Multiple Regression Quadratic Assignment Procedure Research Articles

Exploring the destination network in the context of tourism mobility: a multi-scale analytical framework

ABSTRACT Tourist mobility has attracted considerable attention from tourism academics and industry practitioners. This study explores the destination network, which is constructed based on tourists’ digital footprint data collected from online travel diaries, by proposing a multi-scale analytical framework. In particular, to analyze the tourism destination network comprehensively, the proposed framework integrates traditional quantitative analysis (gravity center model, statistics of flow directions) and three scales of network analysis (macroscopic, mesoscopic and microscopic network metrics), to reveal the structural patterns of the underlying pattern characteristics; furthermore, by using the multiple regression quadratic assignment procedure (MRQAP), the framework also explores the formation mechanism of the destination network by measuring the correlation and causality between the destination network and the corresponding transportation network, combining other potential driving factors. Based on illustrative case study data, which contains 18, 939 travel diaries and 51, 603, 044 transportation records from Chengdu-Chongqing economic circle in China, the empirical results show that the destination network is dynamically changed during four-year period, and the transportation network has great potential in explaining the formation of destination network. The dynamic characteristics of destination network and the exploration of formation mechanism offer the opportunities for improving destination planning and management.

Parsing the Interactive Construction of Crisis Memory on Social Media: From a Memory-Agenda Perspective

ABSTRACT This study applied agenda-setting and agenda-building theories to explore the interactive memory agendas facilitated by social media. Focusing on the crisis memory of SARS constructed on Chinese social media (Weibo) during COVID-19, two competing approaches (top-down versus bottom-up) to crisis memory construction were empirically tested. A content analysis was first conducted to identify various crisis memory narratives, and then, rank-order analysis, cross-lagged correlation analysis, and multiple regression quadratic assignment procedure were performed to evaluate the reciprocal influences of crisis memory agendas of the second level (narrative salience) and the third level (narrative network) among different users. Findings show reciprocal influences among certain users’ memory-agendas in constructing crisis memory: media users showed influences on publics in terms of crisis memory agendas of both levels, while this crisis memory construction online also follows a bottom-up direction.

Interplay of agenda setters in the digital age: The associative issue network between news organizations and political YouTube channels

Two emerging questions in the current digital media environment are how socio-political issues are systematically circulated across various media platforms, including mainstream news organizations and social media platforms, and which media-driven issue networks influence the perceived issue networks of the public. This study addresses these questions by conducting computer-assisted content analysis and an online panel survey in South Korea in 2023. The results of the Quadratic Assignment Procedure (QAP) reveal that political issue networks reported by mainstream news organizations are positively associated with those circulated in YouTube channels. The results of Multiple Regression QAP (MRQAP) indicate that individuals are less likely to perceive issue networks that are emphasized by conservative YouTube channels than those of news media and liberal political YouTube channels.

Tourism policy networks in four Caribbean countries

This paper examines formal power and its influence on the policy roles of tourism actors in four Caribbean countries. The power of policy actors was calculated with a beta centrality measure, and hypotheses of power, policy roles, and policy actor types were tested using the Quadratic Assignment Procedure and Multiple Regression Quadratic Assignment Procedure features of Social Network Analysis software. Power differentials of the tourism policy actors were statistically significant in the Barbados policy network, while policy roles were statistically significant in the Jamaica policy network. Power struggles are a concern as these affect the rate and pace of tourism development and change tourism development outcomes.

Interorganizational collaboration in a trauma-informed community: A network analysis of cohesion and change.

Strengthening interorganizational collaboration is critical to mitigate the impact of adverse childhood experiences (ACEs) and improve community health. We examined change in interorganizational collaboration around ACEs within Peace4Tarpon's network and investigated factors influencing collaboration. We conducted a community-wide social network analysis among 32 trauma-informed organizations in 2016 and 2018, using network analysis methods to examine interorganizational cohesion (density, transitivity, triad census) over time, and multiple regression quadratic assignment procedure to investigate factors influencing collaboration. Network cohesion measures indicated small increases in collaboration level and greater network cohesion over time. Conducting ACEs screenings was a significant factor (b = 0.237; p < 0.01) predicting likelihood of interorganizational collaboration in 2016. No assessed ACEs practices predicted collaboration in 2018, suggesting variables assessed predicted a small proportion of variance in collaboration change. Results provide a foundation for understanding how ACEs/trauma-informed practices influence collaboration and highlight implications of interorganizational collaboration. Peace4Tarpon's 2-year progress provides insights for other trauma-informed communities.

