arXiv subjects

Travis A. Whetsell

Publications and source records attributed to Travis A. Whetsell.

13 recordsLinked to original sources

arXiv2026

Co-evolution of the global research collaboration network and the performance of nations in science and technology

Researchers have long suspected that international research collaboration (IRC) and scientific and technological (S&T) performance are subject to reciprocal causality, yet the endogenous co-evolution of these twin phenomena has yet to be tested by large-scale empirical analysis. This study tests these effects simultaneously using a longitudinal co-evolution model on three decades of global network and national performance data. Stochastic actor-oriented models (SAOM) are used to analyze data on 172 countries from 1993 to 2022. Yearly IRC networks are constructed from Web of Science's XML database, and performance data are gathered from Elsevier's fractional field-weighted citation impact (FWCI). The models also account for geographic, economic, demographic, and political factors, as well as endogenous network processes. The results provide support for co-evolution. Distance and shared language moderate this relationship in contrasting ways. The selection effect of performance on tie formation is amplified across distance and dampened by a shared language, whereas the influence effect of performance on centrality is attenuated by remoteness and strengthened by linguistic reach. This pattern suggests that information asymmetry shapes partner selection, while communication and coordination shape the returns to collaboration, pointing to a signaling role for citation-based performance metrics in collaborator selection.

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arXiv2024

Network Interventions: Applying Network Science for Pragmatic Action in Public Administration and Policy

Public management and policy scholars have engaged in extensive development of theory and empirical study of networks and collaborative systems of governance. This scholarship has focused on understanding the mechanisms of network formation and the implications of network properties on individual and collective outcomes. Despite rich descriptive work and inferential analyses, little work has attempted to intervene in these systems. In this article, we develop the foundation for a new body of research in our field focused on network interventions. Network interventions are defined as the purposeful use of network data to identify strategies for accelerating behavior change, improving performance, and producing desirable outcomes (Valente, 2012). We extend network intervention strategies from the field of public health to public sector inter-organizational and governance networks. Public sector actors have an interest in network interventions based on the fundamental pursuit of efficiency, effectiveness, and equity. Network interventions can increase the uptake of an organizational change among employees, improve the performance of a governance system, or promote the spread of a successful policy across jurisdictions. We provide scholars and practitioners with a useful way to conceptualize where, why, and how network interventions might be deployed in the pursuit of public value.

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arXiv2024

Academic Freedom and International Research Collaboration: A Longitudinal Analysis of Global Network Evolution

The topic of academic freedom has come to the fore as nations around the world experience a wave of democratic backsliding. Institutions of higher education are often targets of autocrats who seek to suppress intellectual sources of social and political resistance. At the same time, international collaboration in scientific research continues unabated, and the network of global science grows larger and denser every year. This research analyzes the effects of academic freedom on international research collaboration (IRC) in a sample of 166 countries. Global international collaboration data are drawn from articles in Web of Science across a 30-year time frame (1993-2022) and are used to construct three separate IRC networks in science and technology (S&T), social sciences (SocSci), and arts and humanities (A&H). The Academic Freedom Index, covering the same time frame, is drawn from the Varieties of Democracy Project, as are numerous country-level control variables. Stochastic actor-oriented models (SAOM) are used to analyze the networks. The results show positive significant estimates for both direct effects and homophily effects of academic freedom on network evolution. These effects appear to increase in strength moving from the S&T network, to the SocSci network, and appear strongest in the A\&H network. However, tests of temporal heterogeneity show a significant decline in the relevance of academic freedom in the most recent period.

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arXiv2024

Network Inference in Public Administration: Questions, Challenges, and Models of Causality

