Social and spatial networks: Kinship distance and dwelling unit proximity in rural Thailand

We address a long hypothesized relationship between the proximity of individuals’ dwelling units and their kinship association. Better understanding this relationship is important because of its implications for contact and association among members of a society. In this paper, we use a unique dataset from Nang Rong, Thailand which contains dwelling unit locations (GPS) and saturated kinship networks of all individuals living in 51 agricultural villages. After presenting arguments for a relationship between individuals’ dwelling unit locations and their kinship relations as well as the particulars of our case study, we introduce the data and describe our analytic approach. We analyze how kinship – considered as both a system linking collections of individuals in an extended kinship network and as dyadic links between pairs of individuals – patterns the proximity of dwelling units in rural villages. The results show that in general, extended kin live closer to one another than do unrelated individuals. Further, the degree of relatedness between kin correlates with the distance between their dwelling units. Close kin are more likely to co-reside, a fact which drives much of the relationship between kinship relatedness and dwelling unit proximity within villages. There is nevertheless suggestive evidence of a relationship between kinship association and dwelling unit proximity among kin who do not live together.     

Comparison of Localisation Motives for R&;D Investment of Multinational Enterprises in the New and Old EU Member Regions

The issue of localisation motives is one of the key topics in attracting and motivating MNEs to establish or enhance their R&D activities abroad. The paper aims to compare localisation motives for R&D investment of multinational enterprises in the new and old EU member regions and to find out main localization motives differences among them. We have found out the key motives were technology/supply side factors, which strongly influence decision-making at MNEs in locating and maintaining R&D in all regions. In the more developed regions, the localisation is positively influenced also by the presence of other important/large (high-tech) companies and important universities in the region, which provide relevant services to MNEs. Localisation decisions in the new EU member regions were positively influenced particularly by presence of a quality and cheap labour force and a suitable R&D infrastructure and experience in R&D in these regions. Considerable differences between the old and new EU member states reflects their distinctive economic history, recent re-opening of their economies and consequences of the process of post-communist transition.     

Innovation Policy Challenges in Transition Countries: Foreign Business R&D in the Czech Republic and Hungary

R&D expenditures of national firms decreased considerably and structural changes of R&D financing followed the fall of planned economy in the transition period of Central Eastern European economies. In the middle of the 1990s, business R&D started to grow in the Czech Republic and Hungary due to investments of foreign affiliates and restructuring of domestic companies. Nowadays multinational companies have a decisive share in business R&D in these countries, which entails special challenges for national innovation policy. In this paper, we look through the development of the Czech and Hungarian innovation policy considering MNEs R&D. We use case studies of the Czech automobile industry, the Hungarian pharmaceutical industry, and the new MNE-related university units and private universities to show how these companies influence innovation systems in transition economies.      

The dual role of R&D expenditures in European Union’s member states: short- and long-term prospects

The objective of this article is to assess a potential dual role of public expenditures in R&D upon economic growth and employment, using these dimensions as partial representations of the socioeconomic state of affairs in European Union’s Member States. First, we look into direct, short-term impacts arising from R&D expenditures, much in the sense of a multiplier effect. Second, we analyse impacts from the stage of development of National Innovation Systems (NIS) upon the macroeconomic conditions of interest, assuming that current stages of development are products of previous commitment to innovation, that is, a structural, long-term outcome of innovation-oriented investments. In order to empirically test our propositions, we have analysed 28 EU Member States (1990–2013) through three sets of econometric (static and dynamic panel data) models. Results highlight that EU countries’ governmental commitment to their respective innovation systems catalyses current and prospective economic growth and employment levels, suggesting a complementarity between Neo-Schumpeterian and Neo-Keynesian perceptions over governmental R&D involvement. This can bring innovation efforts closer to the macroeconomic debate on monetary and fiscal policies and function as a criticism to austerity measures, as this may not only affect the present socioeconomic situation, but also generate the cornerstone for a perennial state of divergence among EU Member States.     

