Norms,status and the dynamics of advice networks: A case study

The issue of the influence of norms on behavior is as old as sociology itself. This paper explores the effect of normative homophily (i.e. “sharing the same normative choices”) on the evolution of the advice network among lay judges in a courthouse. 0020 and 0025 social exchange theory suggests that members select advisors based on the status of the advisor. Additional research shows that members of an organization use similarities with others in ascribed, achieved or inherited characteristics, as well as other kinds of ties, to mitigate the potentially negative effects of this strong status rule. We elaborate and test these theories using data on advisor choice in the Commercial Court of Paris. We use a jurisprudential case about unfair competition (material and “moral” damages), a case that we submitted to all the judges of this court, to test the effect of normative homophily on the selection of advisors, controlling for status effects. Normative homophily is measured by the extent to which two judges are equally “punitive” in awarding damages to plaintiffs. Statistical analyses combine longitudinal advice network data collected among the judges with their normative dispositions. Contrary to what could be expected from conventional sociological theories, we find no pure effect of normative homophily on the choice of advisors. In this case, therefore, sharing the same norms and values does not have, by itself, a mitigating effect and does not contribute to the evolution of the network. We argue that status effects, conformity and alignments on positions of opinion leaders in controversies still provide the best insights into the relationship between norms, structure and behavior.     

The embeddedness of social relations in inter-firm competitive structures

Collaboration with direct competitors is a valuable, yet risky, strategy that might pave the way for competitive advantages. Thus far, we have lacked a detailed understanding of how competitive relations between firms shape collaborative relations between their managers, and consequently the structural interdependencies at both levels. The primary objective of this study is to understand the multi-level structure underlying the ambiguous relationship of coopetition, a state of simultaneous collaboration and competition. Hence, we investigate the influence of perceived inter-firm competition on interpersonal knowledge flows among managers within three high-tech clusters by applying multi-level exponential random graph models to network data. Our results reveal that the interpersonal exchange of advice and information depends strongly on the inter-firm competitive structure and that competitive structures shape these interpersonal exchanges in different ways. Thereby, our research demonstrates that managers utilize asymmetries by means of perceived competitive relations to seek work-related advice and information from their competitors and that stronger forms of competition are significant, but not insuperable, obstacles to the exchange of knowledge.     

Position in formal structure, personal characteristics and choices of advisors in a law firm: A logistic regression model for dyadic network data

This paper presents a statistical model for the analysis of binary sociometric choice data, the p₂ model, which provides a flexible way for using explanatory variables to model network structure. It is applied to examine the influence of the formal structure of an organization on interactions among its members. It is shown to provide a general and precise method for addressing this substantive issue. We identify the respective effects of position in the formal structure (status, seniority, division of work and office membership) and selected personal characteristics of members of a corporate law firm on their choices of advisors. Flows of advice are shown to be consistently shaped by status games and the pecking order in the firm. Other dimensions help members in mitigating the effect of this strong rule. This approach ultimately provides more understanding of how members of such firms try to balance cooperation and competition in terms of access to and management of key resources.     

Relational collaboration among spatial multipoint competitors

The presence of network ties between multipoint competitors is frequently assumed but rarely examined directly. The outcomes of multipoint competition, therefore, are better understood than their underlying relational mechanisms. Using original fieldwork and data that we have collected on an interorganizational network of patient transfer relations within a regional community of hospitals, we report and interpret estimates of Exponential Random Graph Models (ERGM) that specify the probability of observing network ties between organizations as a function of the degree of their spatial multipoint contact. We find that hospitals competing more intensely for patients across multiple geographical segments of their market (spatial multipoint competitors) are significantly more likely to collaborate. This conclusion is robust to alternative explanations for the formation of network ties based on organizational size differences, resource complementarities, performance differentials, and capacity constraints. We show that interorganizational networks between spatial multipoint competitors are characterized by clear tendencies toward clustering and a global core-periphery structure arising as consequences of multiple mechanisms of triadic closure operating simultaneously. We conclude that the effects of competition on the structure of interorganizational fields depends on how markets as physical and social settings are connected by cross-cutting network ties between competitors.     

