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The purpose of this paper is to conceptualize the notion of thin crossing points from a social network perspective and to outline the concrete networking strategies that enable salespeople to foster mutually valuable resource exchange (i.e. to thin crossing points) across a selling ecosystem.

The authors integrate extant theoretical perspectives to advance a conceptual framework of sales-related networking across three key actors in a selling ecosystem: intraorganizational selling actors and actors in customers and external partner organizations.

Thin crossing points are defined as figurative transaction points at the boundary between organizations or organizational subunits at which actors engage in mutually valuable resource exchange in the process of value cocreation. To thin crossing points with key ecosystem actors, salespeople must adapt networking strategies considering the time and trust constraints inherent in a network relationship. Such constraints inform the most advantageous network centralities (degree, eigenvector and betweenness) and actions to impact key network properties (tie strength, contact diversity) that enable salespeople to efficiently develop social capital and thus to optimally thin crossing points across a selling ecosystem.

To the best of the authors’ knowledge, this study is the first social network-based exploration of salespeople’s role in thinning crossing points with key ecosystem actors. It advances a novel conceptual framework of sales-related networking strategies that foster social capital development and optimally thin crossing points across a selling ecosystem.

Research suggests that engaging in networking behaviors can affect individual work outcomes. However, relatively less is known about how internal versus external networking behaviors influence work outcomes, and whether gender moderates these relationships. Drawing on social capital theory and social role theory, the authors propose a positive relationship between employees' internal and external networking behaviors and their work outcomes (job commitment and career success), and the moderating effect of gender. The authors also explore employee preference in networking.

Based on a sequential mixed-method research design with a four-month time lag, Study 1 data on networking behaviors and employee outcomes were collected via a survey of middle managers and their supervisors from 10 private sector organizations in Sri Lanka. Study 2 data were collected via interviews from a sample of those middle managers and their supervisors.

Study 1 findings indicate a positive relationship between internal networking behaviors and job commitment, and external networking behaviors and career success. The authors also found that internal networking behaviors enhance job commitment. Study 2 findings indicate men and women network differently and benefit differently from that networking but achieve equitable workplace benefits.

This study provides pioneering evidence that internal networking behaviors enhance job commitment among women. It appears that past research did not test the moderating effect of gender for internal versus external networking behaviors separately. Moreover, this study refines the evidence that internal and external networking behaviors differentially impact employee outcomes and explains the processes through a qualitative inquiry.

The aim of this paper is to empirically investigate whether social contacts can mediate the way in which current unemployment impacts future unemployment.

We use 2006–2017 data from the Household Income and Labour Dynamics in Australia (HILDA) survey and a dynamic random-effects model to describe the evolution of individual unemployment status over time.

Once controlled for the local context where individuals live and create friendships, we find that above-average social contacts reduce unemployment persistence. However, social contacts seem to be slightly less effective in deprived neighborhoods. These findings are consistent with the idea that individuals obtain information about job opportunities through a network of social contacts, and unemployment may lead to a decay of social capital, making it more difficult to find employment in future periods. Our results also show that neighborhood deprivation increases individual unemployment risk, while above-average neighborhood cohesion reduces the probability of unemployment in deprived neighborhoods.

Although many studies have been published on unemployment persistence, to the best of the author's knowledge, this is the first study quantifying the impact of social contacts on unemployment persistence. The study also offers fresh empirical evidence on the impact of neighborhood characteristics on unemployment risk.

The outbreak of COVID-19 has caused a slowdown of economic activity across the globe, which has resulted in high levels of disruption to labour markets. This study seeks to examine how the outbreak of COVID-19 has impacted the search strategies of students seeking for an internship, and whether these have changed since the start of the pandemic. The study utilises the strength of weak ties hypothesis, social capital theory and status attainment theory to explore the changes in securing a position since the outbreak of COVID-19.

This study draws on data from two cohorts of MBA students seeking to secure internships: one before the outbreak and one during. A multinomial regression is employed to examine how students have used network ties to secure internships and how this has changed since the outbreak of COVID-19.

The multinomial regression results indicate that there was little difference in the strategies employed by students before the crisis compared to those that secured them during, potentially indicating that students are unwilling to deviate from typical job search strategies, especially in times of uncertainty.

This study provides insights into how network ties are used by job seekers during a period of economic and environmental uncertainty.

Transnational migration is a key challenge in migrant-sending and host-receiving countries. However, relatively little is known about how migrants use network capital to foster small and medium-sized enterprises (SMEs) in the ASEAN Economic Community (AEC). Therefore, the purpose of this study is to explore how network capital fosters Laotian migrant workers in Thai family SMEs.

This research was conducted using qualitative network analysis (QNA). Referral snowball sampling was used to draw 20 participants from December 2021 to March 2022. Data analysis was performed using Gephi, a software package developed for QNA (coding, network features, measure nodes and network metrics).

The main findings are the following four emerging themes: chain networks, social networks, human networks and financial networks are associated with network capital for fostering Laotian migrant workers in Thai family SMEs.

To the best of the authors’ knowledge, this study is the first QNA to explore how Laotian migrant workers use network capital in Thai family SMEs.

