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Six factors influencing ethical intensity and actions in each stage

Ethical intensity is the degree of moral importance given to an issue. It is influenced by six factors. 
 The first factor is magnitude of consequences-the harm or benefits accruing to individuals affected by a decision or behavior. An action that causes 1,000 people to suffer a particular injury has greater consequences than an action that causes 20 people to suffer the same injury. 
 The second factor is probability of effect - the likelihood that if a decision is implemented it will lead to the harm or benefit predicted. The production of an automobile that would be dangerous to occupants during normal driving has greater probability of harm than the production of a NASCAR race car that endangers the driver when curves are taken at high speed. 
The third factor is social consensus is the amount of public agreement that a proposed decision is bad or good. Actively discriminating against minority job candidates is worse than not actively seeking out minority job candidates. 
The fourth factor is temporal immediacy - the length of time that elapses between making a decision and when the consequences of that decision are known. A shorter length of time implies greater immediacy. 
An example of this is if Pfizer releases a drug that causes one percent of the people who take it to have acute nervous reactions within one week. This has greater temporal immediacy than releasing a drug that will cause 1 percent of those who take it to develop nervous disorders after 25 years of use. 
The fifth factor is proximity is the sense of closeness (social, cultural, psychological, or physical) that the decision maker has for victims or beneficiaries of the decision. Recently, Citigroup cut 53,000 jobs. This reduced its labor force to 300,000 employees with more layoffs anticipated. This action had a greater impact on the remaining employees than the personal impact the news reporters feel when announcing this layoff. 
The sixth factor is concentration of effect -the inverse function of the number of people affected by a decision. A change in an insurance policy denying coverage to 40 people with claims of $50,000 each has a more concentrated effect than a change denying coverage to 4,000 people with claims of $500 each.