Quantitative Research 

TermiKnowledge - Supply Chain, Procurement and Inventory Terminologies
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Quantitative Research, also called Quantitative Analysis, is basically an economic research approach which concentrates on quantifying the measurement and analysis of economic data. This kind of research has found immense application in many areas of business including supply chain management, warehouse pricing, and manufacturing. It is basically formed by a series of deductive methods in which emphasis is placed upon the testing of statistical theories, formulated by various positivist and econometricians. These theories postulate that there are identifiable patterns in the price of a good or service in relation to its characteristics such as frequency of use, price elasticity, unit costs, and profit margins. The theories also postulate that these characteristics can be variable or constant, and that price levelings can be influenced by external factors.

One great challenge facing researchers in quantitative research is identifying the causes of the observed price changes and patterns. This is very difficult especially in case of changing trends in a country like the U.S. where there are many regional variation, national variation, and micro level variation. The cause-effect relationship in Quantitative market research can be quite perplexing as well. Many theories have been advanced to explain the cause-effect relationship in quantifying the variables of interest. The confusion comes mainly from two different perspectives - one being from the micro level and the other being from the macro level.

Micro level factors such as trade flows and monetary policy can affect the price level directly by influencing demand and supply curves. On the other hand, macro level factors such as inflation, deflation, and interest rates also affect the price level indirectly by influencing aggregate demand and supply curves. Thus, it can be said that understanding Quantitative Research is like trying to understand the key findings and patterns in a statistical study. Since these results are often sensitive and difficult to interpret, it is important for researchers to describe their key findings in terms of traditional economic theory before they make broad and deep explanations of the results that they observe.

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