This chapter makes a case for extending institutional preservation strategies to the entire landscape of knowledge capital. First, the authors define the three primary types of capital – physical, financial, and knowledge. Knowledge capital is further broken down into three categories – human, structural, and relational. The individual types of knowledge capital are defined, along with their variant economic properties and behaviors. The challenges these variations present for preservation are discussed. The authors also highlight these assets’ significant opportunities for curating new knowledge. Each type of knowledge capital is described, along with the preservation challenges and the curation opportunities.

The purpose of this research is to investigate the R&D investment (RDI) of manufacturing firms from the perspective of supply chain network, especially the effect of firms' supply chain network structures (network power and network cohesion) on its RDI, and further to explore the contingency conditions of this effect within the context of Chinese manufacturing supply chains.

The authors collect a large sample of Chinese manufacturing firms over the period 2014–2019 and construct a large-scale supply chain network, and finally obtain 2,390 firms from 20,483 observations. Ordinary least squares regression was adopted to analyse how supply chain network structures affect RDI in manufacturing firms.

It is surprising that firm's supply chain network structures have a negative effect on RDI. In addition, knowledge and technology intensity (KTI) positively moderate the relationship between network cohesion and RDI.

This study contributes to the innovation stream from the perspectives of supply chain network, and provides the empirical findings that the negative role of a firm's supply chain network structure on its RDI for the first time. The rationale for these negative effects is straightforward according to the social capital theory that manufacturing firms with a high level of social capital that are possibly to accept established patterns of thinking and behaviour, causing them to decrease the enthusiasm of RDI.

This paper addresses the relevance of job search methods and strategies in determining vertical mismatch and the risk of underusing skills or knowledge in first jobs amongst graduates from bachelor's and master's programmes in Spain. Support from universities (via internships and career services) is compared to support from public institutions and informal strategies.

The authors use the 2019 University Graduate Job Placement Survey. The dependent variables are estimated with a bivariate probit model with sample selection on a subsample of graduates who were not working at graduation.

Internships and university career employment offices significantly improve the quality of first job matches. Job banks and public examinations also contribute to finding well-matched first positions, while for public employment services, results are mixed. When the job search is not supported by institutions, graduates generally do worse finding their first jobs, particularly when temporary employment agencies are involved. There are also large differences in mismatch risks across fields of study.

If more graduates found their first jobs through internships and university job placement services, educational mismatch rates would decrease substantially. Further collaboration between universities and employers for the provision of high-quality internships may foster their conversion into regular, well-matched jobs. Industrial policies addressed to knowledge-based economic activities would enhance the creation of highly skilled positions. Further orientation towards STEM degrees is required to improve imbalances between supply and demand for graduate labour in Spain.

Evidence about education mismatch among master's degree graduates is very scarce. This paper compares them to bachelor's degree graduates. It addresses two complementary types of education mismatch and takes into account potential self-selection into post-graduation job search.

Crowdfunding (CF) is a digital-financial innovation that, bypassing credit crisis, bank system rigidities and constraints of the capital market, is allowing new ventures and established companies to get the needed funds to support innovations. After one decade of research, mainly focused on relations between variables and outcomes of the CF campaign, the literature shows methodological lacks about the study of its overall behavior. These reflect into a weak theoretical understanding and inconsistent managerial guidance, leading to a 27% success ratio of campaigns. To bridge this gap, this paper embraces a “complex system” perspective of the CF campaign, able to explore the system's behavior of a campaign over time, in light of its causal loop structure.

By adopting and following the document model building (DMB) methodology, a set of 26 variables and mutual causal relations modeled the system “Crowdfunding campaign” and a data set based on them and crafted to model the “Crowdfunding campaign” with a causal loop diagram. Finally, system archetypes have been used to link the causal loop structure with qualitative trends of CF's behavior (i.e. the raised capital over time).

The research brought to 26 variables making the system a “Crowdfunding campaign.” The variables influence each other, thus showing a set of feedback loops, whose structure determines the behavior of the CF campaign. The causal loop structure is traced back to three system archetypes, presiding the behavior in three stages of the campaign.

The value of this paper is both methodological and theoretical. First, the DMB methodology has been expanded and reinforced concerning previous applications; second, we carried out a causation analysis, unlike the common correlation analysis; further, we created a theoretical model of a “Crowdfunding Campaign” unlike the common empirical models built on CF platform's data.

This paper aims to analyze the influence of technology-based business incubators (TBIs) on the resources of technology startups in Brazil. The authors identify which resources are offered and explore the importance of resources for TBIs and startups. The theoretical background is based on the resource-based view, the resource dependency theory and total factor productivity.

The study is characterized by a descriptive approach. The method includes a multiple case study and a survey. For data collection, we conducted interviews with three managers from TBIs and distributed questionnaires to 30 startup founders. The content analysis supports the identification of the resources, while the quantitative approach explores the relationship between total factor productivity and resources.

Resources are the linkage between startups and TBIs, promoting the development and continuity of these organizations. Among the resources offered by TBIs, the most representative is physical resources, due to the early stage of startups. TBIs do not offer financial resources directly but facilitate access through networks with other actors.

The research implications depict the importance of resources as a link between TBIs and startups. The results highlight how TBIs play an important role in promoting entrepreneurship and innovation in the context of emerging economies such as Brazil.

This article performs a multi-theoretical analysis, addressing the perspectives concerning resources. No previous study has used this combination of perspectives to analyze the relationship between TBIs and startups in Brazil, filling the gap about this subject in emerging economies.