Search results

This study analyzed Korea's relations table through network analysis. In particular, among the centralities, eigenvector centrality, PageRank centrality and degree were used. The author studied which network characteristics affected the value-added rate.

A network analysis method was used.

It is the inward relationship that affects the value-added ratio of Korea's industries and the outward relationship has less influence. In particular, the inward relationship not only acts as a cost but also has an effect on the rate of added value recently.

Since the three years of 2010, 2015 and 2019 are the target, the data are somewhat insufficient to generalize.

As for the value-added ratio of an industry, input is more important than output (sales). Therefore, where the input is received is very important.

It is possible to increase the understanding of the determinants of the value-added rate of Korean industries.

(1) It was clarified which side is inward or outward in determining the industry in Korea. (2) The relationship between PageRank, eigenvector centrality and degree was analyzed in Korean cases. (3) Input is a cost and acts to increase added value.

The purpose of this study is to build a consensus model of social network group decision-making (SNGDM) based on improved PageRank algorithm. By objectively and fairly measuring the evaluation ability of participants in the decision-making process, the authors can improve the fairness and authenticity of the weight solution of decision-makers (DM) in the decision-making process. This ensures the reliability of the final group consensus results.

This study mainly includes six parts: preference expression, calculation of DM's weight, preference aggregation, consensus measurement, opinion adjustment and alternative selection. First, Pythagorean fuzzy expression is introduced to express the preference of DMs, which expands the scope of preference expression of DMs. Second, based on the social network structure among DMs, the process of “mutual judgment” among DMs is increased to measure the evaluation ability of DMs. On this basis, the PageRank algorithm is improved to calculate the weight of DMs. This makes the process of reaching consensus more objective and fair. Third, in order to minimize the evaluation difference between groups and individuals, a preference aggregation model based on plant growth simulation algorithm (PGSA) is proposed to aggregate group preferences. Fourth, the consensus index of DMs is calculated from three levels to judge whether the consensus degree reaches the preset value. Fifth, considering the interaction of DMs in the social network, the evaluation value to achieve the required consensus degree is adjusted according to the DeGroot model to obtain the overall consensus. Finally, taking the group preference as the reference, the ranking of alternatives is determined by using the Pythagorean fuzzy score function.

This paper proposes a consensus model of SNGDM based on improved PageRank algorithm to aggregate expert preference information. A numerical case of product evaluation is introduced, and the feasibility and effectiveness of the model are explained through sensitivity analysis and comparative analysis. The results show that this method can solve the problem of reaching consensus in SNGDM.

Different DMs may have different judgment criteria for the same decision-making problem, and the angle and depth of considering the problem will also be different. By increasing the process of mutual evaluation of DMs, the evaluation ability of each DM is judged only from the decision-making problem itself. In this way, the evaluation opinions recognized by most DMs will form the mainstream of opinions, and the influence of corresponding DMs will increase. Therefore, in order to improve the fairness and reliability of the consensus process, this study measures the real evaluation ability of DMs by increasing the “mutual judgment” process. On this basis, the defect of equal treatment of PageRank algorithm in calculating the weight of DMs is improved. This ensures the authenticity and objectivity of the weight of DMs. That is to improve the effectiveness of the whole evaluation mechanism. This method considers both the influence of DMs in the social network and their own evaluation level. The weight of DMs is calculated from two aspects: sociality and professionalism. It provides a new method and perspective for the calculation of DM’s weight in SNGDM.

The manufacturing industry and the producer service industry have a high degree of industrial correlation, and their integration will cause changes in the complex industrial network topology, which is an important reason for the synergistic effect. This paper describes the topology of industrial systems using complex network theory; further, it discusses how to identify the criticality and importance of industrial nodes, and whether node characteristics cause synergistic effects.

Based on the input-output data of China in 2007, 2012 and 2017, this paper constructs the industrial complex network of 30 Chinese provinces and cities, and measures the regional network characteristics of the manufacturing industry. The fixed-effect panel regression model is adopted to test the influence of agglomeration degree and centrality on synergies, and its adjustment mechanism is explored.

The degree of network agglomeration in the manufacturing industry exerts a negative impact on the synergistic effect, while the centrality of the network exerts a significant promoting effect on the synergistic effect. The results of adjustment mechanism test show that enhancing the autonomous controllable ability of the regional industrial chain in the manufacturing industry can effectively reduce the effect of network characteristics on the synergistic effect.

Based on input-output technology, this paper constructs a complex industrial network model, however, only basic flow data are used. Considerable in-depth and detailed research on the economic and technological connections within the industry should be conducted in the future. The selection of the evaluation index of the importance of industrial nodes also needs to be further considered. For historical reasons, it is also difficult to obtain and process data when carrying out quantitative analysis; therefore, it is necessary to make further attempts from the data source and the expression form of evaluation indicators.