MEASURING THE INTERDEPENDENCE OF MULTINATIONAL FIRMS' FOREIGN INVESTMENTS

Earlier work found evidence for geographic linkages of aggregate foreign direct investment across countries and country‐pairs. From a theoretical point of view, such linkages at the macroeconomic level may root in between‐firm as well as within‐firm linkages and originate from information spillovers across or within firms in exploring unknown markets, and vertical linkages between production plants across different locations within the firm. We use data on the universe of German multinational enterprises (MNEs) to empirically explore how marginal investments at one foreign affiliate depend on investments at other affiliates within the same MNE. The empirical approach employs two channels or modes of cross‐affiliate interdependence: mere geography (capturing horizontal linkages through correlated learning and horizontal competition within the firm) and input–output relationships within or across industries (which capture vertical linkages). Adding to earlier findings at the aggregate level, we find evidence of a significant interdependence of investments within the firm. In the firm‐level data at hand, vertical linkages appear to be more important than horizontal ones. Investments at one location tend to stimulate investments at other locations of the same MNE, particularly if input linkages are strong. The opposite seems to be true for output linkages. Beyond vertical linkages, mere geographic proximity matters only to a minor extent. This suggests that evidence of linkages through geographic closeness at aggregate data levels accrue mainly to reasons of vertical linkages within networks of affiliates. (JEL C31, D22, F21, F23, F68, G31, H32)     

LAST OF THE DINOSAURS? BIG WEAPONS,BIG SCIENCE,AND THE AMERICAN STATE FROM HIROSHIMA TO THE END OF THE COLD WAR

This article examines the origins and recent crises in linkages between big science, big weapons, and the U.S. state during and after the cold war. We examine the sources of legitimacy of military dominance of U.S. research and development (R&D) in the first decades of the cold war and argue that the exigencies of a nuclear arms race between two superpowers gave the military an unprecedented peacetime claim on science and technology resources. We argue that economic crises, political challenges by peace movements, and technological exhaustion of the nuclear arms race in the 1980s weakened military claims to science and technology leadership, but that the 1991 Persian Gulf war deflected what might have been a major shift in U.S. R&D priorities. We conclude by examining U.S. post-cold war R&D policy and find that military priorities remain preeminent.     

A deviational approach to blockmodeling of valued networks

This article proposes a novel approach to blockmodeling of valued (one-mode) networks where the identification of (binary) block patterns in the valued relations differ from existing approaches. Rather than looking at the absolute values of relations, or examining valued ties on a per-actor basis (cf. Nordlund, 2007), the approach identifies prominent (binary) ties on the basis of deviations from expected values. By comparing the distribution of each actor's valued relations to its alters with the macro-level distributions of total in- and outdegrees, prominent (1) and non-prominent (0) ties are determined both on a per-actor-to-actor and a per-actor-from-actor basis. This allows for a direct interpretation of the underlying functional anatomy of a non-dichotomized valued network using the standard set of ideal blocks as found in generalized blockmodeling of binary networks.In addition to its applicability for direct blockmodeling, the article also suggests a novel indirect measure of deviational structural equivalence on the basis of such deviations from expected values.Exemplified with the note-sharing data in Žiberna (2007a), citations among social work journals (Baker, 1992), and total commodity trade among EU/EFTA countries as of 2010, both the direct and indirect approach produce results that are more sensitive to variations at the dyadic level than existing approaches. This is particularly evident in the case of the EU/EFTA trade network, where the indirect approach yields partitions and blockmodels in support of theories of regional trade, despite the significantly skewed valued degree distribution of the dataset.     

