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The study utilises unique survey data gathered from 12,427 party members. The dependent variable measures party members’ in-party commitment and is based on willingness to donate money, to contribute effort, the feeling of belonging in the party network and social trust in the party network.

In this article, we study how different extra-parliamentary online and offline activities are associated with in-party commitment amongst political party members from the six largest Finnish parties. We especially delve into the differences between members of the Finnish parties.

We found that extra-parliamentary political activity, including connective action through social media networks and collective action through civic organisations, is highly associated with members’ in-party commitment. Additionally, members of the newer identity parties more effectively utilised social media networks, whilst the traditional interest parties were still more linked to traditional forms of extra-parliamentary political action.

By employing the sociological network theory perspective, the study contributes to ongoing discussions surrounding the impact of social media on political participation amongst party members, both within and beyond the confines of political parties.

The purpose of this study is to investigate whether and how inter-firm cooperation and firm age moderate the relationship between family ownership and productivity.

We first estimate the total factor productivity (TFP) of a large sample of Italian firms observed over the period 2010–2018 and then apply a Poisson random effects model.

TFP is, on average, higher for non-family firms (non-FFs) than for FF. Furthermore, inter-organizational cooperation and firm age mitigate the negative effect of family ownership. In detail, it is found that belonging to a network acts as a moderator in different ways according to firm age. Indeed, young FFs underperform non-FF peers, although the TFP gap decreases with age. In contrast, the benefits of a formal network are high for older FFs, suggesting that an age-related learning process is at work.

The study provides evidence that FFs can outperform non-FFs when they move away from Socio-Emotional Wealth-centered reference points and exploit knowledge flows arising from high levels of social capital. In the case of mature FFs, networking is a driver of TFP, allowing them to acquire external resources. Since FFs often do not have sufficient in-house knowledge and resources, they must be aware of the value of business cooperation. While preserving the familiar identity of small companies, networks grant FFs the competitive and scale advantages of being large.

Despite the wide but ambiguous body of research on the performance gap between FFs and non-FFs, little is known about the role of FFs’ heterogeneity. This study has proven successful in detecting age as a factor in heterogeneity, specifically to explain the network effect on the link between ownership and TFP. Based on a representative sample, the study provides a solid framework for FFs, policymakers and academic research on family-owned companies.

Using overlapped portfolio data on public equity funds in Korea, the authors construct several types of fund-stock weighted bipartite networks and measure fund network centrality. The authors also examine the relationship between network centrality and fund investment performance. The authors' results are three-fold. First, the authors find that the fund centrality of the network in which funds and stocks are connected based on the most active investing behavior positively affects the fund performance. Second, the funds with a high centrality level based on the same network generate higher returns by holding stocks with high value uncertainty. Third, the authors find that fund centrality is not associated with herd behavior. Based on these results, the authors argue that fund centrality is a proxy of information advantage and skill of fund managers. The authors' paper shows that network analysis could be a new way to identify funds with better performance and measure the skill and information advantage to construct an optimal portfolio.

Credit scoring is important for financial institutions in order to accurately predict the likelihood of business failure. Related studies have shown that machine learning techniques, such as neural networks, outperform many statistical approaches to solving this type of problem, and advanced machine learning techniques, such as classifier ensembles and hybrid classifiers, provide better prediction performance than single machine learning based classification techniques. However, it is not known which type of advanced classification technique performs better in terms of financial distress prediction. The paper aims to discuss these issues.

This paper compares neural network ensembles and hybrid neural networks over three benchmarking credit scoring related data sets, which are Australian, German, and Japanese data sets.

The experimental results show that hybrid neural networks and neural network ensembles outperform the single neural network. Although hybrid neural networks perform slightly better than neural network ensembles in terms of predication accuracy and errors with two of the data sets, there is no significant difference between the two types of prediction models.

The originality of this paper is in comparing two types of advanced classification techniques, i.e. hybrid and ensemble learning techniques, in terms of financial distress prediction.

