Exploring the relationship between multilevel highway networks and local development patterns—a case study of Taiwan

The relationship between local development patterns and highway networks is complicated, as suggested by studies using various analytical methods. The spatial effects of each hierarchical highway network on local development patterns remains unclear. This study combines space syntax and the hierarchical linear model (HLM) within the research framework in a case study of Taiwan. The former is employed to model the topological accessibility of multilevel highway networks, and the latter is applied to handle the hierarchical relationship between multilevel highway networks and local development patterns. Results indicate a high R-squared (R² = 0.803) value, and statistically significant cross-level interactions are observed. The results show the different spatial effects of various highway networks on the scale of local development patterns, and confirm consideration of highway networks with classification in the research design. The implications of the findings may be appropriate for substantive planning and future research approaches.     

The fortunes of air transport gateways

The paper explores the idea that the fortunes of some gateway cities are changing as airlines use modern aircraft to respond to new market opportunities. It uses data on inter-city journeys between Australia and Asia to identify a hierarchy of gateway cities, and then shows how the connections between them has changed over the 2000–2013 period. Results show that secondary, and smaller, gateways in both Australia and Asia have played more important roles in passenger movements over this time. In Melbourne in particular, stronger growth in the demand for international travel in that city along with more use made of the smaller long-haul aircraft by airlines, has strengthened its role as a gateway city relative to Sydney. These results confirm that the geography of inter-continental air networks are changing which may have important implications for the air transport roles of some cities in the immediate future.     

Managing security risks for inter-organisational information systems: a multiagent collaborative model

Information sharing across organisations is critical to effectively managing the security risks of inter-organisational information systems. Nevertheless, few previous studies on information systems security have focused on inter-organisational information sharing, and none have studied the sharing of inferred beliefs versus factual observations. In this article, a multiagent collaborative model (MACM) is proposed as a practical solution to assess the risk level of each allied organisation’s information system and support proactive security treatment by sharing beliefs on event probabilities as well as factual observations. In MACM, for each allied organisation’s information system, we design four types of agents: inspection agent, analysis agent, control agent, and communication agent. By sharing soft findings (beliefs) in addition to hard findings (factual observations) among the organisations, each organisation’s analysis agent is capable of dynamically predicting its security risk level using a Bayesian network. A real-world implementation illustrates how our model can be used to manage security risks in distributed information systems and that sharing soft findings leads to lower expected loss from security risks.     

Efficiency Determinants and Capacity Issues in Angolan Insurance Companies

This paper describes a variety of approaches used to assess the efficiency of a sample of major insurance companies in Angola between 2003 and 2012. Starting out with the bootstrapping technique, several data envelopment analysis (DEA) estimates were generated, allowing the use of confidence intervals and bias correction in central estimates to test for significant differences in efficiency levels and input‐decreasing/output‐increasing potentials. Previous studies have focused on the measurement and explanation of the factors affecting the performance rather than the prediction. The use of neural networks combined with DEA results as part of an attempt to produce a model for insurance companies’ performance with effective predictive ability is investigated. The findings indicate that older insurance companies with Portuguese origin tend to be more efficient. Results also suggest that opportunities for accommodating future demand appear to be scarce.     

Job Search and the Measurement of Unemployment in South Africa

We interrogate the distinction between searching and non‐searching unemployment in South Africa using data from the first national panel survey that tracks the individual. In particular, we test whether the non‐searching unemployed display a weaker commitment to the labour market than the searching unemployed, and we investigate what counts as search activity. We find that over the panel, the search status of the unemployed does not predict their subsequent employment status, a result that is robust also for subsamples that vary by age cohort, gender and location. Moreover, social networks are the most important job‐finding strategy of the employed. These findings challenge the exclusion of the non‐searching unemployed from the measure of “genuine” work seekers.     

On the multi-dimensionality and sampling of air transport networks

Complex network theory is a framework increasingly used in the study of air transport networks, thanks to its ability to describe the structures created by networks of flights, and their influence in dynamical processes such as delay propagation. While many works consider only a fraction of the network, created by major airports or airlines, for example, it is not clear if and how such sampling process bias the observed structures and processes. In this contribution, we tackle this problem by studying how some observed topological metrics depend on the way the network is reconstructed, i.e. on the rules used to sample nodes and connections. Both structural and simple dynamical properties are considered, for eight major air networks and different source datasets. Results indicate that using a subset of airports strongly distorts our perception of the network, even when just small ones are discarded; at the same time, considering a subset of airlines yields a better and more stable representation. This allows us to provide some general guidelines on the way airports and connections should be sampled.     

A Pathway Forwards for the Social Capital Metaphor

A major topic in economics is the analysis of a broad class of phenomena associated with interpersonal relationships, a topic that originally grew from theories of “social capital.” While the concept has been instrumental in bringing increased attention to social effects on economic outcomes, it has increasingly been replaced with approaches that consider instead networks and discrete interactions rather than aggregate measures of social capital. This has been an analytical improvement, but a great deal of work remains to bring empirical validity and relevancy to social network analysis. This paper presents two important approaches for achieving this, statistical analysis and agent-based modeling, and discusses their benefits, limitations, and complementary nature. Rather than waiting for either approach to achieve an ambiguous quality of maturity, integrating statistical analysis with simulation models of networks must begin now to push the frontiers of social network analysis forward.     

To post or not to post: social media sharing and sporting event performance

Social networks are becoming increasingly important for consumers, especially in the context of sport, where the service experience is highly intense. Few studies have combined subjective event performance variables and social network variables to analyze social network content sharing by sports practitioners. This article investigates the use of social networks in relation to sporting events. An empirical study examined the role of social network variables and sporting event performance variables in social media use. The sample consisted of 410 triathletes (72.2% male) aged between 18 and 66 years (mean 37.03 ± 8.62). Four analyses were performed using fuzzy‐set qualitative comparative analysis to examine the causes of sharing comments through social media, sharing photos and videos on social media, participant satisfaction, and word‐of‐mouth (WOM). The event's general image was a necessary condition in all cases. The combination of participants’ satisfaction and positive event image and the combination of social network use and positive event image lead to social network content sharing by athletes. The combination of positive event image and participant satisfaction leads to a positive WOM.