A network analysis of international migration: Longitudinal trends and antecedent factors predicting migration

AbstractBuilding on previous research, this study investigates the international migration network and its changes from 1990 to 2017. The findings suggest that certain core countries play pivotal roles in shaping global migration by providing economic opportunities or political refuge. Community detection identified nine groups of nations in 2017, indicating regionalization. The study also examined the networks of antecedent factors that reflect both structural factors, such as geography, language, colonial history, political stability and economic differences, as well as transnational interactions, including student flow, trade, Internet flow and remittance, in relation to the international migration network. Applying multiple regression quadratic assignment procedure, it was found that these networks constituted approximately 11% of the migration network's distribution when chain migration was excluded, and 16.5% when it was included.

Competition and Local Government's Choice Between Informal and Formal Collaborative Mechanisms: Measuring Dyadic Intercity Competition Through the Lens of Business Trade-Offs

Informal and formal collaborative mechanisms are distinctive self-governing strategies that local governments use to mitigate intergovernmental collaboration risks. Studies on local governance have long argued that both mechanisms tend to co-occur and appear mutually complementary. However, extant research drawing on the transaction cost perspective provides a more nuanced and different explanation that as intergovernmental competition increases, local governments lean toward the choice of a formal mechanism over an informal mechanism to effectively address higher collaboration risks. Through a network lens, this study empirically tests the latter view. Using the Orlando metropolitan area as a testbed, Multiple Regression Quadratic Assignment Procedure tests reveal that the use of both collaborative mechanisms is positively associated with the level of intergovernmental competition. However, different from the initial expectation, local governments are more likely to engage in the informal mechanism rather than the formal mechanism as the competition level increases. In doing so, this study developed a new measurement strategy for intergovernmental competition to test the dyadic network-related research hypotheses. The measurement strategy and the research findings should inform future research on intergovernmental relations and local government network management.

A Study of Academic Library through the Prism of Knowledge Use and Problem Solving Networks

Abstract The article describes a social network approach to understanding the relationships between academic library employees: knowledge use network and problem solving network with the division into strong and weak ties. The author collected the data based on a semi-structured interview and a questionnaire on a selected population of library staff in a major academic library in Poland. Then, collected data was analyzed through the non-parametric network statistics tests (quadratic assignment procedure [QAP] and multiple regression quadratic assignment procedure [MRQAP]) to test dependencies occurring in social networks of librarians. The results show a relationship between knowledge use and problem solving based on strong and weak ties between librarians, with the beta for weak ties higher than for strong ties. The network methodology is becoming a critical research approach used to understand the informal structures and complexity of the academic library. Thus, it is a valuable tool in the hands of library directors.

Impacts of China’s exports decline in rare earth primary materials from a trade network-based perspective

Rare earth elements (REEs) are indispensable for the manufacture of high-tech products. Exports decline in China’s REEs primary materials (REEs-PMs) have attracted wide concern owing to China’s key role in the global REEs supply chains. The prevalence of trade frictions between countries motivates us to evaluate the potential impacts of China’s REEs-PMs exports decline. In this context, this study reviews dynamic patterns in the global REEs-PMs trade network from 1990 to 2019. Unlike previous studies, we propose a shock propagation model to evaluate the potential influence of China’s exports decline on other countries while accounting for each country’s shock adaptive capability. Specifically, countries may adjust their trade as a nonlinear function of the original trade level and key drivers of the REEs-PMs trade. Countries can partially absorb shocks by adjusting their domestic production, while the remainder is spread to their trade partners. The corresponding key drivers of the global REEs-PMs trade are revealed through a multiple regression quadratic assignment procedure (MR-QAP). The results indicate that economic scale, contiguity, and geodesic, economic, and institutional distance are the main drivers of REEs-PMs trade between countries. The most directly and indirectly affected countries are located mainly in Asia and Europe. It is worth noting that the long-term impacts of decreasing China’s REEs-PMs exports are quite limited in terms of dealing with trade frictions. Finally, several policy implications are provided for different countries with a view to maintaining the stability of the global REEs-PMs trade.

