Women’s Entrepreneurship: closing the gender gap in access to financial and other services and in social entrepreneurship

This study explores differences between men and women entrepreneurs and social entrepreneurs. It explores the barriers and discriminatory effects that hinder women’s entrepreneurship, including access to finance in the European Union. The study includes four case studies covering the situation in the Czech Republic, Italy, Sweden, and the United Kingdom.

Role of the educator in social software initiatives in Further and Higher Education:a conceptualisation and research agenda

Higher and further education institutions are increasingly using social software tools to support teaching and learning. A growing body of research investigates the diversity of tools and their range of contributions. However, little research has focused on investigating the role of the educator in the context of a social software initiative, even though the educator is critical for the introduction and successful use of social software in a course environment. Hence, we argue that research on social software should place greater emphasis on the educators, as their roles and activities (such as selecting the tools, developing the tasks and facilitating the student interactions on these tools) are instrumental to most aspects of a social software initiative. To this end, we have developed an agenda for future research on the role of the educator. Drawing on role theory, both as the basis for a systematic conceptualization of the educator role and as a guiding framework, we have developed a series of concrete research questions that address core issues associated with the educator roles in a social software context and provide recommendations for further investigations. By developing a research agenda we hope to stimulate research that creates a better understanding of the educator’s situation and develops guidelines to help educators carry out their social software initiatives. Considering the significant role an educator plays in the initiation and conduct of a social software initiative, our research agenda ultimately seeks to contribute to the adoption and efficient use of social software in the educational domain.

Human capital in social and commercial entrepreneurship

We advance research on human capital and entrepreneurial entry and posit that, in order to generate value, social entrepreneurship requires different configurations of human capital than commercial entrepreneurship. We develop a multilevel framework to analyse the commonalities and differences between social and commercial entrepreneurship, including the impact of general and specific human capital, of national context and its moderating effect on the human capital-entrepreneurship relationship. We find that specific entrepreneurial human capital is relatively more important in commercial entrepreneurship, and general human capital in social entrepreneurship, and that the effects of human capital depend on the rule of law.

Autochthonous heritage languages and social media:writing and bilingual practices in Low German on Facebook

This article analyses how speakers of an autochthonous heritage language (AHL) make use of digital media, through the example of Low German, a regional language used by a decreasing number of speakers mainly in northern Germany. The focus of the analysis is on Web 2.0 and its interactive potential for individual speakers. The study therefore examines linguistic practices on the social network site Facebook, with special emphasis on language choice, bilingual practices and writing in the autochthonous heritage language. The findings suggest that social network sites such as Facebook have the potential to provide new mediatized spaces for speakers of an AHL that can instigate sociolinguistic change.

Social capital and tacit knowledge sharing in organisational projects in Malaysian ICT companies

An increasing number of organisational researchers have turned to social capital theory in an attempt to better understand the impetus for knowledge sharing at the individual and organisational level. This thesis extends that research by investigating the impact of social capital on knowledge sharing at the group-level in the organisational project context. The objective of the thesis is to investigate the importance of social capital in fostering tacit knowledge sharing among the team members of a project. The analytical focus is on the Nahapiet and Ghoshal framework of social capital but also includes elements of other scholars' work. In brief, social capital is defined as an asset that is embedded in the network of relationships possessed by an individual or social unit. It is argued that the main dimensions of social capital that are of relevance to knowledge sharing are structural, cognitive, and relational because these, among other things, foster the exchange and combination of knowledge and resources among the team members. Empirically, the study is based on the grounded theory method. Data were collected from five projects in large, medium, and small ICT companies in Malaysia. Underpinned by the constant comparative method, data were derived from 55 interviews, and observations. The data were analysed using open, axial, and selective coding. The analysis also involved counting frequency occurrence from the coding generated by grounded theory to find the important items and categories under social capital dimensions and knowledge sharing, and for further explaining sub-groups within the data. The analysis shows that the most important dimension for tacit knowledge sharing is structural capital. Most importantly, the findings also suggest that structural capital is a prerequisite of cognitive capital and relational capital at the group-level in an organisational project. It also found that in a project context, relational capital is hard to realise because it requires time and frequent interactions among the team members. The findings from quantitative analysis show that frequent meetings and interactions, relationship, positions, shared visions, shared objectives, and collaboration are among the factors that foster the sharing of tacit knowledge among the team members. In conclusion, the present study adds to the existing literature on social capital in two main ways. Firstly, it distinguishes the dimensions of social capital and identifies that structural capital is the most important dimension in social capital and it is a prerequisite of cognitive and relational capital in a project context. Secondly, it identifies the causal sequence in the dimension of social capital suggesting avenues for further theoretical and empirical work in this emerging area of inquiry.

