Levels of influence

Key actors within the pharmaceutical sector—government and private and public interest groups— are usually the main influences on dmg regulation. The political, social and economic stmctures of the country generally determine the level of influence of these players. 

A leverage matrix is used to rank the level of influence stakeholders have on each other. This comes in handy when, for instance, you need to move a stakeholder s support level from opposed to supportive, and you realize that another stakeholder can help move this person in the right direction. 

Modeling and anal3rzing on the level of specific actions (UAs) enables the investigation of the potential impact of each action on the plant response. Additionally, this reveals the level of influence from different contexts on the operator actions and the recovery factors which are reflected in the model and the HEP. This can be observed in Fig. 2, the header 1C (OPEN SRV), contemplates 2 unsafe actions, UA-lCl is the failure to open a SRV when the procedures are followed correctly and UA-1C2 is the failure to open the SRV when only one procedure is followed. 

Where X R" and C R" ea e vectors composed, respectively, of the level of inoperability and external failures associated with each one of theudififerent infrastructures considered in the scenario. A e R is the Leontief matrix, in which entry a,y represents the level of influence that the inoperability of the i-th infrastructure has on the y -th one (interoperability). Notice that in the model, atj = 1 means that the y-th infrastructure is completely dependent on the i-th one, because a given service reduction in the latter will directly induce an equal level of service degradation into they -th one. Applicative examples and results of this approach have been already proposed (Setola 2007 Haimes Jiang 2001). 

D Ohveira (2006), while reviewing the hteratuie on organizational safety, identified different levels of influence (see Figure 11.1). 

These inductive and resonance effects have different levels of influence depending on their position relative to the incoming electrophile. 

The next levels really distinguish the level of influence that the leader may be able exert on the constituents. In the production level constituents follow because of positive accomplishments that the leader has been able to achieve for the organization. The personal level reveals that the constituent follows because of positive things that the leader has done for the follower on a personal basis. Maxwell says that the highest level may be unattainable. At this level, constituents follow based solely on name and reputation. His example, a clearly unattainable one, is Jesus Christ (Maxwell, 1993). 

Equally, applying two or even just one feature to the consequence has intermediate levels of influence on the behaviour. 

What is your level of influence within the organization How are you perceived in the organization ... 

ABSTRACT There are many properties correlated with maintenance costs. Due to minimize the maintenance costs we should recognize them and assess the level of influence and choose them of which the mitigation is the most cost effective. One of the most important property is lifetime which is assessed using statistical methods during accelerated tests. And may be improved based on real data. The parametric and non-parametric statistics could be applied to assessment the lifetime of aviation items. In the paper their advantages and disadvantages were recognized. 

The scarcity of certain PSFs. In some cases, certain PSFs are met so rarely that no data exist for them with regard to their level of influence. 

Errors can occur at each of these levels of influence which can predispose the critical active failure (operator error) which creates an accident. Identifying the level of influence where the predisposing error has occurred is important for two reasons ... 

Each of the levels of influence identified in Figure 2.1 is considered in detail in Chapters 3-8. Each chapter is divided into two sections the first provides a series of examples taken from the mining industry to indicate the type of problems and the potential (sometimes actual) errors that can be predisposed by failures at that level. The second section examines a number of potential routes to improvement to minimise error at that level. 

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