Leader-member exchange (LMX) differentiation and work outcomes:conceptual clarification and critical review

According to Leader-member Exchange (LMX) theory, leaders develop different quality relationships with followers in their team (termed LMX differentiation). An important theoretical question concerns how different LMX relationships within a team affect followers’ work outcomes. This paper provides a critical review of the concept of LMX differentiation. We propose that the LMX differentiation process leads to patterns of LMX relationships that can be captured by three properties (central tendency, variation, and relative position). We describe a taxonomy illustrating the different ways these properties have been conceptualized and measured. We identify two approaches to LMX differentiation as being a ‘perspective of the team’ (that are shared amongst team members) or a ‘perspective of the follower’ (subjective perceptions unique to each follower). These perspectives lead to different types of measures that predict different outcomes at the individual and team levels. We describe theoretical models employed to explain the effects of LMX differentiation (justice, social comparison and social identity theories). Generally, the lower the within-team variation in LMX or the more a team member’s LMX is higher than the mean team LMX, the better are the work outcomes, but many moderators condition these effects. Finally, we identify some key areas for future research

Academic Performance and Behavioral Patterns

Identifying the factors that influence academic performance is an essential part of educational research. Previous studies have documented the importance of personality traits, class attendance, and social network structure. Because most of these analyses were based on a single behavioral aspect and/or small sample sizes, there is currently no quantification of the interplay of these factors. Here, we study the academic performance among a cohort of 538 undergraduate students forming a single, densely connected social network. Our work is based on data collected using smartphones, which the students used as their primary phones for two years. The availability of multi-channel data from a single population allows us to directly compare the explanatory power of individual and social characteristics. We find that the most informative indicators of performance are based on social ties and that network indicators result in better model performance than individual characteristics (including both personality and class attendance). We confirm earlier findings that class attendance is the most important predictor among individual characteristics. Finally, our results suggest the presence of strong homophily and/or peer effects among university students

Team sports performance analysed through the lens of social network theory: implications for research and practice

This paper discusses how social network analyses and graph theory can be implemented in team sports performance analyses to evaluate individual (micro) and collective (macro) performance data, and how to use this information for designing practice tasks. Moreover, we briefly outline possible limitations of social network studies and provide suggestions for future research. Instead of cataloguing discrete events or player actions, it has been argued that researchers need to consider the synergistic interpersonal processes emerging between teammates in competitive performance environments. Theoretical assumptions on team coordination prompted the emergence of innovative, theoretically-driven methods for assessing collective team sport behaviours. Here, we contribute to this theoretical and practical debate by conceptualising sports teams as complex social networks. From this perspective, players are viewed as network nodes, connected through relevant information variables (e.g., a ball passing action), sustaining complex patterns of interaction between teammates (e.g., a ball passing network). Specialized tools and metrics related to graph theory could be applied to evaluate structural and topological properties of interpersonal interactions of teammates, complementing more traditional analysis methods. This innovative methodology moves beyond use of common notation analysis methods, providing a richer understanding of the complexity of interpersonal interactions sustaining collective team sports performance. The proposed approach provides practical applications for coaches, performance analysts, practitioners and researchers by establishing social network analyses as a useful approach for capturing the emergent properties of interactions between players in sports teams

Communication, advice exchange and job satisfaction of nursing staff: a social network analyses of 35 long-term care units

Background: The behaviour of individuals is affected by the social networks in which they are embedded. Networks are also important for the diffusion of information and the influence of employees in organisations. Yet, at the moment little is known about the social networks of nursing staff in healthcare settings. This is the first study that investigates informal communication and advice networks of nursing staff in long-term care. We examine the structure of the networks, how they are related to the size of units and characteristics of nursing staff, and their relationship with job satisfaction. Methods: We collected social network data of 380 nursing staff of 35 units in group projects and psychogeriatric units in nursing homes and residential homes in the Netherlands. Communication and advice networks were analyzed in a social network application (UCINET), focusing on the number of contacts (density) between nursing staff on the units. We then studied the correlation between the density of networks, size of the units and characteristics of nursing staff. We used multilevel analyses to investigate the relationship between social networks and job satisfaction of nursing staff, taking characteristics of units and nursing staff into account. Results: Both communication and advice networks were negatively related to the number of residents and the number of nursing staff of the units. Communication and advice networks were more dense when more staff worked part-time. Furthermore, density of communication networks was positively related to the age of nursing staff of the units. Multilevel analyses showed that job satisfaction differed significantly between individual staff members and units and was influenced by the number of nursing staff of the units. However, this relationship disappeared when density of communication networks was added to the model. Conclusions: Overall, communication and advice networks of nursing staff in long-term care are relatively dense. This fits with the high level of cooperation that is needed to provide good care to residents. Social networks are more dense in small units and are also shaped by characteristics of staff members. The results furthermore show that communication networks are important for staff's job satisfaction. (aut. ref.

