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The purpose of this paper is to explore whether online communities meet their potential of providing environments in which social relationships can be readily established to help patients cope with their disease through social support. The paper aims to develop and test a model to examine antecedents of the formation of virtual relationships of cancer patients within virtual communities (VCs) as well as their effects in the form of social assistance.

Data were collected from members of virtual patient communities in the German‐speaking internet through an online survey to which 301 cancer patients responded. The data were analyzed with partial least square (PLS) structural equation modeling.

Virtual relationships for patients are established in VCs and play an important role in meeting patients' social needs. Important determinants for the formation of virtual relationships within virtual communities for patients are general internet usage intensity (active posting vs lurking) and the perceived disadvantages of CMC. The paper also found that virtual relationships have a strong effect on virtual support of patients; more than 61 per cent of the variance of perceived social assistance of cancer patients was explained by cancer‐related VCs. Emotional support and information exchange delivered through these virtual relationships may help patients to better cope with their illness.

In contrast to prior research, known determinants for the formation of virtual relationships (i.e. marital status, educational status, gender, and disease‐related factors such as the type of cancer as control variables, as well as general internet usage motives, and perceived advantages of CMC as direct determinants) played a weak role in this study of German cancer patients. Studies on other patient populations (i.e. patients with other acute illnesses in other cultures) are needed to see if results remain consistent.

Participants and administrators of patient VCs have different design criteria for the improvement of VCs for patients (e.g. concerning community management, personal behaviour and the usage of information in online communities). Once the social mechanisms taking place in online communities are better understood, the systematic redesign of online communities according to the needs of their users should be given priority.

Little research has been conducted examining the role of VCs for social relationships and social networks in general and for patients in particular. Antecedents and effects of virtual social relationships of patients have not been sufficiently theoretically or empirically researched to be better understood. This research combines various determinants and effects of virtual relationships from prior related research. These are integrated into a conceptual model and applied empirically to a new target group, i.e. VCs for patients.

Scenarios have become a vital methodological approach in business as well as in public policy. When scenarios are used to guide analysis and decision-making, the aim is typically robustness and in this context we argue that two main problems at scenario set level is conservatism, i.e. all scenarios are close to a perceived business-as-usual trajectory and lack of balance in the sense of arbitrarily mixing some conservative and some extreme scenarios. The purpose of this paper is to address these shortcomings by proposing a methodology for generating sets of scenarios which are in a mathematical sense maximally diverse.

In this paper, we develop a systematic methodology, Scenario Diversity Analysis (SDA), which addresses the problems of broad span vs conservatism and imbalance. From a given set of variables with associated states, SDA generates scenario sets where the scenarios are in a quantifiable sense maximally different and therefore best span the whole set of feasible scenarios.

The usefulness of the methodology is exemplified by applying it to sets of storylines of the emissions scenarios of the Intergovernmental Panel on Climate Change. This ex-post analysis shows that the storylines were not maximally diverse and given the challenges ahead with regard to emissions reduction and adaptation planning, we argue that it is important to strive for diversity when developing scenario sets for climate change research.

The proposed methodology adds significant novel features to the field of systematic scenario generation, especially with regard to scenario diversity. The methodology also enables the combination of systematics with the distinct future logics of good intuitive logics scenarios.

The purpose of this study is to explore spatiotemporal factors that affect the empirical analysis of whether crime rates in buffer areas surrounding abandoned properties transferred to a Land Bank that differed among three regimes: before transfer, during Land Bank stewardship and after disposition and whether those differences were associated with differences in relative crime activity in the neighborhoods in which they were located.

This study analyzed crime incidents occurring between 2010 and 2018 in 0.1-mile buffer areas surrounding 31 abandoned properties sold by the Land Bank and their neighborhoods in which those properties were located. Using Copulas, researchers compared concordance/discordance in the buffer areas across the three regime states for each property and approximately matched time periods for associated neighborhoods.

In a substantial number of cases, the relative crime activity levels for buffer areas surrounding individual sold properties as measured by the Copulas shifted from concordant to discordant states and vice versa. Similarly, relative crime activity levels for neighborhoods shifted from concordant to discordant states across three matched regimes. In some cases, the property and neighborhood states matched, while in other cases they diverged. These cross-level interactions indicate that criminal behavioral patterns and target selection change over time and relative criminal activity. The introduction of Copulas can improve the reliability of such models over time and when and where they should be customized to add more granular insights needed by law enforcement agencies.

The introduction of Copulas can improve the spatiotemporal reliability of the analysis of criminal activity over space and time.

Spatiotemporal considerations should be incorporated in setting interventions to manage criminal activity.

This study provides support for policies supporting renovation of abandoned properties.

To the best of authors’ knowledge, this research is the first application of Copulas to crime impact studies. As noted, Copulas can help reduce the risk of applying intervention or enforcement programs that are no longer reliable or lack the precision provided by insights into convergent/divergent patterns of criminal activity.