Learning and change in interorganizational networks:the case for network learning and network change

The ALBA 2002 Call for Papers asks the question ‘How do organizational learning and knowledge management contribute to organizational innovation and change?’. Intuitively, we would argue, the answer should be relatively straightforward as links between learning and change, and knowledge management and innovation, have long been commonly assumed to exist. On the basis of this assumption, theories of learning tend to focus ‘within organizations’, and assume a transfer of learning from individual to organization which in turn leads to change. However, empirically, we find these links are more difficult to articulate. Organizations exist in complex embedded economic, political, social and institutional systems, hence organizational change (or innovation) may be influenced by learning in this wider context. Based on our research in this wider interorganizational setting, we first make the case for the notion of network learning that we then explore to develop our appreciation of change in interorganizational networks, and how it may be facilitated. The paper begins with a brief review of lite rature on learning in the organizational and interorganizational context which locates our stance on organizational learning versus the learning organization, and social, distributed versus technical, centred views of organizational learning and knowledge. Developing from the view that organizational learning is “a normal, if problematic, process in every organization” (Easterby-Smith, 1997: 1109), we introduce the notion of network learning: learning by a group of organizations as a group. We argue this is also a normal, if problematic, process in organizational relationships (as distinct from interorganizational learning), which has particular implications for network change. Part two of the paper develops our analysis, drawing on empirical data from two studies of learning. The first study addresses the issue of learning to collaborate between industrial customers and suppliers, leading to the case for network learning. The second, larger scale study goes on to develop this theme, examining learning around several major change issues in a healthcare service provider network. The learning processes and outcomes around the introduction of a particularly controversial and expensive technology are described, providing a rich and contrasting case with the first study. In part three, we then discuss the implications of this work for change, and for facilitating change. Conclusions from the first study identify potential interventions designed to facilitate individual and organizational learning within the customer organization to develop individual and organizational ‘capacity to collaborate’. Translated to the network example, we observe that network change entails learning at all levels – network, organization, group and individual. However, presenting findings in terms of interventions is less meaningful in an interorganizational network setting given: the differences in authority structures; the less formalised nature of the network setting; and the importance of evaluating performance at the network rather than organizational level. Academics challenge both the idea of managing change and of managing networks. Nevertheless practitioners are faced with the issue of understanding and in fluencing change in the network setting. Thus we conclude that a network learning perspective is an important development in our understanding of organizational learning, capability and change, locating this in the wider context in which organizations are embedded. This in turn helps to develop our appreciation of facilitating change in interorganizational networks, both in terms of change issues (such as introducing a new technology), and change orientation and capability.

Network effects, network structure and consumer interaction in mobile telecommunications in Europe and Asia

This paper estimates the importance of (tariff-mediated) network effects and the impact of a consumer's social network on her choice of mobile phone provider. The study uses network data obtained from surveys of students in several European and Asian countries. We use the Quadratic Assignment Procedure, a non-parametric permutation test, to adjust for the particular error structure of network data. We find that respondents strongly coordinate their choice of mobile phone providers, but only if their provider induces network effects. This suggests that this coordination depends on network effects rather than on information contagion or pressure to conform to the social environment.

Analysis and identification of spamming behaviors in Sina Weibo microblog

Spamming has been a widespread problem for social networks. In recent years there is an increasing interest in the analysis of anti-spamming for microblogs, such as Twitter. In this paper we present a systematic research on the analysis of spamming in Sina Weibo platform, which is currently a dominant microblogging service provider in China. Our research objectives are to understand the specific spamming behaviors in Sina Weibo and find approaches to identify and block spammers in Sina Weibo based on spamming behavior classifiers. To start with the analysis of spamming behaviors we devise several effective methods to collect a large set of spammer samples, including uses of proactive honeypots and crawlers, keywords based searching and buying spammer samples directly from online merchants. We processed the database associated with these spammer samples and interestingly we found three representative spamming behaviors: Aggressive advertising, repeated duplicate reposting and aggressive following. We extract various features and compare the behaviors of spammers and legitimate users with regard to these features. It is found that spamming behaviors and normal behaviors have distinct characteristics. Based on these findings we design an automatic online spammer identification system. Through tests with real data it is demonstrated that the system can effectively detect the spamming behaviors and identify spammers in Sina Weibo.

Connecting social media to e-commerce:cold-start product recommendation using microblogging information

In recent years, the boundaries between e-commerce and social networking have become increasingly blurred. Many e-commerce websites support the mechanism of social login where users can sign on the websites using their social network identities such as their Facebook or Twitter accounts. Users can also post their newly purchased products on microblogs with links to the e-commerce product web pages. In this paper, we propose a novel solution for cross-site cold-start product recommendation, which aims to recommend products from e-commerce websites to users at social networking sites in 'cold-start' situations, a problem which has rarely been explored before. A major challenge is how to leverage knowledge extracted from social networking sites for cross-site cold-start product recommendation. We propose to use the linked users across social networking sites and e-commerce websites (users who have social networking accounts and have made purchases on e-commerce websites) as a bridge to map users' social networking features to another feature representation for product recommendation. In specific, we propose learning both users' and products' feature representations (called user embeddings and product embeddings, respectively) from data collected from e-commerce websites using recurrent neural networks and then apply a modified gradient boosting trees method to transform users' social networking features into user embeddings. We then develop a feature-based matrix factorization approach which can leverage the learnt user embeddings for cold-start product recommendation. Experimental results on a large dataset constructed from the largest Chinese microblogging service Sina Weibo and the largest Chinese B2C e-commerce website JingDong have shown the effectiveness of our proposed framework.