Descriptive and inferential social network analysis has become common in public administration studies of network governance and management. A large literature has developed in two broad categories: antecedents of network structure, and network effects and outcomes. A new topic is emerging on network interventions that applies knowledge of network formation and effects to actively intervene in the social context of interaction. Yet, the question remains how might scholars deploy and determine the impact of network interventions. Inferential network analysis has primarily focused on statistical simulations of network distributions to produce probability estimates on parameters of interest in observed networks, e.g. ERGMs. There is less attention to design elements for causal inference in the network context, such as experimental interventions, randomization, control and comparison networks, and spillovers. We advance a number of important questions for network research, examine important inferential challenges and other issues related to inference in networks, and focus on a set of possible network inference models. We categorize models of network inference into (i) observational studies of networks, using descriptive and stochastic methods that lack intervention, randomization, or comparison networks; (ii) simulation studies that leverage computational resources for generating inference; (iii) natural network experiments, with unintentional network-based interventions; (iv) network field experiments, with designed interventions accompanied by comparison networks; and (v) laboratory experiments that design and implement randomization to treatment and control networks. The article offers a guide to network researchers interested in questions, challenges, and models of inference for network analysis in public administration.

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arXiv2023

Developing an Index of National Research Capacity

Public managers lack feedback on the effectiveness of public investments, policies, and programs instituted to build and use research capacity. Numerous reports rank countries on global performance on innovation and competitiveness, but the highly globalized data does not distinguish country contributions from global ones. We suggest improving upon global reports by removing globalized measures and combining a reliable set of national indicators into an index. We factor analyze 14 variables for 172 countries from 2013 to 2021. Two factors emerge, one for raw or core research capacity and the other indicating the wider context of governance. Analysis shows convergent validity within the two factors and divergent validity between them. Nations rank differently between capacity, governance context, and the product of the two. Ranks also vary as a function of the chosen aggregation method. Finally, as a test of the predictive validity of the capacity index, a regression analysis was implemented predicting national citation strength. Policymakers and analysts may find stronger feedback from this approach to quantifying national research strength.

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arXiv2023

Democratic Governance and International Research Collaboration: A Longitudinal Analysis of the Global Science Network

The democracy-science relationship has traditionally been examined through philosophical conjecture and single country case studies. There remains limited global scale empirical research on the topic. This study explores country level factors related to the dynamics of the global scientific research collaboration network, focusing on structural associations between democratic governance and the strength of international research collaboration ties. This study combines longitudinal data on 170 countries between 2008 and 2017 from the Varieties of Democracy Institute, World Bank Indicators, Scopus, and Web of Science bibliometric data. Methods of analysis include descriptive network analysis, temporal exponential random graph models (TERGM), and valued exponential random graph models (VERGM). The results suggest positive significant effects of democratic governance on the formation and strength of international research collaboration ties, as well as homophily between countries with similar levels of democratic governance. The results also show the importance of exogenous factors, such as GDP, population size, and geographical distance, as well as endogenous network factors including preferential attachment and transitivity.

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arXiv2022

Can We Talk? An Exploratory Study of Gender and Network Ties in a Local Government Setting

We explore the influence of gender and formal organizational status on the formation of discussion ties. Network data, gathered through surveying employees from a municipal organization in the United States, garnered a 92% response rate (n=143). Results of exponential random graph modeling indicate women supervisors are more likely to send discussion ties, while women in general are more likely to receive discussion ties. These exploratory results suggest women may be perceived as more approachable for work discussions, but not as supervisors. Finally, the results identified a consistent homophily effect of gender in the discussion network.

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arXiv2021

Democracy, Complexity, and Science: Exploring Structural Sources of National Scientific Performance

Scholars have long hypothesized that democratic forms of government are more compatible with scientific advancement. However, empirical analysis testing the democracy-science compatibility hypothesis remains underdeveloped. This article explores the effect of democratic governance on scientific performance using panel data on 124 countries between 2007 and 2017. We find evidence supporting the democracy-science hypothesis. Further, using both internal and external measures of complexity, we estimate the effects of complexity as a moderating factor between the democracy-science connection. The results show differential main effects of economic complexity, globalization, and international collaboration on scientific performance, as well as significant interaction effects that moderate the effect of democracy on scientific performance. The findings show the significance of democratic governance and complex systems in national scientific performance.

