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To take relative actions to cope with the threat which network finance information security now encounters by constructing controlling tactical and synergetic model.

It is practical to use the synergetic self‐organization theory to calculate the effects that the force of synergetic system of controlling tactics to financial information security makes on network financial system, and it is also practical to construct the synergetic model of controlling tactics to network financial information security on the basis of it.

Through applying synergetic analysis to controlling tactical system of network financial information security, it can be found out that controlling tactical system is an open system which changes from disorder to order and which keeps away from a balancing state. As an opening system, controlling tactics are interacting with outside from now and then.

Network financial information security takes on dynamics, relativity, integrity and complexity. Accessibility of data is the main limitations which model will be applied.

From the view of network financial information security, constructing controlling tactical and synergetic model of information security are explained.

Network finance is orientated as a special social and economic system. The author does analysis on the network financial system, and expounds order parameters and model of network financial system.

The purpose of this paper is to investigate the effect of different types of networking, namely, business networking, financial networking and political networking, on the performance of new ventures and the extent to which competitive advantage influences the process.

Data were collected through a structured questionnaire using sample size of 319 newly established ventures in Pakistan – an emerging economy. The hypotheses were tested with structural equation modeling by using AMOS 21.

Results of the study indicate that business networking, financial networking and political networking significantly and positively contribute to new ventures performance and competitive advantage. Results also show that competitive advantage is a strong mediator between financial networking and new venture performance, as well as between business networking and new venture performance, respectively. However, in case of relationship between political networking and new venture performance, competitive advantage plays only a partial mediating role.

The study suggests that the owners and managers of new ventures should devote considerable efforts to developing all the three types of networks; in particular these networks are important for newly established ventures operating in emerging markets to access resources and to enhance performance.

Extensive review of available literature indicates that this is the first paper to assess the impact of networking on new ventures’ performance with a mediating role of competitive advantage. This study contributes to the existing literature through empirical evidence.

The purpose of this paper is to examine how firms manage earnings when firms are in interconnected networks, that is, when firms are interconnected to each other in a way that the survival of one firm is crucial to the survival of other firms connected to it.

The paper employs network typology to provide some insight on the earnings management behaviour of firms in regulated and unregulated networks or systems.

The author shows that firms in the inner core of interconnected networks are more likely to rely on income-smoothing behaviour as a preferred form of earnings management because it stabilises the firm’s link with other firms in the network. In regulated networks, the author proposes a negative relationship between a firm’s network centrality and the number of earnings management strategies the manager can adopt. Also, the author proposes a positive relationship between a firm’s network centrality and the propensity to smooth earnings or income when firms are concerned about their reputation or regulatory scrutiny.

This paper is a brief note on earnings management, and is the first study to provide a perspective on how earnings management can be explained using a network typology.

This study aims to provide an in-depth understanding of investors’ cognition and decision-making process with regard to internet financial products. The objective is to effectively guide users’ rational investments.

First, based on grounded theory, this study develops a tool for measuring users’ perceived value (PV) of internet financial products via in-depth interviews. Then, after comprehensively considering users’ environmental, individual and psychological characteristics, this study proposes a theoretical model of internet financial product investment decisions based on the PV of users. Finally, an empirical study is conducted on 693 valid sample data from e-commerce and online banking financial platforms.

The empirical results suggest that network externalities influence users’ financial behavior by herding (HE) (imitating others and discounting their own information) and PV. PV and HE are key factors in users’ investment decisions with regard to internet financial products. Moreover, users’ self-efficacy (SE) and platform type play moderate roles in the influence mechanism.

The research conclusions provide valuable references for designing financial products and establishing regulatory rules, which will help the internet financial industry to grow soundly and innovatively.

This study uncovers the mediating effect of HE and PV between network externalities and users’ investment intentions in the context of internet financial products. In addition, the moderating effect of users’ SE and platform types is revealed.

The purpose of this study is to bridge the gap in the literature on supply chain finance (SCF) by exploring the relationship between network capabilities and corporate financial performance (CFP) in financial supply chains (FSCs).

The authors collect panel data and adopt regression analysis to analyse the joint investment activities among 1359 manufacturing firms and 289 financial service providers in China to explore how network capabilities, both network power and network centrality, improve CFP in the FSCs.

Under the FSCs environments, network centrality (i.e. eigenvector centrality, closeness centrality and betweenness centrality) raises CFP (ROA, ROE and Tobin's Q) and network power (node degree, clustering coefficient) also improves CFP. However, node strength from the network power stream has a negative effect on Tobin's Q, indicating that when the partner of a firm has an extremely strong influence in FSCs; this weakens the bargaining ability and flexibility of the focal firm, thus reducing its long-term financial performance.

The joint investment activities among supply chain partners and financial service providers help managers understand the advanced financing solutions generated by internal and external network organisations as well as be aware of network capabilities' impact on CFP in FSCs.

This study answers the call for more empirical research on SCF to provide a broader sample to examine financial supply chain management. This is one of the earliest studies to shed light on a new perspective – how network capabilities improve CFP in the FSCs.

The financial turbulence resulting from the global financial crisis sparked the interest in improving understanding of financial risks. The transmission of financial institution failures can be determined from the prevailing network structures between banks. The purpose of this study is to identify relationship between payment system network characteristics and financial system condition.

The characteristics of the interbank network structure in the payment system are identified using a graph theory and the relationship between the network characteristics of interbank transactions in the payment system and financial system stability is examined using a vector auto regression model.

