Safety management theory and the military expeditionary organization: A critical theoretical reflection

Management of safety within organizations has become a key topic within safety science. Theorizing on this subject covers a diverse pallet of concepts such as “resilience” and “safety management systems”. Recent studies indicate that safety management theory has deficiencies. Our interpretation of these deficiencies is that much confusion originates from the issue that crucial meta-theoretical assumptions are mostly implicit or applied inconsistently. In particular, we argue that these meta-theoretical assumptions are of a systems theoretical nature. Therefore, we provide a framework that will be able to explicate and reflect on systems theoretical assumptions. With this framework, we analyze the ability of two frequently used safety management theories to tackle the problem of managing safety of Dutch military expeditionary organizations. This paper will show that inconsistent and implicit application of systems theoretical assumptions in these safety management theories results in problems to tackle such a practical problem adequately. We conclude with a reflection on the pros and cons of our framework. Also, we suggest particular meta-theoretical aspects that seem to be essential for applying safety management theory to organizations

What drives the Acceptability of Intelligent Speed Assistance (ISA)? Modeling acceptability of ISA

6370 individuals responded in Belgium (Flanders region) and 1158 persons in The Netherlands on a web-survey about ISA. A model has been estimated, by using SEM, to find out which predefined indicators would be relevant to define the acceptability of ISA. Background factors, contextual issues, and ISA-device related factors were used as indicators to predict the level of acceptability. The factors that were used in the model were based on the methods used in past ISA trials, acceptance and accep-tability theories and models. The effectiveness of ISA (1), equity (2), effectiveness of ITS (3) and personal and social aims (4), were the four variables that had the largest total effect on the acceptability of ISA. Effectiveness was found a relevant predictor for acceptance in many trials (Morsink et al, 2006). The model showed that the willingness of drivers to adopt ISA increases if they experience the system in practice: if people are convinced that ISA will assist to maintain the legal speed in different speed zones, the acceptance will be higher (Van der Pas et al., 2008). Hence, trials seem a good way to demonstrate the effectiveness of ISA. However, trials typically do not allow many people to try out ISA. Therefore, communi-cation strategies that focus on the ISA-effectiveness would be helpful to convince people about the benefits of using such a system. Often when new driver support technologies are intro-duced – especially when it could restrict certain freedom in driving – a majority of the population is reluctant when it comes to ‘buy or use’ the system. In some studies (see Morsink et al., 2006; Marchau et al., 2010) the willingness to pay was reported to be a good predictor for acceptability. However, in the present study the effect of willing-ness to pay was very low or even absent; hence it may be as-sumed that better indicators are put in the model than the willing-ness to pay. With respect to context indicators, ‘personal and social aims’ seemed to be the variable with the highest influence on accep-tability. Drivers, who rate social aims above personal aims with respect to speed and speeding, will accept ISA more. Personal and social aims had also a high influence on most of the device spe-cific indicators. Furthermore, drivers who speed for their personal benefit were found to rather speed more often. Drivers who speed in high-speed zones would also be less inclined to accept ISA. This is in line with previous findings (e.g. Jamson et al., 2006), frequent speeders would support ISA less; those drivers who would benefit most of ISA would be less likely to use it. This is an important finding when considering the strategies for implementing ISA. Some studies (e.g. Morsink et al., 2006) indicated that to increase the acceptability, implementation strategies and campaigns could focus on other benefits of ISA (like reducing speeding tickets, emissions etc.). According to our study these secondary effects have rather small effects to increase acceptability. Drivers who like to speed would even care less for these secondary benefits of ISA. The youngest group of drivers (<25 years old) would influence responsibility awareness negatively. These younger drivers are also less convinced that certain behaviour or circumstances could cause accidents. Many studies indicated that young drivers over-estimate their own driving skills, drive faster and are less aware of accident causes (Shinar et al., 2001). For the implementation of ISA – although there is no direct relationship between younger age and acceptability – a different strategy is needed to convince this group of drivers. Awareness campaigns and communication should be deployed during their education, however, road safety education and training stops during secondary school or higher education (OECD, 2006). Drivers between 25 and 45 years old would also be less inclined to accept ISA, mainly considered out of indirect effects in the esti-mated model. This group of drivers may be labelled as one of the most active groups of drivers. Another aspect is that both of the "significant found age groups were influenced by social norms. This may be very important in implementation strate-gies. For instance, role models could be used in ISA driving. This strategy was also used in the Belgian trial to gain more publicity and attention. The positive image and the improved information communication of ISA as a possible measure in road-safety have led to several voted resolutions in the Belgian federal parliament and senate (Vlassenroot et al. 2007)

Coronavirus (COVID-19) in the United Kingdom: A personality-based perspective on concerns and intention to self-isolate

Objectives Public behaviour change is necessary to contain the spread of coronavirus (COVID‐19). Based on the reinforcement sensitivity theory (RST) framework, this study presents an examination of individual differences in some relevant psychological factors. Design Cross‐sectional psychometric. Methods UK respondents (N = 202) completed a personality questionnaire (RST‐PQ), measures of illness attitudes, concerns about the impact of coronavirus on health services and socio‐economic infrastructures, personal safety, and likelihood of voluntary self‐isolation. Results Respondents most concerned were older, had negative illness attitudes, and scored higher on reward reactivity (RR), indicating the motivation to take positive approach action despite prevailing worry/anxiety. Personal safety concerns were highest in those with negative illness attitudes and higher fight–flight–freeze system (FFFS, reflecting fear/avoidance) scores. Results suggest people are experiencing psychological conflict: between the urge to stay safe (FFFF‐related) and the desire to maintain a normal, pleasurable (RR‐related) life. Ways of ameliorating conflict may include maladaptive behaviours (panic buying), reflecting reward‐related displacement activity. Intended self‐isolation related to FFFS, but also low behavioural inhibition system (related to anxiety) scores. Older people reported themselves less likely to self‐isolate. Conclusions Interventions need to consider individual differences in psychological factors in behaviour change, and we discuss relevant literature to inform policy makers and communicators

Collaborative Verification-Driven Engineering of Hybrid Systems

Hybrid systems with both discrete and continuous dynamics are an important model for real-world cyber-physical systems. The key challenge is to ensure their correct functioning w.r.t. safety requirements. Promising techniques to ensure safety seem to be model-driven engineering to develop hybrid systems in a well-defined and traceable manner, and formal verification to prove their correctness. Their combination forms the vision of verification-driven engineering. Often, hybrid systems are rather complex in that they require expertise from many domains (e.g., robotics, control systems, computer science, software engineering, and mechanical engineering). Moreover, despite the remarkable progress in automating formal verification of hybrid systems, the construction of proofs of complex systems often requires nontrivial human guidance, since hybrid systems verification tools solve undecidable problems. It is, thus, not uncommon for development and verification teams to consist of many players with diverse expertise. This paper introduces a verification-driven engineering toolset that extends our previous work on hybrid and arithmetic verification with tools for (i) graphical (UML) and textual modeling of hybrid systems, (ii) exchanging and comparing models and proofs, and (iii) managing verification tasks. This toolset makes it easier to tackle large-scale verification tasks