Discrete choiceIn economics, discrete choice models, or qualitative choice models, describe, explain, and predict choices between two or more discrete alternatives, such as entering or not entering the labor market, or choosing between modes of transport. Such choices contrast with standard consumption models in which the quantity of each good consumed is assumed to be a continuous variable. In the continuous case, calculus methods (e.g. first-order conditions) can be used to determine the optimum amount chosen, and demand can be modeled empirically using regression analysis.
Supply and demandIn microeconomics, supply and demand is an economic model of price determination in a market. It postulates that, holding all else equal, in a competitive market, the unit price for a particular good, or other traded item such as labor or liquid financial assets, will vary until it settles at a point where the quantity demanded (at the current price) will equal the quantity supplied (at the current price), resulting in an economic equilibrium for price and quantity transacted.
Logistic regressionIn statistics, the logistic model (or logit model) is a statistical model that models the probability of an event taking place by having the log-odds for the event be a linear combination of one or more independent variables. In regression analysis, logistic regression (or logit regression) is estimating the parameters of a logistic model (the coefficients in the linear combination).
Yield managementYield management is a variable pricing strategy, based on understanding, anticipating and influencing consumer behavior in order to maximize revenue or profits from a fixed, time-limited resource (such as airline seats, hotel room reservations or advertising inventory). As a specific, inventory-focused branch of revenue management, yield management involves strategic control of inventory to sell the right product to the right customer at the right time for the right price.
Specified complexitySpecified complexity is a creationist argument introduced by William Dembski, used by advocates to promote the pseudoscience of intelligent design. According to Dembski, the concept can formalize a property that singles out patterns that are both specified and complex, where in Dembski's terminology, a specified pattern is one that admits short descriptions, whereas a complex pattern is one that is unlikely to occur by chance. Proponents of intelligent design use specified complexity as one of their two main arguments, alongside irreducible complexity.
Land transportLand transport is the transport or movement of people, animals or goods from one location to another location on land. The two main forms of land transport can be considered to be rail transport and road transport. Several systems of land transport have been devised, from the most basic system of humans carrying things from place to sophisticated networks of ground-based transportation utilising different types of vehicles and infrastructure.
Demand-chain managementDemand-chain management (DCM) is the management of relationships between suppliers and customers to deliver the best value to the customer at the least cost to the demand chain as a whole. Demand-chain management is similar to supply-chain management but with special regard to the customers. Demand-chain-management software tools bridge the gap between the customer-relationship management and the supply-chain management. The organization's supply chain processes are managed to deliver best value according to the demand of the customers.
Demand for moneyIn monetary economics, the demand for money is the desired holding of financial assets in the form of money: that is, cash or bank deposits rather than investments. It can refer to the demand for money narrowly defined as M1 (directly spendable holdings), or for money in the broader sense of M2 or M3. Money in the sense of M1 is dominated as a store of value (even a temporary one) by interest-bearing assets. However, M1 is necessary to carry out transactions; in other words, it provides liquidity.
ScheduleA schedule or a timetable, as a basic time-management tool, consists of a list of times at which possible tasks, events, or actions are intended to take place, or of a sequence of events in the chronological order in which such things are intended to take place. The process of creating a schedule — deciding how to order these tasks and how to commit resources between the variety of possible tasks — is called scheduling, and a person responsible for making a particular schedule may be called a scheduler.
Aggregate demandIn macroeconomics, aggregate demand (AD) or domestic final demand (DFD) is the total demand for final goods and services in an economy at a given time. It is often called effective demand, though at other times this term is distinguished. This is the demand for the gross domestic product of a country. It specifies the amount of goods and services that will be purchased at all possible price levels. Consumer spending, investment, corporate and government expenditure, and net exports make up the aggregate demand.
Probit modelIn statistics, a probit model is a type of regression where the dependent variable can take only two values, for example married or not married. The word is a portmanteau, coming from probability + unit. The purpose of the model is to estimate the probability that an observation with particular characteristics will fall into a specific one of the categories; moreover, classifying observations based on their predicted probabilities is a type of binary classification model. A probit model is a popular specification for a binary response model.
Global optimizationGlobal optimization is a branch of applied mathematics and numerical analysis that attempts to find the global minima or maxima of a function or a set of functions on a given set. It is usually described as a minimization problem because the maximization of the real-valued function is equivalent to the minimization of the function . Given a possibly nonlinear and non-convex continuous function with the global minima and the set of all global minimizers in , the standard minimization problem can be given as that is, finding and a global minimizer in ; where is a (not necessarily convex) compact set defined by inequalities .