This study shows that the connectedness of large-value payment transaction is more segmented compared to that of retail value payments. A significant relationship is observed between the characteristics of the network and the large-value payment transactions.

This study found the connectedness of large-value transactions is more segmented when compared to retail-value transactions. It also shows a causal effect of the network characteristic on the financial system stability.

Unlike existing studies, this study considers both the connectedness in large-value transactions and retail-value transactions.

By applying models of social and economic networks to financial institutions, the purpose of this paper is to address the issues of how policy makers can promote financial network stability and social efficiency.

The authors characterize the decentralized network formation of financial institutions in three stages through which institutions choose to become member banks connected to a central bank, bank-holding company subsidiaries or non-banks. Financial institutions choose one of the three roles in an endogenous process by considering the effects of sharing shocks among the members of the network. In the model, there is a social-welfare-maximizing government regulator at the center of the network.

The authors show that the stable equilibrium network is not always the efficient network, so the central authority must use policy instruments to ensure that the stable equilibrium network is as close as possible to the efficient network.

To obtain the theoretical results, the authors make assumptions about the utility function and risk aversion of a financial institution, as well as about the costs of network formation. These assumptions might need to be relaxed to bring the model closer to real-world institutions.

The results suggest that regulators must try to set their policy variables to make the efficient network as close as possible to the stable network.

The contribution is to incorporate concepts from social network theory into the modeling of financial networks. The results may be of use to regulators in maintaining the stability of the financial system.

From a financial stability viewpoint, this paper aims to study cyclical interdependencies arising from the cross-holding of securities in the Colombian financial system.

Cross-holding of securities in financial systems occurs when two financial institutions hold securities issued by each other or when more than two financial institutions hold securities issued by each other in a circular structure. Securities cross-holding is key for financial stability because of potential contagion arising from cyclical interdependencies in the connective architecture of financial systems. The presence of cyclical interdependencies is studied based on network analysis. The data set is a multilayer network that comprises bonds, certificates of deposit and equity issued and held by Colombian financial institutions from 2016 to 2019.

Results show that the extent of securities’ cyclical interdependencies is particularly low and stable – even when cross-holding across different types of securities is considered.

The monetary value of exposures and their size with respect to financial institutions’ balance sheets are not considered. Studying the impact on the financial system’s solvency is a compulsory research path.

The network topology suggests that increased potential contagion by cyclical interdependencies and feedback effects from securities cross-holding is rather limited.

To the best of the authors’ knowledge, this is the first time that cyclical interdependencies arising from the securities cross-holding are studied. From a financial stability perspective, the methodology is general and promising for monitoring and analytical purposes.

Drawing on broaden-and-build theory and promotion- and prevention-focus theory, the authors examined the role of positive and negative affectivity (PANA) on the riskiness of investment decisions. The authors also examined the mediating impact of financial knowledge network intensity (i.e. the level of communication with financially literate others in employees' social network) on the PANA—riskiness of investment decisions relationship.

Study 1 used a sample of undergraduate students and operationalized risk using a hypothetical investment scenario. Study 2 replicated and extended the Study 1 findings using employees and operationalized risk using their real-world investment allocations.

Both Studies 1 and 2 provided support for the negative direct relationship between NA and the riskiness of investment decisions. Study 2 found PA was marginally positively related to the riskiness of investment decisions. Financial knowledge network intensity mediated the relationship between NA and the riskiness of investment decisions in Study 2.

The findings suggest that employees who see the world in a generally negative light tended to have weaker financial knowledge networks, and this may be one mechanism that explains why they make low-risk investments.

Financial knowledge networks can provide access to critical information regarding investment opportunities. Socialization training or social mixers can be used to help employees build and improve their financial knowledge networks.

The authors integrate the research on PANA, social networks, and investment decisions to illuminate the social network processes that explain how affectivity impacts the riskiness of retirement investment decisions.

The paper models the financial interconnectedness and systemic risk of shadow banks using Granger-causal network-based measures and takes the Indian shadow bank crisis of 2018–2019 as a systemic event.

The paper employs pairwise linear Granger-causality tests adjusted for heteroskedasticity and return autocorrelation on a rolling window of weekly returns data of 52 financial institutions from 2016 to 2019 to construct network-based measures and calculate network centrality. The Granger-causal network-based measure ranking of financial institutions in the pre-crisis period (explanatory variable) is rank-regressed with the ranking of financial institutions based on maximum percentage loss suffered by them during the crises period (dependent variable).

The empirical result demonstrated that the shadow bank complex network during the crisis is denser, more interconnected and more correlated than the tranquil period. The closeness, eigenvector, and PageRank centrality established the systemic risk transmitter and receiver roles of institutions. The financial institutions that are more central and hold prestigious positions due to their incoming links suffered maximum loss. The shadow bank network also showed small-world phenomena similar to social networks. Granger-causal network-based measures have out-of-sample predictive properties and can predict the systemic risk of financial institutions.

The study considers only the publicly listed financial institutions. Also, the proposed measures are susceptible to the size of the rolling window, frequency of return and significance level of Granger-causality tests.

Supervisors and financial regulators can use the proposed measures to monitor the development of systemic risk and swiftly identify and isolate contagious financial institutions in the event of a crisis. Also, it is helpful to policymakers and researchers of an emerging economy where bilateral exposures' data between financial institutions are often not present in the public domain, plus there is a gap or delay in financial reporting.

The paper is one of the first to study systemic risk of shadow banks using a financial network comprising of commercial banks and mutual funds. It is also the first one to study systemic risk of Indian shadow banks.