Quick Response has become a core strategy to increase competitiveness and has been widely implemented in logistics. Previously, variables affecting logistics quick response have been widely studied from the perspectives of assessment on logistics performance or supply chain performance, primarily in the USA and EU contexts. This paper analyzes the key variables to assess logistics quick response capability in China. It analyzes empirical data collected from 50 experts and professionals in logistics field to identify a hierarchy of the variables. The results indicate that, in the Chinese context, internal variables have a higher impact on logistics quick response than external ones. Moreover, variable customer service was viewed as the most important one, followed by variables of time management and logistics cost. Therefore, the study results in a first layer assessment variables which is composed of the 7 internal variables.
Quick Response has become a core strategy to increase competitiveness and has been widely implemented in logistics. Previously, variables affecting logistics quick response have been widely studied from the perspectives of assessment on logistics performance or supply chain performance, primarily in the USA and EU contexts. This paper analyzes the key variables to assess logistics quick response capability in China. It analyzes empirical data collected from 50 experts and professionals in logistics field to identify a hierarchy of the variables. The results indicate that, in the Chinese context, internal variables have a higher impact on logistics quick response than external ones. Moreover, variable customer service was viewed as the most important one, followed by variables of time management and logistics cost. Therefore, the study results in a first layer assessment variables which is composed of the 7 internal variables.
Quick Response has become a core strategy to increase competitiveness and has been widely implemented in logistics. Previously, variables affecting logistics quick response have been widely studied from the perspectives of assessment on logistics performance or supply chain performance, primarily in the USA and EU contexts. This paper analyzes the key variables to assess logistics quick response capability in China. It analyzes empirical data collected from 50 experts and professionals in logistics field to identify a hierarchy of the variables. The results indicate that, in the Chinese context, internal variables have a higher impact on logistics quick response than external ones. Moreover, variable customer service was viewed as the most important one, followed by variables of time management and logistics cost. Therefore, the study results in a first layer assessment variables which is composed of the 7 internal variables.
Variables that store data for direct or indirect processing include primitive data types, such as integers, floats, and strings, which hold specific values directly. Additionally, complex data structures like arrays, lists, or dictionaries can store collections of values, enabling indirect processing through iteration or manipulation of the stored data. These variables allow programs to manage, analyze, and transform data efficiently during execution.
Yes, a theory can have multiple variables. In fact, theories often aim to explain complex phenomena by considering how different variables interact to produce certain outcomes. By including multiple variables, a theory can offer a more comprehensive understanding of the relationships between different factors.
There are many variables that can be difficult to control in various situations. Some common examples include human behavior, external factors like weather, and complex systems where multiple variables interact in unpredictable ways. It is important to identify and account for these variables when making decisions or conducting experiments to minimize their impact on outcomes.
A direct effect occurs when a change in one variable directly leads to a change in another variable, with no intermediary factors involved. In contrast, an indirect effect involves one or more mediating variables that influence the relationship between the initial variable and the outcome. Essentially, direct effects are straightforward and immediate, while indirect effects are more complex and involve additional pathways or influences.
Maurice Heins has written: 'Complex function theory' -- subject(s): Functions of complex variables 'Selected topics in the classical theoryof functions of a complex variable' -- subject(s): Functions of complex variables
complex numbers
One of the main economic variables that affects business cycles is consumer spending, as it directly influences demand for goods and services. Other significant variables include investment levels, government spending, and net exports. These factors interact in complex ways, contributing to the fluctuations in economic activity that characterize business cycles. Changes in these variables can lead to expansions or contractions in the economy.
Pei-Chu Hu has written: 'Differentiable and complex dynamics of several variables' -- subject(s): Differentiable dynamical systems, Functions of several complex variables
When behavior is described as complex, it usually means that it involves multiple factors or influences that interact in intricate ways to produce the observed actions or responses. Understanding and predicting complex behavior may require considering various internal and external variables, such as cognitive processes, emotions, social interactions, and environmental stimuli.
Murali Rao has written: 'Complex analysis' -- subject(s): Functions of complex variables