On the Effect of Reciprocal Dyadic Relations on the Share of Lexical Practices

Abstract Variationist studies have shown the implication of tie properties in the emergence and preservation of linguistic norms. This contribution deepens the understanding of this mechanism at the dyadic level. It explores relational subjectivity and relativity among individuals of a community and their implications in the distribution of lexical variants. The aim is to understand how the reciprocity of a relation influences the share of lexical practices. To do so, we analyze the network of discussions of bachelor's degree students of the University of Geneva and their lexical practices. Using the modern methods used in social network analysis to study relational properties and by running multiple regression quadratic assignment procedure (MRQAP), reciprocal interactions are found to lead to a higher lexical share and similarity.

High association strengths are linked to phenotypic similarity, including plumage color and patterns, of participants in mixed-species bird flocks of southwestern China.

Participants in mixed-species bird flocks (MSFs) have been shown to associate with species that are similar in body size, diet, and evolutionary history, suggesting that facilitation structures these assemblages. In addition, several studies have suggested that species in MSFs resemble each other in their plumage, but this question has not been systematically investigated for any MSF system. During the nonbreeding season of 2020 and 2021, we sampled 585 MSFs on 14 transects in 2 habitats of Tongbiguang Nature Reserve in western Yunnan Province, China. We performed social network analysis and the Multiple Regression Quadratic Assignment Procedure to evaluate the effect of 4 species traits (body size, overall plumage color, distinctive plumage patterns, and diet) and evolutionary history on species association strength at the whole-MSF and within-MSF levels. All 41 significant relationships showed that species with stronger associations were more similar in their various traits. Body size had the strongest effect on association strength, followed by phylogeny, plumage patterns, and plumage color; diet had the weakest effect. Our results are consistent with the hypotheses that the benefits of associating with phenotypically similar species outweigh the potential costs of interspecific competition, and that trait matching can occur in plumage characteristics, albeit more weakly than in other traits. Several explanations exist as to why similarities in plumage may occur in MSFs, including that they could reduce predators' ability to target phenotypically "odd" individuals. Whether trait matching in plumage occurs through assortative processes in ecological time or is influenced by co-evolution requires further study.

A Network Analysis of Judicial Cross-Citations in Europe

Recent years have seen a growing literature on citations between courts from different countries. What explains why such cross-citations occur between some courts but not others? This article addresses this question with original data on 2,967 citations between the private law supreme courts of the twenty-eight member states of the European Union. These cross-citations form a valued network of twenty-eight nodes, which can be analyzed with tools of network analysis. The article uses the method of a multiple regression quadratic assignment procedure in order to address the dependency of observations in a network. The explanatory variables distinguish between variables that proxy for legal similarities between countries and other factors, and, thus, this article contributes to the wider debate about the predominance of either legal or nonlegal factors in judicial decision-making. The main finding is that nonlegal factors play a decisive role, notably a common native language and overlapping language skills, while legal families are not found to be a significant determinant.

Evolution of innovation networks in industrial clusters and multidimensional proximity: A case of Chinese cultural clusters

The innovation and optimization of cultural industry clusters is important to the promotion of economic structural transformation and high-quality development. Taking 31 provinces (municipalities directly under the Central Government and autonomous regions in China) as the research object, the cross-sectional data included the number of joint patent applications for culture and related industries among provinces (regions) in 2014, 2016, 2018 and 2020. Then, the cluster innovation network was constructed using social network analysis (SNA) based on scientific identification of cultural industry clusters. This new cluster innovation network structure and its spatial evolution characteristics are accessible with the help of UCINet and ArcGIS tools. Finally, the multiple regression-quadratic assignment procedure (MR-QAP) method is used to determine the influence of geographical proximity, technological proximity, and social proximity on the evolution pattern of the cultural industry cluster innovation network. The results of the study are important for improving the efficiency of national cultural industry innovation and promoting regional synergistic development.