In a practical sense this has certain reference value for the formulation of manufacturing industrial policies the optimization of regional industrial layout and the improvement of the industrial development level. It is necessary to formulate targeted and specialized industrial development strategies according to the characteristics of the manufacturing industry appropriately regulate the autonomous controllable ability of the industrial chain and avoid to limit the development of industries which is in turn limited by regional resources. Industry competition and market congestion need to be reduced industry exchanges outside the region encouraged the industrial layout optimized and the construction of a modern industrial system accelerated.

The above research results hold certain reference importance for policy formulation related to the manufacturing industry, regional industrial layout optimization and industrial development level improvement. Targeted specialized industrial development strategies need to be formulated according to the characteristics of the manufacturing industry; the autonomous controllability of the industrial chain needs to be appropriately regulated; limitation of regional resources needs to be avoided as this restricts industrial development; and industry competition and market congestion need to be reduced. Agglomeration of production factors and optimization of resource allocation is an important part of a beneficial regional economic development strategy, and it is also an inevitable choice for industrialization to develop to a certain stage under the condition of a market economy. In alignment with the research conclusions, effective suggestions can be put forward for the current major industrial policies. In the process of promoting the development of the manufacturing industry, it is necessary for regional governments to carry out unified planning and guidance on the spatial layout of each manufacturing subsector. Regional governments need to effectively allocate inter-industry resources, better share economies of scale, constantly enhance the competitive advantages and competitiveness of development zones and new districts and promote the coordinated agglomeration and development of related industries with input industries. Industrial exchanges outside the region should be encouraged, the industrial layout should be optimized and the construction of a modern industrial system should be accelerated.

Complex network theory is introduced to study the industrial synergy effect. A complex industrial network of China's 30 regions is built and key network nodes are measured. Based on the dimensionality of the “industrial node – industrial chain – industrial complex network”, the research path of industrial complex networks is improved.

This paper examines the relationship between supply chain network structures and firm financial performance and the moderating role of international relations. In this study, which is grounded in social capital theory and applies the perspective of systemic risk, the authors theorize the effects of supply chain network structures on firm performance.

The authors extracted data from two Chinese databases and constructed a supply chain network of the firms concerned based on nearly 4,300 supply chain relations between 2009 and 2018. The authors adopted the fixed effects model to investigate the relationship between supply chain network structures and firm financial performance.

The econometrics results indicate that network structures, including the degree, centrality, clustering coefficients and structural holes, are significantly related to firm financial performance. A significant and negative relationship exists between international relations and firm financial performance. The authors also find that international relations strongly weaken the relationship between supply chain network structures and firm financial performance.

This study, which collects secondary data from developing countries (e.g. China) and explores the impacts of supply chain network structures on firm stock performance, contributes to the existing literature and provides practical implications.

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.

This work aims to explore the effects of (equity and non-equity) strategic alliances between banks and FinTechs on FinTechs' online visibility.

For a sample of 124 Italian FinTechs, the authors measured online visibility through their website ranking (Google PageRank) and website traffic (Google Trends). Consistent to the historical depth of these measures, the authors separately investigated the effect of equity and non-equity (contractual) agreements on online visibility by means of ordinal logistic regressions and diff-in-diff analysis.

Strategic alliances with banks enhance FinTechs' online visibility. Although both equity and contractual agreements positively influence the popularity of FinTechs' website achieved through the activity of internal and external online content creators (websites ranking), only equity agreements are effective in attracting Internet users (website traffic).

When deciding to interact with banks, FinTechs' managers should consider that equity agreements may be a powerful strategic choice for enlarging the customer base and boosting visibility of FinTechs.

Fostering strategic alliances between banks and FinTechs contributes to FinTechs' growth, generating virtuous mechanisms of innovation, financial inclusion and better allocative efficiency of the financial system.

This work expands marketing knowledge and literature regarding online visibility determinants, by investigating the benefits of strategic alliances and cooperation in the market, while providing an empirical strategy replicable by future marketing studies.

This study aims to examine the literature from the Web of Science database published on board committees between 2002 and 2023 and outline the quantitative summary, journey of board committees’ research and suggest future research directions.

This study examines bibliometric-content analysis combined with a systematic literature review of articles on board committees to document the summary of the field. The authors used co-citation, co-occurrence and cluster analysis under bibliometric-content analysis to present the field summary.