Corporate competition: A self-organized network

A substantial number of studies have extended the work on universal properties in physical systems to complex networks in social, biological, and technological systems. In this paper, we present a complex networks perspective on interfirm organizational networks by mapping, analyzing and modeling the spatial structure of a large interfirm competition network across a variety of sectors and industries within the United States. We propose two micro-dynamic models that are able to reproduce empirically observed characteristics of competition networks as a natural outcome of a minimal set of general mechanisms governing the formation of competition networks. Both models, which utilize different approaches yet apply common principles to network formation give comparable results. There is an asymmetry between companies that are considered competitors, and companies that consider others as their competitors. All companies only consider a small number of other companies as competitors; however, there are a few companies that are considered as competitors by many others. Geographically, the density of corporate headquarters strongly correlates with local population density, and the probability two firms are competitors declines with geographic distance. We construct these properties by growing a corporate network with competitive links using random incorporations modulated by population density and geographic distance. Our new analysis, methodology and empirical results are relevant to various phenomena of social and market behavior, and have implications to research fields such as economic geography, economic sociology, and regional economic development.     

Where do intra-organizational advice relations come from? The role of informal status and social capital in social exchange

Social status and social capital frameworks are used to derive competing hypotheses about the emergence and structure of advice relations in organizations. Although both approaches build on a social exchange framework, they differ in their behavioral micro-foundations. From a status perspective, advice giving is a means to generate prestige, whereas asking advice decreases one's relative standing. At a structural level these motivations are expected to result in an overrepresentation of non-reciprocal dyads and non-cyclical triadic structures in the advice network, as well as in active advice seekers being unlikely to be approached for advice, especially by active advice givers. From a social capital perspective, advice seeking creates obligations for the advice seeker. At the structural level, this results in an overrepresentation of reciprocal dyads and cyclical triads, and active advice seekers to be unpopular as targets of advice seeking, especially for active advice givers. Analyses of four waves of a longitudinal sociometric study of 57 employees of a Dutch Housing Corporation provide partial support for both approaches. In line with the social capital perspective, we find reciprocal advice relations to be overrepresented at the dyad level. Results at the triad level support the social status arguments, according to which high status individuals will avoid asking advice from low status individuals. The implications for macro-structural properties of intra-organizational advice network are discussed.     

Markets,prices and symbolic value: grands crus and the challenges of global markets

Certain authors have drawn attention to the fact that competition between businesses has taken the form of competition for the power over regulation and the imposition of a particular style of production. The dominant businesses can thus create barriers to those entering the market, which can either be cultural or legal. The strategies employed essentially consist of establishing norms of production which prevent competitors from entering the market in such a way that competition, as Simmel refers to it, never takes the form of direct fonflict. By examining the French wine industry, the aim of this work is to investigate how this form of market control, which is only favourable for a certain number of businesses, can be brought into question. Given that it is usually technological innovation which is responsible for the transformation of the market forces involved with industrially produced products, the wine market is very interesting to study as such innovation is often excluded through the institutionalisation of scarcity. This institutionalisation is constructed on the valorisation of ‘traditional’ methods and the delimitation of certain privileged zones of production. How can such rules which attribute the principle of non-reproductibility to history and nature be brought into question? Firstly, we can investigate the specificity of newcomers to the market who are capable of destabilising the current norms of production. We can also investigate whether we should attribute such questioning of the dominant norms to the particular distinctive properties of said norms, or whether we need to take into account other relevant transformations occurring in a wider social context. Notable examples of such transformations are the increase in standing of oenology from mere knowledge to the status of a science with its recognised professions, the reorganisation of rural space and the reorganisation of market structures, in particular the social composition of demand.     

Multiplexity,generalized exchange and cooperation in organizations: a case study

Cooperation in an organization can be studied empirically by examining the routine transfers or exchanges among members of various kinds of resources. We argue that local regularities in the form of these transfers and exchanges shape the structure of cooperation. Using a case study of resource networks in a corporate law firm, we model the structure of cooperation in a specific work environment, one that is characterized by multifunctional and sometimes multidisciplinary work groups in which `status competition' is argued to be a particularly strong motivation driving participation. Specific statistical tools, p* models, are used to identify local regularities in the interplay between exchanges and transfers of three types of social resource (coworkers' goodwill, advice and friendship). We propose that these regularities help to provide structural solutions for the problems of collective participation and status competition in such organizations.     

Status and welfare under monopolistic competition

This article departs from the traditional welfare analysis of social status seeking by incorporating scale economies, product differentiation, and monopolistic competition into a model. I argue that social status seeking could be welfare improving rather than the usual conclusion that social status seeking is welfare-reducing, under some assumptions that are not particularly strong. Market distortions of the quantity–variety and consumption–leisure trade-off may be corrected by social status seeking. Since modern societies are arguably closer to monopolistic competition than perfect competition, we may also need to rethink the long-held belief that the welfare effects caused by social status seeking are usually negative.     