Performance Information Use in a Purpose-Oriented Network: A Relational Perspective

Abstract Performance information use is an essential component of performance management, which is an important tool to manage purpose-oriented networks (PONs). Conceptualizing performance information use in PONs as network members’ presentation, discussion, and interpretation of performance information during their interactions and communication, this study explores its drivers. Extant studies on performance information use in PONs point out an association between its use and the relationships among network members, but they lack specificity regarding the association. This study focuses on and theorizes that association, relying on network theory (especially the embeddedness approach) and resource dependence theory. Network analysis techniques (Multiple Regression Quadratic Assignment Procedure and Exponential Random Graph Modeling) are applied to investigate the theory empirically, using a pair (dyad) of network members as the unit of analysis. The data were collected from 21 members in a health and human services network serving children and youth with serious emotional disturbance in a US county. Two types of performance information were used in the PON: internally and externally produced information. Despite differences in the breadth and decision-making relevance of using information from these two sources, network analyses identify three relational characteristics consistently associated with the dyads’ use of internal and external performance information: (1) frequency of communication; (2) centrality of position; and (3) extent of mutual dependency. These findings suggest that network members are likely to use performance information in relationships where the benefits of developing a shared understanding of network performance outweigh the costs of using it.

Integration of a social cluster of Atlantic spotted dolphins (Stenella frontalis) after a large immigration event in 2013

AbstractDemographic changes can result in alterations of social structure and behavior which in turn may affect survival, reproduction, or movement and may influence how populations respond to changes in the environment. In 2013, 52 Atlantic spotted dolphins (Stenella frontalis) left Little Bahama Bank (LBB) and immigrated into a resident group of spotted dolphins on Great Bahama Bank (GBB). Initially there was little interaction and two distinct social clusters delineated by residency status. Here we describe the social structure of the dolphins on GBB between 2015–2020. Analyses were conducted with SOCPROG 2.9 and coefficients of association were nonrandom. The number of associations between LBB and GBB individuals increased, and standardized lagged association rates indicated continued associations over time. Modularity analysis showed one community without clear social clusters, although there were preferential associations within the original communities. Multiple Regression Quadratic Assignment Procedure indicated that sex, age, and residency status were good predictor variables that explained the patterns of the association indices. Male alliances were present between LBB, GBB, and LBB/GBB males. New and old relationships are influencing the social restructuring of this community. This study furthers our understanding of how demographic changes can shape the social structure of a population.

Unlocking social network analysis methods for studying human mobility

Abstract. Planning and operations in urban spaces are strongly affected by human mobility behavior. A better understanding of individual mobility is key to improve transportation systems and to guide the allocation of public space. Previous studies have discovered statistical laws of travel distances, but the topology of movement between places has received little attention. We propose to employ network modelling methods to analyze the effect of spatial and context attributes on individual movement patterns. The perspective of mobility as a network allows to explicitly regard dyadic dependencies of sequential location visits. Here, we consider two methods developed for social networks and provide a formulation of mobility networks to justify their applicability. First, we use the Multiple Regression Quadratic Assignment Procedure to test hypotheses on the influence of location attributes on mobility behavior. Secondly, Stochastic Actor-Oriented Models are applied to model the evolution of mobility networks over time. As a proof-of-concept study, we transform data from one GNSS-based and one check-in based dataset into mobility networks and present results from both methods. We find relations that appear for a majority of samples and thus seem inherent to mobility networks. The differences between individuals and the available datasets are further quantified and discussed. We conclude that the transfer of network modeling methods is an interesting opportunity to study network-related phenomena in geographic information science.

Social integration of adolescents with chronic pain: a social network analysis.