Presents descriptive information on interpersonal networks, both inside and outside of one′s organization, among managerial and professional women and men. Sex differences were also examined. Data were collected from 57 women and 55 men in early and mid‐career stages using questionnaires. Respondents indicated an average of 4.9 individuals in their inside networks and 2.8 individuals in their outside networks. There was a higher percentage of men in both networks, but the difference was smaller in outside than in inside networks. Respondents interacted with inside and outside network members about once a week. Inside network members held staff rather than line jobs, were at slightly higher organizational levels and were only modestly connected to powerful organizational leaders. Outside networks consisted mostly of friends and spouses. The networks of women and men had some differences. Women′s networks contained more women than did men′s networks. Women also received a greater number of developmental functions from their outside network, with a similar tendency from their inside network as well.

This paper proposes a new approach source node exclusion method (SNEM) to evaluate terminal pair reliability of complex communication networks.

The proposed approach breaks a non‐series‐parallel network to obtain its sub‐networks by excluding the source node from rest of the network. The reliabilities of these sub‐networks are thereafter computed by first applying the series‐parallel‐reductions to it and if any sub‐network results into another non‐series‐parallel network then it is solved by the recursive application of SNEM.

The proposed method has been applied on a variety of network and found to be quite simple, robust, and fast for terminal pair reliability evaluation of large and complex networks.

The proposed approach is quite simple in application and applicable to any general networks, i.e. directed and undirected. The method does not require any prior information such as path (or cut) sets of the network and their pre‐processing thereafter or perform complex tests on networks to match a predefined criterion.

The proposed approach provides an easy to develop and easy to use tool to determine terminal pair reliability of a communication network. The approach is particularly useful for communication network designer and analysts.

Management of heterogeneous networks continues to be complicated by the persistence of proprietary management schemes. Thus the need for integration of network management capabilities is pressing. One approach is to provide a proprietary system for equipment of other vendors. A preferred approach is to provide internationally adopted network management standards. ISO has adopted this approach, and is developing standards for managing networks, as part of the OSI effort. OSI management functionality includes five areas: configuration, fault, performance, management, accounting and security management. In the early 1990s, a wide cross section of vendors should begin to deliver their initial OSI Management product offerings.

There exist large gaps in research about social networking services, for example in their development. Most of these networks lack any scientific or engineered base in their designing and developing processes. In this paper, a holistic model will be described for the development of social network sites and parts of a scientific social network (SSN) will be developed using it. Users of this site are faculties, students and R&D personnel of a university or an enterprise. The paper aims to discuss these issues.

In this paper, a SSN site is designed along with a brief description of a social network site development methodology. The structure of methodology is based on conceptual template for the construction of a methodology. Using this methodology, a group of 50 users (from all three types of end-users) have been chosen to be interviewed about their expectations from the mentioned site.

Based on the interview, it was discovered that their view about social networks is inflexible and they do not have any new visions about functionalities of these networks. Their emphasis was mostly on exchanging and sharing role of this site. Design and development of social network sites based on the proposed methodology is easily understandable because of using state machine notations.

The innovation of this study is to propose a soft model for social network sites design based on these site's special specifications and regarding differences of them with other regular ones. This can pave the way for investors of such sites for setting up distinct social sites with new functionalities in an innovative approach.

India has seven local library networks and a national library network (INFLIBNET). However, these networks are in differing stages of development. Most are at a preliminary stage although the earliest efforts in this area took place in 1989. This paper presents the results of a survey on factors affecting the development of local library networks. Participating libraries in four networks were administered a structured questionnaire. The study reveals that organisational factors such as planning, governance, funding communication and delivery, and administration are related to each other. Moreover, many factors are highly dependent on each other. Therefore, the library networks should try to raise the levels of awareness among participating libraries to develop the local library networks successfully.

As libraries make increasing use of computer resources, a local network that interconnects personal computers and other machines within the library is becoming a necessity.