Network-based social capital and capacity-building programs: an example from Ethiopia

<p>Abstract</p> <p>Introduction</p> <p>Capacity-building programs are vital for healthcare workforce development in low- and middle-income countries. In addition to increasing human capital, participation in such programs may lead to new professional networks and access to social capital. Although network development and social capital generation were not explicit program goals, we took advantage of a natural experiment and studied the social networks that developed in the first year of an executive-education Master of Hospital and Healthcare Administration (MHA) program in Jimma, Ethiopia.</p> <p>Case description</p> <p>We conducted a sociometric network analysis, which included all program participants and supporters (formally affiliated educators and mentors). We studied two networks: the Trainee Network (all 25 trainees) and the Trainee-Supporter Network (25 trainees and 38 supporters). The independent variable of interest was out-degree, the number of program-related connections reported by each respondent. We assessed social capital exchange in terms of resource exchange, both informational and functional. Contingency table analysis for relational data was used to evaluate the relationship between out-degree and informational and functional exchange.</p> <p>Discussion and evaluation</p> <p>Both networks demonstrated growth and inclusion of most or all network members. In the Trainee Network, those with the highest level of out-degree had the highest reports of informational exchange, χ²(1, <it>N </it>= 23) = 123.61, p < 0.01. We did not find a statistically significant relationship between out-degree and functional exchange in this network, χ²(1, <it>N </it>= 23) = 26.11, p > 0.05. In the Trainee-Supporter Network, trainees with the highest level of out-degree had the highest reports of informational exchange, χ²(1, <it>N </it>= 23) = 74.93, p < 0.05. The same pattern held for functional exchange, χ²(1, <it>N </it>= 23) = 81.31, p < 0.01.</p> <p>Conclusions</p> <p>We found substantial and productive development of social networks in the first year of a healthcare management capacity-building program. Environmental constraints, such as limited access to information and communication technologies, or challenges with transportation and logistics, may limit the ability of some participants to engage in the networks fully. This work suggests that intentional social network development may be an important opportunity for capacity-building programs as healthcare systems improve their ability to manage resources and tackle emerging problems.</p

Online Stakeholder Interactions in the Early Stage of a Megaproject

The purpose of this paper is to examine the network structure of online stakeholder discussions in the planning stage of a UK public mega project, High Speed Rail. By providing new rail connections between London, Birmingham and Manchester, this project is highly complex as it is embedded in a network of stakeholder relationships that may support or oppose the project. Data drawn from Twitter was analyzed using Social Network Analysis and inductive analysis of user profiles and content. Findings indicate that the majority of online stakeholders oppose the project and form stable clusters. Larger clusters within this network may attempt to deploy power directly in the form of a manipulation strategy while smaller clusters may seek to ally themselves with more powerful groups, a pathway strategy. Overall, the methodology is a useful complement to existing methods and may provide real time insights into the complex, evolving discussions around mega projects

Brokering Trust to Enhance Leadership: A Self-Monitoring Approach to Leadership Emergence

What kind of person is likely to emerge as an informal leader in the workplace? Experimental research shows that high self-monitors—who tend to adjust their attitudes and behaviors to the demands of different situations—emerge as informal leaders in temporary groups. By contrast, low self-monitors—who tend to be true to themselves in terms of consistency in attitudes and behaviors across different situations—are less likely to emerge as leaders. But this prior research does not address the criticism that the emergence of high self-monitors as leaders represents ephemeral impression management in the context of laboratory experiments. To address this issue, we collected and analyzed data from a 116-member high-technology firm. Our results show that self-monitoring is related not only to leadership emergence, but also to the provision of advice to co-workers. Further, people who occupied brokerage positions (being trusted by those who did not trust each other) tended to be seen as leaders if they were high rather than low self-monitors. From these results, we build a picture of the high self-monitoring emergent leader as someone who notices problems and ameliorates them through the provision of advice and the brokerage of relationships across social divides. The occupation of a structurally advantageous position may well be more advantageous for some (i.e., high self-monitors) relative to others (i.e., low self-monitors)

Effective healthcare teams require effective team members: defining teamwork competencies

BACKGROUND: Although effective teamwork has been consistently identified as a requirement for enhanced clinical outcomes in the provision of healthcare, there is limited knowledge of what makes health professionals effective team members, and even less information on how to develop skills for teamwork. This study identified critical teamwork competencies for health service managers. METHODS: Members of a state branch of the professional association of Australian health service managers participated in a teamwork survey. RESULTS: The 37% response rate enabled identification of a management teamwork competency set comprising leadership, knowledge of organizational goals and strategies and organizational commitment, respect for others, commitment to working collaboratively and to achieving a quality outcome. CONCLUSION: Although not part of the research question the data suggested that the competencies for effective teamwork are perceived to be different for management and clinical teams, and there are differences in the perceptions of effective teamwork competencies between male and female health service managers. This study adds to the growing evidence that the focus on individual skill development and individual accountability and achievement that results from existing models of health professional training, and which is continually reinforced by human resource management practices within healthcare systems, is not consistent with the competencies required for effective teamwork

Social networks in primates: smart and tolerant species have more efficient networks

Network optimality has been described in genes, proteins and human communicative networks. In the latter, optimality leads to the efficient transmission of information with a minimum number of connections. Whilst studies show that differences in centrality exist in animal networks with central individuals having higher fitness, network efficiency has never been studied in animal groups. Here we studied 78 groups of primates (24 species). We found that group size and neocortex ratio were correlated with network efficiency. Centralisation (whether several individuals are central in the group) and modularity (how a group is clustered) had opposing effects on network efficiency, showing that tolerant species have more efficient networks. Such network properties affecting individual fitness could be shaped by natural selection. Our results are in accordance with the social brain and cultural intelligence hypotheses, which suggest that the importance of network efficiency and information flow through social learning relates to cognitive abilities