Detecting interaction links in a collaborating group using manually annotated data

Identification of network linkages through direct observation of human interaction has long been a staple of network analysis. It is, however, time consuming and labor intensive when undertaken by human observers. This paper describes the development and validation of a two-stage methodology for automating the identification of network links from direct observation of groups in which members are free to move around a space. The initial manual annotation stage utilizes a web-based interface to support manual coding of physical location, posture, and gaze direction of group members from snapshots taken from video recordings of groups. The second stage uses the manually annotated data as input for machine learning to automate the inference of links among group members. The manual codings were treated as observed variables and the theory of turn taking in conversation was used to model temporal dependencies among interaction links, forming a Dynamic Bayesian Network (DBN). The DBN was modeled using the Bayes Net Toolkit and parameters were learned using Expectation Maximization (EM) algorithm. The Viterbi algorithm was adapted to perform the inference in DBN. The result is a time series of linkages for arbitrarily long segments that utilizes statistical distributions to estimate linkages. The validity of the method was assessed through comparing the accuracy of automatically detected links to manually identified links. Results show adequate validity and suggest routes for improvement of the method.     

Parental Housing Assistance and Parent‐Child Proximity in Italy

Many studies of intergenerational exchanges include parent‐child proximity as an exogenous explanatory variable. Proximity may itself be a consequence of intergenerational resource flows, however. We analyze patterns of economic transfers between generations and their relationship to parent‐child proximity in Italy. Parental support for a child's home purchase may influence the child's choice of location, whether to facilitate parent‐child contacts, grandchild care, or parent care. We examine the situation of married couples, focusing on housing help received and the association of that help with proximity to each spouse's parents. Using 1998 survey data and multinomial logistic regression models, we find that past housing assistance has a significant effect on current proximity to each spouse's parents, controlling for parents' survival, family composition, and other factors.     

Measuring the Role of Central and Eastern European Countries in World Drug Research

This paper explores the sociological behavior of firms in the pharmaceutical industry in Central and Eastern Europe as measured by funding linkages. Using the ISI Web of Science data-base, the number of research papers funded by top American and European pharmaceuticals with at least one author from Central and Eastern Europe are identified. Results indicate that Poland leads in the region by both the number of papers funded and by percentage of a firm’s total papers funded, followed closely by Hungary, Greece and the Czech Republic. Though the percentages of any firm’s linkages with a Central and Eastern European author are small (upper limit being 6.6%), this percentage is skewed due to the fact that the US is cited for 50% of papers for most firms. Roche Corporation is the top funder of papers among both US and European firms. Incidentally, zero top American pharmaceuticals were found to have an R&D center located in Central and Eastern Europe whereas European firms: GlaxoSmithKline and Sanofi-Aventis do—possibly indicating a difference in business strategy between European and American pharmaceuticals.     

Network dynamics and its impact on innovation outcomes: R&D consortia in the Dutch water sector

In this study, we explore the relationship between inter-organizational network dynamics and innovation outcomes. We focus on node turnover and argue that both cluster and broker dynamics can range from low (stable) to high (volatile), resulting in differentiated outcomes. The data comprises 318 consortium members participating in 104 R&D consortia forged in a 23-year period in the Dutch water sector. Our analysis reveals two equifinal combinations (stable brokers – volatile clusters and volatile brokers – stable clusters) that both generate significantly higher innovation outcomes compared to networks with low, moderate, or high dynamics across the entire network.     

Research and Development Spillovers in Central and Eastern Europe

The present study considers the implications of different stages of economic integration for endogenous growth models with horizontal differentiation of the intermediate goods. It investigates the decline of the domestic R&D (research and development) sector for countries with lower initial stock of R&D due to partial integration in the form of free trade. The problem is investigated with empirical analysis for panel data for 12 EU accession countries in the period of 1990–2001. The specification relating the growth of total factor productivity, the domestic and the available foreign stock of R&D is estimated with first-differences, ordinary least-squares, dynamic panel data, and GMM methods. The time series are highly persistent and the applied procedures have different advantages according to the assumptions and the purpose of the analysis. All methods establish the comparable result that the foreign R&D stock interacted with the import share is a substantial and significant factor for the growth of total factor productivity. The role of the domestic R&D is insignificant for the growth of total factor productivity, verifying the decline of the sector with free trade.     

