Bridging the gap between research and practice in organizational network analysis: a conversation between Rob Cross and Martin Kilduff

The article features a conversation between Rob Cross and Martin Kilduff about organizational network analysis in research and practice. It demonstrates the value of using social network perspectives in HRM. Drawing on the discussion about managing personal networks; managing the networks of others; the impact of social networking sites on perceptions of relationships; and ethical issues in organizational network analysis, we propose specific suggestions to bring social network perspectives closer to HRM researchers and practitioners and rebalance our attention to people and to their relationships.

Assessment of embodied energy analysis methods for the Australian construction industry

Environmental assessment of buildings typically focuses on operational energy consumption in an attempt to minimise building energy consumption. Whilst the operation of Australian buildings accounts for around 20% of total energy consumption nationally, the energy embodied in these buildings represents up to 20 times their annual operational energy. Many previous studies, now shown to be incomplete in system boundary or unreliable, have provided much lower values for the embodied energy of buildings and their products. Many of these studies have used traditional embodied energy analysis methods, such as process analysis and input-output (1-0) analysis. More recently, hybrid embodied energy analysis methods have been developed, combining these two traditional methods. These hybrid methods need to be compared and validated, as these too have been considered to have several limitations. This paper aims to evaluate a recently developed hybrid method for the embodied energy analysis of the Australian construction industry, relative to traditional methods. Recent improvements to this hybrid method include the use of more recent 1-0 data and th.fl inclusion of capital energy data. These significant systemic changes mean that a previous assessment of the methods needs to be reviewed. It was found that the incompleteness associated with process analysis has increased from 49% to 87%. These findings suggest that current best-practice methods of embodied energy analysis are sufficiently accurate for most typical applications. This finding is strengthened by recent improvements to the 1-0 model.

Communication network analysis of the enterprise grid systems

This paper addresses the problem of performance analysis based on communication modelling of largescale heterogeneous distributed systems with emphases on enterprise grid computing systems. The study of communication layers is important because the overall performance of a distributed system is often critically hinged on the effectiveness of this part. This model considers processor as well as network heterogeneity of target system. The model is validated through comprehensive simulation, which demonstrates that the proposed model exhibits a good degree of accuracy for various system sizes and under different working conditions. The proposed model is then used to investigate the performance analysis of typical systems.

Three dimensional stability charts for slopes based on limit analysis methods

This paper uses finite element upper and lower bound limit analysis to produce chart solutions for three-dimensional (3D) natural slopes for both short- and long-term stability. The presented chart solutions are convenient tools that can be used for preliminary design purposes. The rigorous limit analysis results in this paper were found to bracket the true factor of safety within ±10% or better, which can be used as a benchmark for the solutions from other methods. The depth of the slip surfaces is observed to be generally shallow for most analyzed cases, particularly for the long-term slope stability problem. In addition, it was found that using a two-dimensional (2D) analysis may lead to significant differences in estimating safety factors, which can differ by 2%–60% depending on the slope geometry and soil properties. Therefore, great care and judgement are required when applying 2D analyses to 3D slope problems.

Twitter tsunami early warning network : a social network analysis of Twitter information flows

In the aftermath of earthquakes, tsunamis, such as the 2011 Great East Japan Tsunami, caused enormous damage around the world. With the extreme disaster events of the past, nations improved disaster preparedness and response through sensors and tsunami early warning systems. Even with system usage, however, governments still need to warn the targeted citizens – who may be anywhere within the vulnerable areas – of predicted tsunami and ordered mass evacuations within a very limited lead time. While social media research is on the rise outside the domain of social networking, very little is written about Twitter use for tsunami early warning. In this research, therefore, we examined the utility of Twitter as a tsunami early warning network, which engages citizens and disaster management agencies in diffusing disaster information. We conducted a social network analysis of Twitter information flows among the central disaster warning agency’s Twitter followers during the 2012 Indonesia Earthquake.

