search time and space significantly (up to above 90%), if the snapshots of the system are taken when the level of changes in the network structure is within 25%. In summary, the experimental results indicate that this knowledge-based approach is capable of exploring the evolution and structure of the network with the high level of accuracy while it improves the performance by reducing the search space and processing time