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There are often relational interactions in teams that lead to and drive the spread of work engagement. Despite the potential social impacts on work engagement, such as coworker support and organizational citizenship behaviors within teams, they have rarely been studied from a social perspective using social network analysis (SNA). This review draws on the crossover model and conservation of resources theory to suggest that the effects of social diffusion and the exchange of resources can impact Well-Being, specifically work engagement, in teams and that SNA can help measure those social interactions. Linking several network concepts – closeness centrality, density, degree centrality, and tie strength – to work engagement propositions related to the spread of work engagement as well as the number and quality of network ties, this review elucidates the potential for integrating SNA methodology to the field of Well-Being for teams.

This chapter investigates the effects of economic development, FDI, trade barriers, product characteristics, and air transport network connectivity on both air trade and air cargo demand. The analysis applies gravity model and estimates the air trade and air cargo demand models using seemingly unrelated regressions based on data for the air cargo markets between the United States and its top 61 trading partner countries during the 2004–2019 period. By developing and incorporating “investment distance” as a determining factor in the estimation of air trade, our study fills the gap in literature and sheds light on the importance of air cargo transport in enabling and facilitating the rapid growth of global value chains in recent decades. The results suggest that higher level of FDI between the US and its trading partner countries helps stimulate air trade. Moreover, we also develop several network centrality metrics and examine their relationship with regional air connectivity, which in turn has a positive impact on air cargo traffic. Further analysis using Granger causality tests provides strong evidence supporting the importance of air cargo services as an engine for economic growth and international trade in a dynamic global economic landscape.

This chapter explores an analytical method to understand the decades-long literature on informal lending in the informal sector. Assessing the predominance and interrelationships of numerous issues in informal loans in the informal economy helps in identifying emerging research trends. The analysis employs a method of investigation by thematically analyzing research publications indexed by Scopus from the first publication to 2023 using bibliometrix and PRISMA model in R Studio. Research ideas may be visualized using thematic slices and other visual representations that show their evolution and interconnectedness. Key concepts like “rural credit” and “informal sector” become apparent, shedding light on the evolution of these concepts through time with the help of thematic analysis. Findings on trending themes and tree maps improve thematic comprehension. The study majority restricted to thematic analysis in depth confined to available information. The results may be used as a road map for further study and policy choices in the field of informal lending. Informal lending research promotes financial inclusion and sustainable informal sector economic growth. This bibliometric analysis illuminates informal lending research themes and their consequences for informal economy issues. The results enhance informal lending research and policy development.

This research paper aims to better understand the network structure of higher education in North America. It draws on a relationally networked dataset of 1,292 degree-granting colleges and universities in North America to develop a modularity class approach to categorizing colleges and universities based on their own self-defined peer networks and assesses the utility of the modularity class approach as well as several measures of network centrality for predicting offerings of new curricular fields. Results show that not all measures of network centrality equally predict organizational change outcomes, with hub/authority position being most important. Additionally, results show that an empirically derived modularity class approach to categorizing organizations has important strengths in relation to more typical approaches based on prestige or perceived organizational characteristics. The approaches detailed in this paper will be useful for future analysts seeking to explain the spread of innovations and behavior across the higher education institutional field, as well as those seeking to understand clustering and organizational divergence.

The argument that applications of social network research tools and theories to stakeholder research will advance our understanding of how organizations should and do interact with their stakeholders and how stakeholders influence organizations has been well known for over 15 years. However, the integration of social network analysis and stakeholder research has been limited to date. To motivate stakeholder network research, I illustrate the similarities and complementarities between these research streams, arguing that the social network perspective tackles weaknesses in stakeholder models supporting the creation of more fruitful models of organization–stakeholder environments. I illustrate how stakeholder power and legitimacy, and focal organization obligations can be better modeled theoretically and measured empirically using social network concepts and techniques.

Online social networks are increasingly important venues for businesses to promote their products and image. However, information propagation in online social networks is significantly more complicated compared to traditional transmission media such as newspaper, radio, and television. In this chapter, we will discuss research on modeling and forecasting diffusion of virally marketed content in social networks. Important aspects include the content and its presentation, the network topology, and transmission dynamics. Theoretical models, algorithms, and case studies of viral marketing will be explored.

The trade agreements among major trading countries can open new prospects of development and growth for global economy. The policy changes by a major trading country can alter the global trade and connection patterns. The trade agreement known as Trans-Pacific Partnership (TPP) was between 12 “Pacific-rim” countries signed earlier in 2016 indicates an upcoming and major policy change for global economy (presidential memorandum to withdraw the United States from TPP was signed in January 2017). The agreement would influence the issues related to “economic growth, employment, innovation, productivity, and competitiveness” of every partner and linked economy. This study illustrates how Asia Pacific’s major countries are interlinked with each other, the important sectors and the strength of connections. The level of interconnectedness might have been transformed within regional trade network because of varying global economic patterns and demand trends. The study focuses on the aspects related to agreement and reduction in tariffs that may change the global trading scenarios and appropriate position for region’s prominent and developing economies after implementation of the agreement.

Misinformation can influence decision-making by fueling individual's belief, prejudices, and stereotypes. In the context of international trade, misinformation refers to the spread of false or misleading information and facts mostly with the malicious intent of maligning reputation of products, services, trade policies of a country and thus negatively influencing liberal trade policies toward that country. Stereotypes and prejudices fueled by misinformation coupled with economic nationalism and populism cast a dark shadow over the liberal international order. Exaggerated claims about unfair trade practices laced with stereotypes, prejudices, and misinformation can fuel tensions and may eventually lead to trade dispute and retaliatory action such as the imposition of tariffs or breakdown of trade blocs. Fake News, as a term, came into prominence recently during the 2016 US elections. The spread of fake news during the election generated remarkable interest among researchers. While most research focused on the effect of misinformation, a few studies have shown the influence of misinformation in changing trade preferences. The intricate connection among trading partners can propagate misinformation. Misinformation can lead policymakers to undertake protectionist policies. However, policies driven by misinformation, taken by major economies, can have strong rippling effects on other trading partners because of their strong network connectedness. Therefore, it motivates us to understand and evaluate international trade in terms of network statistics. This chapter provides an in-depth analysis of the network effects of some major and emerging economic powers involved in bilateral or multilateral trade agreements.

Most of us have experienced the “small world” phenomenon; you meet a stranger while traveling or waiting in a queue, for example, and begin to discuss where you are from, what type of work you do, or why you are at this certain location. Surprisingly, you and the stranger discover you both know the same person, possibly from your hometown, academic department, or children's school. You both remark “what a small world” and then go on your way. Small worlds are just one example of social networks, or how individuals know one another. Social scientists have been interested in this phenomenon since the 1930s and have developed network analysis tools to gain an understanding of how social networks are formed and evolve. These methods have improved significantly over the past 15 years and may provide an informative lens through which to investigate international entrepreneurship (IE).