A network analysis of IT governance practices : a case study of an IT centralisation project

Information technology governance (ITG) practices rely on both human and nonhuman actors to support the creation of business value in organisations. The role of nonhuman actors in shaping the ITG practices has been given limited attention within the ITG literature. In proposing a model of ITG, this paper highlights the interplay of human and technological artefacts in shaping the ITG practices. Using a case study approach, this paper explores the relationship and interaction between ITG arrangements and IT infrastructure in an IT centralisation project conducted over a number of years in a university. The analysis from this study highlights how problems in aligning actors’ interests and lack of appropriate strategies lead to a failure in establishing a stable ITG network.

Using social network analysis to identify key child care center staff for obesity prevention interventions: a pilot study

Introduction. Interest has grown in how systems thinking could be used in obesity prevention. Relationships between key actors, represented by social networks, are an important focus for considering intervention in systems. Method. Two long day care centers were selected in which previous obesity prevention programs had been implemented. Measures showed ways in which physical activity and dietary policy are conversations and actions transacted through social networks (interrelationships) within centers, via an eight item closed-ended social network questionnaire. Questionnaire data were collected from (17/20; response rate 85%) long day care center staff. Social network density and centrality statistics were calculated, using UCINET social network software, to examine the role of networks in obesity prevention. Results. “Degree” (influence) and “betweeness” (gatekeeper) centrality measures of staff inter-relationships about physical activity, dietary, and policy information identified key players in each center. Network density was similar and high on some relationship networks in both centers but markedly different in others, suggesting that the network tool identified unique center social dynamics. These differences could potentially be the focus of future team capacity building. Conclusion. Social network analysis is a feasible and useful method to identify existing obesity prevention networks and key personnel in long day care centers.

Analysing stakeholder-associated risks in green buildings : a social network analysis method

In the research of risk associated with developing energy and water efficient green buildings, previous studies had mainly focused on "what the risks are and how the risks may impact on project objectives", which were from an inward looking self-perspective and treated the risks in isolation from one another. While intensive research efforts have been dedicated to risk identification, assessment, classification, prioritisation and mitigation, a research gap exists, that is previous studies had ignored the fact that most risks are interrelated and associated with internal or external project stakeholders. To remedy the gap, this current research developed and presented a SNA (Social Network Analysis) based stakeholder-associated risk analysis method to assess risks in green buildings and the interactions between the risks. A case study has been conducted to demonstrate and validate this method. This research contributes to the development of a new theory to model the interdependent and interactive relationships of risks by using SNA as a methodology. This research should broaden project managers' awareness of the influential risks in green building and enhance their ability to perceive, understand, assess, and mitigate the risks in an effective and efficient way, thereby achieving higher performance in strategic risk management and stakeholder communication in green building development.

Artificial neural network analysis of twin tunnelling-induced ground settlements

In this paper, we apply a computational intelligence method for tunnelling settlement prediction. A supervised feed forward back propagation neural network is used to predict the surface settlement during twin-tunnelling while surface buildings are considered in the models. The performance of the statistical neural network structure is tested on a dataset provided by numerical parametric studies conducted by ABAQUS software based on Shiraz line 1 metro data. Six input variables are fed to neural network model for predicting the surface settlement. These include tunnel center depth, distance between centerlines of twin tunnels, buildings width and building bending stiffness, and building weight and distance to tunnel centerline. Simulation results indicate that the proposed NN models are able to accurately predict the surface settlement.

Social network analysis and small group ‘dark’ networks: an analysis of the London bombers and the problem of ‘fuzzy’ boundaries

Social network analysis (SNA) is believed to be capable of revealing significant insights into crime and terror groups, including identifying important individuals and unique approaches to disruption. However, SNA has a number of theoretical and practical limitations, particularly when applied to ‘dark’ networks. While most analysts certainly acknowledge at least some of these limitations, we need to know more about their potential impact in a crime intelligence context. This article aims to go some way towards that end by placing greater scrutiny on the problem of ‘fuzzy boundaries’ when applied to small group networks. SNA is applied to the groups responsible for the 7 July 2005 London bombings and the 21 July 2005 attempted London bombings. The article concludes that while SNA is a valuable tool for understanding crime and terror groups, the age-old problem of fuzzy boundaries can have a profound impact on the analysis of small dynamic networks.