The evaluation of modified productivity index method on the transitional volcanic-tropical landscape

Firstly, this paper uses DEA's CCR model to evaluate the relative efficiency of city infrastructure investment of 10 cities in Shaanxi province during 2008-2013. Then according to the panel data of city infrastructure input and output in 2008-2013, it has carried on the longitudinal comparison to observe the dynamic effect of infrastructure investment efficiency in the time series by using the Malmquist-DEA index method. Results show that the overall city infrastructure investment efficiency of Shaanxi province during the whole is on the rise; while each city development is not balanced, Xi'an development situation is relatively better; although, the Malmquist productivity index of the whole province infrastructure investment is restricted by the technical level, it is still on the rise.

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Assessment of the spatial distribution of global soil loss tolerance by using the productivity index method

10.5194/egusphere-egu2020-4538 ◽

2020 ◽

Author(s):

Lizhi Jia ◽

Wenwu Zhao

Keyword(s):

Land Use ◽

Soil Loss ◽

Global Scale ◽

Productivity Index ◽

Soil Productivity ◽

Index Method ◽

Land Use Types ◽

Soil Loss Tolerance ◽

Loss Tolerance ◽

T Values

The soil loss tolerance (T value) is the ultimate criterion for determining whether a soil has potential erosion risks. While the existing T value criteria are mainly on national scale, and lack of consideration of the differences in soil erosion, soil properties and soil productivity between different types of land use. We calculated the global T value by using the productivity index method. The global T values ranged from 0.84 to 4.99 Mg ha-1 yr-1, with an average of 1.49 Mg ha-1 yr-1. The distribution of T values in global scale demonstrated significant spatial differences, and the range of T values in most regions of the land (98.23%) was between 1.0 and 2.0 Mg ha-1 yr-1. The mean T values varied from c ontinent to continent, with Africa and Oceania having higher mean T values than other continents. The T values between different land use types varied widely, and the T values of five land use types were as follows: cropland (1.67 Mg ha-1 yr-1) > shrubland (1.61 Mg ha-1 yr-1) > grassland (1.59 Mg ha-1 yr-1) > forestland (1.38 Mg ha-1 yr-1) > wetland (1.28 Mg ha-1 yr-1).

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Efficiency Benchmarking of North American Airports: Comparative Results of Productivity Index, Data Envelopment Analysis and Stochastic Frontier Analysis

Journal of the Transportation Research Forum ◽

10.5399/osu/jtrf.52.1.4139 ◽

2013 ◽

Author(s):

Zhuo (Frank) Lin ◽

YapYin Choo ◽

Tae Hoon Oum

Keyword(s):

Data Envelopment Analysis ◽

Stochastic Frontier Analysis ◽

Stochastic Frontier ◽

Alternative Methods ◽

Productivity Index ◽

Data Envelopment ◽

Index Method ◽

Frontier Analysis ◽

Passenger Volume ◽

Comparative Results

Using three common methodologies for measuring airport efficiency, namely the productivity index method, Data Envelopment Analysis (DEA) method, and stochastic frontier analysis (SFA) method, this study examines the efficiency performances of 62 Canadian and U.S. airports. Unlike most previous studies, this study includes aeronautical and non-aeronautical outputs of airports as they are inexplicably tied to each other in airport production. The empirical results reveal that the efficiency scores and rankings measured by these alternative methods are quite similar to each other in the top 15 and bottom 15 ranked airports, whereas considerable differences exist among the airports in the middle range. We also found that the percentage of non-aeronautical revenue, passenger volume, average aircraft size, percentages of international and connecting traffic significantly affect our airport efficiency estimates in all of the three alternative approaches used.

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Malmquist Indexes of Productivity Change in Tunisian Manufacturing Industries

Sustainability ◽

10.3390/su12041367 ◽

2020 ◽

Vol 12 (4) ◽

pp. 1367

Author(s):

Houyem Zrelli ◽

Abdullah H. Alsharif ◽

Iskander Tlili

Keyword(s):

Productivity Growth ◽

Manufacturing Industries ◽

Malmquist Productivity Index ◽

Productivity Index ◽

Productivity Change ◽

Factor Productivity ◽

Efficiency Change ◽

Index Method ◽

Average Growth ◽

Malmquist Indexes

This research aims to investigate the extent and nature of productivity growth in manufacturing industries using nonparametric frontier techniques. In order to decompose the total factor productivity (TFP) into technical efficiency change and technological change we use the output-oriented Malmquist productivity index method for 34 Tunisian manufacturing industries over the period 2002–2016. The results indicated that TFP has witnessed an average growth of two percent over the period 2002–2016. The productivity growth identified was attributed to the improvements in the technology (or frontier-shift) rather than improvements or changes in the efficiency.

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Detecting Random Responses in a Personality Scale Using IRT-Based Person-Fit Indices

European Journal of Psychological Assessment ◽

10.1027/1015-5759/a000369 ◽

2019 ◽

Vol 35 (1) ◽

pp. 126-136 ◽

Cited By ~ 2

Author(s):

Tour Liu ◽

Tian Lan ◽

Tao Xin

Keyword(s):

Experimental System ◽

Real Data ◽

Fit Indices ◽

Random Response ◽

Person Fit ◽

Index Method ◽

Single Person ◽

Person Fit Index ◽

Random Responses ◽

Response Behaviors

Abstract. Random response is a very common aberrant response behavior in personality tests and may negatively affect the reliability, validity, or other analytical aspects of psychological assessment. Typically, researchers use a single person-fit index to identify random responses. This study recommends a three-step person-fit analysis procedure. Unlike the typical single person-fit methods, the three-step procedure identifies both global misfit and local misfit individuals using different person-fit indices. This procedure was able to identify more local misfit individuals than single-index method, and a graphical method was used to visualize those particular items in which random response behaviors appear. This method may be useful to researchers in that it will provide them with more information about response behaviors, allowing better evaluation of scale administration and development of more plausible explanations. Real data were used in this study instead of simulation data. In order to create real random responses, an experimental test administration was designed. Four different random response samples were produced using this experimental system.

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