The interplay between formal project memberships and informal advice seeking in knowledge-intensive firms: A multilevel network approach

In this study we investigate the interplay between knowledge workers’ formal project team memberships and their informal interactions from a multilevel network perspective. Conceptualizing knowledge workers’ affiliation with project teams as a membership network and their interactions as an advice network, we discuss how shared project team memberships as well as multiple memberships influence patterns of informal exchange in knowledge-intensive organizations. To empirically determine the impact of formal organization on informal exchange we apply exponential random graph models for multilevel networks to relational data collected on 434 R&D employees working on 218 project teams in a high-tech firm in Germany. Our results show that employees sharing project memberships create advice ties to each other but do not exchange advice reciprocally. In addition, we find a negative relationship between having a high number of project memberships and informally seeking or providing advice.     

Time as a limited resource: Communication strategy in mobile phone networks

We used a large database of 9 billion calls from 20 million mobile users to examine the relationships between aggregated time spent on the phone, personal network size, tie strength and the way in which users distributed their limited time across their network (disparity). Compared to those with smaller networks, those with large networks did not devote proportionally more time to communication and had on average weaker ties (as measured by time spent communicating). Further, there were not substantially different levels of disparity between individuals, in that mobile users tend to distribute their time very unevenly across their network, with a large proportion of calls going to a small number of individuals. Together, these results suggest that there are time constraints which limit tie strength in large personal networks, and that even high levels of mobile communication do not fundamentally alter the disparity of time allocation across networks.     

Effects of competition on collective learning in advice networks

This paper looks at the effect of identifying alters as direct competitors on their selection as advisors. We differentiate between two kinds of competition: cut-throat vs friendly. We argue that, unlike cut-throat competition, friendly competition makes collective learning possible as a social process: when knowledge is built in interactions that are able to mitigate the negative effects of status competition and take place in homophilous social niches; and when the quality of this knowledge is guaranteed by members with epistemic status in these niches. Social niches and status facilitate advice seeking and collective learning because advice seeking between direct competitors is not obvious even when members have a common interest in sharing advice – a learning-related dilemma of collective action. We apply this reasoning to a network dataset combining identification of direct competitors and selection of advisors among the elite of cancer researchers in France. We use a procedure of multiplex stochastic block-modeling designed by Barbillon et al. (2015) to measure the effect of these identifications of direct competitors on the structure of the advice network. Results obtained with this dataset support our theory.     

Corporate social responsibility driven innovation

This study identifies the substantial relationship between corporate social responsibility (CSR) and innovation activities of firms. Using the French Vigeo sustainability rating and the Thomson Reuters, we divided 619 firms into groups by their industry sectors, regions, and firm characteristics such as size and age. We premise that innovative investment is needed to prepare tomorrow's profits not only by considering investments in technology and in R&D, but also by dealing with sustainability to human, social, environmental, technical, and economic investments. Consequently, when the firm manipulates its short- and long-run business strategies, the consideration of the correlation between types of investment and CSR initiatives will lead to more cooperating effect on the outcome of investments. The findings provide a comprehensive understanding on the effect of sustainable management strategies on the innovation and sustainability of firms.     

Hubs and Authorities in the Koch Brothers Network

The empirical focus is centered on the large social movement network created by the Koch Brothers to further their aims of transforming the US. The network was obtained by using the VOSON web crawler given a starting set of known allies of the Koch Brothers. This produced a large directed network with links between units. We propose using the idea of hubs and authorities as another way of considering the roles played by the units within this network. These roles may be more complex than has been realized. We have included an analysis of the core interests for the members of this network.     

U.S. unionism and R&D investment: Evidence from a simple cross-country test

This paper implements Freeman’s suggestion that insights into the effect of U.S. unionism on R&D investment may be obtained by correlating U.S. union density by industry with R&D investment by industry in another country, here Germany.     

Unions and innovative activity in Germany

This study is the first attempt to investigate the influence of unions on innovative activities in Germany at the industry level. Econometric models estimated by a highly robust method and submitted to a number of specification tests indicate that trade unions do not have a negative impact on innovative activity which is measured by either the percentage of revenues spent on R&D or the percentage of employees working in R&D. This finding is consistent with evidence on the influence of unions on productivity in Germany and with considerations about the German system of industrial relations.