Browsing by Author "Chiu, Ching-Ren"

Now showing 1 - 4 of 4

An alternative metafrontier framework for measuring the heterogeneity of technology
(2018-08-01)
Wang, Qunwei
;
Hang, Ye
;
Hu, Jin-Li
;
Chiu, Ching-Ren
;
經營管理研究所
The metafrontier framework proposed by O'Donnell et al. enables the evaluation of relative efficiencies for decision-making units (DMUs) operating under heterogeneous technologies. The metatechnology ratio (MTR) constructed under the metafrontier framework helps estimate the gap between group frontiers and the metafrontier, with its score between 0 and 1. However, an unreasonable MTR value (ie, greater than 1) may appear when the traditional metafrontier framework is applied in the nonradial data envelopment analysis (DEA) models. This article proposes an alternative metafrontier framework for addressing this issue. The newly constructed technology gap measurement (TGM) can avoid unreasonable technology gap ratio values in nonradial DEA models and substitute for MTR in radial DEA models. To demonstrate how this alternative metafrontier approach works, this article applies it to the efficiency evaluation of regional transportation sectors in China.
Disaggregate productivity growth sources of regional industries in China
(1970-01-01)
Li, Lan-Bing
;
Zhang, Cong-Cong
;
Hu, Jin-Li
;
Chiu, Ching-Ren
;
經營管理研究所
This paper extends a global slack-based productivity indicator and constructs a unified framework that consists of global and factor levels of total factor productivity (TFP) to evaluate the performance of regional industries, thus enabling global productivity improvement based on factor-level sources. Evaluating regional industrial performance in China during 1995-2014, the findings reveal that rapid growth of industry in China is not only driven by a huge amount of input, but also by TFP improvement, with industrial productivity driven mainly by technology progress and presenting a gradually increasing trend. Regional productivity performances are imbalanced, in which the east ranks first due to its dual advantages of input and output factors. For source identification, input and output jointly contribute to industrial productivity improvement, but output has a much higher contribution ratio to industrial productivity improvement than input, because it is mainly rooted in desirable output. Finally, on the input side, labor is the primary factor driving input productivity improvement followed by energy, while capital productivity shows very slight growth.
Minimizing the Carbon Footprint for the Time-Dependent Heterogeneous-Fleet Vehicle Routing Problem with Alternative Paths
(2014-07-01)
Liu, Wan-Yu
;
Lin, Chun-Cheng
;
Chiu, Ching-Ren
;
Tsao, You-Song
;
Wang, Qunwei
Torespondto the reduction of greenhouse gas emissions and global warming, this paper investigates the minimal-carbon-footprint time-dependent heterogeneous-fleet vehicle routing problem with alternative paths (MTHVRPP). This finds a route with the smallestcarbon footprint, instead of the shortestroute distance, which is the conventional approach, to serve a number of customers with a heterogeneous fleet of vehicles in cases wherethere may not be only one path between each pair of customers, and the vehicle speed differs at different times of the day. Inheriting from the NP-hardness of the vehicle routing problem, the MTHVRPP is also NP-hard. This paper further proposes a genetic algorithm (GA) to solve this problem. The solution representedbyour GA determines the customer serving ordering of each vehicle type. Then, the capacity check is used to classify multiple routes of each vehicle type, and the path selection determines the detailed paths of each route. Additionally, this paper improves the energy consumption model used for calculating the carbon footprint amount more precisely. Compared with the results without alternative paths, our experimental results show that the alternative path in this experimenthas a significant impact on the experimental results in terms of carbon footprint.
Minimizing the Carbon Footprint for the Time-Dependent Heterogeneous-Fleet Vehicle Routing Problem with Alternative Paths
(2014-07-01)
Liu, Wan-Yu
;
Lin, Chun-Cheng
;
Chiu, Ching-Ren
;
Tsao, You-Song
;
Wang, Qunwei
Torespondto the reduction of greenhouse gas emissions and global warming, this paper investigates the minimal-carbon-footprint time-dependent heterogeneous-fleet vehicle routing problem with alternative paths (MTHVRPP). This finds a route with the smallestcarbon footprint, instead of the shortestroute distance, which is the conventional approach, to serve a number of customers with a heterogeneous fleet of vehicles in cases wherethere may not be only one path between each pair of customers, and the vehicle speed differs at different times of the day. Inheriting from the NP-hardness of the vehicle routing problem, the MTHVRPP is also NP-hard. This paper further proposes a genetic algorithm (GA) to solve this problem. The solution representedbyour GA determines the customer serving ordering of each vehicle type. Then, the capacity check is used to classify multiple routes of each vehicle type, and the path selection determines the detailed paths of each route. Additionally, this paper improves the energy consumption model used for calculating the carbon footprint amount more precisely. Compared with the results without alternative paths, our experimental results show that the alternative path in this experimenthas a significant impact on the experimental results in terms of carbon footprint.