2017
DOI: 10.1111/itor.12416
|View full text |Cite
|
Sign up to set email alerts
|

Assessing the efficiency of the accounting industry using multiactivity network DEA: evidence from Taiwan

Abstract: Accounting firms are highly specialized and subject to government recognition through professional licenses. Accordingly, in assessing an accounting firm's performance, the performance measurement system should be generic enough to provide an integrated view of important factors from different perspectives. However, traditional performance measurements are based on several predefined factors that provide a partial view of the system or are limited to a single activity, thereby ignoring their interactions. This… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4
1

Citation Types

0
9
0

Year Published

2018
2018
2022
2022

Publication Types

Select...
9

Relationship

0
9

Authors

Journals

citations
Cited by 12 publications
(9 citation statements)
references
References 32 publications
0
9
0
Order By: Relevance
“…Combined with the traditional and spatial Markov probability transfer matrix, this study quantitatively depicts the spatiotemporal dynamic evolution characteristics of industrial energy eco-efficiency and its constraints on the geographical pattern in the Yangtze River Economic Belt, so as to provide scientific support for improving the eco-efficiency of industrial energy use and sustainable development of the Yangtze River Economic Belt. [13,21]. Among them, the CCR model based on constant return to scale means that every decision-making unit is in the optimal production scale state, but this is not in line with the actual situation.…”
Section: Studied Areamentioning
confidence: 99%
See 1 more Smart Citation
“…Combined with the traditional and spatial Markov probability transfer matrix, this study quantitatively depicts the spatiotemporal dynamic evolution characteristics of industrial energy eco-efficiency and its constraints on the geographical pattern in the Yangtze River Economic Belt, so as to provide scientific support for improving the eco-efficiency of industrial energy use and sustainable development of the Yangtze River Economic Belt. [13,21]. Among them, the CCR model based on constant return to scale means that every decision-making unit is in the optimal production scale state, but this is not in line with the actual situation.…”
Section: Studied Areamentioning
confidence: 99%
“…Compared with the single ratio method, the indicator system method can effectively distinguish the impact of different environments on eco-efficiency, yet it is difficult to exclude the subjective factors. The model method is the fastest growing and most reliable in the field of eco-efficiency evaluation [21][22][23][24]. The commonly used models include data envelopment analysis (DEA), super efficiency DEA, and three-stage DEA and slacks-based measure (SBM), which are all based on DEA.…”
Section: Introductionmentioning
confidence: 99%
“…Dynamic network analyses based on DEA can be found in Tran and Villano (), Moreno and Lozano (), Hsiao et al. (), and Chen et al. ().…”
Section: Introductionmentioning
confidence: 99%
“…The main advantage of DEA is the provision of efficiency scores that can be used as specific goals on which managers can focus to improve their performance within a multiple input and output context as well as the identification of best performers that are not always visible through commonly used management methodology (Sherman and Zhu, ) and can be used as role models in the process of efficiency improvement. DEA has already been applied in numerous domains such as accounting (Hsiao et al., ), agriculture (Chemak et al., ; Da Silva e Souza and Gonçalves Gomes, ; Watto and Mugera, ), airlines (Gomes Junior et al., ), education (Kounetas et al., ; Tran and Villano, ), hardware computers (Sahoo et al., ), hospitals (Marques and Carvalho, ; Ghiyasi, ), power plants (Yadav et al., ; Calabria et al., ), soccer players (Santin, ), and banking and finance (Basso and Funari, ; Chiu et al., ; Shyu et al., ; Chen et al., ; Moreno and Lozano, ), among others.…”
Section: Introductionmentioning
confidence: 99%