Board committee composition, such as their gender, independence and expertise, as well as factors affecting corporate governance, such as reporting quality, earnings management and board monitoring, all have a significant impact on board committee literature. The field is getting growing attention from authors, journals and countries. Nevertheless, there is a need for further exploration in areas like expertise, member age and tenure, the economic crisis and the nomination and remuneration committee, which have not yet received sufficient attention.

This paper has both theoretical and practical contributions. From a theoretical perspective, this study substantiates the prevalence of agency theory within board committee literature, reinforcing the foundational role of agency theory in shaping discussions about board committees. On practical ground, the comprehensive overview of board committee literature offers scholars a road map for navigating this field and directing their future research journey. The identification of research gaps in certain areas serves as a catalyst for scholars to explore untapped dimensions, enabling them to strengthen the essence of the committees’ performance.

This paper aims to investigate whether the establishment of commodity futures can effectively hedge systemic risk in the spot network, given the context of financialization in the commodity futures market.

Utilizing industry association data from the Chinese commodity market, the authors identify systemically important commodities based on their importance in the production process using multiple graph analysis methods. Then the authors analyze the effect of listing futures on the systemic risk in the spot market with the staggered difference-in-differences (DID) method.

The findings suggest that futures contracts help reduce systemic risks in the underlying spot network. Systemic risk for a commodity will decrease by approximately 5.7% with the introduction of each corresponding futures contract, since the hedging function of futures reduces the timing behavior of firms in the spot market. Establishing futures contracts for upstream commodities lowers systemic risks for downstream commodities. Energy commodities, such as crude oil and coal, have higher systemic importance, with the energy sector dominating systemic importance, while some chemical commodities also have considerable systemic importance. Meanwhile, the shortest transmission path for risk propagation is composed of the energy industry, chemical industry, agriculture/metal industry and final products.

The paper provides the following policy insights: (1) The role of futures contracts is still positive, and future contracts should be established upstream and at more systemically important nodes in the spot production chain. (2) More attention should be paid to the chemical industry chain, as some chemical commodities are systemically important but do not have corresponding futures contracts. (3) The risk source of the commodity spot market network is the energy industry, and therefore, energy-related commodities should continue to be closely monitored.

Using bibliometric, this work aims to evaluate the current status of the body of research on the subject of supply chain resilience (SCR) in developing nations and to provide recommendations for potential lines of inquiry for additional research.

Three hundred and thirty-six articles published between 2011 and 2021 were retrieved in Scopus for this bibliometric analysis. This analysis focuses on SCR research conducted in developing countries, highlighting its key authors, countries, institutions, journals, articles and themes.

This bibliometric review seeks to enrich the discourse on SCR in developing nations through a comprehensive and detailed review of 336 articles covering 138 Journals, 73 countries, 877 authors, 743 organizations and 1,145 author keywords. The United Kingdom, India, and the United States provided a substantial share of the publications. Publication-wise, Hong Kong Polytechnic University and The University of Hong Kong play key roles. The author found that supply chain risk management, sustainability, agile management, artificial intelligence and blockchain are trending topics. Additionally, the author identified eight themes by page rank analysis.

This study's importance lies primarily in its examination of the current information about SCR in developing countries and significant cluster areas (themes). In the paths, it recommends for further study, which academics may take, and industry professionals should apply in their businesses to create a more resilient and sustainable supply chain.

Based on published studies, this study gives exploratory data on SCR in developing countries context. This is first of its kind bibliometric study that focuses on developing countries.

The adoption of Islamic banking (AIB) among customers has remained in the limelight due to its significance in the strategic marketing of Islamic banking (IB) services. Although researchers have devoted a significant effort to investigating the drivers of AIB, little is known about the exclusive barriers hampering AIB. Accordingly, this paper aims to examine the underlying barriers to the adoption of Islamic banking (BAIB) and categorize them into different research clusters using bibliometric analysis.

The data was collected from 132 articles published in Scopus database between 2007 and 2022 and analyzed using VOSviewer to explore BAIB.

The findings clustered the barriers to AIB into three groups, namely, efficiency of IB products and services (service quality, Shariah compliance level, availability of services), behavioral (knowledge and awareness, religiosity, trust and intention) and personal attributes (innovativeness, understanding of mobile/internet banking and technology acceptance) factors of Islamic bank customers.

The sample size of this study is relatively small, as the data was imported from Scopus database only to perform Bibliometric analysis. Future studies may use larger sample size by retrieving data from other databases such as Web of Science and PubMed to develop better research clusters of BAIB.

The dynamic business environment and unprecedented changes in consumer behavior require managers creating suitable conditions to foster adoption of their services and capture a better market share.

Following the findings of this research, future research avenues are identified for strategic embeddedness and global development of IB by overcoming BAIB.