Reflections on engaging with an advisory network in the context of a ‘sensitive’ research study

This article surfaces issues about the often-used but widely under-reported practice of working with advisory fora. We critically reflect on our experiences working with an advisory network when co-designing a research study about a ‘sensitive’ subject. We discuss the following: 1) How the network evolved as a matter of ethical and pragmatic choices; 2) Potential issues when discussing sensitive issues ‘outside’ of the participatory or participant context; and 3) Practical and epistemic issues involved in (not) ‘taking’ advice. We suggest that although sensitive research is more conventionally aligned with more ‘radical’ forms of participatory practice, advisory networks can present a useful and sometimes more appropriate form of inclusion and engagement for some advisors and for some types of research study. The article should, therefore, be of interest to a wide range of academic and practice-based health and social care staff and, in particular, those who plan to use advisory fora in their work.     

Social network and content analysis of the North American Carbon Program as a scientific community of practice

The North American Carbon Program (NACP) was formed to further the scientific understanding of sources, sinks, and stocks of carbon in Earth's environment. Carbon cycle science integrates multidisciplinary research, providing decision-support information for managing climate and carbon-related change across multiple sectors of society. This investigation uses the conceptual framework of communities of practice (CoP) to explore the role that the NACP has played in connecting researchers into a carbon cycle knowledge network, and in enabling them to conduct physical science that includes ideas from social science. A CoP describes the communities formed when people consistently engage in shared communication and activities toward a common passion or learning goal. We apply the CoP model by using keyword analysis of abstracts from scientific publications to analyze the research outputs of the NACP in terms of its knowledge domain. We also construct a co-authorship network from the publications of core NACP members, describe the structure and social pathways within the community. Results of the content analysis indicate that the NACP community of practice has substantially expanded its research on human and social impacts on the carbon cycle, contributing to a better understanding of how human and physical processes interact with one another. Results of the co-authorship social network analysis demonstrate that the NACP has formed a tightly connected community with many social pathways through which knowledge may flow, and that it has also expanded its network of institutions involved in carbon cycle research over the past seven years.     

Attending to Social Justice in Clinical Social Work: Supervision as a Pedagogical Space

Although social justice is a central professional value of social work articulated in ethics codes, clinical social workers have been long criticized for not clearly incorporating this professed commitment into practice. Supervision is an optimal space within which clinicians can develop knowledge and skills to attend to the issues related to social justice in their practice. A growing body of literature emphasizes social justice in the delivery of clinical services, yet there is a death of literature on how clinical supervision can promote social justice seeking clinical work. In this paper, we draw from existing literature to identify key elements involved in social justice seeking clinical supervision. Using Goodyear’s (Clin Superv 33:82–99, 2014) learning mechanisms of clinical supervision, which consists of modeling, feedback, direct instruction, and self-directed learning, we discuss a case composite to illustrate ways in which clinical supervision can serve as a pedagogical space to advance clinical social workers’ commitment to social justice.     

When policy advisors cannot reach a consensus

In this paper advisors are selected by two ministers with conflicting interests in order to (1) acquire information, and (2) obtain political legitimacy concerning a project. In the end, parliament decides whether or not the project, of which the consequences are uncertain, is implemented. In principle a minister wants to appoint an advisor whose preferences are similar. However, since the advisor needs to convince the decisive player in the model, the minister may appoint an advisor whose preferences are closer to those of the agents to be persuaded. We also show when polarised advice occurs (the advisors have different preferences) and when consensual advice occurs (they have the same preferences). Received: 29 June 1998/Accepted: 26 May 1999     

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.     

Social Influences and Aggregated Immigration Dynamics: The Case of Spain 1999–2009

This research aims at broadening the applicability and scope of network‐based explanations of international migration to include explanations of aggregated immigration dynamics for multiple immigrant collectives. Using a unique dataset that contains data on approximately 4.5 million international immigration events from 180 different origin countries in Spain between 1999 and 2009, my analysis shows conclusively that information about changes in the supply of immigrant social capital between past and potential immigrants explains the variation in local immigration rates in the destination society. It also show that incorporating information about such social network influences is very informative when the goal is to explain (1) temporal variation in intra‐collective international immigration flows across different locations in the destination, (2) temporal variation in inter‐collective international immigration flows within a specific location in the destination, (3) intra‐collective differences in international immigration across locations in the destination, and finally (4) inter‐collective differences in local international immigration within the same geographical location in the destination.     