Adolescents with chronic pain (ACP) often experience impairments in their social functioning. Little is known about the consequences of these impairments on peer relationships of ACP. This study applied social network analysis to examine whether adolescents with more pain problems are less popular (RQ1), adolescents with similar pain problems name each other more often as being part of the same peer group (RQ2), dyads with an adolescent experiencing more pain problems report less positive (eg, support) and more negative (eg, conflict) friendship qualities (RQ3), and positive and negative friendship qualities moderate the relationship between pain and emotional distress (RQ4). This study used data from the first wave of a longitudinal study (N = 2767) which followed up Swedish adolescents from 19 public schools. For RQ1-3, Multiple Regression Quadratic Assignment Procedure was applied. For RQ4, standard multilevel models with observations of adolescents nested within schools were estimated. Results showed that ACP were not less popular than adolescents without chronic pain. Second, ACP nominated each other more often as being part of the same peer group. Third, results regarding friendship quality showed that adolescents with more pain problems perceived the relationship with their friends as less positive (eg, support) and more negative (eg, conflict) than adolescents with less pain problems. Finally, positive and negative friendship qualities moderated the relationship between pain and emotional distress. This study contributes to the literature on the importance of peer relationships of ACP. Clinical implications and directions for future research are discussed.

Comparative Agent-Based Simulations on Levels of Multiplicity Using a Network Regression: A Mobile Dating Use-Case

We demonstrate the use of agent-based models to simulate the interactions of two mobile dating applications that possess divergent interaction features. We reproduce several expected outcomes when compared to extant literature. We also demonstrate the use of a standard social network analysis technique—the network regression, Multiple Regression Quadratic Assignment Procedure—in conducting a principled and interpretable comparison between the two models with strong results. This combined approach is novel and allows complex system modelers who utilize agent-based models to reduce their reliance on idealized network structures (small world, scale-free, erdos-renyi) when applying underlying network interactions to agent-based models that can often skew results and mislead from a full picture of system-level properties. This work serves as a proof-of-concept in the integration of classical social network analysis methods and contemporary agent-based modeling to compare software designs and to enhance the policy-generation process of online social networks.

Social Capital Leveraging Knowledge-Sharing Ties and Learning Performance in Higher Education: Evidence From Social Network Analysis in an Engineering Classroom

With the growing attention to the effective use of social network analysis in explaining student learning in STEM (science, technology, engineering, and mathematics) education, the authors explore why college students share knowledge and how they achieve their learning in a laboratory class. In particular, the authors investigate how the social capital each student builds influences individual knowledge sharing and its related learning. The authors establish a research model derived from social capital theory that explains the relational, structural, and cognitive capital the class builds. Network data from 120 students in a lab class in a mechanical engineering department in the United States were collected and analyzed to test the research model and hypotheses using the multiple regression quadratic assignment procedure and UCINET. The findings show that the knowledge sharing mechanism and student learning outcomes can be explained in terms of their social capital within social networks. Last, the authors discuss the theoretical and practical implications for college student learning in a laboratory class in STEM education.

The Association Between Social and Spatial Closeness With PrEP Conversations Among Latino Men Who Have Sex With Men.

US Latino men who have sex with men (LMSM) are a group at highest risk for HIV. One driver of HIV among LMSM is inadequate access to pre-exposure prophylaxis (PrEP) information. The social network theory of homophily suggests that sharing similar sociodemographic factors could influence PrEP conversations within networks. This study aimed to determine how the effects of homophily across sociodemographic, immigration, cultural, and PrEP-related factors are associated with PrEP-related communication. This study was conducted in Miami-Dade County, FL. Data collected between August 2018 and October 2019 included 10 sociocentric friendship groups of 13 LMSM (N = 130). Participants were recruited using respondent-driven sampling by a community-based organization in Miami. We used the multiple regression quadratic assignment procedure to identify the effects of homophily and relationship characteristics on PrEP-related conversations using R software. More frequent PrEP-related conversations were associated with dyadic friendships characterized by homophily on knowledge of PrEP effectiveness, heterophily on depressive symptom severity, home addresses proximity, friend closeness, and interaction frequency. Past PrEP-related conversation frequency also increased based on heterophily on the Latino cultural value of familism (ie, emotional support to family). Racial homophily, heterophily on severity of depressive symptoms, home addresses proximity, friendship closeness, and frequency of interactions increased likelihood to encourage a friend to use PrEP. Social and spatial closeness and homophily play a role in PrEP-related conversations. Information from social networks contextualized in geographic settings can be elucidated to contribute toward the design of novel opportunities to end HIV.