Measuring dynamic efficiency with variable time lag effects

Omega ◽  
2021 ◽  
pp. 102578
Author(s):  
Dong-Joon Lim ◽  
Moon-Su Kim
Keyword(s):  
Time Lag ◽  
Dynamic Efficiency ◽  
Lag Effects ◽  
Variable Time

A Multi-Period Input DEA Model with Consistent Time Lag Effects

2019 ◽  
Vol 42 (3) ◽  
pp. 8-14
Author(s):  
Byungho Jeong ◽  
◽  
Yanshuang Zhang ◽  
Taehan Lee
Keyword(s):  
Time Lag ◽  
Dea Model ◽  
Lag Effects

scholarly journals Nonuniform Time-Lag Effects of Asymmetric Warming on Net Primary Productivity across Global Terrestrial Biomes

2018 ◽  
Vol 22 (8) ◽  
pp. 1-26 ◽  
Author(s):  
Youyue Wen ◽  
Xiaoping Liu ◽  
Guoming Du
Keyword(s):  
Partial Correlation ◽  
Net Primary Productivity ◽  
Net Primary Production ◽  
Time Lag ◽  
Correlation Coefficients ◽  
Terrestrial Ecosystem ◽  
Terrestrial Vegetation ◽  
Vegetation Growth ◽  
Lag Effects ◽  
Terrestrial Biomes

Abstract Climate warming exhibits asymmetric patterns over a diel time, with the trend of nighttime warming exceeding that of daytime warming, a phenomenon commonly known as asymmetric warming. Recently, increasing studies have documented the significant instantaneous impacts of asymmetric warming on terrestrial vegetation growth, but the indirect effects of asymmetric warming carrying over vegetation growth (referred to here as time-lag effects) remain unknown. Here, we quantitatively studied the time-lag effects (within 1 year) of asymmetric warming on global plant biomes by using terrestrial vegetation net primary production (NPP) derived by the Carnegie–Ames–Stanford Approach (CASA) model and accumulated daytime and nighttime temperature (ATmax and ATmin) from 1982 to 2013. Partial correlation and time-lag analyses were conducted at a monthly scale to obtain the partial correlation coefficients between NPP and ATmax/ATmin and the lagged durations of NPP responses to ATmax/ATmin. The results showed that (i) asymmetric warming has nonuniform time-lag effects on single plant biomes, and distinguishing correlations exist in different vegetation biomes’ associations to asymmetric warming; (ii) terrestrial biomes respond to ATmax (4.63 ± 3.92 months) with a shorter protracted duration than to ATmin (6.06 ± 4.27 months); (iii) forest biomes exhibit longer prolonged duration in responding to asymmetric warming than nonforest biomes do; (iv) mosses and lichens (Mosses), evergreen needleleaf forests (ENF), deciduous needleleaf forests (DNF), and mixed forests (MF) tend to positively correlate with ATmax, whereas the other biomes associate with ATmax with near-equal splits of positive and negative correlation; and (v) ATmin has a predominantly positive influence on terrestrial biomes, except for Mosses and DNF. This study provides a new perspective on terrestrial ecosystem responses to asymmetric warming and highlights the importance of including such nonuniform time-lag effects into currently used terrestrial ecosystem models during future investigations of vegetation–climate interactions.

Time-Lag Effects in Urban Environment Adaptation as a Warning System for Urban Growth Control: An Application to Flanders

1970 ◽  
Vol 2 (3) ◽  
pp. 303-322 ◽  
Author(s):  
M. van Naelten
Keyword(s):  
Factor Model ◽  
Time Lag ◽  
Growth Control ◽  
Warning System ◽  
Basic Point ◽  
Lag Effects ◽  
Environment Adaptation ◽  
Subsequent Measurement ◽  
Urban Growth Control ◽  
Urban Characteristics

In this paper we wish to discuss some aspects of a particular system approach in urban planning. An attempt has been made to explain the meaning of the first principal factor (Hotelling, 1933) in the verification of a set of supposed urban characteristics. The same factor model has been used in the subsequent measurement of the degree of urbanity in each municipal territory in Flanders. In mapping the results we have also attempted to verify some growth and communication theories for the Flanders case. Finally, the basic point of the paper is the detection of time-lag effects which create gaps between the slower development of more rigid environment elements, with which the planner is concerned, and the more quickly adapting elements—a time lag which could indicate urgent planning areas.

Time Lag Effects and Rainfall Redistribution in Subtropical Evergreen Broad-Leaved Forest in Eastern Coastal China

2013 ◽  
Vol 864-867 ◽  
pp. 2224-2231 ◽  
Author(s):  
Shun Lei Peng ◽  
Peng Li ◽  
Wen Hui You
Keyword(s):  
Time Lag ◽  
Lag Time ◽  
Research Station ◽  
Canopy Interception ◽  
Lag Effects ◽  
Broad Leaved Forest ◽  
Redistribution Function ◽  
Leaved Forest ◽  
Coastal China ◽  
Better Than

In order to reveal the ecological mechanism of rainfall redistribution and lag effects on precipitation of evergreen broad leaved forest in eastern coastal China, 25 m×25 m permanent plot studies were carried inC. fargesiistand andS. Superbastand in Forest Ecosystem Observation and Research station in Tiantong, Zhejiang Province. The results indicated that the total rainfall outside the forest was 5114.0 mm, the average rates of canopy interception, throuhfall, and stemflow were 24.5%, 6.1%, and 69.4% respectively inC. fargesiistand, which were 30.7%, 7.7%, and 61.6% respectively inS. Superbastand. Rainfall redistribution function ofC. fargesiistand was better than that ofC. fargesiistand. Throughfall and stemflow were increased with rainfall class increasing while canopy interception decreased as rainfall class increasing, especially during typhoon storm period. throughfall was observed after 67.6min when rainfall classes<5 mm happened, while throughfall was observed after 11.8 min when special heavy storm happened inC. fargesiistand, 6 times shorter than little rainfall event. The lag time of throughfall inS. Superbastand was longer than that in theC. fargesiistand. The time lag shortened gradually as rainfall class increased. Lag time of stemflow was about 2 times than that of throughfall.

scholarly journals Glucose concentrations in blood and tissue - a pilot study on variable time lag

2015 ◽  
Vol 159 (4) ◽  
pp. 527-534 ◽  
Author(s):  
Rudolf Chlup ◽  
Jan Krejci ◽  
Mark O'Connell ◽  
Blanka Sebestova ◽  
Robert Plicka ◽  
...  
Keyword(s):  
Pilot Study ◽  
Time Lag ◽  
Variable Time
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