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arXiv2021

Formal Hierarchies and Informal Networks: How Organizational Structure Shapes Information Search in Local Government

Attention to informal communication networks within public organizations has grown in recent decades. While research has documented the role of individual cognition and social structure in understanding information search in organizations, this article emphasizes the importance of formal hierarchy. We argue that the structural attributes of bureaucracies are too important to be neglected when modeling knowledge flows in public organizations. Empirically, we examine interpersonal information seeking patterns among 143 employees in a small city government, using exponential random graph modeling (ERGM). The results suggest that formal structure strongly shapes information search patterns while accounting for social network variables and individual level perceptions. We find that formal status, permission pathways, and departmental membership all affect the information search of employees. Understanding the effects of organizational structure on information search networks will offer opportunities to improve information flows in public organizations via design choices.

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arXiv2021

Centrally Administered State-Owned Enterprises' Engagement in China's Public-Private Partnerships: A Social Network Analysis

A salient characteristic of China's public-private partnerships (PPPs) is the deep involvement of state-owned enterprises (SOEs), particularly those administered by the central/national government (CSOEs). This paper integrates the approaches of resource-based view and resource-dependency theory to explain CSOEs' involvement in PPP networks. Built upon a network perspective, this paper differs from earlier studies in that it investigates the entire PPP governance network as a whole and all PPP participants' embedded network positions, rather than individual, isolated PPP transactions. Using a novel data source on PPP projects in the period of 2012-2017, social network analysis is conducted to test hypothesized network dominance of CSOEs' in forming PPPs, in light of CSOEs' superior possession of and access to strategic assets. Research findings suggest that CSOEs have a dominant influence and control power in PPP networks across sectors, over time, and throughout geographic space. It is also suggested that policy makers should reduce resource gaps between SOEs and private businesses, and only in so doing, presence and involvement of non-SOEs in China's PPPs can be enhanced.

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arXiv2020

Government as Network Catalyst: Accelerating Self-Organization in a Strategic Industry

Governments have long standing interests in preventing market failures and enhancing innovation in strategic industries. Public policy regarding domestic technology is critical to both national security and economic prosperity. Governments often seek to enhance their global competitiveness by promoting private sector cooperative activity at the inter-organizational level. Research on network governance has illuminated the structure of boundary-spanning collaboration mainly for programs with immediate public or non-profit objectives. Far less research has examined how governments might accelerate private sector cooperation to prevent market failures or to enhance innovation. The theoretical contribution of this research is to suggest that government programs might catalyze cooperative activity by accelerating the preferential attachment mechanism inherent in social networks. We analyze the long-term effects of a government program on the strategic alliance network of 451 organizations in the high-tech semiconductor industry between 1987 and 1999, using stochastic network analysis methods for longitudinal social networks.

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arXiv2019

Between Promise and Performance: Science and Technology Policy Implementation through Network Governance

This research analyzes the effects of U.S. science and technology policy on the technological performance of organizations in a global strategic alliance network. During the mid-1980s the U.S. semiconductor industry appeared to be collapsing. Industry leaders and policymakers moved to support and protect U.S. firms by creating a program called Sematech. While many scholars regard Sematech as a success, how the program succeeded remains unclear. This study re-contextualizes Sematech as a network administrative organization which lowered cooperation costs and enhanced resource combination for innovation at the cutting edge. This study combines network analysis and longitudinal regression techniques to test the effects of public policy on organizational network position and technological performance in an unbalanced panel of semiconductor firms between 1986 and 2001. This research suggests governments might achieve policy through inter-organizational innovations aimed at the development and administration of robust governance networks.

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arXiv2018

International Research Collaboration: Novelty, Conventionality, and Atypicality in Knowledge Recombination

Research articles produced through international collaboration are more highly cited than other work, but are they also more novel? Using measures developed by Uzzi et al. (2013), and replicated by Boyack and Klavans (2014), this article tests for novelty and conventionality in international research collaboration. Scholars have found that coauthored articles are more novel and have suggested that diverse groups have a greater chance of producing creative work. As such, we expected to find that international collaboration tends to produce more novel research. Using data from Web of Science and Scopus in 2005, we failed to show that international collaboration tends to produce more novel articles. In fact, international collaboration appears to produce less novel and more conventional knowledge combinations. Transaction costs and communication barriers to international collaboration may suppress novelty. Higher citations to international work may be explained by an audience effect, where more authors from more countries results in greater access to a larger citing community. The findings are consistent with explanations of growth in international collaboration that posit a social dynamic of preferential attachment based upon reputation.

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