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  2. Returns to scale - Wikipedia

    en.wikipedia.org/wiki/Returns_to_scale

    [2] [3] [4] However, this relationship breaks down if the firm does not face perfectly competitive factor markets (i.e., in this context, the price one pays for a good does depend on the amount purchased). For example, if there are increasing returns to scale in some range of output levels, but the firm is so big in one or more input markets ...

  3. Accumulation function - Wikipedia

    en.wikipedia.org/wiki/Accumulation_function

    In actuarial mathematics, the accumulation function a(t) is a function of time t expressing the ratio of the value at time t (future value) and the initial investment (present value). [1] [2] It is used in interest theory. Thus a(0) = 1 and the value at time t is given by: = ().

  4. Law of supply - Wikipedia

    en.wikipedia.org/wiki/Law_of_supply

    A supply is a good or service that producers are willing to provide. The law of supply determines the quantity of supply at a given price. [5]The law of supply and demand states that, for a given product, if the quantity demanded exceeds the quantity supplied, then the price increases, which decreases the demand (law of demand) and increases the supply (law of supply)—and vice versa—until ...

  5. Demand curve - Wikipedia

    en.wikipedia.org/wiki/Demand_curve

    The price elasticity of demand is a measure of the sensitivity of the quantity variable, Q, to changes in the price variable, P. Its value answers the question of how much the quantity will change in percentage terms after a 1% change in the price. This is thus important in determining how revenue will change.

  6. Marginal revenue - Wikipedia

    en.wikipedia.org/wiki/Marginal_revenue

    The index varies from zero (when demand is infinitely elastic (a perfectly competitive market) to 1 (when demand has an elasticity of −1). The closer the index value is to 1, the greater is the difference between price and marginal cost. The Lerner index increases as demand becomes less elastic. [34]

  7. Knapsack problem - Wikipedia

    en.wikipedia.org/wiki/Knapsack_problem

    If one rounds off some of the least significant digits of the profit values then they will be bounded by a polynomial and 1/ε where ε is a bound on the correctness of the solution. This restriction then means that an algorithm can find a solution in polynomial time that is correct within a factor of (1-ε) of the optimal solution. [26]

  8. Order of magnitude - Wikipedia

    en.wikipedia.org/wiki/Order_of_magnitude

    Order of magnitude is a concept used to discuss the scale of numbers in relation to one another. Two numbers are "within an order of magnitude" of each other if their ratio is between 1/10 and 10. In other words, the two numbers are within about a factor of 10 of each other. [1] For example, 1 and 1.02 are within an order of magnitude.

  9. Conditional factor demands - Wikipedia

    en.wikipedia.org/wiki/Conditional_factor_demands

    A conditional factor demand function expresses the conditional factor demand as a function of the output level and the input costs. [1] The conditional portion of this phrase refers to the fact that this function is conditional on a given level of output, so output is one argument of the function.