Social Distance and Affective Orientations1

Most groups have social distance norms that differentiate “us” from “them.” Contrary to a widespread assumption in the sociological literature, however, these normative distinctions, even when they are collectively recognized, do not always overlap with the affective orientations of group members in a uniform manner. Relations between normatively close members of a group are not always warm and friendly, and normatively distant groups can sometimes be an object of reverence and love. In this study, a typology of five different ways in which normatively distant groups can be perceived is presented: as competitors, allies, symbols of otherness, saviors, and ambivalent figures. Each type tends to emerge under certain circumstances and triggers different affective orientations. This typology is not a substitute for a general theory, but it aims to provide preliminary insights for investigating why affective orientations toward normatively distant groups take different forms and, more generally, to motivate further inquiry into the relationships between different dimensions of social distance.     

Hospice of the Red River Valley: A nonprofit's response to for‐profit competition

Research of nonprofit versus for‐profit competition points to potential quality and access advantages of the nonprofit, tied to shared community values leading to enhanced social capital and legitimacy, whereas the for‐profit is known for cost and scale advantages. However, the prevailing mode of thinking in mixed‐form competitive contexts urges nonprofits to become “more businesslike” and imitate for‐profit attributes. This qualitative study of a nonprofit organization facing new for‐profit competition illustrates that while it is possible and advisable to learn from for‐profit competitors, it is not necessary or even desirable for the nonprofit to abandon its own unique advantages. Although nonprofits should be increasingly sensitive to cost and scale advantages, they do not have to imitate for‐profit attributes and play the low‐cost game. A competitive response to for‐profit challenges that is carefully crafted and executed based on the unique advantages of the nonprofit organization can truly win the day.     

Limited opportunities: Adolescents’ access to social capital in secondary schools in three European countries

While previous research indicates that students benefit from their peers’ resources, little is known about access to social capital in the school context. Therefore, this study examines differential access to social capital – measured by friends’ socioeconomic status (SES), the number of books they have at home, and their reading habits – in secondary schools in Germany, the Netherlands, and Sweden. Relying on a large-scale dataset, I investigate the association between socioeconomic status, minority status, and social capital using complete friendship network information. I argue that social capital access is connected to a two-stage process consisting of school sorting and friendship selection. To differentiate between these two processes, I apply within-between random effects (REWB). The models show that friendship selection is much less relevant for access to social capital than school sorting. Results indicate that while high-SES students have better access to social capital across dimensions, access patterns for minority students are more nuanced.     

If you do not know who knows what: Advice seeking under changing conditions of uncertainty after an acquisition

In this study we develop a model to explain the dynamics of advice seeking after an acquisition. We build on a theory of advice seeking that draws from prospect theory and expectancy theory. We theorize that immediately after an acquisition there is uncertainty about who knows what, but over time individuals become more aware of the expertise within the organization and they change their advice networks based upon this increased awareness. Our model examines four micro-processes of advice seeking: reciprocity, preferential attachment, transitivity, and legacy-firm tie preferences. To test our hypotheses we use post-acquisition data over four time periods in a recruitment consulting firm. Our longitudinal analysis uses a stochastic actor-orientated model and our results indicate that immediately after the acquisition individuals have a tendency to seek advice based upon reciprocity and preferential attachment. However, over time these tendencies diminish. Surprisingly, transitivity does not play a significant role, which suggests that other micro-processes such as reciprocity are dominant. In addition, individuals in the acquired firm have a tendency to make more ties and there is a preference for same firm ties in both legacy firms, with the tendency being higher in the acquired firm. Our findings add to theories on the process of advice seeking under conditions of uncertainty, on knowledge transfer processes in mergers and acquisitions, and the knowledge based view of the firm.     

Random sampling of alters from networks: A promising direction in egocentric network research

The social network perspective has great potential for advancing knowledge of social mechanisms in many fields. However, collecting egocentric (i.e., personal) network data is costly and places a heavy burden on respondents. This is especially true of the task used to elicit information on ties between network members (i.e., alter-alter ties or density matrix), which grows exponentially in length as network size increases. While most existing national surveys circumvent this problem by capping the number of network members that can be named, this strategy has major limitations. Here, we apply random sampling of network members to reduce cost, respondent burden, and error in network studies. We examine the effectiveness and reliability of random sampling in simulated and real-world egocentric network data. We find that in estimating sample/population means of network measures, randomly selecting a small number of network members produces only minor errors, regardless of true network size. For studies that use network measures in regressions, randomly selecting the mean number of network members (e.g., randomly selecting 10 alters when mean network size is 10) is enough to recover estimates of network measures that correlate close to 1 with those of the full sample. We conclude with recommendations for best practices that will make this versatile but resource intensive methodology accessible to a wider group of researchers without sacrificing data quality.