Does “replacing business tax with value-added tax” promote the energy efficiency of the logistics industry in China?

Liu, Zuankuo; Jiang, Yufan; Dennis, Bolayog

doi:10.1007/s11356-019-06367-5

Cited by 22 publications

(9 citation statements)

References 42 publications

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“…In contrast, in 2017, the logistics industry GTFP showed a slight rebound, reaching 1.0473, which may be the result of China's environmental control measures. Furthermore, the GTECH index and the GML index have a higher degree of curve fitting, which is consistent with the research conclusion conducted by Liu et al [1]. That means, the logistics industry still needs to increase investments of new energy, rely on talent advantages and strengthen technological innovation.…”

Section: Measurement Of Gtfp In the Logistics Industrysupporting

confidence: 88%

“…The capital stock can be calculated as follows: (16) ...where I i,t denotes the investment in the fixed assets of logistics industry in the specific area i in the specific year t. Additionally, P i represents the deflator for fixed asset investment while δ is the depreciation rate. Regarding the selection of the depreciation rate, Liu et al [1] selected 10.96%, and Tang et al [34] calculated it once a year. Considering the characteristics of the logistics industry, this paper directly adopts Wu's research results, that is, the depreciation rate is 4% [35].…”

Section: Input Variablesmentioning

confidence: 99%

“…In recent years, the logistics industry, which integrates transportation, warehousing, freight forwarding and information industry, is regarded as the basic and strategic industry to support the social and economic development and is called "the third profit source" [1]. Although the logistics industry belongs to the service industry, it has become one of the major industries in energy consumption.…”

Section: Introductionmentioning

confidence: 99%

“…However, there is still a lack of research on the driving factors of GTFP in the logistics industry. Liu et al [1] examined the influence of tax reform on energy efficiency in the logistics industry. Besides, Yang et al [22] adopted DEA-Malmquist to analyze the carbon emission efficiency of logistics in 16 cities in Yunnan, and used Tobit to capture the driving factors of the carbon emissions performance in logistics.…”

Section: Introductionmentioning

confidence: 99%

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Spatial-Temporal Distribution Characteristics and Driving Mechanism of Green Total Factor Productivity in China’s Logistics Industry

Li¹,

Jian²

2020

Pol. J. Environ. Stud.

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The rapid development of China's logistics industry is accompanied by the deterioration of the ecological environment and excessive energy consumption. Therefore, how to effectively measure and improve the green total factor productivity (GTFP) of the logistics industry is an important guarantee for achieving the coordination of the logistics industry development and the ecological environment protection in the high-quality development stage. This study evaluated the logistics industry's GTFP of 30 provinces in China from 2004 to 2017 using the Epsilon-based measure model (EBM) and global Malmquist-Luenberger index (GML). Then, this paper applied the geographically and temporally weighted regression (GTWR) to analyze the spatiotemporal non-stationarity of influences of driving factors on GTFP. There are three main conclusions drawn in this paper. Firstly, the GTFP of the logistics industry has significant spatial and temporal differences. From a temporal perspective, the GTFP has undergone a process of alternating changes in ascent and descent. From a spatial perspective, the GTFP has an obvious "east-central-west" gradient decreasing trend. Secondly, compared with the ordinary least squares (OLS) and the geographically weighted regression (GWR), GTWR performs best in terms of goodness of fit. Thirdly, the regression results of GTWR indicate that the influences of factors have different directions and intensities on GTFP in the logistics industry at different times and regions, showing obvious characteristics of spatiotemporal non-stationarity. Finally, some practical recommendations are put forward in this paper.

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Section: Measurement Of Gtfp In the Logistics Industrysupporting

confidence: 88%

Section: Input Variablesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Spatial-Temporal Distribution Characteristics and Driving Mechanism of Green Total Factor Productivity in China’s Logistics Industry

Li¹,

Jian²

2020

Pol. J. Environ. Stud.

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“…Overall, these results form the basis for future IoT applications and QoE requirements and for the development of basic electronic devices (especially wearable technology) [5,6]. Liu et al wanted better performance and the TFEE Chinese companies have shown rapid growth [7]. ey used the regression discontinuity (RD) method to study the relationship between "corporate tax refund and additional tax" (RBTVT) and total electronic power (TFEE) in retail companies.…”

Section: Related Contentmentioning

confidence: 99%

Upgrade Path and Strategy of Logistics Industry Cluster Based on the Internet of Things

2021

Mobile Information Systems

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As the economy grows rapidly and IoT technology advances rapidly, the logistics industry as a service industry is growing rapidly around the world. The logistics industry, meanwhile, is the one that can best play the role of IoT. The rapid development of the logistics industry has brought great competition challenges to the logistics industry. To solve the competitive problems of the logistics industry cluster, this article introduces the research on the upgrade path and strategy of the logistics industry cluster based on the Internet of Things and uses the analytic hierarchy process, investigation method, and expert evaluation method to build the IoT technology information model and logistics cost. According to the established optimization model, the following are proposed: analyzing the problems existing in the logistics industry cluster, giving an upgrade path from the four aspects of manufacturing, technology, structure, and service, and giving specific strategic suggestions from the aspects of talents and enterprises. The accuracy rate of current analysis is as high as 90%, and the implementation rate of upgrade paths and strategy recommendations is as high as 95%.

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Structural equation modeling for three aspects of green business practices: a case study of Bangladeshi RMG’s industry

Sarkar

Peau

2020

Environ Sci Pollut Res

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Does “replacing business tax with value-added tax” promote the energy efficiency of the logistics industry in China?

Cited by 22 publications

References 42 publications

Spatial-Temporal Distribution Characteristics and Driving Mechanism of Green Total Factor Productivity in China’s Logistics Industry

Spatial-Temporal Distribution Characteristics and Driving Mechanism of Green Total Factor Productivity in China’s Logistics Industry

Upgrade Path and Strategy of Logistics Industry Cluster Based on the Internet of Things

Structural equation modeling for three aspects of green business practices: a case study of Bangladeshi RMG’s industry

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